bluuebunny/crossref_metadata_2025 huggingface dataset:
Navigating Privacy and Security in Internet of Medical Things With Machine-to-Machine Interactions
Authors: Arunachalam Manikandan , Akella Saket , Arun Satvik D. , Babu Rakesh Thoppaen Suresh
Published: February 2025

Internet of Medical Things (IoMT) offers immense benefits by revolutionizing healthcare delivery, enhancing patient outcomes, and improving operational efficiencies across the healthcare ecosystem. Also, integration of Machine-to-Machine (M2M) communication with IoMT enables real time patient monitoring, remote diagnostics and intelligent decision making in critical situations. Current state of research shows that adoption of M2M communication with IoMT facilitates the seamless connectivity and data exchange among the health care devices and sensors. However, since M2M communication allows devices to communicate to each other without human intervention, security in the integration of M2M communication with IoMT face critical challenges and issues under different environments. This chapter will thoroughly discuss the security challenges and issues which are essential to address to escape from the evolving threat and to ensure the secure adoption of M2M communication with IoMT.
Integrating Digital Technologies to Optimize Sustainable Supply Chains
Authors: Tariq Muhammad Usman
Published: February 2025

This chapter investigates the coordination of computerized advances as impetuses for improving supportability inside supply chains. It looks at how advances like blockchain, Web of Things (IoT), and man-made reasoning (computer-based intelligence) improve straightforwardness, proficiency, and responsibility across worldwide store network organizations. Through contextual analyses and hypothetical bits of knowledge, the section represents pragmatic uses of these advancements in working on natural stewardship, social obligation, and monetary practicality. The main theme includes the job of blockchain in guaranteeing recognizability and moral obtaining rehearses, IoT's effect on continuous observing and asset the board, and artificial intelligence's commitment to prescient examination and functional productivity. The section likewise talks about difficulties and amazing open doors related with advanced change in supply chains, stressing the significance of administrative systems, cooperation among partners, and persistent development.
ESG Performance and Supply Chain Contracts
Authors: Zhou Jingyan Tracy , Sharpe Wen Hua , Halabi Abdel K. , Song Helen
Published: February 2025

This paper utilizes agency and stakeholder theories to explore the relationship between ESG (environmental, social, and governance) performance and supply chain contracts. Drawing from data using a sample of ASX 300 firms over the period of 2012 to 2021, our analysis reveals a negative relationship between ESG performance and supply chain contracts, aligning with agency theory principles. Furthermore, this negative association is observed to be more pronounced among firms characterized by lower levels of information asymmetry. These findings hold significant practical implications for management, business suppliers, and customers alike. Specifically, managers can leverage these insights to reinforce the commitment of supply chain partners towards ESG initiatives, thereby enhancing sustainability practices within the supply chain ecosystem.
Impacts of Digital Technologies Across Generations
Authors: Kshirsagar Ketki P. , Ingle Anup
Published: February 2025

Digital technologies have significantly influenced different generations, shaping cultural norms, regulatory frameworks, and economic landscapes. Baby Boomers and Generation X have adapted to these changes later in life, valuing traditional interactions while integrating digital tools into their routines. In contrast, Millennials and Generation Z have grown up in a digital world, making technology a core aspect of their culture and daily activities. The impact of digital technologies extends to various domains, including innovation, where younger generations drive the adoption of emerging technologies. Socially, digital connectivity has altered how generations interact, introducing challenges such as the digital divide and mental health concerns. Economically, digital literacy has become essential, offering new job opportunities while requiring older generations to reskill. Understanding these multifaceted impacts is crucial for bridging generational divides and harnessing the full potential of digital technologies for society.
Next-Gen Learning Cloud Integration for Academic and Industrial Synergy
Authors: Mehta Pradnya Samit , Shedge Prachi Pramod , Vyavahare Sakshi , Soundarrajan Srinidhi , Chillarge Geetha
Published: February 2025

In today's rapidly evolving technological landscape, the integration of cloud computing within educational frameworks is revolutionizing the way academia and industry collaborate. This book, “Bridging Academia and Industry: Cloud Integration in Education,” explores the transformative power of cloud technologies in enhancing educational outcomes and fostering innovative partnerships between academic institutions and the industrial sector. By leveraging cloud platforms, educational institutions can streamline resource management, facilitate collaborative research, and equip students with the practical skills required by modern industries. This comprehensive guide provides an in-depth analysis of the strategies, tools, and real-world case studies that demonstrate the myriad benefits of cloud integration in education. From setting up cloud infrastructure and implementing virtual labs to developing cloud-based curricula and enhancing student employability, this book offers valuable insights for educators, researchers, and industry professionals.
Bridging Academia and Industry Through Technology and Entrepreneurial Innovation
Authors: Vettriselvan R. , Deepa R. , Gautam Rashmi , Suresh N. V. , Cathrine S.
Published: February 2025

This chapter explores how technology and entrepreneurial innovation enhance supply chain efficiency. It highlights the transformative impact of advanced technologies such as cloud computing, data analytics, and IoT on supply chain operations, improving responsiveness and reducing costs. The entrepreneurial orientation is emphasized as a key driver of innovation, enabling organizations to adapt to changing market conditions. Through case studies, the chapter illustrates successful collaborations between academia and industry, demonstrating how theoretical insights translate into practical solutions. Challenges in technology integration, such as data security and the need for skilled personnel, are also addressed. By bridging the gap between academia and industry, this work aims to inspire future research and applications that enhance supply chain management, underscoring the importance of fostering a culture of innovation to maintain competitiveness in the global marketplace.
Security and Privacy Considerations in Cloud-Based Education
Authors: Ponde Poonam
Published: February 2025

Cloud computing has transformed education by providing anytime access to educational content, enhancing learning, and fostering collaboration. Adaptive technologies and analytics allow personalizing learning experiences and increasing learner engagement by tailoring education to individual needs. Cloud solutions streamline administrative tasks like attendance and grading, allowing educators to focus more on teaching. However, these benefits come with challenges, primarily concerning security and privacy. Educational organizations manage large amounts of sensitive data, including learner records, academic information, grades, and intellectual property. Storing this data in the cloud raises concerns about unauthorized access, data breaches, and regulatory compliance. The use of cloud-based services for hosting infrastructure and applications makes institutions vulnerable to attacks. Therefore, cloud security in education is crucial; requiring robust strategies and practices to protect data, applications, and infrastructure on cloud platforms.
Predictive Analytics Using Machine Learning for Enhanced Online Advertising
Authors: Rathi Snehal Rahul , Jadhav Narendra , Raut Abhishek , Navhal Abhishek , Patil Manas
Published: February 2025

Forecasting analytics in online marketing serves as the foundation for enhanced user interaction, accurate targeting, and optimization of marketing tactics in a constantly evolving digital environment. By utilizing predictive analytics to customize campaigns, marketers can improve the efficiency of their strategies by targeting particular interests and demographics. This research examines the application of machine learning models in forecasting user ad clicks, incorporating variables like age, internet usage, and daily site engagement time in the datasets. The effectiveness of decision tree and logistic regression models in predicting ad clicks through model building and data analysis is shown in the research. Utilizing actual predictive analytics in advertising strategies can be enhanced by incorporating user engagement signals and responses in real-world scenarios. The research highlights future directions and challenges. It also touches upon potential advancements in predictive analytics and online advertising techniques.
YoZu
Authors: Kachhoria Renu , Waykos Prajwal , Sharma Sathya Krishna
Published: February 2025

In the digital age, students struggle with navigating overwhelming online information. This chapter introduces YoZu, a student-focused chatbot. Powered by large language models, YoZu offers clear and engaging responses, making learning accessible for young minds. Its unique feature filters sensitive content, ensuring a safe learning environment. Additionally, YoZu provides dynamic image and video recommendations, enhancing comprehension. This research illuminates YoZu's transformative potential, simplifying complex information and revolutionizing students' interaction with online content.
Future Trends and Innovations in Cloud-Driven Education
Authors: Paul Sreelekha , Das Dipanjan
Published: February 2025

This chapter analyses the future trends and prospective of cloud-based education especially with regards to the roles of blockchain, augmented reality, virtual reality, artificial intelligence, and the internet of things (IOT). Intelligent tutoring system and adaptive learning both require AI and ML to tailor the education to the individual learner. Education has secure and verifiable credentials for capacity building and continuing education. Apart from experience learning, which is allegedly the best form of learning, AR and VR allow learning outside the limitation of geographical boundaries. Smart classrooms, which include the usage of IoT technology, permit the real-time collection of data and analyses used in an organization to improve learning environments and resource utilization. In enhancing and improving the current teaching-learning environment, these technologies may enable educational establishments to offer a more flexible, diverse, and efficient learning arrangement that prepares learners for today's complex and collaborative nature of workplaces.
A Theoretical Framework for Finding a Business Opportunity in the Healthcare Ecosystem Integrated With Blockchain
Authors: Mary Gerardine Immaculate , Julian Anitha , Jeffrey A. , Ramyadevi R. , Rele Mayur
Published: February 2025

After seeing the success of the Bitcoin blockchain, many assume that the data in a blockchain would only be for financial transactions, but it is not particularly limited to that, the data can be anything of value. It depends on the network and the industry that they are in, it could be transactions or quantity, timestamps, a location, or any other flow of information that can be stored and used on a blockchain. The proposed framework aims to design a business model in the healthcare industry by connecting all the peers in the healthcare supply chain. The result of this framework is a complete patient-centric, decentralized, and immutable healthcare ecosystem.
AI-Driven Discovery
Authors: Roy Pritam , Datta Dhananjoy
Published: February 2025

AI and machine learning have become transformative technologies in R&D across industries. This chapter explores their profound impact on scientific discovery and innovation, examining applications, challenges, and prospects. The authors define AI/ML and highlight their significance in advancing R&D processes. Key techniques like supervised learning, deep learning, and natural language processing are explained, along with their roles in scientific advancement. The chapter provides a comprehensive overview of AI/ML applications in diverse fields such as drug discovery, materials science, and environmental research. Challenges in implementing AI/ML, including data quality, model interpretability, and ethical considerations, are discussed. The authors also investigate future trends, emphasizing emerging paradigms, hybrid approaches, and human-AI collaboration. This work aims to equip researchers, practitioners, and policymakers with a thorough understanding of AI/ML's role in shaping the future of R&D.
Artificial Intelligence and Machine Learning in Research and Development
Authors: AlJadaan Omar Turkey , Ibrahim Omnia Ibrahim Mohamed , Al Ani Nowar Nizar , Jabas Ahmad Omar , Al Faress Mahmoud Yousef
Published: February 2025

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly changing the face of Research and Development (R&D). This chapter deals with a profound review of the current status and future trends of AI and ML in R&D. First of all, it gives an overview of huge investments and fast growth in AI, for instance, spending on AI systems worldwide is projected to reach as high as $110 billion by 2024. In the health sector, AI will potentially add up to $150 billion every year by 2026. The chapter highlights some of the most remarkable achievements in AI and ML, including transformer models like GPT-3 or Google's BERT, setting new benchmarks in natural language processing, low-code/no-code platforms democratize AI. Finally, the chapter asserts that AI and ML have the potential to transform R&D while insinuating that such development should be responsible and ethical. In adopting collaborative and open approaches, the stakeholders could reap maximum benefits from AI technologies in boosting innovation and societal benefits across different industries.
Digital Transformation and Sustainability in the Textile Industry
Authors: Gopal Bharathi S. , Davidson Benny Godwin J. , Tur Anna
Published: February 2025

The purpose of this chapter is to explore the relationship between the Indian textile industry and sustainability. This chapter traces the evolution of the industry in India and its economic contribution. It highlights the emerging trend towards circularity. In this chapter, it is argued that the industry must adopt sustainable practices. The role of digital technology in promoting sustainability is emphasized. To become sustainable, technologies like data analytics, AI, and IOT will help in tracking carbon emissions. The chapter discusses government initiatives for sustainable transformation. It examines the challenges in implementing policies among small businesses. The final section discusses the future of sustainability in Indian textiles and digital transformation's potential to drive sustainable growth. Several actionable recommendations include importance of government support and consumer awareness in adopting sustainable practices. The chapter concludes with a call to action for collaboration among industry stakeholders, government and consumers for a sustainable future.
Green Technology for Sustainable Development
Authors: Chakraborty Soma , Konwar Juthika , Chakrabarty Nilanjana
Published: February 2025

Green technology presents an alternative approach to growth and development that aims to generate economic progress and improve people's lives while simultaneously promoting environmental and social well-being. A crucial aspect of green technology is to encourage the development and widespread adoption of sustainable technologies. The main objective of this article is to explore the concept of green technology, its goals and measures for attainment, the challenges faced in pursuing it, and strategies to overcome those challenges. The article argues that achieving sustainable technological change will necessitate a re-evaluation of the respective roles of private industry and the state. Moreover, future research should increasingly focus on identifying and implementing novel combinations of policy instruments tailored to various institutional contexts.
Open Innovation and Crowd Sourcing
Authors: Ramachandran Ramakrishnan , Pillai Sruthi
Published: February 2025

This chapter examines the two powerful paradigms of Open Innovation and Crowdsourcing, discussing their unique benefits, challenges, and potential for transforming research and development (R&D) processes. Beginning with the conceptual framework, it proceeds with the historical context, types of Open innovation, its benefits, and the challenges. Discussion of some of the successful case studies gives better clarity. The chapter continues similarly with Crowdsourcing, followed by looking at the core features and diverse applications with examples. Proceeding further to the Convergence of Open Innovation and Crowdsourcing, we look at the benefits and challenges of such integration, touching on the implication for R& D. The Chapter also addresses the role of technology and gives some examples. Finally, the chapter concludes on the transformative impact of R&D and dwells upon future trends and opportunities.
Integrating Artificial Neural Networks in Microwave Electronic Design Automation
Authors: You Kok Yeow , Sim Man Seng
Published: February 2025

This chapter comprehensively surveys the application of artificial neural networks (ANN) in microwave circuit electronic design automation (EDA). Traditional microwave circuit EDA typically employs electromagnetic Maxwell's equations aided by numerical computation methods. However, using conventional EDA, circuit designers often need to iteratively adjust input circuit dimensions or parameters to achieve optimal performance. This chapter explores the application of AI algorithms in EDA to streamline the try-and-test design process. Incorporating AI into EDA allows for automatic optimization of circuit designs. Specifically, this chapter examines the combination of particle swarm optimization (PSO), genetic algorithms (GA) and ANN to assist in the analytical calculation of coupled microstrip lines, which are crucial for designing directional couplers and parallel-coupled filters the results are compared and validated against those obtained from commercial simulators. The history, concepts, and recent advancements of PSO, GA, ANN, and EDA are briefly described and discussed.
Microwave Sensors With Artificial Neural Network Implementation for Permittivity Measurement
Authors: Sim Man Seng , You Kok Yeow , Esa Fahmiruddin , Dewan Raimi , Paramasivam DiviyaDevi , Rashid Rozeha A.
Published: February 2025

This book chapter reviews the applications of artificial neural networks (ANNs) in microwave sensors to extract the properties of samples under test (SUTs). ANNs enable the determination of complex and nonlinear relationships between sensing data and desired output data. An overview of ANN architecture, working principle, and state-of-the-art advances of ANN-assisted microwave sensors is provided. Subsequently, a planar microwave sensor based on microstrip transmission line and complementary split ring resonators (CSRRs) is designed and simulated using Computer Simulation Technology (CST). The use of MATLAB software to implement the ANN for the prediction of permittivity of SUTs is demonstrated. Additionally, the challenges and future prospects of ANN-assisted microwave sensors are examined.
Advancements in Crop Yield Prediction Using Deep Learning Algorithms
Authors: Ajina A. , Jaya Christiyan K. G. , Sunithbabau L. , Natarajan Rajesh , Nandyal Vishal
Published: February 2025

Agriculture is at a critical crossroads due to the growing problems brought about by changing environmental conditions, particularly the effects of global warming and climate uncertainty. There has never been a greater urgent need for agricultural techniques to develop and adapt. Machine learning can also help farmers identify the most profitable crops to plant based on market demand and environmental factors. By analyzing historical market data and weather patterns, machine learning models can predict the demand for different crops and suggest optimal planting times and locations. Crop yield prediction is one of the challenging problems in precision agriculture, and many models have been proposed and validated, so crop yield prediction models can estimate the actual yield reasonably, but a better performance in yield prediction is still desirable. This study aims to investigate the potential of deep learning algorithms, such as convolutional neural networks (CNN), long short-term memory networks (LSTM), and deep neural networks (DNN), as revolutionary tools.
ANN Prediction Analysis of Engine Performance and Emissions Characteristics Using a New Set of Plastic Pyrolysis Oil Blended With Pure Diesel
Authors: Tiwari Amit , Varshney Pooja , Swarnkar Harshita , Pandel Neny , Vasnani Himanshu , Akram Muhammad
Published: February 2025

Artificial Neural Network a soft tool enabled by Artificial intelligence was utilized to accurately predict engine performance and emissions analysis using a new set of plastic pyrolysis oil blended with pure diesel. Under various loads, blends, and speeds, this chapter analyzed the effect of plastic pyrolysis oil (PPO) on a diesel engine's performance and emissions, which were used to forecast performance and emissions. The ANN models have the potential to produce a more accurate estimate of the brake thermal efficiency, brake-specific fuel consumption, and emission performance parameters.
Artificial Neural Network Predictions of Heat Transfer of Flat Plate Collector With Hybrid Nanofluids
Authors: Syam Lingala , Mesfin Solomon , Rao Veeredhi Vasudeva
Published: February 2025

The Nusselt number, heat transfer, and friction factor of a flat plate collector operating with hybrid nanofluids of Al2O3-CuO and water are utilized in the Support Vector Regression method of artificial neural networks. The volume loadings used in the experiments were 0.048%, 0.096%, 0.144%, 0.192%, and 0.24%. The experiments ran from 09:00 to 16:30 hours. Time zone 1 (09:00 to 13:00 hr) and time zone 2 (13:00 to 16:30) are applied. Nusselt number is increased by 20.43% at time zone-1, at 13:00 hours, at 0.24% vol. and at a Reynolds number of 364.66, and by 14.08% at time zone-2, at 16:30 hours, at 0.24% vol. and at a Reynolds number of 211.23, respectively, above the base fluid. Similarly, the friction factor is increased by 15.34% and 11.50% above the base fluid for time zones 1 and 2, respectively, at 13:00 and 16:30, at 0.24% vol. and Reynolds numbers 364.66 and 211.23. The support vector regression algorithm in use makes accurate predictions about the values. Nusselt number, heat transfer, and friction factor have correlation values of 0.99497, 0.9947, and 0.9995.
Urban Transportation Planning
Authors: Singh Sitesh Kumar , Alasali Bader Eddin , Belbase Yuvraj
Published: February 2025

The system complexities in urban transportation are increasing. It is difficult for modular planning methods to predict traffic changes, people traveling patterns and mobility needs to develop for a sustainable context. To address this, there has been a paradigm shift in the adoption of Artificial Neural Networks (ANNs). ANNs are capable of understanding patterns of traffic data, and thus can be employed to predict traffic flow, forecast public transit demand or determine the accident risk. The ability to predict these trends enables the country to proactively manage traffic, make smart investments into local safety infrastructure and optimize its public transport system. ANNs are good at discerning patterns in massive data sets and evolving when conditions change. There are, however, difficulties in terms of data availability model interpretability and computational requirements. Given the ongoing improvements in data generation and computational resources, ANNs can revolutionize urban transport planning, creating tomorrow's cities of better functioning, sustainable, and equitable.
The Future of Education
Authors: Ordaz Oliver Mario Oscar , Moreno Evelin Gutiérrez , Ordaz Oliver Jesus Patricio , Hernández Javier Hernández
Published: February 2025

In this chapter, the main educational trends are examined, including the use of technologies such as artificial intelligence to personalise learning; immersive technologies, such as virtual reality, augmented reality, and haptic interfaces, to create more engaging learning experiences; and online and hybrid education methods and tools that enhance flexibility and accessibility to knowledge. This document analyses how the gamification of teaching fosters student motivation. It also explores how technology is transforming teaching and learning, as well as how university students perceive the benefits and opportunities of transitioning from the traditional educational model. According to a survey conducted among Mexican students, the enthusiasm of both educators and learners to embrace these changes is pivotal. Despite the widespread availability of technological devices among students, they continue to face challenges such as connectivity issues and a lack of suitable study spaces.
The Smart Education Contribution to Lifelong Learning
Authors: Rodríguez Reyna del Carmen Martínez , Corona Lilia Benítez , Márquez Jorge Hernández , Azpeitia Luis Arturo Guerrero , Orán Morayma Muñoz , Robles Gutiérrez Martha Patricia
Published: February 2025

This paper critically analyses the contributions of smart education to lifelong learning. It begins by addressing the complexity of knowledge in times characterised by Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) from the perspective of learning ecologies. This approach establishes a foundation to emphasise the importance of developing resilient capacities in the new digital era, which necessitates the transformation of pedagogical strategies through smart education. While tools have emerged that can integrate certain sectors of the population and enhance the speed of information management, challenges persist that demand critical thinking for more effective utilisation of personal and technological resources. The paper concludes that educational systems must undergo transformation, not only by empowering the potential of educational actors through intelligent spaces but also by fostering awareness of future educational challenges and opportunities.
Transformative Learning With Advanced Technologies
Authors: Yadav Seema
Published: February 2025

Immersive technologies, particularly Virtual Reality (VR) and Augmented Reality (AR), are transforming education by enhancing interactive and experiential learning. These technologies create engaging environments in which learners can explore, manipulate, and interact with content, fostering deeper understanding and retention. Trends such as increasingly affordable hardware, the integration of artificial intelligence for personalised learning, and cloud-based platforms are making VR and AR more accessible. However, challenges such as cost, technical proficiency, and data privacy must be addressed. With advancements in technology and thoughtful design, VR and AR have significant potential to reshape education through personalised, collaborative, and inclusive learning experiences. This chapter examines the potential of VR and AR to create immersive learning environments, enhancing educational outcomes through interactive and engaging methodologies.
Unbundling Digital Learning in Higher Education in Iraq
Authors: Abdul-Jabbar Wisam Kh. , Alkilabi Ahmed
Published: February 2025

This chapter contributes to the theories and principles underpinning the challenges of digital pedagogy in higher education in Iraq. The chapter adopts mixed research methods to collect empirical evidence to identify pedagogical and instructional challenges for digital learning in higher education in Iraq, which can be extended and applied to other developing countries. How and to what extent can the implementation of digital education help or hinder the learning process within the context of higher education in Iraq? The study will explore the concept of unbundling as a proposed conceptual response to the identified challenges. Unbundling digital pedagogy refers to organizational changes in software, policy discourse, and instructional strategies. Unbundling addresses mass access to higher education by emphasizing personalization, flexibility, and options that could accommodate institutional missions (Morris et al, 2020). This study proposes that higher education in Iraq can rebundle its digital practices and translate its E-learning endeavors into an educational reality.
Use of Reinforcement Learning Algorithms in the Development of Pedagogical Methodologies
Authors: Aguilar-Ortiz Jaime , Zamudio-García Víctor Manuel , Serrano-Franco Glendamira
Published: February 2025

This document presents an innovative approach to applying artificial intelligence (AI) reinforcement learning techniques in contemporary pedagogical methodologies such as Project-Based Learning (PBL), Flipped Classroom, and Gamification. Through 20 specific examples, the document explores the customization of learning, the formation of teams based on complementary skills, automated feedback, adaptation of educational content, and more. It highlights the importance of adaptation and customization in learning, underlining the potential of reinforcement learning techniques to transform educational experiences. Additionally, specific reinforcement learning methods and strategies, such as Q-Learning and Deep Q-Networks, are discussed from the 20 previous examples in a practical manner and with code to illustrate their application in the educational context. This approach not only advocates for a revolution in pedagogical methodologies through the use of AI but also provides a solid foundation for ongoing research and development in this emerging field.
Artificial Intelligence in Control and Automation Education
Authors: Márquez-Vera Marco Antonio , Noriega-Sánchez Andrea Guadalupe , Ortega-Mendoza Rosa María , Eguiluz-Ruiz Brenda
Published: February 2025

In this dissemination work, we mention the topics covered in a course called Advanced Control, where Artificial Intelligence techniques are employed in the design of controllers. The main topics are fuzzy logic and artificial neural networks, as well as their use in Control Engineering. We also provide some comments on these branches of Artificial Intelligence, their use, and how to implement them in hardware. There are several specialized simulation programs with packages, toolboxes, or atoms where these techniques can be tested, as well as various scientific journals that showcase applications and developments of artificial intelligence in engineering. Due to the novelty and interest of these topics, they have been well-received by the students.
The Role of the Metaverse in Education
Authors: Rohini Rohini
Published: February 2025

This article describes how the metaverse is being used in the education sector and its advantages. The broad term “metaverse” encompasses all future digital developments. Metaverse basically focuses on creating a separate virtual world for users based on their thinking and augmented reality. Metaverse is made possible by using virtual reality devices that support the users and take them to a 3D environment. As a result, in order for sectors like education to remain accessible and survive for a long time, the systems must be updated to accommodate new technology. Digital resources have many advantages, including portability and interactive elements. Still, there are a few obstacles. A summary of a number of metaverses in education's facets is provided in this chapter. The four different varieties of the metaverse will be defined in this article, along with the possibilities and restrictions of its educational uses. The four categories listed on the metaverse roadmap are virtual reality, augmented reality, and lifelogging.
Educational Leadership, Tech Integration Strategies, Success Stories, and Lessons Learned
Authors: Cornejo Arturo Austria , Escorza Brenda Berenice García , García Márquez Marco Antonio , Martínez Mireles Josué Román , Flores Jazmín Rodríguez
Published: February 2025

This chapter highlights the importance of effective leadership and the influence of organizational culture in the educational field. The interaction between leadership and organizational culture is explored to promote a culture based on shared values, strengthen the sense of belonging and commitment, and create an environment conducive to learning and excellence. It provides theoretical knowledge, practical tools, study cases and best practices to inspire educational leaders to cultivate a culture of respect, collaboration and excellence in educational institutions, contributing to the success of all involved in the educational process.
The Dawn of Big Data
Authors: Ayyalasomayajula Sailaja
Published: February 2025

Big Data represents a revolutionary shift in how information is gathered, analyzed, and utilized across industries and academic disciplines. This book chapter explores the origins and early promise of Big Data, charting its evolution as a transformative concept. It delves into the defining characteristics of Big Data—Volume, Velocity, Variety, and Veracity—while highlighting its potential to address complex societal and technical challenges. The chapter outlines the technological advancements that enabled large-scale data storage, processing, and analytics, emphasizing their role in fostering innovation in fields such as healthcare, finance, and ecological science. Additionally, it examines the broader implications of datafication on decision-making, operational efficiency, and knowledge creation. By tracing the historical context and current applications of Big Data, the chapter provides a comprehensive understanding of its capabilities and the challenges it poses for ethical governance and sustainability in a data-driven world.
Big Data Revolution
Authors: Mobo Froilan Delute , Miłek Katarzyna , Garcia Ana Liza
Published: February 2025

The Big Data Revolution has disrupted the process of collection, analysis, and utilization of big data in different fields, staking the future of business, governance, healthcare, and the whole of society at large. This chapter aims at discussing the definition of big data, its evolution process, and its huge impact on various fields. This paper covers the benefits of big data and issues related to the use of this technology, including privacy, security, and ethical issues. In achieving these objectives, this chapter aims to give a detailed analysis of the future understanding of big data.
Review on Big Data Analytics Applications
Authors: Bahadur Preeti Singh , Kumar Jay Krishna , Dixit Shivanshu , Verma Shubham , Maurya Shubham , Jigar Danish
Published: February 2025

Decision-makers in the age of digitization now have easy access to massive volumes of data. Big data are datasets that are challenging to manage with conventional tools and operations due to the fact that their operations are not only big but also extremely changeable and ever-changing. Owing to the exponential growth of this type of data, methods for managing and deriving insights and value from these datasets need to be generated and researched. Furthermore, decision-makers must be capable to draw insightful conclusions from a wide variety of quickly evolving data, including social network data, everyday transactional data, and consumer interactions. Applying advanced analytics methods to massive data sets is known as big data analytics, can be castoff to deliver such value. This study aims to investigate the various analytics methods and resources for working by big data, along with the prospects that arise from utilising big data analytics across multiple decision-making domains.
Optimizing Load Distribution in Big Data Ecosystems
Authors: Diwakar Ravikant , Sharma Rahul , Nayak Deviprasad , Mohapatra Hitesh
Published: February 2025

In today's digital world, managing large volumes of data, known as “Big Data,” presents a significant challenge due to its volume and complexity. Regular software often struggles to handle this, necessitating the use of Load Balancing—a crucial aspect of cloud computing. Load balancing distributes workloads across resources, preventing slowdowns, reducing processing time, and optimizing system performance. This paper explores load balancing strategies in big data processing, including Round Robin, Least Connection, Resource-Based, Task-Based, and Dynamic methods, discussing their pros and cons. Effective load balancing ensures optimal resource usage, higher scalability, increased availability, dependability, fault tolerance, and improved performance. The paper provides a literature review, proposes a model for optimal load balancing, and tests it in a simulated environment, highlighting key findings and suggesting future research directions.
Artificial Intelligence, Machine Learning, and the Revival of Big Data in Pharmaceutical Sciences
Authors: Gudimitla Raveendra Babu , Babu Medarametla Kishore , Bhimana Sasidhar , Dasu Chapala Deva , Perla Swathi
Published: February 2025

The integration of Artificial Intelligence (AI), Machine Learning (ML), and Big Data is transitioning the pharmaceutical industry, specifically in drug discovery, process optimization, and clinical development. This revolution enhances drug target identification through advanced data analytics, empowering the discovery of novel biomarkers and compounds. AI-driven high-throughput and virtual screening methods accelerate the identification of promising drug candidates, while predictive modeling improves the accuracy of drug efficacy predictions. In manufacturing, AI optimizes supply chain management and quality control through real-time monitoring and predictive maintenance, ensuring efficient production processes.
Greenwashing in the High-End Fashion Industry
Authors: Moroaca Andra-Maria , Recio-Menéndez Manuel
Published: February 2025

This chapter examines greenwashing in the high-end fashion industry, exploring challenges and proposing adaptive strategies for sustainable development. It establishes a theoretical framework defining key concepts such as greenwashing, Sustainable Development Goals, and Corporate Social Responsibility. Through case studies of prominent brands, the chapter exposes various forms of greenwashing, from misleading campaigns to inconsistent practices. By critically examining these practices, the chapter aims to foster a more transparent, accountable, and genuinely sustainable high-end fashion sector. It addresses challenges luxury brands face in implementing truly sustainable practices, such as supply chain complexities and the tension between profit margins and environmental responsibility. The chapter concludes with recommendations for stakeholders and suggestions for future research to promote authentic sustainability in luxury fashion.
Nexus Between Sustainable Business Practices, SDGs, and Financial Performance
Authors: Sharma Eliza , Sathish M. , Gadekar Manjiri
Published: February 2025

The research aims to study the Sustainable Business Practices (SBPs) of top Indian companies and how these companies are contributing towards attaining sustainable development goals (SDGs). The research was based on a mixed method approach where SBPs and their linkage have been analyzed using content analysis, and the impact on financial performance has been measured using correlation and regression analysis. The companies' annual reports and business sustainability reports have been used to collect secondary data related to the SBPs of companies. ESG scoring of the company, and the individual score of the E= Environment, S= Social, and G= Governance, have been derived from the ESG rating of “BLOOMBERG” for the last five years. The return on equity has been taken as a proxy variable for the financial performance of the companies. The current study has taken a sample of ten companies from eight different sectors/industries listed on the BSE ESG 100 Index. The data period of the study was from 2017 to 2022.
Integrating Theories and Charting Future Research Directions in Green Marketing
Authors: Agarwal Barkha , Turkan Ittequa
Published: February 2025

Green marketing is crucial today, promoting sustainable practices and meeting the demand for eco-friendly products. By emphasizing sustainable production, it helps companies stand out and attract environmentally conscious consumers. This paper provides a framework to understand green marketing, its evolution, and its impact on consumer cognitive, affective, and behavioral factors influencing purchase decisions. It defines green marketing and explores its history, highlighting key milestones. The study reviews nine consumer-level theories in three groups, detailing each theory's relevance to green marketing. Cognitively, green marketing raises awareness and perceptions of eco-friendly products. Affectively, it connects with consumers' emotions, fostering positive brand associations. Behaviorally, it encourages choosing green products. The paper also discusses future research directions, aiming to enhance understanding of how green marketing influences consumer purchase decisions
Evolving Landscape of Green Marketing
Authors: Singh Niharika , Pathak Ankita
Published: February 2025

This paper provides a bibliometric analysis of green marketing research conducted between 1998 and 2023. The objective was to identify advancements, productive countries, influential organizations, researchers, articles, and academic publications in the field. The study analyzed the latest developments in green marketing research during the specified time frame, highlighting nations, organizations, researchers, articles, and academic publications with high productivity and influence. The analysis revealed the top 10 countries with the highest productivity, most cited journals, and proficient authors. The findings demonstrate the increased focus on green marketing, Eco Marketing, and green products within the marketing field over the past 25 years.
The Link Between Customer Perception and Green Marketing
Authors: Yadav Suraj Jaywant
Published: February 2025

This study explores how green marketing influences customer perceptions in the Indian hotel industry, focusing on sustainable practices. It combines quantitative surveys and qualitative interviews for comprehensive data. Quantitative analysis (descriptive statistics, correlation, regression) examines links between green initiatives, customer satisfaction, loyalty, and brand perception. Qualitative methods (thematic, content analysis) provide insights into sustainable practices' implementation and effectiveness. Results show a positive correlation between green initiatives and favorable customer perception, influenced by demographics. Despite challenges (cost, resources), hotels benefit from improved environmental credentials and operational efficiency. Recommendations include transparent communication, investment in green tech, and adaptive strategies to enhance customer engagement, competitive advantage, and sustainable development in hospitality.
Green Transition in the Restaurant Industry
Authors: Yıldırım Seda , Yıldırım Durmus Cagrı , Rajamanickam Sivarethinamohan
Published: February 2025

The Green economy approach, which originated with the concept of sustainability, has prompted policymakers to adopt new strategies. Aligned with the goal of Sustainable Development, both developed and developing countries are working towards achieving a green transition in economic, environmental, and social domains. While the field of food has a long history of literature on security and sustainability, it has recently garnered increased attention in the context of the green transition. In essence, various disciplines related to food products and the food industry has evolved into a new area of research, exploring alternative strategies and applications within sustainability and food security. This chapter aims to review new trends in food industry through examining recent global indicators and implications. As it is purposed, it is planned to give a brief framework for food waste management, food packaging, food production and food security issues.
Autochtonous Emergomyces pasteurianus subcutaneous infection in an Italian immunocompromised patient: a case report and review
Authors: Farina Claudio , Cavallini Marco , Gambini Daniele , Parietti Michele , Tebaldi Alessandra , Guarneri Davide , Sena Paolo
Published: February 2025

We describe the second case of infection by Emergomyces pasteurianus that occurred in Italy. The patient presented ulcerated nodular lesions primarily in the forehead, beneath the orbital and nasal areas, but also in the neck and fingers in the early stages. Treatment involved amphotericin B, followed by long-term itraconazole, which resulted in complete clinical resolution. A review of the literature is also included.
Knowledge and awareness of Palestinian health care professionals towards probiotics, prebiotics and synbiotics: a cross-sectional study from Palestine
Authors: Zaid Abdel Naser , Ali Iyad , Jaradat Nidal , Al Ramahi Rowa , Hmeidat Rula , Nofal Sanabil , Diab Raneem , Nasser Manwa , Rabaya Heba , Tamimi Mohamed , Shawahni Ramzi
Published: February 2025

Probiotics are live microorganisms believed to confer health benefits when consumed appropriately. Prebiotics are non-digestible food components that promote health by encouraging the growth or activity of beneficial microorganisms. Synbiotics are a combination of probiotics and prebiotics. This study aimed to assess the knowledge and awareness of Palestinian healthcare professionals regarding probiotics, prebiotics, and synbiotics. A cross-sectional study was conducted across the West Bank using a structured questionnaire, and descriptive analysis was performed using SPSS. The results indicated that 68.5% of physicians and 83.4% of pharmacists were aware of probiotics, whereas only 37% of physicians and 48% of pharmacists had knowledge of prebiotics. Awareness of synbiotics was even lower, with only 20% of physicians and 26.6% of pharmacists reporting familiarity. These findings suggest that while there is a reasonable level of knowledge about probiotics, awareness of prebiotics and synbiotics is significantly lacking, which limits their use. Enhancing knowledge of these products could be facilitated through workshops, ongoing education, and the involvement of medical representatives.