Disease Prediction Model Using Multi-Modal Data Fusion
Authors:-Shruti Deokule, Dipti Kause, Suhani Korde, Suhani Korde
Abstract- With recent developments in machine learning and healthcare informatics Strong disease prediction models have been made possible . In order to improve the accuracy and dependability of early disease diagnosis, we present a multi-modal data fusion system in this paper. Advanced fusion techniques that can lessen the drawbacks of single-modality models are used to integrate heterogeneous data sources, such as wearable sensor readings, genomic data, medical images, and electronic health records (EHR). Our method integrates crucial information from multiple datasets by combining feature selection, preprocessing, and ensemble learning. In comparison to the traditional models, we find that the experimental results produce 15% higher prediction accuracy and lower error rates—down to 2.3% for cases of chronic disease.
href=”https://doi.org/10.61137/ijsret.vol.11.issue2.351″>10.61137/ijsret.vol.11.issue2.351
Company Inventory Management System Using Appian
Authors:-Balaji S, Assistant Professor Dr. Krithika. D. R
Abstract- The product in every company decides the availability of resources according to the user needs. Each product must be useful to the user in certain ways to decide as per the demands. This paper speaks about how the products are handled by different departments from storage team to user by choosing the control of each product for the supply and flow in a company. This paper also conveys that this will tell all the activities happens in a single company for deciding how the storage team is very important in storing the products, each team decides the product supply to make it useful for users. When a product gets requested by user it must be decided by the team to inform the availability. The communication mechanism in this application is very useful in understanding the entire system by each team very easily. So, every activity in this application completely named as Inventory to explain about the management of this application.
href=”https://doi.org/10.61137/ijsret.vol.11.issue2.352″>10.61137/ijsret.vol.11.issue2.352
Thermal Analysis of Engine Fins with Different Geometries and Materials
Authors:-Rajat Yadav, Assistant Professor S.N. Dubey
Abstract- In order to make the engine cylinder fins design simpler, CFD (Computational Fluid Dynamics) is used to analyze the thermal and mechanical behavior of the engine cylinder fins. In CFD, the heat transfer and pressure drop characteristics of the engine cylinder fins can be accurately predicted. This helps in understanding the performance of the engine cylinder fins and helps in making necessary modifications to improve the heat dissipation rate. Additionally, CFD can also be used to analyze the airflow characteristics and pressure distribution inside the engine cylinder. This helps in designing the fins properly to reduce the aerodynamic drag and improve the efficiency of the engine. The purpose of this article is to analyze the thermal properties of cylinder fins with different geometries using Ansys Workbench. The geometries were 3D modeled using SOLIDWORKS 2016 and their thermal properties were evaluated using Ansys Workbench R 2016. The change in temperature over time is an important factor in many applications, such as refrigeration, and accurate thermal modeling can help. You determine the key design parameters to improve performance. , The cylinder fin body material is AA 6061 aluminum alloy with a thermal conductivity of 160-170 W/mK. This material is used for current analysis of cylinder ribs.
IoT-Based Electricity Theft Detection System
Authors:-Mohammad Gulrez Zaidi, Deepanshu Punj, Moseen Khan, Ms. Jyoshita Narang
Abstract-Innovative solutions for various industries have been developed as a result of the proliferation of Internet of Things (IoT) devices. IoT has the potential to completely change how electricity is produced, transmitted, and used in the electricity sector. The use of IoT for detecting and preventing electricity theft is one such application. Meter tampering, also known as electricity theft, is a significant problem that affects the revenue and profitability of electricity boards. It entails circumventing meters in an unlawful manner in order to use electricity without paying for it. This not only costs government’s money, but also puts consumers and the electricity grid in danger of injury or damages. In this project, we propose creating an IoT-based system to track down and stop electricity theft. Smart meters with sensors and communication capabilities make up the system, along with a central server for data processing and analysis. Electricity consumption patterns are continuously monitored by smart meters, which also send data to a central cloud-based database. The database values are utilized by the authorities when it discovers anomalies or suspicious activity upon close monitoring of the data stored in real-time. The proposed system could significantly lower the number of instances of electricity theft, increasing revenue and profitability for the electricity providers while enhancing consumer safety. By offering real-time information on electricity consumption and billing, it can also assist utilities in streamlining their operations and enhancing customer service.
DOI: 10.61137/ijsret.vol.11.issue2.357
A Decentralized Social Media Platform with Sentiment Analysis Using Blockchain
Authors:-Nitish Jha, Abhishek Chaudhari, Piyush Pandey
Abstract-This research proposes a decentralized social media platform built on blockchain technology with integrated sentiment analysis using Natural Language Processing (NLP). Traditional social media platforms face issues such as data privacy breaches, central control, and lack of transparency. The proposed system utilizes Ethereum smart contracts and a decentralized architecture to enhance trust, ownership, and user privacy. Sentiment analysis is applied to user-generated content to gain insights and improve user interaction. The system is implemented using the Remix IDE, MetaMask wallet, Sanity database, and ReactJS frontend. This approach provides a transparent, secure, and scalable solution for the next generation of social networking applications.
Welfare Services in Emergency Scenario Management
Authors:-Darshini.S, Assistant Professor Dr. Poongodi.A
Abstract-This Application helps the user to gain the services that are needed for the daily emergency situations. This application provides the services like Petrol, Tow, Hospital, Ambulance and Pharmacy in a Single Module. This application is free for everyone. My goal is to reduce the cost, by providing the maximum service even in any emergency situations to the people needs in a friendly approaching interface. We added braille support so blindly and visually impaired people can also use this application. We added more reliable support system to guide you anytime at anywhere. This application is all in one friendly daily emergency services for people’s welfare.
DOI: 10.61137/ijsret.vol.11.issue2.358
CIFAKE: Image Classification and Explainable Identification of AI-Generated Synthetic Images
Authors:-Assistant Professor Mrs .Shandhini, Roopashree.M, S.Fasiha
Abstract-CIFAKE is a computer program that can detect fake images created by artificial intelligence. It to identifies fake images and provide explanations for its decisions. CIFAKE can help prevent the spread of misinformation and fake news by identifying fake images. This tool can be useful for individuals, organizations, and social media platforms to ensure the authenticity of online images. We introduce the CIFAKE dataset, which consists of 120,000 images (60,000 real images from the CIFAR-10 dataset and 60,000 synthetic images generated using latent diffusion models). Convolutional Neural Networks (CNNs) for binary classification (real vs. fake) and it utilizes Gradient Class Activation Mapping (Grad-CAM) for explainable AI (XAI) to interpret the model’s decisions. The results demonstrate that the given approach achieves a classification accuracy of 92.98%, for detecting AI-generated images.
Solar and Wind Power Electric Vehicle
Authors:-Assistant Professor N. E. K. Chandra., Assistant Professor P.T. Krishna Sai., J. Prudhvi Ganesh.3, Y. Venkata Sai Mohan Krishna., B. Rohit Chandra Sekhar., Md. Saleha.
Abstract-Energy crisis and pollution caused by vehicle emissions are one of the most important issues in the present society. Due to the charging time of battery of electric vehicle, requirement of charging on board is explored as option. This paper deals with the design of a hybrid model of a solar and wind, which uses the battery as its storage system. This system allows the two sources to supply the load separately or simultaneously depending on the availability of the energy sources. The power generated from the wind and solar is fluctuating in nature. The system obtains maximum solar energy during day time and maximum wind energy during the night because the wind blows more at night compared to day time. Therefore, battery of the vehicle can be charged by using hybrid energy system.
A Study on the Challenges in Income Tax Compliance among the Salaried Employees
Authors:-Lavanya S, Assistant Professor Praveen S V
Abstract-This study aims to explore the challenges faced by salaried employees in complying with income tax regulations. Income tax compliance is a significant aspect of the tax system, ensuring the effective functioning of a nation’s economy. However, salaried employees often face various barriers that hinder full adherence to tax laws. These challenges include insufficient knowledge of tax rules, the complexity of tax filing processes, lack of awareness about available exemptions and deductions, and limited access to professional tax advisory services. Additionally, the study examines the impact of digital platforms, such as online filing systems, in facilitating or complicating the compliance process. Data was collected through surveys and interviews with salaried employees from different sectors to identify common issues and concerns. The findings suggest that while digital platforms have made tax filing more accessible, many employees still struggle with understanding tax calculations, deadlines, and documentation. The study also highlights the role of employer assistance in simplifying the compliance process. Recommendations are provided to improve tax literacy, streamline filing procedures, and offer better support systems to enhance overall compliance among salaried employees. This research contributes to understanding the existing barriers in tax compliance and proposes potential solutions to foster greater tax adherence in the salaried workforce.
DOI: 10.61137/ijsret.vol.11.issue2.359
Fitness Club
Authors:-Nirjala Nandekar, Manasi Patil, Vinayak Patil, Chirag Patil, Professor Dr. Prachi Gadhire
Abstract-Being fit physically and mentally is every human being’s ultimate desire. People are always seeking to have a healthy body fitness and they are somehow engaged in day-to-day life. So, we believe that our application can solve this problem in android device users, the apps can be great relief to people who do not have time to visit fitness centre, through help users can manage the healthy life system. Many people who have realized the importance of these apps in their daily life have started making use of such apps. The Current Landscape of the Fitness Apps Market In 2023, the worldwide market for fitness apps clocked in at a solid 1.54 billion USD. Looking ahead, expect this sector to flex its muscles with an impressive compound annual growth rate of 17.7% from 2024 all the way through to 2030. It counts 87.4 million users in the US only. The fitness apps market has evolved dramatically, influenced by changing user preferences and technological advancements. It’s a domain where app users seek personalized experiences, driving the growth of both workout apps and nutrition and diet apps. User Engagement in Mobile Fitness Apps Understanding user engagement in mobile fitness app is crucial. This includes analysing patterns in the Google Play Store and Apple App Store, and how app features cater to diverse user needs. Monetization Strategies: From Paid Apps to In- App Purchases Monetization in the fitness app market varies from paid apps to dynamic in-app purchases, shaping the way developers create revenue streams.
E-Commerce Price Comparison System
Authors:-Assistant Professor Vimmi Malhotra, Kanchan Panwar, Jaya
Abstract-In recent years, mobile apps have become increasingly useful for everyday use. The objective of this project is to provide users with a convenient method to compare product availability and prices across different e-commerce platforms. By inputting the product details into the program, users can effortlessly compare prices from various sources. To compare the product details discovered on multiple websites simultaneously, the application’s databases are searched. To guarantee that they never overlook a fantastic deal, customers can also receive push notifications when items become available or go on sale.
DOI: 10.61137/ijsret.vol.11.issue2.364
AI Chatbot
Authors:-Vipashyna Arun Sable, Professor Suresh Mestry
Abstract-AI chatbots can assist right away by answering questions, providing explanations, and pointing to more resources. Software applications like chatbots can aid teachers in many assignments and become excellent digital teaching assistants.Chatbots are software applications that respond to inputs in natural language. We can see that chatbots are now a part of our daily life. We use them every day to book a movie, reach the closest restaurant, or find an open ATMThese are chatbot software applications that have made life easy. But their uses are not restricted to this. They also entertain users who are bored, play a massive role in home automation projects, give business strategy suggestions, and aid in many other ways.The system was tested on various user inputs and usage scenarios and satisfactory results were observed for usability, accuracy, and responsiveness. The project brings highly evolved chatbot framework technologies like Rasa and chit-chat bots of the likes of facebook and wit.ai to beginner level with a responsive conversational chatbot which could be deployed with minimal coding efforts.The project shows how advanced AI could be used effectively with simple web technologies, and opens up the possibility of further development of using voice, multilingual support, and AI-powered customization.
DOI: 10.61137/ijsret.vol.11.issue2.365
AI Chatbot
Authors:-Vipashyna Arun Sable, Professor Suresh Mestry
Abstract-AI chatbots can assist right away by answering questions, providing explanations, and pointing to more resources. Software applications like chatbots can aid teachers in many assignments and become excellent digital teaching assistants.Chatbots are software applications that respond to inputs in natural language. We can see that chatbots are now a part of our daily life. We use them every day to book a movie, reach the closest restaurant, or find an open ATMThese are chatbot software applications that have made life easy. But their uses are not restricted to this. They also entertain users who are bored, play a massive role in home automation projects, give business strategy suggestions, and aid in many other ways.The system was tested on various user inputs and usage scenarios and satisfactory results were observed for usability, accuracy, and responsiveness. The project brings highly evolved chatbot framework technologies like Rasa and chit-chat bots of the likes of facebook and wit.ai to beginner level with a responsive conversational chatbot which could be deployed with minimal coding efforts.The project shows how advanced AI could be used effectively with simple web technologies, and opens up the possibility of further development of using voice, multilingual support, and AI-powered customization.
Lip-Interpretation Using Deep Learning and Cnn
Authors:-Asmita Chorge, Siddhi Dalvi, Sharvani Mahadik, Ashwini Pawar, Professor Manisha Hatkar
Abstract-Lip interpretation, also known as visual speech recognition, is a challenging task in the field of artificial intelligence (AI) and computer vision. This research explores how deep learning techniques, particularly Convolutional Neural Networks (CNNs), can enhance lip-reading accuracy. By analyzing different architectures, datasets, and methodologies, we present a comprehensive study on various models used for lip interpretation. The findings suggest that deep learning-based approaches significantly improve the accuracy of speech recognition without relying on audio data, thereby opening doors for applications in security, healthcare, and human-computer interaction.
Published by: Anju Tripathi
