Volume 13 | Issue 12 |

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine learning, artificial intelligence

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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 Keywords

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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Creative Commons Attribution 4.0 and The Open Definition

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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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Creative Commons Attribution 4.0 and The Open Definition

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Battery energy system

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition