Volume 13 | Issue 12

 Abstract

Mutual funds have become a fundamental component of contemporary investment portfolios, offering individuals an accessible and professionally managed avenue for wealth creation. By pooling resources and diversifying investments across equities, bonds, and other securities, mutual funds enable investors to achieve an optimal balance between risk and return. Their rapid expansion in recent decades is largely driven by rising financial awareness, technological advancements in online investment platforms, and supportive regulatory frameworks. As participation in mutual funds grows across diverse economic segments, understanding how investment volumes vary among income groups becomes increasingly important. This study examines the growth of investment and engagement levels of mutual fund investors across different income categories.

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 Keywords

Growth, mutual funds, investment, income group

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This research paper examines the transformation in retail investor behaviour due to the unparalleled rise of digital technology and social media in modern India. At over 150 million, the number of demat accounts has surged, with the average age of new investors plummeting as more young people join, mainly those below 35 years of age, who invest through mobile applications and social media platforms. The paper assesses the role of Instagram, YouTube, and Telegram in influencing investment decisions, creating phenomena such as FOMO and herding, which further lead to speculative trading. Although the enthusiasm of young investors has helped make the market more confident during declining trends, the paper also highlights the perils of options trading and the high percentage of retail traders incurring losses. Based on these findings, the study puts forward actionable recommendations to improve financial literacy and encourage responsible trading among the young and new investors. This paper seeks to find an appropriate balance between tapping the potential of the digital natives in the Indian stock market while reducing the risks involved with speculation.

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FOMO, herding, behavioral finance, social media, retail investors, digital natives, and the Indian stock market

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Background:The chronic metabolic disease known as diabetes mellitus (DM) is typified by ongoing hyperglycemia. It could be caused by resistance to insulin's peripheral effects, decreased insulin production, or both. In patients with diabetes mellitus, chronic hyperglycemia can harm several organ systems in concert with other metabolic abnormalities, resulting in the emergence of crippling and potentially fatal health issues. Methods and materials:This study aimed to assess the prevalence of type 2 diabetes mellitus in females aged 35 to 45 at Sree Ramakrishna Medical College of Naturopathy and Yogic Sciences and Hospital is situated in Tamil Nadu, India's Kulasekharam. The study units consisted of women aged 35 to 45. For the study, a questionnaire is employed.When the study's purpose was explained, the women verbally agreed. The study had 30 female participants in total. The questionnaire consists of thirty questions covering topics such as pain, numbness, food cravings, itching in the extremities, medicine, and weight loss.Conclusion:We conclude that the development of comprehensive programs intended to educate people and raise awareness of particular health risks is essential to predictive and preventive healthcare. This emphasizes how crucial awareness is for managing and preventing type 2 diabetes.Adopting a comprehensive awareness and education campaign is crucial to improving predictive and preventive healthcare and eventually lowering morbidity and mortality.

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 Keywords

Diabetes mellitus,hyperglycemia,metabolic disorder,ulcer,blood sugar,itching in extremities

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This paper presents a comprehensive criminal face detection and identification system built using traditional face recognition techniques rather than deep learning or convolutional neural networks (CNNs). The solution is designed for real-time law enforcement assistance, secure access verification, and controlled surveillance environments. The system employs OpenCV's Haar Cascade Classifier for efficient and lightweight face detection, while facial feature extraction and recognition rely on dlib's Histogram of Oriented Gradients (HOG)-based model and 128-dimensional face encodings. The system maintains all identity records inside a local credential database, and facial images are stored securely in a structured local file system, ensuring privacy and data protection without cloud dependency. The proposed approach demonstrates reliable identification accuracy in controlled environments, fast inference speed, and low hardware requirements, making it suitable for organizations with limited computational resources. Experimental evaluations confirm the model's capability to consistently detect and recognize faces under stable lighting conditions and frontal orientations.

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Face recognition, Haar Cascade, HOG, dlib encodings, OpenCV, Criminal identification, Local database, Local file storage.

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In the modern digital era, emotional intelligence in technology has become a vital component of personalized user experiences. MoodTune is an AI-based system that detects users' emotions in real-time using facial expressions and voice tone and automatically recommends suitable music through Spotify and YouTube integration. The system employs Deep Learning models for emotion detection and Natural Language Processing (NLP) for voice-based mood analysis. It integrates Spotify and YouTube APIs to generate unlimited mood-based playlists, offering a seamless and adaptive entertainment experience. The project demonstrates the use of computer vision, deep learning, and cloud API integration to enhance human-computer interaction through emotion-aware multimedia recommendations.

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Emotion Detection, Deep Learning, Music Recommendation, Spotify API, YouTube API, Artificial Intelligence, Human-Computer Interaction.

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E-Commerce portals are now trending in India. It is growing everywhere, and customers are showing interest in using these portals effectively. There are so many portals which are unique in their features and the design of websites. The e-commerce has broken the technological and geographical barriers over the years and has got huge amount of success which many economical analyst and experts never predicted and still it must go a long way ahead in India. By integrating various online information management tools using Internet, various innovative companies have set up systems for taking customer orders, facilitate making payments, customer service, collection of marketing data, and online feedback respectively. These activities are collectively known as e-commerce or Internet commerce. Online shopping made it so easy for everyone with their product variations and simple ways to buy things. Both these big players made their own mark in India, but who is going to be ultimate winner or be the top one is going to be. A comparative study of Flipkart.com with one of the close competitors Amazon.com delivers the information about the different strategies to succeed in e-commerce market and different opportunities available in India.

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Online Shopping, Customers perceptions, Amazon, Flipkart, Shopping, Strategies, Price.

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This study aimed to assess amputees' participation level in physical activities and sports competitions in Yemen and to evaluate the key factors influencing their engagement, including accessibility, infrastructure, and institutional support. The researcher employed a descriptive methodology, collecting data through a questionnaire distributed to 104 amputees. The findings highlight significant limitations in sports facilities, specialized equipment, systematic planning, coaching expertise, and financial support, all of which contribute to low participation in physical activities and sports competitions. Moreover, the absence of an organized sports framework and dedicated policies further exacerbates these challenges. Based on the results, this study proposes a strategic plan to enhance amputees' participation in sports by improving infrastructure, implementing specialized training programs, increasing financial resources, and reforming policies at the Ministry of Youth and its provincial offices. The study emphasizes the importance of collaboration between governmental institutions, sports organizations, and community initiatives to foster an inclusive and sustainable sports environment for amputees and individuals with disabilities. It anticipates that implementing these recommendations will lead to higher participation rates, improved athletic performance, and enhanced overall well-being for amputees in Yemen.

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Amputees; physical activity; rehabilitation; adaptive sport; prosthetics; Yemen; participation

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Cognitive Radio (CR) technology enables adaptive configuration of transmission parameters based on the operating environment and diverse Quality of Service (QoS) requirements, offering a pathway to energy-efficient wireless communications. Among the radio frequency (RF) components, the power amplifier (PA) constitutes a major contributor to energy consumption, particularly in medium- and long-range transmissions. Minimizing PA power consumption is therefore critical for realizing green radio systems. This study presents a mathematical formulation of total system power consumption at a CR transmitter with Class B PA and investigates optimization via parameter reconfiguration for multicarrier data transmission scenarios. Five nature-inspired (NI) metaheuristic algorithms Ant Lion Optimizer (ALO), Grasshopper Optimization Algorithm (GOA), Grey Wolf Optimizer (GWO), Moth Flame Optimization (MFO), and Whale Optimization Algorithm (WOA) are applied and compared based on multiple performance metrics. Simulation results indicate that WOA achieves superior performance in minimizing system power consumption while satisfying multiple QoS constraints, demonstrating its effectiveness for green cognitive radio design.

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Cognitive Radio, Green Radios, Power Amplifier, Nature-Inspired Optimization, Multicarrier Transmission, Whale Optimization Algorithm, QoS Constraints, Energy Efficiency

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This paper presents the design and development of a blog application using the MERN stack (MongoDB, Express.js, React, and Node.js). The project aims to create a dynamic, responsive, and scalable platform for managing and sharing blog content efficiently. Key features include user authentication, content creation and editing, real-time updates, and secure data storage. The system ensures smooth front-end and back-end integration for optimal performance and user experience. Testing results demonstrate that the MERN-based blog application provides improved functionality, speed, and scalability compared to traditional web solutions.

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Keywords- Blog Application, MERN Stack, MongoDB, Express.js, React.js, Node.js, Full-Stack Development, Web Application, Content Management System, User Authentication, RESTful API, Data Security, Responsive Design, CRUD Operations, Real-Time Updates, Scalability, Front-End and Back-End Integration

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Machine learning performance is fundamentally influenced by the quality of data preprocessing this work provides an analytical overview of preprocessing strategies for textual data tokenization and bag-of-words representations are discussed as foundational techniques

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Machine learning, artificial intelligence

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Financial systems are becoming more complex, and this increases the need for powerful tools that can analyze large datasets and handle difficult problems. Quantum computing offers new ways to process information faster and solve problems that are hard for traditional computers. This paper explains the basic ideas behind quantum computing and explores how they can be used in financial modelling, especially in portfolio optimization, risk analysis, and option pricing. It highlights important quantum algorithms such as the Quantum Approximate Optimization Algorithm (QAOA) and Quantum Amplitude Estimation (QAE), which show strong potential for improving financial computations. The paper also discusses current technological challenges, industry readiness, and how quantum-based financial modelling might develop in the next ten years. Our findings suggest that although quantum technology is still in its early stages, it has the potential to bring major improvements to financial modelling.

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Quantum Computing, Financial Modelling, Portfolio Optimization, Option Pricing, Risk Management, QAOA, QAE, Quantum Machine Learning

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In today's competitive market, job seekers struggle to find suitable employment opportunities, and employers face difficulties in reaching skilled candidates efficiently. To address this gap, this paper presents JobDekho, a full-stack job portal designed to simplify recruitment through automated workflows, optimized data handling, and real-time communication. The system enables job seekers to search and apply for jobs while allowing employers to manage postings and applications. JobDekho integrates Spring Boot, MySQL, and REST APIs to provide a scalable and high-performance application. The platform includes advanced search & filter features, email notification support, and performance optimization techniques, ensuring an efficient and user-friendly experience. Experimental results demonstrate improved responsiveness and reduced processing time through optimized API calls and caching. This project shows how modern full-stack architecture can enhance digital recruitment and streamline the hiring process.

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Job Portal, Recruitment System, Spring Boot, MySQL, Full-Stack Development, REST API, Job Search and Filter, Application Management, Email Notification System, Performance Optimization, Redux Caching, Employer Dashboard, Digital Hiring, Web Application, Automated Job Application..

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This paper examines the role of the National Assessment and Accreditation Council (NAAC) in promoting institutional accountability and continuous quality enhancement (CQE) in teacher education institutions (TEIs) in India. It contextualises NAAC within India's higher education quality assurance ecosystem, describes the NAAC assessment-accreditation processes and instruments (with specific emphasis on teacher education manuals and AQAR), analyses mechanisms through which NAAC influences governance, curriculum, teaching-learning, research and stakeholder engagement, and discusses challenges and recommendations for strengthening NAAC's impact on teacher education. Findings indicate that NAAC has catalysed institutional self-evaluation, internal quality assurance (IQAC) structures and data-driven improvements in TEIs, but gaps remain in capacity building, contextual assessment, and sustained post-accreditation follow-up.

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NAAC, Teacher Education, Quality Assurance, Institutional Accountability, Continuous Quality Enhancement, IQAC, AQAR, RAF

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In any organization, the retirement transition represents a turning point in one's life and career. For civilian human personnel of the Philippine Army, the pre-retirement phase is not just a countdown to a separation; it is a juncture of introspection, adjustment, and emotional preparedness molded by years of service within a specially designed setting.

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THE PROBLEM AND ITS BACKGROUND

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Keywords: Level of stress ,coping strategies and high school students.

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This study investigates the dynamic relationship between Collective Bargaining Agreements (CBAs), funding mechanisms, and political influence in Kenya's public sector between 2021 and 2025. CBAs have become central to industrial relations in Kenya, particularly in education, health, and civil service, where unions exert significant bargaining power. The research problem addressed is the persistent gap between negotiated agreements and their enforcement, often shaped by fiscal constraints and political cycles. By examining how funding allocations and political considerations affect the implementation of CBAs, the study contributes to understanding the sustainability of labour relations in Kenya's evolving governance context. The study adopted a qualitative research design anchored in documentary analysis. Data were collected from government budget policy statements, Teachers Service Commission (TSC) circulars, Ministry of Public Service reports, parliamentary Hansards, and union press releases (KNUT, KUPPET, UASU, KMPDU). Secondary sources included academic articles and media coverage of industrial disputes. A thematic analysis approach was employed to identify recurring patterns in CBA funding, enforcement, and political influence. Case studies from the education, health, and university sectors provided sector-specific insights, while triangulation enhanced validity and reliability of findings. The study reveals that CBA enforcement in Kenya is uneven across sectors. Teachers and civil servants benefited from relatively higher allocations, with the 2021-2025 teacher CBA receiving KSh 83 billion, while university staff secured KSh 13.8 billion in 2022 after prolonged negotiations. Health workers' CBAs were partially enforced, with risk allowances implemented but salary adjustments delayed due to fiscal constraints. Funding commitments were frequently politically motivated, with governments making concessions during election cycles or under union pressure to avert strikes. Inflation and currency depreciation eroded the real value of negotiated increments, undermining the intended benefits. Enforcement mechanisms were weak, with phased disbursements and delayed Treasury releases fueling industrial unrest. Strikes remained a recurrent outcome, particularly in the health and education sectors, highlighting the fragility of Kenya's industrial relations system. To achieve sustainable CBA funding and enforcement, the study proposes several measures. First, integration of CBA obligations into the Medium-Term Expenditure Framework (MTEF) would ensure predictable and transparent budgetary allocations. Second, a centralized negotiation framework should be established to harmonize CBAs across unions, reducing fragmentation and duplication of demands. Third, inflation-indexed increments should be introduced to safeguard workers' earnings against economic shocks. Fourth, performance-based funding models could link portions of CBA resources to measurable service delivery outcomes, particularly in education and health. Fifth, enhanced transparency and accountability through annual public reporting of CBA commitments and disbursements would build trust between government and unions. Finally, the study recommends depoliticizing CBA negotiations by anchoring them in fiscal discipline and institutional frameworks rather than electoral cycles, thereby promoting industrial harmony and strengthening public service delivery. The findings underscore that CBAs in Kenya are not merely labour instruments but are deeply intertwined with fiscal policy and political strategy. Sustainable funding and enforcement require a shift from ad hoc, politically driven commitments to structured, transparent, and economically grounded frameworks. By addressing fiscal constraints, harmonizing negotiations, and insulating CBAs from political manipulation, Kenya can enhance industrial stability, protect workers' rights, and improve the efficiency of public sector service delivery.

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Collective Bargaining Agreement (CBA) A legally binding contract negotiated between an employer and a trade union representing employees. It outlines agreed terms of employment such as wages, allowances, working conditions, and dispute resolution mechanisms. In Kenya, CBAs are recognized under the Labour Relations Act and are enforceable once registered with the Employment and Labour Relations Court. Enforcement The process of ensuring compliance with the terms of CBAs through legal, administrat

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The performance, safety, and driving range of modern electric vehicles (EVs) depend heavily on an efficient and intelligent Battery Energy System (BES). This paper presents a comprehensive study on the control and analysis of EV battery systems, focusing on accurate state estimation, optimal energy management, and enhanced lifecycle performance. A Battery Management System (BMS) is used to monitor key parameters such as State of Charge (SOC), State of Health (SOH), temperature, and voltage balance across cells. Advanced control algorithms--including model-based prediction, adaptive control, and machine-learning-based estimation--ensure safe operation, prevent overcharging/over-discharging, and improve battery reliability. The study also evaluates thermal management strategies to maintain optimal temperature and minimize degradation. Simulation results and analytical models highlight how improved control techniques increase energy efficiency, reduce power losses, and extend battery lifespan. Overall, this research demonstrates that an optimized control and analysis framework is crucial for enhancing the performance, safety, and sustainability of electric vehicle battery systems.

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Battery energy system

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Text-Based Spoken Term Detection (STD) is the task of detecting and temporally localizing user-defined textual query terms directly from large collections of unstructured speech data. Unlike Automatic Speech Recognition (ASR), which focuses on generating complete transcriptions, STD concentrates on accurately identifying specific keywords with minimal false alarms and missed detections. Over the last two decades, STD has evolved from template-based methods and HMM-GMM frameworks to modern deep learning and transformer-based architectures. This paper presents a comprehensive survey of text-based STD systems covering literature evolution, system architecture, feature extraction, keyword modeling, ASR-based and acoustic-based techniques, deep learning advancements, similarity matching strategies, standard evaluation metrics, benchmarking tools, key challenges, and real-world applications. In addition, a complete implementation framework using the QUESST-2014 dataset with the Terrier Information Retrieval platform and the Hiemstra Language Model is presented, with speech transcription performed using the HappyScribe platform.

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Text-based Spoken term detection, Automatic Speech Recognition, Terrier Information Retrieval, Hiemstra language model

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From a government aided School, Coimbatore, 312 students from classes 8th and 9th standards were screened for their level of mindful attention awareness (MAA) and emotional health (EH) using Case Study Schedule, Mindful Attention awareness Scale, Children's Automatic Thoughts Scale and Mental Health Risk Scale. Out of them, 66 students (59 boys and 7 girls) with Moderate and Low MAA and EH were randomly selected. They were in the age range of 12 - 17 years. As psychological intervention, Cognitive Behaviour Therapy (CBT) was used. Six sessions of CBT were given to the students in two weeks, with each session lasting for one hour. After two weeks the students were reassessed for Mindful Attention Awareness, Automatic Thoughts and Mental Health Risk. Initially, 15% of the students had Low and 62% of the students had Moderate Mindful Attention Awareness;2% of the students and 14% of the students had High and Moderate Negative Automatic Thoughts and 32% of the students had High and 65% of the students had Moderate Mental Health Risk. After CBT, only 3% of them had Low and 50% of them had Moderate MAA; 2% of the students had High and only 8% of them had Moderate Negative Automatic Thoughts and only 15% and 58% of the students had High and Moderate Mental Health Risk. The differences in the MEAN of the variables, before and after CBT were statistically significant. The results also showed a negative correlation between 'Mindful Attention Awareness and Negative Automatic Thoughts' and Negative Automatic Thoughts and Mental Health Risk.

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Mindful Attention Awareness, Negative Automatic Thoughts, Mental Health Risk, Emotional Health.

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The present study focuses on the "Comparison of Cross-Section of Column and Its Foundation of Framed Structure Building in Seismic Zones IV and V." The objective of this research is to analyze and design reinforced concrete (RC) columns and their respective foundations under different seismic zone conditions as per IS 1893 (Part 1):2016 and IS 456:2000.

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"COMPARISON OF CROSS SECTION OF COLUMN AND ITS FOUNDATION BASE OF FRAMED STRUCTURE BUILDING IN SEISMIC ZONE IV AND V"

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