International Journal of LAW, Arts and Humanities
A COMPARATIVE STUDY OF TRADITIONAL AND DIGITAL MARKETING STRATEGIES
The ever changing environment in technology and wide application of internet has tremendously changed the marketing environment and marketing has taken on a new dimension of being a viable alternative to the traditional way of marketing with the advent of digital marketing. The present research article alludes to a comparative study of the conventional and the digital marketing methods in regard to their efficacy, reach and cost effectiveness and their contribution to the behavioral change of the consumers. Digital marketing incorporates the services of online markets such as social networks, search engines, email and websites to engage target continuous and interactive audiences as compared to traditional digital marketing, which typically involves print, television, radio and outdoor advertising and is mainly aimed at the creation of brand awareness and reaching mass audiences. Primary and secondary data is used in conducting the study. Structured questionnaires are used as a way of collecting primary data to get to know consumer preference, perceptions and responsiveness to the two marketing strategies. Tertiary data will be obtained through the use of the academic journals, industry report and verified internet sources to provide a theoretical background. The effectiveness of the conventional and digital advertising techniques are discussed through the assistance of statistical analysis such as percentage analysis, mean, and comparative analysis. The findings reveal that digital marketing is more advantageous because it is cost effective, real time, they are personalized and the outcomes are measurable. It enables firms to access specific and targeted groups of consumers and target them based on the data analytics. Conversely, conventional promotions proved to be better when it comes to creating brand trust and reaching out audiences who have minimum or no access to the internet and especially rural population. The other observation made in the study is that, despite the rapid emergence of digital marketing being the dominant aspect, in integrated marketing strategies, traditional marketing up to date, is still pertinent. The study finds out that a blend of both early and modern techniques of marketing is the best strategy a company can adopt when it seeks to have maximum exposure and attention. Every business is supposed to take the advantages of the two approaches to formulate an inclusive marketing campaign to meet the emerging dynamics of consumers and technology. The study has a relevance to the marketers, business and policy makers on the dynamic ways of marketing strategies in the digital age.
Traditional Marketing, Digital Marketing, Consumer Behavior, Marketing Strategies, Online Advertising, Brand Awareness, Integrated Marketing
Copyright (c) 2026 https://creativecommons.org/licenses/by-nc-nd/4.0
URBAN ALIENATION AND THE SEARCH FOR MEANING IN PATRICIA LOCKWOOD’S NO ONE IS TALKING ABOUT THIS
Patricia Lockwood’s No One Is Talking About This (2021) dramatizes the psychic condition of being “extremely online” and models with formal daring and tonal oscillation how contemporary digital life can produce both a diffuse communal intimacy and a profound kind of alienation. The novel divides into two contrasting halves: the first renders the protagonist’s immersion in the “portal” (a social-media ecosystem) through fragmentary, aphoristic prose; the second pivots into intimate, embodied grief when a family medical crisis demands attention beyond the screen. This paper argues that Lockwood stages urban alienation as an emergent property of networked culture a condition in which continuous mediated sociality displaces rooted attachment and attenuates language and that the protagonist’s search for meaning ultimately depends on an uneasy reinvestment in physical relations, narrative continuity, and the limits of representability. Close reading of the novel’s form, voice, and recurring motifs (the portal, the “we,” the phone, and the hospital room) together with critical reception and Lockwood’s own commentary illuminates how the book is both a diagnosis of contemporary alienation and a tentative ethics of presence.
Ethnic Federalism, Governance Fragmentation, and Educational Resource Allocation in Post-Conflict Tigray, Ethiopia: A Qualitative Case Study
Education recovery in post-conflict settings is shaped not only by the scale of destruction but also by the institutional design through which reconstruction resources are allocated. This article examines how Ethiopia’s ethnic federal system has structured the allocation of educational resources in post-conflict Tigray. Drawing on a qualitative case study, the analysis combines 30 semistructured interviews conducted between March and April 2025 with federal, regional, and district officials, educational administrators, teachers, lecturers, students, parents, community leaders, NGO actors, and international partners, alongside a review of policy and program documents. The article asks how ethnic federalism has affected the distribution of educational finance, infrastructure, teachers, and learning materials during the early recovery period. Four findings stand out. First, population-based and project-based financing mechanisms did not adequately reflect war damage, displacement, or teacher attrition, producing chronic underfunding at school level. Second, authority was formally decentralized but operationally fragmented: blurred responsibilities across federal, regional, and woreda institutions delayed approvals, disbursements, and implementation. Third, recovery was spatially uneven, with rural and internally displaced persons-hosting communities receiving fewer resources than urban centers. Fourth, shortages of teachers, salary interruptions, and inadequate psychosocial support limited the substantive reopening of schools even where facilities had partially resumed operation. The article contributes to scholarship on ethnic federalism and education in emergencies by showing that post-conflict inequality is reproduced through governance fragmentation rather than scarcity alone. It argues for a conflict-sensitive, needs-based allocation formula, ring-fenced recovery grants, integrated education data systems, and teacher reintegration packages that align reconstruction with equity and durable peace.
ethnic federalism; governance fragmentation; education in emergencies; post-conflict recovery; Tigray; Ethiopia
Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
AN INTELLIGENT FRAMEWORK FOR MONITORING CITIZEN REACTIONS TO GOVERNMENT POLICIES USING SOCIAL MEDIA DATA
The rapid growth of social media platforms has transformed the way citizens express their opinions and reactions to government policies and decisions. Platforms such as Twitter, Facebook, and Instagram provide large volumes of real-time user-generated content that reflects public sentiment and societal concerns. Analyzing this data can provide valuable insights for policymakers, government agencies, and researchers to understand public perception and evaluate the impact of government actions. This study proposes an intelligent framework for monitoring citizen reactions to government policies using social media data. The framework utilizes advanced data analytics, natural language processing (NLP), and machine learning techniques to collect, process, and analyze social media posts related to government initiatives. The system extracts relevant features from textual data and performs sentiment analysis, topic modeling, and trend detection to identify public attitudes toward specific policies. The proposed framework includes modules for data collection, preprocessing, sentiment analysis, feature extraction, machine learning-based classification, and visualization. Social media data is first collected through APIs or web scraping tools and then cleaned and processed to remove noise, irrelevant content, and duplicate posts. Natural language processing techniques are applied to analyze textual information and determine whether public opinions are positive, negative, or neutral. Machine learning algorithms are employed to classify citizen reactions and detect emerging public concerns related to government actions. The system also provides visualization dashboards that display sentiment trends, topic distributions, and geographic patterns of public opinion. These insights can help government authorities monitor public feedback, identify policy challenges, and improve communication with citizens. The results demonstrate that integrating social media analytics with intelligent data processing techniques can significantly enhance the understanding of citizen reactions to government policies. The proposed framework offers a scalable and efficient solution for real-time public opinion monitoring, enabling governments to make informed decisions and strengthen citizen engagement.
M. SURESH BABU, JAVVAJI NARESH, MUSKU BHARGAVI, MARAM SHIVA KUMAR, MANNE VINAY
AI-BASED PREDICTION OF HEART RATE CHANGES FROM BODY TEMPERATURE IN PEDIATRIC INTENSIVE CARE PATIENTS
Monitoring vital signs such as heart rate and body temperature is critical for assessing the health condition of children admitted to the Pediatric Intensive Care Unit (PICU). Variations in body temperature often influence heart rate, and abnormal patterns may indicate infections, inflammation, or other medical complications. Early identification of such physiological changes can assist healthcare professionals in making timely clinical decisions and improving patient outcomes. This study proposes an Artificial Intelligence (AI)-based approach to predict heart rate changes based on body temperature data collected from pediatric patients in intensive care settings. The system utilizes machine learning algorithms to analyze large volumes of patient monitoring data and identify patterns between temperature fluctuations and heart rate variations. Historical patient data, including vital sign measurements and clinical observations, are used to train predictive models capable of estimating heart rate responses to temperature changes. The proposed framework involves data preprocessing, feature extraction, model training, and prediction, enabling the system to detect abnormal physiological patterns and support real-time patient monitoring. Machine learning models such as Random Forest, Support Vector Machine, and Neural Networks can be employed to improve prediction accuracy and reliability. The developed system aims to assist clinicians by providing early warning indicators of potential health deterioration, thereby enabling proactive medical intervention. By integrating AI with pediatric healthcare monitoring systems, the proposed approach enhances the efficiency of patient monitoring and contributes to improved decision-making in critical care environments.
SHRAVANI JASTHI, HARSHA GANESH KARLE, KURME RAGHU, MORISHETTI SAI PRASANNA KUMAR, MUSKU SATHWIK REDDY
INTELLIGENT CREDIT CARD FRAUD PREVENTION USING GRAPH NEURAL NETWORKS AND AUTOENCODER MODELS
Credit card fraud has become a major concern in modern digital banking due to the rapid growth of online transactions and electronic payment systems. Traditional fraud detection methods often rely on rule-based systems or conventional machine learning algorithms, which may struggle to detect complex and evolving fraud patterns in real time. To address these challenges, this study proposes an intelligent credit card fraud prevention framework using Graph Neural Networks (GNN) and Autoencoder models. The proposed approach leverages the ability of Graph Neural Networks to capture relationships and interactions between entities such as users, transactions, and merchants. By representing transaction data as a graph structure, the model can identify suspicious patterns and hidden connections that may indicate fraudulent activities. Additionally, an autoencoder-based anomaly detection mechanism is employed to learn normal transaction behavior and detect unusual deviations that may signal potential fraud. The integration of graph-based learning and deep anomaly detection enhances the system’s capability to detect both known and unknown fraud patterns. The proposed framework processes transaction data in near real time, enabling faster and more accurate fraud identification while reducing false positives. Experimental evaluation demonstrates that the combined use of GNN and autoencoder models significantly improves fraud detection performance compared to traditional methods. This intelligent fraud detection system can assist financial institutions in strengthening security, minimizing financial losses, and improving trust in digital banking services by providing an effective solution for real-time credit card fraud prevention.
SRIKANTH JINDAM, LIKKI LEELA VARDHAN, LINGAM RAM AKSHITH, MATURI KALYANI, M A SHASHANK YADAV, MALYALA GOUTHAM GOUMITH
CLIMATE CHANGE: RISING BURDEN OF INFECTIOUS DISEASES IN INDIA AND MITIGATION STRATEGIES
In modern years, India has eye-witnessed an strengthen number of flare-ups of infectious diseases over the country. Diseases like cholera, malaria, dengue, chikungunya, filariasis, kala-azar have been aboriginal in India for an extended period. Climate change is an anomalous worldwide threat. This study aims to focus on understanding the impact of climate change on infectious disease and importance of adaptation mitigation strategies. Climate shift is growingly identified as a hazardous operator in the appearance, diffusion, and spread of infectious diseases. Proliferating warmer temperatures, change precipitation form, and greatest weather episode influence the bio-ecology of illness carrier, microbes, and hosts. Warmer temperature can expand the variety and action of species such as mosquitoes and parasite, accelerate the spread of vector-borne diseases like malaria, dengue, tick-borne disease, and chikungunya in earlier uninfluenced domain. Moreover, climate-incite living shift and environment disruption may expand contact between person and pathogens. So, this is very crucial to understand these critical, multifaceted correlation for initiate powerful community health and wellness adaptation strategies and boosting inspection set-up to reduce disease burden and improve community health outcomes.
limate change, Infectious Disease, Water-borne diseases, Mitigation strategies
A PROJECT REPORT ON ROLE OF PAYMENTS BANK IN INDIA’S DIGITAL PAYMENTS ECOSYSTEM IN IPPB
The rapid growth of digital payments has significantly transformed India’s financial system by promoting cashless transactions and financial inclusion. Payments Banks play a key role in this transformation by providing basic banking and digital payment services to underserved populations. This study focuses on the role of Payments Banks in India’s digital payments ecosystem with special reference to India Post Payments Bank (IPPB). IPPB utilizes India Post’s wide network to offer services such as savings accounts, UPI, mobile banking, Aadhaar- enabled payments, and direct benefit transfers, especially in rural and semi-urban areas. The study highlights that IPPB acts as a crucial link between traditional banking and digital finance, supporting government initiatives and enhancing inclusive economic growth.
Digital Payments, Payments Banks, India Post Payments Bank, Financial Inclusion, UPI, AEPS
A STUDY ON WORKING CAPITAL MANAGEMENT AT Muthoot Fincorp , Jammalamadugu
This study examines the working capital management practices at Muthoot Fincorp Ltd., one of India’s leading Non-Banking Financial Companies (NBFCs). Working capital plays a crucial role in ensuring liquidity, operational efficiency, and financial stability in financial institutions. The primary objective of this research is to analyze the components of working capital, liquidity position, cash management practices, and efficiency of short-term financial management in the company. The study is based on secondary data collected from annual reports, company records, journals, and financial statements. Tools such as ratio analysis, percentage analysis, and comparative financial statements are used for interpretation. The findings reveal that effective working capital management has helped the company maintain liquidity, improve operational efficiency, and ensure smooth business operations. However, proper monitoring of receivables and short-term liabilities is necessary to maintain financial balance.
Working Capital, NBFC, Liquidity, Current Assets, Current Liabilities, Financial Management, Muthoot Fincorp.
उच्च शिक्षा में संगीत और नृत्य अनुसंधान की वर्तमान प्रवृत्तियाँ
उच्च शिक्षा में संगीत और नृत्य अनुसंधान पारंपरिक संगीतशास्त्र और नृत्य-रचना अध्ययन की सीमाओं से आगे बढ़कर अंतर्विषयी, प्रौद्योगिकी-सक्षम और सामाजिक रूप से संलग्न विद्वत्ता तक विस्तृत हो गया है। समकालीन अनुसंधान में अभ्यास-आधारित पद्धतियों, देहाधारित संज्ञान, डिजिटल उपकरणों और समुदाय-केंद्रित दृष्टिकोणों का समावेश बढ़ रहा है, साथ ही समानता, उपनिवेशवाद-उन्मूलन, सुलभता और कल्याण जैसे मुद्दों पर भी ध्यान दिया जा रहा है। यह शोध-पत्र संगीत और नृत्य कार्यक्रमों में वर्तमान अनुसंधान एजेंडों को आकार देने वाली प्रमुख प्रवृत्तियों की समीक्षा करता है, जिनमें अभ्यास रूप में अनुसंधान, कलात्मक अनुसंधान पद्धतियाँ, स्क्रीन-माध्यमित प्रदर्शन और डिजिटल अभिलेखीकरण, कृत्रिम बुद्धिमत्ता-सहायित सृजन और विश्लेषण, तंत्रिका-विज्ञान तथा स्वास्थ्य विज्ञान के साथ अंतर्विषयी सहयोग, स्थिरता और सांस्कृतिक नीति, तथा समावेशी शिक्षण-पद्धतियाँ शामिल हैं। यह मानव प्रतिभागियों पर आधारित अनुसंधान, सहयोगात्मक सृजन में लेखकीय अधिकार, डिजिटल प्रदर्शन में आँकड़ा स्वामित्व और सांस्कृतिक अधिग्रहण जैसे उभरते नैतिक और पद्धतिगत प्रश्नों को भी रेखांकित करता है। अंततः यह समीक्षा उच्च शिक्षा में आधारभूत संरचना सहयोग, अंतर्विषयी प्रशिक्षण, नैतिक ढाँचों और सामुदायिक साझेदारी के माध्यम से अनुसंधान क्षमता को सुदृढ़ करने के लिए सुझाव प्रस्तुत करती है।
कलात्मक अनुसंधान, अभ्यास-आधारित अनुसंधान, उच्च शिक्षा, संगीत अनुसंधान, नृत्य अनुसंधान, प्रौद्योगिकी, समानता-विविधता-समावेशन, देहाधारित संज्ञान
EXPLORING 21ST CENTURY SKILLS IN CMI ENABLED CLASSROOM ENVIRONMENT AMONGST PROSPECTIVE TEACHERS
The 21st century Skills amongst teacher trainees has been recognised as crucial in their career yet the determinant that could bring a change in the classroom environment to develop 21st century skills remained unexplored. This experimental study involves 100 prospective teachers from one of the Teacher Educational Institutes of Jaipur, Rajasthan, India through random sampling across teacher educational Institutes, teacher education programs and subject discipline. After the pretest of 21st century skills to both groups, CMI treatment was given to 48 teacher trainees when the rest of the 52 teacher trainees continued with their regular activities. This followed by administration of standardized tools to measure Classroom Environment and post 21st century skills of all the participants. On factor analysis of procured data, findings of the study exhibited significant effects of CMI, Classroom Environment & their interaction on 21st Century skills. Supportive Classroom environment interacts more with CMI to facilitate 21st Century Skill. The result also demonstrated that CMI group is significantly superior to Conventional Method Group in attaining 21st Century Skills. This significant difference in attaining 21st century Skills exhibits the need for a shift in pedagogy while transmitting information in class and maintaining a supportive classroom environment to enable the attainment of cognitive, intrapersonal and interpersonal skills
THE CONCEPTUAL FRAMEWORK OF BAPSI SIDHWA ON VICTIMISATION OF WOMEN
This article examines the ideology of victimisation of women in the novels of Bapsi Sidhwa, with close attention to The Pakistani Bride (1983), Ice-Candy-Man (1988; US title Cracking India), An American Brat (1993), and Water (2006). Situating Sidhwa within Commonwealth feminist writing and South Asian Partition literature, the study argues that her fiction represents victimisation not as a naturalised feminine condition but as a historically constructed ideological formation sustained through patriarchy, nationalism, communal violence, religious orthodoxy, and diasporic modernity. Drawing upon feminist theory (Simone de Beauvoir, Judith Butler, Gayatri Chakravorty Spivak), trauma studies (Cathy Caruth), and Partition historiography (Urvashi Butalia; Ritu Menon and Kamla Bhasin), this article demonstrates how Sidhwa exposes systemic gendered oppression while simultaneously foregrounding women’s resilience, testimony, and ethical witnessing. Through sustained close reading and textual quotation, the essay contends that Sidhwa dismantles simplistic binaries of victim and agent. Instead, she presents a continuum wherein women inhabit positions of vulnerability, resistance, negotiation, and survival. Her narrative strategies child focalisation, embodied depiction, irony, and dialogic plurality transform the literary representation of suffering into a site of historical accountability and feminist critique.
victimisation, Partition literature, Feminist Criticism, Postcolonial Theory, Gendered Violence, Commonwealth Literature, Trauma.
THE DISINTEGRATION OF TRIBAL LIFE IN GOPINATH MOHANTY’S THE ANCESTOR
The present paper highlights the disintegration of Tribal life in Gopinath Mohanty’s The Ancestor (Dadi Budha), his first novel on tribals concerning impact of colonial modernity on tribal culture and society. It is a novel about the lives, customs, beliefs and rituals of the tribal communities and about the outer intervention that causes disintegration of tribal society and culture disrupting and affecting tribal harmony in adverse ways. The novel sets in the Lulla village that tells the poignant story of struggle for survival of paraja tribe, facing decadence with the invasion of intruders. The ideologies of modern civilization are personified in the character of Santosh Kumari who seduces Thenga Jani, a representative of tribals. Tenga, under the influence of various forces of modernity, breaks away the tribal norms, devaluing his age-old tradition and cultural beliefs. And the negative consequences of this act also play out in the lives of the tribals. The tribal life is deeply rooted in indigenous eco-ethics, tradition and beliefs which exist in antipathy to modernity. Though, an impact of modernity has influenced their culture to some extent but the key tenets of their tradition remain unaffected.
Tribal, Disintegration, Ancestor, Colonial, Modernity, Intervention, Customs Tradition
A STUDY ON EMPLOYEE ENGAGEMENT TOWARDS SUPER-K
This study examines employee engagement and its influence on organizational performance at Super K, Kadapa. It focuses on key factors such as work environment, leadership support, communication, recognition, salary, work-life balance, and emotional connection that affect employees’ engagement levels and satisfaction at work. The study highlights that engaged and satisfied employees demonstrate higher commitment, motivation, and productivity, which contribute significantly to achieving organizational goals and overall performance. The findings emphasize the importance of effective human resource practices in creating a positive workplace environment, strengthening employee participation, and improving employee retention and performance in the retail sector.
Employee Engagement, Job Satisfaction, Organizational Performance, Employee Motivation, Work environment.
SUSTAINABLE DEVELOPMENT GOALS’ (SDGS): INDIA’S PROGRESS AND CHALLENGES - A STUDY
This study critically analyses India's progress in attaining the Sustainable Development Goals, investigates the challenges faced, and proposes potential ways to accelerate advancements towards sustainable development. The Sustainable Development Goals (SDGs), adopted via the United Nations (UN) in 2015, provide a global blueprint for tackling key social, environmental, and economic challenges. As a country with a diverse and significant population, India's progress towards these goals presents unique opportunities and challenges. across various states and union territories (UTs) in India since 2015. The study considers secondary data derived from the National Institution for Transforming India (NITI) Aayog’s SDG Index. The SDG interaction analysis confirms that the maximum number of goals synergizes with other goals. This study enriches current literature by providing empirical insights into SDG progress and disparities across states and UTs for the first time in the Indian context. However, the study is constrained in its ability to describe the progress and disparities of SDGs across states and UTs. Future research endeavours may delve into the underlying factors contributing to uneven progress.
Sustainable Development Goals (SDGs), India's progress, economic challenges, National Institution for Transforming India (NITI), Indian context
LEGAL ENFORCEMENT, SOCIAL AWARENESS, AND SOCIAL WORK INTERVENTION AGAINST FEMALE FOETICIDE: AN EMPIRICAL STUDY OF TEACHERS IN NAGPUR MUNICIPAL SCHOOLS
Gender conflicts and social inequality amongst men and women in India has persisted overtime due to female foeticide that has contributed negatively to the social justice, human rights and equality. Despite the coming to existence of the Pre-Conception and Pre-Natal Diagnostic Techniques (Prohibition of Sex Selection) Act [PCPNDT Act] and the continuous advocacy that had to take place, the declining child sex ratio in some of the areas portrays that there are violations of the law, ignorance among the people and level of actions of the community. The teachers particularly those working in the municipal schools are in the vantage point because they are the agents of the social change who can shape the attitude of young learners and their families as well. The existing empirical research study will be centered on the extent of legal awareness, the effectiveness of social awareness campaign and the effects of social work intervention in preventing female foeticide among the teachers in Nagpur Municipal Schools. In the research, the level of the knowledge of the teachers concerning the PCPNDT Act, their perception related to gender bias, and the activities they engage in the field of the awareness promotion using both the analytical methods and the structured questionnaire are evaluated. It is estimated that the results will show the significance of gaps in the enforcement and the outreach of the community and establish the potentials to harmonize the schoolbased social work practices. The study article will also help in policy debate as it will be suggestive of multi-stakeholder responses to make enforcement of the law more effective, gender sensitive regarding gender-sensitization programmes, and will empower teaching fraternity as the main driving force of change in halting acquisition of reproductive technology to prevent female foeticide.
Female Foeticide, PCPNDT Act, Legal Enforcement, Social Awareness, Social Work Intervention, Gender Discrimination, Municipal School Teachers, Nagpur
CORPORATE SOCIAL RESPONSIBILITY AND ITS INFLUENCE ON BRAND PERCEPTION AND CONSUMER LOYALTY
CSR has changed its position as a compliance mechanism in a regulatory dimension into a stance of strategic usefulness that defines the existence of the corporate identity and influences the consumer behavior. In this paper, the two areas that will be evaluated are the impact of CSR-based activities on brand perception and customer-loyalty in India. Structured questionnaires will be used to develop primary data on a sample of consumers in the urban areas based on descriptive research design to assemble basic data needed to complete the study, and secondary data will be accessed in order to reach a conclusion on CSR practices in the companies of interest. It turns out that environmentally sustainable, community development, and ethical business activities will assist the consumers in positively perceived brands and developing long-term loyalty. Data analysis will be based on the statistical tools, i.e., correlation and regression analysis to prove the hypothesized relationships. Hopefully, the results shall be practical to the marketers and the managers in throwing down sharper light on the applicability of CSR in enhancing the brand equity, consumer trust as well as long term competitive advantage.
Corporate Social Responsibility (CSR), Brand Perception, Consumer Loyalty, Ethical Business Practices, Socially Responsible Marketing, Brand Equity, Customer Trust
THE ROLE OF DIGITAL LEARNING IN ENHANCING THE QUALITY OF OPEN DISTANCE EDUCATION
Digital learning has significantly transformed Open Distance Education (ODE) by enhancing accessibility, flexibility, learner engagement, and instructional effectiveness. The integration of Learning Management Systems (LMS), virtual classrooms, artificial intelligence-based analytics, and multimedia resources has reshaped pedagogical practices in distance education. This study explores the role of digital learning in improving key quality dimensions of ODE, including instructional design, learner support services, assessment strategies, and student satisfaction. A descriptive research design was adopted, and data were collected from 200 learners enrolled in ODE programs using a structured questionnaire. The data were analyzed through descriptive statistics and correlation techniques. The findings reveal a strong positive relationship between digital learning tools and perceived educational quality. Interactive platforms, timely feedback mechanisms, and digital assessments significantly enhanced learner engagement and academic performance. The study emphasizes the importance of digital infrastructure, faculty training, and learner digital literacy for sustainable quality enhancement in open distance education systems.
Digital Learning, Open Distance Education, E-learning, Quality Enhancement, Learning Management Systems, Online Pedagogy, Educational Technology
माध्यमिक स्तर पर विद्यार्थियों के अभिभावकों की तत्संबंधी आकांक्षा एवं समायोजन का अध्ययन
प्रस्तुत शोध अध्ययन का उद्देश्य माध्यमिक स्तर के विद्यार्थियों के समग्र समायोजन तथा उनके अभिभावकों की तत्संबंधी आकांक्षाओं के मध्य संबंध का अध्ययन करना है। वर्तमान समय में अभिभावकों की अपेक्षाएँ विद्यार्थियों के शैक्षिक एवं मानसिक जीवन को गहराई से प्रभावित कर रही हैं। यदि ये आकांक्षाएँ संतुलित एवं यथार्थपरक हों तो विद्यार्थियों का समायोजन बेहतर होता है, जबकि अत्यधिक अथवा अव्यावहारिक आकांक्षाएँ विद्यार्थियों में तनाव एवं समायोजन समस्याएँ उत्पन्न कर सकती हैं। प्रस्तुत अध्ययन में बाराबंकी जनपद के माध्यमिक स्तर के विद्यार्थियों एवं उनके अभिभावकों को न्यादर्श के रूप में लिया गया है। सर्वेक्षण विधि द्वारा संकलित आँकड़ों का विश्लेषण मध्यमान, प्रमाप विचलन, ज परीक्षण तथा सहसंबंध तकनीक द्वारा किया गया। निष्कर्षो से यह स्पष्ट हुआ कि अभिभावकों की तत्संबंधी आकांक्षा तथा विद्यार्थियों के समग्र समायोजन के मध्य सार्थक संबंध पाया गया।
समग्र समायोजन, अभिभावक आकांक्षा, माध्यमिक स्तर, विद्यार्थी
INTELLECTUAL PROPERTY RIGHTS AND STARTUPDEVELOPMENT IN INDIA: CHALLENGES, REFORMS, ANDOPPORTUNITIES
The Indian startup ecosystem has experienced unprecedented growth in recent years, driven by technological innovation, entrepreneurial spirit, and government initiatives such as Startup India and Make in India. In this dynamic environment, Intellectual Property Rights (IPR) play a pivotal role in protecting innovations, enhancing competitiveness, and attracting investments. This paper critically examines the significance of IPR in the development of startups in India, highlighting its impact as a strategic asset rather than a mere legal formality. It explores the conceptual framework of IPR, the legal and policy initiatives introduced by the Indian government, and the existing challenges that hinder effective implementation for startups. The study identifies key issues such as lack of awareness, high registration costs, procedural delays, and weak enforcement mechanisms that impede startups from fully leveraging intellectual property protection. Furthermore, it discusses recent reforms including fee reductions, fast-track examinations, and the Startups Intellectual Property Protection (SIPP) scheme aimed at promoting innovation-friendly policies. Opportunities arising from a robust IPR framework— such as increased investor confidence, technology licensing, global expansion, and competitive advantage—are also analysed. The paper concludes by emphasizing the need for a holistic approach that combines strong legal frameworks, simplified procedures, awareness programs, financial incentives, and efficient enforcement mechanisms. Strengthening the IPR regime will not only empower startups to safeguard their innovations but also position India as a global leader in innovation and entrepreneurship.
Intellectual Property Rights, Startups, Innovation, Indian Legal Framework, Patent Protection, Trademark Registration
Copyright (c) 2026 Dhartiben Prafulkumar Shah, Dr. Bhavesh H. Bharad (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
IMPLEMENTATION AND PERFORMANCE EVALUATION OF LEANMANUFACTURING TECHNIQUES IN DISCRETE PRODUCTIONSYSTEMS
Lean manufacturing has emerged as an effective approach for improving productivity, quality, and efficiency in discrete production systems. Increasing competition and customer demand require manufacturers to minimize waste while maximizing value creation. This paper presents the implementation and performance evaluation of lean manufacturing techniques in discrete manufacturing environments. Key lean tools such as value stream mapping, 5S, Kaizen, and just-in-time production are systematically applied to a selected production system. Performance indicators including productivity, cycle time, work-in-process inventory, and defect rate are analyzed before and after implementation. The results demonstrate significant improvements in operational efficiency and resource utilization. The study confirms that lean manufacturing provides a structured methodology for continuous improvement. The findings support the adoption of lean practices in discrete production systems to achieve sustainable manufacturing performance.
Lean manufacturing, Discrete production systems, Productivity improvement, Waste reduction, Continuous improvement
Copyright (c) 2025 Yuri (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
HYBRID FRP–CONCRETE COMPOSITE SYSTEMS FOR ENHANCED STRUCTURAL RESILIENCE
Hybrid Fiber-Reinforced Polymer (FRP)–concrete composite systems have emerged as a promising solution for improving the strength, durability, and overall resilience of structural elements subjected to extreme loading conditions. Conventional reinforced concrete structures often experience premature cracking, reduced ductility, and progressive degradation under seismic, impact, and environmental stresses, necessitating advanced retrofit and strengthening strategies. This study investigates the structural performance of concrete elements strengthened with hybrid FRP composites, combining carbon, glass, and basalt fibers to optimize stiffness, energy absorption, and crack resistance. Experimental testing and analytical modeling were conducted to evaluate compressive strength, flexural behavior, and post-cracking response of hybrid FRP-confined specimens. Results indicate significant improvements in load-carrying capacity, deformation control, and failure mode transition, with hybrid systems outperforming single-fiber FRP configurations. The enhanced confinement and synergistic interaction of multiple fiber types contribute to improved ductility and resilience, making hybrid FRP–concrete composites a viable solution for seismic retrofitting, rehabilitation of aging infrastructure, and design of resilient structural systems. The findings highlight the potential of hybrid FRP composites in advancing nextgeneration civil infrastructure with superior performance and long-term reliability.
Market Entry Strategies, GlobalBusiness, International Expansion, CompetitiveAdvantage, Strategic Management
The increasing demand for energy-efficient buildings has intensified interest in passive cooling techniques, particularly the use of phase change materials (PCMs). PCMs have the ability to store and release large amounts of latent heat during phase transitions, making them suitable for thermal regulation in buildings. This research investigates the thermal performance of PCMs integrated into building cooling systems. The study evaluates temperature regulation, heat storage capacity, and indoor thermal comfort improvements achieved through PCM incorporation. An experimental approach is adopted using selected PCMs with suitable melting temperatures for building applications. Temperature variation, heat flux, and energy savings are analyzed under controlled conditions. The results demonstrate that PCMenhanced systems significantly reduce indoor temperature fluctuations and cooling loads. The findings highlight the potential of PCMs in improving building energy efficiency. This research supports sustainable building design and reduced dependency on conventional cooling systems.
Phase Change Materials, Building Cooling, Thermal Energy Storage, Passive Cooling, Energy Efficiency.
Copyright (c) 2025 Stefan (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
STRATEGIC MARKET ENTRY APPROACHES AND THEIR IMPACT ON SUSTAINABLE GLOBAL BUSINESS PERFORMANCE
Globalization has intensified competition and expanded opportunities for firms seeking international expansion. Selecting an appropriate market entry strategy plays a crucial role in determining long-term business success in foreign markets. This study examines various market entry strategies such as exporting, licensing, joint ventures, mergers and acquisitions, and wholly owned subsidiaries, and analyzes their influence on global business performance. The research emphasizes strategic alignment, risk management, and market adaptability as key success factors. A mixedmethod research approach is adopted using secondary data and empirical insights from multinational enterprises. The study highlights how strategic decision-making enhances competitiveness, profitability, and sustainability in international markets. Findings indicate that firms adopting adaptive and knowledge-driven entry strategies achieve superior global performance. The paper provides practical recommendations for managers and policymakers involved in international business expansion.
Market Entry Strategies, Global Business, International Expansion, Competitive Advantage, Strategic Management
BLOCKCHAIN-INTEGRATED IOT ARCHITECTURE FOR SECURE DATA MANAGEMENT
The rapid growth of the Internet of Things (IoT) has resulted in large-scale generation, transmission, and storage of sensitive data across distributed environments. While IoT enables intelligent applications in smart cities, healthcare, and industrial automation, it also introduces critical challenges related to data security, privacy, integrity, and trust. Conventional centralized security mechanisms suffer from single points of failure and limited scalability. Blockchain technology, with its decentralized, immutable, and transparent nature, has emerged as a promising solution for securing IoT data. This paper presents a blockchain-integrated IoT architecture for secure data management. The proposed framework combines IoT devices, edge computing, and blockchain-based distributed ledgers to ensure secure data storage, access control, and traceability. Analytical discussion highlights how the integration improves data integrity, trust, and resilience against cyber threats in large-scale IoT systems.
TECHNOLOGY-DRIVEN BUSINESS MODEL FRAMEWORKS FORENHANCING STARTUP GROWTH AND INNOVATION
In the modern digital economy, startups face unprecedented opportunities and challenges in scaling their operations and fostering innovation. Technology-driven business models leverage digital tools, data analytics, and innovative processes to enhance growth and competitive advantage. This study develops a comprehensive framework to analyze and implement technology-enabled business models for startups. Using qualitative and quantitative research methods, data were collected from emerging technology startups across multiple industries. Key factors influencing growth and innovation, such as digital infrastructure, customer engagement platforms, and data-driven decision-making, were identified. Findings suggest that integrating advanced technologies into business models improves scalability, operational efficiency, and market responsiveness. The framework provides actionable insights for entrepreneurs and policymakers seeking sustainable growth strategies in dynamic markets.
Technology-driven business models, Startup growth, Innovation, Digital transformation, Data-driven decision-making
Copyright (c) 2025 Amelia (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
MACHINE LEARNING–BASED TOOL WEAR PREDICTION IN ADVANCED MACHINING PROCESSES
Tool wear significantly affects surface quality, dimensional accuracy, and productivity in advanced machining processes. Traditional tool wear monitoring methods rely on manual inspection or threshold-based signals, which are often inaccurate and inefficient. This paper proposes a machine learning–based framework for predicting tool wear in advanced machining operations. Sensor data such as cutting force, vibration, acoustic emission, and temperature are utilized to capture tool condition information. Machine learning models are trained to learn complex nonlinear relationships between process signals and tool wear states. Experimental validation demonstrates high prediction accuracy and early detection capability. Comparative analysis shows that the proposed approach outperforms conventional methods. The results confirm that machine learning enables reliable and intelligent tool wear prediction for smart manufacturing environments.
Tool wear prediction, Machine learning, Advanced machining, Condition monitoring, Smart manufacturing
SECURE CYBER-PHYSICAL SYSTEM ARCHITECTURE FOR INDUSTRIAL AUTOMATION
Industrial automation systems increasingly rely on cyber-physical systems (CPS) that tightly integrate computation, communication, and physical processes. While CPS enables higher productivity, flexibility, and real-time control, it also exposes industrial environments to serious cybersecurity threats. Attacks on industrial CPS can lead to production downtime, safety hazards, and significant economic losses. Traditional IT security mechanisms are often inadequate due to realtime constraints, legacy systems, and resource limitations. This paper presents a secure cyberphysical system architecture for industrial automation that integrates layered security mechanisms with real-time control requirements. The proposed architecture combines secure sensing, authenticated communication, intrusion detection, and control-level protection to ensure system resilience. Analytical discussion and simulation-based evaluation demonstrate that the proposed framework enhances security while maintaining operational efficiency in industrial environments
ENERGY-AWARE EMBEDDED SYSTEM DESIGN FOR IOT SENSOR NODES
Energy efficiency is a critical requirement for Internet of Things (IoT) sensor nodes deployed in applications such as environmental monitoring, smart agriculture, healthcare, and industrial automation. These sensor nodes typically operate on limited battery power and are expected to function reliably for long durations without frequent maintenance. Conventional embedded system designs often result in excessive energy consumption due to continuous sensing, inefficient processing, and communication overhead. This paper presents an energy-aware embedded system design for IoT sensor nodes that focuses on minimizing power consumption while maintaining reliable sensing and data transmission. The proposed approach integrates low-power hardware components, duty-cycling techniques, and adaptive power management strategies. MATLAB/Simulink-based analysis demonstrates a significant reduction in energy consumption compared to traditional embedded system designs, validating the effectiveness of the proposed energy-aware approach.
AN INTELLIGENT MACHINE LEARNING–DRIVEN FRAMEWORK FOR ADVANCED PREDICTIVE DATA ANALYTICS
Predictive data analytics has emerged as a vital tool for extracting meaningful insights from large and complex datasets. With the rapid expansion of data-driven applications, traditional analytical methods often fail to provide accurate and scalable predictions. This research presents an intelligent machine learning–driven framework designed to enhance predictive performance through automated preprocessing, feature optimization, and model selection. The proposed framework integrates advanced machine learning algorithms to handle high-dimensional and heterogeneous data effectively. It focuses on reducing prediction errors while maintaining computational efficiency. Experimental evaluations conducted on benchmark datasets demonstrate significant improvements in accuracy and reliability. The framework also adapts dynamically to changing data patterns. The results highlight the robustness and flexibility of the proposed approach. This study contributes to the advancement of intelligent predictive analytics systems. The framework is suitable for deployment across various real-world applications.
Predictive Data Analytics, Machine Learning, Intelligent Framework, Feature Engineering, Model Optimization