The development of artificial intelligence (AI) involves the creation of computer systems that can do activities that would ordinarily require human intelligence, such as visual perception, speech recognition, decision making, and language translation. Through increasingly complex programming approaches, it has been transforming and advancing the discipline of computer science. The Handbook of Research on AI Methods and Applications in Computer Engineering illuminates how today’s computer engineers and scientists can use AI in real-world applications. It focuses on a few current and emergent AI applications, allowing a more in-depth discussion of each topic. Covering topics such as biomedical research applications, navigation systems, and search engines, this premier reference source is an excellent resource for computer scientists, computer engineers, IT managers, students and educators of higher education, librarians, researchers, and academicians.

The implementation of virtual environments in education has been rapidly increasing in frequency after the COVID-19 pandemic. As these technologies rise in popularity, it is essential to understand the roles digital technologies play in fostering connections and learning, the affordances of digital texts and spaces for virtual classroom experiences, the difficulties educators have faced and how these practices have been crafted to meet these challenges, and more. Innovations in Digital Instruction Through Virtual Environments advances knowledge about the pedagogical decisions and lived experiences of researchers and educators both before and after the COVID-19 pandemic. It features research from those who have worked to sustain and develop digital/media pedagogical practices. Covering topics such as active learning environments, emotional labor, and textual engagements, this premier reference source is an excellent resource for educators and administrators of both K-12 and higher education, pre-service teachers, teacher educators, librarians, researchers, and academicians.

Blockchain has become the cornerstone of technologies, supported by others including Big Data and Artificial Intelligence (AI). Originating from cryptocurrency, it transcends boundaries, finding resonance in finance, healthcare, e-governance, and beyond. While blockchain relies on a peer-to-peer approach, enabling nodes to collaborate without the shackles of a central authority, appropriate monitoring and updating of these technologies is a constant necessity. This is especially true for healthcare data systems, where data privacy and security concerns, especially with sensitive health information are paramount. Threads of automation in artificial intelligence (AI) weave through sectors such as business, finance, healthcare, marketing, and governance. Industrial Applications of Big Data, AI, and Blockchain delves into the pulsating realms of big data, AI, and blockchain. From natural language processing's eloquent interpretation of human language to the prowess of AI algorithms in predictive tasks, this book explores how AI enhances decision-making accuracy, catalyzing a paradigm shift in diverse industries. This book is ideal for researchers, business visionaries, tech enthusiasts, and curious minds eager to fathom the transformative potential of these technologies.

With the advancement in computing technologies, the need for power is also increasing. Approximately 3% of the total power consumption is spent by data centers and computing devices. This percentage will rise when more internet of things (IoT) devices are connected to the web. The handling of this data requires immense power. Energy Systems Design for Low-Power Computing disseminates the current research and the state-of-the-art technologies, topologies, standards, and techniques for the deployment of energy intelligence in edge computing, distributed computing, and centralized computing infrastructure. Covering topics such as electronic cooling, stochastic data analysis, and energy consumption, this premier reference source is an excellent resource for data center designers, VLSI designers, network developers, students and teachers of higher education, librarians, researchers, and academicians.

In the current technological world, Web services play an integral role in service computing and social networking services. This is also the case in the traditional FREG (foods, resources, energy, and goods) services because almost all traditional services are replaced fully or partially by Web services. Handbook of Research on Demand-Driven Web Services: Theory, Technologies, and Applications presents comprehensive and in-depth studies that reveal the cutting-edge theories, technologies, methodologies, and applications of demand-driven Web, mobile, and e-business services. This book provides critical perspectives for researchers and practitioners, lecturers and undergraduate/graduate students, and professionals in the fields of computing, business, service, management, and government, as well as a variety of readers from all the social strata.

This book constitutes the proceedings of the First International Conference on Bridging the Gap between AI and Reality, AISoLA 2023, which took place in Crete, Greece, in October 2023. The papers included in this book focus on the following topics: The nature of AI-based systems; ethical, economic and legal implications of AI-systems in practice; ways to make controlled use of AI via the various kinds of formal methods-based validation techniques; dedicated applications scenarios which may allow certain levels of assistance; and education in times of deep learning.

The demand for skilled data scientists is rapidly increasing as more organizations recognize the value of data-driven decision- making. Data science, data management, and data mining are all critical components for various types of organizations, including large and small corporations, academic institutions, and government entities. For companies, these components serve to extract insights and value from their data, empowering them to make evidence-driven decisions and gain a competitive advantage by discovering patterns and trends and avoiding costly mistakes. Academic institutions utilize these tools to analyze large datasets and gain insights into various scientific fields of study, including genetic data, climate data, financial data, and in the social sciences they are used to analyze survey data, behavioral data, and public opinion data. Governments use data science to analyze data that can inform policy decisions, such as identifying areas with high crime rates, determining which regions need infrastructure development, and predicting disease outbreaks. However, individuals who are not data science experts, but are experts within their own fields, may need to apply their experience to the data they must manage, but still struggle to expand their knowledge of how to use data mining tools such as RapidMiner software. Principles and Theories of Data Mining With RapidMiner is a comprehensive guide for students and individuals interested in experimenting with data mining using RapidMiner software. This book takes a practical approach to learning through the RapidMiner tool, with exercises and case studies that demonstrate how to apply data mining techniques to real-world scenarios. Readers will learn essential concepts related to data mining, such as supervised learning, unsupervised learning, association rule mining, categorical data, continuous data, and data quality. Additionally, readers will learn how to apply data mining techniques to popular algorithms, including k-nearest neighbor (K-NN), decision tree, naïve bayes, artificial neural network (ANN), k-means clustering, and probabilistic methods. By the end of the book, readers will have the skills and confidence to use RapidMiner software effectively and efficiently, making it an ideal resource for anyone, whether a student or a professional, who needs to expand their knowledge of data mining with RapidMiner software.

In today's rapidly evolving educational landscape, traditional teaching methods often fail to equip students with the skills necessary for success in the 21st century. The siloed approach to education, where subjects are taught in isolation, must reflect the interconnected nature of modern challenges. This disconnect between traditional educational models and the needs of the future workforce is a serious concern among educators. They face the challenge of preparing students for professions that still need to be created using tools and technologies that are still emerging. Revolutionizing Curricula Through Computational Thinking, Logic, and Problem Solving offers a transformative solution to this challenge. By advocating for computational thinking as a fundamental skill set applicable across all academic disciplines, the book provides educators with the tools to bridge this gap. It introduces computational thinking not just as a technical skill but as a way of problem-solving and logical reasoning that enhances critical thinking across subjects. Through practical lesson plans, case studies, and strategies, educators can seamlessly integrate computational thinking into their classrooms, preparing students for the complexities of the modern world.

Technology Management and Its Social Impact on Education, edited by PC Lai from the University of Malaya, Malaysia, is an essential resource for anyone interested in understanding the transformative role of technology in education and its impact on society. The book covers a broad range of education concepts, strategies, and sectors, including innovation in education, green education, technology management in education, leadership, management & and HR practices, services, and more. It also examines the challenges and opportunities of education value creation, knowledge management, technology transfer, internationalization of education, innovative supply chain, social and economic impact, and social business in the education world. This book provides a forum for the exchange of research ideas and practices and is a reference convergence point for academicians, professionals, managers, and researchers in the entrepreneurship field, including development practitioners. It offers invaluable insights into the transformative role of technology in education and is a must-read for anyone interested in staying at the forefront of education and technology. Whether you are an academician, a practitioner, a researcher, a student, a writer, a blockchain or NFT community member, a corporate manager, a policy maker, or a government official, this book will equip you with the knowledge and skills necessary to navigate the complex relationship between technology, education, and society.

NeutroAlgebra and AntiAlgebra were extended to NeutroGeometry and AntiGeometry in order to catch the Non-Euclidean Geometries. In the real world, the spaces and the elements that populate them and the rules that apply to them are not perfect, uniform, homogeneous, or complete. They are fragmentary and disparate, with unclear and conflicting information, and they do not apply in the same degree to each element. Therefore, these partial, hybrid, and mixed structures are necessary. NeutroGeometry, NeutroAlgebra, and SuperHyperAlgebra in Today's World presents applications of many NeutroStructures in our real world and considers NeutroGeometry and AntiGeometry as new fields of research that resemble everyday life. Covering key topics such as hyperbolic geometry, elliptic geometry, and AntiGeometry, this reference work is ideal for mathematicians, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.