Volume 14 | Issue 4

 Abstract

Gramin Unnayane Panchayati Raj Pratisthan: Paschim Bardhaman Jelar Baidyanathpur O Ukhra Gram Panchayat Elakakendrik Ekti Kshetrasamikshamulak Paryalochana

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Gramin Unnayane Panchayati Raj Pratisthan: Paschim Bardhaman Jelar Baidyanathpur O Ukhra Gram Panchayat Elakakendrik Ekti Kshetrasamikshamulak Paryalochana

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Brand Image, Purchase Intention, Price Sensitivity, Samsung Smartphones, Consumer Behaviour, Chi-Square Test, Kanpur, India

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Career goals and choices are important parts of a person's growth. They are influenced by things like society, education, culture, personality, and work settings. Career decisions can greatly affect a person's life, for better or worse. These choices are often shaped by parents, friends, and the environment. Picking the right career is crucial for students starting professional education because it affects their future success. Research shows that gender plays a big role in career choices. Giving young people the right knowledge and tools helps them plan their futures realistically. This study looks at how gender norms affect career goals in middle school girls. It explores how gender norms shape career goals at a critical stage when societal expectations meet self-perception. It suggests a way to understand how stereotypes, reinforced by family, teachers, and media, limit girls' career choices, often making them ignore STEM fields. The paper calls for a broad approach to break these barriers, stressing the need for inclusive education, role models, and awareness programs. Using data from teenagers aged 13-18 from 1992 to 2025, this study examines changes in career goals, focusing on gender and race/ethnicity differences.

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Career aspirations, Gender norms. Middle school girls

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Alumni engagement plays a significant role in strengthening institutional reputation, supporting student career development, and fostering long-term academic growth. However, many educational institutions continue to manage alumni information using fragmented and manually maintained systems, resulting in outdated data and weak engagement. This paper proposes an artificial intelligence-driven digital platform for centralized alumni data management and engagement. The system integrates automated profile synchronization, intelligent job recommendation, mentorship matching, targeted communication, and real-time analytics within a secure and scalable architecture. The proposed solution improves data accuracy, enhances alumni participation, and reduces administrative effort, thereby enabling sustainable and value-driven alumni-institution relationships.

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Alumni Management System, Artificial Intelligence, Career Services, Data Analytics, Centralized Database.

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Web applications are continuously exposed to advanced cyber threats such as SQL injection, Cross-Site Scripting (XSS), and zero-day attacks. Traditional Web Application Firewalls (WAFs) mainly rely on static rule-based or signature- based detection methods. These systems are reactive in nature and often fail to detect new or unknown attack patterns. To overcome these limitations, this project proposes a Transformer- based end-to-end Web Application Firewall pipeline that uses deep learning for intelligent anomaly detection. The proposed system utilizes a Transformer Auto encoder model to learn the structural and contextual patterns of legitimate HTTP traffic. During the training phase, the model is trained only on benign web server logs collected from platforms such as Apache and Nginx. Dynamic fields like timestamps, session IDs, and user-specific values are normalized to ensure consistent learning. By understanding the normal "grammar" of web requests, the system can identify deviations from expected behavior. In real-time deployment, incoming HTTP requests are processed through pre processing, tokenization, and inference stages. The Transformer model reconstructs each request and calculates a reconstruction loss value. If the loss exceeds a predefined threshold, the request is flagged as anomalous and treated as a potential attack. This method enables the detection of unknown and zero-day exploits without relying on predefined signatures.

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XSS, WAF, SQL Injection, HTTP traffic.

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Social media has become an integral component of contemporary communication and is increasingly shaping teaching and learning practices in higher education. Platforms such as Facebook, Twitter, LinkedIn, blogs, and YouTube offer opportunities for interactive engagement, collaboration, and knowledge sharing, supporting innovative pedagogical approaches like flipped classrooms, collaborative learning, and peer interaction that can enhance student motivation and deepen understanding. However, the incorporation of social media remains uneven, as some educators readily adopt these tools while others face challenges related to limited digital literacy, insufficient institutional support, and concerns about privacy, copyright, and accessibility; moreover, disciplinary differences and cultural contexts further influence patterns of adoption. While existing research has largely focused on student engagement and general usage trends, comparatively little attention has been given to teachers' perspectives and experiences. Addressing this gap, the present study examines how educators perceive and utilize social media in their teaching practices, the challenges they encounter, and the influence of contextual factors such as infrastructure and policy frameworks on its effective use. The findings are expected to provide meaningful insights into the role of social media in higher education and inform the development of more effective, context-sensitive, and sustainable strategies for its incorporation, ultimately enhancing teaching and learning outcomes.

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Social Media, Higher Education, Teacher Perspectives, Student Learning

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Plastic waste management remains a critical global challenge, requiring efficient tracking and processing systems to support circular economy goals. QR code-based tracking systems have emerged as a cost-effective solution for identifying and monitoring plastic waste across its lifecycle. However, these systems currently depend on manual scanning, resulting in tracking inaccuracies, data inconsistencies, and operational inefficiency.

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Artificial Intelligence, QR Code Tracking, Plastic Waste Management, Computer Vision, Deep Learning, Automated Test Case Generation, Waste Classification, Smart Waste Management, IoT, System Validation.

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With the increasing focus on patient centered healthcare, analyzing patient feedback has become essential for improving medical service quality. Traditional methods like manual surveys are time-consuming and fail to capture the full range of patient experiences. To address this, the proposed system uses Artificial Intelligence and Natural Language Processing techniques to automatically analyze unstructured feedback from multiple sources such as hospital forms, social media, and healthcare platforms. It applies sentiment analysis, opinion mining, text classification, and topic modeling to extract meaningful insights, enabling data-driven decision-making and targeted improvements. The framework also integrates predictive analytics to identify recurring issues and healthcare trends, supporting evidence-based policy development. This AI driven approach ensures real-time monitoring, scalability, and adaptability, ultimately enhancing healthcare quality, operational efficiency, and patient trust.

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Sentiment Analysis, Text Classification, Healthcare Analytics, Patient Satisfaction, Healthcare Quality Improvement.

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This study aims to assess the practices related to PCOS among young women in Tamil Nadu and to examine their association with selected socio-demographic. A descriptive research design was adopted for the study. Data were collected from young women aged 18-30 years across selected districts of Tamil Nadu using a non-probability convenience sampling method. A semi-structured questionnaire was used to gather information. The findings reveal that two-thirds of the respondents shows a moderate level of practices, while one-fourth reported low-level practices and less than one-fourth show high-level practices. The majority of respondents belonged to the 21-25 years age group. More than half of the respondents were postgraduates and students. Inferential analysis using non-parametric tests indicated that most socio-demographic variables such as age, employment status, income, awareness, and family history do not show a statistically significant association with practice levels. However, educational level shows a significant association with practices (p < 0.05), indicating better practices among more educated respondents. Overall, the findings highlight that although a moderate level of practices is observed among most respondents, there remains a need to strengthen consistent and effective health behaviours. From a social work perspective, the study emphasizes the importance of community-based interventions and institutional support systems to promote sustainable lifestyle practices and improve the well-being of young women.

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Polycystic Ovary Syndrome, health practices, lifestyle management, young women, preventive health, social work perspective

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The introduction of the Goods and Services Tax (GST) has significantly transformed the accounting landscape, necessitating the adoption of smart accounting systems to ensure transparency, accuracy, and regulatory compliance. This paper examines the role of advanced technological tools--such as cloud accounting, artificial intelligence (AI), machine learning, and automated compliance software--in reshaping accounting practices in the GST era. Smart accounting systems enable real-time data processing, seamless invoice matching, automated return filing, and improved audit trails, thereby reducing human errors and enhancing operational efficiency. The study highlights how digital integration between businesses and tax authorities has increased transparency and minimized tax evasion. It also explores the challenges faced by small and medium enterprises (SMEs) in adapting to these technologies, including high implementation costs, lack of technical expertise, and data security concerns. Furthermore, the paper evaluates the impact of e-invoicing, GST portals, and compliance tools on financial reporting and decision-making processes. By analysing recent trends and technological advancements, this research emphasizes the growing importance of intelligent accounting systems in ensuring timely compliance and fostering a culture of accountability. The findings suggest that organizations adopting smart accounting solutions are better equipped to handle complex GST requirements and maintain competitive advantage. The paper concludes that continuous technological innovation and adequate training are essential for maximizing the benefits of smart accounting systems in the evolving GST framework.

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Keywords: Innovation, Adopting, Compliance, Transparency, Implementation

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This paper critically examines the marginalization of women's intellectual contributions within Indian Knowledge Systems (IKS), encompassing Vedic, Buddhist, Jain, Bhakti, and indigenous traditions. Challenging the dominant perception of IKS as inherently male-dominated, the study argues that such representations are the result of historically embedded processes of erasure, patriarchal transmission, and selective canonization rather than the absence of women as knowledge producers. Drawing on the framework of epistemic injustice as theorized by Miranda Fricker (2007), the paper demonstrates how women were systematically denied recognition as credible knowers and excluded from dominant interpretive frameworks. Through a critical analysis of textual traditions, oral knowledge systems, and socio-historical structures, the study identifies key mechanisms of silencing, including patriarchal canon formation, the privileging of written over oral knowledge, colonial epistemological interventions (as discussed by Dipesh Chakrabarty, 2000), and restricted access to education and linguistic capital. It further highlights the presence of women as philosophers, poets, and custodians of indigenous knowledge, whose contributions have been marginalized or anonymised within dominant narratives. The paper argues that recovering these "silenced scholars" is essential for achieving epistemic justice and for reconfiguring IKS as inclusive and plural knowledge systems. It calls for a reconceptualization of knowledge that values oral, experiential, and vernacular traditions, alongside a critical re-evaluation of canonical texts through feminist and decolonial lenses. By foregrounding women as active agents in knowledge production, this study contributes to ongoing efforts to decolonize knowledge systems and transform contemporary educational practices into more equitable and inclusive frameworks.

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Indian Knowledge Systems, epistemic injustice, women's knowledge, feminist epistemology, oral traditions

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Abstract -- In a world where communication is a fundamental right, individuals with hearing and speech impairments still face major barriers. Language is an essential aspect of human socialization, which poses difficulties for many hearing and speech-imperiled individuals. This paper presents an advanced AI-based system for Indian Sign Language recognition with integrated emotion fusion, aimed at improving real-time communication for individuals with hearing and speech impairments. Developed using Python and a Tkinter-based GUI, the system captures live video through a webcam, processes frames, and utilizes a Machine Learning (ML) to identify hand signs (a-z) alongside seven emotional states. By combining gesture recognition with emotion analysis, the system generates more expressive and context-aware sentences, which are further translated into Hindi or Marathi for regional accessibility. The approach leverages publicly available datasets from Kaggle for training and ensures a low-cost, efficient, and user-friendly solution that enhances inclusivity and bridges communication barriers in social, educational, and professional settings.

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Emotion Fusion, Machine Learning (ML), Real time, Sign Language Recognition.

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Contemporary management theories have significantly advanced organizational efficiency, leadership effectiveness, and performance measurement; however, they continue to struggle with ethical decline, leadership stress, employee disengagement, and lack of purpose. Western management thought predominantly emphasizes rationality, performance outcomes, and external success, often neglecting the inner dimensions of ethics, emotional balance, and spiritual well-being. In contrast, the Bhagavad Gita presents a holistic philosophy of action rooted in duty (Dharma), selfless work (Karma Yoga), emotional equanimity (Samatvam), and detachment from outcomes (Nishkama Karma). This study develops and empirically validates a Holistic Management Paradigm (HMP) that integrates Gita-based ethical-spiritual principles with modern management theories such as Maslow's Self-Actualization and Drucker's Management by Objectives (MBO). Using a mixed-method research design, data were collected from 350 management educators, corporate executives, and postgraduate management students. Statistical analysis employing correlation, regression, and Structural Equation Modeling (SEM) confirms that ethical, emotional, cognitive, and spiritual dimensions significantly enhance leadership effectiveness and organizational performance. The findings establish that integrating Eastern spiritual wisdom with Western managerial rationality offers a sustainable, value-based, and human-centric approach to modern management.

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Keywords: Bhagavad Gita, Karma Yoga, Holistic Management Paradigm, Ethical Leadership, Spiritual Intelligence, Modern Management

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Abstract Background: Menopausal transition is a significant bio-psychosocial phase in a woman's life, often accompanied by vasomotor symptoms, sleep disturbances, mood fluctuations, and psychological distress. These changes can negatively influence quality of life and overall wellbeing. While pharmacological therapies are widely used for symptom management, growing attention has been directed toward non-pharmacological psychosocial approaches. Resilience-based interventions, which aim to strengthen adaptive coping, emotional regulation, and stress management, have emerged as promising strategies during this life transition. Objective: To synthesize existing evidence on resilience-based interventions and examine their effectiveness in improving quality of life and psychological wellbeing among women undergoing menopausal transition. Methods: A narrative review design was adopted. Relevant literature published between January 2000 and December 2025 was searched using electronic databases including PubMed, Scopus, CINAHL, and Google Scholar. Key search terms included "menopause," "resilience," "coping," "psychosocial intervention," "cognitive behavioral therapy," "mindfulness," and "quality of life." Selected studies were organized and analyzed thematically to identify patterns related to intervention types, duration, delivery modes, and outcomes. Results: The review indicates that resilience-based interventions--including cognitive behavioral therapy, mindfulness-based practices, coping skills training, and psychoeducational programs--are associated with improvements in quality of life and psychological wellbeing. These interventions contribute to reduced anxiety, depressive symptoms, and perceived stress, while enhancing adaptive coping and emotional regulation. Evidence suggests that resilience functions as a protective psychological factor that moderates the impact of menopausal stressors. Conclusion: Resilience-based interventions represent effective and feasible non-pharmacological strategies for promoting holistic wellbeing among women undergoing menopausal transition. Integrating structured resilience-focused programs into community and primary healthcare settings may enhance menopause care and support long-term psychological health.

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Menopausal transition; resilience; quality of life; psychological wellbeing; narrative review; psychosocial interventions.

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Everyone involved in education will acknowledge that the use of Information Communication Technology has ushered in a revolution in the field of education. The use of ICT in various aspects of education, such as curriculum development, teaching-learning processes, evaluation, educational administration and management, has made educational activities simpler, more effective and more precise. As a result, the use of ICT is steadily increasing. However, all of this represents the supportive role of ICT in educational activities. So this ICT program is very successful in our school. The purpose of the study was to investigate the attitude towards ICT of secondary schools teachers under West Bengal Board of Secondary Education in West Bengal. Data was collected from 115 secondary schools teachers. The tools used to collect data were 'Teacher's Attitude towards ICT scale' (reliability = 0.753). After analysing the data, it was found that the teachers of secondary schools had almost positive attitude towards ICT.

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Information and Communication Technology, Teachers.

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The study seeks to investigate the correlation between Emotional Intelligence (EI)and Leadership effectiveness among Persons With Disability (PWD) at a workplace. The research used a quantitative, descriptive and analytical approach with data gathered from a sample of 384 PWD workers across many firms using standardised questionnaires on a five point Likert scale scale.The findings demonstrate that Emotional Intelligence has an inextricable relationship with Leadership effectiveness, leadership competenance and peer acceptance among PWD workers and may further augment workplace inclusion as well as effectiveness.

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Emotional Intelligence , Leadership Effectiveness ,Leadership Competance ,Persons with Disability, Peer acceptance, workplace inclusion.

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Traditional fermented foods have been consumed for centuries and are recognized as natural reservoirs of beneficial microorganisms. In recent years, research attention has shifted from conventional probiotics to next-generation probiotics, which include newly identified and functionally characterized microbial strains with targeted health benefits. This review explores the potential of traditional fermented foods such as dahi, kanji, idli, and ugba as sources of next-generation probiotics and evaluates their role in managing metabolic and immune-related disorders. A structured literature search was conducted using databases including PubMed, Google Scholar, and ScienceDirect, focusing on studies published between 2018 and 2025. Evidence from in vitro, animal, and human studies indicates that several indigenous microbial strains exhibit anti-inflammatory properties, modulation of gut microbiota, and improvement in metabolic parameters such as glucose tolerance and lipid metabolism. Compared to conventional probiotics, next-generation probiotics demonstrate strain-specific functionality and enhanced therapeutic potential. However, challenges related to safety assessment, regulatory approval, and clinical validation remain significant. This review highlights current advancements, identifies research gaps, and emphasizes the need for well-designed clinical trials to translate traditional food-derived probiotics into precision health applications.

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Next-generation probiotics, Fermented foods, Gut microbiome, Metabolic disorders, Precision nutrition

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The rapid depletion of conventional fossil fuels and the increasing concern over exhaust emissions have motivated researchers to investigate advanced fuel additives for improving diesel engine performance. In the present study, an experimental investigation was carried out on a four-stroke compression ignition (CI) diesel engine using graphene nanoparticles as a fuel additive in different proportions. Graphene nanoparticles were dispersed in conventional diesel fuel at various concentrations using suitable mixing techniques to ensure stable suspension. The prepared nano-fuel blends were tested in a single-cylinder four-stroke diesel engine under varying load conditions. The performance parameters such as brake thermal efficiency (BTE), brake specific fuel consumption (BSFC), and exhaust gas temperature (EGT) were evaluated to determine the influence of graphene nanoparticles on engine performance.

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Diesel blending, Alternative fuels, Engine performance, Exhaust emissions, Combustion characteristics, Renewable energy.

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The present study Viz., Effectiveness of Blended Learning Strategy on the achievement in Environmental Education among B.Ed trainees is an attempt to study the significant differences in Pre-test scores among the Traditional learning group, E- learning group and Blended learning group, to find out if there are any significant differences in Post-test scores among the Traditional learning group, E- learning group and Blended learning group, to find out if there are any significant differences between Pre-test and Post-test scores of Traditional learning group, E-learning group and Blended learning group, to find out if there are any significant differences in Percentage gain ratio scores among the Traditional learning group, E- learning group and Blended learning group. Mean, Standard Deviation and't' test were calculated to test the hypotheses. The study reveals that there are no significant differences in Pre-test scores among the Traditional learning group, E- learning group and Blended learning group, there are significant differences in Post-test scores among the Traditional learning group, E- learning group and Blended learning group, there are significant differences between Pre-test and Post-test scores of Traditional learning group, E-learning group and Blended learning group and there are significant differences in Percentage gain ratio scores among the Traditional learning group, E- learning group and Blended learning group.

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Blended learning group, E- learning group, and Traditional learning group

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Modern financial applications require highly scalable backend architectures capable of processing real-time market data, handling high-frequency user interactions, and ensuring data consistency across multiple systems. Traditional backend systems often struggle with performance bottlenecks, delayed updates, and inefficient handling of concurrent requests, especially in financial domains where real-time accuracy is critical.

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Portfolio Manager, Real-time, Fintech

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