Browse Items (16481 total)
Sort by:
-
Exploring digital age influences on undergraduate students mental health through social media, academic pressure and digital literacy
The research aims to measure the impact of usage of social media, academic pressure, and digital literacy, on mental health. It also aims to measure the mediating role of perceived stress on mental health of undergraduate students. Survey method was used for collecting data from a sample of 565 undergraduate students from state and private universities of Tamil Nadu, Karnataka, Andhra Pradesh, Telangana, and Kerala. EFA and Path analysis was used for testing and validating the conceptual model. The results showed that Social Media Usage increases Perceived Stress and negatively impacts Mental Health Outcomes both directly and indirectly through Perceived Stress. Academic Pressure increases Perceived Stress, which negatively impacts Mental Health Outcomes indirectly. Digital Literacy reduces Perceived Stress and has a positive effect on Mental Health Outcomes both directly and indirectly through reduced stress. Perceived Stress was found to have a significantly negative impact on the Mental Health Outcomes. The demographic variables namely; age, gender, living status, family type, and course type were found to have a significant impact on the usage of social media, academic pressure, digital literacy, perceived stress, and mental health scores of undergraduate students. The study also came up with interventions for managing mental health of under graduate students. The Author(s) 2025. -
Key AI Concepts for Ages 612: Logic, Patterns, and Algorithms
The digital era is providing new methods of learning, thinking, and problem-solving. Introducing the foundational ideas of AI to young learners helps them adjust to a technology-driven environment more effectively. This study explores effective ways to make young learners aged 6-12 aware of basic AI concepts, including logic, patterns, and algorithms. By utilizing secondary data, the study aims to explore effective pedagogical strategies and challenges in early education related to AI, and provide guidelines for parents and educators. The aim of the study is to enable curriculum designers and educators to design an inclusive stakeholders' model that can be used in primary education to introduce AI literacy in a way that enhances the critical thinking, creativity, and problem-solving abilities of young learners. Copyright 2026, IGI Global Scientific Publishing. Copying or distributing in print or electronic forms without written permission of IGI Global Scientific Publishing is prohibited. -
Big Data and Artificial Intelligence for Strategic Human Resource Management
In this modern world all the organizations are adopting the new technology and making the use of modern technologies to match the HR procedures with the strategic Big Data and AI enhance HR decision-making by providing insights into workforce demographics, performance patterns, and employee behavior. Together, they automate tasks like hiring, training, and performance reviews, while addressing skill gaps, talent acquisition, and retention with unmatched precision. The study examines several important applications, including predictive analysis for workforce planning, AI driven recruitment system and real-time employee sentiment analysis. Additionally, it looks at data protection issues, ethical issues and the necessity of HR personnel being skilled in order to use these technologies effectively. The study demonstrates how Big Data and AI have the ability to change SHRM from a reactive role into a proactive, value-creating discipline by examining case-studies and new trends. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Systematic Literature Review Methodology and Enabling Systems: A Rigorous Framework for Evidence Synthesis
The exponential rise in academic publications has made synthesizing knowledge and identifying research gaps increasingly challenging. The Systematic Literature Review (SLR) offers a rigorous, transparent, and reproducible approach to evidence synthesis. This chapter discusses the methodological foundations and digital systems that support SLRs, distinguishing them from narrative and scoping reviews. It details key phases such as question formulation, protocol design, search, screening, data extraction, quality appraisal, and synthesis, referencing frameworks like PRISMA 2020. Additionally, it explores the role of AI-driven tools (e.g., EPPI-Reviewer, DistillerSR, Covidence, Rayyan) in improving efficiency and scalability. The chapter concludes with challenges, ethical concerns, and future directions, emphasizing AI integration and living review methodologies. 2026 by IGI Global Scientific Publishing. All rights reserved. -
CSR's Role in Resilience via Boosting Social Sustainability in Economic and Environmental Challenges
This particular writing shall explore the role of CSR i.e., Corporate Social Responsibility in building community resilience by evaluating measures like social sustainability, particularly taking into consideration its response to economic and environmental crises. The objective of CSR is driven from the responsibility for a business to go beyond their financial gains and contribute towards societal and environmental wellbeing. As the Multi- National Corporations and large scale businesses grow bigger, their impact on the community is in proportion to the sales that they make, especially those who work in the FMCG that is Fast Moving Consumer Goods industry become household brand to the masses and can significantly make its position in the industry resilient by taking the economic and environmental metric in consideration while determining profits. CSR initiatives such as education, healthcare, disaster preparedness, and sustainable livelihoods are some of the key strategies that major businesses make use of in order to support community resilience. 2025, IGI Global Scientific Publishing. -
Towards Net-Zero Hotels: AI-Enabled Energy Transition and Demand Response Models
This paper presents an AI and machine learning-driven approach to support energy transition and demand-side management in hotel operations, aiming for net-zero energy goals in hot and arid regions. The proposed framework leverages predictive modeling to forecast HVAC energy consumption based on key environmental and operational factors such as temperature, humidity, occupancy, and thermostat settings. Among the tested models, LightGBM demonstrated superior performance in terms of accuracy and computational efficiency. Additionally, a demand response strategy was simulated, where small thermostat adjustments during high-load periods led to significant energy savings without affecting guest comfort. The results highlight the effectiveness of integrating AI-powered decision systems into hospitality energy management, contributing to climate-resilient, sustainable hotel infrastructure. 2025 IEEE. -
A Comparative Review of Lossless Text Compression Algorithms: From Classic Techniques to Hybrid Models
The lossless text compression is an essential part of data transmission and storage that allows using resources effectively without losing data integrity. This paper combines the most recent research with the important discoveries of benchmark research that focuses on essential algorithms such as Huffman LZW and Shannon-Fano and advanced hybrid algorithms such as LZW and Burrows-Wheeler Transform (BWT -based algorithms. The trade-offs between compression ratio, speed and adaptability can be observed comparing how algorithmic concepts, operational stages and empirical performance evolve in different datasets. This evaluation ends with recommendations on how to choose algorithms as well as future research recommendations. 2025 IEEE. -
Tracing the Evolution of Digital Strategy with AI, Blockchain, Cloud, and Cryptocurrencies
This chapter explores the transformative role of key technologies - artificial intelligence (AI), blockchain, cloud computing, and cryptocurrencies - in shaping contemporary digital strategies. It traces the historical evolution of these technologies and highlights their individual and synergistic contributions to business, governance, and society. AI has progressed from theoretical concepts to practical applications across diverse industries, enhancing decision-making, automation, and operational efficiency. Initially conceived for cryptocurrencies, blockchain technology now plays a pivotal role in securing and streamlining finance, healthcare, and supply chain management transactions. Cloud computing has democratized access to advanced technologies, accelerating the integration and scalability of AI and blockchain. Cryptocurrencies, built on blockchain frameworks, are reshaping global financial systems through decentralization and security. The chapter also addresses the challenges and opportunities of technological convergence, including ethical considerations, regulatory challenges, and the strategic need for multidisciplinary collaboration. By analyzing these intersections, this article provides a comprehensive understanding of how AI, blockchain, cloud computing, and cryptocurrencies drive digital strategies' future. 2026 Manjari Sharma, Sharad Gupta. All rights reserved. -
Solar cities: How the UAE is powering urban innovation through sustainable energy infrastructure
This chapter explores how the UAE is advancing sustainable urban development through large- scale solar infrastructure. Focusing on Masdar City and the Dubai Clean Energy Strategy 2050, it analyses governance, innovation, and institutional collaboration. The study highlights key lessons for scaling solar cities in arid regions and aligning urban planning with Sustainable Development Goals, offering insights for policy- makers, planners, and sustainability professionals across the MENA region and beyond. 2026 by IGI Global Scientific Publishing. All rights reserved. -
The role of AI in educational robotics
This chapter investigates the revolutionary combination of AI and educational robotics, looking at developments in technology, real-world applications, and ethical issues. Key case studies, comparative approaches, and effects on learning outcomes and student engagement are highlighted. In addition, the chapter discusses issues of equity and accessibility, makes strategic recommendations, and sketches out potential future research avenues before offering some final thoughts on how artificial intelligence might completely transform education. 2025, IGI Global Scientific Publishing. All rights reserved. -
Green Infrastructure
This chapter explores Green Infrastructure (GI) as a pivotal approach in sustainable urban development, integrating natural and engineered systems to create resilient and livable cities. It examines how GI enhances ecosystem services, mitigates climate change impacts, and supports biodiversity while contributing to human well-being. Through a comprehensive analysis of case studies and policy frameworks, the chapter demonstrates the transformative potential of GI in advancing sustainable urban solutions. It also discusses challenges and opportunities in implementing GI, emphasizing the need for innovative governance strategies to foster collaboration among stakeholders. By highlighting best practices and lessons learned, the chapter provides a roadmap for integrating GI into urban planning and policy to achieve long-term environmental, social, and economic benefits. 2025 by IGI Global Scientific Publishing. -
Sustainable Synergy: Exploring the Relationship Between Environmental Marketing and Green Entrepreneurship for Business
Environmental marketing and green entrepreneurship have emerged as vital approaches for businesses to integrate sustainability principles into their operations. This study explores the relationship between environmental marketing and green entrepreneurship as a sustainable approach for businesses. The methodology adopted for this study involves an exploratory literature review, which includes a review of scholarly articles on environmental marketing and green entrepreneurship. The sample description included a wide range of literature from diverse sources, covering various aspects of environmental marketing and green entrepreneurship. Literature was analyzed using qualitative thematic analysis, which involves identifying recurring themes, patterns, and insights from the literature. The results reveal that environmental marketing and green entrepreneurship are closely interconnected with the themes that emerged. The discussion revolves around the conclusions drawn from the results, including the implications for businesses, consumers, and society, and the potential benefits of integrating environmental marketing and green entrepreneurship as a sustainable approach. The study provides insights for businesses, policymakers, and other stakeholders on the importance of environmental marketing and green entrepreneurship in driving sustainable business practices and fostering environmental sustainability. 2025 by Apple Academic Press, Inc. -
Mechanical and moisture resistance properties of flax and jute fiber embedded epoxy composites for lightweight structural applications
Natural fiber-based materials are increasingly used as substitutes for traditional materials in structural applications. This research evaluated the mechanical and moisture resistance characteristics of unidirectionally oriented Flax and Jute fiber-embedded Epoxy Composites (FJEC) for lightweight structural applications. The inclusion of nano clay in the natural laminates creates more energy-absorbing sites, which improves the ability to withstand impact forces compared to FJEC. The material strength of nano clay-infused hybrid composite attained 94.46 MPa, 98.44 MPa, and 92 KJ/m2 tensile, flexural and impact strength. The consequences of water absorption and humidity exposure to the materials revealed that nano clay helps to reduce the diffusion of water into the surface of the laminate. The nano clay-infused hybrid composite is subjected to Freeze-Thaw (Fz-Tw) cycling under both partial and complete immersion scenarios to analyze the durability and resilience of the composite. The performance loss in nano-clay-infused laminate is caused due to the prolonged exposure to water and thermal stress. The damage factor for a partially and completely immersed hybrid material is 1.2% and 2.2%, respectively. These findings highlighted the need for considering environmental conditions while designing and utilizing fiber incorporated materials in various applications. 2026 Informa UK Limited, trading as Taylor & Francis Group. -
Visual propaganda through social media: A case study of Arab - Israeli crisis /
A picture is worth a thousand words, uploading images immediately attract attention a comments or tweets. Images are able to trigger multiple emotions and are effectively used for propaganda. Visual propaganda stands for usage of images to fulfil propaganda goals. These images carry meaning, emotion and a purpose. -
Impact of pharmacy industries growth on India economy during covid 19 /
Patent Number: 202241050891, Applicant: Deepha V.
Impact of Pharmacy Industries growth on India Economy during COVID 19 Abstract Pharmacy is an industry that can continue to function without being affected by economic fluctuations. This industry is socially respected by people. Whether people have food to eat or not, everyone wants to preserve the health of the body. In particular, the demand for medicines is more than ever in today's era. -
Brand equity management and marketing in the digital era: Strategies for phygital success
The digital revolution has transformed how brands interact with consumers, creating new opportunities and challenges for brand equity management. In the era of convergence between the physical and digital realms, commonly referred to as the "Phygital Era," brands must navigate a complex landscape to build and sustain their value. This chapter explores strategies for managing brand equity in the digital age, focusing on how brands can create cohesive, engaging, and personalized experiences that seamlessly bridge physical and digital touchpoints. It discusses the importance of omnichannel marketing, data-driven decision-making, and the role of social media and online communities in shaping consumer perceptions. Additionally, the chapter examines how digital transformation impacts brand loyalty, customer engagement, and the evolving expectations of consumers. By understanding the interplay between digital innovation and traditional brand-building practices, businesses can successfully position themselves for long-term growth and success in a rapidly evolving market. 2025, IGI Global Scientific Publishing. -
Real-Time Monitoring and Anomaly Detection in Cloud-Based IoT Networks
IoT devices have seen explosive growth, causing a data explosion, which makes it almost impossible to manage and monitor these networks. This has led to a demand for solutions providing real-time monitoring and detection of anomalies in cloud-based Internet of Things (IoT) networks. In cybersecurity, the term real-time monitoring denotes the ongoing analysis of data and network performance to detect potential problems. It allows for the identification of anomalies and possible weaknesses in the system. In contrast, anomaly detection is the process of finding deviations from what is considered normal for a system or data. Within cloud-based IoT networks, this might involve identifying abnormal traffic patterns or unusual activity from devices. To solve these challenges, we propose a cloud computing and machine learning-based solution. IoT devices generate a massive amount of data, which is processed in real-time and stored on the cloudbased infrastructure. Many machine learning algorithms analyze these data algorithms to identify anomalies or threats to security. This solution provides an active early warning detection of security breaches from the network management perspective, along with timely response in the case of abnormal behaviour. It will ultimately result in improved cloud-based networks for IoT devices with regard to reliability, security, and performance. This solution can be a key factor in driving the mass implementation of IoT in various sectors. 2025 IEEE. -
Overcoming the barriers to multi-stakeholder collaboration in supply chains: Strategies to foster co-operation in complex supply chains
The supply networks form the backbones of the global economy as a flow of goods, services, and information across industries and geographies. Meanwhile, globalization and digitalization that promoted the increasing complexity of supply chains highlight even greater urgency for sustainable and responsible supply chain management. This chapter considers the manner in which multi- stakeholder collaboration can become an important enabler of sustainability within the supply chains since no individual stakeholder has a chance of unilaterally solving all of its various problems. From the case studies conducted on Sedex and the automotive sector, this study has shown that sustainability strategies take a diversified view-from corporate management to government bodies, NGOs, and local communities- to align priorities, bridge cultural gaps, and develop collective solutions that will drive systemic change. Given the nature of conflicting priorities, the research finds concentration on cross- industry cooperation and the role of external organizations in promoting responsible practices. 2025, IGI Global Scientific Publishing. All rights reserved. -
Predicting electric vehicle performance metrics using a convolution neural network-gated recurrent unit-attention based deep learning architecture
The indicators of electric vehicle performance such as state of charge (SOC), remaining useful life (RUL), and charge demand need to be accurately forecasted to ensure maximum energy control and battery life. The models used are usually not able to capture the spatial and temporal correlation of battery data and be robust to the presence of noisy measurements. In this study, we model a sequential attention-based deep learning structure with convolutional neural networks, gated recurrent units, and an attention mechanism that can ultimately understand the local features, temporal relationships, and dynamic significance of various features in sequential battery data. The hybrid architecture of this model allows it to extract local spatial features, long-term sequential dependencies and dynamically find the importance of the critical time steps. We also develop a hybrid loss that is an accumulation of Huber loss and Mean Squared Error, which is much more resilient to outliers and at the same time has high prediction accuracy. It is experimentally proven that the proposed model has R2 values of 0.9575, 0.9558, and 0.9199 on SOC, RUL, and charge demand, respectively, which are better than the current single-architecture methods. 2026 The Authors