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Published by: vikaspatanker

Authors: Ifeoma Lynda Okpala

Abstract: Sustainable procurement practices have emerged as critical mechanisms for achieving environmental, social, and economic objectives across global markets. This comparative policy review examines the barriers to sustainable procurement implementation in Sub-Saharan Africa and the United States, analyzing differences in regulatory frameworks, institutional capacity, and market dynamics. Through a systematic analysis of contemporary literature and policy documents, this study identifies key obstacles including corruption, limited technological infrastructure, inadequate policy frameworks, and varying stakeholder engagement approaches. The research reveals that while both regions face common challenges such as cost considerations and knowledge gaps, Sub-Saharan Africa confronts additional systemic barriers including governance deficits and resource constraints. The findings suggest that tailored policy interventions, enhanced international cooperation, and technology-driven solutions are essential for advancing sustainable procurement practices across both contexts.

DOI: http://doi.org/10.5281/zenodo.17213813

Published by: vikaspatanker

An Unmanned Level Crossing Controller with Real Time Monitoring Based on Microcontroller Elements
Authors:-Angel Dixon, Muhammed Ashiq k, Sreenika V Nair, Assistant Professor MS. Sayana M

Abstract-The Automatic Railway Gate Control (ARGC)system is designed to overcome the limitations and inefficiencies associated with traditional manually operated railway crossing gates. This innovative system employs sensors and microcontroller technologies to manage and control the operation of railway gates automatically, thereby enhancing the safety and efficiency of rail and road traffic.

Probiotics in Prevention and Treatment of Allergy and Respiratory Infections: A Review
Authors:-Anchal

Abstract-Probiotics defined as live microorganisms that confer the health benefits, that when administrated in adequate amounts, they have shown potential in the prevention and treatment of allergic and respiratory infections. This paper summarizes current research on the topic. Probiotics may modulate immune responses, enhance gut barrier function, and positively alter microbiota composition, thereby reducing the incidence and severity of allergic conditions such as eczema, atopic dermatitis and allergic rhinitis. In respiratory infections, probiotics can enhance mucosal immunity, inhibit pathogen Adhesion and modulate cytokine productions, leading to reduced frequency and severity of upper and lower respiratory tract infections. Commonly studied strains include Lactobacillus rhamnosus, Bifidobacterium lactis, and Lactobacillus casei. While clinical evidence supports the potential benefits of probiotics, results vary are depending on strain, dose and duration of use . Overall, probiotics represent a promising adjunct in managing allergies and respiratory infections, but further research research is needed to establish standardized guidelines for their clinical applications.

A Study on Hr Practices – Navigating Challenges and Embracing Opportunities Project Report
Authors:-Professor Dr. S.S. Muruganandam, Ms. K. Priyadharshini

Abstract-The purpose of this study is to thoroughly investigate the impact of remote work on Human Resources (HR) practices, with a specific emphasis on addressing challenges and capitalizing on opportunities arising from this transformative shift in the contemporary workplace. In the wake of the widespread adoption of remote work, this research aims to unravel the intricate dynamics that remote work introduces to traditional HR functions and explore innovative strategies that HR professionals can employ to adapt effectively to this evolving landscape.

Night Patrolling System for Improving Security
Authors:-Dr. AY Prabhakar, Abhishek Pandey, Prakhar Pratap Singh, Jayant Dubey

Abstract-The implementation of an IoT-based smart night patrolling robot is presented in this paper, utilizing an Arduino Uno, camera module, sound sensor, ultrasonic sensor, motor driver, motors, Nodemcu, and buzzer. The proposed robot is designed to autonomously patrol a designated area and capture images and videos of the area using the camera module. The ultrasonic sensor is used to detect obstacles and prevent collisions, while the sound sensor is used to detect unusual sounds and alert the user. The buzzer is included to provide an audible alarm in case of any significant disturbance in the patrolling area. The robot is designed to move around and change directions using the motor driver and motors, which are operated by an Arduino Uno. The NodeMCU provides internet connectivity, enabling remote monitoring and control. The proposed system can be used for a variety of applications, such as surveillance and security, and has the potential to improve the efficiency and effectiveness of night patrolling operations. The proposed system is developed at a low cost, making it accessible to a wider range of users. The implementation of the proposed system has been tested, and the results indicate that the system is efficient and effective in detecting and responding to environmental stimuli. The system is controlled using a web-based interface, and the users can monitor and control the system remotely.

Agro-Guide
Authors:-Rachana K, Premalatha H M

Abstract-Agro-Guide is a machine learning based web application designed to provide farmers with crop yield forecasting, crop recommendations and fertilizer recommendations, ultimately improving their crops without apologizing for farming. The app uses advanced techniques to predict yield amounts based on various factors such as seasons, regions, and historical data. Agro-Guide has the ability to recommend suitable crops and fertilizers. It helps farmers to produce better crops and use resources. Agro-Guide differentiates itself by integrating crop sales to facilitate the connection between farmers and people who want the crops. Inclusion of real time payments simplifies the sales process and make farmers to sell their produced crops directly in this platform. This application also has an interactive interface that provides farmers with information required. This chatbot plays an important role in facilitating communication, providing immediate assistance, solving questions and providing responsive user experience.

Resume Analyzer
Authors:-Vinayak Subray Hegde, Premalatha H M

Abstract-The “Resume Analyzer” is the advanced web application which provides the solutions for both Recruiters and Applicants by using the Natural Language Processing (NLP) technology. Its main motto is analysing the uploaded resume and providing the prediction, suggestions or advice to the both Job seekers and recruiters. For candidates they’ll upload the resume in pdf format, and the web application provides the basic information, experience level, predicted job role, existing and recommended skills, course recommendation according to the predicted job role, YouTube links for interview and resume tips and ideas. And for recruiters it’ll analyse the resume and provides the basic information, existing and recommended skills, parsed information of whoever using the tool (for better recruiting process) and downloadable parsed information.

Android “Virtual Clinic” Application for Healthcare Access and Assessment
Authors:-Varshitha M M, Premalatha H M

Abstract-The “Virtual Clinic”, a sophisticated application, is dedicated to addressing the healthcare needs of individuals managing Diabetes, Blood Pressure, and Mental Illness. This comprehensive platform offers a suite of services, including remote lab tests, video conferences for personalized consultations, nutritional guidance, and curated workout and meditation sessions. Recognizing the challenges of physical clinic visits and busy schedules, the Virtual Clinic prioritizes user comfort and flexibility by providing remote access. Unique to this platform is the convenience of at-home blood tests, eliminating the need for patients to visit labs. Online test reports, coupled with expert consultations, inform tailored medical and dietary plans. Weekly assessments ensure ongoing monitoring and adjustment. For mental health support, secure calls with psychiatrists and specialized mental wellness sessions enhance the holistic approach of the Virtual Clinic, redefining healthcare accessibility and personalized well-being.

Android “Virtual Clinic” Application for Healthcare Access and Assessment
Authors:-Yilin Gao, Sai Kumar Arava, Yancheng Li, James WSnyder Jr

Abstract-Artificial intelligence (AI) is widely deployed to solve problems related to marketing attribution and budget optimization. However, AI models can be quite complex, and it can be difficult to understand model workings and insights without extensive implementation teams. In principle, recently developed large language models (LLMs), like GPT-4, can be deployed to provide marketing insights, reducing the time and effort required to make critical decisions. In practice, there are substantial challenges that need to be overcome to reliably usesuch models. We focus on domain-specific question-answering, SQL generation needed for data retrieval, and tabular analysis and show how a combination of semantic search, prompt engineering, and fine-tuning can be applied to dramatically improve the ability of LLMs to execute these tasks accurately. We compare both proprietary models, like GPT-4, and open-source models, like Llama-2-70b, as well as various embedding methods. These models are tested on sample use cases specific to marketing mix modeling and attribution.

A Study on Central Bank Digital Currency
Authors:-Assistant Professor Mr. K. Ponnumani, C. Vasanth

Abstract-This Study aims on the Central Bank Digital Currency (CBDC) represents a digital form of a country’s sovereign currency, issued and regulated by its central bank. Unlike cryptocurrencies like Bitcoin, which are decentralized, a CBDC is centralized and operates under the supervision of the issuing authority. CBDCs aim to combine the efficiency and convenience of digital payments with the safety and stability associated with central bank-issued money. The implementation of CBDCs can potentially enhance financial inclusion, reduce transaction costs, and improve the efficacy of monetary policy. However, challenges remain in areas such as privacy, cybersecurity, and the potential disruption of traditional banking systems. As various nations explore and pilot CBDCs, the global financial landscape may undergo significant transformation, driven by advancements in digital finance and regulatory frameworks.

On Superconductivity, Dimensionality, and Destructive Interference: The Destructive Interference Theory of Superconductivity
Authors:-Donald J. Dodd

Abstract-The “Destructive Interference Theory of Super conductivity” is based on a hypothetical relationship between the destructive interference of phonons and the effect lower energy density has on dimensionality. This lower energy density and subsequent high number of dimensions with open apertures, higher dimensionality, allows the quantum entanglement of electrons. The hypothesis is predicated on a second hypothesis, the “Theory of Dimensionality,” describing, what Einstein characterized as a 4-dimensional spacetime fabric, as a highly dimensional sub-plank-sized quantum particle. At quantum mechanical scales, energy manifests itself as discrete packets of energy called quanta, and it should be apparent that Einstein’s spacetime fabric is no exception. Effects such as wormholes, tunneling, and quantum entanglement are confined to a highly dimensional quantum mechanical world because, at higher energy densities, in joules per meter cubed (J/m3), well below higher energy density found at room temperature, the normally open apertures of the dimensions that allow these effects, are closed. [26] The innate spring tension that holds the apertures of the many dimensions open, and allows energy to pass through them, will close in sequence from the highest dimension to the lowest as energy density increases, like a force compressing a spring. Phonon destructive interference, occurring when two matter waves of the same amplitude in opposite directions come together and cancel each other out, plays a critical role in the formation of lower energy density regions within a solid. [25] A phonon is a bosonic particle with vibration frequencies that typically range from 10 to 30 THz with an amplitude from 0.03 to 0.08 angstroms. [17] This wave-like virtual particle exhibits properties that include constructive and destructive interference, similar to the light and dark regions of the well-known double slit experiment. There is an inverse relationship between highly dimensional spacetime, referred to here as dimensionality, and the lower energy density regions caused within matter caused by the destructive interference. Spacetime is composed of highly elastic, highly dimensional, sub-plank-sized particles, whose size or dimensionality, the number of dimensions with open apertures, is inversely related to their local energy density. In other words, the open apertures of a spacetime particle, close in sequence, like a cascade, from the highest to the lowest dimension as energy density increases to its extrema – a mass approaching the speed of light. Superconductivity is one of many higher-dimensional effects of dimensionality. It occurs at and below a specific energy density when the aperture of the dimension that allows the quantum entanglement of electrons is open. Factors such as temperature and destructive interference are critical in achieving that critical energy density.

DOI: 10.61137/ijsret.vol.10.issue4.179

Indian Premier League 2022
Authors:-Jakkidi Harika Reddy, Sabina Amreen, Keshetty Ramya sri, Associate Professor Dr. Diana Moses

Abstract-The 2022 Indian Premier League (IPL) was a landmark season featuring the debut of two new franchises, Gujarat Titans and Lucknow SuperGiants, expanding the competition to ten teams. Gujarat Titans emerged as champions in their inaugural season, defeating Rajasthan Royals in the final. The season saw stellar performances, with Jos Buttler of Rajasthan Royals winning the Orange Cap for scoring 863 runs and Yuzvendra Chahal claiming the Purple Cap with 27 wickets. The introduction of new teams and an expanded format added excitement and competitiveness to the tournament, making it one of the most memorable editions in IPL history. Key highlights included the rise of young talents such as Tilak Varma, Umran Malik, and Ayush Badoni, who made significant impacts for their respective teams. Established franchises like Mumbai Indians and Chennai Super Kings faced unexpected challenges, failing to reach the playoffs, which underscored the unpredictable nature of the league. Despite pandemic-related challenges, IPL 2022 maintained strong fan engagement and viewership, reaffirming its status as a premier global T20 cricket competition. The season was a testament to the league’s dynamic nature, showcasing both emerging and seasoned cricketing talent.

Role of Cloud Computing in Effective and Intelligent Transport Systems
Authors:-Rohit Ginnare, Assistant Professor Amisha Patodi

Abstract-Intelligent transportation clouds could provide Services such as autonomy, mobility, decision support and the standard development Environment for traffic management strategies, and so on. With mobile agent technology, an urban-traffic management system based on Agent-Based Distributed and Adaptive Platforms for Transportation Systems (Adapts) is both feasible and effective. However, the large-scale use of mobile agents will lead to the emergence of a complex, powerful organization layer that requires enormous computing and power resources. To deal with this problem, we propose a prototype urban-traffic management system using intelligent traffic clouds.

Review on Soil Stabilization Using Plastic Waste and Limestone
Authors:-Avneesh Singh, Dr. Sunil Sugandhi

Abstract-Nowadays plastic has a major role in our life use, but the increased usage of it led to a serious challenge which is plastic waste. Plastic waste is increasing day by day and which led to many bad disposal methods like burning and due to that there are many environmental and pollution problems. Therefore, there is a need to seek for safe and effective disposal methods to protect our plant and next generations’ future. One of the effective and safe solutions is using plastic waste in civil engineering construction as this solution is eco-friendly where it will provide a safe disposal as well as in engineering there is always a seek for economical materials and as plastic waste is almost for free. In addition, adding these materials may improve the properties of the construction materials. This article reviews all the published trials of using waste plastic bottles fibers as soil improvement material to examine the effectiveness of using this material as a reinforcing material in improving soil properties. As well as to provide a data base of information regarding the best dimensions and percentages. After reviewing the literature, it was found that waste plastic bottles can effectively be used as a reinforcing material and it is an eco-friendly solution. But the best benefit is it really economical as this solution has showed good improvement in soil properties this can reduce the thickness of the pavement in highways construction as well as it provided a good stabilization method rather than the other expensive methods.

A Comprehensive Review of Deep Fake Detection Techniques
Authors:-Assistant Professor Mr. Bharath M., Soumya Ranjan Das, Soumya A Bavagi, Soujanya SN, Pradeep Paul

Abstract-The rise of artificial intelligence models has usheredin an era of unprecedentedly realistic fake images and videos, raising increasing concerns about their potential to deceive and manipulate. Dubbed “deepfakes,” these creations pose serious risks, including reputational harm, the dissemination of misinformation, and societal destabilization. To address this threat, researchers are actively engaged in developing computational methods aimed at detecting forged content and alerting users to potential manipulations. This paper explores the different methods for the detection of deepfakes, with a specific focus on aritificial learning-based approaches. It furnishes a comprehensive review of the various categories of deepfake detection methodologies. By examining the nuances ofthese techniques, the paper aims to contribute to the ongoing efforts to mitigate the adverse impacts of deepfakes and safeguard against their harmful consequences.

British Airways Reviews Analysis
Authors:-D. Shrestha, Sreenidhi Katkuri, Unnati Goel, Professor Dr P Lavanya

Abstract-This document provides a comprehensive analysis of customer reviews for [5]British Airways (BA)[5], utilizing Tableau software to visualize and interpret the data. The dataset includes various parameters such as reviewer details, travel specifics, and ratings for multiple service aspects. Key elements analyzed include aircraft type, traveler type, seat type, route, and performance indicators like seat comfort, cabin staff service, food and beverages, ground service, value for money, and in-flight entertainment. The reviews present a wide range of passenger experiences with BA, highlighting both positive and negative aspects. [1]The airline industry is a highly competitive market where customer satisfaction is a key factor for success.[1] Positive feedback often notes the efficiency of short-haul services and the attentiveness of the staff. However, many reviews express dissatisfaction with long-haul flights, citing issues such as uncomfortable seats, faulty in-flight entertainment, poor meal quality, and average service. Recurring themes also include frequent delays, lack of information from staff, and a perceived decline in service standards over time. This analysis, facilitated by Tableau, aims to provide visual insights into customer satisfaction trends and identify areas needing improvement. The goal is to help British Airways enhance its service quality and better meet passenger expectations.

Impact of Blackrock in Indian Economy (Coimbatore City)
Authors:-Assistant Professor Mr.K. Ponnumani, V. Gowthaman

Abstract-Black Rock, the world's largest asset management firm, has increasingly shaped the Indian economy through its significant investments and influence. This paper examines the impact of Black Rock on India, focusing on its role in financial markets, corporate governance, and sustainability initiatives. By analyzing Black Rock's investments in Indian companies, its engagement strategies with corporate boards, and its advocacy for environmental, social, and governance (ESG) standards, this study highlights how Black Rock's actions have influenced market dynamics and regulatory trends in India.

Examining the Evolution of Manufacturing Technologies
Authors:-Assistant Professor N.Rajiv Kumar, Mithun.R, Arun Raj.M, Gowtham.S

Abstract-The manufacturing industry has witnessed a significant evolution with the advent of 3D printing technology, offering an alternative to traditional metal manufacturing methods.This paper examines the fundamental differences between metal manufactured products and 3D printed products, focusing on various aspects such as materials, processes, design flexibility, production speed, cost-effectiveness, and environmental impact. Through a comparative analysis, this study sheds light on the strengths and limitations of each manufacturing approach, providing insights into their respective applications, advantages, and challenges. Understanding these differences is crucial for businesses and industries seeking to leverage the capabilities of both metal manufacturing and 3D printing technologies to optimize product development, production processes, and overall operational efficiency Metal and plastic are two widely used materials in manufacturing, each offering unique properties and advantages in various applications. This abstract presents a comparative analysis of metal and plastic products, focusing on their inherent characteristics, applications across industries, and key considerations for material selection. This paper explores the fundamental differences between metal and plastic products, focusing on their material properties, manufacturing processes, applications, and environmental impacts. It examines how the distinct characteristics of each material, such as durability, weight, flexibility, and recyclability, influence their suitability for various industries and consumer needs. Additionally, it discusses the environmental implications associated with the production, use, and disposal of metal and plastic products, considering factors such as energy consumption, greenhouse gas emissions, and recyclability. By providing a comprehensive comparison, this study aims to inform decision-making processes regarding material selection, promoting sustainability and resource efficiency in product design and manufacturing.

A Research on Comparative Seismic Analysis of RCC Building with and Without Bracing Using ETABS
Authors:-Pramod Kumar Lodhi, Professor Dr. Rajeev Chandak

Abstract-In India the provision of bracing system in RCC structures is very rare feature. This feature is very much desirable in structures built in seismic areas. This study gives a solution to eliminate or reduce the effects of earthquakes caused due to seismic loads. Bracing is a highly economic and efficient method of resisting lateral forces. X Bracing system is more efficient and safe at the time of earthquakes when compared to remaining bracing system. This study aim is to compare the normal building and building with X bracing system at different positions like centre, corner, and both place in on time on all four sides and on exterior face of the building. For this purpose, the G+8 building model is used with X bracing systems .The parameters which will be considered for comparing the seismic effect of buildings are Time period, Maximum story displacement, maximum story drift, maximum and minimum moment and maximum story shear in seismic zones III ,studies of braced and unbraced models are conducted . In this study, analysis of RCC building with X steel bracings is carried out by using ETABSv2021, the Response spectrum Method is used to investigate the RC-framed models. All mentioned data for RCC building is analyzed as per IS:456-2000 and the load combinations and frame model are analyzed as per IS:1893-2016. In this project we will prove the importance of bracing system in order to resist horizontal forces such as earthquake. Conclusions are drawn based on the tables obtained. When compared to an unbraced frame, it has been found that the braced frame’s base shear and moment capacity value increases while its storey displacement, storey drift , ,and time period decrease.

Review on CBR Analysis and Soil Stability Improvement Using Bituminous Stabilization
Authors:-Arvind Patel, Dr. Sunil Sugandhi

Abstract-Soil stabilization is the process of improving the shear strength parameters of soil and thus increasing the bearing capacity of soil. It is required when the soil available for construction is not suitable to carry structural load. Soils exhibit generally undesirable engineering properties. Soil Stabilization is the alteration of soils to enhance their physical properties. Stabilization can increase the shear strength of a soil and/or control the shrink-swell properties of a soil, thus improving the load bearing capacity of a sub-grade to support pavements and foundations. Soil stabilization is used to reduce permeability and compressibility of the soil mass in earth structures and to increase its shear strength. The main objective of this paper is to review the physical and chemical properties of soil in different types of stabilization methods. Stabilization and its effect on soil indicate the reaction mechanism with additives, effect on its strength, improve and maintain soil moisture content and suggestion for construction systems. Soil stabilization can be accomplished by several methods. All these methods fall into two broad categories namely mechanical stabilization and chemical stabilization. Mechanical Stabilization is the process of improving the properties of the soil by changing its gradation and chemical stabilization of expansive soil comprises of changing the physico-synthetic around and within clay particles where by the earth obliges less water to fulfill the static imbalance and making it troublesome for water that moves into and out of the framework so as to fulfill particular designing road ventures.

Microplastic Menace: Unraveling the Presence, Sources and Health Impact in Domestic Tap Water
Authors:-Jyoti Punia, Reena Jain

Abstract-Microplastics, tiny plastic particles less than five millimetres, are a significant ecological risk. They are found in soil, sediment, and surface water. A study examining microplastic contaminants in tap water in residential areas found three types: cellophane, cellulose, and poly (2, 2, 2-trifluoromethyl vinyl ether). The study highlights the need for effective mitigation measures and provides insights into the health concerns associated with different types and concentrations of microplastics. Ensuring safe and clean water is crucial for public health, making water quality protection essential for managing microplastic pollution.

DOI: 10.61137/ijsret.vol.10.issue4.182

Hardware Implementation of BI- Directional Buck Boost Converter for V2g System with Hybrid Energy Storage System
Authors:-Scholar Samyuktha. T, Professor Ganesan.S

Abstract-In modern power system operations, demand side integration is one of the key functions which enables active consumer participation. Electric vehicles (EVs) encourage active participation of consumers for power management. In vehicle to grid integration (V2G), energy storage system (ESS) is connected with the grid through bidirectional converters. The topology for V2G integration consists of ESS, switching bidirectional buck-boost converter, full bridge inverter, and grid. Now-a-days, hybrid energy storage system (HESS) is an attractive solution for EVs. In this work, a topology for V2G with HESS is proposed. This topology comprises of an active HESS in which Li-ion battery is connected to the super capacitor via a bidirectional dc-dc half bridge converter, and full bridge inverter. The fuzzy logic controller using triangular membership functions and hysteresis current controller are proposed for inverters and bi-directional dc-dc converter respectively. The simulation of proposed topology is developed in MATLAB 2021 and the performance is verified. The hardware has been developed which comprises of a bi-directional buck-boost converter (HESS) and converter. The converter plays a crucial role in managing the bi-directional flow of energy between (EV) and the power grid, facilitating both charging and discharging operations. the several critical observations were made. The selected MOSFETs performed reliably under high-speed switching conditions, and the low inductors and capacitors minimized power losses. The tapping transformer provided robust electrical isolation and effective signal transfer, with adjustable voltage taps enhancing MOSFET switching performance. The DSP30F2010 microcontroller, using fuzzy logic control, offered precise and adaptive regulation.

DOI: 10.61137/ijsret.vol.10.issue4.183

Leaveraging AI for Public Health Management
Authors:-Ganesh Ramalingam

Abstract-This whitepaper examines the use of artificial intelligence (AI) in managing population health. It discusses how AI can analyze population health data to identify trends, predict outbreaks, and optimize resource allocation. The paper covers the ethical considerations of using AI in public health and the regulatory measures needed to protect patient data. A novel algorithm called Geo Health AI is presented, along with Python code, to demonstrate how AI can be applied to geospatial population health analysis. Case studies and outcomes from AI implementations in population health management are reviewed. Finally, recommendations are provided for healthcare organizations looking to leverage AI for population health initiatives.

DOI: 10.61137/ijsret.vol.10.issue4.215

Advancements in Predictive Models for Software Defects: A Comprehensive Exploration
Authors:-Professor Mohamed Abdul Jailani, Kallal Bhakta

Abstract-This venture centers on foreseeing program bugs utilizing a dataset from the College of Geneva, Switzerland, which incorporates data from different program frameworks like Overshadow JDT Center, Overshadow PDE UI, and Lucene. By analyzing program properties such as lines of code, strategies, and traits, the point is to anticipate the number of bugs in progress. This foreknowledge makes a difference in proactive imperfection administration and chance relief. The venture envelops intensive information investigation, preprocessing, and visualization, taken after by progressed exploratory information investigation (EDA) utilizing machine learning and dimensionality lessening procedures. It addresses challenges like hyperparameter tuning and lesson awkwardness, endeavoring to classify computer program information by bug seriousness, from no bugs to different bugs. The extreme objective is to make strides in program support and streamline discharge forms.

DOI: 10.61137/ijsret.vol.10.issue4.186

Analysis of Seawater Quality Parameters and Treatment with Hydrodynamic Cavitation Method
Authors:-Divya Patil, Dr. Pankaj Gohil, Dr. Hemangi Desai

Abstract-The aim of the research was to compare the quality parameters of Seawater before and after hydrodynamic cavitation treatment. The Hydrodynamic Cavitation Method for water treatment gives the highest reduction in Turbidity (100%), the second highest reduction in TSS (83.86%), and the lowest reduction in Na+ (8.47%), according to the study and analysis of various quality parameters. When compared to CPCB Water Quality Criteria, treated water is suitable for outdoor bathing; it again satisfies the standards for classes SW-I, SW-II, SW-III, SW- IV and SW-V, i.e., treated sea water can be used for a variety of purposes, including bathing, contact water sports, commercial fishing, mariculture, ecologically sensitive zones, aesthetics, harbour, waters Navigation and Controlled water disposal. The SAR value of treated water, which is 1.72, indicates it is appropriate for all types of soil and crops. The treated water’s WQI, which is 65, showed that it is of Fair quality and may be used for industrial and irrigation uses. Water quality can be improved by recycling the treated water for an additional 24 hours using the hydrodynamic cavitation method. Recycling of one time treated sea water will result in higher-quality water that can be used for a variety of purposes. The Hydrodynamic Cavitation method by using venture orifice is proven to be the most effective over the other methods. Because it does not require any chemical reagent, hence does not produce any hazardous chemical waste, and maintains an eco-friendly and economically sustainable, environment benign technique for the treatment of Seawater.

DOI: 10.61137/ijsret.vol.10.issue4.187

Research on Development of Android Applications
Authors:-Ankur Bhuyan

Abstract-This paper introduces the Android platform and discusses the features of Android operations, furnishing a detailed explanation of the Android operation frame from the point of view of formulators. It includes a demonstration using a introductory music player to illustrate the fundamental workings of Android operation factors. The end of this paper is to prop in understanding how Android operations operate and to grease the development of operations on the Android platform.

DOI: 10.61137/ijsret.vol.10.issue4.188

A Comparative Analysis of Sales Tax, Value Added Tax (Vat), and Goods and Services Tax (GST)
Authors:-Dr. Madhuri Shah

Abstract-The scene of tax collection in India has seen critical changes lately, with the presentation of (GST) denoting an urgent second in the nation’s duty system. This examination paper expects to give a complete examination and investigation of the three significant utilization-based tax collection frameworks – Services tax, VAT, and GST, featuring the critical patterns and suggestions for organizations and the economy. The review digs into the verifiable development, functional instruments, influence on organizations and customers, and strategy suggestions related to every tax collection model. By fundamentally analysing these frameworks, the paper tries to add to a superior comprehension of their assets, shortcomings, and the more extensive financial outcomes they involve. A similar investigation looks at the benefits and difficulties related to Services tax, VAT, and. GST has arisen as a distinct advantage, resolving issues like expense flow, further developing consistency, and advancing a bound-together market. The review investigates the effect of these tax collection models on organizations, government income, and financial development, considering factors, for example, simplicity of carrying on with work furthermore, the general taxation rate in different areas. The review expects to add to a superior comprehension of the patterns and difficulties, and open doors in the Indian assessment framework, offering important bits of knowledge for policymakers, organizations, and researchers.

Role of Data Analytics in HR Decision Making
Authors:-B. Abinaya, Assistant Professor Mr.M.A.Prasad

Abstract-This project aims to explore the transformative impact of data analytics on HR practices, focusing on how data-driven insights can enhance recruitment, employee engagement, performance management, and retention strategies. By leveraging various analytical tools and techniques, HR professionals can make more informed decisions, predict future trends, and implement strategic initiatives that align with organizational goals. This study will examine case studies and real-world applications, providing a comprehensive overview of how data analytics can optimize HR processes and contribute to the overall success of an organization. Through qualitative and quantitative analysis, this project will highlight the benefits, challenges, and future directions of integrating data analytics into HR decision-making frameworks.

Utilising Accounting Ratios for Strategic Implementation in Technology Based Organization: A Case Study of (2019 and 2023)
Authors:-Om Raj Dahal, Professor Murtaza Hussain

Abstract-Companies continue to seek effective ways of maximising efficiency and securing a competitive advantage in the current changing business environment. The study looks at how important accounting ratios are to help companies make strategic decisions and implement them. The paper examines through a rigorous literature review and how accounting ratios can be used to analyse finance performance, operating efficiency and identify areas where improvement is needed. According to the findings, important ratios like profitability, liquidity, leverage, and efficiency are crucial for guiding strategic initiatives in a range of industries. The research also emphasises how crucial it is to incorporate accounting ratio analysis into frameworks for strategic planning in order to improve organisational performance and enable well-informed decision-making. In addition to adding to the body of knowledge on financial management, this study highlights the strategic significance of accounting ratios and provides useful advice for companies hoping to establish a competitive edge in the current global economy. The main objective of the study is to evaluate the Financial table by using tools of accounting (Ratio analysis) in a Technology based business and in order to examine the effects on Strategic management decisions and to evaluate the contribution of these data on building corporate strategies.

DOI: 10.61137/ijsret.vol.10.issue4.189

Mental Status Examination-An Overview
Authors:-Assistant Professor Mrs Purohit Saraswati

Abstract-Companies continue to seek effective ways of maximising efficiency and securing a competitive advantage in the current changing businesThe mental status examination (MSE) is a fundamental component of psychiatric assessment, playing a pivotal role in the diagnosis, treatment planning, and management of mental health disorders. This structured clinical assessment evaluates various aspects of a patient’s psychological functioning, including appearance, behavior, mood, thought processes, cognition, and insight. By systematically examining these domains, MSE provides critical information that aids in diagnosing psychiatric conditions, establishing baseline functioning, identifying risk factors, and monitoring treatment effectiveness. It enhances communication among healthcare providers, ensuring continuity and coherence in patient care, and holds significant legal and ethical implications in contexts such as competency evaluations and involuntary hospitalizations. The structured nature of MSE not only guides clinical decision-making but also underpins evidence-based practice in psychiatry, contributing to improved patient outcomes. This abstract underscores the indispensable role of MSE in comprehensive psychiatric evaluation and highlights its multifaceted contributions to mental health care.

Enhanced Machine Learning Technique for Predicting Cardiac Diseases Using ECG Data
Authors:-Priyanka Singh, Sameeksha Rahangdale, Virendra Kumar Tiwari, Gaurav Kishor Saxena

Abstract-Heart disease is a leading cause of morbidity and mortality worldwide. The advancement of machine learning (ML) has enabled the development of predictive models that can identify cardiac conditions with high accuracy. This paper presents an enhanced random forest-based ML technique for predicting cardiac diseases using ECG data. The proposed model evaluates several metrics including accuracy, classification error, F-measure, recall, and precision, achieving an accuracy rate of 92%. This technique transforms vast amounts of raw healthcare data into valuable insights for informed decision-making and forecasts in clinical settings. Our results demonstrate the efficacy of the proposed method in early diagnosis and prevention of heart diseases.

DOI: 10.61137/ijsret.vol.10.issue4.190

Interference in A/B Testing: Causes and Mitigation
Authors:-Saurabh Kumar

Abstract-A/B Testing is the gold standard for online experimentation used by most companies for testing their product features. While A/B test experimentation works well in most settings, it is particularly susceptible to interference bias, especially in online marketplaces or social networks. This paper examines situations where interference bias occurs and explores potential methods to mitigate its effect on evaluation.

Review of Violence and NonViolence Using Deep Learning Techniques
Authors:-Neeraj Sharma, Dr. Kamlesh Ahuja, Chandni Sikarwar

Abstract-The rapid proliferation of online video content necessitates robust automated screening technologies to mitigate exposure to violent and harmful material. This review examines the application of deep learning techniques in detecting and classifying violent and non-violent content in videos. We explore various neural network architectures, including Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, and their integration for comprehensive video analysis. The review highlights the challenges in distinguishing ambiguous actions and the role of audio analysis in enhancing detection accuracy. Additionally, we discuss the ethical implications and privacy concerns associated with deploying AI-driven surveillance systems. The findings emphasize the need for continuous innovation and responsible use of deep learning technologies to ensure public safety and foster a positive digital environment.

A Study on Digital Tranformation in Retail Marketing
Authors:-Assistant Professor Mr.K.Ponnumani, Jeeva.D

Abstract-The digital transformation of retail marketing has impacted the way companies interact with customers, streamline operations, and drive growth. This study looks at the complex impact of digital technologies on retail marketing strategies, with a focus on the integration of online and offline channels, the use of big data and analytics, the rise of e-commerce, and the change of customer behavior. This study efforts to provide a comprehensive knowledge of how digital tools such as social media, artificial intelligence, and mobile applications are transforming the retail scene through case studies and current trends. The findings emphasize major benefits such as improved customer experience, tailored marketing, and operational efficiency, while also addressing issues such as cybersecurity threats and the digital divide.

Secure Crypto Wallet Solutions
Authors:-Mr.Karthiban.R, Bharathi A K, Deepika P, Pravishka D, Yazhini K

Abstract-With the widespread adoption of cryptocurrency wallets, the risk of theft through malicious software has increased significantly. These wallets heavily rely on cryptographic techniques, such as the elliptic curve digital signature algorithm, to ensure transaction security. Users generate multiple addresses for receiving coins, each requiring a private key for spending authorization. While Bitcoin wallets assist in managing these keys, storing complete private keys locally poses a theft risk. To enhance security, our proposed method combines random seeds and a user-friendly passphrase for private key generation. By storing only random seeds locally, the method adds complexity for attackers, as passphrase knowledge is crucial for deriving complete private keys. Additionally, we introduce a key recovery approach for forgotten passphrases, ensuring usability without requiring advanced technical knowledge. Importantly, these security enhancements come without imposing additional complexity, making it user-friendly even for individuals without professional knowledge in cryptography. By minimizing the risk of unauthorized access and theft, our approach aims to provide a robust and accessible cryptocurrency wallet experience for all users.

Performance Assessment of Reinforced Concrete under Corrosion in Serviceability Conditions: A Review Based on IS 456 Guidelines
Authors:-Sonu Chouhan, Professor Sachin Sironiya

Abstract-Reinforcement corrosion is a common cause of deterioration of cement in reinforced concrete. The corrosion mechanism involved and the consequent structural behaviour of deteriorated reinforced concrete members have been studied by several researchers. Nevertheless, the knowledge obtained is primarily based on experimental investigations of artificially corroded specimens whereas natural corrosion may affect structural behaviour differently. This paper aims to deepen the numerical understanding of the structural effects of natural corrosion deterioration with a focus on the remaining anchorage capacity between deformed bars and concrete, as well as the investigation of possible links between visual inspection data and structural damage.

Review of Thermal Energy Storage System
Authors:-Research Scholar Dhanraj Digodiya, Assistant Professor Khemraj Beragi

Abstract-This research paper investigates the application of Computational Fluid Dynamics (CFD), specifically ANSYS CFX, in the analysis and optimization of Thermal Energy Storage (TES) systems. TES systems are essential for managing energy by storing excess thermal energy for later use, and their efficiency is crucial for sustainable energy solutions. The study reviews recent advancements in CFD methodologies and their impact on TES performance, focusing on simulations of various TES configurations, including those incorporating phase change materials (PCMs). Through detailed CFD analysis, this paper explores how ANSYS CFX can model complex thermal and fluid dynamics, optimize system designs, and improve overall thermal efficiency. The findings highlight the significant role of CFD in addressing design challenges, enhancing energy storage capabilities, and contributing to more effective and sustainable energy management. This paper provides a comprehensive overview of the benefits and applications of CFD in TES systems, offering insights for researchers and engineers working in the field of thermal energy storage.

The Ameliorating Effect of Lactate-rich Akamu in Reversing Depressive Symptoms in Rats
Authors:-Okoli F.A., Anazodo C.A., Chukwura E.I.,

Abstract-Depression is a debilitating mental health condition affecting millions worldwide. Traditional treatments include a range of antidepressant medications and therapies, yet not all patients respond adequately. This study was designed to evaluate the effect of lactic acid-rich akamu on depression and its antidepressant like quality in rodents. Eighteen rats were used in the study, 6 were fed akamu a local food produced from the fermentation of Zea mays, rich in lactate, 6 were administered a standard antidepressant (escitalopram) while the other 6 served as control. The chronic mild stress protocol was used to induce depression. After 3weeks, there was a 71.43% reduction (on the average) in sucrose consumption which was indicative of depression. On the 56th day of the study, 3 weeks after treatment commenced, there was a reversal of depressive symptoms and a rapid increase in the weight of rats that were fed akamu while there was a 14% decrease in the rats that were administered the standard drug. Although this reduction was statistically non-significant (p>0.05). Furthermore, after feeding the rats with akamu, there was a 62.5% average increase in sucrose consumption, indicative of recovery from depression. The level of lactate in the stool of rats before the feeding trial was between 66-80mg/kg. After the feeding trial, it ranged between 153-216mg/kg with the akamu group having the highest value.

Customers’ Experience in the Digital Age of Banking – A Study of Canara Bank in Dharwad Dstrict
Authors:-Research Scholar Shilpa C.Dharwad, Dr.(Smt) A.N.Tamragundi

Abstract-Customer experience with technology based services in Canara Bank branches of Dharwad district are evaluated. For this purpose 400 hundred customers of Canara Bank is chosen using Cluster Sampling technique. The population of the study is divided into three groups (clusters) for research viz; Rural, Semi-Urban and Urban area, wherein each of the cluster, the proportionate of the number of Canara bank branches in an area and the total number of Canara bank branches in Dharwad district is considered. The primary data is collected through structured questionnaires distributed to 400 customers. Kruskal Wallis test is used to test that ‘There is significant difference in the usage rate of technology based services by the customers by the variation in the income level of customers’. Chi-Square test is used to test that ‘There is significant association between the locality of bank customers and their level of satisfaction after using IT enabled services’. The study found that the customers are extremely satisfied with the reliability, tangibility, assurance, security aspects of IT enabled services and are least satisfied with responsiveness. The study suggests that bank should ensure high safety measures and gain the customers’ trust.

Exploring the Strategic Role of Storefront Aesthetics and Design Principles
Authors:-Simar Dhingra

Abstract-This research explores the significance of storefront quality in influencing customer behaviour and purchase decisions. Emphasizing the pivotal role of signage, marquee, and awnings, the study underscores their impact on forming initial impressions and attracting customer attention. Additionally, the importance of a clutter-free entryway and well-designed landscaping in enhancing store appeal is discussed. The research highlights the criticality of effective window and interior displays in serving as information links to potential customers. Furthermore, it delves into the principles of design, such as balance, proportion, emphasis, and harmony, as essential elements for creating compelling visual merchandise displays. Finally, the research examines the implications of brand projection and store layout coherence on customer experience and purchase intent. It contributes to a deeper understanding of the strategic importance of storefront aesthetics and design principles in driving retail success.

DOI: 10.61137/ijsret.vol.10.issue4.191

Design & Analysis of Smart Optimizer Charging System for E-Vehicle
Authors:-Rahul Arya, Dr. Sourabh Gupta

Abstract-There are several challenges associated with electric vehicles. This work discusses the effect of electric vehicles on the load frequency deviation. However, Load cannot be the same throughout, load deviates from time to time. To get rid of these disadvantages related to conventional controllers, a lot many schemes have been put forth in literature. This work presents a new design of various types of load frequency controllers based on different types of Artificial Intelligent (AI) optimization techniques such as Fuzzy logic, ANN tuner for a single area power system. The performance of the controller under study shows an enhancement in the frequency deviation signal as well as the peak overshoot and settling time for the frequency output signal. The performance of the proposed scheme is validated using MATLAB/ SIMULINK tools.

DOI: 10.61137/ijsret.vol.10.issue4.192

Literature Review of Secure Hash Function Algorithm
Authors:- M.Tech.Scholar Birendra Prasad Sah, Professor &Hod Dr.Bharti Chourasia

Abstract-A cryptographic hash work is a phenomenal class of hash work that has certain properties which make it fitting for use in cryptography. It is a numerical figuring that maps information of emotional size to a bit string of a settled size (a hash) and is expected to be a confined limit, that is, a limit which is infeasible to adjust. Hash Functions are significant instrument in information security over the web. The hash functions that are utilized in different security related applications are called cryptographic hash functions. This property is additionally valuable in numerous different applications, for example, production of digital signature and arbitrary number age and so on. The paper talks about different author’s research related to secure hash function, that a reconcilable on this development, and accordingly on these hash functions additionally face same attacks. There are many different hash function definitions and requirements in the cryptographic hash function literature, and many of them are in conflict. This survey discusses the many meanings and attempts to improve the literature by outlining the field’s history and accurately illustrating the current state of research goals.

Effects of Influential Travelers on their Audience
Authors:- Assistant Professor Ms. Lucky Gupta, Mr. Harsh Mohan Sharma, Priya Prasad

Abstract-More than a hundred new occupations have emerged in the last decade as a direct result of social media, which has altered our daily lives in ways nobody could have predicted. It paved the way for alternative means of subsistence for those who didn’t want to conform to conventional wisdom. Travel influencers are one example of this type of job. Internet stars who share stories from their travels on social media are known as “travel influencers” in the tourism, culture, and travel industries. What makes these travel influencers so influential is the subject of this research.

DOI: 10.61137/ijsret.vol.10.issue4.193

PHP Frameworks Usability in Web Application Development
Authors:- Assistant Professor Kondeti Sowjanya

Abstract-A framework defined as a structure that supports the development of dynamic websites, web applications, and services. Framework code and design are often reusable to assist customization, resource service, and API-related tasks. This study discussed current practice to help a developer understand PHP frameworks adoption for web application development. Three approaches were selected to understand the features suitability of the PHP frameworks: the systematic approach, score criteria evaluation, and PHP framework technical factors. A comparison of 23 different frameworks features also has been studied that involves features such as ORM, Code Generator, Template Engine, and CRUD Generator. Besides PHP framework features, understanding the basic core PHP to build web application would help a lot in learning PHP frameworks. Moreover, new developers should not limit themselves to a particular PHP framework only but also allow themselves to explore various PHP frameworks in the development of web application projects.

DOI: 10.61137/ijsret.vol.10.issue4.195

Towards Sustainable Hydrogen: A Comprehensive Research on Dark Fermentation Technologies for Bio-hydrogen Production
Authors:- Morris A.H. Sackor, Ms. Mahenk D. Patel

Abstract-Hydrogen offers a feasible option as a sustainable energy source in place of non-renewable energy. Power or energy made of hydrogen creates water when it is consumed. It is the most prevalent and basic element in the universe. Nowadays, heavy-duty petroleum is used to electrolyze water to make hydrogen in combination with carbon-based biomass or non-renewable resources like gas and coal. However, producing hydrogen from non-renewable resources requires a lot of energy and produces more greenhouse gasses which are of great threat to the environment. Therefore, it’s critical to create renewable alternatives for producing hydrogen, such bio-hydrogen. Reviewing bio-hydrogen production method, this paper focuses on the dark fermentation technologies utilized in bio-hydrogen generation, the mechanism or steps involve in bio-hydrogen production, the variables or parameters influencing bio-hydrogen production, hydrogen purification system, and limitations.

Renewable Energy Sector Mutual Funds in India: A Growth Potential Analysis
Authors:- Mishra Om

Abstract-The renewable energy sector in India has emerged as a critical area of focus in the context of the country’s sustainable development goals and its transition towards a low-carbon economy. This research paper analyzes the growth potential of renewable energy sector mutual funds in India, considering the rapidly evolving market dynamics, policy interventions, and investor interest. The study aims to evaluate the performance of these mutual funds, identify the key drivers of growth, and assess the risks and opportunities associated with investments in this sector. By employing a mixed-method approach that includes quantitative analysis of mutual fund performance data and qualitative insights from industry experts, the study offers a comprehensive understanding of the factors influencing the renewable energy sector. The analysis also explores the impact of recent policy changes, such as the reduction of the angel tax to 0%, which is expected to attract Foreign Institutional Investors (FIIs) and further bolster the sector’s growth. The findings suggest that the renewable energy sector mutual funds in India are poised for significant growth, driven by supportive government policies, technological advancements, and increasing investor awareness. However, the study also highlights the challenges related to market volatility, regulatory risks, and the capital-intensive nature of renewable energy projects. The paper concludes with recommendations for investors and policymakers to enhance the attractiveness and sustainability of renewable energy sector mutual funds in India, positioning them as a key component of the country’s financial landscape.

Securing Communication with Graphical Authentication, Iris Recognition, and AES Messaging
Authors:- M Prathiba, G Rakesh, Associate Professor Dr. T Madhavi Kumari

Abstract-This paper introduces a cutting-edge method for enhancing an Iris-Based Authentication System’s (IBAS) security and communication capabilities utilizing Daugman’s Algorithm. This method improves the protection of sensitive data and provides secure information sharing by seamlessly integrating Daugman’s Algorithm, crypto-steganography, and Advanced Encryption Standard (AES) encryption. User registration, secure message publishing, and dependable message retrieval are among the system’s fundamental capabilities. A distinctive iris watermark is created during user registration and placed within an iris image, acting as both an authentication identifier and a covert conduit for inserting encrypted messages. AES encryption adds an additional degree of security to communication content, securing it against unauthorized access. Messages are AES-encrypted before being included into the iris watermark during the uploading process. Crypto-steganography removes the hidden message on the recipient’s end, and the AES key is then used to decode it. The system’s effectiveness is shown by experimental findings, which support its potential to improve authentication and communication security. Combining crypto-steganography, graphic iris-based authentication, and AES encryption results in a strong and secure communication architecture that significantly reduces the danger of data interception and illegal access. The development of safe information sharing inside modern information systems is aided by this effort.

A Study of Indian Consumers Perception of Industries that Benefit Most From Telemarketing: Special Reference to Consumers in Jabalpur City: Literature Review
Authors:- Ajit Kumar Singh, Dr. Sourabh Kumar Nougriaya

Abstract-Telemarketing gained acceptance, recognition, and popularity. It is currently one of the most widely used strategies to increase sales since it assists sales representatives in making sales pitches before in-person meetings and helps them persuade the customer. The owners of mobile phones receive a call (manually, by recording, or via sms) informing them about the company’s offerings and promotional campaigns. While telemarketing has produced an affordable direct marketing tool, the customer may react differently. The term “telemarketing” is a combination of the words “telecommunication” and “marketing,” and it is related to telephone selling in that it makes use of telephones as a medium. On the other hand, telephone selling involves phoning a random person based on phone directories and convincing them to purchase a product or service or both. The research was carried out to examine Indian consumers’ perceptions of the top 3 industries that benefit most from telemarketing, with special reference to consumers in Jabalpur city. Results show according to the highest mean top 3 industries are the domestic customer service support offerings industry, the retail sector industry, and the sales industry.

Lung Cancer Detection Using DRN Based HBA and Classification Using Nasnet COA
Authors:-Ashmi.C, S.V.Brindha

Abstract-The domain of Artificial Intelligence (AI) is made important strides recently, leading to developments in several domains comprising biomedical diagnostics and research. Among several kinds of cancers, the colon and lung variations are the most frequent and deadliest ones. Deep learning (DL) and Machine learning (ML) systems are exploited to speed up such cancer detection, permitting researchers to analyze a huge count of patients in a lesser time count and at a minimal cost. This study develops a new Biomedical Image Analysis Lung Cancer Detection using Deep Residual Network based Honey Badger Algorithm (DRN-based HBA) model and classification using Neural Architecture Search Network based Coati Optimization Algorithm (NASNet-based COA). The presented DRN-based HBA with NASNet based COA technique examines the biomedical images for the identification of lung cancer. To accomplish this, the DRN-based HBA and NASNET based COA technique applies Gabor filtering (GF) to preprocess the input images. In addition, it employs a U-Net segmentation, then feature extractor used to create a collection of feature vectors such as LBP and HOG. Furthermore, the DRN with HBA is utilized for detecting lung cancer. Finally, the NASNET based COAis employed for classifying lung cancer. To demonstrate the more incredible outcome of the proposed system, an extensive experimental outcome is carried out. The comprehensive comparative analysis highlighted the greater efficiency of the proposed technique with other approaches with maximum accuracy of 99.66%.

Digital Card Transaction Cyber Crime Detection System Using Fuzzy Logic and K-Means Algorithm
Authors:-Assistant Professor S.Hanisha Begam

Abstract-The usage of digital card has dramatically increased, digital card fraud has become increasing rampant in recent years. Nowadays credit card fraud is one of the major issues of great financial losses, for the merchants and individual clients are also affected. This fraud is difficult to find out fraudulent and concerning losses will be barred by issuing authorities. As a result, fraud detection is the important solution and almost certainly the best way to stop credit card fraud types. Fuzzy logic is to analyze the spending profile of each card holder Credit card fraud can be detected on analyzing of previous transactions data. In this study Fuzzy logic and k-means are developed and applied to credit card fraud detection problem. It will be the most effective method to counter fraud transaction through internet. Fuzzy logic and k-means produce a better result comparing to the other data mining techniques.

Forest and Wildlife Conservation in India
Authors:-Assistant Professor Dr.K.Neela Pushpam

Abstract-The term “wildlife” refers to non-domesticated animal species. As a result, any living organism found in the forest is associated with wildlife. It can be found in almost all ecosystems, including rainforests, boreal forests, plains, grasslands, and deserts. Wildlife contributes significantly to the stability of our environment by being directly or indirectly involved in natural processes. Each living organism is equally important in the food chain; they may be a producer, a consumer, or a decomposer; all are interconnected and rely on one another for survival. Forests provide a variety of resources, including food, medicine, textiles, and raw materials. Aside from regulating global temperatures, forests also help to keep soil from eroding and shelter more than 80% of animal species and terrestrial biodiversity. They also help to improve a country’s socioeconomic conditions. It is the practice of preparing and preserving forested areas for future generations’ benefit and sustainability. Conservation is required to protect ecological diversity and our safety systems like air, water, and soil. The Indian Wildlife Act was enacted in 1972 to conservationists’ demands. Our planet earth is a home to millions of living beings. From micro-organisms and bacteria, lichens to banyan trees, elephants, and blue whales, there is a vast multitude of living organisms found on the earth. Sadly, the human beings today have transformed the nature and wildlife into a resource. They obtain different products directly and indirectly from the forests and wildlife such as wood, barks, leaves, rubber, medicines, dyes, food, fuel, fodder, manure, etc. which depleted our forests and wildlife. As said by Gandhiji, ‘The world has enough for everyone’s need but not enough for everyone’s greed.’ Despite knowing and understanding this truth, we do not put it into practice. As a result of this, our natural resources are at a constant risk of depletion. So, here we’ll study about forest and wildlife in particular. Let’s find out more about Forest and Wildlife Resources.

Soft Biometric trait on Fingervein Recognition Using CNN Resnet
Authors:-Femila.K, Dr.V.Dyana Christilda

Abstract-Many finger vein feature extraction algorithms achieve adequate performance due to their ability to reflect texture, while simultaneously ignoring the finger tissue forming intensity distribution and, in some cases, processing it as background noise. Use this kind of noise as a novel soft biometric feature in this project to achieve better output in finger vein recognition. First, a detailed analysis of the finger vein imaging theory and the image characteristics is provided to demonstrate that the intensity distribution produced in the background by the finger tissue can be extracted for identification as a soft biometric feature. Then, two finger vein background layer extraction algorithms and three soft biometric trait extraction algorithms are proposed for intensity distribution feature extraction. In the classification stage developed a system with implementation of convolution neural network specifically resnet18 for the training image dataset and image retrieving process is done. Purpose of introducing deep learning in developing finger vein identification system is to get accurate more performance and speedy results. Results are computed on the basis Euclidean distance between features obtained from test image and features of trained images, the model designed has good robustness in illumination and rotation.

Seismic Performance Evaluation of RCC Building Resting on Slopping Land
Authors:-Ram Krishna Shrestha, Mukil Alagirisamy, Purushottam Dangol, Bijaya Ram Koju, Om Prakash Giri

Abstract-Sloping terrain is a prevalent feature in many regions of Nepal, often necessitating the construction of buildings on uneven ground. These geographical conditions present unique challenges regarding seismic vulnerability and structural integrity. Buildings on sloping terrain are more challenging to design and construct due to the presence of powerful earthquake loads combined with the forces of the sliding slope itself. This conference paper presents a comprehensive study on the seismic performance of Reinforced Concrete (RCC) buildings situated on sloping land. The main objective of this study was to evaluate the seismic performance of RCC buildings resting on sloping ground. To achieve this objective, a Static Non-Linear Analysis, commonly known as Pushover Analysis, was carried out for building models with different ground slopes. Pushover Analysis is a method used to determine the potential seismic performance of a structure by subjecting it to a gradually increasing lateral load until it reaches a target displacement. This analysis helps in understanding the inelastic behaviour and collapse mechanisms of the structures under seismic loads. In addition to analysing buildings on sloping terrain, a comparative study was conducted between buildings on plain ground and those on sloping ground. The findings of this study indicate that the performance of buildings on plain surfaces is superior to those on sloping ground. The primary reason for this is the uniform distribution of forces and the absence of additional stresses caused by the slope. Among the various configurations of buildings on sloping ground, the study found that buildings constructed in a step-by-step back arrangement exhibit better consistency in seismic performance compared to other configurations. This arrangement helps in distributing the forces more evenly and reduces the occurrence of short columns, which are prone to early hinge mechanisms. As the slope angle increases, the formation of hinge mechanisms occurs earlier in short columns due to the increased stress and force concentration. This early hinge formation can lead to a significant reduction in the structural integrity and seismic performance of the building. In conclusion, the study underscores the importance of careful consideration of slope angles and building configurations in the design of RCC buildings on sloping terrain. By employing appropriate design strategies and conducting thorough seismic performance evaluations, the resilience of buildings in earthquake-prone regions like Nepal can be significantly enhanced.

DOI: 10.61137/ijsret.vol.10.issue4.196

Assessment of Corrosion Related Durability Properties for Concrete Containing Lime-stone Powder
Authors:-Scholar Amit Kumar, Professor Dr. P. K. Sharma

Abstract-The utilization of SCMs in the construction industry has increased tremendously. There is a lot of potential for usage of fly ash, RHA and LP in concrete. However, the characterization of blending quaternary cement is not much established due to lack of systematic study and limited availability of data. Further investigations have to be carried out regarding cracking, creep, temperature development and deformation. The use of the SCMs in road works and bridge approaches could be investigated further, as it has a high potential due to huge consumption. Furthermore, an investigation on the pore structure of the quaternary mix, other properties that affect durability such as gas permeability, freeze-thaw resistance, etc. and a study correlating the ponding tests with RCPT results for the quaternary mix may be another avenue to explore.

Departmental Library Oasis
Authors:-Tanveer Singh Deve, Professor Chanchal Bansal

Abstract-This research paper explores the implementation of an online library system within university departments to enhance access and efficiency. The paper investigates the existing challenges in traditional library systems and demonstrates how technological advancements can address these challenges. It further outlines the benefits of an online library system and suggests a comprehensive implementation strategy. With new patterns of information provision, new technology and changing financial circumstances, it is critical to gain new thinking across the profession. The Latest research, innovative theory and best organizational practice are all presented in Library Management System. Library Management System website which is used to supply the books to the user. This is done through JAVA technologies.

Enhancing Oral Proficiency through Computer-Assisted Language Learning: A Quasi-Experimental Study
Authors:-Imad Hamdanat

Abstract-This study investigated the impact of computer-assisted learning (CAL) on Moroccan high school students’ speaking skills. A quasi-experimental design compared a group exposed to ten sessions of CAL-enhanced instruction, featuring short videos of real-world English language situations, with a control group receiving traditional instruction. Data were collected through pre- and post-tests assessing speaking proficiency. Results indicated significant improvements in speaking skills for both groups, with the experimental group demonstrating substantially greater gains as evidenced by a significant difference in post-test scores (t(85) = -12.786, p < .001). These findings suggest that CAL, particularly when integrated with authentic language exposure, can be an effective tool for enhancing oral language development in high school students. The study holds significant implications for teachers, curriculum designers, and educational stakeholders in Morocco, underscoring the potential of CAL to transform language education.

DOI: 10.61137/ijsret.vol.10.issue4.197

A Study on National Education Policy 2020 Influenced to Industry 5.0
Authors:-Mr.K.Ponnumani, Jenifer.A

Abstract-This study explores the interaction between NEP 2020 and Industry 5.0, focusing on how educational reforms may provide the future workforce with the necessary skills and knowledge. It discusses the probable problems of implementing these reforms and proposes solutions to overcome them, providing that the educational system can effectively contribute to and profit from Industry 5.0 developments.

Review On Development and Application of Carbon Nanotube Reinforced Cement-Based Composites as Functional Building Materials
Authors:-Scholar Rahul Kumar, Asistant Professor Shaifali Sehgal

Abstract-Carbon-based nanomaterials (CNMs) have been extensively used to modify cement matrix thanks to their extraordinary specifc surface area, high aspect ratio, and high strength and modulus. This thesis focuses on the current status of research on CNMs modifed cement composites, especially the progress made in the past decade (from 2011 to 2021). At frst, the primary properties of typical CNMs used for manufacturing cement composites, the treatments used to efectively disperse CNMs in water and cement matrix, and the corresponding characterization methods are reviewed. And then, the efects of introducing CNMs on the properties of cement composites (both fresh and hardened) are also discussed in this work.

Exploring the Role of Bioinformatics Data Analysis in Nutrigenomics Research: A Comprehensive Omics Study
Authors:-Vinay Kumar Singh

Abstract-Nutrigenomics is the field of study that examines how individual genetic variations can affect a person’s response to the foods they consume. With the advent of high-throughput sequencing technologies, there has been an explosion of genomic data available for researchers to study the relationship between diet, genetics, and health. Bioinformatics data analysis plays a crucial role in organizing, processing, and interpreting this vast amount of genomic information. In this review, we will explore the role of bioinformatics data analysis in nutrigenomics research, focusing on various techniques and tools that are commonly used in the field.

Machine Learning Applications in Modern Agricultural Science
Authors:-Angshu Kumar Sinha, Sanchita Sarkar, Liza, Rohit Mondal, Amit Kumar, Amisha Gupta

Abstract-Cultivating land and raising crops for human use and consumption is known as agriculture. It contributes significantly to human well-being by offering food and other resources for survival and economic growth. As a result, improving this sector can improve people’s daily lives. We can use a range of machine learning strategies—a branch of artificial intelligence.

Advancements in Software Engineering through Artificial Intelligence
Authors:-Michael Müller

Abstract-The integration of artificial intelligence (AI) into software engineering represents a significant advancement, poised to transform traditional development processes. This research paper explores the multifaceted impact of AI on software engineering, with a focus on its applications, challenges, and future opportunities. Current applications include AI-driven coding, automated software testing, and intelligent maintenance systems. Despite these advancements, challenges such as data quality, AI model explainability, and integration with existing systems persist. Through a comprehensive methodology involving comparative analysis and case studies, particularly within the healthcare sector, this study highlights the practical benefits and limitations of AI in software development. The implementation of AI-powered software in healthcare, specifically for pulmonary embolism assessment, demonstrates a notable decrease in assessment time and in-hospital mortality rates, emphasizing the potential for AI to enhance clinical outcomes. The paper also examines AI’s role in the software development lifecycle, including automated code generation, AI-driven testing, and proactive maintenance. Addressing the challenges of data availability, trust in AI models, and organizational integration is critical for leveraging AI’s full potential. Future research directions suggest a move towards intelligent design assistants, self-healing systems, and proactive defect detection. This paper concludes that while AI offers transformative potential, its successful integration requires addressing significant challenges, advocating for a synergistic approach where AI augments human developers to revolutionize software engineering practices.

Speech to Sign Language Converter
Authors:-Linu Joy, Midhuna Eldho, Meera Ajith, Professor Chinnu Mariya Varghese

Abstract-This research presents an innovative communication system designed for individuals with hearing impairments. The initial phase involves precise conversion of spoken messages into text through advanced speech-to-text algorithms. Subsequently, natural language processing techniques are employed to translate this textual data into dynamic and expressive Indian Sign Language (ISL) representations. A distinctive feature of our system is the strategic integration of Google APIs, which dynamically associates relevant images with the ISL output. This integration contributes to a richer visual context, enhancing the comprehensiveness of communication. In addition, the proposed system incorporates emotion recognition algorithms to analyze the emotional content within spoken input. These algorithms seamlessly embed nuanced emotional cues into the ISL representation, fostering a more authentic and expressive mode of communication. Ensuring accessibility and customization, the user interface is designed to be user-friendly for both deaf and non-deaf users. Privacy and ethical considerations are integral to the technical implementation, ensuring secure data handling. The methodology emphasizes an iterative development process driven by extensive user testing and feedback. This approach aims to continually refine the system, improving both functionality and user experience. Ultimately, this research contributes to advancing assistive technologies, addressing communication barriers, and fostering inclusivity for individuals with hearing impairments.

Foreseeing Maximum and Minimum Temperatures by Integrating Several Machine Learning Programs While Assessing Their Performance
Authors:-Pintu Pal, Deblina Banerjee, Subhodeep Moitra

Abstract-Global warming has led to a boost in both optimum and minima temperatures. So, in this situation, precise prediction of maximum and minimum temperatures plays a very pivotal role in studying various factors related to human comfort, agriculture, ecological and environmental developments, and other causes. We investigated the effectiveness and varied capabilities of data-driven algorithms to anticipate the maximum and lowest temperatures of the third day in accordance with the meteorological situations of the preceding two days in a row.

DOI: 10.61137/ijsret.vol.10.issue4.198

Drones and the Law: Navigating Privacy, Airspace Regulations, and Liability Issues
Authors:-Assistant Professor Dr. Sharmilesh Trivedi

Abstract-This paper examines the lawful difficulties encompassing robots also known as Drones, zeroing in on security, airspace guidelines, and obligation issues. As robot innovation propels and turns out to be more inescapable, existing lawful systems battle to keep pace. This study utilizes a blended techniques approach, including writing survey, contextual investigations, and master interviews, to investigate the viability of current regulations and propose important changes. Discoveries uncover critical holes in security assurance, deficient airspace the executives, and hazy obligation rules. Proposals incorporate refreshing security guidelines, further developing airspace control frameworks, and explaining risk systems to upgrade lawful clearness and guarantee more secure robot tasks.

Digital Twin Technology: A Comprehensive Review
Authors:-Malithi R. Abayadeera, G.U. Ganegoda

Abstract-This review explores Digital Twin technology’s evolution since 2003, beyond replicating physical entities to encompass data ecosystems and service relationships. Analyzing its inception, growth, and multifaceted uses, the review illuminates Digital Twins’ transformative role in modern sectors. It delves into their impact on manufacturing, healthcare, smart cities, defence, agriculture, and utilities, showcasing their ability to enhance decision-making and operational efficiencies. Yet, significant obstacles hinder Digital Twin adoption, including IT infrastructure establishment, data quality assurance, privacy concerns, and ethical implications. These challenges obstruct the full realization of Digital Twins’ potential benefits. The study concludes by outlining critical avenues for future research, emphasizing standardization, data quality, privacy preservation, trust-building, and cross-domain applications. Bridging these gaps is vital for harnessing the true potential of Digital Twins in revolutionizing industries. This review aims to present a comprehensive view of Digital Twins, highlighting their benefits, challenges, and the imperative for further research to unlock their transformative impact.

DOI: 10.61137/ijsret.vol.10.issue4.199

Impact of AI-Driven Predictive Policing on Crime Rates and Civil Liberties: An Empirical Analysis
Authors:-Dr. Rinku M. Darji

Abstract-This paper investigates the effect of artificial intelligence driven prescient policing on crime percentages, public security, and common freedoms. Utilizing true information from purviews that carry out prescient policing apparatuses, this concentrate experimentally surveys the adequacy of these advances in diminishing wrongdoing and their suggestions for individual opportunities. The investigation uncovers nuanced impacts on crime percentages and features huge worries with respect to security and likely predispositions. Suggestions are accommodated offsetting mechanical advantages with the insurance of common freedoms.

A Review of Deep Learning Models for Enhanced Violence Recognition in Modern Surveillance Systems
Authors:-Research Scholar Anand, Assistant Professor Vikas Kamle

Abstract-The growing demand for effective violence detection in public spaces has led to significant advancements in surveillance technologies. This review paper explores the role of deep learning models in enhancing violence recognition within modern surveillance systems. By analyzing various deep learning techniques, including Convolutional Neural Networks (CNNs), and hybrid models, this paper highlights their effectiveness in detecting and classifying violent behaviors in real-time. The review discusses the strengths and limitations of different models, the impact of data quality and preprocessing, and the challenges posed by diverse environmental conditions. Additionally, it examines the use of large-scale datasets, performance metrics, and the potential for integrating multimodal data to improve recognition accuracy. This comprehensive analysis aims to provide insights into current trends and future directions in the field, contributing to the development of more reliable and scalable violence recognition systems in automated surveillance.

A Review of Unsupervised Machine Learning Approaches for Analyzing 5G Quality of Service
Authors:-Research Scholar Vishal Kaleshriya, Assistant Professor Vikas Kalme

Abstract-The purpose of this research is to examine how different machine learning models may be used to analyze 5G QoS. Optimal quality of service assurance is of utmost importance now that 5G technology is here. Throughput, latency, and jitter are some of the quality of service metrics that are clustered in this study using K-Means. In order to find patterns in the dataset, Principal Component Analysis (PCA) is used for standardization and visualization. Metrics including silhouette score, mean squared error, and Davies-Bouldin index are used to assess the efficacy of the clustering model. To round up the evaluation, we calculate classification measures such as recall, accuracy, precision, and F1 score. The results provide important information for optimizing and managing 5G networks, and they demonstrate that machine learning models are effective in improving the QoS of these networks. Research on the use of advanced analytics for next-generation telecoms may build upon the findings of this study.

A Review of Exploring Advanced Methods for Brain Tumor Detection and Segmentation with a Focus on the EfficientNetB3 Architecture
Authors:-Research Scholar Rashmi Jaiswal, Assistant Professor Vikas Kamle

Abstract-Brain tumor segmentation and detection are critical tasks in medical imaging, essential for accurate diagnosis and treatment planning. This study explores the application of the EfficientNetB3 architecture in enhancing the precision and efficiency of these tasks. EfficientNetB3, known for its balance between performance and computational efficiency, is evaluated for its ability to accurately segment and detect brain tumors from MRI scans. The study compares EfficientNetB3’s performance with other existing models, highlighting its strengths in terms of accuracy, speed, and resource utilization. Key challenges in brain tumor segmentation, such as varying tumor sizes and shapes, are addressed, and the model’s robustness in handling these challenges is assessed. The results demonstrate that EfficientNetB3 provides a reliable and effective solution for brain tumor segmentation and detection, offering significant improvements in medical image analysis. This research contributes to the growing body of knowledge on the use of advanced deep learning architectures in medical imaging, particularly in the context of brain tumor detection.

A Detailed Review of Load Balancing Techniques in Cloud Computing
Authors:-Research Scholar Mahendra, Assistant Professor Deepshikha Joshi

Abstract-Cloud registration provides users with access to a wide range of resources and facilitates information exchange. Clients are billed only for the resources they actually use. Cloud computing, which stores data in the cloud, maintains assets and information in a public domain. The level of information accumulation rises rapidly in open environments. Similarly, load balancing is a critical challenge in cloud computing. Load balancing involves distributing the dynamic workload across multiple nodes to prevent any single node from becoming overburdened. This process ensures that resources are used efficiently and enhances the overall performance of the system. Many current algorithms offer improved resource utilization and load balancing. In cloud computing, various types of loads, such as memory, CPU, and network loads, can be managed. Load balancing involves identifying overloaded nodes and transferring the excess load to underloaded nodes.

Review of Exploring Deep Learning Approaches for Effective Gender Identification in Face Images
Authors:-Research Scholar Abhishek Gupta, Assistant Professor Vikas Kamle

Abstract-Gender categorization has garnered significant attention in recent times due to the wealth of information it provides regarding the social activities associated with males and females. Obtaining distinct visual features for gender categorization, particularly with facial images, is a challenging task. Gender categorization is the act of ascertaining an individual’s gender by evaluating their physical characteristics. The increasing popularity of automatic gender categorization is attributed to the rich information that genders provide about male and female social behaviors. Recently, the importance of categorization has grown significantly across several disciplines. In a traditional community, a gender categorization system may be used for several purposes, including in safe environments. It is crucial to determine the gender type, particularly in sensitive regions, in order to prevent radicals from accessing secure locations. Moreover, this approach is used in circumstances when women are separated, such as in female train compartments, gender-targeted advertising, and religious sanctuaries.

A Routing Protocol Design and Enhancement Using Modified Clustering Technique
Authors:-Ayan Shah, Professor Amit Thakur

Abstract-With the huge uses of the sensors networks it is expected to significantly increase dense deployment in next generation future networks. It is the high time to evaluate and he performance of the dense wireless IOT networks. HEED based routing protocols have proven good enough for the routing protocols. It is required to enhance the Energy Efficiency (EE) of clustering based routing protocols. This synopsis proposed to design the optimum parameters based modified HEED routing protocol for the sensors network. The ratio of deployment is scaled by around 200 % for the evaluation of performance. Based on the deployment the optimum network design parameters are experimentally varied to achieve the improved lifetime performance. The number of packets transmission and cluster head counts are used as parameters for performance evaluation.

Application of (Omron) NS10 Pt NS- Designer Ver.3 to Control and Monitor An Automatic Bottle Capping and Tightening System
Authors:-VO PHU VINH
DOI: <a href="10.61137/ijsret.book.9.2024.101

Revolutionizing Web Development – The React Framework
Authors:-Vaishnavi Devi Talluri

Abstract-This abstract provides a structured approach for beginners to master React.js, focusing on fundamental concepts, intermediate techniques, and advanced features. It guides you through setting up your development environment, understanding core principles like JSX, components, and state management, and progressing to more complex topics. Whether you are just starting out or looking to deepen your knowledge, this guide will help you build robust and efficient React applications.

Survey of Generative AI in Code Generation: Privacy, Security and Ethical Considerations
Authors:-Jibin Rajan Varghese, Divya Susan Thomas

Abstract-Generative Artificial Intelligence (Gen-AI) models for code generation have emerged as transformative tools in software development, offering unprecedented productivity gains and democratizing access to programming. However, these advancements come with significant privacy and security implications that require careful consideration. Here, we present a comprehensive analysis of the current state of AI-powered code generation, examining the capabilities and limitations of leading models such as GitHub Copilot, OpenAI’s Codex, and Google’s AlphaCode. Our survey outlines critical privacy concerns, including potential leakage of sensitive information, inadvertent exposure of proprietary code, and security vulnerabilities in both the AI models and their generated code. We also outline key mitigation strategies, including enhanced data sanitization techniques, adversarial training methods, and novel approaches to model interpretability. Our findings suggest that while AI-assisted coding holds immense promise, its integration into software development practices necessitates a nuanced approach that balances innovation with robust privacy and security measures. This survey provides a foundation for future research directions and emphasizes the need for interdisciplinary collaboration to address the complex challenges at the intersection of AI, software engineering, and cybersecurity.

Optical Characterizations of White Light Producing Sr3Al10SiO20:Dy3+ Phosphor
Authors:-Shweta S. Sharma, Nameeta Brahme, D. P. Bisen, Shilpa G. Vidhale, Girish S. Mendhe

Abstract-New efficient luminescent Sr3Al10SiO20:Dy3+ phosphor was successfully synthesized by traditional high temperature solid state reaction method at 1300 ᴼC. Phase study of phosphor was done by powder X-ray diffraction (XRD) analysis. XRD pattern confirmed monoclinic phase of Sr3Al10SiO20:Dy3+ phosphor having space group C2/m. From the Debye-Scherrer equation, average crystallite size was determined for most intense plane. Thermoluminescence (TL) characterization of UV-exposed Sr3Al10SiO20:Dy3+ phosphor was recorded. Glow curve was analysed using peak shape method. Photoluminescence behaviour of Sr3Al10SiO20:Dy3+ phosphor was examined. When the phosphor was excited by 350 nm it showed two emission bands at 483 nm (blue) and 575 nm (yellow) associated with the transition to 4F9/2 → 6H15/2, 13/2 of Dy3+ ions. CIE co-ordinates were calculated and observed in white light zone. This paper concludes that Sr3Al10SiO20:Dy3+ phosphor may be suitable for white lighting in outdoor illumination.

Dnssec on Mi-Lxc
Authors:-Raquel Fabiani Touoyem

Abstract-As part of the Specialized Master in Cybersecurity for Operators of Essential Services providers, learners are required to carry out research and restitution work around a theme consistent with their teaching. It is in this perspective that we were offered DNSSEC on MI-LXC, which is a project whose objectives are initially to master the theoretical aspects around the implementation of DNS and DNSSEC, and to understand MI-LXC, which is above all a learning project simulating a mini-internet with all basic associated protocols, based on Linux containers. It will then come down to implementing DNSSEC through the main steps of key generation and zone signing, zone distribution, record validation and key and signature maintenance. It was also important in the context of this project to understand the problems introduced by the implementation of DNSSEC today, as well as the various attacks on the DNS which constitute the limit of DNSSEC. We have therefore carried out work in line with these main objectives, and this report is a restitution thereof. Throughout this project, we made an effort to convey in concise and precise terms our understanding of the various components and structure of DNSSEC under MI-LXC. The last parts allowed us to understand how DNSSEC was the solution for various attacks on the DNS, in this case cache poisoning. We have also explored the limits of DNSSEC and its implementation, and we have proposed additional security protocols which, coupled with DNSSEC, would make it possible to satisfy the objectives of Confidentiality and Integrity of DNS data, in order to make this Internet cornerstone protocol safer.

DOI: 10.61137/ijsret.vol.10.issue4.201

Influence of Textile Reinforcement on the Thermal Behavior of Steel Reinforced Concrete: Experimental Investigation
Authors:-Alak Kumar Patra

Abstract-Thermal behavior of conventional steel reinforced concrete with embedded glass (GF) and carbon fibers (CF) are experimentally studied at elevated temperatures after 7 days curing under water. The compressive strengths for M20 and M30 grades of concretes with and without fiber reinforcements have been determined at room temperature (27°C). The flexural strengths of prismatic M20 and M30 concrete specimens without any reinforcement and with GF as well as CF have been determined at 60°C and 80°C respectively. Similarly flexural strengths of prismatic M20 and M30 steel reinforced specimens with GF and CF were tested to determine their flexural strengths. Results indicate that the compressive strength of both the M20 and M30 concretes were least for specimens without fibers, maximum for specimens with CF and the compressive strength of GF reinforced cubes were in between the compressive strengths with CF and without any fibers. At 60°C, the flexural strengths of M20 and M30 concrete were observed to be least for conventional samples, maximum for concretes with CF and flexural strengths of samples with GF was slightly less than that with CF. Though the flexural strengths were significantly improved for both the fiber reinforcements, there were no significant change in that for GF or CF reinforcements. The flexural strengths of concrete with steel rebars additionally reinforced with CF and GF show overall improvement in flexural strengths in all cases along with the nature of variation similar to that without steel rebars. The nature of variation for specimens with and without fibers or steel rebars follow same pattern as that at 80°C but with lesser values in all the cases. Which indicates that these variations should be taken into account for design and construction of fiber reinforced concrete with steel rebars facing high temperature variations.

DOI: 10.61137/ijsret.vol.10.issue4.202

Method to Solve Non-Linear Programming Problems With two or More Inequality Constraints
Authors:-Nitish Kumar Bharadwaj

Abstract-In this paper, I’ve discussed the nonlinear programming problem with more than one inequality constraint and its method. Nonlinear programming (NLP) is the method to solve an optimization problem where some of the constraints or the objective function is nonlinear. In this paper, I have also discussed the application of Lagrange’s multipliers together with Karush Kuhn Tucker’s condition to solve nonlinear programming problems. An optimization problem is the problem that is the calculation of extrema (maxima, minima, or saddle points) of an objective function over a set of unknown real variables and conditions to the satisfaction of a system of equalities and inequalities, collectively termed constraints.[1] It is the subfield of mathematical optimization that deals with nonlinear programming problems.

Haematological and Biochemical Indices of Yankasa Rams Fed Maize Stover Supplemented with Molasses-Urea Block
Authors:-Adamu. B, Abdullahi. S, Surayya. A, Usman. K. A. U Dapellum

Abstract-The research was carried out to determine the hematological and biochemical indices of Yankasa rams fed maize Stover supplemented with molasses–urea block. Results of this experiment revealed that PCV, RBC, WBC, HBC, MCH, MCHC, MCV, Lymphocytes, Neutrophils, Monocytes were significantly (P<0.05) influenced by the dietary fed and. were significantly affected (P<0.05) by the level of inclusion of urea-mineral block in the diets. Moreover, for biochemical parameters, Lymphocytes, Neutrophils, Monocytes were significantly affected (P<0.05) by the level of inclusion of urea-molasses block in the diets. it can be concluded that the hematological and biochemical parameters for sheep studied in this experiment fall within the recommended values. Therefore, this study recommends that urea-molasses could be incorporated into the sheep diet up to 50% as replacement level without any health challenge. Generally, the hematological variables of the sheep fed Maize Stover ration supplemented with urea-mineral block were higher than those fed control diet. Based on the performance indices, Nitrogen utilization and the digestibility coefficient with supplemental use of urea-mineral block in feedlot of sheep offered tremendous potentials for increased mutton production in the Sub-Sahara region.

Trends of Renewable Energy Stocks in the era of Viksit & Aatmanirbhar Bharat
Authors:-Research Scholar Ms. Versha Gupta, Assistant Professor Dr. Neetu Jindal

Abstract-In this turbulent phase of climate issues and geopolitical tension, a move towards long-term clean and secure energy alternative is becoming one of the major societal concerns of the 21st century. Government of India’s movement of Viksit & Aatmanirbhar Bharat to make the country independent and self-sufficient is on boom. The Sustainable Development Goal 7 (SDG7) calls “India for an affordable, sustainable, reliable and modern energy for everyone” by year 2030, Self-sufficiency in energy production, an energy independent nation by 2047 & Net-zero carbon emissions targets by 2070 staggering the renewable energy companies’ growth. Indian Government’s established a set of programs, incentives, investments, schemes & policies, 100 % FDI permit, etc. to accelerate the expansion of new green. This transition is giving a new wave to the Green and Renewable energy stocks and make the green energy segment multibagger stocks. Where, India is meeting its 43% energy (about 181 GW) from renewable energy sources in 2024, the targets call India to generate 450-500 GW renewable energy by year 2030. India is running the vast opportunity of renewable energy expansion in the world and thus its stocks too. The objective of this study is to present the trends of Green and Renewable Energy stocks, when the whole world is running for green & sustainability. The present paper highlights the Governments role in promoting the green & renewable energy and its relative impact on best performing Indian Energy companies.

DOI: 10.61137/ijsret.vol.10.issue4.204

Effective Techniques for Generative AI Precision
Authors:-Sachin Vighe

Abstract-Generative AI systems have demonstrated remarkable capabilities in various domains, such as natural language processing and image and audio generation, yet achieving high precision and accuracy in these systems remains challenging. This paper comprehensively reviews effective techniques for enhancing generative AI precision, focusing on three key areas: data preparation, model architecture optimization, and fine-tuning strategies. We explore advanced data curation, synthetic data generation, and data augmentation methods that improve model accuracy. For model architecture optimization, we examine recent advancements in attention mechanisms, hierarchical structures, and multi-modal integration that promise increased precision. Fine-tuning strategies analyzed include few-shot learning, continual learning, and domain-specific adaptation. Additionally, I will discuss novel framework for evaluating and benchmarking generative AI precision, offering researchers and practitioners a standardized approach for assessing improvements. Case studies and empirical evidence demonstrate these techniques’ efficacy across various generative AI applications. My findings underscore the importance of a holistic approach to precision enhancement, combining multiple strategies for optimal results, contributing to efforts to make generative AI systems more reliable, accurate, and trustworthy.

DOI: 10.61137/ijsret.vol.10.issue4.203

Efficiently Identifying and Removing Empty Div Elements for Web Page Performance Optimization
Authors:-Sait Yalcin

Abstract-In modern web development, maintaining a clean and efficient Document Object Model (DOM) is crucial for optimal performance and user experience. This paper presents a novel approach to the removal of empty `div` elements from web pages. The method not only removes elements that are devoid of child nodes but also accounts for `div` elements containing only whitespace or empty text nodes. This refined technique ensures a more comprehensive cleanup, which can lead to improved page rendering times and reduced memory usage. The proposed function, implemented in JavaScript, has been tested and shown to outperform basic methods in various scenarios.

DOI: 10.61137/ijsret.vol.10.issue4.205

Impact of AI-Powered Investment Algorithms on Market Efficiency
Authors:-RB Nitish Kumar

Abstract-The integration of artificial intelligence (AI) into investment strategies has transformed financial markets by enhancing trading algorithms and decision-making processes. This research paper explores the impact of AI-powered investment algorithms on market efficiency, focusing on how these advanced technologies influence the speed, accuracy, and stability of financial markets. AI algorithms, including machine learning and deep learning models, have the potential to process vast amounts of data at unprecedented speeds, leading to more precise market predictions and trading decisions. However, the rapid adoption of AI also raises concerns about market volatility and the potential for new forms of systemic risk. This study evaluates empirical evidence on the performance of AI-driven trading systems, comparing their impact on market efficiency with traditional investment methods. Additionally, it addresses regulatory and ethical considerations related to the deployment of AI in finance. The findings aim to provide insights into the benefits and challenges of AI in investment strategies and its implications for future market dynamics and financial stability.

DOI: 10.61137/ijsret.vol.10.issue4.206

The Interval Valued Fuzzy Graph of the Cyclic Group
Authors:-N. Naga Maruthi Kumari, Sharada Venkatachalam

Abstract-In this paper, the graph whose nodes and edges have membership values as an interval of the system of Real numbers, called as interval valued fuzzy graph (IVFG) corresponding to the original prime graph based on the inverse of the elements of the Cyclic group was constructed and analyze various properties. The edges of the IVFG corresponding to the Original Prime graph can be determined if the Inverse of the element in a group is identified. We proved few theorems and some results, which are carrying over to construct IVFG.

An Analyze the Trends for GST Revenue Collection in Uttar Pradesh
Authors:-Research Scholar Mani Shanker Lal Dwivedi, Assistant Professor Dr. Nancy Gupta

Abstract-GST is an Indirect Tax which has replaced many Indirect Taxes in India. The Goods and Service Tax Act was passed in the Parliament on 29th March 2017. The Act came into effect on 1st July 2017; Goods & Services Tax Law in India is a comprehensive, Multi- stage, destination-based tax that is levied on every value addition. In simple words, Goods and Service Tax (GST) is an indirect tax levied on the supply of goods and services. This law has replaced many indirect tax laws that previously existed in India. GST is one indirect tax for the entire country. This article deals with Analysis of GST Collection of India.

DOI: 10.61137/ijsret.vol.10.issue4.208

Detection of Landuse Land Cover Changes by using Maximum Likelihood Algorithm Application on Landsat Satellite Images
Authors:-Priyanka Gupta, Sharda Haryani, V.B. Gupta

Abstract-The identification of the LULC classes for the Mandsaur district Madhya Pradesh, India is the main objective of this research. The satellite images used in the analysis. Based on pixel-by-pixel supervised categorization of Landsat satellite images taken between 2003 and 2023 using the Arc-GIS tool across 20 year period, the work makes use of maximum likelihood approach. Various classifications of land use and land cover features are considered to predict overall changes, including populated areas, water bodies, agricultural land, forests and desert terrain. Landsat 8 photos from 2023 and remotely sensed Landsat 5 images from 2003 were used to detect changes inorder to accomplish this goal. The five LULC classes for the Mandsaur region are explained in this paper. The maximum likelihood algorithm is used in this work to compare the LULC classes for the Mandsaur region. The validation of the results for the supervised classification using MLC yielded kappa coefficients of 0.8263 and 0.7841 for 2023 and 2003 respectively. Land cover classification should benefit greatly from the application of MLC algorithms.

DOI: 10.61137/ijsret.vol.10.issue4.209

Development and Implementation of Python Applications for 2d Geometry Learning
Authors:-By. Quyen Vo Truong Ngoc

Abstract-In the contemporary educational landscape, integrating technology with traditional learning methods has shown to enhance comprehension and engagement among students. This project explores the application of Python programming to facilitate the learning of 2D geometry. Python, known for its simplicity and powerful libraries, is utilized to create interactive tools and visual aids for understanding fundamental geometric concepts. This study details the development and implementation of a Python-based application designed to assist students in visualizing and computing various 2D geometric shapes, including points, lines, triangles, squares, and circles. The application leverages libraries such as Matplotlib, Pygame, and Turtle to render shapes and perform calculations related to area, perimeter, and other geometric properties. Preliminary results indicate that students using the application show improved understanding and retention of geometric principles compared to traditional methods. This paper discusses the methodology, key features of the application, and its potential impact on enhancing geometry education. Future directions include expanding the application’s capabilities and adapting it for different educational levels.

DOI: 10.61137/ijsret.vol.10.issue4.210

Fake Social Media Profile Detection: A Hybrid Approach Integrating Machine Learning and Deep Learning Techniques
Authors:-Anila S, Meenakshi Mohan, Mariya Jacob, Najiya Nasrin

Abstract-In the contemporary era of rapid information dissemination through social platforms, the proliferation of fake content undermines the trust and integrity of online communities. Existing detection algorithms exhibit limitations in terms of accuracy and adaptability, necessitating the creation of an innovative hybrid model. Our goal is to integrate the strengths of traditional machine learning approaches, such as k- Nearest Neighbors or Support Vector Machines, with the power of deep learning methods. By combining these techniques, we aim to enhance the accuracy and efficiency of fake profile detection beyond current state-of-the-art methods, providing a robust and effective solution for distinguishing between genuine and deceptive profiles in the dynamic landscape of social media.

DOI: 10.61137/ijsret.vol.10.issue4.211

Assistive Technology Application for Slow Learning Disabilities
Authors:-Research Scholar Mr. G. Shobanprabhu, Professor Dr. M. Kanmani

Abstract-This paper was written to expose the meaning, benefits, and answer why the use of assistive technology for children with learning disabilities. The paper discussed the various types of assistive technology devices that were designed and used to solve written language, reading, listening, memory and mathematic problems of children with learning disabilities. It pointed out the need for selecting the right technology tools for the children with learning disabilities, to enable achievement of the target goals, and highlighted instructional guides for the classroom teachers, that would make children with learning disabilities benefit maximally from the use of assistive technology tools, whether in the classroom or at home, in order that the technology would make the teaching – learning process enjoyable and productive. The possible challenges faced by developing nations in using assistive technology were mentioned. It concluded that there was potential for assistive technology to improve the lives and to eliminate learning difficulties for children with learning disabilities.

Assessing the Ecological and Socioeconomic Ramifications of Climate Change on Fisheries: A Scientific Review
Authors:-Scholar Soro Nabintou, Professor Dr Hitesh A. Solanki

Abstract-Climate change poses a significant and escalating threat to global ecosystems, with profound implications for the fisheries sector. This comprehensive review aims to elucidate the underlying causes and multifaceted consequences of climate change on fisheries. The impacts are categorized into three primary dimensions: physical, biological, and geographical transformations. Physical alterations encompass rising temperatures, changes in oxygen levels, ocean acidification, and shifts in salinity, all of which directly influence marine environments. Biological shifts manifest as species extinctions, morphological alterations, population declines, and heightened susceptibility to diseases among fish populations. Elevated temperatures exacerbate mortality rates and disrupt fundamental physiological processes. Geographical transformations disrupt fish habitats and alter the distribution patterns of various species, thereby reshaping marine ecosystems on a global scale. Through synthesizing the latest scientific evidence, this review underscores the urgent need for proactive measures to mitigate the adverse effects of climate change on fisheries, safeguarding both ecological integrity and socioeconomic stability.

DOI: 10.61137/ijsret.vol.10.issue4.212

Getting Around the Blockchain Technology Landscape: A Comprehensive Study of Risks and Solutions
Authors:-Vijay kumar

Abstract-Overview: The included report focuses into a number of areas of blockchain development, from the Bitcoin whitepaper to recent advances in growth, con- fidentiality, and consensus processes. It seeks to define blockchain architecture, investigate protocol improvements, solve important security issues, and debate blockchain integration with upcoming technologies such as the Internet of Things (IoT) Findings: Blockchain is built on decentralized peer-to- peer networks and cryptographic proofs, which provide trust and security without relying on a central authority. Ethereum and Hyperledger Fabric are protocols that ex- pand the capabilities of blockchain to smart contracts and corporate solutions. New consensus algorithms, such as Del- egated Proof-of-Stake and Bitcoin-NG, increase scalability and efficiency. Objectives: To demonstrate basic blockchain ideas like decentralization and cryptographic proofs. Investigate the evolution of blockchain protocols and consensus tech- niques. To examine significant security concerns and pri- vacy solutions in blockchain technology. To investigate the convergence of blockchain with IoT and its potential consequences. Results: Clarification of key blockchain ideas, with an emphasis on decentralization and cryptographic proofs. Insights on blockchain protocol and consensus mechanism improvements. A comprehensive review of security flaws and privacy remedies. Exploration of blockchain-IoT syn- ergies, emphasizing blockchain’s revolutionary influence on developing technologies.

DOI: 10.61137/ijsret.vol.10.issue4.213

Getting Around the Blockchain Technology Landscape: A Comprehensive Study of Risks and Solutions
Authors:-M.Tech Scholar Vikas Kumar Gupta, Professor Santosh Nagar, Professor Anurag Shrivastava

Abstract-Wireless sensor networks play a critical role in various applications, but they are vulnerable to attacks that can compromise network security and performance. One such attack is the DIO suppression attack, which targets the Routing Protocol for Low-Power and Lossy Networks (RPL). This research aims to analyze the impact of the DIO suppression attack on RPL and evaluate the effectiveness of the NLBGNDO algorithm in mitigating the attack. To achieve this objective, a simulation code is developed to accurately model the RPL protocol and incorporate the DIO suppression attack. The NLBGNDO algorithm, a proposed trustworthy and efficient routing algorithm for RPL, is integrated into the simulation code. Key metrics such as packet delivery ratio, path stretch, and power consumption are measured and analyzed under normal network conditions and during the attack. The results of the analysis provide insights into the vulnerabilities of RPL to the DIO suppression attack and the effectiveness of the NLBGNDO algorithm in mitigating its impact. The packet delivery ratio reveals the attack’s effect on the network’s ability to deliver data, while the path stretch metric indicates the efficiency of the routing algorithm under attack conditions.

Cosmic Rays and Space Weather Predictions: Exploring the Dynamic Universe
Authors:-Rajesh Kumar Mishra, Divyansh Mishra, Rekha Agarwal

Abstract-Cosmic rays are high-energy particles originating from various astrophysical sources such as supernovae, black holes, and active galactic nuclei. They travel through space at nearly the speed of light and can interact with magnetic fields and matter, including our atmosphere, as well as with spacecraft and satellites. Space weather prediction involves forecasting the conditions in space, including the behavior of cosmic rays, solar wind, and solar flares that can affect technology and human activities in space and on Earth. While cosmic rays are not directly influenced by solar activity, they can be modulated by the solar magnetic field and solar wind, which in turn are influenced by solar activity. Predicting space weather, including cosmic ray flux, involves monitoring solar activity, solar wind, and the interplanetary magnetic field. Ground-based observatories, satellites, and space probes play crucial roles in gathering data to understand the dynamics of space weather. Mathematical models are then used to forecast space weather conditions, including the intensity and flux of cosmic rays. However, predicting cosmic ray flux with high precision over short timescales remains challenging due to the complex interplay of various astrophysical and solar factors. While long-term trends and general patterns can be forecasted, short-term fluctuations are more difficult to predict accurately. Nonetheless, understanding cosmic rays and their relationship with space weather is crucial for protecting astronauts, satellites, and technological infrastructure in space, as well as for understanding the broader dynamics of our universe. Ongoing research and advancements in observational techniques and modeling are continuously improving our ability to predict space weather, including cosmic ray activity. Space weather refers to conditions on the Sun and in the solar wind, magnetosphere, ionosphere and thermosphere that can influence the performance and reliability of space born and ground based technological systems and endanger human life and health. In our days internet becomes one of the most important tools for researchers working in solar-terrestrial physics. There is a tight relation and mutual penetration of space weather and internet. Information updated every minute or even more frequently is provided by many tens of instruments for studies of different solar, interplanetary and geophysical effects. Cosmic rays, mostly the galactic cosmic rays, are a part of the interplanetary medium and the human environment and their variations reflect all large effects of the solar activity and solar wind disturbances. GOES satellites provide some information on solar cosmic-rays behavior in real time and possible magnetospheric effects. The worldwide network of ground based neutron-monitor stations can provide reliable and complete information on galactic cosmic ray variations for more than a 50-years time period. During the last six years the quality and the abilities of this network increased significantly since a new information system has been installed firstly in Moscow station (Mavromichalaki et al., 2001)[1]. Today a new real-time data collection system has been developed using the latest networking methods in order to achieve maximum data collection reliability through the best synchronization and expandability. The new IP-based network lays the foundation of a worldwide data collection system with the specification to join all neutron monitor stations in a common real-time network, capable of real-time data processing and forecasting. Cosmic rays are high-energy charged particles, predominantly protons and atomic nuclei, originating from various sources in the cosmos, including supernovae, black holes, and active galactic nuclei. They continuously bombard Earth’s atmosphere from all directions at nearly the speed of light. While they are fascinating phenomena, they also pose potential risks to both space and terrestrial systems, including spacecraft, satellites, and even human health. Space weather encompasses various phenomena, including solar flares, coronal mass ejections (CMEs), and cosmic rays. Understanding and predicting space weather is crucial for the safety and functionality of technological infrastructure both in space and on Earth. While solar activity dominates much of space weather, cosmic rays play a significant role, particularly in the realm of long-term effects on spacecraft and their electronics. One of the challenges in predicting space weather involving cosmic rays is the variability in cosmic ray flux due to factors such as solar activity, the Earth’s magnetic field, and even changes in the interstellar environment. Despite these challenges, significant progress has been made in recent years in modeling and forecasting space weather, including cosmic ray flux.

AI-Driven Digital Forensics
Authors:-Rohit Tahsildar Yadav

Abstract-The integration of Artificial Intelligence (AI) into digital forensics marks a significant advancement in the field, addressing the escalating complexity of cyber threats alongside the burgeoning volume of digital data. This paper provides an in-depth exploration of AI’s transformative impact on digital forensics, presenting a detailed analysis of its roles, advantages, and inherent challenges. It begins by exploring the fundamental aspects of AI technologies, such as machine learning and deep learning, and their critical relevance to digital forensic investigations. The discussion emphasizes AI’s capabilities in analyzing vast datasets, identifying complex patterns, and automating repetitive tasks, underscoring its potential to enhance traditional forensic methods and improve investigative outcomes. The paper further investigates various applications of AI within digital forensics, including malware detection, data recovery, and network traffic analysis, demonstrating how these technologies facilitate more efficient and accurate forensic processes. However, despite these advancements, the adoption of AI presents several challenges, such as algorithmic bias, ethical concerns, and issues related to the interpretability of AI models, which could affect the fairness and reliability of forensic conclusions. To provide practical insights, case studies are incorporated, illustrating the implementation of AI-driven solutions in real-world scenarios, and highlighting both the successes and limitations observed in current forensic practices. Additionally, the paper anticipates future developments, considering the potential implications of emerging technologies like quantum computing and advancements in neural network architectures on the evolution of digital forensics. By synthesizing findings from recent literature and case studies, this paper aims to present a balanced view of the capabilities and limitations of AI in digital forensics. It emphasizes the need for ongoing research to overcome existing challenges and fully realize the benefits of AI technologies in enhancing the effectiveness and reliability of forensic investigations.

Nonlinear Analysis of High-Rise Reinforced Concrete Buildings with Different Structural System and Floor Systems Using Fiber Model in Time History
Authors:-Rıza Torkan, Professor Dr. Mustafa Karaşahin, Professor Dr. Reha Artan, Professor Dr. Turgut Öztürk

Abstract-In order to ensure the safety of structures against earthquakes, it is stated that a structural system that takes into account nonlinear behavior should be installed. This is an approach mandated by TBDY2018, especially for tall buildings. Nonlinear behavior is important to ensure that structures behave realistically under earthquakes. This requires a detailed analysis of the structures to account for the elongation and shortening of the material fibers during an earthquake. These analyses are based on nonlinear solutions in terms of materials and geometry, taking into account second-order effects. Although nonlinear analysis is essential for realistic prediction of earthquake effects in tall buildings, comprehensive studies applying advanced nonlinear analysis techniques using Open Sees software to a large set of carefully selected earthquake records are lacking. Evaluation of the seismic performance of tall buildings in specific earthquake zones is not available. This study provides insights that previous studies have made more limited use of by uniquely combining advanced nonlinear analysis techniques in Open Sees with a total of 22 carefully selected earthquake records to provide a more accurate and realistic assessment of the performance of tall buildings in specific seismic zones by averaging these 22 earthquake records. The aim of this approach is to prevent loss of life and property by minimizing the destructive effects of earthquakes. Consideration of nonlinear behavior allows us to more realistically assess how structures will respond under real earthquakes. Thus, building design and assessment can be made safer.

DOI: 10.61137/ijsret.vol.10.issue4.216

Trend and Decomposition Analysis of Apple Production in Jammu and Kashmir
Authors:-Assistant Professor Dr. R. Angamuthu

Abstract-In this paper examines the trend and decomposition analysis of apple production in Jammu and Kashmir in India. Apple fruits production in the world stood at around 2.4 million metric tons in the year 2022-23, making India the fifth largest producer. In India level, the Area, 321.90 in thousand hectares in the beginning year, nosedived to 312.60 in thousand hectares during the year 2020-21. It is exhibited a negative trend upto the end year. At the same time, the growth was not at notable level to area for apple fruits in India over the period. (CAGR = -0.28, t = – 0.59, P < 0.10). On the other hand, it is understood from the table that the production and productivity of the apple fruits in India with average of 2326.94 in thousand million tonnes and 7.57 million tonnes / hectares have reached to 2275.80 in thousand million tonnes and 7.30 in million tonnes / hectares after testing at as high as 2814.30 thousand million tonnes and 9.10 million tonnes / hectares in 2019-20 from 2203.40 thousand million tonnes and 6.80 million tonnes / hectares in 2011-12 at significant compound rate of 1.69 per cent (CAGR = 1.69, t = 1.58, P < 0.10) and 2.04 per cent (CAGR = 2.04, t = 1.55, P < 0.10). From the inferences of these results, it is found that negative growth in area of apple fruits, but notable growth in production and productivity of apple fruits in India level. Apple production in the Jammu and Kashmir region experienced substantial growth, with a notable upward trend during the period under consideration.

DOI: 10.61137/ijsret.vol.10.issue4.217

A Review of Modeling and Design of Grid Dfig System in Matlab
Authors:-Sekdiya, Assistant Professor Raghunandan Singh Baghel

Abstract-Doubly Fed Induction Generator (DFIG)-based wind turbines have become increasingly popular in recent years due to their capacity to operate at varying speeds. Weaknesses in the DFIG system can arise from issues with the power grid due to the stator’s direct connection and the excitation converter’s power rating limitation. Under situations of unbalanced grid voltage, this study aims to explore the efficacy of the Direct Power Control (DPC) approach in managing wind turbine systems based on DFIG. Throughout the experimental investigation, we evaluated the system in standard and unbalanced grid voltage settings. MATLAB/SIMULINK simulations implement DPC, specifically tailored for a MW DFIG-based wind farm. The results of these simulations show that the changed control method effectively reduces torque oscillations by making it possible to create active and reactive power references for the rotor-side converter. This eliminates the requirement for sequence component excitation, which was previously necessary. Furthermore, the research highlights the intrinsic link between control techniques and grid circumstances, showing this connectivity’s crucial role in improving wind energy systems’ stability and operational efficiency based on DFIG.

Functional Planning, Analysis and Design of G+4 Sustainable Commercial Office Building in Large City Corporation Area under COVID-19 Situation
Authors:-Alak Kumar Patra, Amarjeet Chaudhary, Aman Pandey, Sivam Goswami

Abstract-The paper presents a novel functional planning and design aspect of a sustainable commercial multi storeyed building under COVID19 situation in a tropical country, India. India, the second largest populous and democratic country in the world has been affected by three consecutive waves of COVID 19 pandemic. Construction sector, the second largest industry of the country is the most seriously affected one. Under the situation closure and job scarcity for construction people has resulted in a recession in the country’s economy and danger to social survival. The functional planning of the office building of a medium sized construction firm is executed following minimum office space requirements for the officers of the engineering department per Govt. of India and modified per World Health Organization (WHO)’s regulation on COVID19 propagation. A specific example on the functional planning for commercial office building based on National Building Code (NBC) of India and Chennai Corporation building rules have been presented as a useful addition to literature on disaster resilience of a populated large city in a tropical country like India. Analyses and designs are executed by finite element software package for different load cases including seismic loading to make it useful for professional applications. Finally, the building is made sustainable per Sustainable Development Goal (SDG) Policy of the United Nations using energy efficient materials for power supply, for construction of non-load bearing members and green building concepts. These concepts are found to be useful for medium sized construction companies through making their office building functional during and after the pandemic situation in India and other countries like India also thereby mitigating the recession in economy of construction sector.

DOI: 10.61137/ijsret.vol.10.issue4.218

The Impact of Social Media on Mental Health among Young Adults
Authors:-Assistant Professor Dr. Puja Tripathi, Assistant Professor Mr. Gaurav Raghuvanshi

Abstract-This study investigates the impact of social media on the mental health of young adults aged 18-25. Utilizing a qualitative research approach, the study explores how social media usage influences both positive and negative mental health outcomes. Through in-depth interviews and thematic analysis, key factors such as social connection, support, social comparison, cyber bullying, and addiction were identified. The findings reveal a dual impact: while social media can foster a sense of community and provide access to mental health resources, it also contributes to anxiety, depression, and low self-esteem when usage is excessive or driven by negative comparisons. The study underscores the importance of promoting balanced and mindful social media use among young adults to enhance positive outcomes and mitigate adverse effects. Recommendations for healthier social media practices and directions for future research are also discussed.

DOI: 10.61137/ijsret.vol.10.issue4.219

Enhancing BERT for Question Answering with Token Transformation Networks
Authors:-Yoga Harshitha Duddukuri, Dr. Yugandhar Garapati

Abstract-This paper proposes an enhanced architecture to improve the accuracy of BERT models fine-tuned on the Stanford Question Answering Dataset (SQuAD). The presented approach introduces a Token Transformation Model designed to refine embedding, making them more effective for question answering tasks. Initially, the question and context inputs are tokenized using a BERT-large tokenizer. These tokens are then processed through the Token Transformation Model, which enhances the quality and relevance of the embedding. The refined embedding are subsequently utilized by a TinyBERT model that has been fine-tuned on SQuAD with knowledge distillation (KD) techniques. The proposed method aims to leverage the strengths of large-scale tokenization and advanced embedding transformations to achieve higher accuracy in question answering scenarios, offering a more precise and efficient solution. Experimental results demonstrate the effectiveness of this architecture in improving the performance of BERT models on SQuAD.

DOI: 10.61137/ijsret.vol.10.issue4.220

Real Time Biometrics Based Smart EVM with FPGA Implementation
Authors:-Akshay Prakash, Rahul M, Karthik Ramesh, Pranav K S, Associate Professor Dr. Poornima G

Abstract-In today’s rapidly evolving landscape, numerous techniques have emerged to improve voting systems, focusing on individual authentication and reducing malpractices. Recognizing each voter remains challenging, but advancements like a controller-based electronic voting machine using the R307 Fingerprint sensor for biometric authentication offer solutions. The proposed digital biometric-based EVM provides an efficient method for casting votes, implemented on an FPGA board using Verilog software on Xilinx ISE. This system ensures unique voter authentication and streamlines the voting process, demonstrating its capability to verify identities accurately and enhance the security of elections. As a result, it offers a reliable and secure solution for modern electoral processes. As a result, it offers a reliable and secure solution for modern electoral processes, improving voter confidence and reducing fraud. The implementation showcases a robust approach to addressing the shortcomings of traditional EVMs while maintaining the integrity of the electoral system.

DOI: 10.61137/ijsret.vol.10.issue4.221

AI Will Not Replace Human Workforce
Authors:-Aanand Kumar Sah

Abstract-This research paper explores the relationship between Artificial Intelligence (AI) and the human workforce, with a particular focus on the question of whether AI will replace human workers. The research is based on a thorough analysis of existing literature, as well as original insights and arguments. The key findings of the research are as follows:
• AI is designed to perform repetitive, mundane, and data-intensive tasks, freeing human workers to focus on more complex, creative, and high-value tasks.
• AI systems lack human intuition, empathy, and critical thinking skills, and are therefore unlikely to replace human workers in their entirety.
• Human workers bring a unique set of skills, experiences, and perspectives to the workplace, which are essential for innovation, problem-solving, and decision-making.
• AI will augment human capabilities, free workers from mundane tasks, and create new job opportunities, but it will not replace the human workforce.
The research methodology involved a thorough review of existing literature on the topic, as well as original analysis and argumentation. Key sources included academic articles, industry reports, and expert opinions. The research findings suggest that while AI will certainly change the nature of work, it will not replace the human workforce. Instead, AI will augment human capabilities, free workers from mundane tasks, and create new job opportunities. In conclusion, this research provides a comprehensive and nuanced analysis of the relationship between AI and the human workforce. By prioritizing human- centered design and ensuring that AI systems are transparent, explainable, and accountable, we can create a future where AI enhances human capabilities, rather than replacing them.

DOI: 10.61137/ijsret.vol.10.issue4.222

AI-Powered Video Analytics for Border Surveillance Using Drones
Authors:-Ashish Vijayeendra Kulkarni

Abstract-The use of drones in border surveillance has revolutionized the way security forces monitor and protect vast and remote areas. By incorporating AI-powered video analytics, this research presents a cutting-edge system that automates the process of detecting and analyzing real-time changes in border environments. The system compares live drone footage with archived data to identify potential threats or irregularities, thus reducing human error and enhancing security effectiveness. Leveraging advanced computer vision algorithms and machine learning models, this AI-driven approach significantly improves situational awareness and allows for quicker, more accurate responses to security breaches. This paper also discusses the challenges associated with environmental factors, drone autonomy, and the need for multi-modal sensor integration. Future research directions focus on improving prediction models and autonomous drone swarming.

White Research Paper for INRTether
Authors:-Mr. Deepak Singh

Abstract-INRTether is a proposed fiat-backed cryptocurrency pegged to the Indian Rupee (INR) in 1:1 (i.e., 1INRTether = ₹1). This paper aims to explore the feasibility and potential benefits of such a digital asset. We delve into the underlying technology, economic considerations, and regulatory implications of INRTether. By analyzing existing stablecoin models and the specific context of the Indian financial landscape, we assess the potential advantages and challenges of implementing INRTether. Our research contributes to the growing body of knowledge on cryptocurrencies and their potential role in financial systems, particularly in emerging economies.

DOI: 10.61137/ijsret.vol.10.issue4.223

Published by: vikaspatanker

Authors: Sudhir Vishnubhatla

Abstract: Information Management Systems (IMS) have historically operated in centralized architectures where ingestion, storage, and retrieval workflows were executed in tightly controlled environments. However, the rapid growth of digital documents in regulated domains such as finance, healthcare, and public archives demands real-time processing, semantic enrichment, and compliance-aware access. The emergence of Edge AI deploying lightweight intelligence at the data source—combined with hyperscale cloud services now offers a hybrid path forward. This article synthesizes research from 2000–2024, spanning early distributed file systems, service-oriented architectures, edge intelligence frameworks, and cloud-native analytics. We propose a layered architecture for real-time document understanding in IMS that leverages edge devices for low-latency inference while relying on the cloud for scalability, orchestration, and governance. Three illustrative figures demonstrate the evolution from reference edge-cloud topologies to optimized deployment pipelines, culminating in end-to-end IMS analytics integration.

DOI: http://doi.org/10.5281/zenodo.17452281

Published by: vikaspatanker

Review on to Design and Develop an Anti-Sleep Alarm for Drivers
Authors:-Ankit W Kolarkar, Nisha R Sontakke, Gaurav A Kukadkar, Yogilesh K Gujar, Professor Achal Kambale, Profssor Nutan Dhande, Profssor Abhishek K Singh

Abstract- The Worldwide, sleepiness and driver weariness play a major role in traffic accidents and fatalities. We have created an inventive Anti-Sleep Alarm system especially for drivers in order to solve this pressing problem. Advanced sensor technologies, and an intuitive design are combined by this system to efficiently identify and warn drivers when they are in danger of while operating a vehicle. The three main parts of the Anti Sleep Alarm system are an alert mechanism, and a design of the Anti-Sleep Alarm system user- friendliness, ensuring that it is easy to use, comfortable to wear, and non-intrusive during normal driving conditions. It offers customization options to adapt to individual driver preferences and sensitivities.

Towards Digital Transformation: Improving Hostel Accommodation through Software Innovation
Authors:-Assistant Professor Vikas Desai, Yash Chavhan, Tejas Patil, Savi Dhoble, Tushar Rathod, Chirag Shrigod

Abstract- In this fast-paced era where society is growing rapidly students and working professionals confronts blockade in various aspects like finding residence in metro cities, authenticity, software availability, and accessing information. These confrontations can significantly impact to their personal growth and social interaction leading to deterioration of quality of life. Through this study we present approach towards addressing this issue through development of software precisely designed for residence oriented with aspect of tenant and owner. The main objective of our project is to bridge the gap between tenants and owners through the digital way ensuring safety, security and avoid the problems when carried manually. System take input from student regarding the hostel and shows the relevant data like availability of rooms and number of people and etc. whereas it shows summary details of fees paid and authority to add, delete and edit details of person on administrator module. This proposed android app is designed to be error free, secure, reliable and fast booking system enabling the digital security and preventing wastage of time by means of user-friendly app and administrator module Key features of the project include users to get easy-to-use interface in order to sort, search, reserve room and services. Additionally, the system offers flexibility in terms of customization, allowing users to settings and preferences according to their specific needs. Through the development and implementation of this project we aim use of digital systems in manual work of hostel system in current world and increased transparency in the system from tenant and owner using security framework and administrator module of the software application by Software Development Life Cycle (SDLC) with PHP and XAMPP server. Successful implementation leads to use in different unorganised sectors for the noble cause.

Life Line: Redefining Blood-Bank Management in the Digital Age
Authors:-Mr. Assistant Professor Vikas Desai, Shreyas Patil, Prathvish Shetty, Nikhil Shinde, Piyush Takalkar, Ashirwad Swami, Harish Thube

Abstract- Lifeline is a web-based blood-bank management system, that is designed to facilitate the process of blood donation and transfusion. One of the major obstacles that is faced by almost all blood transfusion services is the engagement of the voluntary blood donors. This remains a critical issue as only 62 out of 193 WHO Member States, that accounts for only 32% of the countries, reported to have received more than 99% of their blood supply via VNRBD. The dependence on voluntary donors points up the need of effective strategies to encourage individuals to donate blood willingly and regularly to meet the demand for blood transfusions [1]. With the aim of addressing the critical need for a sustainable blood supply and automate the current manual system with the aid of fully functional computer software and computerised equipment, Lifeline provides a centralized platform for donors, recipients, and healthcare providers to connect and coordinate blood donation activities. Key features of Lifeline include user registration and profile creation, blood donation booking system, recipient blood request management, real-time notifications, and an interactive dashboard for donors and administrators. The system levels up the technology to improve donor interaction, improve operational efficiency, and ensure timely access to blood for patients in need. The primary goal is to automate its present manually relying system using computerised equipment and a full-fledged computer software to meet their demands, so that their valuable and exclusive data can be saved for a longer period of time with ease of access and manipulation. The system will help in the efficient management of blood donations and blood samples. The system will also allow for tracking of donor information, blood types, and inventory records. The aim of Lifeline is to raise awareness about the importance of blood donation and develop a culture of selflessness in the community by means of Community Awareness Campaigns.

Green Cloud Computing
Authors:-Pratima Mall, Assistant Professor Dr. Sunil Gupta

Abstract- The future of the IT industry is at a turning point and unless sustainable solutions are developed in the industry, this could be the end of the world. Data centers in the industry use most of the energy, and existing energy needs to be converted into green and clean energy. This study investigates the development of green cloud services and conducts a literature review to investigate the needs, impacts and trends of green cloud services. Analyzing features, issues and trends, this study shows that the future of IT will be deeply based on green energy. Research results show that the use of green cloud can be effective in improving the results of cloud computing and reducing its impact on the environment.

Developing an Integrated Framework for Ensuring Patient Privacy and Confidentiality in the Age of Social Media: A Case Study and Research Approach in the Healthcare Sector of India
Authors:-Sanika Satish Lad, Shifa Siraj Khan, Sanika Rajan Shete, Anant Singh, Devesh Amlesh Rai

Abstract- The rapid development of the use of communication technologies and social media among healthcare providers raises potential privacy issues for patients. Health Information can be easily transmitted using platforms like Facebook, Instagram, Twitter, Snapchat and TikTok that allow users to communicate electronically with friends and family all over the world. Thus, offering means of spreading sensitive healthcare information—as well as an easy way to compromise patient privacy. the purpose of this research is to shed light on how medical information shared on social media by healthcare providers poses risks to patient’s privacy in the India. To better explain and understand the research problem, both qualitative and quantitative methods were used. These include scientific facts, statistics, surveys, interviews, social media posts and studies conducted from 2000 to 2023. Also, all quantitative data used were taken from the existing literature done by other researchers. Before conducting the research, the expectations were to use primary data to better show the existing gap and explain the research problem. However, due to some limitations, many assumptions and analyses were made based on secondary data. This research paper will help healthcare professionals to improve in ways that are “privacy-respecting and privacy reinforcing.

DOI: 10.61137/ijsret.vol.10.issue3.160

The Proliferation of Individual House Builders (IHB) in the Raigad Districts
Authors:-Associate Professor Dr. Deepti Pande Rana

Abstract- This research extensively investigates the dynamic scenario of individual house builders (IHBs) in Raigad district, delving into the notable growth within the real estate sector and its affiliated industries. The primary focus lies on residential structures, encompassing a variety from bungalows to row houses and small individual buildings, tailored to accommodate diverse family configurations. The upswing in construction activities is ascribed to factors such as ample land availability, improved connectivity, burgeoning employment opportunities, urbanization trends, and the expanding middle class.Various approaches are employed for the construction of these dwellings, involving professional builders, contractors, self-development, or outsourcing. Raigad district, in particular, has experienced remarkable advancements in this domain, solidifying its status as a fertile ground for individual house builders. The synergistic effect of favorable conditions, including accessible land and enhanced connectivity, has led to a noteworthy surge in residential construction.The study adopts a descriptive analysis methodology to fulfill its objectives. By closely examining the challenges faced by individual home builders (IHBs) in Raigad district, the research aims to provide a comprehensive understanding of the impediments that could potentially hinder the sector’s growth. Concurrently, it investigates the growth trajectory of IHBs in the region, shedding light on the factors contributing to their success.The significance of this study transcends the immediate context, offering valuable insights into the potential of the real estate industry in Raigad district. The focus on this specific market niche allows for a nuanced exploration of the complexities involved, presenting stakeholders, policymakers, and industry players with a strong foundation for well-informed decision-making. In the midst of ongoing urbanization and economic development shaping Raigad district, this study serves as a timely and pertinent exploration of the evolving dynamics within the local real estate landscape.

Design and Fabrication of Pedal Operated Shredder Machine
Authors:-Chandan sahoo, Ajay vikash kumar behera, Abinash mallick, Ananta Prasad sethi, Dr. Mamata kumari padhy

Abstract- The scope of this project was to design and development of Shredder machine focus on chopping of vegetables, areca leaves, this chopped powder to prepare the vermin compost. The project began with collection of information and data on user lifestyle and current process by which they perform their job. Concepts were developed with reference of four different shredder machine and operating processes. Concept was developed considering the safety factor users operating environment and maintenance. Considering the users’ needs and buying capacity, spur gear, bearings, structural frame, cutter and dual shaft. The machine frame is built using mild steel and tungsten carbide is used for cutter tip preparation. Two Blade are mounted on Singal shafts, which rotate parallely driven by a spur gear. The power from the by cycle is transmitted to cutter shaft through a chain drive. Cut is made inside the chopping house due to the effect of tensile, friction, and impact effect in chopping process. The vegetables get chopped and powder is collected at the bottom.

DOI: 10.61137/ijsret.vol.10.issue2.159

Blockchain Technologies and its Application
Authors:-Research Scholar Satya Prakash Gupta, Professor Dr. Sunil Gupta

Abstract- Blockchain technology has become a revolutionary new technology that has the potential to change many industries. Originally developed for Bitcoin, its applications have expanded to include finance, healthcare, supply chain management and more. This research article provides a detailed overview of blockchain technology, its concepts, features, and various recommendations. It also dives into real world applications, exploring how blockchain can be used to increase transparency, security, and efficiency in a variety of fields. Be a coup machine. This article provides an in depth study highlighting the basic principles, architecture, proposals and applications of blockchain. From crypto currencies like Bit coin and Ethereum to revolutionary solutions in finance, supply chain management, healthcare and more, the distributed, transparent and immutable nature of blockchain is pioneering new approaches to information management and trust. This article also discusses the benefits, challenges, and real life case studies of blockchain adoption. Looking ahead, scalability solutions, integration with the Internet of Things, and the need for regulatory frameworks are said to be important for the continued development of blockchain. Through this analysis, blockchain technology and its different applications can be better understood and one can gain insight into its potential to revolutionize business and create a new era of trusted digital ecosystems. Crypto currency, smart contract, decentralized management.

A Study of Effectiveness of Training and Development Program on Performance of Employees in Tata Motors
Authors:-Vikas Kumar

Abstract- Tata motors Limited is India’s largest automobile company. It is the largest commercial vehicle manufacturer in India and 2nd largest passenger car and bus manufacturer. This study investigates the impact of training and development programs on employee performance within Tata Motors, a renowned automotive company. The research explores the effectiveness of these programs in enhancing various aspects of employee performance, including productivity, skills acquisition, job satisfaction, and overall organisational performance. Utilising both qualitative and quantitative research methods, data is collected through surveys, interviews, and performance evaluations. The findings highlight the significance of training and development initiatives in fostering employee growth and organisational success. Recommendations are provided for enhancing the design and implementation of training programs to maximise their effectiveness and ensure long-term benefits for both employees and the company.

The Future of Clean Energy: Exploring Green Hydrogen Production through Electrolysis
Authors:-Nayan Chafale, Yash Nagoshe, Sumedh Jadhao, Yash Ingole, Chaitanya Durugkar, Manjiri Chaware

Abstract- In recent years, the demand for clean and sustainable energy sources has intensified due to concerns over climate change and environmental degradation. Green hydrogen has emerged as a promising alternative that can play a pivotal role in the transition towards a low-carbon economy. This research paper delves into the processes involved in the generation of green hydrogen, the technologies driving its production, its potential applications across various sectors, as well as the challenges and opportunities associated with its widespread adoption.

Money Minder: Personal Finance Tracker
Authors:-Om Mahajan, Vedant Mahanavar, Sumit Malwadkar, Kiran Mangde, Ved Mehta, Pranav Patil

Abstract- In the current financial crisis-ridden globe, everyone is looking for the greatest and most efficient methods to handle their personal affairs. This article presents Money Minder, an online tool for thorough and efficient financial tracking. Money Minder was created with the goal of enabling users to successfully manage their finances. Money Minder is easy to use because of its user- friendly UI. Money Minder robustness and security come from its user security features. Its many features enable them to manage their finances. It keeps track of account and transaction balances, deposits, transfers, and category-specific expenses. It also assists in maintaining data regarding current, recurring, non-recurring, and saved transactions. It also serves as a reminder for individuals with approaching or past-due invoices and deposits. Users have the option to filter summary reports by timeframe and view them both by account and by category. It provides a financial summary report, which is useful for people who want a broad overview of all their financial accounts.

Solar Powered Mechanized Paddy Transplanter
Authors:-Dr. Salim Sharieff, Professor Tansif Khan, Mohammed Saqlain, N S MD Azharuddin, Noor Mohammed Khan

Abstract- The adoption of mechanical agricultural operations is happening quickly in certain nations, like India. Most crops, including rice, need between 70 and 85 labor days per acre and are labor-intensive. Agriculture is labor-intensive and labor-intensive due to the enormous workforce involved. Getting labor and water when needed for different farming tasks has grown more difficult in the modern day. In order to overcome these obstacles, the area of crop cultivation needs mechanical tools. A mechanized crop transplanter is one example of such a gadget. The goal of this project is to create a machine that will solve labor and resource constraints that farmers confront. The adoption of mechanical agricultural operations is happening quickly in certain nations, like India. Most crops, including rice, need between 70 and 85 labor days per acre and are labor- intensive. Agriculture is labor-intensive and labor-intensive due to the enormous workforce involved. Getting labor and water when needed for different farming tasks has grown more difficult in the modern day. In order to overcome these obstacles, the area of crop cultivation needs mechanical tools. A mechanized crop transplanter is one example of such a gadget. The goal of this project is to create a machine that will solve labor and resource constraints that farmers confront.

A Study on Impact of Mergers and Acquisition in Indian Banking Sector
Authors:-Himanshu Singh, Professor Dr Manoj Pandey

Abstract- Mergers and Acquisitions (M & As) continue to be a significant force in the restructuring of the financial services industry. The Indian Commercial Banking Sector, which has played a pivotal role in the country’s economic development, is currently passing through an exciting and challenging phase. With the onset of economic reforms, the banking sector in India has embarked upon mergers and acquisitions to capture the synergistic benefits like economies of scale and scope, in the face of increasing competition from domestic as well as foreign players and rapid technological developments.

Hospital Hub: Transforming Healthcare Management for Enhanced Patient care
Authors:-Dipika Medankar, Shriya Naphade, Aakanksha Nimbalkar, Piyush Panchmukhe

Abstract- The hospital management system aims in enhancing the operational efficiency and quality of health care service. It includes improving management in hospital management, improving profitability. The study aimed at enhancing the efficiency of hospital operations and improving standards. The platform would provide a facility such as booking a doctor’s appointment, booking test slots and getting health programs. Hospital record-keeping is currently done manually, which is slow and prone to mistakes. Because hospitals are vital to people’s lives, it’s important to find a better way to manage records to save time and prevent errors. The project’s goal is to bring day-to-day hospital activities online, automating them for improved efficiency and accessibility. Each phase provided clear direction for the researchers, assisting in the study’s development and ensuring effective organization of tasks throughout the workflow. With a growing IT sector, data plays an major role in analyses data for diagnosis. The data helps in understanding and making decision accordingly. In this article, main focus is on restructuring the healthcare sector with the help of IT. The study will help to understand the current HMS and improve the hospital management run smoothly.

Practical Application of the Sup-Wald Test in Regression Models Using R
Authors:-Research Scholar Siddamsetty Upendra, Dr. R. Abbaiah, Dr. P. Balasiddamuni, Dr. K. Murali

Abstract- The Sup-Wald test is an important tool in regression analysis, especially for evaluating the joint significance of coefficients in a model. This paper presents a practical and descriptive study of the Sup-Wald test, focusing on its application to the simple linear regression model. We define hypotheses, elucidate the calculation of the Wald statistic, examine its distribution, determine critical values, and interpret results. Emphasis is placed on Ordinary Least Squares (OLS) estimation and variance precision. A practical illustration is presented through an R program, offering researchers hands-on guidance for implementing the Sup-Wald test in real-world scenarios. This paper provides practitioners with a clear understanding and practical skills for utilizing the Sup-Wald test in regression analysis.

DOI: 10.61137/ijsret.vol.10.issue3.161

Aluminium Beverage Cans: A Pop-Culture Artifact
Authors:-Shifa Mehra

Abstract- This paper will decode an evolutionary product design of an Aluminium Beverage can that had a dripping effect in the mainstream medium of entertainment, and it still maintains its iconicity and relevance even though it is a by product of events that highlighted the New York post World War. To understand the process of the evolution of ‘a simple product’ throughout the years of creative brainstorming of ideas, we need to study the historical reasons behind this evolution, the way its basic design was enhanced and the important role it plays in the market industry.

UMIT Placement Management Portal
Authors:-Komai Kamble, Srushti Jadhav, Sakshi Khanvilkar, Prachi Dhannawat

Abstract- From student’s point of view, placements can be very beneficial and offer a range of opportunities. The training and placement cell is an important part of every institution. But here most of the work is done manually. There are many errors in the colleges’ manual work as it requires time, effort and manpower. There are times when the data gets edited or deleted, which can be a problem for many students. Developing a website for colleges’ training and placement cell is the objective of this website. We have aim to develop a web portal to solve this issues. This portal helps the Placement coordinators and Students to manage activities all in one place as a Web Portal with Chatbot facilities. This Chatbot handles the basic queries realted to placements ask by students. This web portal consists of three modules: student, admin and company. This system will be used by the college with proper logins enabled. It can be used by the Placement Officer in the college to manage student information information about placement thus reducing the manual work. In our portal, admin can view the personal and academic information of the student.

Emerging trends of E-commerce in India: Some Crucial Issues, Opportunities and Challenges
Authors:-Gourav Kamboj, Trishi, Nandini, Jaspreet Kaur, Lalit Kumar, Supriya, Tisha

Abstract- The global business landscape is undergoing a dynamic Transformation due to the increasing penetration of internet and communication Technologies. This article reviews the e-commerce literature to understand the Emerging trends and future directions, which are shaping the competitive trends In the global business landscape. The article focuses on the following research Dimensions – e-commerce definition; underlying research themes; theoretical Models and frameworks used to understand e-commerce adoption; and key Challenges faced by the e-commerce providers. The first contribution involves elaborating the broad perspectives and statistical overview of the selected Articles including the publications summary, research themes, methodology, And locations. The second contribution involves presenting an integrated view Of e-commerce definitions across five dimensions – information, technology, Buy-sell transactions, monetary transactions and competition. The third Contribution involves highlighting the theoretical models being used to study Patterns of consumer behaviour. The fourth contribution lies in identifying the Key challenges faced by the e-commerce organisations.

Paws for Progress: Harnessing Technology for Animal Welfare
Authors:-Aqdas Mirza, Yashraj Misal, Omkar Ovhal, Prajwal Naukarkar, Prashant Patil,Saurabh Patil, Vikas Desai

Abstract-In our paper, we present a comprehensive approach to the development of a website dedicated to animal rescue and rehabilitation. Recognizing the contemporary significance of animal welfare, our project aims to leverage digital platforms to amplify efforts in this domain. Through meticulous research, planning, and implementation, we delineate the blueprint for a dynamic website that serves as a centralized hub for education, collaboration, and action in the realm of animal welfare. We discuss essential features and functionalities, including adoption listings, donation portals, volunteer sign-up, and educational resources, designed to facilitate adoptions, donations, and community engagement. Furthermore, we emphasize the importance of intuitive design, responsive navigation, and accessibility to ensure a seamless user experience across devices. Technical implementation considerations, such as website development platforms, hosting, security measures, and integration with third-party services, are also addressed. Evaluation and testing methodologies, including usability testing, functionality testing, and performance optimization, are outlined to ensure the effectiveness and reliability of the website. Through continuous iteration and feedback, we strive to create a digital sanctuary that fosters compassion, collaboration, and positive change in the lives of animals in need.

Stacked Classification Model with Cryptographic Process in IoT Data to Prevent and Detect Attacks
Authors:-N. Shashikala, T.N Anitha, Priti Mishra, Renuka Patil Herakal, Jayasudha Kolur

Abstract-The paper introduces a novel approach termed Gradient Optimization Features Integrated Stacked Classifier (GOFI-SC) for enhancing intrusion detection and attack prevention in Internet of Things (IoT) environments. GOFI-SC integrates feature optimization, cryptographic processes, and stacked classification models to effectively identify and classify various types of attacks. The feature importance analysis underscores the significance of attributes such as source IP address, destination IP address, and protocol in detecting malicious activities. Optimization of features with GOFI-SC demonstrates progressive reduction in loss values over iterations, indicating improved model convergence. the cryptographic process ensures secure communication and data integrity, with encryption and decryption speeds of approximately 150 MB/s and 175 MB/s, respectively. Classification results exhibit high accuracy, precision, recall, and F1-scores across different epochs and attack types, with accuracy reaching up to 0.990 and F1-scores exceeding 0.990.

DOI: 10.61137/ijsret.vol.10.issue3.162

Language Translator Tool
Authors:-Deepanshu Agrawal, Aryan Vats, Sameer Khan

Abstract-The Language Translator Tool leverages natural language processing and machine learning to bridge linguistic gaps, enabling effortless communication across diverse languages. Its real-time translation, intuitive interface, and support for numerous languages make it indispensable for global interactions in business, travel, and education. By breaking down language barriers, it fosters understanding and collaboration among individuals and communities worldwide. Whether facilitating international trade negotiations, aiding travelers in foreign lands, or enhancing cross-cultural education, this tool plays a pivotal role in promoting unity and connectivity in our increasingly interconnected global landscape.

Natural Processing Language for Sentiment Analysis in Social-Media
Authors:-Research Scholar Bhishm Kumar, Professor Dr Sunil Gupta

Abstract-Social media is very popularly used every day with daily content viewing and/or posting that in turn influences people around this world in a variety of ways. Social media platforms, such as YouTube, have a lot of activity that goes on every day in terms of video posting, watching and commenting. While we can open the YouTube app on our phones and look at videos and what people are commenting, it only gives us a limited view as to kind of things others around us care about and what is trending amongst other consumers of our favourite topics or videos. Crawling some of this raw data and performing analysis on it using Natural Language Processing (NLP) can be tricky given the different styles of language usage by people in today’s world. This effort highlights the YouTube’s open Data API and how to use it in python to get the raw data, data cleaning using NLP tricks and Machine Learning in python for social media interactions, and extraction of trends and key influential factors from this data in an automated fashion. All these steps towards trend analysis are discussed and demonstrated with examples that use different open-source python tools.

Research Paper on 256-Bit Encryption
Authors:-Aditya Jevlikar

Abstract-This paper presents a comprehensive analysis of 256-bit encryption algorithms, examining their structure, functionality, and security efficacy. We explore the mathematical foundations of these algorithms, their practical implementations, and their role in securing data in various applications. By focusing on Advanced Encryption Standard (AES) as a primary example, this paper discusses the theoretical and practical aspects of 256-bit encryption, comparing it with other encryption standards, and evaluating its performance in real-world scenarios. We also address potential vulnerabilities and future directions in the development of encryption technologies.

Design and Development of CNG Tank to Transform IC Engine Vehicle to Hybrid Dual Powered Vehicle
Authors:-Assistant professor Abdul Mujeeb N, Fardeen Khan F, Mohammed Sharjeel Ahmed, Shaik Abdul Kareem

Abstract-This paper presents the process of designing, retrofitting and testing a compressed natural gas (CNG) fuel tank on a two-wheeler and operating the hybrid vehicle in solo modes as well as in hybrid mode. The study evaluates the viability of applying CNG as alternative source of energy in view of depleting conventional fossil fuels and performance of CNG fueled and CNG-petrol fueled two wheeler vis-à-vis conventional petrol engine two wheeler. The contribution of this research paper is design and integration of a custom-designed CNG Fuel Tank, ensuring compliance with safety standards and emission standards of Bharath Stage VI regulations. The CNG Fuel Tank is designed and installed in the most realistic position to prevent the vehicle from becoming unwieldy structure and several modifications were made to accommodate the CNG tank without compromising vehicle stability orperformance. The study concludes that CNG is a promising alternative to petrol for two- wheelers to attenuate green house gas emissions. The test results suggest that broader adoption of CNG in two-wheelers could contribute to more sustainable transportation besides superior fuel economy. The research findings will benefit the automotive industry community in their stride to attain zero emissions aimed at circumventing the ecological and environmental perils of global warming and ensuing climate change.

Alert System for Detecting Driver Drowsiness and Prompting Intervention
Authors:-Assistant Professor S.Ramani, Assistant Professor A.Jaya Priya, Assistant Professor T.Dhivya, Assistant Professor P.Muthulakshmi, PR .Krithika Priya

Abstract-Driving while feeling drowsy poses a significant risk of causing dangerous traffic accidents. Particularly when driving alone on highways or for extended periods, drivers often experience boredom and drowsiness, increasing the likelihood of falling asleep at the wheel. Many of the currently available anti-sleep detection products on the market merely consist of earphones emitting intermittent noises, which are both irritating and ineffective. Consequently, there exists a pressing need for an affordable and efficient solution for detecting driver drowsiness. In response to this demand, we conceived and successfully developed a system for detecting and alerting drivers of drowsiness, effectively addressing this critical safety concern on the road.

Sentiment Analysis Text Extraction from Tweets with Spacy NER
Authors:-Pijush Pathak, Linson Thomas Verghese, Dr.G.Divya

Abstract-This project investigates sentiment analysis on Twit- ter data using spaCy, a flexible Natural Language Processing (NLP) framework. Our goal is to create algorithms that can recognize and extract text segments from Tweets that convey sentiment. This entails using tagged Twitter data to train two spaCy Named Entity Recognition (NER) models: one for positive sentiment and one for negative sentiment. Next, new Tweets are subjected to these models in order to predict user emotion and extract pertinent sentences. By identifying sentiment-infused text fragments, we are able to better comprehend the emotions around particular issues or phrases by gaining insights into the opinions and motivations of Twitter users.

DOI: 10.61137/ijsret.vol.10.issue3.163

Blockchain and AI in Pharmaceutical Supply Chain
Authors:-Piyush Bhalerao, Jatin Shinde, Aditya Ghodke, Professor Supriya Balote

Abstract-Presently, the widespread issue of counterfeit drugs poses a significant threat, fuelled by a lack of transparency in the pharmaceutical system and challenges in investigating supply chain tampering. Our innovative solution combines the power of Blockchain and AI. Blockchain, as a decentralized ledger, ensures transparent and immutable recording of transactions, providing a robust solution to combat counterfeit medicines. In parallel, AI in pharmacology enhances customer service, fosters loyalty, and facilitates seamless access to medical intelligence via the blockchain. This paper introduces a system leveraging both technologies to ensure the secure supply of medical drugs throughout the supply chain. By adopting an event request-response framework, authenticated entities can transmit each product along the chain, reducing the problems brought on by phony medications and unethical business activities.

Practices of Continuous and Comprehensive Evaluation at Elementary School
Authors:-Assistant Professor Dr.P.Shiney

Abstract-Continuous and Comprehensive Evaluation is a new approach to the system of evaluation that aims to make evaluation more systematic and dynamic. The major assumption of CCE is that every child can improve. With the broader aim of examination reforms in mind, the scheme of continuous and comprehensive evaluation envisages that every learner is to be evaluated over the entire period of learning schedule rather than one three-hour external examination at the end of a course of learning. CCE emphasis on the all-round development of every child and that can be achieved by active participation in different activities which in turn helps to derive self-belief in the learners. The evaluation process is school based. In this new scheme, the role of formative evaluation is of utmost importance. CCE aims at making children capable of becoming responsible, productive and useful member of a society. Introduction of continuous and comprehensive evaluation (CCE) is one of such reforms in entire education that can make education more meaningful for the learners. This article examines the concept of continuous and comprehensive evaluation, its historical perspectives, its need and importance, its features and role of teacher in implementing CCE in the modern education system.

Effectiveness of Life Skills Activities on Academic Anxiety of Middle School Students of Indore City
Authors:-Assistant Professor Dr. Sangeeta Ranadive, Scholar Ms Mamta Narvariya

Abstract-The main purpose of the study was to check the Effectiveness of life skills activities on academic anxiety of middle school students of Indore city. Objectives of the study was to study the Effectiveness of life skills activities on academic anxiety of middle school students. Null hypotheses were formulated for testing. One group pre post group design was used for this experimental study. Purposive sampling technique was used. There were 17 boys and 34 girls of private school were randomly assigned for the treatment group. Data were collected by standardized scales and questionnaire. The corelated t test and non-parametric test were used for data analysis purpose. It was revealed in the study that the life skills were effective on change the academic anxiety positively.

<!–Investigation of Mechanical and Microstructural Properties of Concrete Using Fly Ash Cenosphere as Fine Aggregate
Authors:-Satyajeet Nayak, Professor Ananya Punyotoya Parida

Abstract-The construction industry is constantly seeking sustainable and innovative materials to enhance the mechanical and microstructural properties of concrete while reducing its environmental impact. This research focuses on the utilization of fly ash cenosphere as a fine aggregate in concrete, aiming to investigate its impact on the mechanical strength and microstructure of the resulting material. Fly ash cenospheres, hollow microscopic spheres derived from the combustion of coal in power plants, are increasingly recognized for their lightweight and high-strength properties. Integrating these cenospheres into concrete as a partial replacement for traditional fine aggregates presents an opportunity to enhance both the structural and environmental performance of concrete. The study begins with an extensive literature review, summarizing the current state of knowledge on the use of fly ash cenospheres in concrete. Previous research has highlighted the potential benefits of cenosphere incorporation, including reduced density, improved workability, and enhanced durability. However, there remains a need for a comprehensive investigation into the mechanical and microstructural aspects of concrete containing fly ash cenospheres. The experimental phase of this research involves the preparation of concrete mixtures with varying proportions of fly ash cenospheres as fine aggregate replacements. Standard concrete mixes with traditional fine aggregates serve as control specimens for comparison. The mechanical properties, including compressive strength, tensile strength, and flexural strength, are evaluated at different curing periods to assess the short-term and long-term effects of cenosphere incorporation. Microstructural analysis is conducted using advanced imaging techniques such as scanning electron microscopy (SEM) and X-ray diffraction (XRD). These analyses provide insights into the distribution, size, and interfacial characteristics of fly ash cenospheres within the concrete matrix. Additionally, porosity, permeability, and the hydration products of the mixtures are examined to understand the impact on the overall microstructure. Preliminary findings indicate that the addition of fly ash cenospheres positively influences the mechanical properties of concrete, with enhanced strength observed in certain mix proportions. Microstructural analysis reveals improved packing efficiency and a refined pore structure, contributing to the overall performance of the material. However, challenges such as optimal cenosphere dosage and potential drawbacks are also identified. The implications of this research extend beyond the laboratory, as the incorporation of fly ash cenospheres in concrete has the potential to offer sustainable solutions for the construction industry. The study contributes valuable data to the existing body of knowledge, guiding future research directions and providing insights for engineers, researchers, and practitioners interested in the development of environmentally friendly and high-performance concrete. In conclusion, the investigation of mechanical and microstructural properties of concrete using fly ash cenosphere as a fine aggregate showcases promising results for the enhancement of concrete performance. As sustainability becomes a paramount concern in the construction sector, the findings of this research contribute to the ongoing efforts to develop eco-friendly and high-strength concrete formulations for a greener and more resilient built environment.

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Prediction of Skin Disease Using Machine Learning
Authors:-Professor Rajendra G. Pawar, Akash Panchal, Pratik Singh, Jaideep Chadha

Abstract-This research paper delves into the application of advanced machine learning techniques for the diagnosis of skin diseases, exploring how artificial intelligence can enhance the accuracy and efficiency of dermatological assessments. Amid the challenges posed by the subjective nature of physical examinations and the variability of clinical symptoms, machine learning offers a promising solution by leveraging its capability to process vast datasets and identify intricate patterns. This study evaluates the effectiveness of various machine learning algorithms, including the adaptable k-nearest neighbor, robust support vector machine (SVM), and sophisticated convolutional neural networks (CNNs), in diagnosing skin conditions. Furthermore, the paper investigates advanced deep learning strategies such as recurrent neural networks (RNNs) for processing sequential data, generative adversarial networks (GANs) for synthesizing data, and attention mechanisms for emphasizing critical image areas. Each algorithm’s advantages and limitations are analyzed to determine their practicality for clinical use. By providing a comprehensive overview of current technological advancements, this paper aims to underscore the potential of machine learning to revolutionize the field of dermatology, thereby improving diagnostic processes and patient outcomes in skin care.

Exceeding the Expectation in IOT Using Machine Learning
Authors:-Associate Professor Dr.M.Senthil Kumaran, Vigneshwaran S

Abstract-This paper presents an innovative approach to automated lighting control that integrates manual, mobile, and intelligent machine-driven operations. The principal aim is to optimize energy economy and user comfort through dynamic lighting control through data collection. To make well-informed decisions about lighting requirements, the system collects user activity data pertaining to time and ambient light levels. The suggested system makes use of sensors to track ambient darkness and identify when a user enters a room. It enables both remote control using a mobile application and manual control using traditional switches. In addition, it analyzes trends in user behavior and ambient variables to autonomously control lighting. The lights are automatically turned on by the system when it detects low light levels and the presence of a user, guaranteeing ideal illumination. Additionally, the system uses machine learning algorithms to forecast lighting needs, which reduces wasteful energy use. In addition to offering a seamless user experience, this adaptive lighting system helps promote sustainable energy practices by using less electricity in areas that are either adequately lighted by natural light or vacant.. This paper demonstrates a comprehensive and user-friendly approach to current lighting systems, opening the door for smarter and more energy-efficient living environments through the combination of manual, mobile, and intelligent controls.

Life Estimation of Cable Insulation under Varying Load and Ambient Temperature Conditions
Authors:-Sweta Mishra, Arun Pachori

Abstract-Power cables are one of the major components of a power distribution system, and a failure occurring in the cables will directly affect the operation of the distribution system. Hence it becomes imperative to make an assessment of the condition of the power cable and to make an estimate of the residual life of the cable. The failure of power cables is mainly attributed to the failure of the cable insulation which is the weakest part of a cable. The insulation fails primarily due to aging and the aging in cable insulation can be due to multiple reasons which includes thermal stress, electrical stress, mechanical stress and other environmental as well as operating conditions acting over a long duration of time. In this work, we use the Arrhenius equation to predict the aging of the electrical insulation in power cables. The original Arrhenius equation gives a constant which represents the reaction rate of the chemical process that is causing the degradation of the insulation material. We use a different form of the Arrhenius equation to estimate the life of cables. The simulations and calculations done in MATLAB suggest that this method of estimating cable life gives realistic estimates and can be used for cable life assessment.

Changing Patterns of Consumer Behavior in the Evolving Indian Economy: Omnichannel Retailing, from the Focus on Consumer Behavior through Organizational and Retailer Impact
Authors:-Ms. Priya Wagh, Ms. Diksha Telmore, MR. Mayur Kamble

Abstract-In an increasingly digital world characterized by the rise of web 5.0, mobile internet, and broadband, companies find themselves in a process of profound adaptation. The different modes of interaction with customers also undergo systematic transformations due to the revolution that technology, especially the Internet is imposing on the market. So, this work aims to understand the complexity of Omnichannel retailing using bibliometrics and a systematic review of methodological strategies. This study also presents an investigation of the aforementioned theme considering the marketing lens as the main approach. The research was conducted in seven databases to list the main articles on the topic. The search terms were “Omnichannel” and its main variant “omnichannel”. The databases used were: Google Scholar, Web Science, Scopus, and Ebsco Host. The main results indicate that marketing researchers are addressing omnichannel from the consumer’s perspective (consumer experiences and the importance of the customer journey in omnichannel retailing), the business strategies adopted by companies to act in this retail format (investments in technology to integrate performance across different channels), and the interaction of marketing with other organizational domains (integration of the marketing domain with other domains to act in this retailing context). In conclusion, we suggest the following research perspectives: a) themes for understanding the customer’s journey; b) stages covered and how consumer experiences can impact new purchases; c) understanding how companies are preparing to deal with this omnichannel scenario.

Review on Design and Analysis of an Alloy Wheel
Authors:-Vinay Jagtap, Professor Ganesh Kesheorey

Abstract-The purpose of the car wheel rim provider’s a firm base on which to fit the tire. Its dimensions, shape should be suitable to adequately accommodate the particular tire required for the vehicle. In this review study a tire of car wheel rim belonging to the alloy wheel category is considered. Review of various Design in an important industrial activity which influences the quality of the product. The wheel rim is designed by using modelling software catiav5r20. In modelling the time spent in producing the complex 3-D models and the risk involved in design and manufacturing process can be easily minimised. So the modelling of the wheel rim is made by using CATIA.

IOT Enabled Smart Fire Suppression Drone for Enhanced Efficiency and Effectiveness
Authors:-Assistant Professor Mary Stella J, Abin Alexander, Fasik Rumaiz P F, G B Harsha, Justin Jose A

Abstract-The increasing threat of fire disasters has emphasized the urgent need for innovative fire fighting technologies. This paper introduces a ground breaking prototype of a smart fire suppression drone that utilizes advanced sensors and water pump system to detect and suppress fires. The drone incorporates a flame sensor for precise fire detection, allowing it to quickly identify the presence of flames. Once a fire is detected, the drone activates its water pump system to extinguish the flames by spraying water. This integration of technologies aims to revolutionize fire fighting practices by enhancing efficiency and effectiveness in mitigating fire disasters. This research highlights the potential of drones in improving fire fighting capabilities and contributing to efficient fire management strategies.

Robot for Cleaning Solar Panels
Authors:-Ks lalith, Aman Raj, Jayesh Nikam, Professor Sheetal Mali

Abstract-This research paper explores the design, development, and implementation of a robotic system for cleaning solar panels. The increasing deployment of solar panels worldwide necessitates effective maintenance solutions to ensure optimal performance. Dust, dirt, and other particulates significantly reduce the efficiency of solar panels. Manual cleaning methods are labor-intensive and costly, especially for large-scale installations. The proposed robotic system offers an automated, efficient, and cost-effective solution. This paper details the design considerations, mechanical and electrical components, control systems, and field-testing results of the solar panel cleaning robot.

Comparison of Transport Sectors of Mumbai and Chennai City from Earlier Done Studies
Authors:-J. Rathiga, Dr. Umadevi

Abstract-Cities population and area is increasing gradually. Chennai is facing a multitude of issues such as severe congestion; deteriorating air quality; increasing greenhouse gas (GHG) emissions from the transport sector; increasing road accidents; and an exploding growth in the number of private vehicles (largely motorcycles). With the urban population projected to more than double in the next generation, the situation could easily get out of control and affect Cities’ economic development efforts unless remedial measures are soon taken. By providing free public transport for all in the city could reduce personalized transportation and avoid congestion in the city and enhance the air quality of the city. This paper describes about the public transport and alternate fuels which reduces greenhouse gas emissions and decarbonizes the transport sector of Mumbai and Chennai City.

Analysis & Design of Reinforced Earth Slope in Cohesion Less Soil
Authors:-Assistant Professor Mr. Arbaz M. Kazi, Ms. Deeksha Shetty, Ms. Kimaya Salunkhe, Mr. Krutik Patil, Mr. Sahil Rathod

Abstract-Nicobar Islands with its terrain of brilliant diversity is of remarkable importance to the government of India due to its strategic place. Existing street infrastructure has come to be antique and deteriorated because of common calamities. Subsequently a brand-new course for transportation is being developed inside the areas which would not contact the coastal ends. The proposed road connects some parts of Nicobar Island. On this assignment our essential aim is to analyze and design an appropriate retaining structure for bridge infrastructure proposed to be built along a river. The preserving wall could be designed as Counterfort Retaining Wall, and Reinforced Earth Slope. Even as there are numerous masses appearing on the wall, the primary one is lateral earth strain which absolutely relies upon on angle of friction, cohesion, and density of the soil. The safety factors taken in consideration are sliding, overturning, subsiding and seismic zones which facilitates to examine the sturdiness, load bearing capability and structural integrity. Concluding with a value evaluation stating more suitable and economical solution for the region.

Review on Motorized Scarecrow Bird Animal Repellent
Authors:-Professor Mukesh Mane, Anuradha Chinchkar, Anurag Tembhurnikar, Shivam Parkale, Vishal Phakatkar

Abstract-This project is designed to design and build a solar-powered smart fence that uses renewable energy to prevent birds and other pests from damaging crops. The solar-powered smart scarecrow is equipped with many sensors and devices such as sound sensors, cameras, and speakers to detect and scare away birds and animals approaching or reaching the crops. The railing is powered by a solar panel that charges the battery and powers various sensors and devices. V Scarecrows are used to scare away birds and animals to save crops in the fields. A farmer placed a scarecrow in the middle of his field to protect his crops from birds and animals. When the bird flies or enters the field, we see that the scarecrow does not move or work in any way.

A Survey on Image Feature Extraction Techniques
Authors:-Urvi Upadhyay, Surendra Gupta

Abstract-Images play a vital role in various real-life areas like Object Detection, Image Classification, Image Detection, etc. While studying about images we come across various types of image features such as colour, shape, texture, etc. These image features are mainly used to illustrate the important features or properties of an image that can be used to classify and identify it. This paper provides a detailed study of various image features and its extraction techniques methods along with their mathematical function, real-life application and advantages of these features.

Values Education Integrating in Teaching in the Elementary Grade Level
Authors:-Daizey Balong, Maricel W. Mateo, Rose S. Alibal, Abigail P. Velasco, Jolly B. Mariacos

Abstract-The objective of study was to assess the values education in integrating in teaching in the elementary grade level in the Province of Benguet for the academic year 2023-2024. The descriptive survey method was used in the study. The five-point scale was used in the study. The checklist questionnaire was the main tool in gathering the data. The respondents of the study were one hundred four (104) respondents. The assumptions, weighted mean, frequency was used in the study. The findings of the study were drawn from the study: the level of implementation of the objectives of values education in enhancing in teaching in the elementary grade is very highly contributory, level of implementation of strategies in integrating values education in teaching in the elementary grade level is very highly implemented, and the degree of seriousness of the problem encountered by elementary teachers in integrating values in education in teaching is moderately serious. Based on the findings the following conclusion were drawn: level of implementation of the objectives in enhancing values education in teaching in the elementary grade level is extremely implemented by the public elementary schools in selected province in the Benguet provinces; the implementation of strategies integrating values education in teaching in the elementary grade level in the province of Benguet highly implemented by the teachers; and the problem encountered by public elementary teachers in integrating values education in teaching in the different subject areas was not so serious.

Solid Waste Management System
Authors:-Kanishka Jain, Gunjan Gupta, Pranav Gupta, Ashutosh Bansal, Ritu Singh

Abstract-The impact of solid waste on climate change is considerable, as emissions from landfills and dumps are a major source of emissions of methane. Strong greenhouse gas methane is one of the main causes of climate change, is generated through the breakdown of organic waste in anaerobic environments. Proper waste management is essential in order to mitigate these emissions and minimize the environmental impact. Waste prevention, composting, and recycling all play crucial roles in reducing greenhouse gas emissions associated with solid waste. By implementing strategies such as composting organic waste and capturing methane from landfills, significant reductions in emissions can be achieved. Municipal solid waste management has the ability to significantly aid in the mitigation of climate change by reducing global solid waste emissions towards a future of net-zero warming. By addressing the issue of solid waste management, we can actively combat climate change and safeguard the environment for future.

Comparative Study of Mechanical properties of Aluminium, Aluminium 7075 alloy Reinforced with Titanium Oxide and Magnesium
Authors:-Assistant Professor Nawaz Ahmed, Professor & HOD Dr. Salim Sharieff, Mohammed Adnan shariff, Ankit Kumar, VS Muthahar

Abstract-This study investigates the mechanical properties of aluminum and aluminum 7075 alloy composites reinforced with titanium oxide (TiO2) and magnesium (Mg) nanoparticles. The fabrication process involved powder metallurgy techniques to achieve homogeneity and dispersion of the nanoparticles within the matrix. Various mechanical tests, including tensile, compression, and hardness tests, were conducted using Universal testing machine to evaluate the strength, ductility, and hardness of the composite materials. The results revealed enhancements in mechanical properties compared to the base materials, attributed to the synergistic effects of reinforcing phases. This study provides insights into the potential applications of these composite materials in aerospace, automotive, and other industries where lightweight, high-strength materials are required. Initial findings reveal that the addition of TiO2 and Mg particles significantly influences the mechanical behavior of both Al and Al 7075 alloy. The composites exhibit enhanced tensile and yield strengths compared to their respective base materials. Moreover, improvements in hardness and impact resistance are observed, indicating the potential for applications requiring structural integrity and durability.

Industry Power Consumption Penalty Minimization Using APFC Unit Project
Authors:-Ms. Anjali Balaji Shelar, Ms. Kejal Shantaram Karkare, Professor P.V.Gaikwad

Abstract-The Automatic Power Factor Correction (APFC) unit is a pivotal system employed in electrical networks to enhance power efficiency by managing and maintaining an optimal power factor. This unit operates by sensing the reactive power in the system and dynamically adjusting the connection of power factor correction capacitors to achieve near unity power factor. This abstract delves into the fundamental principles, design, and functionality of the APFC unit, outlining its significance in industrial, commercial, and residential applications. It discusses the key components, such as capacitors, controllers, and sensors, along with their roles in ensuring efficient power factor regulation. Additionally, the abstract explores the advantages of employing an APFC unit, including reduced energy losses, minimized electricity bills, enhanced equipment lifespan, and compliance with power quality regulations. Furthermore, the abstract highlights the technological advancements and emerging trends in APFC systems, including smart grid integration and remote monitoring capabilities, paving the way for more sophisticated and efficient power factor correction solutions.

A Review on CFD Analysis of Perforated Fin Heat Sink by Various Fin Configuration
Authors:-Research Scholar Vikas Kumar, Professor Dr. Ajay Singh, Professor Nitin Barodia

Abstract-This review explores the application of Computational Fluid Dynamics (CFD) in analysing perforated fin heat sinks with diverse pin configurations, aiming to elucidate their thermal performance characteristics. By synthesizing findings from a range of studies, the review systematically investigates the influence of pin geometry on heat transfer efficiency, pressure drop, and fluid flow dynamics within these complex systems. Through a comprehensive examination of CFD simulations, insights are provided into the intricate interplay between pin arrangement and thermal behavior, offering valuable guidance for engineers and researchers seeking to optimize thermal management systems. The review underscores the significance of simulation-driven research in advancing heat transfer technology and highlights potential avenues for further innovation in the design and optimization of perforated fin heat sinks across various engineering applications.

Fatique and Corrosion Analysis of Alluminium 7075 Metal Matrix Composite with Reinforcement Silicon Nitride (SI3N4) and Zirconium Oxide (Zro2)
Authors:-Assistant Professor Nehal Ahmad, Dr. Salim Sharieff, Rashmitha NC, Shujaith Ali Khan, Ramu M

Abstract-This study investigates the fatigue properties of a 7075 aluminum alloy under axial and torsional loadings. Fully reversed tension-compression and torsional fatigue tests were performed on polished dumbbell-shaped specimens. The tension- compression fatigue data were presented in an S- N plot and modeled using Basquin’s equation. The axial fatigue data were used to predict torsional fatigue life through equivalent shear stress, applying Tresca, von Mises, and maximum principal stress criteria. Scanning Electron Microscopy (SEM) was employed to examine fracture surfaces, revealing distinct cracking mechanisms under different loadings. The study found that von Mises criterion provided the most accurate predictions for torsional fatigue life. The findings contribute to a better understanding of fatigue behavior in 7075 aluminum alloy, enhancing the reliability of fatigue life predictions for components subjected to complex loading conditions.

Generating Realistic Facial Images from Text Descriptions Using Fully Trained Generative Adversarial Networks
Authors:-D. Pragathi, P. Varshini, N. Sandeep Kumar, Associate Professor Mr. P. Raveendra Babu

Abstract- Conditional Generative Adversarial Networks (GANs) were first applied for text-to-image synthesis in early research projects led by Reed et al. (2016). The goal of this creative method was to convert written explanations into appropriate visuals. Later developments, such as Zhang et al. (2017) and their creation of two-stage architectures such as StackGAN, aimed to improve image quality by means of multi-stage refining procedures. Even with these advancements, it is still difficult to achieve coherence between generated images and input text, which motivates more research into dialogue and attention processes to support semantic alignment and realism. In the meantime, the development of GAN architectures like StyleGAN and DCGAN has made it easier to generate facial images of a high caliber for text-to-face applications. But correctly aligning these pictures with written descriptions remains a difficult task. In an attempt to improve fidelity, methods such as edge-to-face conversion and attribute swapping have been investigated. But substantial improvements are needed before faces can be produced from text with any degree of reliability, highlighting the need for creative approaches to close the semantic divide. To address these issues, we provide a novel architecture that uses trainable GANs to generate realistic-looking faces from descriptions found in texts.

IoT Based RFID Attendance System
Authors:-Prabhash Kumar, Ritesh Kumar, Hareesh Sharma, Dr. Sandeep Bidwai

Abstract- An innovative method of tracking attendance is the RFID Attendance System, which is based on the Internet of Things and integrates cutting-edge technology to improve accuracy and efficiency. By utilizing RFID technology and the ESP32 microcontroller, the system provides tracking and recording of attendance information in real-time. RFID tags or cards are used for individual identification, with the ESP32 acting as the central hub. This allows for seamless attendance tracking. Users can easily retrieve attendance records through the system’s online interface, which shows crucial data in an easy-to-understand tabular format, including names, roll numbers, and attendance status.

Design and Development of IoT Based Device for Measuring Deflection of Bridges Remotely
Authors:-Professor Dr. Ajay Radke, Mr. Jeet Ghelani, Mr. Prasad Bate, Mr. Harsh Sharma, Mr. Saish Sankhe

Abstract- Bridges serve as indispensable components of our infrastructure, known for their strength and durability. Yet, ensuring their ongoing safety demands attention to various factors, with deflection standing out as a critical indicator of structural health. Recognizing this imperative, this paper introduces an IoT (Internet of Things) based prototype device designed for remote deflection measurement in bridge structures. Through the integration of ultrasonic sensors and IoT technology, the device presents a comprehensive solution for continuous deflection monitoring. This approach not only facilitates proactive maintenance strategies but also enhances the overall resilience of bridges against unforeseen challenges. By harnessing the power of real-time data transmission and analysis, stakeholders can effectively identify and address potential issues before they escalate, thereby ensuring the lasting safety and integrity of bridge infrastructure. The efficacy and reliability of the prototype are underscored through experimental validation conducted on a meticulously crafted bridge model. These findings highlight the prototype’s potential for real-world deployment, showcasing its ability to revolutionize current practices in bridge maintenance and management. This IoT-enabled solution holds promise for safeguarding the longevity of bridge infrastructure, paving the way for a safer and more resilient future.

Efficient Flow – Project Management System
Authors:-Abhiraj Bondre, Sujit sherkar, Umar Shaikh, Sahil Hanwate, Tanyush pandey, Piyush Sawsakade

Abstract- The Efficient Flow – Project Management System is a collection of actions that facilitate the effective execution of a project. A project is characterized by a set of interconnected activities that are organized and carried out in a particular order to produce a distinct output (good or service) in a predetermined amount of time. The most important distinction between research and development projects is the former’s (lack of) explicit requirements and the latter’s (inability) to plan an output from the outset. Evaluation criteria for research projects must consider these kinds of “particularities” when it comes to outputs; for instance, demonstrating that something is impossible to accomplish could be a research project’s success.

A Comprehensive Analysis of False News Identification
Authors:-Research Scholar Amol Parde, Associate Professor Rachna K. Somkunwar

Abstract- The need for automated fake news identification has increased due to the exponential spread of false news. Positive outcomes have been obtained from several methods for identifying bogus news. Nevertheless, these detecting algorithms don’t explain their predictions, nor do they give a rationale. Explainability’s key benefit is its ability to identify discrimination and bias in detection algorithms. The ability to recognize bogus news using intelligent and autonomous news data mining and analysis based on information characteristics has been made possible by ongoing advancements in artificial intelligence technology. Nevertheless, there is a shortage of research on the interpretability of related methodologies and the use of multidisciplinary expertise in this study. This work focuses on the technologies currently in use to detect false news. The study contains broad technical models, multimodal-related technological approaches, datasets linked to false news, and research techniques for detecting fake news. We identify and outline a few open research challenges after analysing the most recent explainable fake news detection techniques. We classify the existing literature in this area by approaching it from four different perspectives: the explainability meter, the explained type, the explanation type, and the categorization features. This report also includes a list of possible study subjects in the four areas that have not yet been investigated but require attention.

Mechanical Tools Classifier Using Industry 4.0
Authors:-Associate Professor Dr Nadeem Pasha K, Dr. Salim Sharieff, Prem Kumar, Rakesha, Tharun

Abstract- This paper presents a novel approach to mechanical tools classification within the framework of Industry 4.0, focusing on the use of machine learning to automate tool identification in industrial settings. The objective of this work is to develop a reliable classifier that can accurately categorize various mechanical tools, thereby streamlining manufacturing processes and reducing the potential for human error. To achieve this goal, we collected a comprehensive dataset consisting of mechanical tool characteristics, including size, shape, and operational context. The classifier was trained using this dataset, employing robust machine learning algorithms to ensure high accuracy and adaptability. To validate the classifier, we conducted extensive testing in both controlled and real-world industrial environments. The results demonstrate that the classifier achieves high precision and recall rates, significantly improving the efficiency of tool identification and categorization. This automation has the potential to save considerable time and resources in manufacturing processes, as well as enhance overall productivity.

An Analysis of Drone Routing Algorithms: Approaches, Capabilities and Future Directions
Authors:-Mohit Kumar, Anshul Kalia, Sumesh Sood

Abstract- This paper presents an evaluation and comparative assessment of diverse routing algorithms used for optimizing drone trajectories and paths. The paper starts off evolved with the useful resource of way of highlighting the important characteristic drones play throughout several industries and the way inexperienced routing algorithms are paramount for optimizing drone operations like delivery, surveillance, and environmental tracking. The paper then gives a view of numerous routing algorithms which incorporates A*, LAHC, ABC, Learn and Fly, Iterative, Chicken Swarm Optimization, Genetic Algorithms, and hybrid techniques like combining ABC with LAHC. These algorithms are compared primarily based totally on their critical thoughts, direction period and usual overall performance, use of AI techniques, and protection issues like collision avoidance. Key strengths of every set of suggestions are analyzed. The paper moreover discusses disturbing situations like strength overall performance, city air mobility integration, protection risks, and the want for real-international attempting out. Finally, the summary highlights destiny studies recommendations together with self preserving navigation, multi-agent collaboration, dynamic re-planning, AI/tool gets to know integration, location computing, and regulatory compliance for truly unleashing the capability of drone routing algorithms inside the route of diverse applications.

An Overview of the Analytical Profile of Elitriptan
Authors:-T.Navya Sri, A.Swathi, K.Shivani, T Srujanya, Dr.T. Mamatha, Assistant Professor R.Swetha Sri

Abstract- Elitriptan is used to treat acute cases of migraine headaches by acting on the brain to lessen their pain. It is a member of the triptan class of medications. The present study evaluates the different methods for triptan analysis in bulk drugs and formulated products. A review provides an overview of the collection and discussion of analytical techniques, including electrochemical methods, HPLC, and UV spectroscopy. HPLC techniques are given in triptans alone and in combination. The procedures are reported in a table with parameters such as stationary phase, mobile phase combination, Flow rate, RT, wavelength detection and matrix. The UV-spectrophotometric method was used to investigate elitriptan in bulk samples, biological media, and various dosage formulations. Spectrophotometric techniques for triptans include variables like λ max, solvent, matrix, and more, both individually and in combination.

Prediction of Tensile Strength of ABS Material Manufactured by Fused Deposition Modeling Using Machine Learning
Authors:-Assistant Professor Ch. Raju, Assistant Professor A. Bhargav, Ch. Akshay, V. Dinesh Reddy, T. Shiva shanker, K. Laxmi Narasimha

Abstract- Additive Manufacturing (AM) processes, such as Fused Deposition Modelling (FDM), are increasingly used to fabricate functional parts using Acrylonitrile Butadiene Styrene (ABS) material in which the tensile strength of 3D printed materials, such as those fabricated using Acrylonitrile Butadiene Styrene (ABS), is a critical mechanical property that determines their suitability for various applications. However, predicting the tensile strength of these parts remains challenging due to the complex interplay of various printing parameters. This study proposes a machine learning approach to predict the tensile strength of ABS parts based on their defined printing parameters such as Layer height, Infill density, printing speed, nozzle temperature and Bed temperature. In order to conduct the experiment, Taguchi’s Design of the Experiment is employed to create an L25 orthogonal array sample dataset. This dataset encompasses a range of combinations of the printing parameters, allowing for a comprehensive analysis of their effect on Tensile strength. The machine learning algorithms are then applied to this dataset, and their performance is compared to identify the most accurate model-fit. Using a Universal testing machine the tensile strength value of each specimen is known. From these experiment values, A machine learning model was trained and validated, Various machine learning algorithms, like linear regression, random forest regressor, are employed to model and analyze the complex relationships between the printing parameters and Tensile strength. The best machine learning model is selected based on the least error.

Application Control Robotic Arm Vehicle
Authors:-Smita Desai, Swapnil Rathod, Prashant Harnawal, Swaminath Bandichode

Abstract- Many assistive technologies implemented to help the disabled people. The purpose of this research is to design and implement a new mechanism for disabled people which can be used as a helping hand. Generally, disabled people depend on others to live their lives. Our target is to make a robotic system that has different characteristics to help the physically challenged people. The robot will be able to move in any direction. An open- source Android application is used to control the robot via Bluetooth. The robot responds to move commands in the forward, backward, left, and right directions. A disabled person, especially those who cannot walk will be able to send this robot anywhere. The project also implements a robotic arm with pick and place capability. It is able to pick any object and carry it and place it to the required position. The robotic arm is designed such that it can be controlled by a number of different mechanisms, namely a smartphone as the remote control, or human voice command or an RF controller. Disabled people can use any one of these methods according to his or her comfort. The robot also uses an IP camera for video observation as well as video communication with others.

Design and Analysis of Aircraft Engine Cooling Fan
Authors:-Assistant Professor D. Jagan, G. Suresh, N.Mahesh Kumar, R. Sridhar, B. Sai Kumar

Abstract- An internal combustion engine produces power by burning fuel within the cylinders; therefore, it is often called a heat engine. Engines that make their energy by heat and combustion have a problem of maintaining safe operating temperatures. Thirty to thirty-five percent of the heat produced in the combustion chambers by the burning fuel is dissipated by the cooling system along with the lubrication and fuel systems. Forty to forty-five percent of the heat produced passes out with the exhaust gases. If this heat were not removed quickly, valves would burn and warp, Engine cooling fans are an essential component of the engine cooling system which is used to dissipate the excess heat generated by the combustion of fuels inside the engine. This project consists of designing the fan and analyzing it for its strength in structure using the Finite Element Method (FEM) approach. In this project, a complete design with calculation was developed by using the CAD tool Creo and analyzed with the CAD tool Ansys workbench. By using static and dynamic analysis we can understand the maximum strength and stress values for different materials.

Impact Analysis of Spider Web
Authors:-Associate Professor C. Venkatesh, M. Sai Manoj, M. Ganesh, P. Yeshwanth, P. Nithin

Abstract- Spider web, one of nature’s most remarkable structure renowned for its remarkable strength, elasticity, and lightness, making it one of the most intriguing structure in nature. In this work, we investigate the modal analysis and static structural analysis of a bio-inspired spider web, focusing on understanding the effects of point load and natural frequency on the web’s behavior. To achieve this, we design spider web structures using four different materials silk, nylon, steel, and aluminum. These materials are chosen for their diverse mechanical properties, allowing us to explore how variations in material affect the web’s performance. By utilizing Fusion 360 for design and Ansys Workbench for analysis, we aim to gain insights into the structural behavior of spider webs made from these materials. Additionally, we employ machine learning as a prediction tool to predict the total deformation of each material in the design of spider webs for practical use. This work not only advances our understanding of bio-inspired design but also has the potential to impact various engineering fields by offering innovative solutions derived from nature’s own designs.

Finest Approach to Synthesize Bio-Ethanal from Bluegreen Algae (River Algae- Chlorella Sorokiniana) Cultivated Through Closed Photobioreactor System
Authors:-Professor Dr. Younus Pasha, Dr. Salim Sharieff, Muhammed Tanzeem A, Mohammed Huzaifa, Shrithik Chandra

Abstract- In light of the growing global demand for sustainable energy sources, this study proposes an innovative approach to bioethanol production by synthesizing bioethanol from blue-green algae (Chlorella sorokiniana) cultivated within a closed photobioreactor system. Capitalizing on the rapid growth and high lipid content of algae, in conjunction with the utilization of vegetable waste, this method offers a sustainable and efficient route for bioethanol synthesis. Through meticulous optimization of algae cultivation and fermentation processes, our project aims to achieve maximal ethanol yield while maintaining purity. Additionally, the integration of algae-derived ethanol as an alternative fuel for spark-ignition engines presents a promising avenue for reducing reliance on fossil fuels and mitigating environmental harm. Despite challenges such as the high capital and operating costs of algae cultivation, seasonal variations in polluted water availability, and the processing of seaweeds with relatively low carbohydrate content, our interdisciplinary effort strives to overcome these obstacles and contribute to the advancement of renewable energy technologies. Ultimately, our work aims to address pressing environmental concerns and pave the way towards a greener and more sustainable future.

Prevalence of Multidrug-Resistant Urinary Tract Infections (UTIs) Among Male and Female Students at Nnamdi Azikiwe University, Awka, Nigeria
Authors:-Awari V.G., Umeoduagu N. D, Adepeju D.M, Abana C. C, Obasi C.J, Okeke C.B., Aniekwu C. J., Ikegwuonu E. A, Chidubem-Nwachinemere N. O, Agu K.C, Uwanta L.I.

Abstract- Multidrug resistance among organisms causing Urinary Tract Infections (UTIs) is a major public health problem, threatening the effective treatment of UTIs. This study investigated the multi-drug resistance UTIs among male and female students of Nnmadi Azikiwe University, twenty mid-stream urine samples were collected from 10 male and 10 female students from the Department of Applied Microbiology and Brewing. The samples were cultured on different media and identified through the morphological and biochemical characteristics of the isolates. The antimicrobial susceptibility patterns were determined using Kirby-Bauer disc diffusion technique. The results revealed a high incidence of urinary tract infections (UTIs), with 100% of females and 90% of males showing infection. Morphological and biochemical analyses identified forty isolates, with Proteus spp., Klebsiella spp., and Enterobacter spp. being predominant among others. Susceptibility tests for Gram-negative isolates indicated varying responses to antibiotics, with Proteus spp. showing sensitivity to gentamycin, intermediate susceptibility to ofloxacin, and resistance to ciprofloxacin. Klebsiella spp. displayed intermediate susceptibility to ofloxacin and resistance to other antibiotics. E. coli exhibited intermediate susceptibility to ofloxacin and ciprofloxacin, while Enterobacter spp. was resistant to all tested antibiotics. Among Gram-positive isolates, Enterococcus spp. showed susceptibility to all antibiotics except erythromycin and ciprofloxacin, while Staphylococcus was solely sensitive to levofloxacin. Antibiotic resistance poses a significant challenge for both individuals and healthcare professionals. Therefore, there is an urgent need to identify and prevent the proliferation of antimicrobial resistance among uropathogens in community settings.

Strategic Approach for Increasing Sales in Computer Retail Sector through Paid Social Media
Authors:-Simran Chhabria, Dr. Ashish Jaswal

Abstract- This research paper explores strategic approaches for leveraging paid social media campaigns to increase sales in the computer retail sector. In an era where digital presence significantly influences consumer behaviour, retailers must utilize social media platforms effectively to enhance visibility, engagement, and conversion rates. This study examines various paid social media strategies, including targeted advertising, influencer partnerships, and dynamic retargeting, to identify their impact on sales growth. Through a comprehensive analysis of case studies, market data, and expert interviews, the paper provides actionable insights and best practices for computer retailers aiming to optimize their social media investments. The findings suggest that a well-orchestrated social media strategy, tailored to the specific audience and product offerings, can substantially drive sales and foster customer loyalty in the competitive computer retail landscape.

Power Quality Improvement in a Grid Connected Wind-Solar Integrated System Using UPQC
Authors:-M.Tech Scholar Manpreet Singh, Assistant Professor Manpreet Singh

Abstract- The integration of renewable energy sources such as photovoltaic (PV) and wind power systems into the grid has gained significant traction in recent years as a means to reduce carbon emissions and enhance energy sustainability. The integration of these renewable energy sources, into the existing power grid poses challenges related to power quality due to their intermittent and variable nature. This thesis investigates the enhancement of power quality in grid-connected PV-wind integration systems using Unified Power Quality Conditioner (UPQC) Flexible AC Transmission System (FACT) devices, implemented and analysed through MATLAB/Simulink simulations. The research aims to evaluate the efficacy of UPQC FACT devices in improving power quality parameter harmonic distortion suppression.

Nexus between Financial Inclusion and Economic Growth: Evidence from the Emerging Indian Economy
Authors:-Amedee Havyarimana

Abstract- Financial inclusion is becoming crucial for fostering economic growth and reducing poverty, particularly in developing countries like India. This study investigates the intricate dynamics of financial inclusion in India, examining its underlying factors, patterns, and impact on GDP development. The study examines different dimensions of financial inclusion, including the utilization and availability of financial services, the role of technology, and institutional factors. This is done by employing theoretical frameworks and analysing empirical data. The paper comprehensively analyses the complexities and challenges associated with financial inclusion by integrating various conceptualizations and measurement approaches through a thorough review of the existing literature. In addition, the study investigates the determinants of financial inclusion by analysing the influence of institutional, macroeconomic, and socioeconomic factors in different countries and regions. The study examines the relationship between financial inclusion and economic growth, analysing the factors contributing to this connection and exploring how financial inclusion can stimulate economic growth. This research contributes to a more comprehensive comprehension of the impact of financial inclusion on fostering inclusive and sustainable economic growth. It achieves this by consolidating current empirical studies and providing novel perspectives. This will assist policymakers, practitioners, and researchers promote financial inclusion initiatives in India and other regions.

Intelligent Wireless Wan Encroachment Discernment Using Machine Learning Techniques
Authors:-Scholar Mr.S.Chitrapandi, Assistant Professor Mrs.S.P.Audline Beena, Dr. D. Rajinigirinath

Abstract- Network attacks pose a significant threat to the security and integrity of computer networks. The ability to predict and prevent these attacks is crucial for maintaining a secure network environment. Supervised machine learning techniques have emerged as effective tools for network attack prediction due to their ability to analyze large amounts of network data and identify patterns indicative of malicious activity. We present a comprehensive analysis of supervised machine learning techniques for the prediction of network attacks. We collect and pre-process the data, extracting relevant features and transforming them into a suitable format for machine learning algorithms. We evaluate the performance of these algorithms. We investigate the interpretability of the trained models to gain insights into the underlying patterns and characteristics of network attacks. This allows network administrators to understand the nature of attacks and develop appropriate defenses strategies. Additionally, we discuss the challenges and limitations associated with the application of supervised machine learning techniques in the domain of network attack prediction, such as the need for real-time analysis and the emergence of sophisticated evasion techniques.

In Vitro Activity of Β-Lactams and Other Antimicrobials against Multidrug-Resistant Pseudomonas Aeruginosa
Authors:-Obasi C. J., Agu K.C., Anazodo C. A., Aniekwu C. J., Okeke C. B., Adepeju D. M., Okoli F.A., Umeoduagu N. D.

Abstract- Pseudomonas aeruginosa is a major opportunistic pathogen, causing a wide range of acute and chronic infections. β-lactam antibiotics including penicillins, carbapenems, monobactams, and cephalosporins play a key role in the treatment of P. aeruginosa infections. However, a significant number of isolates of these bacteria are resistant to β-lactams, complicating treatment of infections and leading to worse outcomes for patients. Resistance to β-lactams is multifactorial and can involve changes to a key target protein, penicillin-binding protein 3, that is essential for cell division; reduced uptake or increased efflux of β-lactams; degradation of β-lactam antibiotics by increased expression or altered substrate specificity of an AmpC β-lactamase, or by the acquisition of β-lactamases through horizontal gene transfer; and changes to biofilm formation and metabolism. The table 1 shows that all the soil samples gotten from the different faculties in unizik have Pseudomonas spp. The β-lactam antibiotics test carried out on the Pseudomonas spp gotten from different soil samples as shown in table 2,3 and 4 shows that in soil sample B is resistant to ampicilin in 250mg/L, 125mg/L and also Resistant in 125mg/L of ciprofloxacin. While in table 4, soil sample B, C, and E are Resistant in 125mg/L of Chloramphenicol. The total heterotrophic bacteria count of P. aeruginosa on nutrient agar in table 5 shows that sample C has the highest number of P. aeruginosa (9.70 x 104cfu/ml) while sample B is the lowest (1.88 x 105 cfu/ml).

Antibacterial Activities of the Leaf Extracts of Bryophyllum Pinnatum (African Never Die Flower) on Pathogenic Bacteria Isolated from Cow Dung
Authors:-Nnaebue N. D., Onuorah S. C., Soludo O. C., Anyaoha V. N, Ajogwu T. M. C.

Abstract- The cost of orthodox drugs and incidence of antibiotic resistance among bacteria has inspired scientists to search for natural alternatives like plants extracts as they are safer in biological system. The leaf extracts of Bryophyllum pinnatum has been used in folklore medicine in the treatment of varieties of diseases in Nigeria, India and China. Ethanol and methanol extracts of leaf of B.pinnatum were analyzed and their antibacterial activities were also tested against pathogenic bacteria isolated from cow dung. The six pathogenic bacteria isolated were identified as Salmonella entrica, Proteus mirabilis, Staphylococcus aureus, Pseudomonas aeruginosa, Vibro cholerae and E.coli. The result showed that the ethanol and methanol extracts have antibacterial properties. The pathogenicity of the isolates was studied by infecting the mice with them. There were death of two mice infected with Pseudomonas aeruginosa and Vibro cholera. Other mice in the same group with them were asymptomatic carriers. For the mice infected with Salmonella entrica, Proteus mirabilis, Pseudomonas aeruginosa, E.coli, Staphylococcus aureus and Vibro cholerae, 50×108, 20×108, 25×108, 10×108, 10×108, 2×108 cfu/ml of the infected organisms were recovered from the intestine respectively. The bacterial load in the intestine reduced drastically after the ethanol and methanol treatment.

Advancing Warehouse Management Systems: Optimizing Loading-Unloading, Conditioning, Packing and Marking Processes with Adaptive AI Technology
Authors:-Abu Sied

Abstract- Warehouse management efficiency is critical in current supply chain operations, necessitating the deployment of adaptive technological solutions. This study investigates the application of modern technologies to improve several areas of warehouse management systems (WMS), such as loading and unloading, conditioning, packing, marking, and provisioning. This study explains the challenges faced by traditional warehouse management procedures and the potential given by adaptive technological improvements using a detailed analysis of existing literature. Key technologies such as the Internet of Things (IoT), robotics, artificial intelligence (AI), and automation are reviewed in the context of their use to improved warehouse operations. Furthermore, the paper emphasizes the advantages of integrating these technologies, such as increased efficiency, accuracy, and scalability, while also discussing potential barriers and concerns for successful implementation. Warehouses can satisfy the changing needs of contemporary supply chain systems and improve productivity by using adaptive technological solutions.

DOI: 10.61137/ijsret.vol.10.issue3.164

An Application of Water Quality Index (WQI) and Graphical Interpretation to Evaluate the Groundwater Quality of Tonk District, Rajasthan, India
Authors:-Aruna Saini, Priya Kanwar

Abstract- India at present is the largest user of groundwater in the world and more than 70% of it is used for irrigation. Along with rainfall the return flow from irrigation is also accounted in recharge to groundwater. This irrigation return flow contains fertilizers that are being applied by the farmers to get better crop yields. Groundwater quality assessment is essential to ensure sustainable safe use of water. Therefore, an attempt has been made to assess the overall groundwater quality of Tonk District by analysing the groundwater samples collected from entire district for twelve basic parameters pH, EC, TDS, TH, Ca2+, Mg2+, Na+, K+, Cl-, SO42-, NO3- and F-. The chemical results were compared with the Bureau of Indian Standards (BIS) and World Health Organisation (WHO) standards for drinking purposes and calculating the water quality index using these parameters that illustrates the overall suitability of groundwater from the study area for human consumption. The Hill Piper plot, Gibb’s plot and scatter plots facilitated in understanding the geochemical processes in the enrichment of groundwater by minerals. The water quality indices revealed the drinking suitability of groundwater in the study area that helps to identify the priority areas to be managed through remedial measures in order to keep water safe for consumption.

A Next-Generation Plant Disease Detection System Using Transfer Learning & Edge Impulse
Authors:-Jai Raj Singh Kirar

Abstract- One of the primary factors determining a nation’s growth is its agricultural sector. In India, agriculture employs around 65% of the country’s workforce. A variety of diseases can infect crops as a result of different seasonal circumstances. These illnesses initially damage the plant’s leaves before spreading to the entire plant, which has an impact on the type and quantity of crop that is grown. Because there are so many plants on the farm, it is quite challenging for the human eye to identify and categorize each plant’s condition. And since these diseases have the potential to spread, it is critical to identify every plant. Our findings indicate that when utilizing Edge Impulse for adaptive learning, plant disease detection accuracy and efficiency may be increased in comparison to starting from scratch. This has the potential for the development of plant illnesses. This work advances learning and edge computing by offering insights and recommendations for creating accurate and efficient learning models for identifying plant diseases on edge devices.

Recommending Right Cloud Service Provider Using Autonomic Computing
Authors:-Research Scholar Harcharan Singh Mittu, Associate Professor Dr. Rachna K. Somkunwar

Abstract- Choosing the right cloud service provider (CSP) is a pivotal decision for organizations seeking to leverage cloud computing for operational efficiency and scalability. This paper aims to provide a structured approach to recommend the most suitable CSP using autonomic computing techniques. By automating the decision-making process, we can evaluate and compare various CSPs based on performance, cost, scalability, reliability, and security. Our approach not only simplifies the selection process but also ensures that the chosen provider aligns with the organization’s strategic objectives and technical requirements.

DOI: 10.61137/ijsret.vol.10.issue3.171

Credit Card Fraud Detection using PSO-SVM Algorithm
Authors:-Kulsum Inamdar, Yash Gupta, Pawan Pawar, Abhishek Nandre, Professor Vidya Deshmukh

Abstract- Detecting credit card fraud is essential in the financial sector, as it helps prevent unauthorized transactions and safeguards both consumers and financial institutions. One effective approach to enhance fraud detection algorithms involves combining Particle Swarm Optimization (PSO) with Support Vector Machines (SVM). This integration leverages the strengths of both methods, addressing challenges in detecting fraudulent activities by offering improved accuracy, adaptability to evolving patterns, and efficient parameter tuning. By synergizing PSO and SVM, we can develop a more effective and reliable system for detecting credit card fraud.

Review on Design and Analysis of Multi Story Building and Prediction of its Deflection Using Artificial Intelligence Method
Authors:-Deepak Parmar, Associate Professor Rajesh Chouhan

Abstract- Designing and analysis of structural buildings by manual calculation is a complicated and time-consuming work, it is not always the best option. A computer aided program named Staad.Pro is available which allows it to design and analyze a structural building in an easy way and consume less time prior to its construction. Staad.Pro can also apply static and dynamic loads and their combinations in a quite simple method. The Staad.Pro software can design and analyze a structure for different types of a materials such as concrete, steel and timber.

Detecting DDOS Attacks Enhanced-KDD Algorithms
Authors:-Immadi Lahitha, Madala Anjali, Nadella Suma Valli Devi, B Suneetha

Abstract- Considering the widespread and constantly changing nature of DDoS attacks, the introduction emphasizes the vital necessity for efficient detection techniques. It promotes the use of ensemble approaches and deep learning for machine learning-based intrusion detection, highlighting the need for current datasets. The work makes significant additions to the discipline by introducing structured data exploitation, creating supervised machine learning classifiers, and validating suggested techniques against previous research.

Review on Design and Analysis of Highway Deck Slab Bridge with Prediction of its Durability
Authors:-Shubham Kumar Pandit, Professor Dr. J.N. Vyas

Abstract-Suspension bridge is an efficient structural system particularly for large spans. Many difficulties related to design and construction feasibility arises due to its long central span. There are many suspension bridges around the world and dynamic behaviour has been found to be the primary concern for those bridges. Natural period of a suspension bridge mainly dependent on the span and other structural dimensions related to the stiffness. .In the review study, we observed various design and analysis of the deck slab for suspension bridge under different types of loading in the software based on IS provisions to carried out the deflected shapes and impact on the deck slab. On the technical drawings, reinforced concrete slabs are often abbreviated to “R.C.C. slab” or simply “R.C.” Technical drawings are often created by structural Engineers who use software such as STAAD pro software.

A Case Study of Advanced Earthquake Resistant Techniques for Civil Engineering Project
Authors:-Sri. Diganta Mili

Abstract-Earthquakes are one of the most devastating forces on the planet. The seismic waves that travel through the ground can demolish buildings, kill people, and cost billions of dollars in damage and restoration. According to the National Earthquake Information Centre, there are over 20,000 earthquakes every year on average, including 16 major disasters. The damage was caused by the collapse of buildings with people inside, as in previous earthquakes, prompting the development of earthquake-resistant constructions. Constructions intended to withstand earthquakes are known as earthquake-resistant structures. While no structure can be completely safe from earthquake damage, earthquake-resistant construction aims to build structures that perform better than their conventional equivalents during seismic activity. Building rules state that earthquake-resistant constructions must be able to withstand the greatest earthquake with a reasonable chance of occurring at their site. There are now various design philosophies in earthquake engineering that use experimental results, computer models, and historical earthquake observations to provide the requisite performance for the seismic threat at the location of interest. In this article, we will deal with numerous techniques that can help improve a structure. Earthquake-resistant design of structures has developed into a genuine multidisciplinary field of designing wherein numerous energizing advancements are conceivable in the not so distant future. Most outstanding among these are: (a) an entire probabilistic examination and configuration approach; (b) execution based outline codes; (c) different yearly likelihood danger maps for reaction unearthly increasing velocities also, top ground increasing velocities with better portrayal of site soils, geology, close field impacts; (d) new basic frameworks and gadgets utilizing non-conventional structural designing materials and procedures; also, (e) new refined explanatory devices for solid expectation of basic reaction, including nonlinearity, quality and solidness debasement because of cyclic loads, geometry impacts and all the more critically, impacts of soil– structure connection. Some huge advancements that the coming years will witness are talked about in this Project.

Skin Cancer Classification and Comparision from HAM10000 Dataset Images Using Ensemble of Convolutional Neural Networks
Authors:-Yogendra Sharma, Tushar Manger, Amar Sanyasi, Janiela Bhutia, Anushka Pradhan, Smriti Koirala

Abstract-Skin cancer is a growing global health concern, and early and accurate diagnosis is crucial for effective treatment. Convolutional Neural Networks (CNNs) have emerged as powerful tools for skin lesion classification. They offer the potential to improve diagnostic accuracy and assist dermatologists. This study com- pares the performance of five CNN architectures – DenseNet121, DEnseNet201, InceptionResNetV2, Xception, and SCC-NET on the preprocessed Ham10000 dataset. This dataset contains 10,000 dermoscopic images, categorized into seven skin lesion types, with 500 images per class. The objective is to identify the model that achieves the best accuracy and generalizability for this specific dataset. To evaluate the models, we use metrics like accuracy,, and F1-score. This research contributes to the growing body of knowledge on utilizing CNNs for skin cancer classification. It has the potential to pave the way for develop- ing reliable computer-aided diagnosis systems, which can further improve the accuracy of skin cancer diagnosis.

Study on SDLC for Development of Resource Management Group System
Authors:-Yogendra Sharma, Tushar Manger, Amar Sanyasi, Janiela Bhutia, Anushka Pradhan, Smriti Koirala

Abstract-Effective resource management is vital for achieving organizational goals and maintaining a competitive advantage in today’s business environment. This study investigates the application of Software Development Life Cycle (SDLC) methodologies in developing a Resource Management Group (RMG) system. The SDLC offers a structured framework for software development, ensuring systematic and efficient system construction. This research examines various SDLC models, such as Waterfall, Agile, Spiral, and DevOps, to identify the most appropriate approach for developing an RMG system. The study emphasizes the significance of requirements gathering, system design, implementation, testing, deployment, and maintenance in resource management contexts. Each SDLC phase is evaluated for its impact on the RMG system’s overall efficiency and effectiveness. Additionally, the study explores the critical challenges and best practices in managing resources, including human, financial, and physical assets, within an organization. It also discusses how modern technologies like cloud computing, artificial intelligence, and data analytics can enhance the RMG system’s functionality and scalability. The findings provide valuable insights for project managers, software developers, and business analysts involved in resource management system projects. By selecting the appropriate SDLC model, organizations can ensure the successful development and implementation of an RMG system that optimizes resource allocation, boosts productivity, and supports strategic decision-making.

Employing Machine Learning for Anomaly, Malware and Intrusion Detection in Real World Network Environments
Authors:-Research Scholar Yashkiran, Professor Gurpreet Singh, Assistant Professor Simrandeep Kaur

Abstract-Employing machine learning for anomaly, malware, and intrusion detection in computer networks offers significant potential for enhancing security posture and mitigating cyber threats. By leveraging data-driven algorithms and adaptive detection mechanisms, machine learning enables proactive identification of anomalies, timely detection of malware, and accurate recognition of intrusions within network environments. However, challenges such as dataset labeling, model generalization, and real-time processing remain areas of active research and development. Moving forward, continued advancements in machine learning techniques and their integration with network security frameworks will play a crucial role in safeguarding critical infrastructure and protecting against evolving cyber threats.

Film-Fund: Unlocking Investment Opportunities in Film and Web Series Production: A Study of Interest-Based Financing
Authors:-Ranjeet Kumar Yadav

Abstract-The most popular entertainment destinations are films and web series, and project initiators have tried a variety of strategies. To entertain an audience, filmmakers can use niche or broad entertainment platforms. However, the primary challenge lies in obtaining funding for small and emerging directors to produce films and web series. Hence, a new initiative approach involves giving regular people a platform to directly invest in the creation of films and web series. They use interest-based or equity-based investment and provide fixed or flexible budgets. Production might be fully or partially financed by investment. As of now, there isn’t a common platform for investing in the creation of films and web series. Web series with a content focus have become more and more popular recently on over- the-top (OTT) services like Netflix, Hotstar, and Amazon Prime. The goal of this research is to close this conceptual gap and provide an investment model for films and web series that can be implemented and utilized to the advantage of all parties involved, including the investors, platform owners, supporters, distributors, and future viewers in general. The conceptual approach put forth here is founded on a critical examination of people, as individuals nowadays are willing to make direct investments in films because they are aware of the risks involved.

Review on Design and Analysis of Multi Story Building and Prediction of its Deflection Using Artificial Intelligence Method
Authors:-Deepak Parmar, Associate Professor Rajesh Chouhan

Abstract-Designing and analysis of structural buildings by manual calculation is a complicated and time-consuming work, it is not always the best option. A computer aided program named Staad.Pro is available which allows it to design and analyze a structural building in an easy way and consume less time prior to its construction. Staad.Pro can also apply static and dynamic loads and their combinations in a quite simple method. The Staad.Pro software can design and analyze a structure for different types of a materials such as concrete, steel and timber.

Event Decoration with AR
Authors:-Assistant Professor Uma Bhokare, Rachana Sadamate, Vasudha Sabale, Sharayu Pisal, Shreeya Shete, Himani Salunkhe

Abstract-Augmented Reality (AR) technology has emerged as a transformative tool in various industries, offering immersive and interactive experiences. In the context of event decoration, AR presents a promising avenue for enhancing creativity, engagement, and customization. This research paper explores the application of AR in event decoration, aiming to revolutionize the traditional methods of designing and visualizing event spaces.

DOI: 10.61137/ijsret.vol.10.issue3.169

Bioplastic: A Boon to Degrading Environment
Authors:-Mandeep Kaur, Associate Professor J J Mohindru

Abstract-Petroleum-based plastics have come under a lot of surveillance in the past decade owing to the properties that made them endless items; their durability and expendability. The exploitation of such features during the industrial era has now resulted into the major environmental issue of plastic pollution. Bioplastics are being considered as an environment-friendly alternative. However, not all materials under this category are the same and this has caused many misconceptions about the asset and its after-life processing, which has led to illusioned perception of people about its use. Proper disposal and sorting procedures required for many of these bioplastics are not well known, which affects their optimum degradation. This review aims to: (i) outline the production and properties of the most prominent bioplastics along with their impacts on the environment and the economy, (ii) discuss the differences between oxo and hydro biodegradable materials, (iii) explore the superiority of bioplastics compared to conventional plastics, and (iv) enumerate the future directions that can help them become a ubiquitous asset . Proper knowledge of the various bioplastics and the implementation.

DOI: 10.61137/ijsret.vol.10.issue3.165

Sociopedia: A Social Media Web App
Authors:-Abdullah, Anshu Bhaskar, Chetna Sharma, Shivam Bhagat, Assistant Professor Shyamapriya Chatterjee, Assistant Professor Sujata Kundu

Abstract-MERN stack technology is a popular technology stack used by many developers worldwide. MERN is an acronym for four powerful technologies, including MongoDB, Express JS, ReactJS, and NodeJS. This technology stack is known for its ability to build fast and robust web applications. It is no surprise that the MERN stack is gaining popularity among developers, and many are beginning to explore its potential. In this project, the MERN stack covers the entire web development process, from server-side programming to client-side programming. This project introduces a modern and dynamic social media application built on the MERN (MongoDB, Express.js, React, Node.js) stack. The app aims to address the evolving needs of online communities by providing an innovative platform for users to connect, share, and interact in a vibrant digital environment via chat and posts.

Developing Viability Conditions for Sewer Heat Recovery
Authors:-Hambal A Khan

Abstract-Sewer wastewater has a temperature between 10-25°C, which is an attractive source of energy, and it can be recovered by installing a heat recovery system (heat exchanger and heat pump) inside or outside sewer. The viable conditions for effective heat recovery and proper functioning of heat systems are wastewater temperature, flow rate, heat exchanger system, and heat pump. Viability conditions for heat recovery have been developed and applied to the Antwerp case study. Three methods perform heat recovery estimation: temperature drop method, Specific performance value (kW/L/s/m2 and kW/m2), and heat balance equation which is applied to the Antwerp case study of 29 and 1697 pipes to estimate heat recovery for selected pipes from the case study. Excel software has been used to performs calculations for heat recovery methods. IF Function is done additionally, to check with the Antwerp case study results as 200kwh/pipe. 29 pipes heat recovery was around 0.45-3.6kwh for the temperature drop method for 15 modules of heat exchanger. Specific values results are 1.04kw/L/s/m2 and 2.4-8.75kw/m2 for 29 pipes scenario. Selected pipes from 1697 results show 0.45-2.7kwh for temperature drop method for 15 modules, whereas specific values are 0.15-0.65kW/L/s/m2 and 2.4-8.75kw/m2.

A Review on Optimisation of Counterflow Heat Exchanger Using Box Behnken Design
Authors:-Neeraj Gupta, Dr. B.K. Chourasia

Abstract-This review focuses on the optimization of counter flow heat exchangers using the Box-Behnken design (BBD), a response surface methodology (RSM) approach for experimental design. Counter flow heat exchangers are widely utilized in various industrial processes due to their high efficiency in thermal energy transfer. However, optimizing their performance involves multiple parameters, including fluid flow rates, temperature differences, and heat transfer coefficients. The Box-Behnken design offers a systematic and efficient way to explore the effects of these variables and their interactions on the performance of heat exchangers. In this review, we summarize recent advancements in the application of BBD to optimize counter flow heat exchangers.

A Review on Parametric Study on Fins Attached to PV Solar Panel
Authors:-Shakti Choudhary, Bhupendra Gupta

Abstract-The study on the cooling effect of attached fins of different geometries on photovoltaic (PV) panels using Computational Fluid Dynamics (CFD) simulation is motivated by the increasing demand for efficient cooling solutions in solar energy systems. This review provides a comprehensive analysis of parametric studies on fins attached to photovoltaic (PV) solar panels, focusing on enhancing their thermal performance and efficiency. The utilization of fins in PV systems is a critical area of research aimed at mitigating the adverse effects of temperature rise on solar panel efficiency. This study reviews various fin geometries, including rectangular, trapezoidal, and triangular fins, and examines their impact on the thermal regulation of PV panels. The review highlights the influence of fin number, thickness, and length on temperature management.

Comparative Seismic Evaluation of Multistory Buildings Using Red Brick and AAC Block Walls using ETABS
Authors:-Khomdram Vijayraj Singh

Abstract-A building has been defined is an enclosed structure intended for human occupancy. Constructions work has been seen in most the countries developing. With the increases in material cost in the construction work, there is a need to find more cost saving alternatives so as to maintain the cost of construction houses, multistorey etc, which can be affordable to people. In the manufacturing of burnt clay bricks, smoke evolved at a great extent and also some toxic gases which can harm an environment. So as to overcome with all these problem, Autoclaved Aerated Concrete (AAC) blocks are used which is more economical and ecofriendly. This project includes the analysis, design and estimates of structure, comparing between autoclave aerated concrete and conventional brick in the form of steel consumptions. Autoclaved Aerated Concrete (AAC) is a lightweight concrete building material cut into masonry blocks or formed larger planks and panels. Currently it has not seen widespread use in the United States. However, in other parts of the world it has been used successfully as a building material. Cost of construction is reduced and it will be safe and economical in earthquake forces also. The seismic Parameter Lateral displacements are also compared.

Automating Billing Systems for Enhanced Efficiency and Sustainability
Authors:-Manish Pandey, Mayank Shukla, Kunal Singh, Assistant Professor Deepak

Abstract-This case study explores the development and implementation of electronic (e-invoicing) systems. As a work on paper, the writing process is labor-intensive, error-prone, and environmentally neutral. By switching to an electronic payment system, businesses can increase efficiency, accuracy, reduce costs and customer satisfaction, and support the environment at the same time. The proposed system uses modern network technology and strong security measures to improve the payment process. This article describes how to create such a system, discusses its advantages, and describes the solution to problems that may arise.Keyword: Optimisation, counterflow heat exchanger, box Behnken design.

Digital Text Document Clustering Using Frog Leaping Feature Optimization
Authors:-Seema Pal, Professor Sumit Sharma

Abstract-As the amount of online digital text, like blogs, study content, and news, has grown, it has become harder to find the information one need. Here, the search process is made more difficult by information that is not structured, especially text content. Researchers have come up with a number of models for grouping, but the unstructured model is the one that is most wanted. This paper has proposed a model that cluster text document as per relevant content. Each document terms are filter by frog leaping algorithm that do not need any supporting information. Selected terms were used for the training of neural network. Experiment was done on real dataset and result shows that proposed model has increases the work performance as compared to other existing work.

Tailored Strategies for Tax Compliance in Alaba International Market: Addressing Evasion, Underpayment and Avoidance
Authors:-Godson Christian Osita

Abstract-This research article aims to explore tailored strategies for tax compliance in Alaba International Market, focusing on addressing tax evasion, underpayment and avoidance. The study utilizes a mixed-method approach, incorporating both qualitative and quantitative data to provide a comprehensive understanding of the factors influencing tax compliance in the market. The theoretical framework draws on behavioral economics, tax compliance theories, and institutional perspectives to analyze the dynamics of tax compliance behavior among market traders. The findings highlight the need for tailored strategies that consider the unique characteristics of the market and its traders to effectively address tax evasion and underpayment. The article concludes with recommendations for policymakers and tax authorities to enhance tax compliance in Alaba International Market.

Investigating Business Strategies for the Biotechnology, Medical Device, and Healthcare Sectors to Manage Uncertainty
Authors:-Atharva Prasad Jakhadi

Abstract-The medical devices, biotechnology, and healthcare industries thrive on innovation, necessitating substantial investment in research and development (R&D) and the introduction of new products. These innovation activities, while essential, come with high costs and the complexities of commercialization. Thus, effective business models (BMs) that align with such innovation activities are vital. This study explores the intricacies of BMs within innovator companies in the health-tech sector, highlighting the critical role these models play in managing uncertainties and promoting innovation. A systematic literature review was conducted, analyzing 34 recent papers to synthesize knowledge on BMs in health-tech companies and compare models across dimensions such as infrastructure, offerings, customers, and finances. This review identified 9 key BMs: open innovation, sustainable, dynamic, dual, spin-off, frugal, high-tech entrepreneurial content marketing, backend, and product-service systems BMs. It was found that open innovation, sustainability, and dynamicity are foundational models that can serve as a basis when combined with others. The study presents a Dynamic Sustainable Business Model (DSBM) for Health-Tech, tailored to integrate adaptability and sustainability, offering a framework for leveraging emerging technologies effectively. Additionally, a conceptual framework of 28 groups of uncertainty factors in BMs was developed to aid risk management in health-tech. These findings provide crucial insights for health-tech companies, assisting them in managing innovation and value creation in a rapidly evolving landscape.

DOI: 10.61137/ijsret.vol.10.issue3.166

A Novel High Voltage High Frequency Charging Method for Electrets for Polymer Films
Authors:-Research Scholar Venkata Veeranjaneyulu I, Dr. Ashwani Tapde

Abstract-An innovation in corona charging of electrets of polymer films has been adopted in locally designed and fabricated corona charging set up by replacing the regular high voltage DC power supply with a light, portable handy 3V-6V DC to DC 400kV boost step-up power module high voltage generator. Polymer film electrets of polyethylene transparency film have been corona charged using this innovative setup. The measurements were done and the results have been analyzed in the light of cited literature to show the effectiveness and advantage of the innovation.

An Overview of Nanoparticles Function in Sustainable Agriculture
Authors:-Sujana J, Sonia Ruben, Bhavya D K

Abstract-In the world of agriculture, nanoparticles are gaining recognition for their ability to remediate soil degradation in a sustainable manner. They have recently been identified as prospective fertilisers because of their characteristics, which make them easier for plants to absorb and use than their bulk equivalent. Due to the overuse of traditional fertilisers, which are unsustainable, expensive, and hazardous to the environment, soil degradation over time has decreased agricultural yields and nutritional quality. Nanotechnology is the manipulation of matter on a near-atomic scale to produce new structures and materials. Nanotechnology is emerging out as the greatest imperative tools in recent agriculture and predictable to become a driving economic force in the near future. Nanotechnology can contribute to enhance agricultural productivity in a sustainable manner, using agricultural inputs more effectively, and reducing by-products that can harm the environment or human health. Integrating nanotechnology into agriculture, including fertiliser creation, is considered one of the greatest feasible methods to significantly increase crop yield and sustain the world’s constantly growing population. The application of nanoparticles in agriculture as is attributed to their improved characterization, absorption and responsiveness, as well as surface and adhesion effects. There has been main attention in using nanotechnology in agriculture and the food system due to great potential as it can improve the quality of different products. Through nano biotechnology, we can understand the biology of different crops, which will eventually help enhance the yield and nutritional value of those crops through breeding. Carbon nanotubes can enhance the germination of tomato seeds through the better conveyance of moisture. Nanotechnology also prevents waste in agriculture. From this technique we are able to study plant’s regulation of hormones which is responsible for root growth and seedling establishment. Nanotechnology will play a vital role in the development of the agricultural sector, as it is capable of being used in agricultural products that protect plants and monitor plant growth and detect diseases. Nanotechnology considers a novel key to growing agricultural production through implementing nutrient efficiency, improve plant protection practices also. Nanotechnology may have real solutions for various agriculture problems like improved crop varieties, plant protection, detect diseases and monitor plant growth. However, fewer studies have investigated the broad application of nanoparticles in pest and disease management, offering an opportunity for future research in crop protection.

Automatic Pill Dispenser
Authors:-Rutuja.S.Sangade, Gauri.P.Dhumal, Onkar.R.Dhole, Arya.P.Gaikwad, Pranav.A.Dhakate, Onkar.D.Gaikwad, Siddhant.K.Doiphode

Abstract-In today’s world full of rat race people forget to take care of themselves and their loved ones. And as far it goes for the medicines many geriatrics rely on medications for keeping themselves healthy which is understood as medicines are intended to help us live a longer and healthier life but this also means sorting the medicines according to given time and doses taking the wrong medicines or taking medicines in the wrong way can lead to dangerous consequences. Making mistakes with doses, the number if doses are to be taken and the medicines that are to be included in those doses are some medication problems faced by geriatrics which might lead to unnecessary hospital/doctor visits and may lead to illness or even death. So, it becomes necessary to design an Automatic Pill Dispenser for those geriatrics who take their medications without any supervision. This paper proposes an Automatic Pill Dispenser that dispenses the right pill in the right amount as per the prescribed schedule as well gives reminder to those who are dependent for daily medications.

Womenpreneurship: A Veritable Weapon against Female Gender Marginalization for Socio-Economic Development in Nigeria
Authors:-Godson Christian Osita

Abstract-The marginalization of female gender in Nigeria remains a significant hindrance to both economic and social advancement. Womenpreneurship, a portmanteau of “women” and “entrepreneurship,” which refers to the entrepreneurial activities and initiatives undertaken by women, has emerged as a successful approach to tackle the prevalent issue of gender marginalization in Nigeria (Awak 2022; Yousafzai, Fayolle, Saeed, Henry, & Lindgreen. 2021). This article explores the importance of Womenpreneurship as a powerful strategy for tackling female gender marginalization in Nigeria. This study examines the socio-economic significance of women’s entrepreneurship, the challenges faced by women entrepreneurs, and the potentials of Womenpreneurship to advance gender equality and foster inclusive economic growth. This study also highlights the need of enacting targeted policies and support structures to empower women entrepreneurs and promote their active participation in Nigeria’s economic landscape.

The Impact of Government Expenditure in Addressing Human Development Inequality in Lampung Province
Authors:-Karina Rahmi Maulidya

Abstract-Development is an ongoing process of change within a society that involves improvements in quality of life, economic progress, social development, and infrastructure enhancement. The UNDP introduced the concept of the Human Development Index (HDI) to measure the improvement of human quality of life. This concept is known as the IPM in Indonesia. The purpose of this study is to analyze the efficiency of local government spending in the education, health, and economic sectors on IPM in Lampung Province using the Stochastic Frontier Analysis (SFA) method. The results of the panel data regression analysis show that spending in the education, health, and economic sectors has a significantly positive impact on the education, health, and economic indexes. The SFA analysis indicates that the use of spending in the education, health, and economic sectors in the districts of Lampung Province has been efficient.

A Web Management Platform for Coronavirus Detection Using CNN
Authors:-Sanitha Sajikumar

Abstract-A web-based platform designed for the identification of coronavirus infections through analysis of chest X-ray scans. Amidst the global pandemic, rapid and accurate diagnosis is paramount. Our platform offers healthcare professionals a streamlined interface to upload and examine X-ray images, utilizing cutting-edge machine learning techniques. By harnessing advanced image processing and deep learning algorithms, our platform aims to expedite the detection process, facilitating early intervention and treatment. Moreover, it provides intuitive visualization tools to aid in result interpretation. Our solution represents a promising advancement in the battle against COVID-19, empowering healthcare providers with a reliable means of screening and monitoring infections through accessible medical imaging data. Our technology uses deep learning models and image processing techniques to help diagnose and treat COVID-19 patients as soon as possible. The software also provides visualization capabilities to help with decision-making and result interpretation. Our method has the potential to be an effective tool in the pandemic response, allowing for the fast screening and tracking of coronavirus infections using easily accessible medical imaging data. The Medical Website is named as Medico.

A Review Casting Defect Reduction in Manufacturing Industry Using Six Sigma
Authors:-Scholar Akshay Arzare, Professor Yogesh Ladhe

Abstract-The art of meeting customer specifications, which today is termed as “quality”. Quality is the symbol of human civilization, and with the progress of human civilization, quality control will play an incomparable role in the business. It can be said that if there is no quality control, there is no economic benefit. In the current world of continually increasing global competition, it is imperative for all manufacturing and service organizations to improve the quality of their products. In today highly competitive scenario, the markets are becoming global and economic conditions are changing fast. Customers are more quality conscious and demand for high quality product at competitive prices with product variety and reduced lead time. It is a data-driven quality strategy used to improve processes. Therefore, this paper aims to review casting defect reduction in manufacturing industry using six sigma.

A Review on Quality Management of Propeller Shaft Using Seven Quality Tools
Authors:-Scholar Sourav Choukade, Assistant Professor Vipul Upadhyay

Abstract-Quality, a beacon of human civilization’s advancement, signifies not just the excellence of a product or service, but the very essence of progress itself. As humanity marches forward, propelled by innovation and ingenuity, the significance of quality control in business becomes indisputably profound. Indeed, it can be unequivocally stated: without quality control, economic prosperity remains an elusive dream. In today’s landscape of relentless global competition, manufacturing and service entities alike find themselves at a pivotal juncture. The imperative to enhance the quality of their offerings looms large, casting a shadow over complacency and mediocrity. In this era of heightened consumer discernment and ever-evolving market dynamics, organizations are compelled to embark on a relentless pursuit of perfection. The ethos of quality control permeates every facet of modern enterprise, from meticulous production processes to attentive customer service. It is the cornerstone upon which reputations are built, and the currency through which trust is earned. By embracing quality as a guiding principle, businesses not only meet the demands of today but also lay the groundwork for sustained success in the future.

Qualitative Phytochemical Screening of Hydrocotyle Umbellata Leaf Extract
Authors:-Monisha A, Assistant Professor Dr. N. Gunavathy

Abstract-Hydrocotyle umbellata, commonly known as water pennywort, is renowned for its medicinal properties in traditional medicine. This study aimed to conduct a qualitative phytochemical analysis of Hydrocotyle umbellata leaf extract to identify its chemical constituents. Various standard phytochemical tests were employed to detect alkaloids, flavonoids, tannins, saponins and other secondary metabolites. The findings contribute to understanding the chemical composition of Hydrocotyle umbellata and its potential pharmacological applications.

Protecting Circuits with Over Voltage and Under Voltage Protection System with Triggering Circuit
Authors:-Barkat Ali Lone

Abstract-Consistently more research is made in the field of electrical energy explicitly in photovoltaic/warm (PV/T) authorities, which is a blend of both electrical advancements. Specialists have focused on this framework setup since it has an improved generally productivity, with a correlation with both photovoltaic (PV) and electrical authorities, and it spares space utilizing one region for two frameworks as opposed to utilizing two zones. In this paper we have proposed a PV array based technique that is used for enhancing MPPT. It improves the power fluctuation and reduces the voltage uses.

Advancing Microgrid Systems: Analysis and Optimization for Enhanced Performance
Authors:-Umi Roman, Assistant Professor Er Kamaljeet Singh

Abstract-Microgrids, small-scale power supply networks, can operate independently or in conjunction with the main grid, offering a resilient and sustainable energy solution. To maximize their efficiency and reduce power consumption, clustering mechanisms have emerged as a pivotal strategy. These mechanisms involve grouping interconnected microgrids or distributed energy resources (DERs) to optimize load balancing, enhance energy storage management, and streamline demand response. By employing advanced clustering algorithms, microgrids can dynamically adjust to fluctuating energy demands and integrate renewable energy sources more effectively, minimizing energy wastage. Clustering also facilitates improved coordination between microgrids, ensuring reliable power distribution and reducing overall operational costs. This paper explores various clustering techniques, such as k-means, hierarchical, and fuzzy clustering, and their application in enhancing microgrid performance. The findings demonstrate that clustering mechanisms not only improve energy efficiency and reliability but also contribute to significant cost savings and environmental benefits by optimizing resource utilization and minimizing dependency on traditional fossil fuels.

Literature Survey on Image Denoising Using Wavelet Transforms
Authors:-Scholar Nidhi Verma, Professor Dr Bharti Chourasia

Abstract-Image processing means we enhance the quality of image to extract useful information from it for further processing and it is a very important in many field such as medical, space, agriculture etc. In this paper we study various authors paper related to image processing and noise. Authors also discuss different type of wavelet filters which are used in removing the effect of noise from images. Image denoising is a principal technique majorly used for original image restoration, segmentation and image classification. It is basically used to refine the images by eliminating. Noise embedded. In the current work, authors present a denoising technique based on Wavelet Domain Filtering. Denoising of images after domain transform helps in separating the noise and data components. One of the main techniques for segmenting, classifying, and restoring original images is image denoising. Its main purpose is to refine the photos by removing embedded noise. The authors of the publication describe a denoising method that uses Wavelet Domain Filtering. After domain transformation, image denoising aids in the separation of the data and noise components.

Automated Health Alerts for in Home Residents (Senior Citizens) Using Sensors and Machine Learning Techniques
Authors:-Keerthana Chandran

Abstract-The techniques and methods used in the automatic alerts of getting chances of one’s health is getting into trouble are described in this paper. A thorough Analysis on the existing systems that helps to identify the health issues and the problems of that Systems Helped to do some advancements in this work, through this work Focus More on Heart diseases by the introduction of sensors that can capture the impacts occurs in heart; Respiratory Rate Sensors ZEPHYRx (respiratory monitoring), and MAX30102 which Uses photoplethysmography (PPG) to measure heart rate by detecting blood flow changes in the skin. Addressing the difficulties of existing system and improving the general functionality of the current system is the main goal of this work. One of the Challenges faced an individual is getting into a stage where disease cannot be cured “Prevention is better than cure” this is the motivation behind this work. health alert systems significantly aid in chronic disease management, addressing the escalating prevalence of conditions like diabetes, hypertension, and heart disease.

An Analysis of Digital Media-Based Voice Activity Detection Protocols
Authors:-Devika, Meenakshi Arora

Abstract-Voice Activity Detection (VAD) is a crucial technology in the field of digital media, enabling efficient and effective audio processing by distinguishing speech segments from non-speech segments. This paper provides a comprehensive analysis of various VAD protocols used in digital media. The study delves into traditional methods, such as energy-based and zero-crossing rate approaches, and contrasts them with contemporary techniques that leverage machine learning and deep learning models. We examine the performance, accuracy, and computational complexity of these protocols, highlighting their respective strengths and limitations. The analysis includes a review of publicly available datasets and benchmarks used for evaluating VAD systems, offering insights into the current state of the art. Furthermore, we discuss the impact of different environmental conditions and noise levels on VAD performance, underscoring the challenges and advancements in robust VAD development. The findings indicate that while traditional methods are computationally efficient and easy to implement, they often fall short in noisy environments. In contrast, machine learning-based methods demonstrate superior accuracy and robustness, albeit at the cost of increased computational requirements. This paper aims to guide researchers and practitioners in selecting appropriate VAD protocols for their specific applications, fostering further innovation in the field of digital media.

The Novel Approach of 5G Network in Electronic Health System
Authors:-Professor Dr P Sumithabhashini, Associate Professor Ramesh Alladi

Abstract-In these years, there has been a lot of focus on how medical and health monitoring devices, remote sensors can contribute to better health for patients and more efficient healthcare systems. The fifth generation of mobile, cellular technologies, networks and solutions, promises high bandwidth, low latency and reliability are highly demanded in order to support the needs of healthcare, it is undeniable that what is needed is the transformation of the healthcare providers-patients relationship by integrating rich- media communications into medical care. A key challenge refers to the amount of this information and the way it is transmitted and processed. The different formats, rates and size of datasets (continuously increasing) raise the need for environments able to manage these datasets in an efficient way, while also incorporating and facilitating the requirements of approaches that aim at analyzing them (e.g. through machine learning and artificial intelligence mechanisms) towards efficient healthcare. In this paper i propose an innovative e Health system powered by 5G network, in order to meet the requirements for establishing an efficient network with high capacity.

Economic Load Dispatch Using Differential Evolution
Authors:-Er.Raman Kumar Sofat, Assistant Professor Kamaljeet Singh

Abstract-The Economic Load Dispatch (ELD) problem is an essential component of power system, aimed at efficiently allocating power generation between various generators to satisfy requirement while reducing prices. This research study describes Differential Evolution (DE) technique for addressing ELD challenges. The primary goal of the proposed DE approach is to minimize the inaccuracy among required and produced loads, as well as the associated unit costs. This goal is achieved by employing DE. Applying Differential Evolution in a specific ELD issue improves converging rate, exploratory capabilities, and the effectiveness of solutions. DE generates the fitness function based on error along with expense reduction that must be minimized to a lowest. The simulations are run on the standard IEEE bus system with six units to match the load demand of 1263 MW. These results demonstrate the suggested technique’s durability and excellence in handling the Economic Load Dispatch (ELD) issue, particularly its ability to maximize power generation with unsurpassed accuracy and economics.

Design and Verification of AHB to APB Bridge Protocol Using UVM
Authors:-Elamathi.G

Abstract-The project focuses on the design and verification of a bridge protocol that connects the AHB (Advanced High-performance Bus) to the APB (Advanced Peripheral Bus) using UVM (Universal Verification Methodology). It aims to create a reliable interface between these two commonly used bus architectures. The design process includes implementing the bridge logic in UVM, addressing critical elements such as data transfer, address mapping, and control signals. Various verification techniques, such as simulation and testing, are employed to ensure the bridge protocol’s accuracy and reliability. The goal is to provide an efficient communication interface between AHB and APB, thereby improving interoperability in complex digital systems. The bridge unit is responsible for converting system bus transfers into APB transfers, including latching the address to maintain its validity throughout the transfer and driving data onto the APB for write operations. Additionally, the project generates a coverage report for the bridge protocol.

The Solution to Unemployment in Rural and Urban Areas
Authors:-Hritik Srivastav, Durgesh Rao, Vaibhav Suman

Abstract-Unemployment is a persistent issue for many Individuals. It is a serious predicament that has persisted for years. The government continues to introduce various schemes, but no permanent solution has been found. Daily wage laborers in the unorganized sector face significant issues due to irregular working hours and wages. I have attempted to address this problem by developing an Android app that connects daily wage workers with employers (who need manpower in construction, farming, fishing head loading, home-based work, etc.)

Experimental Investigation of M35 Concrete by Partial Replacing Fine Aggregate by Marine Sand
Authors:-Balkrishna Kumawat Sarwa, Assistant Professor Mahroof Ahmed, Assistant Professor Kishor Patil

Abstract-The process of depleting sources of natural aggregates challenges the production of technically and environmentally adequate concrete. Alternative material from marine sources is good enough for the replacement of fine aggregate in the concrete. The material was stockpiled in the open air and no washing, drying or decontamination process was carried out. Physical and chemical properties of Marine Sand (MS) material were determined. All the materials used in the concrete were selected and tested as per the standard procedures of the Indian standards. A unique design mix of M35 will be done based on the entire material test results. Different mixtures were produced using MS in different proportions from 25% to 100% as per the finalized trial of the design mix. The concrete were submitted to compressive strength tests, split tensile strength test & flexural strength test after 7 & 28 days of moist curing.

Harnessing the Power of Gen AI & Cloud Computing for Customer Relationship Management
Authors:-Rohit Alladi

Abstract-With rapid technological transformation and dynamic digital landscape partnership of Generative AI (Gen AI) & cloud computing is revolutionizing customer engagement strategies and driving innovations. Gen AI combined with Cloud computing presents unprecedented opportunities for businesses to forge deeper engagement with customers and gain loyalty. In today’s highly competitive business landscape it’s imperative for every business to stay ahead of the curve and address the challenges to avoid churn and focus on driving business growth. These challenges require deployment of the right mix of technologies. Gen AI provides a very powerful mechanism to extend tailor approach to interaction and service provision. while cloud computing offers a scalable, flexible and economic infrastructure for deploying AI powered solutions to meet evolving customer expectations. Having the right combination of Gen AI and Cloud computing enables customer relationship management applications to process vast amounts of data in real-time, empowering businesses towards actionable insights & delivering targeted & hyper personal experiences to the customers.

DOI: 10.61137/ijsret.vol.10.issue3.177

Cryptographic and Non-Cryptographic Approaches for Collaborative Social Network Data Publishing: A Comprehensive Survey
Authors:-Urvashi K. Mandwale, Mansi Kotadiya, Inderjit Kaur

Abstract-Trillions of people worldwide now give their data to social network data providers so they can connect, communicate, and share info with other users. The data supplier may use the gathered information for analytical purposes. On the other hand, a number of data suppliers would rather work together to achieve better analysis results from the pooled data. Due to privacy concerns, the data providers in this partnership share the collected data with the reliable data publisher rather than sharing their data directly. After compiling this gathered data, the data publisher publishes the information. Sensitive personal information about specific people can be found in data gathered from many sources and published on reputable data publisher websites. Hence, if the publisher publishes it in its original form, people’s privacy might be compromised. As a result, many cryptographic and non-cryptographic strategies for publishing collaborative social network data while protecting anonymity are explored in the literature.

Advancements in Generative AI for Image Synthesis
Authors:-Aditya Kumar Sharma

Abstract-Generative Artificial Intelligence (AI) has made sig- nificant strides in recent years, particularly in the field of image synthesis. Techniques such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) have enabled the creation of highly realistic images. This paper explores recent advancements in generative AI, focusing on the improvements in GAN architectures, their applications in various industries, and the challenges that remain. Experimental results demonstrate the enhanced capabilities of state-of-the-art models in generating high-quality images. Future directions for research are also discussed.

Enhancing Job Recommendation Systems through Machine Learning: A Comprehensive Analysis of Skill Sync Job Recommendation System
Authors:-Rupali Sharma, Rupam Maji, Mudabbir Shazan, Rutika Khose, Nidhi Gaikar

Abstract-This study explores the efficacy of employing advanced algorithms and machine learning techniques within job recommendation systems, focusing on precise matching between user profiles and job descriptions. By incorporating factors such as skills, experience, and industry trends, the system optimizes career recommendations, aligning with individual preferences and professional goals. Leveraging resume parsing for user profiles and machine learning algorithms like collaborative filtering for job matching, alongside natural language processing for enhanced understanding, the system offers tailored suggestions. It integrates an email notification system and dynamically generates personalized content, thereby enhancing the job recommendation experience.

DOI: 10.61137/ijsret.vol.10.issue3.167

Theoretical Framework on Accounting for Planet
Authors:-Assistant Professor Ravi Kiran N

Abstract-Planet accounting is one of the very important and contemporary topics as it addresses the impact of business on the environment. In today’s world planet is of utmost important and every organisation must strive to uplift the quality of the planet and not deteriorating it. Planet accounting helps making business responsible from environmental point of view. Present study tries explore the concept of Accounting for planet, by describing various branches and its relevance to the current scenario. Further, study also tries to explain importance of each branch and how can one adopt those methods for the benefit of both organisation, society and Environment. Ultimately, study explains how an accountant can successfully implement accounting for planet in an organisation.

DOI: 10.61137/ijsret.vol.10.issue3.168

Dynamics of Structural Transformation and Employment Opportunities in Indonesia: Panel Data Approach
Authors:-Wetry Putri Yusman, Wiwiek Rindayati, Tanti Novianti

Abstract-This research aims to examine the impact of structural transformation on employment opportunities in Indonesia. This research uses secondary data in panel data (pooled data) consisting of time series data from 2017 to 2022 and cross-section data covering 34 provinces in Indonesia. Secondary data was obtained from literature studies sourced from the Indonesian Central Statistics Agency (BPS). The results of panel data analysis show that the primary sector GDP share, secondary sector GDP share and tertiary sector share variables, which reflect structural transformation, have a positive and significant effect on employment opportunities in Indonesia. Other economic variables such as investment, population, human development index, and average years of schooling positively and significantly affect employment opportunities. Meanwhile, the provincial minimum wage variable does not affect employment opportunities.

Prediction of Stock Market Using Machine Learning
Authors:-Prashant Kumar, Yash Sonawane, Dheeraj Gupta, Snehal Bopche, Shrikrishna Patil

Abstract-Stock Market is a method and technique through which people trade stocks of any listed company. A person can buy one or multiple shares of a company and sell it for a profit or loss depending on his prediction of the movement of the share price. While some people may think of it as gambling, with proper infrastructure and knowledge, the prediction can be perfected for achieving higher profits. With the revolution of data science, machine learning and artificial intelligence, this task has become easier. Predicting the trend and outcomes for any given dataset with a high degree of accuracy and speed is one of the most crucial problems in machine learning. Prior to the development of artificial intelligence and machine learning, statisticians would manually make predictions by plotting graphs and using mathematical models and procedures to identify patterns.

Effect of Projectile on Fiber Metal Laminate (FML) Material from Different Impact Angle
Authors:-Mr. Krunal R. Mandwale

Abstract-The impact resistance of epoxy composites incorporated with bamboo fibres was investigated, focusing on fibre metal laminates (FMLs) fabricated using a hand lay-up technique. The FML specimens were composed of bamboo yarn, aluminum sheets, epoxy resin, and hardener. To assess the behavior of these composites under impact, notched specimens were subjected to varying impact velocities using an instrumented Charpy machine. The objective was to evaluate the energy absorption and fracture toughness of the FMLs at different impact velocities. Results demonstrated how variations in impact velocity influenced the fracture toughness of the bamboo fibre-reinforced epoxy composites, providing valuable insights into their potential applications in engineering materials requiring high impact resistance.

Availability Analysis of Tube in Tube Heat Exchanger
Authors:-Ch. Uday Kiran, Assistant Professor T. Siva Krishna, Associate Professor J A Ranga Babu

Abstract-The Heat Exchangers are used to transfer heat between one fluid and another fluid without allowing two fluids to come into direct contact with each other, the fluids may be either liquid or gaseous form. In this paper we are going to perform analysis for tube in tube Heat Exchanger. The availability Analysis involves the identification of the Heat transfer rate, Entropy Generation, Availability loss. In this paper the availability analysis is performed for tube in tube heat exchanger by considering four working fluids, water, N- pentane, Mineral oil, Glycol, with two flow arrangements, parallel flow and counter flow. And the four working fluids are compared each other. After the availability analysis is performed, graphs are drawn for the four working fluids and compared. It seems to be that the water has high heat transfer rate than other working fluids, also the entropy generation and the availability loss is less for the n- pentane, the efficient fluid is n- pentane in this analysis among the four working fluids.

DOI: 10.61137/ijsret.vol.10.issue3.170

Unlocking Trust: Blockchain’s Role in Auditing and Assurance
Authors:-Associate Professor Dr. Abdul Haleem Quraishi, Associate Professor Dr. Sree Krishna K S

Abstract-In the contemporary landscape of rapidly evolving digital transactions and complex financial ecosystems, the need for transparent, secure, and efficient auditing and assurance practices has become paramount. Blockchain technology, renowned for its immutable ledger and decentralized architecture, emerges as a transformative force in redefining trust within auditing and assurance processes. This study explores the potential of blockchain technology in the field of auditing. By examining existing literature and conducting empirical research, it aims to identify how blockchain can enhance the transparency, efficiency, and reliability of auditing processes. The study highlights current applications, challenges, and future prospects of blockchain in auditing, providing valuable insights for auditors, regulators, and policymakers.

A Comprehensive Review of Skin Cancer Risk Prediction Models
Authors:-Research Scholar Santara Chouhan, Professor Jitendra Khaire

Abstract-We review the development, validation, and adaptation of risk prediction models for both clinical and public applications. Our focus encompasses the challenges encountered at each stage of this process and highlights existing gaps across the continuum of risk prediction model development, which includes numerous published models; validation, with relatively few models being validated; and implementation, with even fewer models being adopted in clinical settings, despite more widespread implementation on websites. We address the design of models for end users and the critical issues related to implementing and evaluating these models, supported by examples from direct experience.

Text and Image Classification Using Shape Context and Bag of Visual Words
Authors:-Pooja, Assistant Professor Meenakshi Arora

Abstract-The rapid growth of multimedia content necessitates robust techniques for text and image classification. This paper presents a novel approach that integrates Shape Context and Bag of Visual Words (BoVW) for effective classification tasks. Shape Context, a descriptor capturing the spatial distribution of points, is employed to extract distinctive features from image shapes. Concurrently, the Bag of Visual Words model is utilized to represent images as a collection of visual words, analogous to the Bag of Words model in text classification. In the proposed method, images are first converted into a set of shape contexts, enabling the capture of geometric and spatial information. These shape contexts are then transformed into visual words through clustering techniques such as k-means, creating a visual vocabulary. Each image is subsequently represented as a histogram of these visual words, facilitating the classification process. For text classification, traditional Bag of Words and Term Frequency-Inverse Document Frequency (TF-IDF) methods are used to vectorize the text data. Experimental results indicate that the integration of Shape Context and BoVW significantly enhances the accuracy and robustness of both text and image classification tasks.

Investigation of Stress Patterns of Trapezoidal Cross Section Specimens Using Experimental Photoelasticity Method and Finite Element Analysis
Authors:-Om Prakash Sondhiya, Roopesh Tiwari

Abstract-In the fields of mechanics and materials science, photo elasticity is a reliable experimental method that provides a visual evaluation and analysis of the distribution of stress in materials that are transparent or translucent. This non- destructive testing technique uses the special property of materials known as birefringence or double refraction to visualize stress on a model under load. The process involves building a physical model that mimics real-world structures, applying mechanical stress to the model, and carefully choosing a suitable photo elastic material that exhibits birefringence. The material undergoes birefringence when it is under stress, which causes changes to its optical characteristics. As a consequence, different stress levels are reflected in the pattern, which makes it easier to identify stress concentrations and possible failure areas and offers insights into how materials behave under varied circumstances. In the current study a photo elasticity unit was used to evaluate the trapezoidal specimen under four different stresses. Next a comparison was made between the experimental analysis results and ANSYS simulation (Finite Element Analysis). Because of its intuitive user interface, the software functions as a virtual laboratory by enabling simulations with user-defined problem parameters that are tailored to the users circumstances.

DOI: 10.61137/ijsret.vol.10.issue3.431

Suitability of Wireless EEG Head Set for BCI Application: Emotiv vs. Neuphony
Authors:-Greeshma Sharma, Rohit Kumar Mishra, Aakash Deep, Saumya Kushwaha, Priyanka Jain, Naveen Kumar Jain

Abstract-This study compared the suitability of consumer- grade wireless Electroencephalography (EEG) headsets to Brain computer interface (BCI) paradigms on open-source and in-house built applications. One participant performed ten tasks using two EEG devices, i.e., the Emotiv EPOC+ and Neuphony. The participant performs a 2-minute eye-close dand eye-open task comprising a resting EEG task.The resting EEG task was carried out to evaluate the signal quality of EEG signals. Subsequently, motor imageryandP300-based speller tasks were performed using open Vibe software for BCI. At the end, participant performed a P300-based 3*3 speller task for an in-house-built BCI application. Preliminary analysis revealed that raw EEG data from Emotiv EPOC+ had a higher SNR compared to Neuphony. However, by treating both sets of data through Independent Coponent Analysis (ICA), we found that the signal quality of Neuphony is on par with that of Emotiv EPOC+. Furthermore, accuracy in BCI application was comparable in both devices, demonstrating their suitability in BCI paradigms. This plethora of measurements gives a thorough comparison that encompasses several features of EEG data for BCI. Our findings indicatethat the Neuphony may be utilised effectively in BCI applications across research and clinical settings with comparable quality to the Emotiv EPOC+.Index Terms-WPT, Inductive and Capacitive power transfer technique, Far field techniques.

DOI: 10.61137/ijsret.vol.10.issue3.173

Examining the Impact of Income Generated from Game Management Areas on Overall Household Income and its Distribution: A Case Study of Rufunsa Game Management Area in Zambia
Authors:-Moses Chiposa, Wen Yali, Yi Xie, Hou Fangmiao

Abstract-Game Management Areas (GMAs) in Zambia are designed to integrate conservation efforts with the economic upliftment of rural households. While local communities have been involved in wildlife conservation in Zambia for an extended period, the socio-economic impact in terms of community participation raises concerns. Residents in GMAs often do not receive sufficient benefits from the natural resources in their vicinity. Surrounding wildlife sanctuaries are marked by severe poverty, hindering local inhabitants from deriving adequate livelihoods. This research aims to contribute to the existing knowledge by exploring (i) income-generating activities in GMAs, (ii) the influence of GMA-related income on overall household income, and (iii) the distribution of GMA-related income among villages in Rufunsa District, Zambia. Employing descriptive statistics, multiple linear regression analysis, and the Gini coefficient, the study yielded noteworthy findings. Regression results indicate that 75% of the selected variables significantly correlate with total household income at both p < 0.01 and p < 0.1, except for honey, which, although positively related to total household income, is not statistically significant. Notably, wild vegetables display a negative coefficient and lack a significant association with total household income. Consequently, GMA-related income exhibits a positive impact on total household income in Rufunsa GMA. The Gini coefficient results (0.3) further reveal a relative equality in the distribution of GMA-related income among the fourteen villages in Rufunsa GMA. Despite the promising socio-economic outcomes demonstrated by Rufunsa GMA, additional efforts are imperative to enhance tangible and intangible benefits for local communities, ensuring the sustainable management of both wild animals and forests.

A Comparative Analysis of Deep Learning Based Object Detection Models
Authors:-Urvashi Verma, Anshul Kalia, Sumesh Sood

Abstract-As object detection has a close relationship to both image interpretation and video analysis, it has captivated a lot of interest in research recently. Modern object detection methods are based on superficial trainable structures and handcrafted characteristics. Their performance rapidly gets static because they construct complex ensembles that combine high-level information from object detectors and scene classifiers with multiple low-level image properties. As deep learning advances quickly, more influential tools that can understand deeper, higher-level, semantic aspects are being developed to solve issues with conventional architectures. In terms of network design, training methodology been presented a review of SSD, YOLOv9 and Detectron2 – three deep learning based object detection frameworks. Additionally, experimental studies are offered in order to contrast different approaches and derive some insightful findings. Lastly, a number of worthwhile objectives and directions are offered as a basis for future research in the fields of object detection and pertinent neural network-based learning systems, optimisation function, etc., these models exhibit dissimilar behaviours. The study has.

Village Savings & Loan Associations (Vsla) Services and Household Welfare: Among Selected Vsla Services in Kamuli District
Authors:-Wolukawu Ambrose

Abstract-This study examined Village Savings and Loan Associations services (VSLA) and household welfare in Kamuli District. In particular, the objectives of the study were to examine the relationship of saving money on household welfare, relationship of providing loans on Household welfare, relationship of pursuing entrepreneurship on household welfare in Kamuli District. A cross-sectional survey design was applied to collect data from randomly and purposively selected samples from a population of 150 VSLA members. Additionally, interviews were conducted on key informants. Data was collected using questionnaires, and interview guides. Quantitative data was analyzed using descriptive statistics and inferential statistics, while qualitative data was analyzed using content analysis. The key findings indicated a moderate but positive significant contribution of savings on household welfare, a moderate positive significant contribution of loans on household welfare, a moderate positive significant contribution of entrepreneurship on household welfare. It was recommended that a fair and reasonable penalty system should be put in place to promote a more conducive savings environment, provision of regular training sessions on the benefits and best practices of savings. VSLAs services should consider offering specialized loan products that cater to specific needs, such as loans for entrepreneurial ventures, education, healthcare, asset acquisition, and emergency funds. VSLA services should offer comprehensive financial literacy programs within the community to help borrowers understand the implications of taking loans, the importance of loan repayment, and strategies for effectively managing finances and clear communication of the loaning process. VSLA services need comprehensive entrepreneurship training programs targeting community members and focus should be on equipping individuals with essential business skills, financial literacy, and knowledge of market dynamics. Lastly, promotion of initiatives that facilitate access to startup capital to improve capital accessibility.

Use of RBI Grade 81 for Stabilization of Expansive Soil
Authors:-Manjula Singh, Professor Dr. P. K. Sharma

Abstract-Subgrade soil failure due to insufficient strength, weak bearing capacity, excessive deformation and desiccation cracking of problematic soils is commonly observed on the road network, and this leads to huge expenditure in the maintenance and repair of highway projects every year. It is necessary to reduce these engineering problems and economic losses through environmentally and economically friendly methods. Previous studies have shown that randomly distributed fibers can significantly improve various soil properties. However, there is a lack of comprehensive study on the engineering properties of fiber reinforced high plastic clay. Also, limited mechanical models have been proposed for predicting the shear strength behaviour of fiber reinforced clay. In order to investigate these problems, a series of laboratory investigations including compaction, bearing capacity, one-dimensional consolidation, linear shrinkage, desiccation cracking, direct tensile strength, compression tests should be conducted on unreinforced and Coir fiber reinforced Clay. For this study, the soil samples were prepared with different proportions of RBI grade-81 i.e. (2%, 4%, 6% and 8% of soil) respectively. After that the coir fibers in different ratio i.e. 0.5%, 1%, 1.5% and 2% respectively will be added to the sample containing suitable content of RBI grade-81. Then OMC, MDD and CBR values evaluated for these sample.

Lighter-Than-Air Revolution: Advancements in Airship and Aerostat Materials
Authors:-Mukta Tiwari

Abstract-Lighter-than-air (LTA) vehicles, including airships and aerostats, are experiencing a revival due to advancements in materials technology. This paper explores these advancements, highlighting the transition from traditional materials like rubberized cotton fabrics and polyester films to modern high-strength fabrics, composite materials, and nanomaterials. The paper discusses how these advancements address critical challenges like gas retention, weather resistance, and flexibility. Additionally, it explores innovations in envelope materials for thermal insulation and heat management. Advancements in gas management systems, including improved gas cells and smart materials, are also addressed. The paper concludes by showcasing applications in military and surveillance, commercial and civil uses, and environmental monitoring. Finally, it discusses remaining challenges concerning cost, scalability, and sustainability, while highlighting promising research trends in recyclable materials, self-healing materials, and electric propulsion systems. Overall, this paper emphasizes how material advancements are propelling a new era for LTA technology.

Plant Disease Detection Using Deep Learning
Authors:-Saranya.T, Ananda Selva Karthik.T

Abstract-Deep learning, a subfield of artificial intelligence, has garnered significant attention in recent years due to its capabilities in automatic learning and feature extraction. This paper provides a comprehensive review of the research progress in utilizing deep learning technology for the identification of crop leaf diseases. The advantages of deep learning, including objective feature extraction and improved research efficiency, are highlighted, particularly in comparison to traditional methods reliant on manual feature selection. Moreover, the paper discusses the current trends, challenges, and advancements in the detection of plant leaf diseases using deep learning and advanced imaging techniques. By presenting both the progress and the unresolved challenges, this review aims to serve as a valuable resource for researchers in the fields of plant disease detection and pest management.

Review of Use of RBI 81 Along with Coir Fiber for Stabilisation of Expansive Soil
Authors:-Manjula Singh, Professor Dr. P. K. Sharma

Abstract-Expansive soil is considered one of the most common causes of pavement distresses. Depending upon the moisture level, expansive soils will experience changes in volume due to moisture fluctuations from seasonal variations. During periods of high moisture expansive will “swell” underneath pavement structure. Conversely during periods of falling soil moisture, expansive soil will “shrink” and can result in significant deformation. These cycles of swell and/or shrinkage can also lead to pavement cracking. Puppala et al. (2006) implied that expansive soils encountered in various districts particularly in northern Texas are the primary causes of pavement failures. Expansive soils located in regions where cool and wet periods followed by hot dry periods are more prone to such problems.

Early Warning Prediction System for War and Crisis Response
Authors:-Uroosa Mukri, Dr. Dhananjay Dakhane

Abstract-The report presents a sophisticated early warning prediction system tailored for anticipating conflicts and crises, particularly in the realm of war and crisis response. Leveraging the power of Natural Language Processing (NLP) and Autoregressive Integrated Moving Average (ARIMA) techniques, the system meticulously analyzes vast amounts of textual data sourced from diverse online news sources. By distilling insights from this data, the system aims to provide stakeholders with timely and precise assessments of potential threats and intensities, facilitating proactive interventions and strategic decision-making. The methodology encompasses data collection, preprocessing, feature engineering, model development, and rigorous evaluation, ensuring the system’s reliability and effectiveness in forecasting and preempting conflicts. In addition to its robust methodology, the early warning prediction system employs cutting-edge machine learning algorithms to continuously adapt and refine its predictive capabilities. Through iterative learning and feedback mechanisms, the system can dynamically incorporate new data sources, refine feature selection techniques, and enhance model performance over time. Moreover, the integration of domain-specific expertise and contextual understanding further enriches the system’s predictive accuracy, enabling it to discern subtle nuances and emerging patterns in geopolitical landscapes. This holistic approach empowers decision-makers with action- able insights and foresight, enabling proactive measures to mitigate risks, foster diplomatic resolutions, and promote sustainable peace-building efforts on a global scale.

Electric Vehicle Battery Health Monitor with Static Cooling System
Authors:-Professor Ashvini. H. Kale, Professor Gayatri B. Ghangale, Professor Deepak U. Chaudhari, Professor Sanika S.Lokhande

Abstract-The temperature of an electric vehicle battery system influences its performance and usage life. To prolong the lifecycle of power batteries and improve the safety of electric vehicles, this paper designs a liquid cooling and heating device for the battery package. On the device designed, we carry out liquid cooling experiments and preheating experiments. Then, a three-dimensional numerical model for the battery package is built, and its effectiveness is validated by comparing the simulation results with the experimental outcomes in terms of battery surface temperature and temperature difference. Furthermore, we investigate the influences of the liquid flow rate and the inlet temperature on the maximum temperature and temperature difference of batteries by the cooling and preheating models. Results show that: at the cooling stage, it can keep each battery working at an optimal temperature under different discharge conditions by changing the flow and the inlet temperature of liquid; at the heating stage, large flow rates and high inlet temperatures can speed up the preheating process, thereby saving time of the drivers.

Pupil’s Homework Engagement and Learner Academic Achievement in Universal Primary Education Schools in Moroto District, Uganda
Authors:-Ilukol Rose Peggy Nakoru, Dr. Patience Tugume

Abstract-When the government introduced Universal Primary Education (UPE) in Uganda, there was an increase in numbers of students attending school. Despite the increased numbers of learners, academic achievement of students is still low, many of the learners cannot read and write and also the skills of pupils aren’t being developed. The study examined the relationship between Pupil homework engagement and learner academic achievement in UPE schools in Moroto District. The study was guided by the following objectives: To examine the relationship between: i) homework time management and learner academic achievement, ii) amount of homework and learner academic achievement, ii) time spent on homework and learner academic achievement. A cross-sectional correlational survey research design, drawing on both quantitative and qualitative approaches with a sample size of 304 consisting of teachers and pupils from 13 primary schools in the sub-counties of Nadunget, Tapac and Rupa was used. Qualitative data was collected from headteachers from each sub-county. Homework Time Management (HTM), Time spent on homework (TSH) and Actual amount of homework done (AHD) has a positive relationship with Learner Academic Achievement (0.472, 0.514, 0.398) respectively based on the results from data collected from pupils. Furthermore, Homework Time Management (HTM), Time spent on homework (TSH) and Actual amount of homework done (AHD) has a positive relationship with Learner Academic Achievement (0.516, 0.367, 0.529) respectively based on the results from data collected from teachers. The study recommends that; Schools need to sensitize students to create a checklist of everything they need to get done in the homework assignments. Parents need to be sensitized by schools on helping their children to create a master schedule which can help learners to take note of the time to be spent and timetable to be used on tasks and anything else they need to do in a homework task within a prescribed time. Therefore, schools need to sensitize students to tackle the homework tasks in bits which enriches learning. The results will be of benefit to learners because it highlights how to manage time while attending to homework assignments. The study is also of benefit to parents because it highlights the role they can play to make homework assignments a success .

Analyzing the Quasi-Static Behavior of Fiber Composite Filament Used in 3D Printing Applications
Authors:-Assitant Professor J Kaleeswaran, N Natraj S, Nandha Kumar R

Abstract-The rapid evolution of 3D printing technologies has catalyzed the exploration of new materials designed to enhance the mechanical performance and reliability of printed structures. Among these materials, fiber-reinforced composite filaments offer significant advantages due to their enhanced mechanical properties and light weight. This project aims to investigate the quasi-static behavior of fiber composite filaments, particularly focusing on their performance under various load conditions. The primary objective is to characterize the mechanical properties of these composite materials when subjected to slow rates of loading, providing crucial insights into their applicability in 3D printing applications. To achieve this, an experimental study involving tensile, compression, and bending tests will be conducted on different types of fiber composite filaments, including those reinforced with glass and carbon fibers. Additionally, this study will explore the impact of environmental factors such as temperature and humidity on the mechanical performance of these filaments, which is critical for their application in diverse climatic conditions. The findings of this research could significantly contribute to the development of more robust and efficient materials for 3D printing, potentially leading to broader industrial applications. The results of this study are expected to provide valuable guidelines for the design and selection of fiber composite filaments for 3D printing, ensuring optimal performance and durability of the printed objects. Through this comprehensive analysis, this project will enhance the understanding of the quasi-static behavior of composite materials and pave the way for their advanced applications in the realm of additive manufacturing.

Design of Pre-Stressed Concrete Slabs (Grade of Concrete: M40)
Authors:-Ravi Shankar Singh, Mr. Chitranjan Kumar (Assistant Professor)

Abstract-Prestressed concrete is a method for overcoming concrete’s natural weakness in tension. It can be used to produce beams,floors,or bridges with a longer span than is practical with ordinary reinforced concrete. Prestressing tendons are used to provide a clamping load which produces a compressive stress that balance the tensile stress that the concrete compression member would otherwise experience due to a bending load. The design of prestressed concrete slabs has emerged as a crucial area in modern structural engineering, offering significant advantages over traditional reinforced concrete systems. This project aims to develop an optimized design methodology for prestressed concrete slabs, focusing on enhancing load-carrying capacity, minimizing material usage, and improving overall structural performance. The research encompasses a comprehensive analysis of various prestressing techniques, material properties, and slab configurations. Through the application of advanced computational tools and finite element analysis, the project evaluates the behavior of prestressed slabs under different loading conditions. Key design parameters, such as tendon layout, prestress level, and slab thickness, are systematically investigated to determine their impact on structural efficiency and durability. The findings contribute to establishing design guidelines that ensure safety, cost-effectiveness, and sustainability in construction practices. Ultimately, this project aims to provide practical insights and innovative solutions for the implementation of prestressed concrete slabs in diverse civil engineering applications.

A Study on Service Quality and Patient’s Satisfaction towards Government Hospital in Nilgiris District
Authors:-Assistant Professor Dr. M.R. Chandrasekar, Ms. Sukirtha.P.M

Abstract-This study aims at the relationship between service quality and patient satisfaction in government hospitals in the Nilgiris district. Understanding the characteristics that lead to patient satisfaction is becoming increasingly important as healthcare services shift toward patient-centered care. To collect thorough data, the study uses a mixed-methods strategy that combines quantitative surveys and qualitative interviews. The findings indicate that service quality factors such as responsiveness, reliability, empathy, assurance, and tangibles have a substantial impact on patient satisfaction levels. The analysis identified five critical elements of service quality—responsiveness, reliability, empathy, assurance, and tangibles—that have a significant impact on patient satisfaction. Statistical analysis found variable degrees of influence across these characteristics, underscoring the complexities of patient experiences in public healthcare systems. These findings are helpful to legislators, hospital administrators, and healthcare practitioners working to improve service quality and patient satisfaction in public healthcare settings. This investigation provides significant information for healthcare regulators, administrators, and providers looking to improve service performance and patient satisfaction in government hospitals. Addressing these results can help stakeholders create environments that promote patient-centered care and aim for better healthcare outcomes in the Nilgiris district and beyond.

Do-It-Yourself-Recommender System
Authors:-Dr. Ravva Santosh Kumar, Ravula Tanishq, Chandan Mishra

Abstract-Rapid urbanization with population growth leads to a sharp increase in waste generation, which causes significant environmental damage. Despite the daunting nature of this challenge, it can be effectively managed by promoting waste recovery. In our research, we propose a new approach that uses machine learning and blockchain technologies to solve this problem. Our system uses a Deep Neural Network (DNN) based on the Efficientnetb0 architecture, which is trained on about 11,700 images and achieves a training accuracy of 94% in identifying garbage objects. We have developed a complete solution where DNN detects garbage objects and makes suggestions. several do-it-yourself (DIY) ideas to reuse or recycle them. To ensure transparency and make decision- making more efficient, all transactions are recorded in a blockchain ledger that allows verification and validation of DIY ideas proposed by network participants. The integration of smart contracts with the Ethereum blockchain platform further improves the reliability and security of our system. Our template is accessible through a user-friendly web platform built with Streamlit, which includes a web-capture script written in Python that effectively sources DIY ideas. . Scraping the web typically takes about a second on a desktop computer running Ubuntu 18.04 64-bit with an Intel Core i7 processor, 16GB of RAM, and Python 3.6.In addition, we perform a blockchain performance evaluation. based on smart contracts that evaluate latency and performance using Ethereum benchmarking tools. To our knowledge, our research is a pioneering effort to integrate blockchain technology and deep learning to develop a DIY recommendation system to address waste management challenges.

Power Meter Billing Plus Load Control
Authors:-Prachi Dukate, Priyanka Gajakosh, Niranjan Kini, Siddhesh Rasam

Abstract-Electric utilities load shed when there is huge demand for electricity exceeding supply or if power generated is less than the consumers demand, the need to shed load is eminent in order to avoid total breakdown of equipment’s used by power distribution companies as a result of overloading effect. Power failure in the power system is mainly due to the overloading. The possible damage to the area is losing a power. The ESP32 based load control system is a device which automatically control overload on supply by controlling power and cut-off supply whenever system exceeds the amount of power supplied for peak period.

Study and Analysis of Substation Mitigation Techniques Using MATLAB
Authors:-Kapil Dev Sharma, Mr. Harpreet

Abstract-This thesis presents the techniques to mitigate transients caused by capacitor switching in the distribution system. It includes the theory of capacitive switching transients with different methods of mitigation. The thesis uses MATLAB/SIMULINK software package to simulate the specific mitigation devices. The mathematical calculations of different parameters such as transient voltages, current, and frequencies for each device are compared with obtained value from the simulations of each case study POWER-FACTOR improvement increases transformers and lines capacities, decreases the power loss of distribution feeders, improves voltage drops and minimizes the electric bills for consumers [1, 2]. Inrush current leads to make failure for system equipment.

Influence of Strategic Management Practices on Financial Performance of Small and Medium Manufacturing Firms in Nairobi County, Kenya
Authors:-Abdullahi Mohamed Ali, Dr. Francis Kijogi Mutegi

Abstract-The business environment has become more competitive, resulting in increased consumer alternatives, reduced pricing, increased competition, and lower profit margins, all of which have increased the importance of strong strategic marketing practices. The main objective of the study was to determine the effect of strategic management practices on financial performance of SMEs in Nairobi County. The specific objectives of this study were to determine the influence of environmental scanning, market positioning practices, cost leadership practices and differentiation practices on financial performance of manufacturing SMEs in Nairobi County. The study was guided by three main theories including McKinsey 7s Model, Resource-Based Theory and Game Theory. This study used a descriptive research design which aims at revealing the actual phenomenon in question exactly the way it is without any alterations. The population for this study were 58 managers and owners from 58 manufacturing SMEs in Nairobi County. This study employed a census sampling approach in selecting the sample population for the study and target respondents were the managers, owners or their equivalents in the SMEs. Data was collected using questionnaires and analyzed using descriptive and inferential analysis. The findings of the descriptive statistics indicate that environmental scanning practices play a significant role in influencing the financial performance of manufacturing SMEs in Nairobi County. The analysis of market positioning practices suggested a mixed level of utilization among manufacturing SMEs in Nairobi County. The model summary indicated that the combination of Differentiation Practices, Market Positioning Practices, Environmental Scanning, and Cost Leadership Practices explains approximately 29.9% of the variance in financial performance (R square= 0.299). the adjusted R square, which accounts for the number of predictors in the model, stands at 0.241, suggesting a relatively moderate fit. Additionally, market positioning, cost leadership, and differentiation practices also demonstrated positive and significant coefficients (β= 0.182, p= 0.015; β= 0.325, p= 0.043; β= 0.329, p= 0.012, respectively), indicating their importance in enhancing SME financial performance. The study revealed that cost leadership practices significantly influence the financial performance of manufacturing SMEs in Nairobi County. The study concluded that environmental scanning plays a significant role in influencing the financial performance of manufacturing Small and Medium Enterprises (SMEs) in Nairobi County. Contrary to expectations, the study found that there is no statistically significant relationship between market positioning practices and financial performance among SMEs in Nairobi County. The study recommended that manufacturing SMEs in Nairobi County prioritize and enhance their environmental scanning practices to improve their financial performance.

Empowering Smart Cities: Exploring the Role of IoT in Urban Transformation
Authors:-Chaitanya Labhe, Mayur Patil

Abstract-The integration of Internet of Things (IoT) technology within urban settings has emerged as a transformative force, exerting a profound influence across diverse sectors such as transportation, utilities, public safety, and sustainable urban development. Within transportation, IoT facilitates real-time traffic monitoring, enhances the efficiency of public transit systems, and simplifies parking processes, all of which contribute to mitigating congestion and improving the overall commuter experience. In utilities management, IoT-enabled solutions like smart grids, meters, and waste management systems optimize resource allocation, fostering sustainability by minimizing waste and maximizing efficiency. Public safety also stands to benefit significantly from IoT innovations, with smart surveillance and emergency response systems bolstering law enforcement capabilities and aiding in disaster management scenarios. Furthermore, IoT plays a crucial role in public health monitoring, enabling the tracking of air quality and disease spread to facilitate timely interventions and mitigate health risks. The concept of sustainable urban development is further advanced through IoT technologies, which allow for the optimization of energy consumption, transportation networks, water management systems, waste disposal processes, and environmental monitoring. This holistic approach to urban management not only enhances efficiency but also elevates the overall quality of life for residents. Despite the immense potential of IoT, its widespread implementation encounters various challenges, including concerns related to security, technological limitations, infrastructural barriers, and socioeconomic disparities. However, ongoing advancements in IoT, such as the integration of 5G connectivity, artificial intelligence, sensor technology, urban digital twins, and blockchain solutions, hold promise for overcoming these obstacles and ushering in an era of smarter, more sustainable, and inclusive cities.

DOI: 10.61137/ijsret.vol.10.issue3.172

Tap Water Disinfection in the Electrochemical Precipitation Process by Using Novel Conductive Concrete
Authors:-Md. Shoriful Islam, SK Imdadul Islam, K M Risaduzzaman

Abstract-The effect of electrochemical precipitation (EP) on tap water disinfectants is being investigated. Without the use of chemical additives, this procedure involves delivering electricity through electrodes submerged in water to precipitate dissolved metals, such as hardness. This study assesses the impact of EP on disinfectants in tap water. In addition to hardness, residual disinfectants found in tap water are essential for preventing possible pathogens from entering the water supply before they reach customers. Free chlorine levels in drinking water must be kept between 0.2 mg/L and 4 mg/L, according to USEPA regulations. The chemical makeup of chlorine species can change during the EP process due to pH variations close to the electrodes. In contrast to the sacrificial metallic cathodes used in traditional EP procedures, a newly created conductive concrete block is used in this work. Constructed from concrete, these blocks have conductive graphite flakes imbedded in them. The purpose of the study is to quantify the amounts of free and total chlorine in tap water under various treatment circumstances, including pH levels, chloride concentrations, current densities, and treatment times. Greater amounts of free chlorine disinfectants are found in water with greater chloride concentrations, longer treatment periods, and higher current densities, according to preliminary research findings. This study presents conductive concrete and EP as a novel way to eliminate hardness and maybe improve disinfection. It seeks to present early data demonstrating its effectiveness and value addition as a disinfection technology.

DOI: 10.61137/ijsret.vol.10.issue3.174

Productivity of Rice Production: A Study of Ecowas Countries
Authors:-Losene A M Talawally, Dr. Sakshi, Dr. Aasif Ali Bhat

Abstract-This study aims to analyze how productive the countries in the Economic Community of West African States (ECOWAS) are in producing rice. Rice is a vital staple food that contributes to food security, hunger reduction, and poverty alleviation for a large segment of the ECOWAS population. However, rice importation and prices are high across the region, reflecting the low domestic production. This study considers the role of agriculture in the economy and the diversity of resources among the countries, and evaluates the effect of various inputs such as labour, harvested area, fertilisers, and energy (electricity) on rice cereal production at the country level from 2011 to 2020. This study uses Malmquist Productivity Index (MPI) to measure the performance of countries. The findings indicate that the performance of countries differs, with six out of 11 countries have increased their productivity over the time period studied. According to the study, improved production management can help optimize the inputs and increase rice production.

Sewage Waste Water Treatment by the Hydrodynamic Cavitation Method
Authors:-Chanchal Valvi, Dr. Pankaj Gohil, Dr. Hemangi Desai

Abstract-The sewage water sample obtained after secondary treatment, was given treatment with Hydrodynamic Cavitation Method. Physico chemical parameters were determined using standard methods of APHA, before and after treatment at 24 hour in cavitation device. the water quality obtained is comparable to Drinking Water Standards (IS). The water quality parameters selected were: pH, Electrical Conductivity, Turbidity, TS,TSS, TDS, DO, Cl- ,Alkalinity (as CaCO3), Cu2+ ,Zn2+ ,Mg2+ Hardness, Total Hardness (as CaCO3), Phosphate and BOD. The highest reduction obtained was 88.88% for Cl- . Except TS, TSS and Cu2+ all the parameters were get back in the range of drinking water quality standards. The mechanism supports the reduction in parameter may be due to the collapse of cavities induces effects such as high shear forces, extreme temperatures, shock waves, turbulence, and extreme pressure in the fluid, formation of OHo free radicals provide to reduce pollution. The Cavitation method is proven to be the most effective over the other methods. Because, it does not require any chemical reagent, hence do not produce any hazardous chemical waste and maintain eco-friendly and economically sustainable environment benign technique for the treatment of wastewater.

DOI: 10.61137/ijsret.vol.10.issue3.185

Numerical Study of Flow Over NACA 2412 Airfoil at Various AOA’s
Authors:-Nadirge Chandravadan

Abstract-An aerodynamic study was conducted to examine the effect of airflow around the NACA 2412 airfoil using CFD methods. The airfoil’s coordinates were taken from the airfoil database and imported into a geometry modeler. A mesh was created, and simulations were performed using Fluid Flow (Fluent) software. The study involved solving the governing equations (Continuity, Reynolds Averaged Navier-Stokes, and Energy Equation) in 2-D using Fluent. Graphs were made to compare lift (CL) and drag (CD) coefficients at different angles of attack (α). Results showed that lift and drag forces increased with the angle of attack until reaching the stall point. The optimal angle of attack was found to be 8 degrees, where the NACA 2412 airfoil produced the highest lift-to- drag ratio. The critical stall angle was 16 degrees. Beyond this angle, the lift force decreased, indicating stall. The CFD simulation results closely matched the experimental results, indicating that CFD is a reliable alternative for determining drag and lift.

DOI: 10.61137/ijsret.vol.10.issue3.184

New Way of Identification in Web3 – Soul Bound Tokens
Authors:-Punith N

Abstract-As the digital landscape continues to evolve, the emergence of Web3 has brought forth a paradigm shift, emphasizing the transmission of financialized assets over the recording of social connections of trust. This transformation, while indeed revolutionary, has also faced criticism for promoting an atmosphere of extreme financialization, frequently emphasizing speculative activities and immediate gains over sustained value generation. In response to this critique, this research paper delves into the exploration of non-transferable “soulbound” tokens (SBTs), a novel concept proposed by Ethereum founder, Vitalik Buterin, as a mechanism to foster trusted networks within the digital economy. Soulbound Tokens, uniquely tied to individual users, resist the hyper-financialization of Web3 by holding value despite being non-transferable. They embody a fresh aspect of Web3, which is more community-oriented and less monetarily driven, possibly facilitating a more significant and impactful integration of Web3 into societal structures. As a form of decentralized identity, SBTs have potential applications in establishing trust within networks and implications for digital inheritance, thereby addressing some of the key challenges of the current digital landscape. This research paper presents a comprehensive study of Soulbound Tokens, exploring their theoretical underpinnings, practical applications, and future implications. The study employs a mixed-methods approach, beginning with an extensive literature review to understand the current state of research and identify knowledge gaps. It then moves into the empirical phase, involving primary data collection through surveys and interviews with experts in the field of blockchain technology and decentralized societies, as well as case studies of organizations or networks that have implemented or are planning to implement Soulbound Tokens.The findings from the study suggest that Soulbound Tokens have significant potential in establishing trust within networks, enhancing the credibility of individuals, and addressing issues related to digital inheritance. However, the research also reveals several challenges associated with the implementation of Soulbound Tokens. Despite these challenges and limitations, the research concludes that Soulbound Tokens represent a promising development in the field of blockchain technology and decentralized societies. The insights gleaned from this research contribute to the existing body of knowledge on Soulbound Tokens and have the potential to guide future developments in the field. This research underscores the importance of continuing to explore and understand the evolving digital landscape, particularly as it relates to the development and implementation of innovative concepts like Soulbound Tokens.

Industrial Radiography Testing and Technique or Safety Human Body
Authors:-Professor Dr. Rashmi Shrivastava, Hardev

Abstract-The use of Industrial Radiography for examining the quality of Weld joints is very popular worldwide. In India, many welding activities like construction and laying the huge pipelines for gas and water transportation and distribution as well construction of storage tanks are performed. The objects are working under high pressure and therefore, it is important to produce the weld beads with high quality. Industrial radiography uses ionizing radiation to view objects in a way that cannot be seen otherwise. The method has grown out of engineering, and is a major element of non-destructive testing (NDT) to inspect materials for hidden flaws. The radiation caused by these facilities is very dangerous however, with the use of new technologies and proper protection, risks of injury and death associated with radiation can be greatly reduced. This paper questions the common assumption that an industrial radiographer has role responsibility for job safety, pointing out that the owner, or supervisor in charge of the overall work, has overall responsibility. Management models are proposed in which the owner or supervisor takes a more active role than has usually been the case. It also discusses a radioisotope retrieval incident and recommends a revision to gamma camera designs, proposing that the lock should be fitted to the delivery port not the control port.

DOI: 10.61137/ijsret.vol.10.issue3.175

Demand Forecasting in Textile Industry for Weaving Materials Using AI
Authors:-Prapti Jain

Abstract-Artificial intelligence (AI) is changing the future of several industries, including the apparel and textile sectors. This white paper provides an overview of AI applications for demand forecasting, process innovation, sustainable manufacturing, and defect detection in the textile and apparel industry. This investigate incorporates numerous investigate papers and scholastic articles to appear the critical part of AI, particularly in estimating the request for material fabric. Procedures such as fake neural arrange (ANN), back vector machine (SVM) and information mining procedures are utilized for application forecast and blame discovery. This paper too investigates the affect of AI on organizational effectiveness, supportability and customer behavior within the attire industry. This paper points to supply information on the current state of AI integration within the material industry and the suggestions for future improvement through writing investigation and case considers.

DOI: 10.61137/ijsret.vol.10.issue3.176

Understanding Consumer Perceptions and Behaviour towards Novel Food Innovations
Authors:-Jaya Upraity

Abstract-Consumer perceptions and behaviour towards novel food innovations play a pivotal role in shaping the success and adoption of innovative food products in the market. This abstract provides a comprehensive overview of existing literature and research findings on consumer attitudes, preferences, and behaviours concerning novel food innovations. As the food industry continues to evolve with advancements in technology and changing consumer demands, understanding how consumers perceive and interact with novel food products is essential for food manufacturers, marketers, and policymakers. Consumer acceptance of novel food innovations is influenced by various factors, including sensory attributes, health considerations, cultural norms, and socio-economic backgrounds. Research suggests that while some consumers exhibit openness and curiosity towards trying new food products, others may display scepticism or reluctance due to concerns about safety, authenticity, and ethical implications. Marketing strategies, product labelling, pricing, and social influences also play significant roles in shaping consumer perceptions and purchasing decisions regarding novel food innovations. Furthermore, demographic factors such as age, gender, income, and education level contribute to divergent consumer attitudes and behaviours towards novel food products. For instance, younger consumers often exhibit greater willingness to experiment with new food trends and flavours, while older demographics may prefer traditional foods with familiar ingredients. Understanding consumer perceptions and behaviour towards novel food innovations is crucial for fostering innovation, driving market success, and promoting consumer well-being. By addressing consumer concerns, enhancing transparency, and effectively communicating the benefits of novel food products, stakeholders can facilitate greater acceptance and adoption of innovative food solutions. Future research should continue to explore the dynamic interplay between consumer attitudes, preferences, and behaviours in response to evolving food trends and technological advancements.

Human Machine Interaction Using Dynamic Hand Gesture Recognition
Authors:-Sruthi D K, Shyfija P A, Devananda Praveen, Assistant Professor Ms Aswathy J

Abstract-This is an easy, user-friendly way to interact with robotic systems and robots. An accelerometer is used to detect the tilting position of your hand, and a microcontroller gets different analogue values and generates command signals to control the robot. This concept can be implemented in a robotic arm used for welding or handling hazardous materials, such as in nuclear plants.

Mechanical Properties of 202 Stainless Steel Weld by Using Metal Arc Welding
Authors:-Research Scholar Aazam Bashar, Assistant Professor Dr. Faizan Hasan, Assistant Professor Dr. Mohd Reyaz ur Rahim

Abstract-This paper investigates the mechanical properties of 202 stainless steel welds produced by Metal Arc Welding (MAW). Stainless steel 202, known for its excellent corrosion resistance and high toughness, was welded using MAW to understand the effects on mechanical performance. Various mechanical tests, including tensile strength, hardness, and impact resistance, were conducted on the welded joints. The microstructural changes in the heat-affected zone (HAZ) and the fusion zone were also analyzed using optical microscopy. Results indicated that the MAW process significantly influences the mechanical properties of the 202 stainless steel welds. Enhanced tensile strength and hardness were observed in the welded joints, although a slight reduction in impact toughness was noted. The findings provide valuable insights for the application of MAW in fabricating stainless steel structures where mechanical performance is critical.

Synergizing Deep Learning and IoT: A Tri-Module Approach for Intelligent Home Security
Authors:-Likhith Sai Valluru, Parnashri Nandam, Professor Dr. Y. Rama Devi, Assistant Professor G. Kavita

Abstract-In our current digital phase, ensuring security and safety is paramount, especially when it comes to protecting our homes. Traditional methods, like relying on keys, pose vulnerabilities that can result in oversights and potential security ruptures. A robust home security system is necessary for addressing these concerns. Historically, people have secured their homes with keys, but the risk of theft increases when residents forget to lock their doors. To tackle this challenge, the research at hand leverages Deep Learning and Internet of Things (IoT) technology to elevate home security. The proposed system introduces a door lock mechanism based on facial recognition to ensure that only authorized individuals, such as friends and family, can access the premises, thereby deterring intruders. This forward-thinking solution goes beyond homes, extending its application to workplaces and campuses. Utilizing facial recognition as a seamless means of unlocking doors eliminates the need for physical effort. The system incorporates biometric and two-factor authentication, enhancing security with the integration of OpenCV. This concept combines biometric matching, human face recognition, and Twilio service-powered One-Time Password (OTP) transmission. It is powered by a Raspberry Pi 4 microprocessor. Although face recognition-based door locking systems have been around for a while, this research stands out since it incorporates extra security elements while still being reasonably priced. Consequently, it presents a comprehensive solution for heightened security in various settings.

DOI: 10.61137/ijsret.vol.10.issue3.178

Analysing Profitability Drivers in Indian Commercial Banks: A decade Long Study
Authors:-Research Scholar Jeba Samuel P M, Professor Dr. R. Shanthi

Abstract-The Indian banking industry has been a crucial driver of economic growth in India. However, in recent times, Indian banks have been facing a consistent rise in non-performing assets (NPA). The financial stability and strength of a bank are closely tied to the performance of its own assets. When the quality of these assets deteriorates, it leads to an increase in non-performing assets. This has resulted in public sector banks in India witnessing a decline in their profits and, in some cases, even reporting losses in their financial results. The performance of a bank’s loans is intricately linked to the overall economic conditions and how well the operating economy is faring. We use both return on assets (ROA) and return on equity (ROE) as indicators to gauge the profitability of banks. Our findings suggest that the profitability of banks in India is influenced by a combination of internal and external factors. Factors such as the strength of equity capital and operational efficiency have a notably positive impact on bank profitability. Additionally, a higher ratio of banking sector deposits to the gross domestic product (GDP) also contributes positively to profitability. On the flip side, factors like credit risk, the cost of funds, the ratio of non-performing assets (NPA), and consumer price index (CPI) inflation exert a significant negative influence on banks’ profitability Interestingly, the size of the bank and the ratio of priority loans to total loans do not seem to have any discernible influence on profitability. Moreover, there is a negative correlation between GDP growth and ROA, while inflation has a positive effect on ROE.

Soil Microbial Communities in the Continuous Sugarcane Cropping Fields: A study
Authors:-Ashu Chaudhary, Vikas Kumar, Ankit Kumar, Zehra husaini, Vipin Kumar Saini, Shayma Saifi, Darshika Sharma, Vandana Sharma

Abstract-Soil microbial communities are pivotal for soil health and agricultural productivity, comprising bacteria, fungi, protozoa, and viruses that interact with each other and with plant roots. They break down organic matter, releasing essential nutrients, maintain soil structure, and help protect plants from disease and pests. However, human activities like land use change and chemical use can negatively impact these communities, leading to soil degradation and reduced crop productivity. Continuous sugarcane cropping exacerbates soil degradation, reducing fertility and increasing susceptibility to pests and diseases due to nutrient depletion, soil compaction, and altered microbial balance. To mitigate these impacts, practices such as crop rotation and organic matter application are crucial. This study examines the taxonomic and functional diversity of soil microbial communities in continuous sugarcane cropping fields in Uttar Pradesh. Methodologically, it identifies research questions, evaluates methodology, analyzes taxonomic and functional diversity, interprets results, and communicates findings effectively. Results indicate high microbial diversity but reduced abundance of beneficial taxa due to continuous sugarcane cropping, impacting soil health and sustainability. Adoption of sustainable agricultural practices is essential to support soil health and microbial diversity. Further research is needed to understand the long-term effects of continuous sugarcane cropping and develop mitigation strategies.

DOI: 10.61137/ijsret.vol.10.issue3.260

Isolation and Analysis of Amylase Producing Bacteria from Soil Samples
Authors:-Vipin Kumar Saini, Disha Sharma, Saba Rana, Zehra Husaini, Mohd Salman, Shalini Mishra, Shayma Saifi

Abstract-The aim of this study is to reveal the ability of various isolates obtained from soil to produce amylase enzyme. Soil samples were collected from Shri Ram College nursery. Amylase is an enzyme that catalyzes the hydrolysis of starch into simpler sugars such as maltose and glucose. It is produced by various organisms including bacteria, fungi, plants, and animals, and plays a crucial role in carbohydrate metabolism. A total of 10 species were isolated from soil. The two isolates were showed better results on Nutrient agar starch medium plates. A Gram stain test was carried out to identify the two isolates as Gram-positive rods. Morphological and biochemical analysis on the basis of standard indicated that they all associated mainly with members of the Bacillus sp.

DOI: 10.61137/ijsret.vol.10.issue3.261

Effect of Unique Chromium Reductase Activity on Bioremediation of Chromium in Proteus SP. Isolated from Waste Water
Authors:-Assistant Professor Suhal Sardar, Assistant Professor Aabid Ahmad, Assistant Professor Anjali Jakhar, Assistant Professor Vikrant Kumar

Abstract-This is the first time where Proteus sp. has been isolated from waste water which has higher potential for bioremediation. Chromium (Cr) compounds are used in dyes and paints and in the tanning of leather. So they are found in soil and ground water at abundant industrial sites, now needing environmental clean-up and remediation. More toxic Cr (VI) is reduced by the chromium reducing bacteria to Cr(III) which is less toxic. Isolation of chromium reducing bacteria from water samples from the industrial area of muzaffarnagar was done to observe the effect of Chromium on them, to study their growth curve characteristics and for remediation assay of heavy metal contaminated industrial wastes by evaluating their Cr(VI) reducing ability through chromate reductase activity. Potassium dichromate (K2Cr2O7) and potassium chromate (K2CrO2) were employed for the growth of these bacteria. Attempts were made to isolate the genomic DNA of the organism and to amplify its 16S rRNA gene for identification of the organism using Bioinformatics tools. The organism identified was Proteus sp. Fourier transform infrared (FT-IR) spectroscopic study was performed to obtain information of the possible cell-metal ion interaction. This study has application in terms of bioremediation of metal contaminated industrial waste water with the bacteria isolated from waste water. This process is environment friendly and cost effective. Moreover the chromate reductase enzyme from isolated bacteria can be purified and immobilized which can be further used to detoxify of Cr from tannery wastes.

DOI: 10.61137/ijsret.vol.10.issue3.262

Published by: vikaspatanker

The Effect of an Alcohol Excise Tax Rate Increase on DUI Incidents, Evidence from Connecticut
Authors:-Mason Sheppard

Abstract-This research paper investigates the efficacy of alcohol excise taxes as a policy instrument to reduce the amount of alcohol-related traffic accidents. Using data from the University of Connecticut’s car crash repository and the National Oceanic and Atmospheric Administration, this study conducts an Ordinary Least Squares (OLS) regression analysis to determine the effect that a 2011 increase of 20% on the alcohol excise tax rate had on the daily average DUI rates in Connecticut, while controlling for average daily temperature and time of day. Historical data shows that alcohol excise tax rates have seen significant decreases since the 1970’s, lowering tax revenues and eroding a strong deterrent to alcohol over-consumption. Results indicate that the tax increase of 20% showed a negative correlation to DUI rates, reducing them by an average daily rate of 9.6%. This paper also reviews the literature on alcohol tax incidence and pass through rates, indicating that consumers bear the entire burden of such taxes, enhancing the impact of alcohol excise tax rate changes.

DOI: 10.61137/ijsret.vol.10.issue2.158

Published by: vikaspatanker

AYU E-Health
Authors:-Siddharth Mahankal, Suyesh Shinde, Gayatri Patil, Nashrh Khan, Associate Professor Dr. Rajendra Pawar

Abstract-A certain number of patients attend a hospital or clinic per day. In many Indian hospitals, patient data is still manually managed. If hospitals have an excellent software system for handling patient data, they can save time and money. The concept involves creating web-based application software that may be used to monitor patient registration and visitation data at a medical facility. Additionally, this system must to enable searching for patients by name and retrieving their past visit records. Traditional human record-keeping in hospitals has become a bottleneck in this era of technology innovation, leading to inefficiencies, inaccurate data, and higher administrative costs. The creation of a web-based hospital record-keeping system has become a game-changing answer to these problems. This abstract offers a thorough synopsis of the suggested system, emphasizing its key components, advantages, and possible implications for healthcare administration. The creation of an online platform for hospital record-keeping signifies a significant change in healthcare administration. It claims to transform the administration of healthcare by boosting accessibility, efficiency, and data security. In compliance with data privacy laws, this system has the potential to optimize patient care, lower costs, and raise overall quality of healthcare services. Its effective application may open the door to a new era of superior healthcare administration. This project focuses on the detection of body constitution and its significance in maintaining optimal health through personalized diet and exercise recommendations. Body constitution, often referred to as “Prakriti” in Ayurveda, is a fundamental concept that describes an individual’s unique physiological and psychological characteristics. Understanding one’s body constitution plays a vital role in promoting overall well-being and preventing diseases. The project utilizes a questionnaire-based approach to assess various aspects of an individual’s constitution, such as physical attributes, mental temperament, and lifestyle habits. By analyzing the responses provided by the user, the system employs machine learning algorithms to predict the predominant body constitution based on established Ayurvedic principles. The importance of knowing one’s body constitution lies in its ability to tailor dietary and exercise regimens according to individual needs. Each body constitution has specific dietary requirements and exercise preferences that can help maintain balance and harmony within the body. By adhering to personalized recommendations, individuals can optimize their health, prevent imbalances, and alleviate existing health issues. Through this project, users will gain insights into their unique body constitution and receive personalized recommendations for diet and exercise. By adopting a holistic approach to health based on Ayurvedic principles, individuals can embark on a journey towards improved vitality, longevity, and overall wellness.

DOI: 10.61137/ijsret.vol.10.issue2.157

Published by: vikaspatanker

Pharmacy Management System
Authors:-Assistant Professor Vikas Desai,Vinay Basargekar, Shraddha Thorbole, Siddhi Uttekar, Saurabh Rai, Pooja Shingade, Yashraj Dhamale

Abstract-In the today’s healthcare, pharmacy management systems have become crucial in enabling effective medicine distribution and inventory optimization. The rapid adoption of electronic technologies has disconnected and transfigured traditional practices across various industries, and the field of healthcare is no exception. As a result, various managerial solutions have came into view to meet the particular requirements of different sectors, including the medical industry.] Traditional data management in pharmacies frequently addresses challenges like limited capacity, slower processes, restricted access to medications, complicated stock management, and the need for skilled staff to meet demands. To deal with these challenges, this paper proposes the implementation of an e-pharmacy system, precisely designed to streamline operations and services to overcome the previously mentioned impediments. Automation helps to improve the traditional method of pharmacy management. This proposed solution presents a grate chance to improve effectiveness of pharmacy management in medical environments, thereby contributing to improved overall healthcare delivery. Key features of the pharmacy management system consists of the ability to properly record and handle prescription data, as well as a comprehensive database of medication information to make sure the medication issuing procedures are relevant and accurate. Additionally, the system offers flexibility in terms of customization, allowing healthcare providers to adjust settings and preferences according to their specific operational needs and protocols. Through the development and implementation of this pharmacy management system, we aim to empower medical facilities with the tools and resources needed to deliver efficient and safe medication management. By facilitating streamlined processes for prescription handling, inventory control, and patient record maintenance, our system helps improve care quality, minimizing medication errors, and enhancing overall operational efficiency within pharmacies and healthcare settings. Our pharmacy management system seamlessly integrates with other healthcare systems, promoting easy access, collaboration among professionals, and better patient outcomes, benefiting the healthcare ecosystem as a whole.

DOI: 10.61137/ijsret.vol.10.issue2.156

Published by: vikaspatanker

Deep Learning Approaches in Genomic Analysis: A Review of DNA Sequence Classification Techniques
Authors:- Vishakha Nerkar, Dr. Vinod Kimbahune

Abstract-In bioinformatics, DNA sequence classification poses many challenges due to its inherent complexity and volatility. In this paper, the difficulties in applying deep learning techniques to DNA sequence classification are examined. Variable sequence lengths, complex data representation, and the requirement for efficient feature extraction are all highlighted by the analysis. Moreover, when developing a model, factors like uneven data distributions, interpretability issues, and the possibility of overfitting must be carefully considered. Deep learning in genomic analysis has tremendous potential, but there are still many unanswered questions. Using transfer learning and genomics domain expertise can help overcome some of these obstacles. Despite these challenges, applying deep learning methods could greatly improve our comprehension of genetic data and how it relates to health and illness. Researchers can move the field toward transformative work by taking on these obstacles. Discoveries in genomic medicine and beyond.

DOI: 10.61137/ijsret.vol.10.issue2.153

Published by: vikaspatanker