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
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:
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.