IJSRET Volume 10 Issue 2, Mar-Apr-2024


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

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

Smart Security Surveillance
Authors:-Yash Avhad, Ravikiran Pagar, Ganesh Khairnar, Krushna Bhabad

Abstract- The COVID-19 pandemic epidemic has paralysed the entire international health system. To stop the infection from spreading, it is now essential. Around the world, putting on a mask, washing our hands often, and avoiding social contact have all become priorities. The World Health Organization (WHO) strongly advises against spreading the new coronavirus by using a mask that covers the mouth and nose. The primary objective of a computer vision system is to find moving objects. The performance of these systems is insufficient for many applications. One of the main causes is that moving object detection is more difficult when dealing with various constraints, including environmental changes. After object recognition, object counting is a process that is improved upon and made more reliable with the aid of Open CV. Open CV comes with a variety of helpful methods for item recognition and counting. Numerous industries, including transportation, health care, and environmental science, use object counting.

Exploring the Potential of Unlisted Shares: An Analysis of Performance and Shareholding Patterns in the Indian Market
Authors:-Shravani Gambhire, Prerna Telge, Sneha Soundararaj, Neha Sahu

Abstract- This study explores the untapped potential of unlisted shares as an investment avenue, conducting a thorough analysis of their performance within a closed market environment. Focused on thirty-three diverse unlisted Indian companies across sectors like Banks & NBFC, manufacturing, IT, and insurance, the research utilizes a stratified random sampling approach. Secondary data from annual reports and company records supplement primary data collected through interviews. The analysis reveals sector-specific trends, emphasizing the strong performance of manufacturing and insurance while highlighting challenges in the banking, financial, and IT sectors. The study underscores significant public shareholding in the unregulated maroiket, indicating its accessibility to retail investors. Despite liquidity challenges and information disparities, the unlisted market presents alternative investment opportunities for those strategically navigating its dynamics. In conclusion, the research not only provides insights for diversification-seeking investors but also raises awareness among policymakers about the unlisted market’s role in the broader investment landscape, emphasizing the need for informed decision-making in a volatile yet potentially lucrative market.

DOI: 10.61137/ijsret.vol.10.issue2.134

Connecting Minds
Authors:-Mohammed Imran A, Nithish Kumar S, Prabin C S, Princilla S, Manoj Kumar T

Abstract- Their profiles, and investigate their creative projects. By providing a cooperative space for information exchange and project demonstration, Seniors Interaction and Project Showcase Webpage empowers consumers to elevate their connected to the internet appearance and help the vibrant type of educational institution environment. Join us as we reformulate the barriers of tech socializing for professional or personal gain and project reveal, place creativity, cooperation, and novelty gather to shape the future of technology.

How AI and ML are Contributing to the Sophistication of Cyber Attacks
Authors:-Kiran Sharma Panchangam Nivarthi

Abstract- Artificial Intelligence (AI) and Machine Learning (ML) are being extensively used to make cyber security more robust and adaptive to new forms of attack. At the same time, the two technologies have the potential to make several conventional cyber attack vectors significantly more potent and sophisticated. They are also introducing new attack vectors. With the help of AI and ML, malware can become more adaptive and harder to trace, and we already have an example in the form of IBM’s Deep locker. They can also be used to identify better phishing targets and make phishing emails more believable by using freely available tools like Chat GPT. AI and ML can augment cyber attacks like DDoS that rely on botnets to adapt to a wide range of defensive measures and make coordinated botnet attacks easier to orchestrate. Man-in-the-middle attacks can become more potent with new AI and ML-augmented cryptanalysis and real-time spoofing. SQL injections can become more sophisticated by leveraging the right algorithm to generate queries that are more likely to bypass database security. The technologies can also be used for more comprehensive payload and traffic analysis of DNS servers for new generation of DNS tunneling attacks. AI and ML capabilities of adaptive behavior, more sophisticated automation, identifying patterns in data, and mimicking existing traffic/human patterns can lead to more sophisticated cyber attacks.

A Survey on Keystroke Dynamics Using K-NN and Manhattan Distance
Authors:-Professor Prasad A M, Indu P, Manoj N, Sachin G L, Vijayalakshmi P

Abstract- Keystroke dynamics is an active area of study; numerous solutions have been put out in this subject utilizing various implementations, most of which use the Euclidean distance to measure feature vector similarity. The Euclidean distance method is less effective than other classification techniques since it has a higher mistake equal rate. Therefore, in order to increase the authentication efficiency, we present our implementation of keystroke dynamics in the next paper, which uses Manhattan distance and K-NN as classifiers. In this investigation, the flight times and dwell periods between keys are used.

Application of Reinforced Earth Principles in the Construction of Subhas Phatak Rob Approach at Bhopal
Authors:-Abhishek Tiwari, Assistant Professor Santosh Kharole

Abstract- Shubhas Phatak (SP) ROB crossing has been built in a very busy route of new Bhopal urban area compared with limited working space due to existing railway tracks, roads and builtup area on the road sides. At SP there was level crossing of Central Railway ( RKP station to Bhopal section and the anterior road from AIIMS to BHOPAL railway station. This artery has peak traffic during the business hours. Closers of the gate while passing the trains at SP traffic stagnation were most frequent thus it was a serious public concern. Due to construction of ROB and connecting approaches the railway and road traffic is now separated and channelized over the natural routes. Due to space constraints reinforced earth walls have been used in place of reinforced construction or gravity abutments and returns of ROB. In the old existing 2 (two) lane road now 4(four) lanes have been planned in the limited space of 10.89 m width. Reinforced earth filling as well as reinforced soil (RS) walls and back fills have been used. This work has been relatively simple fast in construction and economic in comparison to a concrete construction work.The reinforced earth has been made by a composite material formed by the friction between the earth and reinforcement. The embankment is performing satisfactorily to pass the vehicular traffic. In this study; the principles and method of reinforcement soil construction has been described.

DOI: 10.61137/ijsret.vol.10.issue2.132

A Study on Challenges Faced by Garment Industry With Special Reference to Tirupur City
Authors:-Assistant Professor Dr. M. Kowsalya, Mr. Nishanth.S, Mr. Rallapalli Yogeswara Naidu

Abstract- Tirupur, a prominent textile and garment hub in India, has earned recognition as a major player in the global export market. However, the export industry in Tirupur faces various challenges and problems that impact its growth and sustainability. This study aims to investigate and understand the multifaceted issues confronted by Tirupur exporters, providing valuable insights for stakeholders and policymakers. The primary objective of this study is to study the challenges and problems faced by the Garment Exporters in Tirupur City in export business. This research was based on descriptive research methodology. We have applied Simple Random Sampling technique to select the sample for the study. Totally 152 sample respondents were selected and the statistical tools simple percentage analysis, factor analysis and ANOVA was used to analyse the collected data.

Review on Improvement the Heat Transfer Rate of Ac Evaporator by Optimizing Materials
Authors:-Vishal sironiya, Assistant Professor Khemraj Beragi

Abstract- Air Conditioning is referred to the treatment of air so as to all together control its temperature, moisture content, cleanliness, odor and circulation, as required by occupants, a process, or products in the space. The subject of refrigeration and air conditioning has evolved out of human need for food and comfort, and its history dates back to centuries. The history of refrigeration is very fascinating since every aspect of it, the availability of refrigerants, the prime movers and the developments in compressors and the methods of refrigeration all are a part of it. In the present work the Experimental Investigation for Air Conditioning Condenser to Increase the Heat Transfer Rate by Varying the Tube Arrangement.

Review on Motor Torque Control and Speed Control by Using Artificial Intelligence Controller
Authors:-Yogesh Jamre, Assistant Professor Raghunandan Singh Baghel

Abstract- This article offers a comparison of several controlled induction motor drive approaches and provides an overview of induction motor (IM) drives. Additionally, it looks at several voltage and current control approaches. Induction motors are commonly used utilised in commercial and domestic appliances, which use more than 50% of the total electrical energy produced. This essay offers comprehensive study of the literature on the different 3-phase induction motor strategies, including pwm, phase control, and vector control. The authors have a strong conviction that this survey article will be extremely helpful to researchers in locating relevant references in the field of speed control for 3-phase induction motors using vector control methods. Simulation results of the proposed system are obtained using MATLAB/Simulink software.

Analysis of Thermodynamics Properties of an Isolated System
Authors:-Kingsley E. Madu, Chike M. Atah

Abstract- Thermodynamic systems provide a means to harness useful work from various energy inputs and transfers within naturally occurring processes. Maximizing the work extracted from a given system can lead to more efficient energy utilization across many engineering applications. This paper explores various techniques for optimizing the work output of an isolated thermodynamic system based on fundamental principles from engineering thermodynamics. Key strategies discussed include targeting specific process parameters, cycle configurations, and working fluid properties to maximize pressure differentials driving work and minimize irreversible entropy generation according to the first and second laws of thermodynamics. Additional optimization frameworks are considered from perspectives of exergy destruction minimization, maximum power output, predefined efficiency levels, and accounting for finite-rate irreversibilities in real systems. Integrated multi-scale and multi-physics modelling techniques are also examined for their ability to most comprehensively capture system behaviour. A variety of example technologies are reviewed that highlight successful applications of multi-scale optimization approaches. Overall conclusions drawn indicate that continual refinement of optimization methodologies, incorporating emerging fields like quantum thermodynamics, promises further advances in harnessing thermodynamic resources to energize diverse technologies critical to society.

Effect of Sudden Pressure Drop in a Nozzle Flow
Authors:-Kingsley E. Madu, Chike M. Atah

Abstract- This research study delves into the intricate dynamics of sudden pressure drops in nozzle flow, aiming to provide a deeper understanding of the phenomena involved. Nozzle flow plays a pivotal role in various engineering applications, such as aerospace propulsion, industrial processes, and automotive systems. The primary objective of this investigation was to elucidate the consequences of abrupt pressure reductions within a nozzle, with a focus on flow behavior, efficiency, and potential implications for system performance. Experimental and computational methods were employed to simulate and observe the behavior of fluid flow within a nozzle subjected to sudden pressure drops. The study encompassed a range of nozzle geometries and operating conditions to explore the impact of varying parameters on flow characteristics. Findings from this research reveal intricate interactions between pressure drops, flow velocities, and thermodynamic properties, shedding light on the underlying physics. Key findings include insights into the formation of shockwaves, boundary layer effects, and alterations in flow patterns as a consequence of sudden pressure drops. Furthermore, the study highlights the potential for efficiency losses and structural stress in nozzle systems subjected to rapid pressure fluctuations. These findings contribute valuable knowledge for optimizing nozzle designs, enhancing system reliability, and minimizing energy losses in various engineering applications. Overall, this research underscores the significance of comprehending the effect of sudden pressure drops in nozzle flow, offering valuable insights for engineers and researchers seeking to optimize fluid flow systems and improve overall efficiency.

Advancing Ethical and Accurate Hate Speech Detection with Machine Learning Techniques
Authors:-Jorge White

Abstract- In recent years, the proliferation of social media platforms has significantly increased, providing a digital space where individuals from diverse backgrounds can express their opinions and thoughts. This surge in social media usage has brought to light the challenge of managing and moderating hate speech—a form of content that can incite violence, discrimination, and hostility. The primary difficulties in detecting and processing hate speech stem from the linguistic diversity of users, the nuanced usage of language that can alter meanings based on context, and the scarcity of robust datasets for the development and evaluation of detection models. This paper explores these challenges in depth and proposes an innovative approach to enhance the efficiency and effectiveness of hate speech detection. We critically analyze the limitations inherent in current methodologies and introduce a model based on Support Vector Machine (SVM) algorithms. Our comparative analysis demonstrates that SVM-based models offer superior performance in detecting hate speech compared to conventional neural network approaches. This is attributed to the SVM’s ability to handle high-dimensional data and its effectiveness in classifying complex, nuanced linguistic patterns. Furthermore, we delve into the technical and ethical implications of automating hate speech detection. The paper discusses the ongoing challenges in balancing accuracy with the need for ethical considerations, such as avoiding censorship and respecting free speech. We address the technical hurdles related to algorithmic bi as, model interpretability, and the need for continuous adaptation to evolving language and social norms. In conclusion, while significant strides have been made in employing machine learning techniques for hate speech detection, several critical issues remain unresolved. Our research underscores the importance of interdisciplinary efforts, combining insights from linguistics, social sciences, and computer science, to develop more sophisticated, ethical, and effective hate speech detection systems. By advancing the use of SVM and exploring its potential in this domain, we contribute to the broader discourse on making digital platforms safer and more inclusive.

DOI: 10.61137/ijsret.vol.10.issue2.135

Strategic Data Management: Frameworks, Implementation Challenges, and Success Stories
Authors:-Jorge White

Abstract- In the current landscape where digital innovation shapes every aspect of business operations, the adept management and strategic use of data stand as pivotal factors in securing organizational prosperity and a competitive edge. This study ventures into the realm of data strategy, shedding light on its pivotal role in the digital age and its profound influence on the operational dynamics of contemporary organizations. It outlines a variety of methodologies for the formulation of a holistic data strategy, encompassing essential facets such as governance, data quality, architectural integrity, and organizational data literacy. Furthermore, this research identifies prevalent obstacles encountered during the deployment of data strategies and furnishes actionable strategies derived from the successful experiences of leading organizations. By engaging in a comparative scrutiny of diverse strategic models and probing into the avant-garde trends shaping data management, this paper prognosticates the trajectory of data strategy evolution and its repercussions for future business models. Offering an amalgam of theoretical constructs, empirical challenges, and illustrative success narratives, the paper serves as a comprehensive guide for entities aiming to optimize their data strategy endeavors, thereby maximizing the utility of their digital information reservoirs.

DOI: 10.61137/ijsret.vol.10.issue2.136

Cloud Mongo Database – Applying Security and Encryption to NoSQL DB
Authors:-Dr. Karuturi S R V Satish

Abstract- As technology develops, massive volumes of data are produced daily from a variety of sources, including social media, banking, hospital administration, etc. Big data use-cases in contemporary enterprises are contributing to the development of alternative technologies to SQL (Structured Query Language). The volume of data being gathered from various sources is growing, and this is driving the transition from relational database management systems (RDBMS) to NoSQL (not only SQL) databases, making data migration crucial now. Reviewing a technique for data migration from RDBMS to NoSQL database is the aim of this paper. This method implements software prototypes using MongoDB as a NoSQL database and SQL as an RDBMS. Data from Mongo databases and SQL databases is therefore kept safe. NoSQL databases perform better than conventional RDBMSs because of their high performance, scalability, and capacity to retrieve massive volumes of data more quickly. These databases have become more and more necessary in recent years due to the massive growth in data collection. NoSQL allows the storage of structured, unstructured, and semi-structured data, something that traditional databases do not enable. NoSQL must make up for its incredible features of quicker data access and vast data storage with its security features. The primary source of concern is the sensitive data that is kept in the system. Protecting this sensitive data is essential to avoid issues with privacy and confidentiality. It’s critical to acknowledge security concerns in order to comprehend the gravity of protecting sensitive data.

Investigating the Integration of Biophilic Design Principles in University Campuses: A Case Study of Caleb University, Lagos, Nigeria
Authors:-Adewole Esther Adegbolafunmi, Ogidiagba Oghenetega Hilda, Tejumaiye Ayomide Oluwatimilehin, Akinyemi Hafeez Olorunsegun, Professor Matthew Dayomi

Abstract- This research explores the integration of biophilic design principles within the educational environment, focusing on the case study of Caleb University in Lagos, Nigeria. Biophilic design, rooted in the concept of humans’ innate connection with nature, seeks to enhance well-being, cognitive function, and academic performance by incorporating natural elements into the built environment. Drawing on the rich literature of biophilic design and its application in educational settings, this study investigates the specific impacts of biophilic interventions on student learning outcomes, emotional well-being, and the overall campus experience. By examining the challenges and opportunities associated with implementing biophilic design in a university context, the research aims to provide valuable insights for sustainable campus development. The case study of Caleb University in Lagos offers a unique perspective on biophilic design implementation in a diverse cultural and geographical context. This research contributes to the evolving discourse on biophilic design in academia, shedding light on its potential to create inclusive, supportive, and environmentally conscious educational spaces.

Prospects and Challenges in the Adoption of E-Commerce in Exports by Manufacturers with Special Reference to MSMEs in Coimbatore District
Authors:-Assistant Professor Mr. K. Chandrabose, Mr. N.P Raghuraam

Abstract- A large number of economies rely heavily on Small and Medium-Sized Enterprises (SMEs) to contribute to the GDP. Particularly in developed economies, new technical advancements have aided a great number of SMEs in increasing their Electronic Commerce (e-commerce) capacities following the development of the newest Information and Communication Technology (ICT) instruments. But in developing nations, this kind of progress is quite uncommon. This article focuses on the opportunities and problems faced by Micro, Small, and Medium-sized Enterprises (MSMEs) in India. MSMEs are important for reducing poverty, creating jobs, and increasing income, but they also face several obstacles that limit their ability to grow. The objective is to recognize and evaluate these obstacles, investigate prospects, and offer a road map for MSME success.

Artificial Neural Network Approach of Deep Learning for Prediction of Phishing Websites
Authors:-Pritam Kumar, Sujeet Gautam, Surendra Vishwakarma

Abstract- The act of attempting to gain sensitive information such as usernames, passwords, and credit card numbers is referred to as “phishing” (and sometimes, indirectly, money). In this particular investigation, the machine learning classifiers are attempting to determine whether website is phishing. The data obtained through phishing is used as input data and is processed using a pre-processing procedure. In the pre-processing procedure, the dataset should be cleaned up, and the label encoding should be applied. After that, a feature selection approach is used to the dataset, and during this procedure, the dataset is divided into a training Dataset and a testing dataset. Following that, the PCA method will be applied, and it will proceed to reduce the number of features. The accuracy of the decision tree is 91.51%, whereas the accuracy of the KNN is 97.69%, the accuracy of the random forest is 94.44%, and the accuracy of the suggested ANN is 98.04%.

A Review Article of EMG Signal Classification and Feature Extraction Using Machine Learning and DWT Technique
Authors:-Jaspreet Singh Dhanjal, Dr. Hemant Amhia

Abstract-In recent years, there has been major interest in the exposure to physical therapy during rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and human machine interface (HMI) applications. An automated system will guide the user to perform the training during rehabilitation independently. Advances in engineering have extended electromyography (EMG) beyond the traditional diagnostic applications to also include applications in diverse areas such as movement analysis. This paper gives an overview of the numerous methods available to recognize motion patterns of EMG signals for both isotonic and isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who would like to select the most appropriate methodology in classifying motion patterns, especially during different types of contractions. For feature extraction, the probability density function (PDF) of EMG signals will be the main interest of this study. Following that, a brief explanation of the different methods for pre-processing, feature extraction and classifying EMG signals will be compared in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.

Electronic Voting Using Block chain Technology
Authors:-Govind Tiwari, Kartik Sharma, Vaishnavi Parhad, Nikhil Ghule, Professor Priyanka Kute

Abstract-In today’s world, the use of technology into different aspects of life has grown increasingly. Traditional voting methods frequently confront issues relating to security, transparency, and trust worthiness. To overcome these challenges, block chain technology appears to be a potential answer. Block chain, a decentralized and irreversible ledger system, has intrinsic qualities that can help improve the integrity and fairness of online voting systems. This abstract investigates the design and implementation of an online voting system utilizing block chain technology, with a particular emphasis on Ethereum smart contracts. The fundamental goal is to provide a safe, transparent, and tamper-resistant platform that allows people to vote with confidence while protecting their privacy and anonymity. The proposed online voting system consists of many major components, including a front end UI, Ethereum smart contracts, Web3.js integration, and Meta Mask support. The front end interface is the user-friendly gateway through which voters engage with the system, view candidate information, and cast their ballots. Web3.js, a JavaScript library, provides communication between the front end interface and the Ethereum block chain, allowing for easy interaction with smart contracts. Meta Mask, a popular browser plugin, is essential for allowing users to safely view the Ethereum block chain and authenticate transactions. By incorporating Meta Mask, users may sign transactions and interact with the smart contract directly from their web browsers, providing a quick and secure voting experience. The Ethereum smart contracts are the foundation of the online voting system, managing the rules, processes, and integrity of the election process. These smart contracts allow for transparent and decentralized candidate registration, voter verification, vote casting, and result tabulation. The implementation of smart contracts guarantees that the voting process is irreversible, auditable, and immune to manipulation or fraud. The abstract also highlights the role of security measures in ensuring the integrity of the online voting system. Cryptographic hashing, digital signatures, and encryption are used to safeguard sensitive data from unauthorized access or manipulation. Furthermore, audit trails and event recording methods improve openness and accountability by allowing stakeholders to confirm the validity and integrity of the voting process. Furthermore, the abstract discusses the possible benefits and problems of block chain-based online voting systems. While block chain technology provides unprecedented levels of security, transparency, and decentralization, it also has scalability constraints, legal impediments, and usability issues that must be solved in order to achieve mainstream use and acceptance. Finally, the abstract emphasizes block chain technology’s transformational potential for online voting systems, opening the way for more secure, transparent, and inclusive political processes. Block chain-based online voting systems have the potential to transform the future of elections by leveraging the power of decentralization and encryption, enabling confidence, participation, and accountability in democratic society.

A Study of Parameter Optimization Metal Alloy for Modern Industrial Trends in Manufacturing
Authors:-Research Scholar Sandip Das, Associate Professor Dr. Dinesh Soni, Prof. Dr. Ankit Goyal

Abstract-The purpose of this paper is to the optimization of parameters for metal alloy manufacturing is crucial for meeting the demands of modern industrial trends. This study investigates the process of parameter optimization in metal alloy manufacturing within the context of contemporary industrial practices. The research explores various optimization techniques, including advanced algorithms, real-time data monitoring, and machine learning, to enhance the efficiency, quality, and sustainability of metal alloy production processes. By analyzing the implications of parameter optimization on productivity, cost reduction, and environmental sustainability, this study aims to provide insights into the significance of adopting modern optimization methods in the manufacturing industry. The findings highlight the importance of integrating advanced technologies and best practices to achieve optimal results in metal alloy manufacturing, thereby enabling industries to stay competitive in today’s rapidly evolving industrial landscape.

Contemporary Problems Faced by Freight Forwarders in Using Intermodal Transportation of Persihable Goods
Authors:-Assistant Professor Dr. V. Saranya, V. Gnana Surya

Abstract-The utilization of intermodal transportation for perishable goods poses modern challenges for freight forwarders. These hurdles encompass the preservation of product quality throughout multi-modal journeys, compliance with diverse regulations, and managing coordination issues arising from network fragmentation. Tackling these issues necessitates collaborative efforts, investment in technology, and the development of innovative solutions to improve efficiency and reliability. By overcoming these challenges, freight forwarders can enhance the effectiveness of intermodal transportation for perishable goods, providing customers with dependable and economical solutions globally.

Landslide Detection System Using IOT
Authors:-Sanika Janardan Awad, Sandesh Dilip Kurhade, Rounak Suresh Gawand, Ms. Komal Golimbade

Abstract-A geological phenomenon called a landslide is defined as a mass of rock, soil, or debris sliding down a slope. Depending on a number of variables, including soil type, weather, and the steepness of the slope, it may happen abruptly or gradually. A further review states that landslides account for 64.15% of fatalities caused by common disasters. Considerations indicate that the number of landslide fatalities has increased as a result of a laborious and dubious forecasting methodology. One potential solution to lessen these severe effects is to predict landslides accurately and efficiently, without taking a lot of effort. Most of the examined studies make use of sensor technology; WSN (Remote Sensor Network) is the most popular variety, offering large-scale monitoring. When an avalanche is predicted to have a high probability, the disaster administration office receives an alert. The rates of precision for each of these tactics varies. his study paper talks about different approaches for identifying and foreseeing landslide in this manner decreasing fatalities.

A Review on Geopolymer Concrete with Basic Norms
Authors:- Assistant Professor Kasarla Sagar, Assistant Professor MD Akber, Assistant Professor Modugu Naveen Kumar

Abstract-The most adaptable, dependable, and long-lasting construction material in the world is concrete. The most commonly used substance, after water, is concrete, which calls for a lot of Portland cement. The manufacturing of ordinary Portland cement is the second largest source of atmospheric pollution caused by carbon dioxide emissions, after automobiles. In addition, the manufacturing of cement required a significant quantity of energy. Finding a substitute for the current Portland Cement, which is the priciest and uses the most resources, is therefore inevitable. An novel building material called geopolymer concrete is created by the chemical reaction of inorganic molecules. There is an abundance of fly ash, a by-product of coal from thermal power plants, around the world. Flyash has high alumina and silica content.

Casting Defect Reduction in a Manufacturing Industry Using DMAIC Technique
Authors:- M.Tech. Scholar Kunwar Kuldeep Singh, Professor Ashutosh Diwedi

Abstract-The art of meeting customer specifications, which today is termed as “quality”. Quality is the symbol of human civilization, and with the progress of human civilization, quality control will play an incomparable role in the business. It can be said that if there is no quality control, there is no economic benefit. In the current world of continually increasing global competition, it is imperative for all manufacturing and service organizations to improve the quality of their products. In today highly competitive scenario, the markets are becoming global and economic conditions are changing fast. Customers are more quality conscious and demand for high quality product at competitive prices with product variety and reduced lead time. It is a data-driven quality strategy used to improve processes. It is an integral part of a Six Sigma initiative, but in general can be implemented as a standalone quality improvement procedure or as part of other process improvement initiatives such as lean. Any enterprises that cannot manage the quality of its methods and products have a tendency to fall apart. Quality is crucial to sales, price control, productivity, risk control and compliance. As essential as quality is, there’s little agreement as to its definition. The following definitions observe excellent from a control, high-quality guarantee, product, advertising and marketing, production and economic point of view.

Blockchain Enabling Web 3.0: Decentralized Trust and Secure Exchanges for the Future Web
Authors:- Yash Chachdiya, Vishnukumar Boda, Assistant Professor Sweety Patel

Abstract-The ascent of Web 3.0 has set out a freedom for a more decentralized, secure, and straightforward web. Blockchain innovation has arisen as a basic empowering influence for Web 3.0, empowering the improvement of decentralized applications that form trust and backing secure exchanges. In this review, we examine how blockchain innovation can further develop Web 3.0 by utilizing properties like changelessness, agreement components, and brilliant agreements. The decentralized idea of blockchain innovation further develops security and protection, giving purchasers more command over their own information. It likewise gives more secure and more productive exchanges and can improve on stage similarity. By giving a straightforward and secure stage, decentralized blockchain-based applications can possibly change an extensive variety of industry regions, from production network the executives to computerized casting a ballot. As Web 3.0 creates, blockchain innovation will assume an undeniably significant part in empowering new use cases and reforming a great many organizations. We can construct a superior web that is safer, more secure, and more impartial for all clients by embracing blockchain innovation.

A Study on Challenges and Impact on Performance of Pump and Motor Industries with Special Reference with Coimbatore
Authors:- Associate Professor Dr. S. Mohanraj, Chandru. D, Meshach Ronald.H

Abstract-This study is piloted to know the challenges faced by pump and motor industry and performance in motor and pump industry. This industry encompasses the entire supply chain from production to distribution and servicing of electric motors and pumps, fulfilling critical needs including water supply, irrigation, industrial processes, and construction activities. This study is conducted in Coimbatore District. The tool used to know the challenges on the performance of pump industries were simple frequency, rank analysis and anova. The data was collected from 61 respondents from the working people in pump and motor industry in Coimbatore district.

Sun – The Star of the Solar System
Authors:- Subhasis Sen

Abstract-A critical study indicates that our knowledge on interior of the Sun which are concealed under the thick envelop of intensely heated material, need thorough scrutiny and revamping. Though it is difficult to surmise what occurs in the interior of the Sun, in the prevalent notion, considering its low density, composition of this overwhelmingly huge object of the Solar System has been conjectured to be mainly super-heated gases like hydrogen and helium. I shall present a totally contrasting view that considers the Sun to be a hugely expanded object and due to expansion its overall density has lowered down. Because of expansion of the Sun, in its interior a void zone has developed that occurs between two solid zones in the Sun’s interior. Due to such orientation in the interior of the Sun, in addition to the normal downward gravitational force, a reversely directed force of gravitation would manifest. Such disposition of occurrence of reversely directed gravitation in the Sun’s interior would give rise to the prevalence of low pressure and low temperature around the core, composed of solid iron. The core showing magnetic characteristics, can, therefore, be rationally considered as a huge dipolar magnet.

Planets of the Solar System – The Misinterpreted Objects of the Sky
Authors:- Subhasis Sen

Abstract-A critical study reveals that the previous explanations on planets of the Solar System need thorough scrutiny. Here, I have pointed out that all planets of the Solar System are basically composed of similar objects and no planet can be mainly constituted of gases. The study reveals that Earth is an expanded planet and matching thickness of its outer core with the extent of expansion reveals that due to expansion, the former geosphere has opened up as a void zone. The prevalent concept conceives that the outer core is a fluid geosphere comprised of liquid iron. Here I envisage that because of occurrence of a void geosphere between the solid mantle and the solid inner core, in addition to the normal downward force of gravitation, a reversely directed gravitational force would be manifested in the Earth’s deep interior. Accordingly, temperature and pressure at the Earth’s deep interior would be sufficiently low, thereby, keeping the inner core a dipolar permanent magnet. Since all planets of the Solar System are similar in nature, the information gained here in regard to planet Earth can be applied for unravelling the features of all other planets of the Solar System as well.

Review on a Efficiency Enhancement of Solar Based HVAC System
Authors:- Ashish Pandey, Assistant Professor Khemraj Beragi

Abstract-Solar energy converts the renewable energy to increase growth. The development of energy in to generated worldwide. It in the most easy to construct the process of solar air Conditioning systems. The different energy are involved into the solar air conditioning to the decreasing current Sources Then using high oil and concern environmental effects have been Controlling. The most comfortable Process of the solar energy system. It we implemented nowadays, increase in progress. we are air Conditioning systems are using in. every building, malls, Colleges industries, flats, etc. solar power air conditioning system is the hot issue to study building energy Consumer. To increasing the efficiency of air Conditioning intensity of the cooling system. The transient thermal efficiency we can using the storage system to maintain the temperature to indoor, The solar system must be using the different.

Personalized OSAS Detection in Pateints
Authors:- Tony Thomas, Mrs. S.Mohanapriya

Abstract-Obstructive sleep apnea (OSA) significantly impacts patients’ recovery and outcomes across various conditions. Accurate and personalized apnea detection is crucial for effective intervention and improved patient care. However, traditional methods often struggle to capture the complex dynamics and individual variations present in different sleep disorders This paper proposes a novel deep learning architecture for automated OSA detection that incorporates a self-attention mechanism to enhance performance and interpretability. The model leverages a Convolutional Neural Network (CNN) to extract features from Electrocardiogram (ECG) data, followed by a Long Short-Term Memory (LSTM) network to capture temporal dependencies and sequential information. A self-attention mechanism is then integrated before the final dense layer, focusing on the most relevant segments of the LSTM output for improved prediction accuracy. Additionally, the model generates attention weights that highlight the crucial parts of the ECG data contributing to the final prediction. These weights are incorporated into a scorecard, promoting interpretability and transparency in the model’s decision-making process. The proposed approach offers a promising avenue for accurate and interpretable OSA detection, potentially benefiting both patients and healthcare professionals.

Integration of Under Ground Utilities for Smart Cities
Authors:- Chintan Patel, Associate Professor Ankita J Parikh

Abstract-The rapid urbanization and population growth in modern cities necessitate innovative solutions to enhance urban infrastructure efficiency, sustainability, and overall quality of life. This paper explores the integration of underground utilities as a key component of smart city development. Smart cities leverage advanced technologies to optimize resource utilization, improve services, and create more resilient urban environments. Focusing on the buried realm, this research explores into the integration of various underground utilities, including water supply, sewage, storm water, power distribution network, telecommunications, and gas. The proposed framework employs a comprehensive approach to seamlessly connect and manage diverse underground utility systems through the utilization of sensor networks, Building Information Modeling (BIM), Geographic information system (GIS), Internet of Things (IoT) devices, and advanced data analytics. By integrating these systems, cities can achieve real-time monitoring, predictive maintenance, and efficient resource allocation, ultimately reducing operational costs and minimizing environmental impact. Key aspects of the integration include the development of a unified communication infrastructure, interoperability standards, and intelligent control systems. The paper also addresses challenges related to data security, privacy, and the coexistence of different utility networks. Additionally, the study explores case studies and pilot projects from around the world, highlighting successful implementations and lessons learned. The outcomes of this research contribute to the foundation of a roadmap for the integration of underground utilities in smart cities. By creating interconnected, adaptive, and sustainable underground infrastructure, cities can enhance their resilience, optimize resource usage, and improve the overall quality of life for their residents. The findings presented in this paper aim to guide urban planners, policymakers, and technology developers in the pursuit of more efficient and intelligent urban development.

Analysis and Design of G+9 Educational Building Using Etabs
Authors:- S.Kasilingam, Professor Dr.A.Arivumangai

Abstract-In this project work, an attempt has been made to plan and design a G+9 storied educational building. This project work involves planning, analysis, designs, and drawings of a typical multi storied building. The salient features of the G+9 storied building are as given below the basement floor is 1.20m above the existing ground level. The shopping complex consists of G+9 floors with 4.00m ceiling height. The carpet area available in each floor is 3000sq.m. This educational building having all facilities under one roof, designed with workstations, conference hall, individual cabins for higher officials, Discussion rooms with all other amenities and very good water supply and sanitary arrangements. Structural analysis is a branch which involves determination of behavior of structures in order to predict the responses of real structures such as buildings, bridges, trusses etc, with economy, elegance, serviceability and durability of structure. Structural engineers are facing the challenge of striving for the most efficient and economical design with accuracy in solution, while ensuring that the final design of a building must be serviceable for its intended function over its design lifetime. This project attempts to understand the structural behavior of various components in the multi-storied building. Analysis, designing and estimation of multi-storied building has been taken up for Basement+G+2 Building, thereby depending on the suitability of plan, layout of beams and positions of columns are fixed. Dead loads are calculated based on material properties and live loads are considered according to the code IS875-part 2, footings are designed based on safe bearing capacity of soil. For the design of columns and beams frame analysis is done by limit state method to know the moments they are acted upon. The structural design has been manually done. The estimate of the building is prepared on the basis of plinth area rate. Necessary structural drawings are enclosed at appropriate places.

DOI: 10.61137/ijsret.vol.10.issue2.141

Evaluation of Building Structural Stability by Using Rebound Hammer Test
Authors:- A.Paulmakesha, Professor Dr.S.Arivalaganb

Abstract-The quality problems encountered in concrete structures appear at different stages of the construction of works, It is for this reason that for a long time there has been an increased demand for more precise and, at the same time, more flexible methods of concrete quality assessment. This paper presents some notions concerning the Schmidt rebound hammer test and Rebar Locator test which is one of the non-destructive methods most used for the recognition of the condition of building structures. This test is quick and easy, it makes it possible to control the quality of the construction and to indirectly measure the compressive strength of concrete in situ. The rebound hammer calibration procedure was detailed on an example by presenting the different steps. I have selected five blocks ar Dr.M.G.R Educational and Research Institute, Maduravoyal, Chennai. It contains Anna block, Mother thesera block, Abdul Kalam block, Ramanujam Block and V.O.C Block. The location of rebar in reinforced concrete is a major examination item in the field of Construction. The location of rebar in reinforced concrete is a major examination item in the field of construction. As a kind of non-destructive testing method, I measure the magnetic susceptibility on the surface of reinforced concrete structures with a susceptibility meter. Rebar locator & corrosion detectors provide fast, accurate information to detect reinforcement bars in concrete, identifying rebar’s location, direction and an indication of the depth of concrete over the rebar. Non-destructive testing is a descriptive term used for the examination of materials and components in such way that allows materials to be examined without changing or destroying their usefulness. NDT is a quality assurance management tool which can give impressive results when used correctly. It requires an understanding of the various methods available, their capabilities and limitations, knowledge of the relevant standards and specifications for performing the tests. NDT techniques can be used to monitor the integrity of the item or structure throughout its design life. Structural audit is the overall health and performance checkup of the building like doctor check the patient. Structural audit helps to understand the status of the old building. The Audit helps to highlight & investigate all the risk areas, critical areas and whether the building. needs immediate attention.

DOI: 10.61137/ijsret.vol.10.issue2.142

A Review of Strenthening the Structural Elements for Stability Using Jacketing Techniques
Authors:- Allwin Jeenu Bhaskaran, Professor Dr.Deepa Ra.B

Abstract-It is important to analyze the old structures for structural integration to understand the type and extent of damage the structure has sustained and what type of retrofitting is further required. Non-Destructive Testing (NDT) is a wide group of analysis techniques used in Science and Industries to evaluate the properties of a material component on the system without any damage. Structural audit is an overall health and performance check-up of building .It is important to the building to check their safety and they have no risk. It is process of analyses of building and this process suggest to perform better in its service life, structural audit is an important tool for knowing the real status of the old building. Currently, safety of old buildings which is present in heavy rainfall area is one of the critical issues in India though, there are many practices to conduct structural audit of such buildings. The need of structural audit is for maintenance and repairs of existing structure whose life has exceeded the age of 30 years to avoid mishaps and save valuable human life. The concrete is widely used as construction material being inexpensive, easy for construction, application and because of it high strength-cost ratio. More than ever, the construction industry is concerned with improving the social, economic and environmental parameters of sustainability. NDT measurement technique has been used for more than two decades for concrete quality evaluation and assessing concrete compressive strength. During this period, the advantages of its use and the factors influencing the test results have been widely reported. The major issues in executing the Structural Audit are Peoples are not aware about the importance of the Audit. They do not come forward. There are many misconceptions about the audit such that the buildings will be demolished. Secondly there is no Standard or Legal Procedure to Carry out Structural Audit. It completely depends on knowledge and Experience of Structural Engineer.

DOI: 10.61137/ijsret.vol.10.issue2.143

Moderate Air Quality Prediction Model Using Regression
Authors:- Vishnu A M, Vinish A, M.E

Abstract-In response to the escalating environmental challenges posed by air pollution, our project aims to develop a comprehensive and user-friendly Tracking and Predicting Air Pollution Platform. This innovative web-based system consists of three distinct components – Past, Present, and Future – each offering valuable insights into air quality dynamics. The” Past” section leverages historical data to provide users with a retrospective analysis of air pollution trends. Through interactive visualizations and detailed summaries, users can explore patterns, identify sources of pollution, and comprehend the evolution of air quality in their region. The” Present” component offers real-time air pollution values, enabling users to stay informed about the current state of the atmosphere. This section not only displays live data but also performs a comparative analysis against normal pollution levels, shedding light on the immediate environmental impact. The” Future” segment harnesses advanced forecasting models to predict future air pollution trends. By utilizing cutting edge algorithms, the platform provides users with actionable insights into upcoming pollution scenarios, enabling people to take precautions and make educated judgments. The website serves as a one-step destination for comprehensive details about the air pollution. Engaging visual representations, such as charts and graphs, facilitate a user-friendly experience, making complex datasets easily understandable. Additionally, the platform elucidates the reasons behind the rise in pollution, fostering public awareness and understanding. Through this initiative, our project aims to bridge the gap between data analysis and public awareness. By presenting a holistic view of air quality – encompassing the past, present, and future – we empower individuals to comprehend the gravity of pollution issues and actively contribute to mitigating their environmental impact. This platform is not only a tool for making quick decisions, but it is also an educational resource, promoting a better understanding of air pollution and encouraging efforts to make the natural world cleaner and healthier.

A Comprehensive analysis on Life Cycle Optimization of Residential Air Conditioner Replacement Using AI
Authors:- Heeru Baghel, Assistant Professor Khemraj Beragi

Abstract-The aim of this paper is to present a general bibliographic review about recent scientific papers focused on the design and operation of air conditioning systems in green and smart buildings. The suggested review is developed using tools offered by the Scopus academic research directory, with a defined search criteria. Furthermore, the VOS viewer science bibliometric analysis software has been used. Nowadays, increasing energy efficiency and decreasing carbon footprint of current and future buildings, both green and smart is considered more important. The most frequent fields of research in scientific contributions related to the cooling of green buildings are: sustainable development, energy efficiency and the construction industry; while in smart buildings they are: energy efficiency, smart grids, energy management.

Customer Relationship Marketing of Clothing Brand in Shopping Malls and it’s Effects on Customer Decision Making and Satisfaction in Coimbatore City
Authors:- Assistant professor Mr. K. Chandrabose, Ms. V. Sharmila, Ms. A. Muthuselvi

Abstract-This study analyzes the dynamics of relationship marketing, or CRM, within the framework of the clothing sector in shopping malls, with a particular emphasis on how it affects consumers decision-making processes and levels of satisfaction in general. The research, which is positioned towards Coimbatore city’s backdrop, aims to shed light on the strategies used by clothing brands to build and maintain relationships with their customers in the bustling surroundings of shopping malls. The investigation adopts a mixed- methods approach, combining surveys and interviews to acquire information from a wide range of clients. The results add to the body of knowledge in research and have relevance for clothing industries that sell in malls. They offer suggestions for improving CRM tactics that will build long -lasting connections and maximize their levels of pleasure.

An Experimental Study on Strength Properties of Concrete by Partial Replacing Coarse Aggregate, with Broken Bricks, Glass Fibre, Rubber Tyre Waste and Fine Aggregate by Slag and Lime Kiln Dust
Authors:- Scholar Jyoti Vishwakarma, Professor Pawan Dubey, Professor Rakesh Sakale

Abstract-Global warming and environmental destruction are currently the most significant concern. Many people’s perspectives have shifted because of the realisation that the industrial production of greenhouse gases have serious negative consequences for the climate. Currently, there is a movement towards a zero-emissions society, away from the wasteful, over-consumption, mass-production norms of the last several decades. They can achieve this while also lowering our environmental effect by recycling and repurposing industrial waste. Researchers argued that depletion of natural resources is a major problem in the world. Many previous studies argued that use of recycled waste in industrial activities can save natural resources from depletion. Further, concrete is use commonly in construction industry, coarse (CA) and fine aggregate (FA) is a major and natural sources which are depleted. To save these various industrial waste can be used and mixed in concrete to improve its strength. Therefore, present paper aims to experimental study on strength properties of concrete by partial replacing coarse aggregate, with broken bricks, glass fibre, rubber tyre waste and fine aggregate by slag and lime kiln dust.

A Review on Eco Friendly Geo Polymer Concrete
Authors:- Assistant Professor MD Akber, Assistant Professor Kasarla Sagar, Assistant Professor Modugu Naveen Kumar

Abstract-In this study we do a point by point ecological assessment of geo polymer substantial creation utilizing the Existence Cycle Evaluation strategy. The writing shows that the creation of most standard kinds of geo polymer concrete affects an Earth-wide temperature boost than standard Normal Portland Concrete (OPC) concrete. While our outcomes affirm this they likewise show that the development of geo-polymer concrete has a higher ecological effect with respect to other effect classifications than an Earth-wide temperature boost. This is because of the weighty impacts of the development of the sodium silicate arrangement. Geo polymer concrete produced using fly remains or granulated impact heater slags based require less of the sodium silicate arrangement to be initiated. They in this manner have a lower ecological effect than geo polymer concrete produced using unadulterated metakaolin. In any case, when the development of fly remains and granulated impact heater slags is considered during the existence cycle evaluation (utilizing either a monetary or a mass distribution technique), apparently geo polymer concrete likewise affects an unnatural weather change than standard cement. This study features that future innovative work in the field of geo polymer substantial innovation ought to zero in on two expected arrangements. As a matter of some importance the utilization of modern waste that isn’t recyclable inside different ventures and besides on the creation of geo polymer substantial utilizing a blend of impact heater slag and enacted dirts. Moreover geo polymer substantial creation would acquire from utilizing waste material with a reasonable Si/Al molar proportion to limit how much sodium silicate arrangement utilized.

Design Aspects and Energy Efficiency of Green Buildings
Authors:- M.Renga Ramanujam, Professor Dr.V.Manjula

Abstract-Green building, also called sustainable design and development, is the practice of using healthier and more resource-efficient land planning, construction, renovation, operation, maintenance and demolition. Today, it’s much more than the original understanding of simply incorporating recycled materials into a home.In this globalization era, sustainable constructions have taken on some new steps to stimulate green building practice. Green buildings help reduce negative impacts on the natural environment by using less water, energy, and other natural resources; employing renewable energy sources and eco-friendly materials; and reducing emissions and other waste.Green building criteria basis are energy efficiency, material and resource conservation and sustainable design of the building itself. Energy efficiency still has a long way to go, due to some barriers that prevail in the practice of energy efficiency. This study will be done using a case of the construction sector in Malaysia. The data will be collected through an interview with several Property Development Companies or projects that apply the green building criteria. The recommendation is that more property development companies should be interviewed so that more comprehensive results can be gathered.

DOI: 10.61137/ijsret.vol.10.issue2.144

Safe-Eye: Weapon Detection Using Computer Vision
Authors:- Suraj Mittal, Dhananjay Kohli, Vedant Prasad, Tanmay Jain, Dr. Amutha S.

Abstract-This project is designed to create an efficient and accurate real-time weapons detection system using computer vision. Leveraging the power of Open CV and the cutting-edge YOLOv4 (You Only Look Once version 4) object detection algorithm, our system addresses the growing need for security measures in public places. The solution combines the speed of YOLOv4 with the versatility of Open CV to instantly analyze video streams, enabling rapid detection of threats. The project involves using Open CV to pre-process images, improve image quality, and feed them into the YOLOv4 model for object detection. The training model is effective in identifying various types of weapons, providing a strong defense against various security challenges. This system provides instant warning to security personnel by releasing the box tied around the found weapon. Additionally, the project demonstrates capacity and efficiency, making it suitable for use in crowded areas such as airports, schools and public events. The integration of technology technology demonstrates the potential of advanced security solutions to effectively reduce threats. The results of this work will help improve stability and make it possible to find tools that will use Open CV and YOLOv4 integration.

Review Paper on Surveillance Robot Using IOT
Authors:-Yash P. Chitale, Sahil S. Gandhi, Rucha N. Shinde, Prof. Amol R. Sutar

Abstract-This project explores the integration of robotics, IoT, and real-time data processing in the context of an innovative surveillance robot. Focusing on key components such as Arduino, Raspberry Pi, sensors, cameras, and wireless communication, the study discusses challenges and solutions in hardware integration, software development, communication protocols, security, and IoT implementation. By merging robotics with IoT, the research offers valuable insights into the future of intelligent surveillance systems, providing concise guidance for researchers and engineers.

Effect of Guided-Inquiry Teaching Method on Academic Performance of Philippine Public Secondary School Grade 12 Students: A Quasi-Experimental Research
Authors:-Jomar P. Flores, Nivea Louwah D. Sermona

Abstract-This study investigated the effect of the guided inquiry teaching method on the academic performance of Philippine public secondary school grade 12 students in Electrical Installation and Maintenance. A quasi-experimental design was adopted for the study. A pre-test and post-test were conducted for both control and experimental groups. The instruments used for data collection were 30 objective questions tagged as the Electrical Installation and Maintenance Achievement Test (EIMAT). The instrument was validated by five experts in the field. To determine the instrument’s reliability, Cronbach’s alpha formula was used and a reliability coefficient of 0.84 was obtained. Means and standard deviations were used to analyze the descriptive data, while the null hypothesis was tested using a t-test at a 0.5 level of significance. Findings revealed that students taught with the guided-inquiry teaching method performed better with higher post-test mean scores than those taught using the lecture-demonstration teaching method. Also, findings indicated that the guided-inquiry teaching method makes the students perform better in terms of their performance skills than the lecture-demonstration teaching method. Given the findings, it was recommended, among others, that the guided-inquiry teaching method be adopted in technical colleges and secondary schools for instruction in EIM to improve the academic performance of the students.

DOI: 10.61137/ijsret.vol.10.issue2.137

Social Media’s Impact on Food Industry
Authors:-Palak Sinha, Mohd. Faisal, Krishna Rajput, Ms. Tanya Sharma

Abstract-This in-depth analysis examines the profound impact that social media has had on consumer behavior and how it has changed the food industry. The unique connection between advanced stages and the culinary scene is analyzed, featuring the crucial job of virtual entertainment in forming dietary inclinations, dietary patterns, and feasting decisions. The review researches the meaning of client created content, powerhouse advertising, and arising advancements in reshaping the food environment, with suggestions for nourishment, culinary culture, and monetary strengthening. Tending to scholastics, industry experts, and policymakers, this paper offers important bits of knowledge into the developing computerized age food industry.

DOI: 10.61137/ijsret.vol.10.issue2.138

Fettle: A Vegetarian Diet Planner Website
Authors:-Abdul Aziz, Vaishnavi Dhule, Smriti Dube, Mrs. Surekha Mali

Abstract-The Vegetarian Diet Planner project has been developed as an innovative solution for individuals embracing a vegetarian lifestyle, with a focus on providing personalized and user-centric dietary planning. Leveraging the MERN stack and integrating Firebase for secure authentication, the platform offers a seamless user experience. Featuring user registration and data storage capabilities, the system assigns each user a unique identifier for efficient record-keeping and retrieval of customized diet plans. Algorithms such as bcrypt for password hashing ensure robust security, while JWT tokens facilitate secure authentication. Additionally, the platform incorporates algorithms for recipe analysis and nutritional calculation, enabling the generation of personalized diet plans tailored to individual preferences and dietary requirements. Accessible through a secure login system, the Vegetarian Diet Planner ensures a user-friendly experience, with administrators managing user information and creating customized diet plans, and users accessing their personalized plans through an intuitive interface. By revolutionizing the vegetarian diet planning experience, this digital solution aims to promote efficiency, personalization, and overall well-being for users at various stages of their dietary journey.

Influence of Instagram Marketing on Fashion and Style of Teens
Authors:-Sudarsan SP, Swetha E, Karthikeyan, Krish N

Abstract-Instagram might focus on its evolution, impact on society, and key features. It could delve into its role as a social media platform for sharing photos and videos, its algorithm-driven feed, influencer culture, advertising strategies, and controversies surrounding privacy and mental health. Additionally, it might explore Instagram’s role in shaping trends, fostering communities, and influencing user behavior and perceptions.

Recognition of Phishing Website Using Techniques of Machine Learning
Authors:-Onkar Pawar

Abstract-In today’s fast-changing digital world, we’re heavily involved in the online space for both work and personal activities. But, this shift to spending more time online has led to an increase in cybercrime. Criminals are taking advantage of the internet to target people and organizations, trying to steal important information or money. The internet has unintentionally become a place for illegal activities like fake online stores, financial scams, and spreading harmful software. As the internet keeps growing, online shopping is becoming more popular than traditional shopping. However, this change has also led to scams like phishing, where bad actors trick people into giving away personal information. So, there’s a big need to find and stop websites that are part of these crimes, protecting people from falling for these tricks. In order to distinguish between authentic websites and phishing websites, this study explores various machine learning techniques. In the context of zero-hour phishing attempts, in particular, the effectiveness of machine learning approaches in predicting the legitimacy of websites is under the limelight. These solutions are a better option for fending against cutting- edge phishing attempts because of their extraordinary capacity to quickly identify evolving phishing threats. In this work we are using three machine learning algorithms viz DT, RF and KNN. We are able to achieve accuracy more than 95% for each algorithm.

MQTT Publisher: Bridging Devices and Data in the Internet of Things Era
Authors:-Assistant Professor Priyanka Shinde, Miss.Sunishtha Sakunde, Miss.Sapna Kudale, Miss.Virakshi Habbu

Abstract-The MQTT (Message Queuing Telemetry Transport) protocol has emerged as a mainspring technology in Machine-to- Machine (M2M) and Internet of Things (IoT) ecosystems, facilitating efficient communication between interconnected devices. This abstract aims to provide a incisive overview of the MQTT protocol’s significance, its underlying principles, and its role within M2M and IoT systems. MQTT, designed as a lightweight messaging protocol, prioritizes low bandwidth and low power consumption, making it particularly well-suited for resource-constrained environments characteristic of M2M and IoT deployments. Its publish- subscribe messaging pattern enables asynchronous communication, allowing devices to exchange data without direct, continuous connections. This paradigm aligns with the distributed nature of M2M and IoT architectures, where innumerable devices communicate over diverse networks, often with fitful connectivity.

Unveiling the Complexities of Behavioral Finance: Understanding Human Decision Making in Financial Markets
Authors:-Preeti Padma Sahu, Aniket Burman

Abstract-Behavioral finance is a subject of finance that studies the impact of psychological factors on how people make financial choices. This study intends to make valuable contributions to the expanding body of research in behavioral finance by exploring the behavioral biases and heuristics that affect investors’ decision making processes. Through a comprehensive review of existing literature, key concepts such as loss aversion, overconfidence, and herding behavior are examined, providing insights into the irrational behavior observed in financial markets. The objective of this research is to empirically analyze the impact of behavioral biases on investment decisions using a mixed methods approach combining qualitative and quantitative analysis. Data is collected through surveys and interviews with investors, supplemented by quantitative analysis of market data. The findings reveal significant correlations between certain behavioral biases and investment outcomes, shedding light on the complexities of human behavior in financial decision making. The conclusions drawn from this study underscore the importance of understanding and mitigating behavioral biases to enhance investment performance and promote financial wellbeing. This research contributes to both theoretical understanding and practical applications in the field of behavioral finance, offering valuable insights for investors, financial practitioners, and policymakers alike.

DOI: 10.61137/ijsret.vol.10.issue2.139

An Exploratory Study on Bioenergy- A Solution for Affordable Modern Green Energy
Authors:-S. Pramu Mira, Assistant Professor Dr. Praba.K

Abstract-This article explores the potential of algae-based bioenergy as a sustainable cost-effective alternative. Algae’s rapid growth and high lipid content make it a promising source of Bioenergy. The article discusses challenges, models, methods, goals and technology in bioenergy. Bioenergy’s role in reducing carbon-emission. It highlights the socio-economic benefits and challenges associated with algae-bioenergy. This article aims to provide a concise overview of advancements and opportunities in utilizing algae for green energy, contributing to the ongoing transition towards sustainable and accessible energy solutions.

NIRBHAY: Analysis and Prediction of Crime
Authors:-Ms. Sayali Angat, Mr.Kapil Gharat, Mr.Angarak Gurav, Ms. Harshala Patil, Professor Prachi Sorte

Abstract-The increasing complexity and scale of urban areas requires new crime analysis and prediction strategies The research project focuses on harnessing the power of machine learning algorithms to analyze historical crime data and predict future crime in specific areas. This study explores the potential of predictive analytics for crime prevention and law enforcement using clinical data that includes various crime types, demographic data, and characteristics of the area. This approach involves pre-processing the dataset to resolve missing values, outliers, and feature engineering to extract relevant information. To find patterns and correlations between variables, a range of learning models such as support vector machines, random forests, and decision trees are fed into the data. Utilize measures like accuracy, precision, recall, and F1 score to assess the performance of the model. Furthermore, the actual offense is incorporating predictive models into internet platforms in order to allow users to get predictions based on characteristics like time, location, and publicly accessible data. The platform provides law enforcement, legislators and urban planners with information to better allocate resources and prevent crime. The results demonstrate the effectiveness of the machine learning process in crime analysis and prediction, with high accuracy in predicting crime scenes. The use of the website promotes easy access and usability, providing participants with the skills to reduce crime and increase public safety in the city.

DOI: 10.61137/ijsret.vol.10.issue2.140

Comparative Seismic Study of RC Multistoried Structure with Shear Wall at Different Locations and in Different Seismic Zones
Authors:-Sachin Mishra, Professor Rajeev Chandak

Abstract-Earthquake is a major concern for the engineers to give stability to the structures. Properly designed and detailed structures with lateral load resisting component i.e. shear walls, bracings etc have shown very good performance in past earthquakes. Shear Walls are one of the most commonly adopted lateral load resisting systems. Shear Walls possesses very high in-plane stiffness and strength, this allows them to resist large horizontal, gravity and lateral loads caused by seismic and wind loads. Besides that they also carry gravity loads. This dissertation work was an attempt towards distinguishing that how introduce a shear wall in a structural system which can make in difference in performance of the structure against seismic disturbance. Most of the structures in India are RC frame, and seismic disturbance are felt every now and then in some or the other part of the country. Hence through this dissertation it was tried to appreciate the effectiveness and role of this small extra structural elements that can protect both life and property, at least for most of the earthquakes In this dissertation work we considered 5 models (with & without shear wall) with G+14 storey & 30m x 30m plan area and comparison has been made for following 3 Parameters namely Base Shear, Storey Shear, Inter storey Drift for ground motion in x direction in all Seismic Zones of India. The Seismic Analysis performed according to IS 1893- 2016 (PART I) by Dynamic Response Spectrum method (RSA) using the well known structural analysis and design software Staad. Pro V8i . This analysis will help in understanding the improvement in seismic resistance through the implementation of shear walls and their ideal location in multi storey structures.

Review on Urban Road Safety and Sustainable Transportation Policy through the Hierarchy of Hazard Controls
Authors:-Naveen Singh Rathore, Assistant Professor Mr. Vinay Deulkar

Abstract-Governments globally have endorsed Vision Zero, declaring that no person should be killed or permanently injured on public roads. Concurrently, the wider social, public health, and environmental implications of urban structure and transport choices have gained intense policy attention, as cities aim to transition toward sustainable accessibility. This is especially the case as research reveals a range of counter-intuitive road safety dynamics; many narrow approaches to road safety management appear to trigger adverse risk compensation and negative externality effects, potentially running counter to broader sustainability goals. Recognizing the urgent need to integrate road safety with broader urban sustainability measures, this synopsis presents a review of road safety literature using the established Hazard Control Hierarchy. In doing so, we identify and categorize opportunities to more effectively combine Vision Zero with broader sustainable accessibility policy objectives. We synthesize the literature against the Hazard Control Hierarchy to devise a framework to more effectively integrate the work of professional disciplines which shape the safety and sustainability of the urban built environment.

Review on Exploring Causes of Delay in Payment from Parties Involved in Road and Highway Projects in India
Authors:-Pratyush Singh, Assistant Professor Mr. Vinay Deulkar

Abstract-Construction delay is one of the serious concerns of the road industry in INDIA. The study aims to identify the causes of delays that have adverse effects on road projects in terms of time, cost and quality. Literature of different types of delays, their causes and effects on road construction projects were intensively reviewed. The study identified a number of causes of delays at great risk and have adverse effects on construction of road projects. A questionnaire based on 15 causes and 5 effects was sent to the clients, consultants and contractors.

Supply Chain Management Practices and its Effects on Textile Industries in Tiruppur
Authors:-Assistant Professor Ms. S. Priyanka, N. Srimathi

Abstract-A wide range of tasks fall under the umbrella of supply chain management (SCM), including ordering fulfilment, inventory management, warehousing, materials handling, supply/demand planning, customer support, sourcing and procurement, and packaging. Increasing demand in both local and international markets is opening up new potential for the Indian textile sector, which is centred in the Coimbatore region of Tamil Nadu. India is one of the world’s leading hubs for textile manufacture. Raw materials, complements, and apparel production are all part of the textile industry’s long chain. Supply chain management (SCM) is widely regarded as a traditional management technique that manufacturers can utilize to enhance product quality, lower costs for goods and services, and accelerate product delivery in a fiercely competitive market. We have applied Simple Random Sampling technique to select the sample for the study. Totally 118 sample respondents were selected and it was analysed using simple percentage analysis, ranking analysis Anova and chi-square was used to analyse the collected data. This research contributes to academic understanding and provides actionable insights for fostering sustainable growth in Tirupur’s apparel export sector.

Evaluation of Acoustic Comfort in Library Building Spaces
Authors:-Adejo Chubiyojo Daniel, Professor Dare Abel, Umoh Itoroabasi Judith, Otuonuyo George Arerosuoghene

Abstract-Acoustic comfort is an important aspect of the quality of library spaces, as it affects the users’ satisfaction, performance, and well-being. However, the design of acoustic environments in modern public libraries is often challenging, due to the diversity of functions, users, and sound sources. This paper aims to evaluate the acoustic comfort in library building spaces, using a soundscape approach that considers both the physical and perceptual aspects of sound. The paper reviews the existing literature on acoustic design strategies and soundscape methods for library spaces, and presents a case study of the University of Birmingham Library, a modern public library with an open-plan layout and a variety of activities. The paper discusses the findings and implications of the survey, and provides some recommendations for improving the acoustic comfort in library building spaces.

Innovative Strategies and Practices for Enhancing Energy Efficiency in Shopping Mall Design
Authors:-Sekene, Anthony .B, Oduwaiye Emmanuel Champion, Okon, Utibeabasi Praise

Abstract-The design and operation of shopping malls play a crucial role in shaping urban landscapes and impacting energy consumption patterns. In response to growing environmental concerns and the need for sustainable development, there is an increasing emphasis on implementing innovative strategies and practices to enhance energy efficiency in shopping mall design. This research explores the key principles and approaches for achieving energy efficiency in shopping mall architecture, highlighting case studies and examples of successful implementation. Through the integration of advanced technologies, green building materials, renewable energy sources, and smart design solutions, shopping malls can mitigate their environmental impact, reduce operational costs, and create more sustainable and resilient built environments. The abstract concludes with recommendations for stakeholders to promote further advancements in energy-efficient shopping mall design, emphasizing the importance of collaboration, education, and ongoing innovation in addressing the challenges of climate change and resource depletion.

A Transformer-Based Siamese Network for Change Detection
Authors:-Shreyansh Goyal, Riya Subash, Kaustubha A Madyalkar, Cia Shetty, Krishnan R

Abstract-This paper uses a Siamese network structure employing a transformer-based architecture, designed for the task of Change Detection (CD) using a pair of co-registered remote sensing images. In contrast to recent CD frameworks predominantly relying on fully convolutional networks (ConvNets), our proposed method integrates a hierarchically structured transformer encoder with a Multi-Layer Perception (MLP) decoder within a Siamese network architecture. This amalgamation effectively captures multi-scale long-range details essential for precise CD. Experimental results obtained from two distinct CD datasets demonstrate that the proposed end-to-end trainable Change Former architecture outperforms its predecessors in terms of CD performance. In addition to the proposed Change Former model, we have implemented a user interface for intuitive visualization and analysis of detected changes, enhancing the accessibility and user-friendliness of our approach.

Advancing Healthcare through IoT-enabled Prosthetics and Orthotics: A Comprehensive Framework for Smart Rehabilitation
Authors:-Chandresh Rajpoot

Abstract-This research aims to pioneer advancements in healthcare by leveraging the capabilities of the Internet of Things (IoT) in the domain of prosthetics and orthotics. The proposed framework encompasses smart prosthetic and orthotic devices, remote patient monitoring, predictive maintenance, data analytics, security and privacy considerations, human-machine interfaces, tele health integration, and sustainable IoT solutions. The objective is to enhance patient care, improve rehabilitation outcomes, and contribute to the evolution of personalized and technology-driven healthcare practices.

Human Resources and Skill Gap in Logistics Services Industry with Reference to Coimbatore
Authors:-Assistant Professor Dr. K. Chandrabose, Ms. B.K Monisha, Mr. Harihara Sudhan

Abstract-Regarding purchasing power parity (PPP), Namibia is the fourth- largest nation and among the economies developing the quickest in the world. The globalization of business have created a highly competitive and unstable environment for the Indian sector. Infrastructure bottlenecks, growing supply chain network uncertainly, shortened product life cycle, and a wide range of product have brought up concerns about selecting and collaborating with appropriate supply chain partners (suppliers, consumer, and logistical service providers as supply chain partners), promoting mutual trust among them, and developing an appropriate performance measurement system. Globalization and shifting economic conditions achieve it imperative for supply chain companies to create tactics that provide customers with distinct value at the best possible price. For service providers to keep up with the fierce competition, they urgently require human resources and a wide range of experience in logistics. This study report aims to examine the evolving trends in Indian logistics and the increasing need for human resources with the necessary skills and training. The researcher has attempted to highlight the worsening skill gap scenario in the business because of the Indian logistics sector’s shift from using only internal employees to using sophisticated a supply chain management system that is third party (3Pl).

Impact of Sensory Experiences in the Design of a Cultural Center Celebrating African Heritage in Lekki-Epe, Lagos State
Authors:-Ojo Dipo, Abraham Zaccheus

Abstract-This study explores the adoption of the sensory experiences shapes the design of a cultural center celebrating Africa heritage in Lekki-Epe, Lagos State. Cultural centers are important because they help in learning about our history and traditions. In places like Lekki-Epe, where people come from different backgrounds. This study employed a descriptive research design on exploring how adding sensory experiences shapes the design of a cultural center celebrating Africa heritage in Lekki-Epe, Lagos State. The target population includes the Lekki-Epe community, comprising of architects, structural engineers, and local interior designers. This study found out that visitors really appreciate colorful displays, vibrant artworks, and dynamic exhibits. These visual elements not only catch their eye but also tell stories and evoke emotions, making the cultural center interesting. Visitors enjoy hands-on activities, tactile displays, and interactive installations that allow them to engage with the exhibits in a more physical way. And when it comes to smell, incorporating scents like aromatic plants or traditional fragrances can really enhance the overall experience, triggering memories and emotions. Hence leveraging sensory design principles, cultural institutions can create inclusive and transformative spaces that celebrate diversity, foster cultural understanding, and inspire meaningful connections between individuals and communities.

Quicklearn:- Educational Website (E-Learning)
Authors:-Piyush Agarwal, Krishna Sharma, Priyansh Vijay

Abstract-Quick Learn is a cutting-edge online resource designed to give B.Tech students at Rajasthan Technical University (RTU) simple access to a wide range of learning materials. QuickLearn, which aims to democratize education, provides a wide range of study resources in a number of academic subjects, including textbooks, lecture notes, study guides, and past year question papers. This study clarifies QuickLearn’s features, functionality, and effects on RTU B.Tech students’ academic journeys, highlighting the platform’s contributions to academic success, self-directed learning, and community participation. With its user-friendly interface, sophisticated search features, and dedication to frequent updates, Quick Learn is a prime example of how technology can revolutionize education by enabling anybody to access it, regardless of location or means.

Quicklearn:- Review on Digital Spring Load Testing Machine
Authors:-Yash Mendhekar, Dinesh Sahare, Jay Raut, Shubham Gupta, Aftab Ahmad, Dr. I. A. Khan

Abstract-The design of a digital spring load testing machine involves the creation of a sophisticated apparatus capable of accurately measuring the mechanical properties of various types of springs. This abstract outlines the key aspects of designing such a machine . The digital spring load testing machine consists of several main components, including a sturdy frame, a loading mechanism, measuring instruments, and a control panel. The frame provides the structural support for the machine and ensures stability during testing operations. The loading mechanism applies a controlled force to the spring under test, allowing for precise measurement of its load-deflection characteristics. Measuring instruments, such as load cells and displacement sensors, are used to capture data on the applied load and spring deflection. These instruments are interfaced with digital displays or computer software, enabling real-time monitoring and analysis of test results. The control panel facilitates user interaction with the machine, allowing for input of test parameters and adjustment of testing conditions.

Quicklearn:- Financial Transactions Using Machine Learning
Authors:-Assistant Professor Dr. Pankaj Malik, Anoushka Anand, Anmol Kumar Baliyan, Anant Dongre, Palak Panwar

Abstract-Credit risk assessment and fraud detection are crucial tasks in the financial industry, essential for maintaining the stability and integrity of financial institutions. Traditional methods often fall short in accurately assessing risk and detecting fraudulent activities in a timely manner. In recent years, machine learning has emerged as a powerful tool for enhancing these processes, leveraging large volumes of transactional data and sophisticated algorithms to make more informed decisions. This research paper explores the application of machine learning techniques in credit risk assessment and fraud detection within financial transactions. The paper begins with an overview of the importance of accurate risk assessment and fraud detection in financial transactions and introduces the role of machine learning in addressing these challenges. A comprehensive literature review is conducted to analyze existing methodologies, algorithms, and research trends in the field. Data acquisition and preprocessing techniques are discussed, emphasizing the importance of clean and relevant data for model training. Feature engineering strategies are explored to extract meaningful information from financial transaction data and enhance the predictive capabilities of machine learning models. Various machine learning algorithms suitable for credit risk assessment and fraud detection are examined, including logistic regression, decision trees, random forests, support vector machines, and neural networks. Ensemble methods and model evaluation metrics are discussed to assess the performance of these algorithms, with a focus on metrics such as accuracy, precision, recall, and ROC-AUC. The paper presents case studies and experimental results illustrating the application of machine learning models in real-world scenarios, highlighting their effectiveness in improving risk assessment and fraud detection processes. Additionally, challenges such as imbalanced datasets, model interpretability, and regulatory compliance are discussed, along with potential research directions and future trends in the field. In conclusion, this research emphasizes the transformative potential of machine learning in credit risk assessment and fraud detection within financial transactions. By leveraging advanced algorithms and data-driven approaches, financial institutions can enhance their decision-making processes, mitigate risks, and safeguard against fraudulent activities, ultimately contributing to a more secure and resilient financial ecosystem.

Quicklearn:-Comprehensive Cybersecurity Pentest Methodology for Car Dongle Systems
Authors:-Juan A. Sanchez, Jesus Munoz

Abstract-Low budget car dongles are widely used worldwide and problems regarding the security of these OBD devices, with mobile connectivity and GPS, could affect user privacy as well as car security. Cyber-attacks on vehicles have been a concern over the past few years with several headlines news of hacks around the world. The study provides a systematic approach to assessing the cybersecurity of a car dongle system, covering various aspects such as hardware, firmware, mobile app, cloud API, and associated communication channels. It emphasizes thorough analysis, proactive risk management, and continuous improvement to enhance the security posture of the target system and mitigate potential threats and vulnerabilities.

Quicklearn:-A Comprehensive Study on Big Data Processing with Apache Spark
Authors:-Mukesh Singh, Nikhil Bhardwaj, Raghav Sringhi, Mr. Laxmikant Vashistha

Abstract-The research paper explores the dynamic realm of big data processing, focusing on Apache Spark’s evolution, applications, and advancements in addressing challenges posed by massive data volumes and complexity. Apache Spark represents a significant shift in data processing systems, offering a robust framework to handle intricate demands of large datasets, as discussed in the paper’s exploration of historical context, architecture, and applications. In the current landscape of big data analytics, Apache Spark emerges as a powerful tool for organizations seeking actionable insights from expanding datasets, promoting innovation and efficiency in data processing.

An Interdisciplinary Approach to Enhancing Energy Efficiency through Human-Centric Design: A Case Study of Public Space Integration in Shopping Malls
Authors:-Okon Utibeabasi Praise, Dr O. Uwakonye, Sekene Anthony B., Oduwaye Champion Emmanuel

Abstract-This research looks into how human-centered design might improve energy efficiency in commercial settings, with a special emphasis on how public spaces can be integrated into shopping malls. There is a rising need to investigate cutting-edge strategies that not only minimize energy usage but also give human comfort and well-being priority as worries over energy consumption and environmental sustainability develop. This study uses a mixed-methods approach to assess how well public space integration contributes to the creation of a more user-friendly and energy-efficient shopping mall environment. It does this by combining quantitative measurements of energy usage with qualitative analysis of design principles. The results show that well-planned public areas improve user comfort and save a substantial amount of energy thanks to better natural lighting, ventilation, and thermal comfort. The findings highlight the significance of human-centered design in promoting sustainable practices in business environments and offer insightful information to architects, designers, and legislators who wish to advance user pleasure and energy efficiency in built environments.

Blockchain Wallet Tracker
Authors:-Vedant N. Patil, Alina A. Haji Peera, Rohit N. Gavhane, Yash S. Thakare

Abstract-The Blockchain Wallet Tracker is a web-based tool designed to empower users with seamless and real-time monitoring of their crypto currency wallet transactions across various blockchain networks, including Ethereum, Polygon, and Binance Smart Chain. As the adoption of blockchain technology continues to surge, there is a growing need for comprehensive and user-friendly tools that provide insights into transaction activities. This project aims to address this demand by delivering a robust and user-centric solution. By leveraging APIs from prominent blockchain explorers such as Etherscan, Polygon Scan, and BscScan, users gain access to transaction data, including sender and receiver addresses, transaction values, timestamps, and network specifics. This data is presented in an intuitive and secure web interface. Key features of the Blockchain Wallet Tracker encompass a user dashboard for real-time transaction updates, user authentication for secure access, and a resilient backend system for data management. Data security is paramount, with encryption, access control, and threat detection mechanisms implemented to safeguard user information. The project’s estimated size is around 30 KLOC (Kilo Lines of Code), equivalent to 15 Person-Months of development effort. The projected development time is approximately 3.75 months, with a skilled team of four individuals. In a world where crypto currencies play a pivotal role in financial transactions, the Blockchain Wallet Tracker empowers users with the means to effortlessly monitor their wallet activities, bridging the gap between blockchain networks and enhancing the user experience.

Assessment of a Job Suggestion Tool through the Application of Machine Learning
Authors:-Research Scholar Mangal Sawle, Assistant Professor Vikas kalme

Abstract-This study is being conducted with the intention of evaluating the effectiveness and performance of a job suggestion tool that makes use of machine learning techniques. The objective of the programme is to provide users with individualised recommendations for careers that take into account their skills, experiences, and interests as the foundation for the proposals. The review process includes a number of different components, including the collection of data from users, the training of a machine learning model, and the evaluation of how accurate and useful the tool is in terms of linking users with acceptable job opportunities. Additionally, the study takes into consideration significant factors of the user experience, such as the usability of the interface, the general enjoyment of the user, and the design of the interface. Not only do the findings provide developers and stakeholders with valuable information, but they also provide insights into the capabilities and limitations of the tool, as well as potential areas for further development.

An Examination of Breast Cancer through the Lens of Deep Learning
Authors:-Scholar Rishabh Shrivastava, Professor Sudha Sharma

Abstract-Breast cancer ranks second worldwide after lung cancer. Women are always most impacted by this problem. Women who can have children are more likely to die from breast cancer, the most common malignancy. Medical imaging is no different since there is always more to learn and potential for improvement in every field. It is anticipated that early detection and treatment of cancer will reduce the number of deaths. Health care workers may improve diagnostic accuracy using machine learning. Deep learning, or neural networking, may be used to discern healthy breasts from cancerous ones. This method may distinguish healthy from sick breast tissue. A thorough study examined the subject, including breast cancer and Indian women’s screening procedures. A major goal of the review was to discover this. A literature research utilised several libraries and other sources. Researchers were told to use “breast carcinoma” and “breast cancer awareness,” as well as “knowledge” and “attitude,” and the gender-neutral phrase “women.” India also contributed to the study. This search does not include English-language articles from the last twelve years.

An Analysis of the Load Balancing Mechanism Used in Cloud Computing Review Article
Authors:-Research Scholar Sakshi Singh, Assistant Professor Pradeep Tripathi

Abstract-Cloud registration gives users access to a range of resources and enables information exchange. Clients are only billed for the resources they actually use. Cloud computing, which stores data in the cloud, maintains the assets and information in a public domain. The level of information hoarding rises rapidly when circumstances are open. Similarly, stack adjustment is a first test carried out in the presence of cloud cover. In order to prevent any one hub from being overworked, load adjustment entails dividing the dynamic workload across numerous hubs. It helps ensure that assets are used lawfully. Furthermore, it enhances the system’s overall functioning. Many of the algorithms now in use provide enhanced asset utilisation and stack adjustment. Among the many different kinds of stacks that may be utilised in cloud computing are memory, CPU, and system stacks. Load adjustment refers to the procedure of identifying overcrowded hubs and then shifting the additional load to under loaded hubs.

Age Vision:AI Powered Facial Age Progression Platform
Authors:-Associate Professor Dr.Deevi Hari Krishna, Sikhakolli akshay, A.N.S.Manikumar, D.Hemanth Sukumar

Abstract-Facial image analysis in the context of aging progression is a crucial area of study within the computer vision community. While machine-based solutions have been extensively explored, human performance in this domain remains relatively understudied. This paper aims to address this gap by conducting a detailed investigation into human proficiency in face verification and age estimation tasks using facial images captured at various stages of aging. Through meticulous experimentation, we analyze the influence of factors such as age group, age gap, race, and gender on human capabilities in facial analysis. Our findings provide valuable insights into the complexities inherent in facial analysis across different demographic contexts and age brackets. Particularly noteworthy is the increased difficulty observed in age estimation tasks when analyzing adult photos compared to those of young individuals, emphasizing the need for tailored approaches. Our study establishes a foundational reference for machine-based solutions by comprehensively examining human capabilities in facial analysis across aging progression. We anticipate that our insights will inform the development of more robust algorithms, thus advancing our understanding and capabilities in facial analysis across diverse demographic contexts. Furthermore, our findings have significant implications for various applications including security, healthcare, and digital entertainment, where accurate age estimation and facial verification are crucial. In conclusion, this paper contributes to the growing body of research aimed at understanding human abilities in facial analysis. By leveraging GAN modeling and CNN networks in Py Torch, our study aims to propel advancements in computer vision technologies, paving the way for more effective and inclusive methodologies.

HEAL:AI Powered Mental Health Chatbot
Authors:-Vikrant Ahir, Dhananjay Gharat, Maithilee Vishe

Abstract-A Chatbot is a feature enabled by artificial intelligence (AI) that functions similarly to a human conversation partner. It uses natural language processing(NLP) and machine learning (ML) techniques to understand and analyze user queries and deliver intelligent, human-like responses. Conversational agents serving as a go-between for the user and the system. With regular talks, the chatbot therapist aims to alleviate the symptoms of mental disease(stress, anxiety, depression) and encourage improved mental health through the application of cognitive behavioural therapy (CBT). Cognitive Behavioral Therapy (CBT)modifies an individual’s thought processes and behavior by addressing their beliefs, imagination, and attitude. Most of these treatments are offered without charge and at any time. Individuals are truthful. People are usually more open to talk online than they are in person. The public sector has access to conversational agents such as Flow, Wysa, Woebot, joy, and Talk space. Chatbots are an essential tool for everyday user motivation and for educating people about the possibilities that technology presents.

Sustainable Materials of Innovative Construction Techniques in Green Building
Authors:-P.Pratish, Professor Dr.M.Narmatha

Abstract-Materials are the essential components of buildings construction. Chemical, physical and mechanical Properties of materials as well as an appropriate design are accountable of the building mechanical strength. The design of green buildings should thus begin with the selection and use of eco-friendly materials with related or better features than traditional building materials. Building materials are usually selected through functional, technical and financial requirements. The green building movement has gained significant traction as a means to address the environmental impact of buildings and promote sustainable development. This research paper examines the application of green building practices in the context of sustainable development in India. Buildings in India account for a substantial portion of resource consumption, energy use, and carbon dioxide emissions. Uncontrolled urban development has further intensified these environmental challenges. Recognizing the need for a more sustainable approach, the green building movement has emerged as a solution to minimize the environmental footprint of buildings.

DOI: 10.61137/ijsret.vol.10.issue2.146

A Study on Awareness about Automobile Spare Parts Exports of Selected Districts in Western Zone, Tamil Nadu
Authors:-Professor Dr. T. Vasumathi, P. Rohit Kumar

Abstract-This study looks into how much knowledge there is about vehicle spare parts exports in a few areas in the western region of Tamil Nadu, India. Even with the notable expansion of the business, research on stakeholder awareness is still lacking. It investigates awareness among producers, suppliers, exporters, and legislators in areas like Coimbatore, Tiruppur, Erode, and Salem through surveys, interviews, and data analysis. In an effort to raise awareness and encourage export-related activity, the findings point up opportunities and gaps. This study adds to our understanding of export dynamics in the automotive industry by examining elements that influence awareness, such as avenues for disseminating information and policy frameworks. In the end, it seeks to educate industry participants and policymakers on the need of raising knowledge regarding automobile spare parts exports from Tamil Nadu’s western zone, with implications for opportunities in the global market and sustainable growth.

Exploring the Use of Biophilic Design Trends/Innovations for Vertical Living
Authors:-Tejumaiye Ayomide Oluwatimilehin, Adewole Esther Adegbolafunmi, Akinyemi Hafeez Olorunsegun

Abstract-Rapid urbanization and population growth around the world have created an increased demand for sustainable and space-efficient living solutions. In answer to this problem, biophilic design arose as a comprehensive strategy that incorporates nature into architectural and interior aspects. This study investigates the emerging trends and developments in biophilic design, with a particular emphasis on their use in vertical living environments. By investigating the convergence of technology, environmental consciousness, and urban development, we hope to shed light on biophilic design’s potential to improve the well-being and quality of life for residents of vertical communities. The study discusses essential biophilic design principles, examines case studies, and predicts future breakthroughs that will influence the vertical living landscape.

Sentiview: AI-Driven Sentiment Analysis and Insight Extraction from YouTube Comments
Authors:-Associate Professor Dr.Deevi Hari Krishna, Teleprolu Sai Sri Harshini, Gudipati Pavani, Nagabhairu Varshitha

Abstract-In our research, we employ sentiment analysis to scrutinize public sentiment by processing comments on YouTube as our primary data source. Our goal is to identify a broad spectrum of sentiments, including positive, negative, and neutral, as well as to understand the underlying opinions and attitudes expressed in the text. We utilize comments on YouTube to gain insights into public viewpoints on various aspects of videos. Given that YouTube boasts over a billion unique users, it serves as a significant platform for this analysis. Users can voice their opinions through various means such as voting, rating, favoriting, sharing, and commenting on videos. We have designed a machine learning system grounded in Naïve-Bayes algorithms and assessed the accuracy of these classification algorithms using several metrics, including the F-score and Accuracy score. To boost our system’s performance, we have also incorporated numerous feature selection techniques. Our research adds value to the domain of text analytics, which involves scrutinizing unstructured data embedded in natural language text using various machine learning tools and methodologies. The insights we glean hold considerable potential for understanding user behavior and sentiment on platforms like YouTube.

DOI: 10.61137/ijsret.vol.10.issue2.145

Sentiview: Easy OCR Applied in Digital Format for Text Extraction Using Deep Learning Technology
Authors:-Soumyadeep Das, Kripashankar Manglam, Dr. Kamatchi K S

Abstract-It describes an OCR effort aimed at creating a sophisticated system for precise and effective text recognition across a variety of documents and languages is shown in this abstract. By leveraging cutting-edge machine learning methods like multilingual training, attention mechanisms, and deep neural networks, the system seeks to outperform conventional OCR systems. Convolutional and recurrent neural networks are trained, preprocessed, and extensive data collecting are all part of the methodology. The versatility of the OCR system is demonstrated by its capacity to adapt to a wide range of scripts, including Latin, Cyrillic, Chinese, and Devanagari. When compared to benchmark datasets, evaluation shows significant advances in recall, accuracy, precision, and F1-score, often reaching human-like levels. The real-world uses include data entry automation, information retrieval optimization, digitizing archives, and assistance for the blind. In conclusion, this OCR project represents a substantial development in text recognition technology and offers improved processing accuracy and efficiency for a variety of document applications.

Review on Error Control and Minimization across UPFC Controller Using Ann Layer Modelling
Authors:-Shivali Verma, Assistant Professor Sudeep Mohaney

Abstract-In these paper, we discuss and study about the placement of one of the most versatile flexible alternating current transmission system (FACTS) device which is unified power flow controller (UPFC). By using unified power flow controller we can control all power system parameters individually or simultaneously. But without placing these device in its critical position it is impossible to get a better power flow improvement. The purpose of this paper is to present a comprehensive survey of UPFC controller incorporated in load flow analysis for optimal power flow control. We also discuss different optimization techniques for the optimal placement.

Review on Improvement Transportation Efficiency Using Modified Clustering Algorithm
Authors:-Ankit Shridhar, Assistant Professor Mr. Vinay Deulkar

Abstract-Exploring urban travel patterns can analyze the mobility regularity of residents to provide guidance for urban traffic planning and emergency decision. Clustering methods have been widely applied to explore the hidden information from large-scale trajectory data on travel patterns exploring. How to implement soft constraints in the clustering method and evaluate the effectiveness quantitatively is still a challenge. In this study, we propose an improved trajectory clustering method based on fuzzy density-based spatial clustering of applications with noise (TC-FDBSCAN) to conduct classification on trajectory data. Firstly, we define the trajectory distance which considers the influence of different attributes and determines the corresponding weight coefficients to measure the similarity among trajectories. Secondly, membership degrees and membership functions are designed in the fuzzy clustering method as the extension of the classical DBSCAN method. Finally, trajectory analysis in MATLAB software, india, are divided into two types (workdays and weekends) and then implemented in the experiment to explore different travel patterns.

Review on Highway Road Defect and its Low Cost Maintenance Observation in Case Cracks and Deterioration of Pavement
Authors:-Hitesh Sharma, Professor Jitendra Chouhan

Abstract-This work presents a road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to storage the digital images that will be further processed to identify road cracks. Pre-processing is firstly carried out to both smooth the texture and enhance the linear features. Non-crack features detection is then applied to mask areas of the images with joints, sealed cracks and white painting, that usually generate false positive cracking. A seed-based approach is proposed to deal with road crack detection, combining Multiple Directional Non-Minimum Suppression (MDNMS) with a symmetry check. Seeds are linked by computing the paths with the lowest cost that meet the symmetry restrictions. The whole detection process involves the use of several parameters. Also this research work give a method crack treatment and low maintenance criteria.

3D CAD Modeling of Digital Spring Load Testing Machine with Touchscreen Interface
Authors:-Yash Mendhekar, Dinesh Sahare, Jay Raut, Shubham Gupta, Aftab Ahmad, Dr. I. A. Khan

Abstract-The 3D CAD modeling of a digital spring load testing machine with a touchscreen interface represents a significant advancement in testing technology, offering enhanced user interaction and control capabilities. This abstract provides an overview of the key aspects and benefits of designing such a sophisticated testing system. The digital spring load testing machine with a touchscreen interface combines state-of-the-art 3D CAD modeling techniques with intuitive user interface design to create a powerful testing apparatus. The 3D CAD modeling process involves the creation of detailed virtual representations of the machine’s components, including the frame, loading mechanism, measuring instruments, and touchscreen interface. These components are meticulously designed to ensure structural integrity, precision, and ease of assembly. The integration of a touchscreen interface enhances the usability and functionality of the spring load testing machine, allowing users to interact with the system in a more intuitive and efficient manner. The touchscreen interface provides a visual and interactive platform for controlling test parameters, monitoring test progress, and analyzing test results in real time. This intuitive interface streamlines the testing process, reduces the risk of user error, and enhances overall productivity.

DOI: 10.61137/ijsret.vol.10.issue2.146

To Evaluate the Proposed Routing Protocol Across Several Networks Circumstances
Authors:-Assistant Professor Thrisha V.S., Professor Dr. T.N. Anitha

Abstract-This Internetv of Thingsv (IoTv)v has become one of the greatest noteworthy areas of computing because to the quick development of technology and internet-connected gadgets. IoTv ecosystem-targeting standards, technologies, and platforms are being created quickly. For a variety of uses, including healthcare, home automation, disaster recovery, and industry automation, IoTv makes it possible for things to communicate and plan activities. Itv isv anticipated that it will eventually cover even more applications. This article examines several standards developed by the IEEEv, IETFv, and ITUv that support technologies allowing the explosive rise of IoTv. To fulfil the needs of the IoTv, these standards encompass protocols for the communicationsv, routingv, networkv, and sessionv layers. The issue also includes management and security standards, providing details on the research being done to address these difficulties in addition to the current IoTv challenges. We propose simulation-based research to put a number on how important a cross-layerv designv is for better-quality QoSv sustenance in radiocommunication adv hocv systems. Using the J-Simv simulator, we contrast the layered architecture utilizing the AODVv routing protocol with the CROSS-LAYERv Engine design using QoS-PARv as a routing protocol. We make use of J-Sim since cross-layer implementations are suited for it. In addition to the recommended routing protocol, QoS-PARv, and the LYMPv protocol, we used it to create the entire CROSS LAYERv Engine architecture. The movement of nodes in mobile ad hoc networks frequently changes the network structure, making routing in MANETsv a challenging problem. The efficient routing algorithms could considerably benefit mobile ad hoc networks in terms of performance and reliability. Such networks have been the subject of several routing protocol proposals thus far. There have been some studies published in the literature evaluating the performance of suggested routing protocols under CBRv traffic with various network conditions, but little attention has been paid to evaluating their performance when applied to traffic generators other than CBRv, such as FTPv, TELNETv, etcv. The complexity of traffic in actual applications is not reflected by CBRv trafficv, and the trafficv scenarios described here are more like the network loads experienced by MANETsv in the real world. This article examines the performance of the three routing protocols AODVv, DSRv, and WRPv for FTPv, TELNETv, and CBRv traffic in terms of packet delivery ratio, throughput, average end-to-end delay, and routing message overhead. Many network circumstances are considered, including the effects of modifying the halt length and the quantity of source destinations. For the consolidation and centralization of the public safety network’s main services, it is essential to assess which routing protocol provides the best performance and throughput in a mission-criticalv setting. The following routingv protocolsv are evaluated: Routingv Informationv Protocolv (RIPv), Openv Shortestv Pathv Firstv (OSPFv), Interior Gatewayv Routingv Protocolv (IGRP), and Enhancedv Interiorv Gatewayv Routingv Protocolv (EGIRPv). Convergencev, throughputv, and queuingv delay are also evaluated. The network is simulated using Riverbed Modeler Academic Edition 17.5vv. According to a study of the results, which procedure should be utilized.

DOI: 10.61137/ijsret.vol.10.issue2.147

Exploring Multi-Tenancy in Cybersecurity across Cloud Platforms
Authors:-Pyla Srinivasa Rao1, T. Gopi Krishna, Mohamed Abdeldaiem Mahboub

Abstract-As businesses increasingly embrace the use of cloud computing for their operations, ensuring the security of sensitive data has become a top priority. In particular, cloud multitenancy has emerged as a potent solution to address the growing needs of organizations. This article explores into the realm of cybersecurity in cloud multitenancy, exploring the challenges and potential threats that arise while highlighting the essential strategies and technologies employed to maintain a secure cloud environment.

Design and Implementation of Moon Autonomous Robotic System Using Rocker Bogie Mechanism
Authors:-Professor Mr. Kuraganti Syam Babu, Thumbeti Govardhan, Yenumula Srinivasa rao, Shaik Imran

Abstract-The exploration of Moon has been a subject of immense scientific interest, prompting the development of advanced robotic systems capable of traversing the challenging martian terrain. The Rocker Bogie mechanism has emerged as a reliable and efficient mobility system for moon rovers, allowing them to navigate over rough and uneven surfaces with enhanced stability and mane uverability. This abstract presents a comprehensive overview of the design, analysis, and performance evaluation of a moon robot utilizing the Rocker Bogie mechanism. The proposed moon robot employs a six wheeled configuration with a Rocker Bogie suspension system, enabling the robot to maintain stability while traversing obstacles and uneven terrain. The design process involves the selection of appropriate materials and components that can withstand the harsh martian environment, including extreme temperatures, low atmospheric pressure, and dusty conditions. The robot’s ability to negotiate obstacles, climb slopes, and traverse loose or rocky surfaces is assessed, providing insights into its operational capabilities and limitations. The robot will be equipped with cameras, spectrometers, and other scientific instruments to analyse the Martian environment and gather valuable data for further exploration and research.

Advancing Dermatology with Deep Learning: An Ensemble Model for Classifying Skin Lesion
Authors:-Associate Professor D. Chandra Mouli, R. Abhishek, J. Ritesh, K. Chandra Karthik, D. V. Swaroop, S. Pavan Kumar

Abstract-Numerous individuals are being crazy about the moles which are considered as primary identification marks during their life time, But some of the moles which appears at some stage of the life, which might leads to dangerous circumstances. Due to various reasons human beings spot lesions on their skin. Now our study is about to classify the lesions which are harmful and harmless. While most are benign, meaning they’re not cancerous, some can be cancerous. It’s crucial for doctors to distinguish benign and Malignant at early stage, so they can recommend the most appropriate treatment. Exciting advancements in computer software, particularly powerful programs called deep learning, are showing promise in aiding doctors. These programs, especially a type called convolutional neural networks, can potentially help doctors automatically identify and classify these skin lesions. This research explores a technique that combines a special tool called U-Net to cluster the lesion from the surrounding skin. It then uses pre-trained deep learning models like DenseNet169, ResNet101, and VGG16 to figure out what kind of lesion it is. Trained on the HAM10000 dataset, the ensemble achieves superior performance. We emphasize the importance of factors like image quality, preprocessing, model architecture, and evaluation metrics. Our methodology encompasses data acquisition, preprocessing, model training, and potential deployment for personalized care based on lesion severity. Collaboration with Skin specialists made our study clinically relevant and exceptionally precise. Results illustrate the ensemble model’s effectiveness and its potential to improve healthcare outcomes.

Review on Experimental Study of Stone Matrix Asphalt in Pavement
Authors:-Shivpal Singh, Professor Jitendra Chouhan

Abstract-Stone matrix asphalt, was as a matter of first importance created in 1960 in Germany which now to a great extent helps in giving a more noteworthy changeless twisting protection, strength to surfacing materials, longer administration life, enhanced maturing, high protection in splitting, exhaustion, wear, better slide protection and like in diminishing commotion. A fiber that is promptly accessible in nature. Less savvy contrasting with other non-traditional filaments has been utilized as stabilizer. It is Sisal fiber, which is fiber. It has high quality in fiber course, more noteworthy malleable, flexural and affect quality. Slenderness level of fiber can undoubtedly be acquired from it. It is solid in nature, has steadiness and great security esteem. An endeavor has been made to discover its appropriateness in expanding the dependability and stream an incentive in the blend of Stone Framework Black-top Blends.

Attention-Augmented LSTM Networks for Image Caption Generation using VGG16 Embeddings
Authors:-Assistant Professor Mrs.G.Hima Bindu, B.Satya Sasi Vatsal, L. Dharma Teja, T.Pramod Kumar, T.Juvvi Raju, Ch.Keerthi

Abstract-In an era marked by the widespread integration of AI-driven applications across diverse domains, accurately understanding and describing images becomes increasingly crucial. Image captioning stands as a critical pillar in multimodal language models (LLMs), allowing these models to grasp visual data more comprehensively and enhance their overall understanding, but seamlessly merging textual and visual information is a challenging task. So, the solution we propose is a novel approach to enhance image comprehension and captioning through cutting-edge deep learning techniques. It harnesses the combined advantage of pre-trained VGG16 models for robust feature extraction and a precise captioning architecture driven by LSTM networks enhanced with an attention mechanism. The primary goal is to leverage VGG16’s strengths in extracting high-level image features, which serve as a foundation for generating descriptive captions using robust LSTM network architecture equipped with a custom attention mechanism. These custom attention mechanisms allow the model to selectively focus on different parts of the image while generating descriptive captions, enhancing the richness and relevance of the generated text. The proposed methodology represents a significant stride in bridging the gap between visual understanding and textual description advancing the capabilities of AI systems to comprehend and interpret images, subsequently influencing a wide array of AI applications across industries.

A Study on the Perception of Textile Exporters on Green Supply Chain Management Practices in Tiruppur District
Authors:-Assistant Professor Dr. N. Chandrakala, S. Kavin Kumar

Abstract-In the textile industry’s epicenter in Tiruppur District, this study explores exporters’ perceptions of green supply chain management (GSCM) techniques. Knowing how exporters feel about and are aware of GSCM procedures is important because sustainability is becoming a major concern. By using a mixed-methods approach that includes interviews and surveys, the difficulties encountered and the variables affecting textile exporters’ perceptions are examined. Based on social and economic aspects, the findings show differing levels of knowledge and acceptance of GSCM techniques. Enhancing GSCM techniques is crucial to promoting sustainable textile manufacturing, as the report emphasizes. There are recommendations for promoting a more ecologically conscious textile sector for governments and industry stakeholders.

Colour Controlled Car Using TCS3200 Sensor
Authors:-Assistant Professor Sharath Chandra.M, Julukanti Sathwik, Kandi Naveen, Peter Vikas Varma

Abstract-In a time where preserving data privacy is vital, encryption serves a pivotal role in protecting information from unauthorized intrusion. This review examines its application in encrypting and decrypting text data, shedding light on its mechanisms and practical implications. The encryption algorithm utilizes advanced cryptographic techniques to safeguard the confidentiality of messages exchanged. The purpose of cryptography encryption and decryption method leveraging for secure communication. This review provides a comprehensive overview of AES encryption and decryption, highlighting its strengths, weaknesses, and practical considerations. It effectively communicates the importance of AES in securing text data while acknowledging its limitations and areas for improvement.

A Review of Encryption and Decryption of Text Using the AES Algorithm
Authors:-Assistant Professor Dr.P. Manikandaprabhu, Ms. M. Samreetha

Abstract-The “Colour Controlled Car using TCS3200 Colour Sensor” is an innovative project that combines robotics, electronics, and computer programming to create an autonomous vehicle capable of responding to different colours in its environment. The project utilises a TCS3200 colour sensor, which can accurately detect a wide range of colours, and an Arduino microcontroller to process the sensor data. The car is equipped with an L298 motor driver to control its movement. The system is designed to identify specific colours and execute predefined actions in response. For example, when the colour sensor detects a red object, the car may stop; when it detects blue, the car might turn left, and so on. This colour- based control system can have various applications, such as in automated logistics, educational robotics, or entertainment. The project aims to demonstrate the potential of colour sensing technology in creating intelligent and responsive robotic systems. It involves both hardware and software integration to achieve the desired functionalities. The abstract highlights the importance of innovation and automation in the field of robotics and electronics.

Pomegranates: A Nutritional and Medicinal Powerhouse
Authors:-Vibha Maheshwari, Ajay Kumar Rajawat, Amit Parashar

Abstract-Pomegranates (Punica granatum L.) have been revered for centuries for their unique flavor, nutrition, and medicinal properties. This research paper explores the multifaceted benefits of pomegranates, encompassing their nutritional composition, health-promoting phytochemicals, and therapeutic potential against various diseases. Drawing upon a comprehensive review of scientific literature, this paper delves into the biological activities of pomegranates, including antioxidant, anti-inflammatory, anticancer, cardio protective, and antimicrobial effects. Furthermore, this paper examines the potential mechanisms underlying these health benefits, elucidating the role of bioactive compounds such as punicalagin, ellagic acid, anthocyanins, and flavonoids. Additionally, this paper discusses the emerging applications of pomegranates in functional foods, nutraceuticals, and pharmaceutical formulations. Through a synthesis of evidence-based research, this paper aims to provide a thorough understanding of the therapeutic potential of pomegranates and inspire further investigation into their diverse health-promoting properties.

A Study on”Exploring Consumer Behaviour in the Realm of Digital Marketing and Services: A Comprehensive Study”

Abstract-The goal of this study is to find out which developing media marketing options are the most popular. Many new approaches to promoting and advertising things have emerged in the internet age. Market research may now be undertaken online, thanks to the evolution of “desktop research” into “Internet research.” To stay ahead of the competition, many Indian businesses are turning to digital marketing. People utilize social media because it enables them to engage with one another and exchange information and opinions. Companies have been pushed to adapt the way they move their products as information technology has advanced, contributing to the growth of digital communication tools. The Digital Marketing Communications Strategy is a plan for using digital media to communicate. The study’s goal is to examine the influence of online digital media advertising and other new media marketing strategies.

ARIMA and XG Boost Stock Market Forecasting: A Review
Authors:-Dr. Rachna K. Somkunwar, Amit Pimpalkar, Vaibhav Srrivastava

Abstract-Forecasting stock market movements is a complex task, given the market’s inherent unpredictability and volatility. This paper scrutinizes the hurdles faced when employing two popular forecasting methods: Autoregressive Integrated Moving Average (ARIMA) and eXtreme Gradient Boosting (XG Boost). Despite their widespread use, both models struggle to capture the nuanced patterns of stock market data accurately. The review delves deep into these challenges, spanning model assumptions, data preprocessing, feature selection, parameter tuning, and addressing non-stationarity and high dimensionality. Moreover, the paper investigates how external factors such as economic indicators, geopolitical events, and market sentiment influence the forecasting accuracy of ARIMA and XG Boost. By critically analyzing existing literature and empirical studies, the review pinpoints opportunities for overcoming these obstacles and enhancing the predictive power of these models. It also discusses emerging trends in machine learning and time series analysis that offer promising avenues for improving traditional forecasting methods.

An Analysis on the Financial Literacy of Working Professionals: A Special Reference to Shrusti Engineering Consultancy Pvt Ltd
Authors:-M.Bala Murugan, Assistant Professor Dr.C. Hariharan

Abstract-This research investigates the significance of financial literacy among working professionals at Shrusti Engineering Consultancy Pvt Ltd, focusing on their attitudes towards finance and aspirations for entrepreneurship. By examining employees’ perceptions and attitudes towards finance, the study aims to uncover any underlying desires for entrepreneurship and assess how financial literacy influences their confidence, risk assessment skills, and readiness for entrepreneurial ventures. Moreover, it explores the impact of financial knowledge acquisition on decision-making, financial management practices, and the success rates of entrepreneurial endeavors. The findings provide valuable insights for organizational management and policymakers to develop interventions, training programs, and policies aimed at promoting entrepreneurship and financial empowerment within the company. Ultimately, these efforts are expected to enhance the long-term sustainability and competitiveness of the organization in the market.

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

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

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

Challenges in Vanet for Autonomous Vehicles
Authors:-Rohit Surutkar, Dr Chaya Jadhav

Abstract-Vehicular Ad Hoc Networks (VANETs) represent a crucial component of the infrastructure for future intelligent transportation systems, particularly in facilitating communication between autonomous vehicles (AVs) and supporting various safety and efficiency applications. However, the deployment of autonomous vehicles in VANETs introduces a myriad of challenges that must be addressed to ensure the reliability, security, and efficiency of communication networks. This paper reviews the key challenges faced by AVs in VANET environments and explores potential solutions to overcome these obstacles. Challenges discussed include communication reliability in dynamic vehicular environments, efficient data dissemination strategies, security and privacy concerns, integration with existing infrastructure, and standardization issues. Additionally, the paper examines the impact of these challenges on the performance and deployment of autonomous vehicles in VANETs and highlights the need for collaborative efforts between researchers, policymakers, and industry stakeholders to address these challenges effectively. Through a comprehensive understanding of the obstacles encountered in VANETs for autonomous vehicles, this research aims to contribute to the development of robust and reliable communication systems that can support the widespread adoption of autonomous driving technologies in the future.

Deep learning-Based Packet Analysis for Invasion Detection and Attack Classification
Authors:-Devi Divya Sri Perni, Dr. N. Neelima, Charan Aluri

Abstract-Wireless Sensor Networks (WSNs) facilitate the gathering of data in several domains under the Internet of Things (IoT) framework. However, be- cause of their inherent flaws, WSNs are susceptible to many security threats; for this reason, robust intrusion detection systems are necessary. The research on enhancing WSN security through CNN integration with Long Short-Term Memory (LSTM) networks is extended in this publication. We further study the efficacy of our hybrid LSTM+CNN model in recognizing and classifying differ- ent types of WSN attack threats. In-depth analysis of several attack routes, such as denial-of-service (DoS) attacks, data manipulation, and node compromise, is covered within the additional research. To successfully capture the spatial and temporal information associated with each type of assault, we modify and fine- tune the LSTM+CNN model. This improves the accuracy and dependability of intrusion detection in WSNs. Additionally, it incorporates an Application Programming Interface (API) to facilitate the smooth integration of our intrusion detection system with current WSN infrastructures, guaranteeing scalability and deployment simplicity. By reducing false alarms, improving threat detection capabilities, and supporting the dependability of IoT applications in many areas, our study advances WSN security. To sum up, this expanded initiative is a big step in the right direction toward protecting the confidentiality and integrity of wireless sensor networks. The objective is to enhance confidence in IoT application deployment by tackling many forms of assaults and optimizing the intrusion detection model.

Design and Performance of Square Microstrip Patch Antenna for Super Wide Band
Authors:-Alok Kumar, Assistant Professor Dr. Ram Milan Chadhar

Abstract-A square microstrip patch antenna needed for wideband transmission must be small, light, and easy to make. The present idea is to create a square microstrip patch antenna that would offer reasonable bandwidth and have a simple geometrical shape. The article presents the design research of a rectangular or square-shaped square microstrip patch antenna. A larger bandwidth and sufficient return loss are offered by the square microstrip patch antenna in contrast to the rectangular square microstrip. The Ku-bands of frequencies are intended for use with the little antenna. The proposed of square microstrip patch antenna offers gain; return loss, directivity, and a wide bandwidth.

Implementation of Vending Machine through Verilog HDL
Authors:-Himanshu Shekhar Vivek Kumar, Jayant Kumar Choudhary, Chanchala Kumari, Professor Dr. Shruti Oza-Rahurkar

Abstract-The paper proposes the use of the Finite State Machine (FSM) methodology in Verilog HDL to design, implement, and verify a vending machine. The vending machine has different states managed by the FSM, such as “idle,” “accepting coins,” “dispensing item,” and “returning change.” The FSM is implemented as a state diagram, while the vending machine is implemented in Verilog HDL. The design is synthesized using the Genus synthesis tool and implemented using the Encounter implementation tool. The Genus tool uses optimization techniques like clock tree synthesis and timing-driven placement to enhance the performance and area of the design. The Encounter tool executes physical design tasks like placement and routing to adhere to the timing, power, and area constraints of the design. To verify the accuracy and functionality of the design, a test bench that mimics the vending machine’s operation is created. The simulation results are then used to confirm compliance with specifications and the expected behavior of the FSM.

Traffic Management System at Railway Crossing Using IOT
Authors:-Chirag Bhosle, Kiran Chavan, Aditya Dhavale, Akash Gaikwad, Prasad Jagtap, Professor Vishaka Chilpipre, Professor Trupti Khose

Abstract-This paper presents a comprehensive study and implementation of a traffic management system utilizing Internet of Things (IoT) technology at railway crossings. The project aims to address the critical need for enhanced safety and efficiency at railway crossings, a fundamental aspect of transportation infrastructure worldwide. The significance of this project lies in its potential to mitigate the risks associated with railway crossings, which are prone to accidents and delays due to the intersection of vehicular and railway traffic. By integrating IoT principles and utilizing Arduino Uno microcontrollers, this system offers a proactive approach to traffic management, particularly in scenarios where train detection and signalling are crucial for preventing accidents and ensuring smooth traffic flow. The paper begins by discussing the importance of railway crossing safety and the challenges faced in current real-world situations. Through an analysis of existing systems and practices, it highlights the need for innovative solutions that leverage modern technology to address these challenges effectively. Furthermore, the paper explores the possibility of using the proposed system in emergency cases, emphasizing its potential to improve response times and coordination during critical situations such as railway accidents or medical emergencies at crossings. Additionally, the paper discusses the practical applications and benefits of the traffic management system in real-world scenarios, including its impact on reducing accidents, improving traffic flow, and enhancing overall transportation efficiency. A significant portion of the paper is dedicated to detailing the software programming aspects for Arduino Uno microcontrollers. It provides insights into the development process using the Arduino IDE, including sensor integration, data processing, and LED activation logic .Overall, this paper presents a comprehensive overview of the project, from its inception to implementation and potential real-world applications.

Survey on Monitoring Temperature and Humidity and Keeping Records on Cloud
Authors:-Mandar Gholap, Shubham Ubale, Aditya Habbu, Kartik Pawar, Ketan Bhujbal, Asst. Prof. Vishakha Chilpipre, Asst. Prof. Trupti Khose

Abstract-This research paper presents a survey on implementing a system for monitoring temperature and humidity, with a particular emphasis on recording and storing data on cloud platforms. The system integrates sensor technology with cloud computing to enable real-time monitoring, data analysis, and remote access to environmental data. Through a review of existing literature and case studies, the paper highlights the significance of cloud-based temperature and humidity monitoring systems in various domains such as agriculture, healthcare, and infrastructure management. It also discusses the challenges and considerations involved in deploying such systems, including data security and scalability. Overall, the findings contribute to the discourse on leveraging emerging technologies for environmental monitoring and suggest avenues for further research and development.

Breast Cancer Detection Using Texture Analysis and Convolutional Neural Network
Authors:-Ashutosh Gupta, Surbhi Goria, Pallavi Awasare

Abstract-Breast cancer is a big problem for women all over the world and it can make them very sick. Researchers have worked hard to improve how we diagnose and detect this disease accurately. It remains one of the most life-threatening illnesses, affecting about one in eight women. The unclear causes make it challenging to manage, and prevention is difficult. So, early detection becomes crucial. This paper wants to explain a clear way to find breast cancer early by using computer tools to analyze images. It will explain the steps involved, such as image enhancement, segmentation, and feature extraction, utilizing a Convolutional Neural Network (CNN).

DOI: 10.61137/ijsret.vol.10.issue2.152

Skin Cancer Detector App
Authors:-V.Harini, Dr.V.Sathya

Abstract-This paper presents the development of a skin cancer detector app aimed at assisting users in early detection of skin cancer lesions. The app utilizes machine learning algorithms trained on a diverse dataset of skin images to accurately classify lesions as benign or malignant. Through a user-friendly interface, the app provides real-time analysis of uploaded images, accompanied by educational resources on skin cancer prevention and self-examination. Preliminary testing demonstrates promising results in terms of accuracy and usability, making the app a valuable tool in promoting early detection and improving outcomes for individuals at risk of skin cancer.

Development of a Virtual Personal Assistant for Enhanced Productivity and Efficiency
Authors:-Vijaya Chaturvedi, Shankar Sharan Tripathi, Aditi Pateria, Hem Prabha Chakrapani, Mansi Yadav, Vinay Rathore

Abstract-This research paper presents the development and implementation of a Virtual Personal Assistant (VPA) aimed at augmenting productivity and efficiency in various domains. The proposed VPA integrates natural language processing (NLP) techniques, machine learning algorithms, and advanced user interface design to deliver personalized assistance tailored to the user’s needs. Through an iterative design process, the VPA’s capabilities have been refined to encompass task scheduling, information retrieval, Email management and personalized recommendations, among other functions the findings of this research contribute to the ongoing discourse on the integration of intelligent technologies into everyday life, offering insights into the design, implementation and evaluation of VPAs for enhanced personal and professional productivity.

Development of an LPG Monitoring and Automatic Cylinder Booking System Based on Wireless Sensor Networks
Authors:-Assistant Professor M.Y. Veeresh, N.V. Pushpalatha, S. Archana, S. Nayeem, B. Namrutha, V. Pravallika, B. Lavanya

Abstract-LPG is frequently utilized for cooking in many countries because it is more affordable, more convenience or the fuel of choice. This study focuses on the use of Internet of Things (IoT) to measure and show the gasoline content of residential LPG cylinders, which helps with automatic LPG cylinder booking and gas leak detection. We will show the LPG level because the capacity of the cylinder is typically unknown. The load sensor (SEN-10245) is used to measure the LPG level. An Arduino R3 is attached to the sensor’s output. The user receives information by SMS (short messaging service) when the GSM Module is used, and automated booking is made by calling the registered gas booking number. Next, a gas sensor (MQ-6) detects the gas leak. This allows us to continuously display the current LPG level on the LCD and allows us to detect it. From the date of initialization, we are able to determine the authenticity of LPG usage. Utilizing IOT, the user receives a notification on their mobile device when the LPG level drops to a crucial 20%. We avoid pre-booking and late booking by automatically scheduling a fresh LPG by dialing the gas booking number. Then, we can stop the LPG by finding the gas leak.

Study on Parts of Speech (POS) Tagging for Grammar Checking of Telugu Language Sentences
Authors:-Associate Professor Dr. V Suresh

Abstract-A grammar checking system for simple, compound and complex sentences of Telugu language has been done with grammatical error detection and correction. This research work on grammar checking of simple, compound and complex sentences is based on the assumption that the input sentences will be in Telugu script. The fundamental task of the grammar checker is to check the internal and external structure of the sentence to detect the grammatical errors and to give a suggestion to rectify these errors. Grammar checking is one of the widely used applications in the field of Natural Language Processing (NLP). A Grammar checker for simple, compound and complex sentences of a language is a system that checks various structural and grammatical errors in a given text based on the available possible patterns of simple, compound and complex sentences and grammatical rules of that particular language, and reports errors. The part of speech tagger has been developed using the hybrid approach (combination of rule based and statistical approach).As the simple, compound and complex sentences are composed of more than one clause, therefore, for checking the grammar of simple, compound and complex sentences, each clause needs to be processed separately. Also, the complex sentences are composed of two different types of clauses i.e. dependent clause and independent clause and the relative location of these two types of clauses is not fixed. The identification and separation of clauses play an important role in grammar checking of simple, compound and complex sentences. A clause dentification and separation system has been developed using pattern matching approach, and grammar checking has been done by using hand crafted rules. Like earlier system, our system does not perform the full parsing to arrive at the decision to check if the given sentence is grammatically correct or incorrect. However, unlike earlier systems, it performs the pattern matching to identify the type of sentences. Various types of grammatical errors like agreement error, postposition error etc. have been detected and corrected in compound and complex sentences. This research paper will also improve the accuracy of simple sentences and is also useful for writers in writing long sentences like compound and complex sentences. This work will be beneficial for the students to understand the concept of simple, compound and complex sentences.

Smart Hire – An Intelligent Hiring Platform
Authors:-Nikhil Kumar Thakur, Aakriti Chowdhary, Ujjwal Bhattarai, Professor Geetha Rani K, Dr. Shivakumar C

Abstract-In the rapidly evolving landscape of human resources and talent acquisition, traditional methods of hiring are proving increasingly inadequate in meeting the demands of modern organizations and job seekers. The inefficiencies inherent in manual resume screening, subjective evaluations, and disjointed recruitment processes contribute to extended timelines, suboptimal candidate selections, and diminished candidate experiences. Recognizing these challenges, this research endeavors to introduce a paradigm shift in recruitment practices by harnessing the power of micro-service architecture. Through the development of a sophisticated web application, this study aims to revolutionize the hiring process by integrating cutting- edge technologies such as Natural Language Processing (NLP) for resume screening, examination management, and interview scheduling. By adopting a modular micro- service architecture, the system promises to streamline recruitment workflows, enhance decision-making accuracy, and elevate the overall candidate experience. The primary objective of this research is to create a comprehensive solution that not only addresses the immediate pain points of recruiters and job seekers but also lays the foundation for a more agile and responsive recruitment ecosystem. By automating repetitive tasks, minimizing bias in candidate evaluation, and facilitating transparent communication between stakeholders, the proposed system seeks to transform recruitment into a strategic advantage for organizations. Furthermore, this research explores the potential benefits of the micro- service based approach, including improved efficiency, enhanced accuracy, better candidate experiences, and greater scalability. Through meticulous design and rigorous testing, the system aims to deliver tangible outcomes that align with the evolving needs of the talent market and contribute to organizational success in an increasingly competitive landscape.

DOI: 10.61137/ijsret.vol.10.issue2.154

Oil Skimmer RC Boat
Authors:-Rutuja Sanagade, Vedant Ikhar, Sakshi Hingamire, Shubham Ingale, Harshwardhan Ingle, Isha Barhate

Abstract-A highly acidic alkaline and salty environment remains a great challenge to aquatic organisms and also pollutes the coastal areas. Sea water has been polluted due to oil spillage which also affects the water bodies. Oil spillage results in the release of harmful hydrocarbons into water bodies causing contamination of the ecosystem. An increase in oil spillage results in serious damage to the environment. The project aims to address the environmental impact of oil spills in water bodies. Here we use the skimming medium as a Mild steel disc. The oil skimmer is used to separate oil from a mixture of aqua and oil. It plays a crucial role in environmental management and industrial processes by efficiently removing oil and other hydrophobic substances from water surfaces. The skimming medium runs over the surface of water in which oil is brought out with a small amount of water. The disc coupled with a simple design effectively breaks down solid oil mats providing an impactful tool for mitigating the environmental damage caused by oil spillage.

Garbage Collection and Management System
Authors:-Sagar Shinde, Kiran Jadhav

Abstract-The proposed system can be used to monitor and control the entire garbage collection process. It utilizes a GSM module, a webcam, and a database to collect and track garbage. In addition to providing real-time tracking, the system can also help reduce the use of fossil fuels, improve the environment, and provide access to suitable vehicles. The proposed garbage collection and tracking system has all the necessary features to meet the needs of an eco-friendly environment. Its real-time monitoring system can help administrators keep track of the different containers and paths used throughout the process. It can additionally help them make informed decisions and increase the efficiency of their operation. It will be useful for municipal corporations, and large cities for well-monitored and maintained hygiene. Also, it will have the best impact on society through an automatic real-time system of garbage collection.

A Deep Learning Structure for Forecasting Cyclone Intensity
Authors:-Assistant Professor Kavitha, Abhineet Raj, Tanmay Tiwari, Ayush Madurwar

Abstract-In a world where cyclone frequency and intensity pose major risks to people living along the shore, there has never been a more urgent need for accurate and early forecast. The paper “Cyclone Intensity Prediction,” aims to advance forecasting techniques by developing and implementing a novel approach. This research, which embraces cutting-edge technologies, uses advanced modelling approaches, machine learning algorithms, and meteorological data analytics to establish a solid foundation for predicting cyclone intensity with previously unheard-of accuracy. The combination of these elements enables a thorough comprehension of the intricate dynamics affecting the development and evolution of cyclones. The research attempts to find patterns and connections in historical cyclone data that were previously missed by performing in-depth data analysis and feature engineering. Modern deep learning algorithms make it possible to extract insightful information that helps build a predictive model that can predict cyclone intensity more accurately and with more advance warning. Furthermore, the paper focuses on real-time data integration to guarantee that the prediction model adapts dynamically to changing meteorological conditions. The integration of satellite imaging, oceanic data, and atmospheric factors increases forecast abilities, resulting in a more complete and nuanced knowledge of cyclone dynamics. This study not only advances the scientific community’s understanding of cyclone dynamics, but it also has far-reaching societal ramifications. Improved cyclone intensity forecasts can empower disaster response organizations, governments, and vulnerable communities by allowing them to take proactive measures to reduce potential damage and save lives.

DOI: 10.61137/ijsret.vol.10.issue2.155

A Comparative Review of Server Rendering and Client Side Rendering in Web Development
Authors:-Darshan Verma, Parmeshwari Aland

Abstract-This review paper critically examines the comparative advantages and limitations of two fundamental approaches to rendering in web development: Server Side Rendering (SSR) and Client Side Rendering (CSR). Rendering efficiency plays a pivotal role in shaping user experience, making it essential to assess the performance, functionality, and suitability of these rendering methods. Through an in-depth analysis of key metrics, case studies, and real-world scenarios, this paper aims to provide valuable insights into the optimal selection of SSR or CSR based on specific project requirements. The significance of the topic lies in its direct impact on user interaction, accessibility, search engine optimization (SEO) performance, and overall web application responsiveness. By understanding the distinct characteristics of SSR and CSR, developers can make informed decisions to enhance the quality and usability of their web applications. The main findings of this review highlight the trade-offs between SSR and CSR. SSR offers faster initial page load times, improved SEO performance, and broader compatibility with older devices and browsers. However, it may impose higher server loads and limit interactivity. Conversely, CSR enables enhanced interactivity, smoother user experiences, and better support for complex interfaces but may result in slower initial page loads, SEO challenges, and accessibility concerns. (Karan Shah • et al., 2020).

Design and Analysis of a Sky-Walk Pedestrian Bridge Over Y Shape Flyover
Authors:-Professor Mr. Shubham Dashore, Priyansha Verma, Geetika Painkra, Janhvi Dhruwe, Khushboo Nagwanshi

Abstract-The project focuses on the comprehensive design and analysis of a state-of-the- art skywalk bridge, aiming to enhance urban connectivity and provide a sustainable solution for pedestrian traffic in densely populated urban areas. The skywalk, spanning (specific distance) between (start point) and (end point), is designed to seamlessly integrate with the existing urban infrastructure while offering an aesthetically pleasing and functional pedestrian pathway. The project incorporates a multidisciplinary approach, combining principles of Civil Engineering, structural analysis, and architectural design. The structural elements of the skywalk are meticulously engineered to meet stringent safety standards while minimizing the environment footprint. Advanced materials, including high-strength steel and innovative composites, are employed to ensure structural integrity and longevity. Key features of the skywalk design include (list of distinctive features), which are strategically integrated to optimize pedestrian flow, enhances user experience, and contribute to the overall urban landscape. The project also emphasizes sustainability by incorporating energy efficient lighting, green technologies, and eco-friendly materials. The design process involves the utilization of computer-aided design (CAD) software for the creation of detailed 3D models and finite elements analysis (FEA) tools to simulate various loading scenarios. The structural analysis ensures that the skywalk not only meets but exceeds safety and performance standards. The project aims to address the growing demand for efficient and safe pedestrian path ways in urban environments, promoting sustainable and smart city development. The outcomes of this project contribute valuable insights into the integration of innovative bridge design concepts, materials science, and urban planning.

Integrating AI And 5G in Healthcare System
Authors:-Sailesh Singh, Associate Professor Dr.R.V.Manjunath

Abstract-The convergence of Artificial Intelligence (AI) and Fifth Generation (5G) wireless technology is poised to revolutionize the healthcare sector. AI offers the ability to analyze vast amounts of medical data and derive insights for improved diagnostics, personalized treatments, and operational efficiency. At the same time, 5G provides high-speed, low-latency connectivity that can support real-time data transmission and remote healthcare services. This article explores the synergy between AI and 5G in healthcare, focusing on key applications and benefits. We examine how AI algorithms can be deployed in various healthcare settings, from hospital-based systems to wearable devices, leveraging 5G’s fast and reliable connectivity. The integration of these technologies enables enhanced telemedicine, remote patient monitoring, and surgical assistance, allowing for faster response times and more accurate decision-making. The article also addresses the challenges associated with AI and 5G integration, such as data security, privacy, and ethical concerns. We discuss potential solutions, including robust encryption methods, regulatory compliance, and responsible AI practices. Additionally, we consider the future of healthcare in an era of AI and 5G, exploring emerging trends and potential breakthroughs.

Arduino Based Low Cost Active Dual Axis Solar Tracker
Authors:-Assistant Professor M.Y.Veeresh, U.Prashanth, S.Dinesh, G.Pavan kumar, E.Mahendra

Abstract-Sun is an abundant source of energy and this solar energy can be harnessed successfully using solar photovoltaic cells and photovoltaic effect to convert solar energy into electrical energy. But the conversion efficiency of a normal PV cell is low. One of the main reason for this is that the output of PV cell is dependent directly on the light intensity and with the position of the sun in the sky changing continuously from time to time; the absorption efficiency of an immobile solar panel would be significantly less at certain time of the day and year; for the solar photovoltaic cells are maximum productive when they are perpendicular to the sun and less productive otherwise. So to maximize the energy generation and improve the efficiency; solar trackers come into play. This paper presents the design and construction of an inexpensive active dual -axis solar tracking system for tracking the movement of the sun so as to get maximum power from the solar panels as they follow the sun. It uses Light Dependent Resistors to sense the position of the sun which is communicated to a Arduino Uno microcontroller which then commands a set of two servo- motors to re- orient the panel in order to stay perpendicular to the sun rays. The design was constructed successfully and tested using Lab View to determine the improvements in efficiency. Evaluation results show that the new system performs 13.44% better than the immobile solar PV system.

Environmental Impact Assessment in Highway Construction Case Study and Data Sampling
Authors:-Gaurav Kumar, Assistant Professor Jitendra Chauhan

Abstract-The Environmental Impact Assessment is a systematic investigation of both positive and negative impacts on the physical, biological socioeconomic environment, which would be caused or induced due to a proposed project. EIA provides a plan to reduce the negative environmental effect of proposed development project through alternative approaches, design modification and remedial measures. Highway construction is a major activity of economic development countries. Road development is major source of damage to the environment, including ecological destabilization, habitat disturbance and damage to flora and fauna. In this study, environment impacts are analyzed. The study concentrate on the environmental impact assessment of the project in the light of the existing situation at the site.

Hybrid Solar PV and Wind Powered UPS System
Authors:-S.Mohammad Shabeer, B.Vishnu Vardhan, G.Srinivasulu, E. Ajay Kumar, R.Adharsha, N.Pavankumar

Abstract-Reaching the non electrified rural population is currently not possible through the extension of the grid, since the connection is neither economically feasible, nor encouraged by the main actors. Further, the increases in oil prices and the unbearable impacts of this energy source on the users and on the environment, are slowly removing conventional energy solutions, such as fuel genets based systems, from the rural development agendas. This problem can overcome by using “HYBRID POWER GENERATION USING SOLAR ANDWIND ENERGY”. Hybrid systems have proved to be the best option to deliver “high quality” power.

Cancer Patients and Cancer Related Death Cases in Nigeria: A Case Study of Abuja and Ibadan Cancer Registries
Authors:-Oladoyin Idris Atolagbe, Dr. Eugene C. Ukaegbu

Abstract-The transformative shift in health patterns across sub-Saharan Africa has sparked a significant surge in the prevalence of non-communicable diseases, particularly cancers. Despite the global recognition of the pivotal role played by cancer registries in understanding the disease burden, conducting research, and shaping effective control measures, sub-Saharan Africa often grapples with the neglect of cancer registration due to resource constraints in the healthcare sector. The Nigerian National System of Cancer Registries (NSCR), a ground breaking initiative aimed at establishing a comprehensive, nation-wide approach to cancer registration in Nigeria. This system not only coordinates the efforts of existing cancer registries but also bolsters their capabilities, creates new registries, meticulously compiles and analyzes data, and freely disseminates this invaluable information to researchers and policymakers alike. This report not only shows the successful implementation of the NSCR but also sheds light on the formidable challenges faced during this transformative journey and the innovative solutions that propelled its success. Serving as a beacon for other low- and middle-income countries aspiring to enhance their cancer registration coverage, this narrative emphasizes the crucial components of training, mentoring, scientific and logistic support, and advocacy that are indispensable in sustaining effective cancer registration programs in similar settings. Dive into the narrative of overcoming challenges and triumphs, offering a roadmap for nations striving to fortify their stance against the growing cancer epidemic.

Smart Energy Meter Using IoT
Authors:-Rupesh Rai, Niraj Bamne, Snehal More, Swapnil Utekar

Abstract-The effort of collecting electricity utility meter reading. Internet of Things (IoT) present an efficient and co- effective to transfer the information of energy consumer wirelessly as well as it provides to detect the usage of the electricity the main intention of this project is measure electricity consumption in home appliances and generate it’s bill automatically using IoT. The energy grid needs to be implemented in a distributed topology that can dynamically absorb different energy sources. IoT can be utilized for various applications of the smart grid with distributed energy plant meter, energy generation and energy consumption meter smart meter, energy demand side management and various area of energy production.

Smart Home Automation Using Alexa with Node MCU
Authors:-Assistant Professor S.Seetharamudu, M.raveendra Naik, B.Jithendra, K.Hemavardhan, S.Abhilash, G.Zuber

Abstract-In the era of rapid technological advancement, smart home automation has emerged as a promising domain, offering convenience, efficiency, and enhanced living experiences. This project focuses on integrating Amazon’s Alexa voice assistant into a smart home environment, aiming to streamline daily tasks and optimize resource utilization. Leveraging the Internet of Things (IoT) technology, various household devices such as lights, thermostats, and security systems are interconnected and controllable through voice commands facilitated by Alexa. The project entails the development of a comprehensive system architecture encompassing hardware, software, and cloud components. Smart devices equipped with IoT capabilities are interconnected via a local network or cloud platform, enabling seamless communication and data exchange. The integration with Alexa adds a layer of intelligence, allowing users to interact with their smart home ecosystem effortlessly using natural language commands.

Creative Internet of Things for Smart Homes and Cities Using Artificial Intelligence
Authors:-M.Tech Scholar Rupesh Kumar, Associate Professor Dr. Ritesh Kumar Yadav

Abstract-Functioning of the Internet is persistently transforming from the Internet of Computers (IoC) to the “Internet of Things (IoT).” Furthermore, massively interconnected systems, also known as Cyber Physical Systems (CPS) are emerging from the assimilation of many facets like infrastructure, embedded devices, smart objects, humans and physical environments. What we are heading to is a huge “Internet of Everything in a Smart Cyber Physical Earth.” IoT and CPS conjugated with “data science” may emerge as the next “smart revolution”. The concern that arises then is to handle the huge data generated with the much weaker existing computation power. The research in data science and artificial intelligence (AI) has been striving to give an answer to this problem. Thus, IoT with AI can become a huge breakthrough. This is not just about saving money, smart things, reducing human effort or any trending hype. This is much more than that – easing human life. There are, however, some serious issues like the security concerns and ethical issues which will go on plaguing IoT. The big picture is not how fascinating IoT with AI seems, but how the common people perceive it – a boon, a burden or a threat.

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

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

Surveillance of Children and Tracking System Using IoT
Authors:-Senthil S, Nambirani E

Abstract-The System is a comprehensive solution designed to ensure the safety of children by incorporating cutting-edge technology. The project integrates essential components, including temperature and pulse sensors, GPS, a panic button, and GSM communication. The core concept revolves around immediate response to sensor-triggered events. In case of abnormal sensor readings or activation of the panic button, the system utilizes GSM to swiftly dispatch messages, alerting caregivers or parents. The real-time monitoring capabilities, facilitated by GPS, enable precise tracking of a child’s location. This project addresses the critical need for enhanced child safety by providing a robust and efficient tool for remote monitoring, alerting caretakers to potential emergencies promptly. Through seamless integration of sensor data and communication technologies. The utilization of temperature and pulse sensors provides a means to assess the child’s health conditions remotely, while the GPS system enables accurate tracking of their geographical location. In the event of any detected anomaly or activation of the panic button, the system initiates an instant alert through GSM, allowing for swift response and intervention. The Child Tracking and Monitoring System aims to offer peace of mind to parents, ensuring a proactive approach to child safety.

Quill Talk: Scripting Conversations with Artificial Intelligence
Authors:-Arihant Surana, Pulkit Bansal, Hritik Kumar, Khushwant Virdi

Abstract-This research highlights “Quill Talk,” an original method of acquiring conversational scripts by means of the Artificial Intelligence (AI) /AI technology, when it comes to scaling and management of the large language models (LLMs) in production areas. With the focus on Open LLM, which is a tool intended to facilitate the core processes related to LLMs, we provide comprehensive evaluation of the effectiveness and practicality of using AI to write scripts for dialogue in diverse areas. We will have a tighter approach to Open LLM implementation by taking into account the model support for hosted Hugging Face and the good usability and easy installation procedure. Through empirical study and qualitative analysis, we show that Open LLM is an ideal technology platform for the easy integration of complex LLMs into dialogue interfaces and improve the coherent and responsive nature of AI-driven discussions. The results explain that the Quill Talk and Open LLM technologies will have a bigger role to play in future as they can now actually be used to develop and manage conversational AI aiding decision-making on such matters. This article not only focuses on the technical aspects of scripting conversations with an AI, but also investigates the wider issues of human-computer interaction. The paper tries to address issues that stymies the development of AI conversational technologies and contributes to the advancement of AI technologies in general.

Implementing Machine Learning Models for Detecting and Mitigating DDOS Attacks in SDN Networks
Authors:-Abhishek Rana, Aryan Rawat, Sandeep Singh

Abstract-The availability and security of networks in Software-Defined Networking (SDN) contexts are seriously threatened by DDoS attacks. By applying techniques for detecting and mitigating DDoS attacks, this research intends to create a solid solution for improving the resilience of SDN networks. We employ several machine learning algorithms to identify DDoS. We test our system’s effectiveness in detecting threats and mitigating them by simulating different DDoS attack scenarios. Comparing the results to conventional security techniques, it is clear that DDoS attack detection and mitigation have been substantially enhanced.

Auditing for Group Data Sharing Scheme in Cloud Computing by Providing Security through Privacy Preserving Techniques
Authors:-Dr.L.Kartheesan, P.Thulasi, P.Supriya, P.Sravani, J.Vasavi

Abstract-In the era of emerging cloud computing, a significant amount of storage data is required throughout the advent of cloud computing to guarantee safe and efficient data sharing. Ensuring the confidentiality of shared data is essential. A strong public auditing mechanism that incorporates privacy-preserving measures has been designed to guarantee the security of shared cloud data. Homomorphism authenticators are used to build ring signatures to improve the auditing process. These authentication techniques allow public verifiers to evaluate the accuracy of shared data without requiring full access to the dataset by protecting the user’s identity inside designated blocks. Moreover, our methodology adapts to batch auditing, greatly boosting the effectiveness of cross-checking several auditing activities at once. On the other hand, the privacy-preserving method uses uniform encryption and introduces AES. The “Substitution-permutation network,” which is the main part of AES, is made up of a series of related procedures. Bit manipulation and exchanging inputs for particular outputs are involved in these activities. Interestingly, by organizing the 128 bits in a plaintext block into a matrix with four rows and four columns, each containing sixteen bytes, AES performs calculations on bytes rather than individual bits. The use of advanced cryptographic technology, including ring signatures to create homomorphism authenticators, highlights how sophisticated our methods are for protecting privacy. Research on traceability issues is still ongoing, with a particular focus on the user’s identity being revealed by group management in certain circumstances. This outcome advances the field of safe cloud computing by establishing the foundation for improved data privacy and effective audit in shared cloud environments.

Purification of Water Using Moringa Oleifera Seed as a Natural Coagulant
Authors:-Fathima Risni T, Assistant Professor Dr.N.Gunavathy

Abstract-Moringa Oleifera (MO) is a multipurpose, medium sized tree. Its pods have been employed as an inexpensive and effective sorbent for the removal of organics and coagulant for water treatment. The main objective of this work was to use the MO seeds as a natural coagulant for the purification of water. This study was designed to perform the phytochemical analysis of Moringa Oleifera seed. The phytochemical screening revealed the presence of saponins, tannins and carbohydrates but the absence of alkaloids, flavonoids and phenols. The present work aims to determine the various physico – chemical parameters like – colour, taste, odour, chloride, alkalinity, total acidity, total hardness, calcium, total dissolved solids, pH and conductivity of collected water samples (open well, waste water and bore well). Results showed that the parameters were well within the recommended standard limits after the purification using Moringa Oleifera seeds. The results demonstrated a significant reduction in impurities, indicating the potential of Moringa Oleifera as a sustainable and effective water purification method. This research aims to explore Moringa Oleifera as an eco – friendly solution for water treatment, contributing to sustainable practices in purification.

End-to-End Facial Recognition System and Data Visualization of Students Attendance
Authors:-Mr. Talha Momin, Mr. Sahil Mehra, Mr. Izrail Khan, Ms. Himani Tiwari

Abstract-In the rapidly advancing landscape of education technology, the demand for efficient and secure attendance management systems has never been higher. This research presents a comprehensive solution that integrates cutting- edge facial recognition technology with dynamic data visualization to revolutionize student attendance processes. The system features a user-friendly interface for student registration, capturing essential details, including facial images. Upon registration, the system securely stores the student data in a database, enabling further analysis and visualization. A key highlight is the seamless integration of facial recognition for attendance tracking. During attendance sessions, the system employs advanced facial recognition algorithms to verify student identity, automating the process and reducing manual intervention. The collected data are not only stored but also presented in a visually appealing and insightful manner. The system includes a customizable dashboard that offers real-time attendance statistics, empowering educators to make informed decisions. Additionally, the data can be exported for more in-depth analysis or compliance purposes. This end-to-end solution aims to enhance traditional attendance management systems, offering improved accuracy, efficiency, and a modernized approach to student data visualization. By leveraging emerging technologies, the research contributes to the evolving field of education technology, providing a practical implementation for creating a more connected and intelligent educational environment.

The Integration of AI in Biotechnology: A Review and the Prospects for a New Era of Discovery
Authors:-Rithish Tholkappian

Abstract-The integration of Artificial Intelligence in Biotechnology marks a significant moment in scientific advancement advancement. This paper presents a review on the transformative role played by AI in Biotechnology, highlighting its current applications, challenges and future prospects. This paper discusses recent advancements in AI techniques like machine learning, deep learning and natural language processing which has accelerated research, improved accuracy, and unlocked new possibilities in healthcare, agriculture, and bio manufacturing. We also discuss the challenges and ethical considerations associated with AI integration in biotechnology such as data quality, model interpretability and ethical considerations. Finally, propose future research directions to overcome these challenges and maximize the potential of AI in revolutionizing the field of biotechnology.

Green Cloud Computing in the Industry
Authors:-Vidhya Suresh, Hareen Venigalla

Abstract-This study delves into the integration of green cloud computing technologies in industrial settings, with a focus on environmental consciousness. Here’s a glimpse into the current state of cloud computing and the significance of implementing eco-friendly practices to reduce its environmental impact and energy usage. This article discusses green cloud technologies such as advanced virtualization techniques, renewable energy sources, and energy-efficient data centers. The study explores the environmental and economic benefits of these practices, offering valuable insights into how organizations can leverage cloud computing to achieve sustainability objectives while remaining competitive and efficient. The results emphasize how technology can drive sustainable development and encourage a shift towards eco-friendly computing solutions in industrial settings.

Comparative Study of Pushover Analysis of Zone III & Zone V of RC Framed Building Using Etabs Software
Authors:-Scholar Bhoopenra Singh, Associate Professor R.K. Grover

Abstract– Non-linear analysis is necessary to evaluate the seismic demand of the proposed or existing structure, as linear analysis is inadequate in assessing the seismic demand under severe earthquakes. In this article non-linear static analysis (pushover analysis) has been done to understand the behavior of 8 multi storied residential building located in different seismic zones (III, V) of India having similar geometrical properties using ETABS2019. The behavior of multi storied building has been investigated in terms of force-displacement relationships, inelastic behavior of structure and sequential hinge formations etc. Plastic hinge formation gives real behavior of the structure. From the analysis results, it was observed that, when of structure. Results indicate that, the damage in a building is limited and columns at the lower stories can be retrofitted based on the importance of the structure. The zone varies from (III to V) base shear, story displacement ,story drift, story shear and auto lateral loads has been increased gradually, indicating the severity of seismic activity. In this analysis, firstly hinges were formed in beams and then in columns at ground floor of structure because of column member of the structure are critical in seismic design. The hinge formation propagates from ground floor to middle floor columns and then finally to the upper floor columns.

Navigating the Devops Interview Process: Strategies for Success
Authors:-Venkatesh Kunchenapalli

Abstract-DevOps has become a critical component of modern software development, bridging the gap between development and operations teams to ensure efficient software delivery. With the increasing demand for skilled DevOps professionals, it is essential for job seekers to effectively prepare for the interview process. This article explores the typical DevOps interview process, including the recruiter screening, take-home challenge, hiring manager screen, coding round, and technical round. It provides strategies and best practices for navigating each stage successfully. The preparation strategies discussed include outlining and strengthening the required skills, practicing articulating answers and storytelling, solving coding problems on platforms like LeetCode, reviewing common DevOps interview questions, gaining hands-on experience with relevant tools and technologies, and staying updated with the latest trends and best practices in the field. By understanding the interview patterns, diligently preparing, and demonstrating a combination of technical expertise, problem-solving abilities, and effective communication skills, candidates can increase their chances of success in securing a desired DevOps role. The article emphasizes the importance of customizing preparation to the specific role and company requirements, setting aside adequate time for practice, and adopting the right mindset to confidently navigate the DevOps interview process.

A Comprehensive Guide to Interviewing for Applied Science Manager Positions
Authors:-Hareen Venigalla, Vidhya Suresh

Abstract-This article provides a comprehensive guide for experienced professionals and aspiring candidates seeking Applied Science Manager positions. Drawing from the author’s firsthand experience of going through over 25 phone interviews and 18 onsite interviews, the article outlines the typical interview process and the key areas of focus in each stage. The interview process consists of an initial HR round, a phone interview (either a Hiring Manager round or a coding round), and a series of onsite interviews. The HR round focuses on discussing the candidate’s needs, expectations, and the role’s responsibilities. The phone interview assesses the candidate’s qualifications, technical abilities, and problem-solving skills. The onsite interviews, usually conducted in 5-6 rounds, cover various aspects such as product management, leadership, ML modeling, statistics, and experimentation. Each round evaluates the candidate’s specific skills, experience, and fit for the role. The article emphasizes the importance of technical proficiency, effective communication, and the ability to provide data-driven insights and solutions. It also highlights the differences in evaluation criteria for managerial candidates compared to individual contributors. By understanding the interview process, the key areas of focus, and what the interviewers are looking for, candidates can better prepare themselves and increase their chances of success in securing an Applied Science Manager position.

Android OTA Update for Non-GMS Devices
Authors:-Uchinta Kumar Boddapati, Ayush Vijaywargi

Abstract-This article provides an in-depth exploration of the challenges and complexities involved in delivering over-the-air (OTA) updates to non-GMS (Google Mobile Services) Android devices, such as Amazon Fire TV, Peloton treadmills, Xiaomi smartphones, and Tonal fitness machines. It examines the reasons behind the absence of Google services on these devices, including licensing fees, privacy and security concerns, customization requirements, and regulatory compliance. The article then delves into the technical aspects of the OTA update process, covering the preparation of updates, server infrastructure setup, metadata creation, device authentication, and the actual update installation. It also discusses the role of the Update Engine, a critical component of the Android OTA update process, and how manufacturers can leverage it to streamline their update delivery. Additionally, the article explores the use of Amazon Web Services (AWS) for hosting update payloads and providing secure API access, as well as the importance of device authentication and digital signatures in ensuring the security and integrity of the update packages. The article concludes by highlighting real-world examples of OTA update implementations and emphasizing the significance of investing in robust OTA update solutions for non-GMS Android devices.

Design and Fabrication of a Mobile Furnace Fueled by Waste Motor Oil
Authors:-Anaidhuno U.P, Ologe S.O.

Abstract-The research focused on designing and fabricating a mobile furnace fueled by waste motor oil for melting aluminum in the mechanical engineering department workshop at the Federal University of Petroleum Resources, Effurun, Nigeria. Locally sourced materials were utilized in the fabrication process. A mild steel tank, with a thickness of 3mm, width of 450mm, and height of 860mm, served as the heating chamber of the furnace. Additionally, a steel tube, 10mm thick, 314mm high, and 100mm wide, was used as the crucible. The waste oil is ignited using a syphon nozzle, creating a fine spray of fuel and air. Compressed air is employed to atomize the liquids into fine droplets, serving as the fire source for the furnace. Refractory materials were developed using a composite of plaster of Paris, clay, and cement at a ratio of 2:1:1. A fiber blanket with a melting point of 1,400°C was utilized as an insulator. The waste oil was siphoned from the tank at an elevated height, utilizing the principle of gravity and centrifugal flow. The project was successfully completed at a total cost of #300,000, proving cost-effective compared to acquiring a foreign alternative. The furnace is mobile, aided by three rolling tires, facilitating flexible movement.

Vertical Farming: An energy effective form of Agriculture
Authors:-Rajesh Jagdish Dhake, Shane Stany D’Costa, Vaibhav Bhuwaniya, Abhinanadan Daga, Aryan Chaure

Abstract-The title of our project is Vertical Farming. Compared to traditional farming where the crops are grown in open flat land which uses a lot of space, vertical farming utilizes vertical frames for growing plants in a vertical columnal manner. The crops are grown in closed spaces where all the parameters and conditions of the plant are monitored and controlled. Using vertical farming has several benefits. The major benefit is reduced consumption of water and reduced amount of space required. There are mainly three types of vertical farming: – Hydroponics, aquaponic and aeroponics. But there are many challenges such as the high startup cost and the vast amount of energy required. But we have made our own innovative design modifications and a separate system to counter the problems.

IOT Based Anesthesia Control Machine
Authors:-Dr. Prasanna Palsodkar, Anuja Jiwane, Arya Pande, Jivan Dhandole, Prathamesh Pattiwar, Varad Bansod

Abstract-The careful balancing act of safely and successfully providing anesthetic is critical to modern surgery. In order to maintain the ideal depth of anesthesia, anesthesia specialists carefully monitor a patient’s physiological condition and precisely modify the anesthetic dosage depending on real-time readings. This study investigates a new method of anesthetic control using a machine that is Internet of Things (IoT) based. This approach attempts to expedite the administration process while also enhancing patient safety. An Arduino Uno microcontroller, which serves as the machine’s brain by interacting with a network of sensors, is at its heart. These sensors are essential because they continuously record critical physiological indicators that offer a window into the health of the patient. The study explores this system’s complex inner workings and highlights some of its possibilities.

Efficient Call Admission Control Schemes for Mobile WiMAX Networks
Authors:-Salil Chaudhary

Abstract-With the proliferation of network services offered by operators, users’ Quality of Service (QoS) requirements in the network exhibit significant diversity. Operators strive to meet agreed-upon QoS levels while efficiently utilizing bandwidth to manage network traffic effectively. The dynamic and unpredictable nature of networks, coupled with exponential traffic growth, underscores the necessity for intelligent Call Admission Control (CAC) techniques. Although the IEEE 802-16-2004 standard defines air interface specifications for Broadband Wireless Access (BWA) in Wireless Metropolitan Area Networks (MANs), it leaves admission control unspecified, posing open research challenges. This paper presents two novel and efficient call admission control schemes (CAC-1 and CAC-2) tailored for mobile WiMAX networks, addressing bandwidth and QoS requirements. Both schemes adopt a bandwidth partitioning approach, allocating constant bit rate partitions for UGS traffic, variable bit rate partitions for rtPS and nrtPS traffic, handover partitions for handover traffic, and shared partitions for all traffic types. In the first scheme, service flows are admitted into their respective partitions based on available bandwidth; otherwise, they are blocked or dropped. The second scheme extends the first by implementing waiting queues to reduce blocking probability. Performance evaluations through simulations demonstrate the superiority of the proposed schemes over the existing FZ-CAC scheme. The proposed schemes exhibit reduced call dropping and blocking probabilities, along with improved spectral efficiency and total bandwidth utilization. To address traffic issues, WiMAX leverages adaptive modulation and coding schemes (AMC), where modulation type is determined based on the distance between Subscriber Stations (SS) and Base Stations (BS). WiMAX defines slots as the minimum allocatable resource, depending on permutations such as partial usage sub-channelization (PUSC), full usage sub-channelization (FUSC), adaptive modulation and coding (AMC), and tile usage sub-channelization (TUSC). SSs can request bandwidth through unicast polling, multicast group polling piggyback, or ranging channels, with BSs responding via grant per subscriber station (GPSS) or grant per connection (GPC). Local schedulers at SSs manage service order and QoS in GPSS mode, while bandwidth is granted per connection packet in GPC mode, with requests sent via piggybacking. For the research paper titled “Efficient Call Admission Control Schemes for Mobile WiMAX Networks,” here is a detailed expansion for each section incorporating hypothetical data, concepts, and methodologies to align with the project’s goals.

Poshinda: Empowering Agriculture through Innovative Technology
Authors:-Prithviraj Jadhav, Prathamesh Kapare, Diya Bhandari, Aditya Kumdale

Abstract-In the age of technological advancement, the agricultural sector stands poised for a transformative journey, fueled by innovation and digitalization. This paper introduces “Poshinda,” a pioneering web- based platform designed to redefine the agricultural landscape by seamlessly integrating a spectrum of essential services catering to stakeholders across the Agri-value chain. At its core, Poshinda leverages state-of-the-art AI algorithms to deliver personalized crop recommendations, harnessing data on factors such as crop type, soil composition, weather patterns, and historical yields.This innovative feature not only optimizes crop selection but also enhances productivity and sustainability for farmers. In addition to its AI-driven recommendation engine, Poshinda serves as a gateway to governmental schemes and subsidies pertinent to agriculture, empowering farmers with crucial information and resources to maximize their yields and profitability. Furthermore, the platform fosters community engagement through vibrant open forums and discussion boards, facilitating knowledge exchange, best practice sharing, and peer support among users. Poshinda goes beyond mere information dissemination; it catalyzes transactions and commerce within the agricultural ecosystem through its robust e-commerce marketplace. Here, farmers can seamlessly buy, sell, and rent agricultural produce, machinery, and labor, thereby streamlining operations and enhancing access to essential resources. Moreover, Poshinda envisages future enhancements, including premium services such as last-mile delivery logistics, aimed at further enriching user experience and convenience. This research paper provides an in-depth exploration of Poshinda’s development, implementation, and transformative potential in driving agricultural modernization and socio-economic development. By empowering farmers with knowledge, resources, and a platform for collaboration, Poshinda emerges as a catalyst for sustainable agriculture, rural prosperity, and inclusive growth.

Solar Tracking System
Authors:-Sushmita Baburao Kharat

Abstract-Maximizing solar energy utilization through innovative tracking systems presents a pivotal avenue for enhancing renewable energy adoption. Leveraging technologies such as Light Dependent Resistors (LDRs) for precise sunlight detection, coupled with servo motors for efficient panel orientation, not only optimizes energy yield but also underscores cost-effectiveness in both initial setup and operation. Embracing dual-axis tracking mechanisms further augments efficiency by dynamically aligning with sunlight from multiple angles, while the project’s focus on low-power and portable design renders it a viable solution for empowering rural communities. Consequently, this research explores the integration of Internet of Things (IoT) principles with solar energy infrastructure, revolutionizing electricity generation paradigms and advancing sustainable development objectives.

Music Recommendation System Using Facial Expression
Authors:-Tezash, Shivesh Raj, Dr.T Manoranjitham

Abstract-Music plays a vital role in our everyday life. Life without music cannot be imagined. Music changes our mood; Whatever our mood might be, the only thing we do in all of our moods is to listen to music. We also listen to music when working, driving, travelling and even when reading a comic or a story. Music can induce a clear emotional response in its listeners. The pitch and rhythm of the music are managed in the areas of the brain that deal with emotions and mood. Thus, music plays an important role in enhancing our mood. As elders have said “Face is the Index of the Mind”, the mood of a person can be known by looking at the face of the person. The abstract of this system/ project is to build an automated system that builds playlists and plays the songs according to the mood of the user by directly discerning the facial emotions of the user. This model requires a camera to capture the face of the user and then the mood of the user is recognized by CNNs. Then the playlist is recommended to the user based on the discerned “Mood” of the user. This disposes of the tedious and monotonous task of physically gathering tunes into various records and helps in creating a suitable playlist dependent on a person’s passionate highlights. Hence, the proposed system can be used to build a music recommendation system based on the facial emotion gestures of the user.

Medical Image Segmentation
Authors:-Sowmya A.M, Assistant Professor R.V. Manjunath

Abstract-Medical image segmentation serves as a critical pillar in clinical practice, empowering accurate diagnosis, treatment planning, and disease monitoring. Yet, prevailing methodologies often cater to specific imaging modalities or disease subtypes, thereby limiting their applicability across the vast spectrum of medical image segmentation tasks. Enter MedSAM, a pioneering foundation model meticulously crafted to bridge this divide by unlocking universal medical image segmentation capabilities. Developed leveraging a vast and diverse medical image dataset encompassing a staggering 1,570,263 image-mask pairs, MedSAM boasts unparalleled breadth, covering 10 distinct imaging modalities and over 30 types of cancer. Through meticulous evaluation, including scrutiny across 86 internal validation tasks and 60 external validation tasks, MedSAM emerges triumphant, showcasing superior accuracy and robustness when compared against specialized, modality-specific models. By seamlessly delivering precise and efficient segmentation across a myriad of medical imaging challenges, MedSAM emerges as a transformative force poised to accelerate the evolution of diagnostic tools and usher in a new era of personalized treatment planning. Its universal applicability not only streamlines clinical workflows but also holds immense promise in driving advancements at the intersection of medicine and artificial intelligence. The Segment Anything Model hailed as the inaugural foundation model for general image segmentation, has demonstrated commendable performance across various natural image segmentation tasks. However, tackling medical image segmentation presents unique challenges due to intricate modalities, fine anatomical structures, uncertain object boundaries, and diverse object scales. In order to thoroughly evaluate SAM’s efficacy in the medical domain, we meticulously curated 53 open-source datasets, resulting in a vast medical segmentation dataset comprising 18 modalities, 84 objects, 125 object-modality paired targets, 1050K 2D images, and 6033K masks.

Streamlined Claims Processing: AI Damage Estimation for Insurance
Authors:-Shan Keiko

Abstract-Vehicles significantly influence people’s daily safety. Given the wide variety of materials and sizes, it might be difficult to accurately perceive and identify the surrounding conditions of the vehicle. This study focused on the analysis and identification of automotive damage, which can be used by insurance companies to efficiently automate the resolution of vehicle insurance claims. Deep convolutional networks are capable of detecting automotive damage. Recent advancements in computer vision, mostly due to the construction of fast, scalable, and fully trainable CNNs, have contributed significantly to this progress. There is a significant prevalence of accidents in both urban and rural settings.By creating precise prediction models, one may identify patterns associated with distinct situations and automatically distinguish between numerous unintentional occurrences. Therefore, we are presenting a system that can accurately predict whether a car has been involved in an accident or not. The CNN-based transfer learning algorithm (MobileNet) of deep learning is utilized to execute this operation. This study will examine the subject of automotive damage detection. Identification of vehicular damage. Utilizing photographs captured at the site of an incident can expedite the process and save costs associated with submitting insurance claims, while also offering greater convenience to motorists. Artificial intelligence (AI), specifically referring to the utilization of machine learning and deep learning algorithms, has the capability to assist in problem-solving.

Data Strategy Mastery: Architectures, Overcoming Obstacles, and Triumphs in Implementation
Authors:-David Miller

Abstract-Amidst the prevalence of digital transformation, effectively managing data has become a crucial factor in achieving organizational success and gaining a competitive edge. This study explores the topic of data strategy, analyzing its significance and influence in contemporary businesses. This text presents a range of frameworks for creating a thorough data strategy, focusing on important aspects including data governance, quality, architecture, and literacy. In addition, the study examines typical difficulties encountered during implementation and suggests practical remedies, based on empirical evidence from successful businesses that have overcome these hurdles. This study provides a forward-looking view on the future implications of data strategies by conducting a comparative analysis of different techniques and exploring upcoming trends. This article intends to assist businesses in optimizing their data assets by offering a combination of theoretical frameworks, practical problems, and success stories to support the development and improvement of their data strategies.

Observations and Analysis of Intrusion Detection Systems
Authors:-Research Scholar Kamini Sharma, Assistant Professor Virendra Verma

Abstract-An intrusion detection system (IDS) serves as a vigilant guardian, constantly surveilling networks to detect any unwelcome activity that threatens the smooth functioning of systems, potentially leading to policy breaches. This article delves into the realm of intrusion detection systems and software, examining their diverse classifications and assessing their efficacy through performance evaluations. IDS, whether in the form of hardware devices or software applications, operate on the fundamental premise of scrutinizing network traffic and system activities for anomalies or suspicious patterns. By identifying deviations from established norms, IDS can raise alerts or take preemptive actions to thwart potential threats. Various classes of intrusion detection systems exist, each tailored to specific network environments and security requirements. These classes encompass signature-based detection, anomaly-based detection, and hybrid approaches that combine elements of both. The performance of IDS is subject to rigorous evaluation and measurement methodologies. Metrics such as detection accuracy, false positive rates, and response time are pivotal in gauging the effectiveness of IDS solutions. Through comprehensive analysis and assessment, stakeholders can make informed decisions regarding the deployment of intrusion detection systems, bolstering the resilience of networks against emerging cyber threats.

An Analysis of the Load Balancing Mechanism Used in Cloud Computing Review Article
Authors:-Research Scholar Ankit Ukey, Assistant Professor Jitendra Khaire

Abstract-Cloud registration facilitates information sharing and offers customers access to a diverse range of resources. Customers are billed based on the resources they utilize, promoting cost-efficiency. Cloud computing, which employs cloud storage, maintains information and resources in an accessible state. However, in open conditions, information hoarding tends to proliferate rapidly. Stack balancing serves as a preliminary measure in cloud computing, particularly during periods of cloud cover. Load balancing entails distributing dynamic workloads across multiple nodes to prevent any single node from becoming overburdened. This promotes efficient resource utilization and enhances overall system performance. Many existing computations focus on stack balancing and optimizing resource utilization. Various types of stacks, including memory, CPU, and system stacks, are utilized in cloud computing. Load balancing involves detecting overloaded nodes and redistributing the excess workload to under loaded nodes, thereby optimizing system performance and ensuring equitable resource allocation.

Digital Retail
Authors:-S.Prasath, Associate Professor Dr.V.Sathya

Abstract-Our manuscript presents the conceptualization and development of “Elevate Retail,” a ground breaking digital retail platform designed to revolutionize the online shopping experience. Utilizing advanced technologies such as artificial intelligence, machine learning, and augmented reality, Elevate Retail offers a personalized and immersive journey for consumers. Through sophisticated data analysis and algorithms, the platform delivers tailored product recommendations, enhancing user engagement and driving sales. Augmented reality features allow customers to visualize products in their own environments, fostering informed decision-making and reducing the likelihood of returns. With a focus on accessibility and inclusivity, Elevate Retail prioritizes compatibility with various devices and screen readers, catering to users with diverse needs. This manuscript contributes to the field of digital retail by presenting a comprehensive framework for designing and implementing next- generation online shopping platforms.

Overpopulation, Unemployment and Poverty Crises in Nigeria Since 1960
Authors:-Aijinnahen, S. Ludovic

Abstract-This study examines the negative relationship between overpopulation, unemployment and poverty crises in Nigeria using data from 1960 to 2022. The historical method was deployed with stats and data analysed to prove the scourges between the three variables. Extended literatures related to the three variables were also consulted to elucidate the contention of this study. Descriptive statistics were used to analyse the data collected. The hypothesis test indicated that statistically, overpopulation is the major cause of unemployment and poverty crises in Nigeria.

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

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

Intelligent Monitoring for Anomaly Recognition using CNN and YOLOv9
Authors:-Abhishek Mohan Hundalekar, Assistant Professor Dr. Vishal Shirsath, Vamshi Rajkumar Naidu, Siddesh Bhagwan Pingale

Abstract-The prompt and precise detection of firearms is essential in today’s security environments to ensure public safety. This research paper provides a novel method for real-time weapon detection using Convolutional Neural Network (CNN) techniques and YOLOv9 object recognition framework in both live and prerecorded film. By integrating YOLOv9, object detection accuracy and speed are considerably improved, facilitating the quick identification of possible threats. The presented method exhibits strong performance in various lighting settings and environments, with excellent recall rates and precision thorough testing and assessment. This approach used CNN based architecture and deep learning to effectively detect and categorize weapons in video frames which achieves 97.62 % accuracy.

Review on Analysis of Recycled Aggregates From Construction and Demolition Wastes as Alternative Filling Materials for Highway Construction in Indian Domain-A Review
Authors:-Pradeep Kumar Verma, Professor Shashikant B. Dhobale

Abstract-Highway Construction waste aggregate leads to disasters, and the solution for that consists of 5 steps. For one, bring an end of being a part of causing waste by prevention. On the other hand, waste can be managed by recycling, reusing, recovering, and last option is to clearance or disposal. Also, other factors such as economical and marketing are considered to be effective answers. Review, urbanization, resource recovery, waste recycling, and environmental assessment are the top five keywords. Estimation and quantification, comprehensive analysis and assessment, environmental impacts, performance and behavior tests, management plan, diversion practices, and emerging technologies are the key emerging research topics. To identify research gaps and propose a framework for future research studies, an in-depth qualitative analysis is performed. This study serves as a multi-disciplinary reference for researchers and practitioners to relate current study areas to future trends by presenting a broad picture of the latest research in this field. These wastes are heavy, having high density, often bulky and occupy considerable storage space either on the road or communal waste bin/container. It is not uncommon to see huge piles of such waste, which is heavy as well, stacked on roads especially in large projects, resulting in traffic congestion and disruption. Waste from small generators like individual house construction or demolition, find its way into the nearby municipal bin/vat/waste storage depots, making the municipal waste heavy and degrading its quality for further treatment like composting or energy recovery. Often it finds its way into surface drains, choking them.

Review on High Performance Concrete Design in Highway Construction with Soil Stabilization Using Heavy Compaction Test
Authors:-Deepak Jyoti Sen, Professor Jitendra Chouhan

Abstract-Stabilization is a broad sense for the various methods employed and modifying the properties of a soil to improve its engineering performance and used for a variety of engineering works. In today’s soil stabilization is the major problem for civil engineers, either for construction of road and also for increasing the strength or stability of soil and reduces the construction cost. Soil stabilization can be explained as the alteration of the soil properties by chemical or physical means in order to enhance the engineering quality of the soil. The main objective of the soil stabilization is to increase the bearing capacity of the soil, its resistance to weathering process and soil permeability. Due to rapid growth of urbanization and industrialization, minimization of industrial waste is serious problem in present days. To encounter this innovative and nontraditional research on waste utilization is gaining importance now a days. Soil improvement using the waste material like Slags, Rice husk ash, Silica fume etc. In geotechnical engineering has been recommanded from environmental point of view. This paper reviews on the influence of blast furnace slag, fly ash and micro silica when used as admixtures with black cotton soil to improve various properties of soil.

Fake News Detection Using Machine Learning
Authors:-Research Scholar Rahik Khan, Professor Dr. Sunil Gupta

Abstract-The internet has become an essential part of our daily lives, and social media platforms have played a significant role in shaping public opinion and spreading information. With the increasing number of users and the ease of access to these platforms, the spread of misinformation, including fake news, has become a significant issue. Machine learning (ML) classifiers have been proposed as a potential solution to automatically detect and filter out fake news. This systematic literature review aims to explore the existing ML classifiers used for detecting fake news and their effectiveness. The rapid proliferation of fake news and its detrimental impact on democracy, justice, and public trust necessitate urgent action and research. This tutorial aims to provide a comprehensive overview of fake news research, its challenges, and future directions, as well as to distinguish it from related concepts such as rumours. We will introduce fundamental theories from various disciplines, including computer and information science, political science, journalism, social science, psychology, and economics, that contribute to interdisciplinary research on fake news detection. The identification of fake news is a complex task due to the diverse nature of the content and the strategies employed by the spreaders of fake news. ML classifiers have been employed to address this issue by analysing the textual content of the news articles and identifying patterns that indicate the likelihood of a news article being fake.[1]

WebRTC (Web Real-Time Communication)
Authors:-Research Scholar Shivam Barthwal, Dr.Sunil Gupta

Abstract-Web Real-Time Communication (WebRTC) is an open-source project that enables real-time communication via the web browser without plugins. It allows for audio and video communication as well as file sharing capabilities directly within web applications. This paper provides an overview of the WebRTC technology including its core components, architecture, and capabilities. WebRTC utilizes open standards for real-time communications including Session Description Protocol (SDP), Session Traversal Utilities for NAT (STUN), and Traversal Using Relays around NAT (TURN) to enable peer-to-peer connections directly in the browser. It handles tasks like network traversal and encryption transparently to developers and users. The core WebRTC APIs allow JavaScript applications to access audio/video input and output devices, capture media, and establish peer connections between browsers. This paper then discusses some common WebRTC use cases and applications including video conferencing, online meetings, screen sharing, file sharing, collaborative white boarding, and real-time multiplayer gaming. It analyses how major companies like Google, Microsoft, and Facebook have incorporated WebRTC into their products and services. Challenges and limitations of the technology are also explored. In conclusion, WebRTC has the potential to revolutionize real-time communications on the web by removing the need for plugins and making rich media experiences possible directly within browsers. As support continues to expand across browsers and platforms, WebRTC applications are poised to become ubiquitous. Further standardization efforts are still needed but WebRTC shows great promise for the future of real-time communications on the internet.

Securing Today, Innovating Tomorrow: Hybrid Defense
Authors:-Gagana Sree V, Assistant Professor Venkatesh Y, Madhumitha M, Dinesh P, P Mahesh

Abstract-In the rapidly evolving cyber landscape, where new threats emerge with increasing sophistication, traditional intrusion detection systems (IDS) often fall short. Identifying and managing emerging threats is a big issue for conventional intrusion detection systems (IDS) in today’s continually changing cyber ecosystem. This study suggests a novel hybrid intrusion detection system (IDS) that combines Suricata’s signature-based detection capabilities with LSTM CNN’s adaptive learning capabilities. By offering dynamic and adaptive recognition of both known and unknown cyber threats, this innovative technology seeks to solve the shortcomings of traditional detection techniques. In addition, several Kafka brokers are integrated into the system architecture, which makes use of the TCP and UDP protocols to handle a variety of packet types effectively. Afterwards, a central Kafka broker that communicates with the ML model (CNN-LSTM) receives these processed packets. The machine learning model categorizes several kinds of attacks, like brute force attacks on FTP and SSH, denial-of-service (DDOS) and DOS attacks, and benign activities. This allows the system to sound a warning when abnormalities are detected, like a buzzer. This research paper introduces a novel hybrid IDS that synergizes the strengths of Suricata, a signature-based detection system adept at identifying known threats, with the advanced learning capabilities of a Long Short-Term Memory Convolutional Neural Network (LSTM CNN). This innovative approach aims to bridge the gap between conventional signature-based detection methods and the need for adaptive recognition of novel and complex cyber threats. By integrating the reliable detection of known attack patterns provided by Suricata with the dynamic learning and anomaly detection capabilities of LSTM CNN, this hybrid system offers a comprehensive solution to network security challenges. It is designed to improve detection accuracy, adapt to emerging threats, and ensure scalability, thus significantly enhancing the overall security posture of networks. The motivation behind this initiative is to address the limitations inherent in singular detection approaches by developing a more resilient and accurate IDS capable of defending against both familiar and unprecedented cyber intrusions. The objective is to deliver a cutting-edge, hybrid intrusion detection framework that offers superior precision and effectiveness in identifying cyber threats, thereby fortifying network defenses against the vast spectrum of cyberattacks.

Vibration Analysis of Propeller Shaft of Passenger Vehicle
Authors:-Surwase Ramesh Limbaji, Dr. Santosh B. Jadhav

Abstract-The power transmission system is the system that causes the movement of vehicles by transferring the torque produced by the engines to the wheels after some modifications. The transfer and modification system of vehicles is called as power transmission system. The power transmission system of vehicles consists of several components which encounter unfortunate failures. The propeller shaft and the universal joints form the important links that help in transmitting power from the engine to the wheels. In this study, analysis is being performed on the propeller shaft. In this, project the propeller shaft of TATA was investigated for static & vibration characteristics response. Considering the system, torque acting on a shaft used to calculate the Stress analysis by using FEA. A propeller shaft of a TATA truck was analyzed and optimized for weight reduction in this study. The shaft’s natural frequency and durability were studied using finite element analysis. Experimental validation of natural frequency will be performed using an FFT analyzer and impact hammer test.

Role of 2 Deoxy-D-Glucose in Covid-19
Authors:-Sravankumar, Asif Ali, Mamtha Purohith, Mehraj Sultana

Abstract-During pandemic year this drug has played a vital role in patients infected with SARS-CoV2. severely to acute respiratory tissue, as it helped in early recovery of covid patients. In this we briefly discussed about the mode of action, chemical document, clinical trials data and other ongoing researches of 2DG. The Drug Controller General of India (DCGI) has given emergency use approval to 2-deoxy-D-glucose (2-DG), an anti-Covid drug developed by INMAS, a DRDO lab, in collaboration with Dr Reddy’s Laboratories (DRL), Hyderabad. The 2 DG has been researched for its Anti-Inflammatory property as it also cured inflammation in many patients. It has also been testing for its Hypoglycaemic effect as it is similar to glucose in structure. Basically, it is isolated from a micro-organism called streptococcus nigrum.

Predictive Analytics: Mitigating Risks in Fintech Products with AI
Authors:-Chintamani Bagwe

Abstract-In Fintech, predictive analytics play an important role in dealing with increasing complexity in the financial sphere, radically altering risk assessment and hence the nature of financial choices. This paper examines the interaction between cutting-edge predictive analytics and artificial intelligence in promoting corporate risk assessment, fraud detection, and operational productivity in solution providers. It discusses a number of predictive analytics models, such as time set classification and neural networks and uses them to think through market trends, customer clustering behaviour, and anomaly identification. The identification links are then used in many financial service scenarios to consider their impact on risk solvency development and customer experience and to predict market patterns. The paper looks at difficulties in data administration, illustration, and ethics, and suggests a solid data management approach and an ethical concept. It concludes with thoughts and ideas that would lead to more risk awareness and AI-driven decisions in the future, and highlights the predicted growth in competitively elegant predictive forecasting and situation control. The sense-the essay makes is to remind Fintech managers and specialists of the importance of keeping their learning up-to-date to take full advantage of the most recent advances in artificial intelligence and predictive analytics to make sensible decisions and policy thinking in their career.

Housing Price Prediction Using Linear Regression
Authors:-Research Scholar Manthan Ved, Dr.Sunil Gupta

Abstract-The housing sector, which is projected to grow by 30% over the next ten years, is India’s second biggest employment provider after agriculture. Housing is one of the most important sectors of the real estate market and is complemented by the growth of urban and semiurban housing. It is hard for the buyer to choose his or her dream house because of ambiguities in real estate prices. In order to avoid overestimating or underestimating the price, the interests of buyers and sellers should be taken into account. In order to provide a better informed decision system on multiple aspects, our system provides buyers and sellers or real estate agents with an accurate model for the prediction of housing prices. To do so, a variety of features are selected as input from the feature set and different approaches such as regression models or ANN can be used.

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

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

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

Digital Marketing Using AI
Authors:-Meghna Vashishth, Professor Dr. Sunil Gupta

Abstract-This paper examines how digital marketing and artificial intelligence (AI) intersect and complement each other. It discusses how businesses utilize AI to enhance marketing through personalized content creation, predictive analytics, customer segmentation, and chatbot assistance. By leveraging AI, marketers can refine targeting, boost engagement, and increase conversions across various digital platforms. Moreover, it addresses challenges like data privacy, algorithmic biases, and ethical concerns, underscoring the need for responsible AI integration in digital marketing strategies. In sum, this abstract highlights AI’s transformative role in reshaping the digital marketing landscape.

Enhancing Tornado Prediction in the United States Using Light GBM: A Machine Learning Approach
Authors:-Jiawei Zhou

Abstract-This study advances tornado prediction method- ologies by integrating the Light Gradient Boosting Machine (Light GBM) with the Seamless Hybrid Scan Reflectivity (SHSR) dataset from the Multi-Radar Multi-Sensor (MRMS) system. Current tornado prediction approaches, primarily based on conventional radar systems, face challenges such as high false positive rates and limited spatial resolution, which often lead to inadequate response times for safety measures. Our research employs Light GBM, an innovative machine learning algorithm known for its efficiency and capability to handle large, complex datasets, to address these challenges. By incorporating SHSR data, which provides enhanced atmospheric scanning capabilities, this study aims to improve the accuracy and reliability of tornado predictions. We present a comparative analysis of Light GBM against other prevalent machine learning algorithms like Random Forest and XG Boost. Results demonstrate that Light GBM, with its unique model architecture and data processing efficiency, significantly outperforms other models in terms of prediction accuracy and computational speed, making it a superior choice for real-time tornado prediction systems. This integration not only proposes a robust framework for meteorological applications but also sets a foundation for future enhancements in severe weather forecasting.

Transmuting From Tradership to Entrepreneurship in Alaba International Market: A Catalytic Trajectory for Nigeria’s Socio-Economic Development
Authors:-Godson Christian Osita

Abstract-The Alaba International market, a hub for electronics, electrical goods, ICT products, and allied businesses, is a significant commercial hub. With over 5,000 registered enterprises and 100,000 dealers (Awoniyi, 2016) supported by a strong apprenticeship incubator scheme (The Igbo Business School Scheme), the market attracts many business visitors from West Africa and beyond. However, the market’s alleged lack of acceptable business ethics, etiquettes, and corporate governance standards impacts government revenue generation and socio-economic development. Therefore, a shift from a tradership mindset to an entrepreneurial mindset is crucial, as trading proficiency doesn’t necessarily translate to entrepreneurship proficiency. Trading skills and entrepreneurship abilities are distinct, and their outcomes also vary. As a result, this study, adopting the Narrative-Textual Case Study methodology (NTCS), employs Hagen’s Social Change theory to suggest that proactive traders and their apprentices can systematically become entrepreneurial by acquiring some requisite entrepreneurial knowledge and adjusting their tradership mindset, while retaining some good aspects of tradership that agree with entrepreneurship. This will extricate them from the toga of merchants of fake and cheap products to a respectable position in the entrepreneurship cadre. Hence, the need for a transition from a trader mindset to an entrepreneurial mindset is hereby advocated. Besides emphasizing the acquisition of requisite skills and social capitals for value creation for the purposes of wealth creation, multiplication, distribution, diversification, preservation, and perpetuation, this transmutation should also be driven by the enhancement of human skills and competencies. The study deliberately delved into various variables, including challenges in the Alaba International Market ecosystem, and submits that there is need for both LGA and State government authorities to create an enabling business environment to promote entrepreneurship transition. This, ultimately, would promote quality products and services, fair competition, transparency, better customer relations, rule of law, human rights, inclusivity, ethical behavior, environmental conservation, and adaptive learning that can endanger socio-economic development in Nigeria.

Real Estate Price Forecast Web Application Using Machine Learning
Authors:-Assistant Professor Mr. G. Ravi Kumar, Ms. G. Greeshma

Abstract-Real estate price forecasting plays a crucial role in aiding buyers, sellers, and investors in making informed decisions. With the advancement of machine learning techniques, researchers and practitioners have explored various methodologies to develop accurate real estate price prediction models. This literature review aims to provide an overview of the approaches and techniques utilized in building real estate price forecast web applications using machine learning. The review begins by discussing the data collection and preprocessing steps, highlighting the sources of real estate data and the importance of feature engineering. Various feature selection techniques are explored, along with the significance of incorporating location-based features, amenities, and neighborhood characteristics. Next, the review delves into the selection of machine learning models for real estate price prediction. It discusses the suitability of linear regression, decision trees, random forests, gradient boosting machines (GBM), support vector machines (SVM), and neural networks, emphasizing the importance of model interpretability and robustness. Evaluation metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared are examined to assess model performance. Techniques for model interpretability, including SHAP values and Partial Dependence Plots (PDP), are also discussed. Furthermore, the review addresses the deployment of real estate price forecast models as web applications. It outlines the frameworks and technologies commonly used for building interactive web interfaces, allowing users to input property features and obtain price predictions in real-time. Lastly, considerations for updating and maintaining real estate price forecast models are discussed, emphasizing the dynamic nature of real estate markets and the importance of regular model updates. By synthesizing the existing literature, this review provides valuable insights into the best practices, methodologies, and challenges associated with developing real estate price forecast web applications using machine learning.

Blood Flow: Blood Bank Management System Enhancing Blood Donation Accessibility
Authors:-Zoha Attar, Dariyan Naagar, Kajal Hake, Shraddha Hiwrale, Assistant Professor Vikas Desai

Abstract-The efficient management of blood banks poses a critical challenge worldwide, characterized by a lack of proper mechanisms for blood donation, requests, and inventory management, despite a widespread willingness among individuals to donate. This deficiency becomes glaringly apparent during emergencies, where urgent supplies of blood are needed for patients. Consequently, lives are put at risk, and the consequences can be dire. In response to these challenges, this research paper proposes a Blood Bank Management System project aimed at overcoming these obstacles. This project offers a user-friendly and efficient platform that connects donors, receivers, and management, streamlining the entire process from donation to distribution. By integrating HTML, CSS, JavaScript, and database technologies, this system facilitates effortless blood donation and inventory management, ultimately saving lives and enhancing the effectiveness of blood bank operations.

Design and Simulation of 100 KW Photovoltaic Grid Connected System Using Boost Convertor and MPPT Technique
Authors:-Er. Parwinder Singh, Assistant Professor Er. Kamaljeet Singh

Abstract-The human exercises add to the worldwide temperature alteration of the planet. Accordingly, every nation endeavor to lessen fossil fuel by products. The world is confronting the exhaustion of non-renewable energy sources, yet in addition its rising costs which causes the overall monetary insecurity. Quantities of endeavors are being attempted by the Administrations around the planet to investigate elective fuel sources and to accomplish contamination decrease. Sun oriented electric or photovoltaic innovation is one of the greatest sustainable power assets to produce electrical force and the quickest developing force age on the planet. The fundamental point of this work is to break down the interface of photovoltaic framework to the heap, the force hardware and the technique to follow the Maximum power point Tracking (MPPT) of the sun-based board. At that point fundamental accentuation is to be put on the photovoltaic framework, the demonstrating and reenactment photovoltaic exhibit, the MPPT control and the DC/DC converter will be dissected and assessed. The progression of demonstrating with MATLAB and Simulink of the photovoltaic framework is shown individually and reenactment results are given. The Simulink model of the PV could be utilized for broadened concentrate with various DC/DC converter geography. Enhancement of MPPT calculation can be actualized with the current Photovoltaic and DC/DC converter. The simulation results were analyzed for assessing the performance of the photovoltaic system.

An Empirical Analysis of Inflation Dynamics in India
Authors:-Aala Abhinaya, Dr Shantanu Ray Chaudhuri

Abstract-Inflation is defined as a general rise in prices, leading to reduced purchasing power across the economy. This study aimed to investigate the compositional shift in the inflation determining factors from being primarily demand-driven to being cost-pushed between 1990-1991 and 2021-2022. This period includes the critical years from 2014-2015 to 2021-2022 which marked by significant economic events affecting Indian economy. These events include the demonetization of currency, the implementation of the Goods and Services Tax, the COVID-19 pandemic, and the Russia-Ukraine war. Each event had a profound impact on Indian economy, particularly the recent changes in the interest rates indicating the Prescence of inflation. The study implemented vector error correction and vector auto regression models, along with graphical analysis to analyse the short-term and long-term relationships among the indicators influencing inflation in India. The findings of the study indicated a notable shift in the drivers of inflation from traditional demand-pull factors to predominantly cost-push factors, increased by recent domestic and global disruptions. The study made recommendations to central bank that included specific actions to stabilize exchange rates and fiscal measures to mitigate the impact of external price shocks. These strategies aimed to enhance the overall economic resilience and stability.

Security in Java Web Application
Authors:-Research Scholar Hemant Kumawat, Professor Dr. Sunil Gupta

Abstract-In today’s digital landscape, ensuring security within Java applications is crucial due to the ever-increasing threats posed by cyberattacks. As one of the most widely used programming languages for building diverse applications, Java must adhere to rigorous security standards to safeguard sensitive data and protect against potential vulnerabilities. Preventive measures involve adopting secure coding practices from the outset. Developers must validate and sanitize user inputs, utilize parameterized queries to prevent SQL injection, and implement proper authentication and authorization mechanisms. Frameworks such as Spring Security provide comprehensive solutions for authentication, authorization, and protection against common vulnerabilities. Securing communication channels through Transport Layer Security (TLS) is also essential for ensuring data integrity and confidentiality. Configuring server settings to disable unnecessary services and applying security headers can mitigate common exploits. Continuous monitoring and threat detection mechanisms are essential components of a robust security strategy. Implementing intrusion detection systems (IDS) and web application firewalls (WAF) enables real-time monitoring of traffic and identification of suspicious activities. In summary, ensuring security within Java applications requires a multi-faceted approach that includes secure coding practices, communication security, and continuous monitoring and threat detection. By adopting these measures, developers can help safeguard sensitive data and protect against potential vulnerabilities, ensuring that their applications are secure and reliable.

Algorithm & Complexity of Binary Search
Authors:-Research Scholar Mohd. Afjal, Dr.Sunil Gupta

Abstract-This article introduces a variation of traditional binary search that checks at each iteration whether there is a point between the input and the cluster. The improved binary search algorithm optimizes the worst-case scenario of the binary search algorithm by comparing the input with the first and last datasets and intermediate points and checking the Enter a number in the given now option data. The number of numbers is adjusted at each iteration by decreasing the worst-case times used by the binary search algorithm.

Entertainment Hub
Authors:-Anand Mishra, Nallasingu Ram Kishore, Sai Ganesh Peruri, Dinesh G, Edara Venkata Sai Sukesh Chowdary, Vulimiri Naga Hari Chandana

Abstract-Entertainment Hub emerges as a dynamic online plat- form, finely tuned to cater to a diverse array of entertainment preferences, seamlessly amalgamating three core sections: Mu- sic, Movies, and Games. Harnessing state-of- the-art web technologies including HTML, CSS, React.js for frontend development, and Node.js with Express.js for backend architecture, it guarantees a user-friendly and intuitive interface for effortless navigation through its extensive content offerings. In the Music segment, users are immersed in an expansive repertoire of songs, accompanied by a robust music player replete with standard playback controls and customizable options for curating beloved tracks. Similarly, the Movies division showcases a thoughtfully curated selection of films and series, each accompanied by com- prehensive details encompassing titles, directors, descriptions, and ratings, alongside fundamental video playback functionalities. Meanwhile, the Games arena elevates the user experience through an assortment of HTML and JavaScript-based games, fostering interactive gaming encounters directly within the web- site interface. Facilitating these seamless operations lies a sturdy backend infrastructure powered by Mongo DB, ensuring stream- lined data management for user preferences, song particulars, movie information, and beyond, thereby guaranteeing optimal organization and retrieval of data. Beyond mere entertainment delivery, Entertainment Hub places paramount importance on user experience, security, and performance, guided by user- centric design principles to augment usability, robust security protocols to fortify data integrity and privacy, and performance optimization techniques to enhance website responsiveness and loading times. Representing a holistic solution for entertainment enthusiasts, Entertainment Hub seamlessly integrates music, movies, and games within an accessible web environment. With prospects for future enhancements and scalability, it stands as a testament to the harmonious fusion of technology and entertainment in the digital epoch, offering limitless possibilities for immersive and captivating entertainment experiences.

Credit Card Fraud Detection Using Ml
Authors:-Shikshit Kumar Verma, Professor Dr. Sunil Gupta

Abstract-It is very important that credit card companies are able to identify fraudulent credit card transactions so that customers are not charged for items that they did not purchase. This project intends to explain the model of a data set using machine learning with Credit Card Fraud Detection. The Credit Card Fraud Detection Problem includes modelling past credit card transactions with the data of the ones that turned out to be fraud. This model is used to recognize whether a new transaction is fraudulent or not. Our objective here is to detect 100% of the fraudulent transactions while minimizing the incorrect fraud classifications. In this process, we have focused on analyzing and pre-processing data sets as well as the deployment of multiple inconsistency detection algorithms.

A Comprehensive Analysis of Parallel Heat Pipe System with Evolution of its Properties
Authors:-Nikhlesh Pindoliya, Professor Khemraj Beragi

Abstract-Recently, multi-channel flat heat pipes have been developed to improve the heat recovery from flat surfaces, such as solar panels and batteries. In this paper, the thermal performance of a multi-channel flat heat pipe is experimentally investigated and analytically predicted. The multi-channel heat pipe studied transmits heat from silicone flat heaters to a water flow circulating inside a cooling manifold. The manifold heat sink is a flat aluminium surface comprising channels in which water recovers thermal energy by forced convection. The impact of the water flow rate on the working temperature of the heat pipe is investigated. To predict the performance and working temperature of the multi-channel flat heat pipe, a theoretical model has been developed. The thermal model considers the two-phase heat transfer in a multi-channel heat pipe geometry. It is shown that the heat pipe working temperature decreases with the water flow rate as a result of a reduced forced convection resistance of the manifold. Finally, the analytical multi-channel flat heat pipe model developed is compared with experimental data. It is shown that the thermal model, considering both cooling manifold and the multi-channel heat pipe geometry, is able to predict the heat pipe working temperature evolution within 7%.

The Role of the Four Tempters in Murder in the Cathedral

Abstract-T.S. Eliot’s “Murder in the Cathedral” explores the theme of martyrdom through the character of Thomas Becket, who confronts four tempters offering worldly enticements. This paper analyzes these temptations using Marxist, deconstructionist, postcolonial, and psychoanalytic theories to reveal the complexities of Becket’s spiritual and ethical dilemmas. By rejecting these temptations, Becket embodies resistance against capitalist exploitation, colonial domination, and personal ambition, highlighting his moral integrity and spiritual devotion. Eliot’s play thus serves as a rich text for examining the intersections of power, morality, and identity.

Optimization of Current Generation with High Speed Moving Vehicles Using PV Array
Authors:-Er. Manish Kumar, Assistant Professor Er. Kamaljeet Singh

Abstract-This study investigates the feasibility of utilizing a photovoltaic (PV) array mounted on high-speed movie vehicles to generate electrical current while in motion. The aim is to explore the potential for harvesting solar energy from the PV panels under varying vehicle speeds. The simulation model considers factors such as PV panel efficiency, solar irradiance, and vehicle speed to estimate the amount of current that can be generated. MATLAB simulations are employed to analyse the dynamic interaction between vehicle motion and solar energy capture, providing insights into the practicality and effectiveness of this renewable energy concept.

Sky-Cast App
Authors:-Yash Bhalekar, Om Jadhav, Sarthak Belvalkar, Nikhil Bhamare, Ajinkya Dighe, Saksham Deore, Assistant Professor Vikas Desai

Abstract-We currently face significant challenges in obtaining immediate and accurate real-time weather updates. This task often requires intricate skills in observing and analyzing extensive data sets. Weather phenomena vary widely, from small, transient thunderstorms to expansive weather systems spanning thousands of miles and enduring for days. As a result, obtaining precise forecasts can be difficult, leading to various issues. Leveraging technology can greatly aid in addressing these challenges. Our Android application, developed using Android Studio and APIs, The goal is to furnish users with current and accurate weather updates. specific locations, helping mitigate forecast uncertainties and enhance preparedness.

Fundamental Analysis of Varun Beverages Ltd.
Authors:-Assistant Professor Dr. Sumant Wachasundar, Rishikesh Rajkarne, Ritik Thorat

Abstract-This project report is based on the ratio analysis of the financial statement and performance of Varun Beverages Ltd. for five years i.e., FY2019 to FY2023. This report will provide an assessment and analysis of the profitability, liquidity, performance and financial position of Varun Beverages. In the analysis, financial ratios were used to interpret a critical review of the specific areas of assessment of the company’s performance. The financial statements in the annual report of the enterprise helped to provide a clear view of the overall performance of the organization. From the various financial ratios mentioned in the report we can examine that the FY2023 has been the most profitable. Unfortunately, in between the years the profitability of the organization has deteriorated. The analysis shows that the company is on the right track to tackle their losses due to the COVID19. There have been some positive elements which predicts towards company’s growth over the next few years. The financial study has been possible so that we can depict the actual position in terms of financial health of the organization. Given the industry-oriented nature of the business, it would have been interesting to evaluate and analyze the business by comparing with past years results to set the industry benchmark.

Facilitating Learning through “DAYAW”
Authors:-Jessica S. Moc-eng, Jolly B. Mariacos

Abstract-This phenomenological study determined the best strategies through DAYAW(Developing and enhancing learners’ Academic performance through the Yearning of parents as facilitators in various Activities to drive them to accomplish Works) Approach as intervention teachers. Fourteen teachers were chosen as key participants for purposive sampling. Descriptive-survey method of research was used in this study. After a careful analysis of the answered questionnaires from the participants, the extent of used of the DAYAW approach as intervention in facilitating the grade 3 pupils was regularly facilitated. The level of effectiveness of DAYAW approach as intervention was highly effective. It is therefore recommended that the grade three teachers should sustain implement the DAYAW approach and action plans to enhance the performance of the grade three learners and lessen the risks of failures among the pupils.

Volunteer’s Zone: Website for Volunteers to Find Social Events
Authors:-Sneha Gonjari, Ishwari Abuj, Satwik Garje, Gauri Dighe, Vikas Desai

Abstract-The Volunteer’s Zone is an innovative online platform designed to connect individuals with diverse community initiatives and volunteer opportunities. With its intuitive features and user-friendly interface, the website facilitates seamless engagement between event organizers and volunteers, thereby promoting active participation in meaningful causes. The platform offers essential functionalities such as volunteer registration, event posting, search and filtering options, personalized dashboards, and communication tools. By simplifying the process of discovering and signing up for events, the website aims to encourage community involvement and nurture a sense of social responsibility among its users. This abstract highlights the objectives, features, and benefits of the Volunteer’s Zone, emphasizing its role in promoting accessibility, engagement, and community building. Leveraging standard web technologies such as HTML, CSS, and JavaScript, the Volunteer’s Zone endeavors to make volunteering more accessible and rewarding for everyone involved.

TORMS: Transplant Organ Registry and Management System
Authors:-Assistant Professor Mr Vikas Desai, Danish F Homavazir, Sahil M Gedam, Anusshka Teli, Atharv R Bhagat, Alok Bhuyan, Om Hajare

Abstract-New technologies in organ donation registry and organ transplantation have generated new intuitions and opportunities in this new world for the cure of diseases. Moreover, the big commitment of transplantation has been faced by several people with several sincere issues. The most usual problem normally aroused of concern is moral implication but in a society with various social and religious beliefs like Malaysia, the concerns will be far greater. These problems need to be conveyed as the way of things and acceptability of organ transplantation and registry is varied by society, lifestyle and religious aspects. The diverse society, religious, and established thoughts on donation of organs may hinder the acceptability of organ donation and the eagerness to donate organs. This paper in depth explores the moral issues involved and the religious views on organ donation. On this note, there is a study organised in India to show association between the behaviour towards organ donation and gender with 80% of the male audience is willing to donate organs whereas only 60% of the women audience were willing to donate organs. Similar researches reported the same situation. Organ donation can be stated as “When a person allows an organ of their own body to be removed legally, either by consent while the donor is alive or after death with the allowance of the next of the person”. Transplantations next of donor donations includes several body parts like lungs, pancreas, liver, heart, intestines, bones, kidney etc. These organs can be given away as so donate as the donor is alive, maximum number of the donations take place after the persons death. In our India, foundation system for health and organ donation was then established in 1994 amended in 2011, with the supervision of Transplantation of human organs act. It supported the needful non-obligatory and see through system for organ donation. Donation of organ has a crucial role of rescuing lives, but willingness of people to donate makes the real change and transplant donated organs. Understanding behaviours is difficult for the achievement of the organ donation services in many areas. This paper was a description of the data targeted at understanding human’s behaviour towards organ donation registry. Reports showed that 600 patients were randomly interviewed, approx. 60% sympathize to donate their organs after death. The amount of those people agrees to donate their organs after death encourages taking a useful step to encounter a continuous organ donation system. Keeping that in mind that there are no strings attached with the criteria of age, sexuality or even literacy level, which suggests that the system may have a different set of people.

Design and Fabrication of Resuscitation Ventilator
Authors:-Ramachandra Kulkarni, Salim Sharieff, Naveen Kumar S, Ravi M, Amar

Abstract-Ventilators are critical lifesaving devices for patients suffering from respiratory failure, yet many regions around the world face shortages of these machines. This paper presents the design and fabrication of a low-cost, portable resuscitation ventilator intended for emergency use. The ventilator is designed with a focus on affordability, ease of use, and rapid manufacturing using welded metal components and machined parts. Key features include volume control ventilation, adjustable tidal volume and breaths per minute. A crank mechanism converts the rotary motion of a gear motor to reciprocating motion to drive air delivery by squeezing the AMBU bag. This ventilator shows promise as a scalable solution to increase access to respiratory support in crisis situations.

Flood Resilency and Emergency Crowed Funding
Authors:-R.Sivasurya, Dr.D.Swamydoss

Abstract-Flood problem is the major issues in Chennai, Thirunelveli, Thuthukudi etc. There is not a separate portable to save this kind of people. Thus is our proposed system “Flood Resilency and Emergency Crowd Funding” is done with Python and HTML. The development system is down Here the Environment Agency admin will be available where the concern people will be alerted before the problematic situation arises. The admin can make a donation request as a Prevention Policy Fund where other peoples can help them. This paper examines the theoretical underpinnings of crowd funding in the context of disaster management and explores its practical implications for enhancing flood resilience. Drawing upon existing literature and case studies, we highlight the potential benefits of emergency crowd funding, including its ability to facilitate rapid response, promote inclusivity, and foster social cohesion among affected communities. We explore the role of technology and social media in amplifying crowd funding efforts and reaching a wider audience of potential donors.

Crop Yield Prediction Using Leveraging Linear Regression
Authors:-Research Scholar Aman Rajwanshi

Abstract-Crop yield prediction is a critical aspect of agricultural planning, impacting both farmers’ decision-making and broader food security initiatives. This paper explores the application of linear regression, a fundamental machine learning technique, in predicting crop yields. The study outlines the process of data collection, preprocessing, feature selection, model training, evaluation, and prediction validation. Challenges and considerations inherent in this approach are discussed, including data quality, model complexity, and external factors. By leveraging historical data and relevant environmental and agronomic variables, linear regression offers a data-driven solution to optimize agricultural practices and inform policymaking. The abstract underscores the importance of ongoing research and innovation to enhance the accuracy and reliability of crop yield predictions, thereby contributing to sustainable agriculture and global food security efforts.

Performance Analysis of PV Pumping Systems
Authors:-Research Scholar Manish Kumar, Assistant Professor Abhijeet Patil

Abstract-The most promising non-conventional energy source for meeting the energy needs of remote rural areas is solar energy, such as photovoltaic. A solar photovoltaic water pumping system design with an enhanced control method is presented in this research. System dependability and efficiency are increased by the innovative basic switching of SRM drive scheme across the maximal operating time. The MATLAB simulink software is used for simulation. According to simulation data, the current model performs significantly better than the previous model.

AI Revolution: Transforming Risk Management in Financial Institutions
Authors:-Kinil Doshi

Abstract-This article reviews the implications and enhancements that Artificial Intelligence may bring to financial institutions in terms of risk management transformation. In a dynamically evolving environment provided by the progressed state of AI technologies, the transformation solved becomes evolutionary more strategic. This paper examines the power of AI in improving the accuracy, efficiency, and transparency of risk assessments and management processes. A necessary focus is on AI’s possibility to process unlimited data in real-time, thus creating a new paradigm of proactive decision-making and risk assessment by identifying it early in the process. Apart from that, some potential applications such as credit assessment, regulatory compliance, and cybersecurity are also considered, since the latter issues are the field of a problem to institutions where major disruptive innovation is required. The challenges and the moral concern of AI are also discussed, including the pros and cons of data use and the compliance function. Overall, highlighting existing and potential use cases and forward-thinking trends allow for this article to see AI as vital since, in a developing industry, financial institutional survival is impossible without it.

Expert System for Healthcare Diagnostics using Tensor Flow
Authors:-Assistant Professor Mr.V.Nehru, Dinesh.M.B, Rangesh.V.S, Ujit Kumar, Shai Shukesh Reddy

Abstract-This transformative project aims to pioneer a cutting-edge healthcare diagnostics system by harnessing the power of Convolutional Neural Networks (CNNs) for the precise analysis of medical images, particularly X-rays and MRIs. Amidst the backdrop of traditional diagnostic methods, which often rely on manual interpretation by healthcare professionals, the proposed system offers a pioneering solution for disease detection and diagnosis. Notably, this endeavor extends its scope by considering the potential integration of blood donation information, thereby striving to provide an all-encompassing healthcare ecosystem. By delving into the intricacies of medical image analysis, our project seeks to achieve an ambitious yet attainable goal: to empower healthcare providers with an automated, accurate, and efficient diagnostic tool. This tool holds the promise of significantly enhancing diagnostic accuracy, ensuring that no subtlety or anomaly goes unnoticed. The marriage of cutting-edge deep learning techniques with the extensive and diverse medical image dataset promises to unlock a new era in healthcare diagnostics. Healthcare diagnostics have undergone significant advancements with the integration of deep learning techniques, particularly convolutional neural networks (CNNs). CNNs serve as powerful tools for analyzing medical images and extracting crucial diagnostic information. Leveraging their capability to automatically learn hierarchical features from raw data, CNNs excel in tasks such as image classification, segmentation, and abnormality detection. In the healthcare sector, CNNs find application across various imaging modalities, including MRI, CT, X-ray, and histopathology images, to assist in diagnosing a wide array of medical conditions. For instance, in radiology, CNNs demonstrate accuracy in identifying and categorizing abnormalities like tumors, fractures, and lesions in medical images, facilitating earlier detection and more precise diagnoses. Moreover, CNNs aid pathologists by automatically segmenting different cell types and structures in tissue samples, enhancing accuracy and efficiency in cancer diagnosis and grading. Overall, the integration of deep learning and CNNs in healthcare diagnostics shows significant promise in enhancing diagnostic accuracy, reducing interpretation time, and ultimately improving patient outcomes.

E-Commerce Website
Authors:-Assistant Professor Rakshak Sood, Vedant Naik, Tejas Patil, Tejas Parab, Siddhesh Salian

Abstract-Creating an e-commerce website is a multifaceted task that requires careful planning, execution, and adherence to best practices to ensure success in competing online in the marketplace. This article provides a comprehensive guide to the ecommerce website development process, including basic ideas and best practices for creating an online store. The first stage of planning and research. It emphasizes the importance of understanding business objectives, strategic business objectives, and conducting market research to clearly understand the business, customer preferences, and competitive landscape. In addition to choosing a platform, create and work on a website. It discusses the importance of user experience (UX) design in creating intuitive and visual interactions that improve customer engagement and encourage conversions. Additionally, this article also covers aspects such as website architecture, database design, and security measures to ensure the reliability, scalability, and security of the website. The right to manage inventory, fulfillment and payment functions to streamline operations and ensure user satisfaction. It discusses the integration of key features such as trucks, inspection systems, and customer support to facilitate efficient and profitable business operations. Mobile responsiveness, omnichannel integration and artificial intelligence (AI). It emphasizes the importance of keeping up with technological developments and changing customer preferences in order to remain competitive in a dynamic e-commerce environment. Developers provide useful information.

Web Based Check Post Activities Controlling System
Authors:-Shalini R, Assistant Professor Asr Sulthana

Abstract-The project entitled as “Web Based Check Post Activities Controlling System“, which has been developed using Eclipse IDE. Here java as the front ends and MYSQL server as the back end. The aim of the project is to computerize the Check Post complete activities. The proposed project is developed and introduce for handling activities takes place inside Check Post. Project proposes a new technique is used in Check Post center, which deals with driver info, vehicle complete information, goods/product info, and complaint details along with timing details. This project helps to maintain the all details of the Check Post centers in systematic process. This project is used to Monitoring its day-to-day check post center activity. This project reduces the manual activity Monitoring details.

× How can I help you?