Volume-11, Issue-2

March-April, 2025

Review Paper

1. Big Data Analytics for Real-Time Fraud Detection in Insurance Claims

The integration of Artificial Intelligence (AI) and Big Data Analytics is revolutionizing industries by optimizing efficiency, accuracy, and security. In healthcare and insurance, AI-driven intelligent Document Processing (IDP) automates workflows such as claims automation, medical data extraction, and regulatory compliance management. By utilizing Machine Learning (ML), Natural Language Processing (NLP), and Optical Character Recognition (OCR), IDP accelerates document classification, data validation, and anomaly detection, reducing errors by 90% and cutting processing time by 80%. In the financial sector, AI enhances fraud analytics, risk modeling, and compliance monitoring. Advanced deep learning architectures, pattern recognition, and predictive analytics improve credit risk assessment and real-time fraud mitigation. AI-powered anomaly detection techniques identify suspicious transactions, reducing cybersecurity threats and financial fraud losses.

Published by: Shaba Khatoon, Ankita Srivastava, Dr. Shish Ahmad Research Area: Big Data Analytics

Organisation: Integral University, LucknowKeywords: Artificial Intelligence (AI), Intelligent Document Processing (IDP), Machine Learning (ML), Natural Language Processing (NLP), Fraud Detection, Risk Assessment, Financial Technology (FinTech), Regulatory Compliance, Cybersecurity, Automation in Healthcare, AI in Insurance.

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Research Paper

2. Small Businesses as the Basis of the Indian Economy

India's economic progress and GDP growth have been mostly driven by small and medium-sized businesses, or SMEs. As of March 27, 2022, there were over 7.9 million MSMEs in India, according to the Ministry of Micro, Small & Medium Enterprises. India's and the world's economies have grown because of small enterprises. In a nation with an economy the size of India, small businesses make up 95% of the industrial units, and they provide 40% of the nation's total industrial production. Once more, tiny companies account for around 45% of India's overall export earnings. This paper explores the importance of small businesses in India, their contributions, their challenges, and their evolving role in driving sustainable and inclusive economic development.

Published by: Aayaan SardanaResearch Area: Economics And Business

Organisation: Modern School Vasant Vihar, New DelhiKeywords: MSME Act, Sole Proprietorship, General Partnership, Limited Liability Partnership (LLP), Corporation, Franchise, Home-Based Business, Social Enterprise, Non-profit Organization, Employment Generation, Rural Development, Economic Diversification, Innovation, Gross Domestic Product (GDP), Export Promotion, Social Impact, Government Revenue, Capital Management

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Research Paper

3. Comparative Analysis of Machine Learning Models for Diabetes Prediction: A Performance Evaluation Study

Diabetes is a chronic disease affecting millions worldwide, necessitating early diagnosis and effective prediction models for improved healthcare outcomes. This study evaluates seven machine learning algorithms for diabetes prediction using healthcare data. We compared Logistic Regression, K-Nearest Neighbors (KNN), Random Forest, Decision Tree, AdaBoost, XGBoost, and Support Vector Machine (SVM) models. The analysis focused on key performance metrics: accuracy, precision, recall, F1-score, and Area Under the Curve (AUC). Results showed that logistic regression achieved the highest overall performance with 79% accuracy and 0.88 AUC, suggesting its potential utility in clinical diabetes prediction applications.

Published by: Taaha Ansari, Vaishali M. BagadeResearch Area: Machine Learning

Organisation: Alamuri Ratnamala Institute of Engineering and Technology, Tute, MaharashtraKeywords: Diabetes Prediction, Machine Learning, Logistic Regression, KNN, F1-Score, AUC.

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Research Paper

4. Design and Development of V-Twin Stirling Engine

This project aims to address environmental issues like air pollution and noise generated by internal combustion (IC) engines through the development of a V-Twin Stirling engine. Stirling engines, which operate through cyclic expansion and contraction of gas via external heat sources, offer a more efficient and cleaner alternative to traditional IC engines. The design leverages a unique mechanism where one piston drives the motion of both pistons using a gear system, reducing fuel consumption and emissions. The project involves comprehensive analysis and design, with the engine components, such as flywheels, gears, and pistons, being meticulously crafted for optimized performance. The development process includes part drawings, weight and volume calculations, and precision manufacturing using aluminum. The Stirling engine’s potential to harness renewable energy, integrate into power generation systems, and recover waste heat positions it as a viable alternative for future sustainable automotive technologies. The total project budget is approximately INR 6000, covering materials, manufacturing, and necessary accessories.

Published by: Viraj Tambe, Ravi Singh, Rahul Mayekar, Tanish Tilak, Prof. Nikhil V.S.Research Area: Mechanical Engineering

Organisation: Rajiv Gandhi Institute of Technology, MumbaiKeywords: Environmental Issues, Air Pollution, Internal Combustion (IC) Engine, V-Twin Stirling Engine

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Research Paper

5. Energy Harvesting Poles: Harnessing Piezoelectric Power for Sustainable Infrastructure

The integration of piezoelectric poles in road infrastructure presents a promising avenue for sustainable energy generation and smart infrastructure development. Piezoelectric materials, which generate electrical energy when subjected to mechanical stress or pressure, can be embedded in road poles to harness the energy from vehicles passing by. These poles can convert the vibrations and pressure created by traffic into usable electrical energy, which can then be utilized to power streetlights, traffic signals or even be stored for future use. The potential for reducing dependency on traditional energy sources while improving the functionality and sustainability of roadways is substantial. Furthermore, piezoelectric poles can contribute to the development of smart roads, integrating sensors and communication systems that enhance traffic management and safety. This paper explores the feasibility, design, and applications of piezoelectric poles on roads, evaluating their potential environmental and economic benefits, as well as the challenges in scaling this technology for widespread use in modern transportation networks.

Published by: Ansh Mahadik, Aditi Gavand, Vivek Magar, Harashad Dhandar, Chaitali BagulResearch Area: Civil Engineering

Organisation: Vivekanand Education Society's Polytechnic, Chembur 400071Keywords: Piezoelectricity, Energy Harvesting, Smart Roads, Sustainable Energy, Road Infrastructure, Traffic-Induced Vibrations, Renewable Energy, Energy Conversion, Mechanical Stress, Road Sensors

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Research Paper

6. Crumb Rubber used in Pavement Design

Pavement design is a critical process in the construction of road infrastructure, aimed at creating durable, cost-effective, and sustainable surfaces that can withstand traffic loads, environmental conditions, and wear over time. The design methodology involves several factors, including traffic load, climate, soil properties, material selection, and the type of pavement (flexible or rigid). Traditional pavement design methods such as empirical approaches (e.g., AASHTO) rely on established guidelines and field data, while more advanced techniques, such as mechanistic-empirical methods, integrate both mechanical analysis and field performance data for a more accurate prediction of pavement behavior.

Published by: Lavanya Santosh Rokade, Manasi Shubhas Fulare, Srushti Kishor Salve, Saburi Shashikant Shivan, Suraj SurveResearch Area: CIVIL ENGINEERING

Organisation: VES Polytechnic, Mumbai, MaharashtraKeywords: Industrial Waste, Agricultural Waste, Rubberized Concrete

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Research Paper

7. Ai-Driven Vibebox: Adaptive Music Streaming Personalized Based on Emotion

Music recommendation systems play a crucial role in addressing the challenges of information overload and personalization in the digital music landscape. This paper presents the implementation and contribution of a novel music recommendation system that aims to enhance the user experience and overcome the limitations of existing approaches. The AI-Driven VibeBox: Adaptive Music Streaming personalized based on Emotion provides an overview of the project's architecture, methodology, and key findings, highlighting its contributions to music recommendation systems. The exponential growth of digital music platforms has led to an overwhelming abundance of music content, making it increasingly difficult for users to discover and explore new music that aligns with their preferences. Music recommendation systems have emerged as a vital tool to address this challenge, leveraging various techniques to provide personalized suggestions and enhance the user experience. MoodSync Vibebox is a music recommendation system that seeks to advance the state-of-the-art in this domain. This review paper aims to critically analyze the project's methodology, findings, and contributions, while also situating it within the broader context of music recommendation system research.

Published by: Dr. M.K. Jayanthi Kannan, Anirudh Kanwar, Harsh Chaturvedi, Aditya R Patil, Abhimaan YadavResearch Area: Machine Learning And Deep Learning

Organisation: VIT Bhopal University, Bhopal-Indore Highway, Kothrikalan, Sehore, Madhya Pradesh - 466114Keywords: Artificial Intelligence, ML, Intelligent Automatic Playlist Generation, Text Analysis, Fine-tuned BERT model, Sentiments and Emotions Recognition, Facial Emotion Analysis, CNN, Playlist Generation Model, React.js, Firebase, Web Application Development.

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Research Paper

8. CropVion: A VGG16-based Convolutional Approach for Plant Disease Detection

This project focuses on developing a machine learning-based system for detecting plant diseases, providing valuable support to farmers, botanists, and researchers. The aim is to improve agricultural productivity and research efforts through automated plant health monitoring. The solution includes a user-friendly and responsive interface built with Streamlit, a Python framework that facilitates the creation of web applications, enabling efficient interaction for users, whether they are in farming or research. The system leverages Convolutional Neural Networks (CNN) with a fine-tuned VGG16 pre-trained model, utilizing transfer learning to accurately classify plant diseases based on leaf imagery. A diverse dataset of plant diseases is used for training, with advanced image preprocessing techniques applied to improve classification accuracy. This solution ensures a scalable, precise, and user-friendly method for disease detection, facilitating seamless adoption into modern agricultural workflows.

Published by: Rishika Gazula, Asiya Jamadar, Avinash Shinde, Gauri BilayeResearch Area: Machine Learning

Organisation: Marathwada Mitra Mandal's College of Engineering, Pune, MaharashtraKeywords: Streamlit, CNN, VGG16, Deep Learning

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Case Study

9. Rehabilitation and Retrofitting of the Rajabai Clock Tower

The Rajabai Clock Tower, an iconic Gothic Revival structure in Mumbai, has stood as a cultural and architectural landmark since its completion in 1878. Over the years, factors such as weathering, pollution, material aging, and structural stress have led to deterioration, necessitating a comprehensive rehabilitation and retrofitting strategy to preserve its historical and structural integrity. This study focuses on assessing the structural condition of the tower using non-destructive testing (NDT) techniques, such as ultrasonic pulse velocity, rebound hammer tests, and thermal imaging. A detailed damage assessment was conducted to identify material degradation, cracks, moisture infiltration, and foundation settlement. Computational finite element analysis (FEA) was also used to evaluate load distribution and stress concentrations. The rehabilitation approach involves restoration of damaged stonework, stained glass panels, and intricate carvings using compatible materials. Retrofitting techniques include micro-jacketing, crack injection, fiber-reinforced polymer (FRP) reinforcement, and waterproofing to enhance the tower’s structural resilience while maintaining its original aesthetics. Advanced conservation methodologies ensure that modifications blend seamlessly with the existing heritage fabric. By implementing a sustainable and minimally invasive retrofitting approach, this project ensures that the Rajabai Clock Tower remains a historically preserved and structurally sound landmark for future generations. This research serves as a case study for heritage conservation, demonstrating a balance between architectural restoration and modern engineering solutions.

Published by: Muktesh Hemanta Patil, Aakash Kedar Chauhan, Sujal Arwel, Suraj SurveResearch Area: Civil Engineering

Organisation: VES Polytechnic, Mumbai, MaharashtraKeywords: Rajabai Clock Tower, Gothic Revival Architecture, Non-Destructive Testing (NDT), Finite Element Analysis (FEA), Material Degradation, Conservation Methodologies, Sustainable Restoration, Architectural Preservation, Engineering Solutions, Historical Landmark, Structural Integrity

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Research Paper

10. Marine Pollution & Implementation of Regulations

The Global Environment Report on the Rule of Law, published by UNEP, emphasizes that inadequate enforcement of existing environmental laws and regulations is a significant barrier to preventing environmental degradation. Despite the existence of international legal frameworks to address and manage marine plastic pollution, they are frequently weakened by inconsistent enforcement and a lack of accountability. Consequently, these laws are not applied uniformly across nations, undermining their effectiveness in mitigating marine pollution. The lack of specific regional guidelines leaves countries to establish their standards, creating a disjointed and varied response to the issue. Many neighboring nations focus on enhancing their solid waste collection and management systems to combat marine plastic pollution. However, improving waste management infrastructure requires substantial financial investment, a considerable challenge for many low and middle-income countries. In this context, regional collaboration provides more benefits than multilateral agreements or bilateral pacts. Although global initiatives engage a broader range of stakeholders, countries' varying levels of commitment and capacity frequently hinder prompt collective action. Conversely, while bilateral agreements are simpler to negotiate, they have a limited scope and are less effective in addressing the cross-border nature of marine plastic pollution. As a result, regional cooperation emerges as a more practical solution because it reflects shared interests, considers geographical and political contexts, and enables customized strategies that meet the unique needs and priorities of the region.

Published by: Laranya Sharma, Prof. Arun D RajResearch Area: Environmental Law

Organisation: VIT School of Law, Chennai, Tamil NaduKeywords: Plastic, Prevention, Responsibility, Contamination, Effectiveness

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Research Paper

11. Offline Multimodal Medical Assistant

Healthcare accessibility in regions with limited internet connectivity remains a critical challenge, as traditional telemedicine solutions are heavily reliant on online infrastructure. This paper presents Viksith, an innovative offline multimodal medical assistant designed to provide medical guidance through speech, text, and image inputs without requiring internet access. Viksith employs resource-efficient algorithms, including locally optimized machine learning models and rule-based decisionmaking, to deliver accurate and timely medical support on low-power devices. The architecture ensures compatibility with resource-constrained environments, making it ideal for rural and underserved areas. Comprehensive testing and pilot deployments demonstrate Viksith’s high performance in recognizing symptoms, analyzing visual inputs, and generating actionable medical insights. This paper provides a detailed exploration of Viksith’s design, implementation, and evaluation, positioning it as a scalable solution for bridging healthcare gaps in offline scenarios.

Published by: Priyanka Waghmare, Prathamesh Kulkarni, Aditya PranekarResearch Area: Medical

Organisation: Sardar Patel Institute of Technology, Mumbai, MaharashtraKeywords: Healthcare, Multimodal, Medical Support

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Research Paper

12. The Impact of GST on Accounting Practices in Chartered Accountant Firms

This study seeks to examine the effects of the implementation of Goods and Services Tax (GST) on the accounting practices of Chartered Accountant (CA) firms in India. Since its introduction in 2017, the GST has significantly transformed the landscape of indirect taxation, influencing how businesses and professionals approach financial reporting and compliance. The study delves into changes in accounting methodologies, the advisory roles of clients, the workload associated with compliance, and the adoption of technology by CA firms. Utilizing both primary and secondary data, the research assesses how these firms have adjusted to the GST framework, the challenges encountered, and the opportunities that have arisen. The findings reveal that while GST has simplified tax reporting processes, it has simultaneously heightened the complexity and frequency of compliance requirements, leading CA firms to invest in automation and digital solutions.

Published by: Akshaya M, Arun Kumar S K, K M RakshithResearch Area: Accounting

Organisation: CMR University, Bengaluru, KarnatakaKeywords: Goods and Services Tax (GST) Chartered Accountant (CA) Firms Tax Compliance Accounting Practices Indirect Tax Reform Technology Adoption GST Portal Input Tax Credit (ITC) Regulatory Framework Client Advisory Services Training and Development Digital Transformation Tax Filing and Returns Compliance Burden GST Challenges and Opportunities

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Research Paper

13. Evaluating the Role of Artificial Intelligence in Tax Administration in India

This study explores how Artificial Intelligence (AI) is transforming tax administration in India. AI is helping the government improve efficiency, reduce tax evasion, and make tax processes easier for both officials and taxpayers. With tools like data analytics and machine learning, AI can quickly detect fraud, analyze large sets of financial data, and ensure better compliance. It also supports faster processing of returns and smarter decision-making. As India moves toward a digital economy, AI plays a crucial role in modernizing tax systems, making them more transparent, accurate, and user-friendly for everyone involved. AI is reshaping the landscape of tax administration in India by automating routine tasks, minimizing human errors, and enhancing transparency. It enables tax departments to identify irregularities through predictive analysis and real-time monitoring of transactions. Chatbots and AI-driven platforms are improving taxpayer services by offering instant support and guidance. Additionally, AI helps in risk assessment, audit selection, and fraud detection, ensuring a fair and efficient tax system. As technology continues to evolve, AI has the potential to bridge gaps in tax compliance, reduce administrative costs, and build trust between taxpayers and authorities, paving the way for a more robust tax framework.

Published by: Delip Kumar S S, Dhanush Kumar A, Anshu kumar C, K S MonikkanthResearch Area: Tax

Organisation: CMR University, Bengaluru, KarnatakaKeywords: Artificial Intelligence (AI), Tax Administration, Tax Compliance, Fraud Detection

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Research Paper

14. The Influence of Social Media on Customer Preference

In the modern digital era, social media sites play a dominant role in shaping consumer behavior. This research examines the complex interplay between social media usage and customer preference and the role of online participation, influencer promotion, and user-generated content in shaping purchasing behavior. Employing the analysis of a varied dataset of consumer behavior and purchasing behavior, we seek to identify the particular mechanisms by which social media shapes brand perception and product choice. Our results emphasize the influence of authenticity and community involvement in shaping positive customer preference, providing insightful recommendations to firms looking to harness the power of social media for strategic leverage.

Published by: Prathiksha.s, Sushmitha .M, Sushmitha .VResearch Area: Marketing

Organisation: CMR University, Bengaluru, KarnatakaKeywords: Social Media, Customer Preference, Interior Design, Online Behavior, Brand Perception, Influencer Marketing, User-Generated Content, Engagement Metrics, Content Types, Demographics, Sustainability, Personalization, Technology, Consumer Behavior

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Research Paper

15. The Role of Consultants in Empowering SMEs

This research paper explores the vital role that consultants play in empowering SMEs. By providing access to specialized knowledge, skills, and expertise, consultants can help SMEs develop effective strategies, improve their operations, drive innovation, and expand their market reach. The paper highlights the benefits of consultant-SME partnerships, including enhanced performance, improved competitiveness, and sustainable growth. Through a nuanced examination of the consultant-SME relationship, this research sheds light on the ways in which consultants can tailor their services to meet the unique needs of SMEs. By adopting a collaborative approach and prioritizing the needs of their SME clients, consultants can deliver impactful results that drive long-term success. Ultimately, this paper demonstrates the value of consultants in empowering SMEs to achieve their full potential. By leveraging the expertise and guidance of consultants, SMEs can overcome their challenges, capitalize on opportunities, and thrive in an increasingly complex business environment.

Published by: Blessing David, Ashish Pradhan, Jeffrey AugustineResearch Area: Consulting And Professional Services

Organisation: CMR University, Bengaluru, KarnatakaKeywords: Small and Medium Enterprises (SMEs), Consultancy Services, Business Growth, Operational Efficiency, Financial Management, Market Expansion, Digital Transformation, Regulatory Compliance, Strategic Planning, Business Sustainability

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Research Paper

16. Regulations to be Followed by Banks

With an emphasis on compliance, risk management, and internal control systems, this research examines the broad framework of banking rules that oversee banks' financial operations. The report highlights the significance of reconciliation methods, regulatory compliance, and operational control across several regions through an internship at ANZ. It offers information on statutory ratios, capital adequacy standards, the Reserve Bank of India's directives, and regulatory acts such as the Prevention of Money Laundering Act of 2002 and the Banking Regulation Act of 1949. ANZ data analysis is also included in the research, outlining patterns in the company's financial performance, difficulties with regulatory compliance, and tactical recommendations for long-term banking operations.

Published by: Sohan Das, Prarthana Panicker, V RoopashreeResearch Area: Banking

Organisation: CMR University, Bengaluru, KarnatakaKeywords: Money Laundering, Regulations, Financial Operations

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Research Paper

17. Research on the Role of Social Media in Marketing

This study examines the transformative effects social media has made on marketing strategies to many variables. With the emergence of sites like facebook.com, instagram.com, twitter.com, linkedIn.com, and tik-tok.com, companies and organizations have shifted from their historic forms of marketing to more engaging, dynamic, and consumer-centric forms of health promotion and marketing strategies. This paper evaluates the impact of social media on developing brand awareness, targeting and engaging customers, and assessing the purchasing behaviours of consumers of brands and services, but also outlines the methods and benefits of use in paid social media advertising (targeted advertising, influencer marketing). The study is based upon a response of using quantitative and qualitative research practices/ techniques (surveys, expose case studies and data analysis) to determine various key trends, benefits and pitfalls associated with leverage social media advertising as part of a health promotion or social marketing strategy. The combination of research findings indicated to the study that social media offers huge opportunities for immediate engagement and can provide a whole new level of engagement using data-driven points of view. However, it invites brands to constantly innovate and respond to consumers. The research also provides evidence that a good social media marketing strategy is now essential for businesses who want to remain competitive and secure long-term growth, profit, and competitive advantage moving into an increasingly digital era of using social media for promotion, marketing, and advertisement.

Published by: Yakshendra Praneeth, Aishwarya. P, Madhavan. T, Vishwamoorthi HebbarResearch Area: Marketing

Organisation: CMR University, Bengaluru, KarnatakaKeywords: Social Media, Marketing Strategies, Brand Awareness, Consumer Behavior

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Research Paper

18. SynapseEd-Systematic LLM Neural Application for Personalized Educational Development

Education is evolving, yet traditional learning models struggle to adapt to individual student needs. Synapseed is an AI-driven, innovative learning system that personalizes education through Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent AI frameworks. It dynamically tailors learning paths, providing real-time AI-driven content, interactive explanations, and coding assistance across various programming languages. The system integrates vector databases, conversational memory models, and CrewAl-powered multi-agent systems to enhance knowledge retrieval from PDFs, YouTube transcripts, and structured academic resources. Additionally, Code Synapse offers multi-language coding support with syntax-aware responses. The platform is scalable and suitable for K-12, higher education, and professional training. A key innovation of SynapseEd is its efficient memory utilization and computational optimization. Unlike traditional LLM-based educational models that require high-end GPUs and large-scale infrastructure, SynapseEd achieves similar functionality on a non-GPU system with just 8GB of RAM. Leveraging quantization (4-bit QLoRA) and lightweight fine-tuning techniques demonstrates that LL.M-powered educational platforms can be built within limited hardware constraints, making AI-driven learning more accessible and deployable across diverse environments.

Published by: Vinmay Vidyadhar Tondle, Priyanka Dhulchand Kapade, Rushikesh Jitendra Bobale, Dr. Geetanjali Vivek KaleResearch Area: Artificial Intelligence And Computer Science

Organisation: New Horizon Institute of Technology, Thane, MumbaiKeywords: Large Language Models (LLMs), Finetuned-LLM, Retrieval-Augmented Generation (RAG), Synapse Agents, CrewAI, LangChain, LLMChain, Conversation Buffer Memory, Vector Databases, PEFT, LORA-QLORA

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Review Paper

19. A Review On Alzheimer's Disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder marked by a gradual decline in cognitive function, which affects memory, thinking, and reasoning abilities. As the disease advances, individuals experience worsening impairments in daily activities and exhibit behavioral changes. This condition is the most common cause of dementia, with a significant impact on quality of life for both patients and caregivers. Alzheimer's disease (AD) is the most common form of both pre-senile and senile dementia, affecting about 5% of men and 6% of women over the age of 60 worldwide, according to the World Health Organization (WHO). The disease typically begins with subtle memory failure, which progressively worsens and can become debilitating. Current treatments offer minimal impact, including acetylcholinesterase inhibitors (rivastigmine, galantamine, donepezil) and the NMDA receptor antagonist memantine. While these drugs can slow disease progression and relieve symptoms, they do not cure or prevent the disease's onset. Although the neuropathological features of AD are known, the exact mechanisms behind the disease remain unclear, which contributes to the lack of effective treatments. However, recent advances in understanding AD's pathophysiology have led to new therapeutic targets that may directly address the underlying disease process. This article discusses these recent developments in AD research and how they could potentially improve disease management and reduce care costs. It highlights the importance of advancing knowledge in this area for better treatment outcomes..

Published by: Munshi Shaikh Rahat, Maniyar Hassan, Surwase Mohini, Bagwan Wasim, Kasture Pranav, Sustarphod Vijay, Budge Ganesh, Chandel AdityasinghResearch Area: Pharmaceutics

Organisation: Godavari Institute of Pharmacy, Kolpa, MaharashtraKeywords: Alzheimer's, Management, Diagnosis, Treatment, Therapy, Types & Phases of Dementia.

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Research Paper

20. The Israel-Palestine Conflict: A Legal and Geopolitical Overview

The Israel-Palestine conflict is one of the most intractable and controversial geopolitical disputes in modern history. Rooted in colonial legacies, competing nationalist movements, and overlapping religious claims, it continues to generate widespread humanitarian, legal, and political implications across the globe. This paper seeks to provide a brief but comprehensive overview of the conflict by addressing its historical evolution, major flashpoints, key legal controversies, and contemporary developments—including the 2023–24 Israel-Gaza war, the South Africa v. Israel genocide case before the ICJ, and the regional reverberations involving Iran, Hezbollah, and major global powers.

Published by: Siddharth DuaResearch Area: Law, Politics, History

Organisation: Amity Law School, Noida, U.PKeywords: Israel, Palestine, Conflict, War, Crises, Politics, Law

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Research Paper

21. ARIA: An Intelligent Voice-Enabled Virtual Assistant for Desktop Automation and Conversation

To increase desktop productivity through natural language interaction, this research paper, Aria, introduces a Virtual Virtual Personal Assistant (VPA), built in Python. Application controls (memo blocks, calculators, etc.), webbrows, language typing, email, weather invocations, and natural conversations with DialOgpt conversation models are just some of the many tasks that ARIA can do. To interpret, create, and automate tasks on the user's computer, the assistant uses a variety of Python libraries, such as Speech_Recognition, Pyttsx3, Pyautogui, and Trans. Easy-to adjust modular architecture allows users to improve their skills according to their special needs. Integration of language-based automation into smartphones and intelligent devices has been passed considerably thanks to the efforts of established virtual assistants, providing Google Assistant, Siri, Siri, Alexa, Alexa and Cortana. The system and its capabilities rely primarily on a cloud-based ecosystem. Similarly, several open source initiatives, such as desktop-based Jarvis Clones and Mycroft AI, aim to introduce AI assistants to HR computers, but often only limited offline capabilities, are born on a specific platform and require conversational skills. Aria overcomes these limitations by providing a fully adjustable and conscious desktop assistant through privacy. Data security and user control are guaranteed by offline and online operations, support for customer-specific commands, and independence from local task cloud storage. These are open-source libraries, allowing developers and researchers to change or extend functionality at will. Aria is a convenient and clever way to improve interactions between humans and computers in everyday arithmetic environments. Thanks to the integration of conversation AI, you can respond directly to commands and have contextual conversations.

Published by: Aniket Supe, Amey Waikar, Aditya Tripathi, Dr. Shudhodhan BokefodeResearch Area: Computer Engineering

Organisation: Terna Engineering College, Navi Mumbai, MaharashtraKeywords: Virtual Personal Assistant (VPA), Speech Recognition, Natural Language Processing (NLP), Text-to-Speech (TTS), Python, Artificial Intelligence (AI), Voice Automation, Desktop Assistant, Offline Functionality, Conversational AI.

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Research Paper

22. Utilization of Sugercane Bagasse Ash in Concert (SBA)

Sugarcane bagasse ash (SCBA) is an agro-industrial byproduct generated from sugarcane bagasse combustion in sugar mills. Due to its pozzolanic properties, SCBA can partially replace cement in concrete, enhancing sustainability and reducing environmental impact. This study explores the potential benefits of incorporating SCBA in concrete mixtures, focusing on its effects on mechanical properties, durability, and workability. Experimental results indicate that SCBA improves compressive strength, reduces permeability, and enhances resistance to chemical attacks when used in optimal proportions. Utilizing SCBA in concrete production minimizes industrial waste and contributes to cost-effective and eco-friendly construction practices.

Published by: Druv Ratndeep Aru, Karan Raju Ingle, Ganesh Gautam Gaikwad, Sujal Sunil Kamble, Chaitali BagulResearch Area: Civil Engineering

Organisation: Vivekanand Education Society Polytechnic Chembur Mumbai, MaharashtraKeywords: Sugarcane Bagasse Ash, Pozzolanic Material, Sustainable Concrete, Cement Replacement, Mechanical Properties, Durability, Green Construction.

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Research Paper

23. Autonomous AI Agents for Real-Time Financial Transaction Monitoring and Anomaly Resolution Using Multi-Agent Reinforcement Learning and Explainable Causal Inference

Real-time financial fraud detection systems face significant challenges from adversaries' continually evolving attack strategies. Traditional static classifiers fail to adapt to these changes and often lack interpretability, leading to false positives and missed anomalies. This paper proposes a novel framework combining Multi-Agent Reinforcement Learning (MARL) with Explainable Causal Inference for transaction anomaly detection and resolution. A defender agent learns to identify and intercept fraud in an adversarial environment where an attacker agent simulates fraudulent behaviors. The agents interact within a stochastic game setting and are trained using a centralized critic and decentralized policies. A causal inference module constructs a directed acyclic graph over transaction features to enhance interpretability and applies do-calculus and counterfactual reasoning to explain flagged transactions. We implement a scalable, real-time deployment architecture and evaluate the system using simulated and real transaction data. Results demonstrate that our MARL-based agent outperforms static classifiers in adaptability and recall, while the causal module reduces false positives and provides transparent justifications for fraud decisions. This combination of adaptability and explainability makes the system highly suitable for practical deployment in financial institutions..

Published by: Akash Vijayrao Chaudhari, Pallavi Ashokrao CharateResearch Area: Information Technology/Computer Engineering

Organisation: Santander Bank, Sayreville, NJ, USAKeywords: Real-Time Fraud Detection, Multi-Agent Reinforcement Learning (MARL), Explainable Ai, Causal Inference, Financial Transactions, Anomaly Detection, Adversarial Learning

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Research Paper

24. Sign Language Translator

Sign language is a fundamental mode of communication for the deaf and hard-of-hearing yet there is often a gap in understanding between sign language Operators and the broader population. this search introduces amp real-time house speech Explainer mature exploitation tensorflow mediapipe and opencv specifically organized to Method arsenic associate in nursing informative drive that acquired immune deficiency syndrome non-signers inch acquisition house speech. The system translates sign language gestures into spoken language while providing interactive Characteristics that allow Operators to practise receive feedback and Improve their signing Precision. done Fancy motion credit and judgement Operators get increasingly arise their skills devising house speech acquisition available and visceral. This paper details the system's Structure Applyation and real-world Use emphasizing its potential to Improve communication and inclusivity across linguistic communities by fostering a broader understanding of sign language.

Published by: Khan NausheenResearch Area: Computer Science

Organisation: SK Somaiya Vidyavihar, Mumbai, MaharashtraKeywords: Sign Language, Real-Time Translation, Gesture Recognition, Interactive Learning, Inclusivity

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Research Paper

25. The Development and Importance of Complex Numbers in Mathematics

The journey of complex numbers from mathematical heresy to fundamental scientific tool represents one of the most remarkable intellectual transformations in history. These numbers of the form a + bi (where i² = -1) have transcended their origins in algebra to become indispensable across physics, engineering, and technology. This comprehensive study examines their historical evolution, deep mathematical properties, and unparalleled applications that continue to shape modern science. Through detailed analysis of pivotal developments, we demonstrate how complex numbers provide the mathematical language for describing phenomena from quantum entanglement to wireless communication.

Published by: Aniruddha KumarResearch Area: Mathematics

Organisation: DAV Degree College, LucknowKeywords: Algebra Physics Engineering Technology Historical Evolution Mathematical Properties Applications Modern Science Quantum Entanglement Wireless Communication Mathematical Language Intellectual Transformation Pivotal Developments

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Research Paper

26. Personalized Medicine Using AI and Genomics

A conceptual change in healthcare, personalized medicine uses an individual's genetic profile to forecast disease risk, customize drug treatments, and increase patient outcomes. With its great genomic variety, the development of such systems is hampered in the Indian setting by the scarcity of region-specific, annotated clinical datasets. Using IndiGenome and PharmGKB as main references, this work presents a framework for combining genomic and pharmacogenomic data to enable personalized medicine. A manually built dataset with standardized notations was produced to replicate patient data due to integration difficulties between accessible datasets. This enabled the application of treatment logic and important gene mutations (BRCA1, BRCA2, TP53) based on working artificial intelligence. Future deployment with actual genomic data builds on this Streamlit-based application, which is able to predict treatments and provide health recommendations.

Published by: Khan NavidShabaResearch Area: Artificial Intelligence In Healthcare

Organisation: S. K. Somaiya College, Somaiya Vidyavihar University, Mumbai, MaharashtraKeywords: Personalized Medicine, Artificial Intelligence, Genomics, Brca1, Brca2, Tp53, Random Forest, Machine Learning, Drug Prediction, Pharmacogenomics

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