Volume 14 | Issue 4

 Abstract

Lithium-ion batteries are widely used in electric vehicles and electronic devices, but they are prone to thermal runaway, which can lead to safety hazards. This paper presents an AI-based battery thermal runaway prediction system that monitors key parameters such as temperature, voltage, and current in real time. The system uses machine learning algorithms to analyze sensor data and predict potential failures before they occur. By integrating IoT technology, the system enables remote monitoring and timely alerts. This approach improves battery safety, enhances performance, and reduces the risk of accidents, making it suitable for modern energy storage and electric vehicle applications.

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 Keywords

Battery Management System, Thermal Runaway, Machine Learning, IoT, Predictive Maintenance, Lithium-ion Battery

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Heart disease remains a leading cause of death globally, necessitating early detection for effective intervention. This study introduces HeartFL, a scalable and efficient machine learning system that predicts heart disease risk using patient health data. Leveraging a Decision Tree algorithm, HeartFL analyzes critical medical factors--including age, cholesterol, blood pressure, and heart rate--to assess disease likelihood. The system supports privacy-preserving federated learning, enabling decentralized model training without exposing sensitive patient information. A user-friendly interface allows input of health parameters or medical report uploads for automated prediction. Experimental evaluation confirms the model's reliability and accuracy, facilitating timely diagnosis. By combining intelligent prediction with privacy-aware methods, HeartFL aims to enhance clinical decision-making and improve patient outcomes. The system is deployed as a web application and can be accessed at: https://adityaindana.pythonanywhere.com/

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 Keywords

Heart disease prediction, Machine learning, Decision Tree algorithm, Patient health data, Federated learning, Data privacy, Medical diagnosis, Early detection, Healthcare technology, Predictive modeling

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ESG investing will be the subject of this study, with a particular emphasis on non-financial aspects of the Indian investment sector, such as environmental, social, and governmental factors. To determine whether investors and investment managers in the Indian investment sector are likely to adopt these practices or do they possibly pose a threat to maximize returns and increase financial wealth for their clients and themselves? Investment managers and investors from different Indian investment organisations provided a total of 385 replies to the survey used to collect the primary data for the study. The sample is chosen using a random sampling technique. In order to collect data pertinent to the Indian investment sector and show a link between organisational success and sustainable investment, the study employed quantitative methodologies and a descriptive statistical approach. Journals, papers, newsletters, books, government portals, regulatory websites, stock exchanges, and annual reports are all sources of secondary data. Every question in the questionnaire is analysed using SPSS software. Here, the coefficient correlation between two variables is determined using Pearson's correlation analysis. It was discovered that there was a significant correlation between the factors influencing investors' interest in sustainable investments and the benefits they provided. The conclusion is that sustainable investments will increase economic transactions, financial responsibility, and transparency, all of which contribute to the long-term success of Indian organisations.

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 Keywords

Words: Environmental, Social, and Governance, Indian Investment, Investment managers and investors

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The problem of financial fraud detection is one of the major problems that are faced by the digital banks. The financial fraud losses incurred by the countries across the globe are estimated to be over 485 billion dollars annually. In this paper, the authors are proposing a production-grade real-time financial fraud detection system known as FraudGuard based on ensemble machine learning, behavioral DNA profiling, and graph-based network analysis for financial fraud detection with 88.1% model confidence. In the proposed system, the transactions are processed within 10ms with a 22-feature XGBoost model, synthetic transactions, and Indian banking patterns. Additionally, the proposed financial fraud detection system uses the WebSocket protocol. As part of the proposed system, the authors are able to attain a 0.941 AUC-ROC score, precision of 0.891, recall of 0.863, and F1-score of 0.877 along with multi-channel financial fraud alerting via SMS with the help of Twilio. Additionally, the proposed financial fraud detection system uses six different financial fraud detection patterns. Six financial fraud detection patterns are card testing, AML structuring, geographic impossibility, account takeover, velocity attacks, and cryptocurrency conversion fraud.

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 Keywords

Financial fraud detection, Machine learning, XGBoost, Behavioral analysis, Real-time systems, AML, SHAP, WebSocket streaming

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Independent navigation and social interaction remain challenging for individuals with visual impairments, necessitating the development of assistive technologies that enhance safety and independence. This work proposes a smart wearable system designed to provide real-time facial recognition and location-based support. The system utilizes a computer vision model, YOLOv8, deployed on a Raspberry Pi 5 platform to identify familiar individuals and deliver immediate audio feedback to the user. To ensure user safety, a GPS module is incorporated for continuous location tracking, while a GSM module enables emergency communication by sending alerts and initiating calls to predefined contacts during critical situations. All components are integrated into a compact and lightweight wearable configuration consisting of camera-equipped glasses connected to a portable processing unit. By focusing on essential functionalities such as facial recognition, real-time tracking, and emergency connectivity, the proposed system offers an efficient and reliable assistive solution, thereby promoting greater autonomy, confidence, and social interaction for visually impaired individuals.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Assistive Technology, Computer Vision, Raspberry Pi, YOLOv8, Visual Impairment.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

SDG 11 (Sustainable Cities and Communities), Urban unemployment, Sustainable urban development, State-level analysis, India, Urbanization, Population density, Per capita NSDP.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The present study aims to explore the relationship between interpersonal communication and psychological resilience among professionals working in crime scene investigations. The study seeks to understand communication patterns, identify challenges faced during collaborative work, and examine how resilience contributes to effective teamwork in high-pressure situations. A mixed-method research design was adopted for the study. Data were collected from approximately 50 participants, including crime scene experts, Forensic scientists, and Police officers, using purposive sampling. Information was gathered through structured questionnaires and socio-demographic forms to assess communication practices, stress experiences, and resilience levels. In addition, semi-structured interviews were conducted to obtain deeper insights into communication dynamics, coping mechanisms, and collaborative experiences in investigative settings. The study emphasizes the importance of strong interpersonal communication and psychological resilience in enhancing teamwork, improving coordination, and supporting mental well-being among Forensic and Police professionals. The findings are expected to provide valuable insights for developing training programs and workplace interventions aimed at strengthening communication skills and resilience among personnel working in high-stress investigative environments

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Interpersonal Communication, Psychological Resilience, Forensic Science, Police Personnel, Crime Scene Investigation, Occupational Stress, Team Collaboration, Mental Health in Law Enforcement.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study presents a comparative evaluation of the tensile properties of Fe550D grade TMT reinforcement bars from various manufacturers, including Polaad, Rajuri, Icon, and Uma. Fe550D bars are widely used in structural applications due to their high strength and enhanced ductility, which is essential for earthquake-resistant and high-rise constructions. The evaluation focuses on key mechanical properties such as yield strength, ultimate tensile strength, and elongation, in accordance with IS 1786:2008 standards. Results indicate variations among brands, with some bars exceeding the minimum standards in tensile strength and ductility, highlighting the importance of selecting manufacturer-certified materials for structural safety. The more study emphasizes the need third-party testing and certification to ensure compliance and consistent quality across batches.this is only for case study purpose.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fe550D, TMT reinforcement bars, Tensile strength, Yield strength, Ductility

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid increase in consumption patterns and disposal culture has resulted in significant environmental challenges, including excessive waste generation and inefficient utilization of resources. The concept of a circular economy has emerged as a sustainable solution, aiming to extend product life cycles through reuse, recycling, and refurbishment. However, existing online marketplaces do not effectively incorporate intelligent systems that promote sustainable practices or assist users in making informed decisions. Vijay Shukla Information Technology Shri Ramswaroop Memorial college of Engineering and Management Lucknow,India vijayshukla.cs@srmcem.ac.in significant role in enabling circular economy practices by connecting buyers and sellers of used goods. However, existing online marketplaces primarily focus on facilitating transactions and lack intelligent features that support sustainability or optimize user decision making processes. This research proposes the development of a Smart Circular Economy Marketplace using the MERN stack, which includes MongoDB, Express.js, React.js, and Node.js, integrated with Artificial Intelligence techniques for recommendation and price prediction. The system enables users to buy and sell second-hand products while leveraging machine learning algorithms to provide personalized recommendations and fair price estimations. The recommendation system utilizes collaborative filtering and content based approaches, whereas the price prediction module employs regression models to estimate appropriate product values based on multiple attributes. The proposed system not only enhances user experience but also contributes to environmental sustainability by encouraging reuse and reducing waste. The results indicate improved user engagement, increased transaction efficiency, and better pricing accuracy, making the system a viable solution for modern sustainable marketplaces

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

MERN Stack, Full Stack Development, AI For Recommendation And Price Prediction

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Lactose intolerance is commonly perceived as an irreversible enzymatic deficiency. However, emerging evidence suggests that intestinal adaptability and microbial modulation play a significant role in symptom manifestation. Ayurveda correlates similar conditions with Agnimandya, Ama, and Grahani Dosha. This study proposes the concept of lactose intolerance as a Gut Plasticity Disorder, emphasizing reversibility. A case series of three patients treated with an integrative protocol demonstrates restoration of lactose tolerance. The findings support a paradigm shift from dietary restriction to functional gut rehabilitation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

intolerance, Grahani, Agni, Gut plasticity, Case series, Ayurveda

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Manjusha painting, a traditional art form from Bihar is known for its vibrant colors, intricate designs and rich cultural symbolism, often depicting folklore, mythology and spiritual themes. The craft is based on a popular folktale of Sati Bihula Devi Bishahari which dates back to the 7th century CE. Despite its historical and cultural significance, the awareness and recognition of this unique art appears to be limited, particularly outside its native region. Through this study, the level of public awareness will be assessed, throwing light on factors that affect the visibility and appreciation of the art form. An in-depth exploration will document the traditional methods, motifs and themes used in this artform, emphasizing its unique storytelling aspect. During the study a contemporized collection will be designed for working women using Computer-Aided Design (CAD) and AI technology. This integration of digital tools with traditional techniques will not only preserve the essence of Manjusha art but also open up new avenues for its application in contemporary design contexts. Ultimately, this research strives to bridge the gap between traditional craftsmanship and modern technology, ensuring its continued relevance and growth in the digital age.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Folk-Tale, Storytelling, Craft Preservation, Religious Art, Motif Development, Women's Wear, Business Casual, 3D Garment visualization.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

[3:18 pm, 01/04/2026] Shanvi: Proliferation of cases of missing persons around the world with grave humanitarian considerations that are at times made worse by the impotence of old ways of searching, hard work being put into rummaging through documents, public announcements, and putting posters up. Conversely, our approach using AI involves a deep-learning face recognition for rapid and improved identification of missing persons. As such, the framework integrates OpenCV and dlib-ResNet algorithms to achieve highly accurate near-real-time face matching on the Euclidean distance of 128-dimensional face embeddings. The front end of the user interface for this reporting and monitoring service is designed in React.js while the back end uses Node.js and Express.js and the underlying scalable data management is supported by MongoDB. The facility together with using the WhatsApp Business API for sending real-time alerts to matches magnifies the arena for citizen-family-government collaboration. Performance evaluation based on accuracy, precision, recall, and F1 score to confirm reliability was conducted using benchmark data sets. FaceTrace ensures the scalability of the system, quick delivery, and data security through cloud-based hosting. This platform is attached to the technology-based social model whereby the recovery of missing persons will be an expedited community-impelled intelligent process.

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 Keywords

Facial Recognition, Deep Learning, Missing Person Identification, OpenCV, dlib-ResNet, MongoDB, WhatsApp API, Artificial Intelligence.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

AURA is an AI-based institutional platform designed to support student mental wellness and academic assistance in a college environment. The system integrates a Flask and MongoDB backend with a Gemini-powered chatbot, mood-aware user interface personalization, and multimodal study support for text, image, and PDF inputs. It continuously analyzes mood and conversational sentiment to estimate stress levels, identify at-risk students, and generate timely alerts for proctors and HODs through role-based dashboards. In addition, AURA provides grievance management, self-regulation activities, and secure session-based access control to support both intervention and engagement. The platform demonstrates a closed-loop approach that combines emotional monitoring, AI assistance, and administrative oversight to improve student well-being and academic support

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

student mental wellness, AI-based academic support, stress detection, mood analysis, sentiment analysis, emotion-aware computing, mental health monitoring, chatbot assistance, adaptive user interface, institutional analytics, early intervention, role-based dashboards, grievance management, multimodal learning support, predictive risk assessment.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Freshwater ecosystems and their associated biodiversity face unprecedented threats from anthropogenic pressures, habitat degradation, and climate change.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Aquatic biodiversity, avian ecology, Silgi River, freshwater fish, behavior patterns, riparian ecosystem

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

SmartShelf AI is an intelligent book recommendation system that integrates emotion AI, semantic understanding, and quantum computing to deliver highly personalized suggestions. It analyzes user mood through natural language input using a 27-class emotion detection model. These emotional profiles are mapped into a semantic space alongside book metadata for deeper contextual matching. A quantum kernel-based similarity model captures complex relationships beyond classical methods to improve recommendation accuracy. The system is implemented as a full-stack, privacy-preserving application, demonstrating the practical use of quantum machine learning in real-world scenarios.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Book Recommendation System, Emotion-Aware AI, Quantum Computing, Quantum Kernel, Variational Quantum Circuit, Semantic Embeddings, Natural Language Processing, GoEmotions, SentenceTransformers, Hybrid Recommendation System, Affective Computing, Privacy-Preserving AI

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the 21st century, shifting toward a green economy is not merely an environmental choice; it is also an important economic strategy. For a developing country like India, this transition represents a "double dividend" because it protects the environment while simultaneously creating employment opportunities. This paper examines the relationship between green growth and employment generation in India. The study focuses on major sectors such as renewable energy, sustainable agriculture, waste management, and green infrastructure. By analysing recent policy reports and international data sources, the paper identifies emerging patterns in green job creation and evaluates the effectiveness of government initiatives supporting this transition. The findings indicate that India's expansion in solar and wind energy has created significant employment opportunities. However, the growth of green jobs is constrained by several challenges such as lack of specialised skills, limited technological capacity, and financial barriers. The study concludes that stronger policy support, increased investment in green technology, and large-scale skill development programmes can transform the green economy into a major driver of sustainable and inclusive employment generation in India.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Green Economy, Green Jobs,EmploymentGeneration,Renewable Energy, Sustainable Development, India.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

HR Analytics, also called Human Resource Analytics, is becoming popular in organizations. It helps improve employee performance and reduce turnover. This study focuses on how HR Analytics improve employee performance and retention in the manufacturing industry.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

HR Analytics, Employee Performance, Employee Retention, Workforce Planning, Data-Driven Decision Making, Predictive Analytics, Employee Engagement, Human Resource Management, Productivity Improvement, Employee Turnover

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Phonetic Orthography, Artificial-English, Grapheme-Phoneme Correspondence, ESL Pedagogy, Spelling Reform, Orthographic Depth Hypothesis.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The classic marketplaces are increasingly being digitized in the academic space, and the necessity for e-commerce solutions that bridge with this peculiar university ecosystem has arisen. Campus Kart is fulfilling this need by providing a reliable, scalable, and student-friendly platform for intra-campus transactions that focus on buying, selling, and renting of academic as well as personal items. This campus-centric shopping system operating on a MERN stack platform (MongoDB, Express.js, React.js, Node.js) utilizes movie AI for recommendation and chat- based assistance, while transactional trust is established with the help of secure payment gateways, thus stimulating the circulation of campus economics by reuse and redistribution of items for lessening financial burden and environmental waste. The system also has the reliability and scalability to cater to large student communities owing to this cloud deployment. The paper elaborates on the architectural design, implementation framework, and marketplace positioning of Campus Kart with respect to other contemporary campus-based e-commerce models. Findings indicate that local AI-enabled platforms not only make higher education ecosystems more accessible and affordable but also more sustainable. It thus concludes that Campus Kart is an attempt to blend the model of digital marketplaces into academia for economic inclusion and sustainable campus development.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Campus marketplace, localized e-commerce, MERN stack, artificial intelligence, student community, cloud computing, secure payment gateway, circular economy

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Obesity is a blessing of the modern age of machines and materialism. It occurs as a result of lack of physical activity with increased intake of food. The industrialization, stress during the work, dietary habits, lack of exercise and various varieties among the daily diet e.g. fast food, frozen fruits, increased amount of soft drinks and beverages, canned foods result into the clinical entity which we can be called as obesity. The procedure of massaging the whole body below the neck in a direction opposite to the orientation of hair with some pressure is called Udvartana. In present case study, a 40 year female patient weighted 90 kg, with triphla churna and kulatta powder along with Navaka guggulu 500 mg and Arogyaardhini vati 500mg twice a day with lukewarm water given for a period of 1 month. A significant reduction in weight and symptoms of obesity was reduced.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

obesity, triphla churna

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Creative Commons Attribution 4.0 and The Open Definition