International Journal of Convergent Research
The International Journal of Convergent Research is a multidisciplinary, peer-reviewed, open-access and refereed journal dedicated to advancing the frontiers of research through the integration of diverse fields of study. International Journal of Convergent Research aims to foster innovation and collaboration by publishing high-quality research that bridges the gaps between traditional disciplines, promoting convergent approaches to address complex global challenges. With a commitment to excellence, it provides a platform for researchers, scholars, and practitioners to share their findings, insights, and advancements in a wide array of subjects.
Young Women as Peer Mediators and Understanding the Skills and Capacities Needed for Effective Peer Mediation
The present study provides the dynamics of peer mediation programs, with particular emphasis on participants' prior experience and comfort levels with conflict resolution. Utilizing quantitative analysis, the research emphasizing participation patterns, preferred conflict resolution methods, and perceptions regarding the effectiveness of peer mediation. The study further analyzes perceptions of peer mediation's efficacy, revealing an optimistic outlook among participants, although skepticism persists. This paper advances the understanding of peer mediation's influence on conflict resolution, underscoring the importance of gender-inclusive approaches and the necessity for targeted training to improve effectiveness and engagement. Future research directions are outlined, emphasizing the exploration of mediation outcomes and the long-term impacts on participants and their communities.
Copyright (c) 2026 Nrityanjali Sarmah, Nibedita Paul https://creativecommons.org/licenses/by/4.0
Towards Transparent Fake News Detection Systems Using Large Language Models
The rapid spread of fake news across digital platforms poses growing risks to public health, electoral integrity, and trust in institutions. Classical machine-learning and deep-learning detectors rely on handcrafted features or large labelled datasets and generalize poorly to unfamiliar topics and evolving manipulation tactics. Transformer-based large language models (LLMs) such as BERT, GPT, and RoBERTa markedly improve detection through contextual understanding and transfer learning, yet their opacity, heavy computational cost, susceptibility to bias, and vulnerability to adversarial attacks hinder trustworthy deployment. Although several surveys examine LLM-based detection, the theme of transparency remains underexplored. This paper reviews LLM-based fake news detection through the lens of transparency. Specifically, it (i) traces the evolution from classical models to transformer-based LLMs; (ii) proposes a transparency framework spanning interpretability, explanation generation, confidence calibration, bias auditing, accountability, and human oversight; (iii) annotates an end-to-end detection pipeline to indicate where each transparency mechanism can be applied; and (iv) synthesizes recent explainable and trustworthy approaches, mapping them to these dimensions. The review finds that LLMs deliver clear accuracy gains over earlier methods, but that transparency, fairness, and robustness are the decisive obstacles to real-world adoption. It concludes with a research agenda directed at auditable and socially responsible detection systems.
Copyright (c) 2026 Usha Rani, Kavita Mittal https://creativecommons.org/licenses/by/4.0
Does Money Change the "Why" of Study? Economic Disparity and the Spectrum of Extrinsic Academic Drive
Economic disparity is frequently analyzed as an obstacle to participation and persistence in education; however, less attention has been directed toward understanding how economic conditions influence students’ motivations for pursuing higher education. This study investigates whether financial factors alter the underlying reasons for study by examining the relationship between Standard of Living/Economy, academic motivation, and student retention. Drawing upon Self- Determination Theory, the research assesses whether economic conditions serve as predictors of academic motivation and whether motivation subsequently explains retention outcomes. Data from a sample of 1, 059 students were scrutinized using Structural Equation Modeling. Five distinct models were evaluated, including a baseline motivation spectrum model, a career- purpose mediation model, models comparing motivation spectrums, and a robustness model based on scoring metrics. The final, accepted latent SEM was identified as the Economic Disparity–Career- Purpose Motivation–Academic Retention Mediation Model. This model demonstrated an excellent fit, with CFI = 0. 990, TLI = 0. 987, RMSEA = 0. 051, and SRMR = 0. 044. The Standard of Living/Economy significantly predicted Career- Purpose Motivation (β = 0. 284, p <. .001), which in turn strongly predicted Academic Retention (β = 0. 592, p <. .001). Additionally, the direct effect of Standard of Living/Economy on Academic Retention remained significant (β = 0. 254, p <. .001), thus indicating partial mediation. The robustness model based on scoring further corroborated the primary interpretation, with Identified Extrinsic Motivation exhibiting the most potent pathway to retention. These findings suggest that economic disparity not only influences the likelihood of students remaining in higher education but also impacts their underlying reasons for persistence. Students are more inclined to continue their studies when they perceive education as personally meaningful for career development, employability, professional competence, and future socio- economic mobility.
Copyright (c) 2026 Thomson Thomas, Selva Dass, Baby Niviya Feston https://creativecommons.org/licenses/by/4.0
Modelling the Determinants of Access to Finance and Entrepreneurial Intention
This study examines the challenges faced by young entrepreneurs (aged 17–22) in accessing seed funding in India, with a particular focus on the role of government support, financial readiness, and structural constraints. It aims to evaluate whether existing policy interventions effectively improve access to finance and reduce funding barriers for this demographic. The study adopts a quantitative research design using primary data collected through a structured questionnaire administered via snowball sampling. Data from young entrepreneurs in Gurgaon, India were analyzed using Structural Equation Modeling (SEM) to examine the relationships between government support, entrepreneurial ability, financial readiness, access to finance, funding barriers, and entrepreneurial intention. The results indicate that young entrepreneurs face significant diffi-culties in accessing seed funding from formal financial institutions. Government support and entrepreneurial ability positively influence access to finance, while financial readiness significantly reduces perceived funding barriers. Access to finance has a strong positive effect on entrepreneurial intention, whereas funding barriers negatively impact entrepreneurial intention. These findings highlight that both institutional support and individual preparedness play a critical role in shaping entrepreneurial outcomes. The study is limited by its reliance on non-probability sampling and self-reported data, which may affect generalizability. Future research may incorporate longitudinal designs and comparative analysis across regions or age groups. The findings suggest that policymakers should en-hance awareness and accessibility of government schemes, while financial insti-tutions should adopt alternative credit assessment mechanisms to support young entrepreneurs. Improving financial readiness through education and training can further reduce funding barriers. Improving access to finance for young entrepreneurs can promote innovation, reduce youth unemployment, and contribute to inclusive eco-nomic development. This study contributes to the literature by focusing specif-ically on young entrepreneurs, an underexplored demographic, and by integrating government support, financial readiness, and behavioral factors into a unified em-pirical framework using SEM.
Copyright (c) 2026 Rituj Khari, Surbhi Sharma, Sanjay Boora, Amar Wadhwa, Swati Shrivastava https://creativecommons.org/licenses/by/4.0
Today, clothing is purchased more readily, discarded more rapidly, and produced on a scale that would have been inconceivable three decades ago. Nevertheless, consumers who drive this pattern often express genuine concern about the environmental costs. This coexistence of awareness and continued participation constitutes the contradiction that this paper aims to examine. Drawing upon scholarship from consumer behavior, social psychology, marketing, and sustainability science, the authors develop a conceptual literature review to explore the authentic motivations behind fast-fashion purchasing and, critically, why environmental concerns seldom translate into corresponding changes in purchasing behavior. The outcome is a four-domain framework that delineates psychological motivations, social influence mechanisms, structural market conditions, and sustainability tensions as mutually reinforcing forces. The analysis is grounded in the Indian market- a context that much of the existing literature has historically overlooked. The fundamental argument is clear: the disparity between knowledge and action is not, fundamentally, due to a lack of information. It is a structural condition. Addressing this gap will necessitate more than improved messaging regarding sustainability.
Copyright (c) 2026 Priyanka Chadha Vermani, Himadri S Dey, Sachin Datt https://creativecommons.org/licenses/by/4.0
Price Sensitivity and Social Influence as Dual Moderators of the Attitude- Behaviour Gap in Sustainable Fashion
Despite decades of increasing environmental awareness, sustainable fashion remains responsible for less than 7% of global apparel sales, even as urban consumers' perceptions of sustainable fashion grow more positive. This review investigates the underlying reasons for the persistent gap and, more specifically, explores how Behavior–Context framework and considering price sensitivity and social influence as interacting dual modifiers of the attitude–behavior1966 to 2026 were selected from Scopus, Web of Science, PsycINFO, and Google Scholar, following the PRISMA 2020 guidelines. The quality of the studies was assessed using MMAT Version 2018 (with a median score of 4 out of 5), and an integrative framework combining the Theory of Planned Behaviour, the Theory of Consumption Values, and Norm Activation Theory was employed through framework synthesis. Four key findings emerge: first, that price sensitivity varies according to individual identity, cultural background, and information access, indicating it is not solely a cost barrier; second, that social influence mechanisms such as peer pressure, identity signaling, electronic word-of-mouth (eWOM), and FOMO actively draw consumers toward fast fashion, functioning in both positive and negative directions; third, that much of the current research is based on intention questionnaires rather than actual behavior, likely leading to an overestimation of what is understood; and fourth, that the disparity is most pronounced in Tier 2 urban areas where actual financial constraints conflict with sustainability aspirations. This constitutes the first comprehensive review explicitly differentiating this model from the Attitude–Behavior–Context framework and considering price sensitivity and social influence as interacting dual modifiers of the attitude–behavior gap within urban sustainable fashion.
Copyright (c) 2026 Priyanka Chaudhary, Rajender Kumar Yadav, Himadri S Dey , Sachin Datt https://creativecommons.org/licenses/by/4.0
India’s Journey of Industrial and Agricultural Change
This study critically examines the structural transformation of India’s agriculture and manufacturing sectors from 1960 to 2025, with a focus on three distinct phases: pre-liberalization (1947–1991), post-liberalization (1991–2014), and the contemporary period (post-2014). The primary objective is to analyze sectoral growth trends, employment dynamics, value addition, and urban–rural shifts within the Indian economy. The research employs World Bank time-series data and utilizes trend analysis and regression techniques to evaluate long-term changes across these sectors. The findings suggest that agricultural value addition increased at an average annual rate of approximately 3.04%, whereas the manufacturing sector experienced higher absolute increases in value addition but demonstrated relatively limited employment absorption. The proportion of employment in agriculture declined by approximately 0.79% annually, concomitant with a significant urban population growth, indicative of ongoing structural transformation. Nevertheless, sectoral imbalances continue to exist, particularly concerning productivity and income distribution. The study advances the field by synthesizing sectoral growth, employment trends, and urbanization within an integrated empirical framework, emphasizing the necessity for targeted policy measures to promote inclusive and sustainable economic development in India.
Copyright (c) 2026 Preety Sharma, Anand Kumar, Shikhar Kumar https://creativecommons.org/licenses/by/4.0
From Demonetization to Digital Dominance
India’s digital payments revolution gained unprecedented momentum following the 2016 demonetisation, with the Unified Payments Interface (UPI) emerging as the central pillar of retail digital transactions. Designed as a low-cost, interoperable, and real-time payment system, UPI significantly advanced financial inclusion, reduced transaction frictions, and transformed everyday consumer and merchant payment behaviours. Its rapid diffusion across urban and rural India positioned it as a global benchmark in instant payment systems. However, recent regulatory interventions reveal an emerging paradox in India’s cashless transition. The issuance of Goods and Services Tax (GST) notices to small traders in Karnataka, based on UPI transaction data, has triggered a visible retreat from digital payments toward cash among segments of the informal economy. This development underscores growing tensions between digital transparency and the economic vulnerabilities of small merchants. This paper analyses the evolution of UPI in post-demonetisation India and examines how its adoption has reshaped payment practices across socio-economic groups. It further explores the behavioural responses of merchants and consumers, focusing on fear of compliance burdens, working capital constraints, and perceptions of surveillance. The study evaluates the policy dilemma of balancing revenue enforcement with financial inclusion objectives and argues that the long-term sustainability of UPI depends not only on technological innovation but also on regulatory alignment that safeguards small businesses while enabling gradual formalisation of the economy.
Copyright (c) 2026 Ananya Arora, Avantika Tyagi, Amrita Sasi, Aneesh K A https://creativecommons.org/licenses/by/4.0
Climate change has become one of South Asia's most serious problems. This region has a lot of people living in a small area, is economically vulnerable, and has a lot of low-lying beaches. This study analyzes the changing patterns and future predictions of climate change in South Asia, concentrating on its effects on coastal communities. Floods, cyclones, coastal erosion, and saline intrusion are happening more often and with more force because of rising temperatures, unpredictable monsoon patterns, and faster sea-level rise. These changes severely affect livelihoods depending on agriculture, fisheries, and coastal ecosystems, while also leading to relocation, health hazards, and destruction of vital infrastructure. Using an interdisciplinary approach, the analysis synthesizes modern climate models, regional assessments, and community-level case studies to understand the geographical and socio-economic dimensions of vulnerability. Enhancing resilience requires bolstering early warning systems, climate-resilient infrastructure, ecosystem-based adaptation, and community-led catastrophe risk reduction. The results highlight the critical need for inclusive adaptation methods, investments in climate-smart development, and coordinated regional policies to protect the future of South Asia's coastal inhabitants in the face of escalating climate hazards.
Copyright (c) 2026 Ruchi Dhawan, Kanika Sachdeva, Gunjan A Rana https://creativecommons.org/licenses/by/4.0
AI-Driven Genomic Surveillance Systems for Public Health Governance
Rapid urbanization, climate-driven ecological changes, increased human mobility, and the accelerated evolution of infectious agents underscore the urgent need for next-generation, real-time public health intelligence systems in smart-city environments. Conventional surveillance approaches remain largely reactive, fragmented, and dependent on delayed laboratory reporting, limiting their effectiveness in densely populated urban settings. This paper proposes an AI-driven genomic surveillance system (AIGSS) that integrates IoT-enabled biosensing, distributed genomic sequencing, and predictive artificial intelligence models to support proactive public health monitoring and governance. Using the Issue Identification, Review, Methodology, Analysis, and Discussion (IRMAD) framework as a conceptual system design methodology, we develop a multi-layered surveillance architecture encompassing data acquisition, edge preprocess, AI-based genomic analytics, and governance-oriented decision support. The proposed framework is evaluated through simulation-based analysis and benchmarking against performance trends reported in existing surveillance systems. Results indicate that AI-enabled integration of genomic and IoT data has the potential to substantially reduce outbreak detection latency and improve variant classification performance when compared to traditional approaches. Rather than presenting real-world clinical validation, this study focuses on architectural feasibility, analytical workflow design, and governance implications. Beyond technical performance, the framework emphasizes ethical data governance, transparency, accountability, and equitable access, aligning genomic intelligence with smart-city public health objectives. This work contributes a scalable and policy-aware reference model for the convergence of AI, genomics, and IoT, providing a foundation for future empirical validation and deployment in urban public health surveillance systems.
Copyright (c) 2025 Shanti Singh https://creativecommons.org/licenses/by/4.0
Speech-Driven Information Retrieval Systems: A Review of AI and NLP Techniques
This paper offers a critical review of the progress, issues, and future of speech-driven information retrieval (SDIR). Following ten studies as references, this paper focuses on the use of artificial intelligence (AI) and natural language processing (NLP) in support of speech-based interaction within information retrieval systems (IRSs). Innovative difficulties, including differences in the accents, noise, and the peculiarity of the words, and the contextual and multilingual approach are also mentioned. This paper discusses how current trends in AI, such as transformers like GPT and BERT, restore in-depth features for the enhancement of the speech recognition rate, semantic content analysis, and operational queries in real time. Furthermore, future trends, including multilingual retrieval systems and real-time processing, are examined as significant advancements in improving the SDIR systems’ accessibility and speed. Overcoming these challenges and building on advances in AI, the study aims towards the development of future SDIR systems that offer optimal, easy, and versatile solutions for various uses
Copyright (c) 2026 Hamza Aziz, Sadaf Fatima https://creativecommons.org/licenses/by/4.0
The Impact of Islamic Work Ethics on Employee Motivation in Islamic Banks
Islamic Work Ethics (IWE) has emerged as an essential foundation for ethical behaviour, organizational harmony, and intrinsic motivation in Islamic financial institutions. Rooted in the Qur’an and the Sunnah, these ethics emphasize honesty, justice, accountability, and spiritual fulfillment, forming the moral compass for Islamic banking operations. This study explores how IWE influences employee motivation within Islamic banks by examining its core dimensions—honesty, fairness, teamwork, accountability, and spirituality. Drawing from existing literature and conceptual frameworks, the paper highlights the intrinsic linkage between faith and work motivation, discusses challenges in implementation, and proposes leadership strategies and HR policies to enhance motivation. The findings indicate that adherence to Islamic ethical values fosters moral integrity, loyalty, and organizational commitment, providing a distinctive model for sustainable human resource management in the Islamic banking sector.
Copyright (c) 2026 Fathima Amra Mohamed Hussain, Thuwannaweed Thuwansajihan https://creativecommons.org/licenses/by/4.0
Bridging Cultures: A Comparative Study of Female Agency in African and Indian Women’s Novels
This paper presents a comparative literary analysis of female agency in African and Indian women’s novels, highlighting how women writers from these regions challenge patriarchal structures and reclaim female subjectivity. Drawing on selected works by authors such as Buchi Emecheta, Chimamanda Adichie, Mahasweta Devi, and Kamala Das, the study examines thematic concerns including gender roles, resistance, identity, and the tension between tradition and modernity. The analysis reveals both convergences and divergences in narrative strategies, socio-cultural contexts, and feminist articulations. Using feminist literary theory and postcolonial criticism as frameworks, the research underscores how these authors employ literature not just as artistic expression but as political resistance, offering counter-narratives to dominant patriarchal and colonial discourses. The study concludes that African and Indian women writers serve as cultural agents who not only document but actively shape feminist consciousness in their respective societies.
Copyright (c) 2025 Priyanka Malik, Girish Panth, Saroj Bala https://creativecommons.org/licenses/by/4.0
Green Marketing as a Competitive Strategy in Emerging Economies: A Conceptual Perspective
As countries like India, Brazil, and Indonesia continue to grow economically, they also face rising environmental challenges such as pollution, climate change, and overconsumption of natural resources. At the same time, people in these countries are becoming more aware of environmental issues and are starting to expect more responsible behaviour from businesses. In this changing landscape, green marketing—promoting products and services that are environmentally friendly—is becoming more than just a trend. It’s turning into a key business strategy that helps companies stand out from their competitors. This paper takes a deeper look at how green marketing can be used as a competitive strategy in emerging economies. Rather than treating it as just a way to advertise eco-friendly products, we explore how it can become a core part of a company’s overall strategy. The paper reviews existing studies draws on well-known business theories and proposes a model that shows how factors like government rules, customer expectations, and corporate values can drive green marketing efforts. These efforts, in turn, can lead to better brand reputation, stronger customer loyalty, and access to new market segments. We also discuss some of the challenge’s companies face, such as the high cost of going green and the risk of being accused of “greenwashing”—pretending to be environmentally responsible without real action. In the end, this paper suggests that if done genuinely and thoughtfully, green marketing can offer long-term business advantages while also supporting environmental sustainability.
Copyright (c) 2025 Kalpana, Dr. Himadri S. Dey, Dr. Abdullah H. Ahmadini, Dr. Richa Nangia https://creativecommons.org/licenses/by/4.0
Harnessing the Power of E-HRM: Enhancing Organizational Performance in Delhi-NCR's IT Sector
The integration of electronic human resource management (E-HRM) systems has revolutionized traditional HR practices, particularly in the IT sector, where agility and innovation are critical for success. This study investigates the impact of E-HRM on organizational performance in Delhi-NCR's IT industry, focusing on operational efficiency, employee satisfaction, and strategic HR roles. Data collected from 490 respondents across seven IT firms reveal significant improvements in recruitment cycle times, onboarding processes, and data accuracy, demonstrating E-HRM's potential to streamline HR operations. Employee satisfaction was notably enhanced through the introduction of e-learning tools and self-service portals, which fostered autonomy and engagement. However, challenges such as resistance to change, data security concerns, and high implementation costs hindered the full realization of E-HRM's benefits. The study underscores the strategic role of E-HRM in aligning HR functions with organizational goals and highlights the importance of robust leadership support, effective change management, and continuous employee training to maximize its potential. By addressing implementation challenges and leveraging digital innovations, organizations can unlock the transformative capabilities of E-HRM, driving long-term success in a dynamic business environment.
Copyright (c) 2025 Debabrata Saha, Nitish Kumar Minz https://creativecommons.org/licenses/by/4.0
Interplay of Academia, Market and Human Involvement: A Holistic Analysis of Puppetry in India through the Triple Helix Model
Puppetry, deeply rooted in Indian culture, transcends temporal boundaries to embody a cherished cultural heritage and dynamic artistic form. Scholars and practitioners have long celebrated the resilience and adaptability of puppetry, which continues to evolve in response to changing socio-cultural contexts. This study explores the interplay of academia, market dynamics, and human involvement in puppetry in India, shedding light on its enduring relevance and transformative potential within Indian society and beyond. Through the lens of the Triple Helix Model, this research delves into the multifaceted landscape of puppetry in India, examining its intersection with tradition, market dynamics, and human involvement. Key findings emerge by analyzing academic literature, government initiatives, case studies, and stakeholder perspectives regarding cultural heritage, government support, market dynamics, and human involvement in puppetry. The study highlights the complex interplay of supply and demand forces, the importance of collaborative efforts, and the challenges and opportunities puppeteers face in navigating a rapidly changing socio-cultural landscape. Ultimately, this research provides a holistic understanding of puppetry in India, offering insights for future research, policy interventions, and community engagement initiatives to support the sustainability and growth of this ancient art form.
Copyright (c) 2025 Anshika Prakash, Dr. Monika Yadav, Nitish Kumar Minz, Maryam Irfan https://creativecommons.org/licenses/by/4.0
A Review: Case Studies Involving Glass Evidences
This paper reviews forensic case studies highlighting the pivotal role of glass evidence in criminal investigations. Focusing on five diverse cases, it explores how meticulous forensic analysis of glass can uncover crucial details, such as the direction of impact, the sequence of events, and potential sources of contact. The paper outlines the primary methods used in forensic glass analysis, including refractive index measurement, elemental analysis and density gradient techniques. Each method’s role in establishing connections or exclusions is evaluated in the context of the cases presented. This study highlights the forensic value of glass evidence in linking suspects to crime scenes and reinforces the need for precision to avoid misinterpretation and investigative delays.
Copyright (c) 2025 Dr. Komal Yadav, Agastya Arsh, Bibaswan Maitra, Ayushi Sinha, Sristy Agarwal, Vanshika Wali https://creativecommons.org/licenses/by/4.0
Structural Exclusion and Social Protection: A Critical Examination of India’s Urban Informal Workforce
The urban informal sector in India maintains a crucial role in facilitating city life involving the formal sector, household jobs, development projects and sustainable living for the urban poor. Approximately 80% of the urban workforce is employed informally, contributing 45% to the GDP. However, these contributions remain unrecognised by legal and social security frameworks. Being unrecorded and excluded from policy frameworks for social protection exposes them to insecurity and exploitation, depriving them of well-deserved options for sustainable livelihood. To recognise and uplift the sector from vulnerabilities, the government introduced the E-Shram Portal, PM-SVANidhi and the Street Vendors Act to ensure financial inclusion and legal visibility. The policies face bureaucratic challenges, exposed to barriers in formalisation deterring small businesses from entering the formal sector and low awareness among the workers, reducing the impact of existing policies. For a country as dynamic and varied as India, a comprehensive and centralised set of policies for the informal urban workers is required to uplift their status while maintaining the essence of their nature of work.
Copyright (c) 2025 Aneesh K A, Anoushka Saxena, Siddhi Goyal https://creativecommons.org/licenses/by/4.0
AI-Driven IoT Systems for Sustainable Development
This paper examines how Artificial Intelligence (AI) and the Internet of Things (IoT) are reshaping urban governance and everyday life in Delhi—a flagship city under India’s Smart Cities Mission. Moving beyond a purely technical analysis, the study adopts an urban sociological lens to understand the sociopolitical implications of data-driven governance. It conceptualizes AI-IoT systems as socio-technical infrastructures that reconfigure how public services are delivered, how space is experienced, and how citizens interact with the state. Through a mixed-method approach—combining a critical literature review, technical analysis, and a case study of Delhi—the paper proposes a layered governance framework that accounts for both technological efficiency and social embeddedness. Empirical insights from traffic, pollution, and waste management systems reveal that smart technologies, while enabling operational gains, often reproduce existing inequalities in digital visibility, spatial access, and civic participation. The framework underscores the need for participatory, inclusive, and ethically grounded smart governance. It highlights how AI-IoT systems are not neutral tools but are embedded in political decisions, bureaucratic processes, and contested urban imaginaries. The paper concludes by proposing a roadmap for integrating urban sociological thinking into digital policy design, ensuring that the smart city remains not only technologically advanced but also socially just.
Copyright (c) 2025 Maryam Irfan, Heena Yusuf, Shivani Kain https://creativecommons.org/licenses/by/4.0
Barriers and Facilitators to Inclusive Participation in Co-Curricular Activities: A Case Study of Undergraduate Students
This study is dedicated to finding a way to make co-curriculars inclusive by gaining insight into what makes voluntary activities which are extremely helpful in the holistic development of personality, accessible to some students and not others. Using a questionnaire,102 undergrad students were surveyed to see whether the chosen variables: income, disability, familial caretaking and a different ethnic background are related to student participation in co-curricular activities. The data collected was analyzed and indicated that the chosen factors of income and ethnic background have a significant relationship with one's likelihood of participating in co-curricular activities. A section proposes brief solutions based on the results and previous strategies that have been employed. This chapter further discusses the results and proposes solutions based on the findings.
Copyright (c) 2024 Bhumika Sharma https://creativecommons.org/licenses/by/4.0
Problems Faced by the Silk Handloom Weavers in Azamgarh and Varanasi Districts of Uttar Pradesh
Handloom weaving stands as one of the primary economic activities in India, second only to agriculture. This industry contributes approximately 15% to the nation's total fabric production and is responsible for over 95% of the global output of hand-woven cloth. According to the 4th All India Handloom Census (2019-20), the sector employs around 35.23 lakh workers, including over 26 lakh weavers and more than 8 lakh allied workers, operating across 28.20 lakh looms. This study examines the problem faced by the silk handloom weavers in the Azamgarh and Varanasi districts of Uttar Pradesh, based on primary data through a structured interview schedule. The data was evaluated using a simple percentage and presented by tables. The research identifies several key problems impacting the handloom sector's productivity and sustainability. Among these, the high cost, poor quality, and scarcity of raw materials are significant issues. Marketing difficulties are prevalent, with 75.3% of weavers reporting challenges such as competition from power looms, inadequate promotional activities, and restricted market access due to the dominance of master weavers and cooperative heads. Financial instability is another critical concern, affecting 80% of the weavers, who struggle with poor access to funding, high-interest loans, and increasing debt. Design-related problems are also noted, with 46.7% of weavers expressing the need for greater creativity and innovation to remain competitive. Moreover, 89.4% of weavers report a lack of access to training and workshops, emphasizing the need for skill development to meet modern market demands. Technological challenges are also significant, with 82.7% of weavers lacking access to modern tools and equipment, which hampers their efficiency and output quality. Additionally, awareness of government schemes is alarmingly low, with only 27.9% of weavers informed about available support, revealing a critical communication gap. To address these multifaceted problems, the study recommends several policy interventions. The establishment of a Raw Material Bank is proposed to ensure the availability of essential inputs for handloom weaving. The introduction of a Yarn Passbook system is suggested to subsidize yarn costs for eligible weavers. The government is also urged to provide interest-free loans or soft loans with flexible repayment terms, tailored to the specific needs and performance of the weavers. A collaborative platform that brings together silk handloom weavers and fashion designers is recommended to foster design innovation and enhance market competitiveness. Additionally, the modernization of looms and equipment, particularly those that reduce physical strain and increase productivity, is essential for the sector's sustainability. These policy recommendations aim to improve the socio-economic conditions of the weavers, strengthen their market position, and ensure the long-term viability of the handloom industry in these regions.
Copyright (c) 2024 Parvez Ahmed, Zeba Sheereen, Aneesur Rahman https://creativecommons.org/licenses/by/4.0
A Comparative Study on Search Engine Optimization and Search Engine Marketing: Optimizing Strategies in Business Growth
This study examines the comparative effectiveness of Search Engine Optimization (SEO) and Search Engine Marketing (SEM) in driving business growth. By analyzing various strategies, metrics, and outcomes associated with both SEO and SEM, this paper provides insights into how businesses can optimize their online presence for sustained growth. Using a combination of quantitative data, qualitative case studies, and industry-specific analysis, the paper offers a comprehensive comparison of these two key digital marketing strategies. The findings suggest that while both SEO and SEM are critical for online visibility, their effectiveness varies depending on business objectives, industry context, and target audience. Additionally, the study proposes a hybrid approach, combining the strengths of both strategies to maximize business growth.
Copyright (c) 2024 Dr. Richa Arora , Dr. Parul Tyagi https://creativecommons.org/licenses/by/4.0
Leveraging Artificial Intelligence for Personalized Promotion Strategies on Social Media Platforms: Opportunities, Challenges, and Ethical Implications
AI has changed marketing, especially on social media, by letting folks do personalised ads. With machine learning and natural language, marketers can look at tons of data to make custom ads. This way, there are lots of good things like better engagement from customers and more people buying stuff. But it also comes with big challenges like unfair bias in algorithms and problems with keeping data private. The ethics of using AI for targeted ads on social media are super important. Being clear about what's happening, making data safe, and trying to be fairer by using all kinds of different data is key. People in charge have gotta make rules to make sure AI in marketing is fair and not unfair to anyone. Schools can help out with this by pushing for research that looks into AI, marketing, being fair, and how people shop. To do a good job with these fancy personalized ads driven by AI, marketers need to learn about AI, teach customers about it, and come up with rules that keep everyone safe. Keeping the balance between new cool stuff and looking out for people is super important. Gotta always check and change what's right to keep up with new problems and tech changes. This bit talks about how important it is to get this balance right and always be ready to deal with whatever comes up in the world of AI driven marketing.
Copyright (c) 2024 Shruti Chandra https://creativecommons.org/licenses/by/4.0
Data-Driven Entrepreneurship: Exploring People Analytics in Delhi SME Startups
Purpose: This study aims to investigate the implementation of HR policies and the utilization of people analytics in SME startups based in Delhi, through a content analysis of Glassdoor reviews. The study seeks to identify the major issues employees face in SME startups, examine the alignment between company values and HR systems, compare the performance of different startups based on employee reviews, and provide suggestions for incorporating and improving people analytics practices. Methodology: This research conducts a content analysis of Glassdoor reviews for 10 SME startups in Delhi: Niro Street, Quick Drycleaning, Bech De Khareef Le, Buyume, Tradeboox, Bookkeeper, Acropolis Infotech, Gadget Wood, Get Me a Shop, Transjovan Capital. The content analysis involves the identification of key themes and patterns related to HR policies, company values, management practices, and the implementation of people analytics. Insights obtained from the analysis are used to address the research goals. Findings: The content analysis reveals insights into the major issues faced by employees in Delhi SME startups, the alignment between company values and HR practices, and the perceived effectiveness of people analytics implementation. It provides comparative insights into the performance of the 10 startups based on employee reviews, highlighting areas of strength and areas for improvement. Practical Implications: The findings of this study offer practical implications for HR practitioners and startup leaders in Delhi. By understanding the challenges and opportunities identified through content analysis, startups can make informed decisions to improve employee satisfaction, align HR practices with organizational values, and enhance the implementation of people analytics for strategic decision-making. Originality and Value: This research contributes to the understanding of people analytics in Delhi's SME startup ecosystem by leveraging employee-generated data from Glassdoor. It provides valuable insights into the HR practices, company values, and implementation of people analytics in startups, offering actionable recommendations for fostering a culture of data-driven entrepreneurship in Delhi.
Copyright (c) 2024 Hitika Kalra https://creativecommons.org/licenses/by/4.0
Relationship between Precipitation and Cyclones in the Bay of Bengal India during 2015-2019: Using Tropical Rainfall Measurement Mission (TRMM)
The Bay of Bengal (BoB) is a cyclone hotspot as it's warmer than the Arabian Sea. The North Indian Ocean, according to Neumann, was home to 7% of all worldwide Tropical Cyclones (TCs) (NIO). TCS was relatively common in the Bay of Bengal (BoB), accounting for 5% of all worldwide TCs. May, October, and November were the months with the greatest TC activity, while January, April, and July had the weakest TC activity. To evaluate the distribution of TC rainfall throughout an inter-annual and monthly timescale, rainfall data from the Tropical Rainfall Measurement Mission (TRMM) were employed (i.e., how much TC contributed to total rainfall). Using TC best track data from the Indian Meteorological Department, this article initially examined TC activity in this region from 2015 to 2019 (January–December) (IMD). The present study describes the role of cyclones in seasonal rainfall over the period from 2015 to 2019. The precipitation does not depend upon any stage of cyclones, it sometimes peaks higher value at the D stage, sometimes also at its mature stage. The study also concludes that the maximum rainfall does not have to be proportional to the intensity. The rainfall areas of a TC are not proportional to its intensity; Therefore, TC categories with higher intensities do not generate excessive rainfall.
Copyright (c) 2024 Anupama Sahoo, Ghulam G. Zahid, Nepal Singh, Usman Aarif Chaudhary, Mohammad Zahbi, Dr. Ajhar Hussain https://creativecommons.org/licenses/by/4.0
Documentation of Dry Preserved Mounted Mammalian Collection of The Zoology Museum
The museums have a long history dating back to the 3rd century B.C. when the first known museum was opened at the University of Alexandria in Egypt. As we know, museums are an institution that collects, document, preserve, exhibit and interpret material evidence and associated information for public benefit. The value of a museum's collection depends on the amount of information it possesses about each item. Even a valuable object loses much of its worth if details like its origin, purpose, and unique characteristics are unknown. This holds for art objects, where artist names, historical context, and associations are equally important. Failing to provide such basic information is a dereliction of a museum's primary duty, and it should maintain records in registers rather than relying on staff memory, which can fade with time and increased collections. These records also serve legal purposes, addressing potential disputes about objects even decades after their acquisition into the collection. The museum movement in India is to be traced to the Asiatic Society of Bengal founded by the brilliant scholar Sir William Jone in 1784. The greatest motion to the development of museums in the country was given at the time of Lord Curzon. Calcutta is the first full-fledged university museum in the name of Sir Ashutosh Mukherji to come into existence. The Department of Zoology was established as a constituent section of the MAO College in 1909. It was the individual and untiring efforts of Prof. M.B. Mirza in 1935, which resulted in the creation of a museum on department premises that houses more than 1000 species ranging from porifera to mammals. The focus of the work is to develop a well-designed documentation system for the dry-preserved mounted mammalian collection displayed in the Zoology Museum, Faculty of Life Science, A.M.U. Aligarh, along with what preventive measures should be taken by collecting maximum information as far as possible from every possible source. Later, this well-developed documentation system will be followed by a well-designed automated system by which an online database will be developed and made available via the Zoology Department’s official website to provide valuable information worldwide about its valuable, rare and diverse collection.
Copyright (c) 2024 Shaista Waheed, Shakeel Ahmad, Abduraheem K https://creativecommons.org/licenses/by/4.0
Federated Learning: A Potentially Effective Method for Improving the Efficiency and Privacy of Machine Learning
A new AI paradigm called federated learning (FL) decentralizes data and enhances privacy by delivering education straight to the user's device. However, additional privacy concerns arose during the exchange and training of server and client parameters. Integrating FL privacy solutions at the edge level can result in higher computational and communication costs, which can compromise learning performance metrics and data value. To promote the best trade-offs among FL privateness and different performance-associated application needs, including precision, privation, convergency, value, computational protection and connection, this study offers a thorough research overview of key techniques and metrics. Reaching stability among privateness and different standards of factual international Federated Learning utilization is the focus of this paper, which also explores quantitative methodologies for evaluating privacy in FL. To mitigate server-related risks, decentralized federated learning removes the server from the network and uses blockchain technology to compensate for its loss. However, this benefit comes at the expense of exposing the system to additional privacy risks. An extensive safety study is required in this new paradigm. This survey examines various security mechanisms and addresses potential adversaries and dangers in decentralized federated learning. The verifiability and trustworthiness of decentralized federated learning are also considered.
Copyright (c) 2024 Nishant Jakhar, Sajjan Singh https://creativecommons.org/licenses/by/4.0
Critical Insights into Context-Aware Systems: A Literature Review
Recently, automobile networks, health monitoring, and industrial alarm systems have used context-aware systems more. These systems make sense of environmental cues and simulate productivity gains using fuzzy logic and machine learning. They can verify machine integration into the human body and perform logical sensor data analysis to improve healthcare monitoring. They can also help to create systems that adapt to changing conditions, such as emergency vehicle communication networks. Regardless of scale, these adaptive systems have varying modularity to improve results in a wide range of application areas. They enable secure, efficient, and intelligent interaction across domains. This study investigated 20 context-aware system studies. It covers strategic shifts, challenges, and dynamics in this field in detail. Business analytics, the Internet of Things, remote care, human capital, recommendation systems, vehicle networks, human-robot interactions, smart product service systems, and successful recruitment are covered. Consider the entire synthesis to determine the value of contextuality and system use in various sectors. Fuzzy logic, machine learning, and architectural frameworks help explain context-aware computing formation and ongoing advances.
Copyright (c) 2024 Hamza Aziz, Shahnwaz Afza https://creativecommons.org/licenses/by/4.0
Artificial Intelligence (AI) in Human Resource Management (HRM): A Bibliometric Research
Purpose: The purpose of this study is to conduct a bibliometric analysis to explore the scholarly literature on the integration of Artificial Intelligence (AI) in Human Resource Management (HRM), by focusing on identifying trends, key contributors, research themes, and emerging areas of interest. Methodology/Approach: The research employs systematic bibliometric analysis, utilizing academic databases such as Scopus to collect relevant literature. Keywords including "AI," "Artificial Intelligence," "HRM," and "Human Resource Management" were used to retrieve documents. Bibliometric software such as bibliophily is utilized to visualize co-authorship networks, citation patterns, keyword co-occurrence, and publication trends. Findings: The analysis shows how AI applications in HRM have developed over time, moving from theoretical explorations to empirical studies and the incorporation of cutting-edge AI technologies. Important researchers and research clusters are highlighted, along with field-wide collaborative networks and key contributors. Personalized learning, employee performance prediction, AI-based hiring, and ethical issues are among the often-studied topics. Emerging fields include cross-cultural research, ethical frameworks for AI deployment, and the integration of AI with emerging technologies. Originality: By providing an organized bibliometric overview of the academic environment on AI in HRM and offering insights into trends, important contributors, and developing research areas, this study adds to the body of current literature. The methodical approach used in this study guides future research and practice while also improving our grasp of the revolutionary potential of AI in HRM practices.
Copyright (c) 2024 Wamika Sehgal, Dr. Thenmozhi M https://creativecommons.org/licenses/by/4.0
Enhanced AML Compliance and Predictive Risk Management: Generative AI Empowering Synthetic Blockchain Transaction Data and Financial Crisis Scenarios
The importance of adhering to AML (Anti Money Laundering) regulations in the FinTech sector is constantly evolving, and shifting towards risk management. Our study delves into utilizing AI technology to generate blockchain transaction data and simulate financial crisis scenarios for improved AML compliance and risk management strategies. We leveraged cutting-edge generative models to create transaction datasets that mirror real-world blockchain data. Additionally, we implemented AI-powered simulations of crises to stress test. Refine predictive models. Our findings indicate that Generative AI can significantly enhance AML frameworks by providing quality synthetic data for training and validation purposes. It also serves as a tool for assessing the resilience of systems, identifying vulnerabilities and offering valuable insights into potential risks. This research showcases the potential of using AI to fortify institutions against money laundering activities and bolster their ability to foresee and address risks, in today's intricate financial environment.
Copyright (c) 2024 Tanay Saxena, Shweta Sanjay Thakur https://creativecommons.org/licenses/by/4.0
Revolutionizing Aerospace with Artificial Intelligence: A Review
In recent times, the utilization of artificial intelligence (AI) has facilitated the creation of numerous applications across nearly every field of human knowledge. Though it is still relatively new in aviation, products are already enhancing the abilities and skills of those in charge of it. This study examines the scientific literature regarding the benefits, drawbacks, and factors to consider. in relation to the use of AI techniques in aviation operations, such as building, navigation, and defense against cyberattacks, as well as climate changes that could have an impact on the navigation system. AI Every day, advancements bring with them new benefits and difficulties for navigation. However, on the one hand, these strategies facilitate independent flight until complete autonomy is attained. However, they also include special vulnerabilities and worries about the growing use of digital and computerized communication channels, which are open to attacks by nefarious people or groups.
Copyright (c) 2024 International Journal of Convergent Research https://creativecommons.org/licenses/by/4.0
Anticoagulant Therapy for Alzheimer's Disease: A Review of Recent Research
Alzheimer's disease (AD) is a neurodegenerative, vascular, and hemostatic disease characterized by cerebral-amyloid angiopathy (CAA). Thrombin, fibrin, and amyloid-(Aβ) toxic proteins are important initiators of vascular anomalies and resulting neurodegeneration in AD, which can be managed with anticoagulants, as this article reviews. Recent research suggests that the pathophysiology of AD is influenced by risk factors for cardiovascular disease, dysregulated intrinsic coagulation, and cerebrovascular damage. Anticoagulants may be a viable treatment option for AD patients with vascular condition cognitive impairment. This article provides a thorough analysis of recent research, demonstrating that anticoagulant-particularly those of the direct oral anticoagulants (DOAC) type-may be able to combat the vascular-driven progression of AD-related neuroinflammation and CAA, given complete cerebral perfusion and a decreased milieu that accumulates fibrin and Aβ. When administered early, either therapeutically or prophylactically, DOAC may be more effectively utilized to reduce inflammation and vascular dysfunction due to pharmacological reasons. Preclinical research in AD animal models will be the first step in determining whether this treatment strategy can actually effectively combat the cerebral-vascular dysfunction that are a component of AD etiology.
Copyright (c) 2025 Vinayaka Madivalar, Shubham Teli, Shivaraj Hiremath, Vani Chatter, Gouthamachari Shrinivas, Anjana Kulkarni, Bhushan Khombare, Mallappa Shalavadi https://creativecommons.org/licenses/by/4.0