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A multicore platform uses distributed or parallel computing in a single computer, and this can be used to assist image processing algorithms in reducing computational complexities. By implementing this novel approach, the performance of imaging, video, and vision algorithms would improve, leading the way for cost-effective devices like intelligent surveillance cameras. Multi-Core Computer Vision and Image Processing for Intelligent Applications is an essential publication outlining the future research opportunities and emerging technologies in the field of image processing, and the ways multi-core processing can further the field. This publication is ideal for policy makers, researchers, technology developers, and students of IT.

Image and Video Processing is an active area of research due to its potential applications for solving real-world problems. Integrating computational intelligence to analyze and interpret information from image and video technologies is an essential step to processing and applying multimedia data. Emerging Technologies in Intelligent Applications for Image and Video Processing presents the most current research relating to multimedia technologies including video and image restoration and enhancement as well as algorithms used for image and video compression, indexing and retrieval processes, and security concerns. Featuring insight from researchers from around the world, this publication is designed for use by engineers, IT specialists, researchers, and graduate level students.

Robotic systems consist of object or scene recognition, vision-based motion control, vision-based mapping, and dense range sensing, and are used for identification and navigation. As these computer vision and robotic connections continue to develop, the benefits of vision technology including savings, improved quality, reliability, safety, and productivity are revealed. Robotic Vision: Technologies for Machine Learning and Vision Applications is a comprehensive collection which highlights a solid framework for understanding existing work and planning future research. This book includes current research on the fields of robotics, machine vision, image processing and pattern recognition that is important to applying machine vision methods in the real world.

Multimedia represents information in novel and varied formats. One of the most prevalent examples of continuous media is video. Extracting underlying data from these videos can be an arduous task. From video indexing, surveillance, and mining, complex computational applications are required to process this data. Intelligent Analysis of Multimedia Information is a pivotal reference source for the latest scholarly research on the implementation of innovative techniques to a broad spectrum of multimedia applications by presenting emerging methods in continuous media processing and manipulation. This book offers a fresh perspective for students and researchers of information technology, media professionals, and programmers.

In today's world, the integration of Artificial Intelligence (AI) with Communication Technologies (ICT) has become an essential aspect of research and development. However, this convergence poses numerous challenges and bottlenecks that need to be addressed. Introducing AI and Its Convergence with Communication Technologies, a research book edited by a team of expert scholars, including Badar Muneer, Faisal Shaikh, Naeem Mahoto, Shahnawaz Talpur, and Jordi Garcia. This book offers an interdisciplinary platform that provides a comprehensive overview of the state-of-the-art research and practical challenges related to the AI convergence with ICT. It is designed for engineers, professionals, scientists, and academicians, providing them with insights into the ICT industry and research from an AI expert perspective. Readers associated with the field of computer science, information technology, software engineering, telecommunication, and electronics engineering will find this book to be beneficial. AI and Its Convergence with Communication Technologies covers a wide range of topics, including recent advancements and applications in AI; its uses in signal processing, mobile and modern wireless networks, decision-making and policy-making; and AI towards automation. It also addresses the potential applications of AI in the domains of national defense, military technology, hybrid warfare, medical & health sciences, and energy-efficient systems. Furthermore, the book highlights the strengths and weaknesses of AI convergence with ICT, along with emerging frontiers and recommendations. The book offers a brief history of AI in ICT and a comprehensive introduction to ICT-related methods and techniques in artificial intelligence and machine learning. It also covers data management with AI, data fusion, and knowledge discovery, as well as the use of AI in digital image processing. The book also emphasizes the role of AI in extracting knowledge and making predictions in decision-making strategies for businesses, management, and governance. Overall, this book provides a significant contribution to the understanding of AI and its convergence with communication technologies. While presenting a general trend and emergence of AI in ICT and related areas, it also highlights the challenges, limitations, and emerging frontiers. This book is a must-read for scholars and researchers who seek to understand the growing intersection of these two technologies and how it impacts modern industries and research.

Chatbots powered by artificial intelligence (AI) have captivated the academic world as tools for human-like interaction across various settings. Within the realm of education, AI-powered chatbots, such as ChatGPT, hold the potential to revolutionize teaching, learning, and research processes. By simulating human conversation through vast data and machine learning algorithms, generative AI has unveiled new opportunities for personalized and adaptive learning experiences. Facilitating Global Collaboration and Knowledge Sharing in Higher Education With Generative AI delves into the promising prospects and challenges of applying generative AI in education while employing a critical interdisciplinary perspective. The book offers comprehensive insights into the transformative effects of generative AI on teaching, learning, and research. However, the application of generative AI in education also brings ethical, pedagogical, and technical challenges to the forefront. Concerns over privacy, data protection, and the impact of automation on human interaction and creativity demand thorough examination and practical solutions. Intended for educators, researchers, and administrators in higher education institutions, as well as policymakers and industry professionals at the intersection of AI and higher education, this book highlights innovative approaches and best practices for integrating generative AI into various educational aspects. It explores the potential of generative AI in fostering global collaboration and knowledge sharing, addressing cross-cultural understanding, and promoting internationalization in educational settings. The book encompasses a wide range of themes, including the impact of AI-generated content on student engagement and performance in online learning environments, ethical implications of automating education through AI-powered chatbots, personalization of learning experiences for diverse student populations, and the challenges of integrating generative AI into traditional classroom settings. Additionally, the book addresses generative AI's potential to enhance accessibility and inclusivity in education for individuals with disabilities, support lifelong learning initiatives, and revolutionize distance education and remote learning. It also delves into its role in promoting intercultural understanding, critical thinking, and global competency.

In today's complex and fast-paced world, decision-making is critical to problem-solving across industries and academia. However, traditional optimization techniques often need help to cope with the challenges posed by dynamic and intricate environments. This limitation hampers decision-makers'ability to tackle complex problems and seize opportunities effectively. As such, there is a pressing need for innovative approaches that can enhance decision-making processes, enabling individuals and organizations to navigate uncertainty and achieve optimal outcomes. Bio-Inspired Intelligence for Smart Decision-Making offers a compelling solution to this challenge. By exploring the intersection of bio-inspired optimization techniques and decision-making, this book presents a fresh perspective that can revolutionize decisions. The book introduces readers to powerful bio-inspired algorithms such as genetic algorithms, swarm intelligence, and evolutionary strategies through a multidisciplinary lens that encompasses computer science, artificial intelligence, optimization, and decision science. These algorithms mimic natural systems'efficiency and adaptability, offering a robust framework for addressing complex decision-making problems in diverse fields. This book equips readers with a deep understanding of bio-inspired optimization principles and provides practical guidance on their implementation in various decision-making scenarios. By combining theoretical foundations with real-world case studies, the book enables readers to grasp both the conceptual framework and the practical application of bio-inspired techniques for intelligent decision-making. Whether you are a researcher, a graduate student, or a professional seeking to enhance your decision-making capabilities, this book is an invaluable resource that will empower you to leverage nature's wisdom for optimal decision-making in your respective field.

As libraries transition into the digital age, they encounter a pressing challenge: outdated information systems hinder their ability to meet the diverse needs of patrons. Traditional library management systems struggle to cope with the demands of modern users, resulting in inefficient resource allocation, limited accessibility, and disjointed user experiences. This disconnect between antiquated systems and evolving user expectations poses a significant barrier to libraries striving to remain relevant in an increasingly digital world. Improving Library Systems with AI: Applications, Approaches, and Bibliometric Insights presents a comprehensive solution to this pressing problem. By integrating modern digital tools and technologies, libraries can revolutionize their information systems, enhancing accessibility, efficiency, and user satisfaction. This book offers practical insights and strategies for modernizing library services and operations, from digitizing physical resources to implementing advanced search algorithms and data analytics. Librarians, administrators, and technology providers will find invaluable guidance on navigating the complexities of digital transformation and maximizing the impact of their efforts. Through case studies, best practices, and in-depth analysis, this book equips stakeholders with the knowledge and tools to navigate the digital landscape and future-proof their libraries. The principles outlined in this book empower libraries to overcome the challenges of outdated information systems and emerge as vibrant, dynamic hubs of knowledge and innovation.

The shift to virtual education has presented numerous challenges, including maintaining student focus and participation. Traditional methods of instruction often need to catch up in capturing the attention of digital learners, leading to disengagement and reduced learning outcomes. However, there is a solution at hand. AI Algorithms and ChatGPT for Student Engagement in Online Learning offers a comprehensive approach to leveraging artificial intelligence (AI) algorithms and ChatGPT to enhance student engagement in digital classrooms. This book addresses the pressing need for innovative strategies to keep students actively involved in their online learning journey. By harnessing the power of AI algorithms, educators can personalize learning paths to suit individual student needs, ensuring that content is relevant and engaging. Additionally, ChatGPT serves as a virtual assistant, providing students with instant feedback and support, fostering a sense of connection to the learning process. AI Algorithms and ChatGPT for Student Engagement in Online Learning is a valuable resource for educators, students, researchers, and practitioners seeking to enhance the online learning experience. Through a deep dive into the role of AI in education, this book equips readers with the knowledge and tools needed to create dynamic and engaging online learning environments. Whether you want to improve student participation or enhance learning outcomes, this book offers practical insights and strategies to revolutionize online education.

In today's rapidly advancing digital world, governments are increasingly relying on technology to enhance security systems and streamline governance. However, this growing reliance on digital platforms and data collection also presents significant challenges. Cybersecurity threats and privacy concerns pose large risks to sensitive information and can potentially leading to inaccuracies or breaches within deep learning models. There is a pressing need for comprehensive solutions that address these security issues and protect valuable data in the realm of e-governance. Futuristic e-Governance Security With Deep Learning Applications is a timely and indispensable resource that offers a holistic approach to tackling the security challenges of the digital era. The book presents a global perspective on the integration of intelligent systems with cybersecurity applications, highlighting cutting-edge techniques and methodologies to safeguard deep learning models from security attacks and privacy vulnerabilities. By exploring the latest advances and countermeasures in deep learning, this book equips scholars, researchers, and industry experts with the knowledge and tools they need to address security concerns and develop robust e-governance systems. This comprehensive volume not only sheds light on the current state-of-the-art methods but also delves into future trends and challenges. From skill development and tools for intelligence systems to deep learning, machine learning, blockchain, IoT, and cloud computing, the book covers a wide range of topics essential to understanding and implementing secure e-governance systems. With its practical insights and interdisciplinary approach, this book serves as a vital resource for academics, researchers, and professionals seeking to navigate the complex landscape of e-governance security and leverage deep learning applications to protect valuable data and ensure the smooth functioning of government operations.

In an era defined by the relentless march of technology, the seamless integration of Artificial Intelligence (AI) into our daily lives has ushered in a transformative landscape. At the forefront of this evolution are the Digital Natives of Generation AI, navigating the complexities of a digital world where algorithms are integral to their daily experiences. This juncture presents a dual influence, marked by the continuous progression of technological advancements and the dynamic ways the youngest members of our society engage with and adapt to the digital environment. As we stand at the crossroads of youth studies and AI, there arises a pressing need to comprehend the profound impact of this convergence on the future leaders of our world. Addressing this imperative, Exploring Youth Studies in the Age of AI emerges as a comprehensive solution to unravel the complexities and opportunities within this evolving landscape. This book, meticulously crafted for academics, researchers, educators, policymakers, and technology ethicists, serves as a guiding beacon in understanding how AI shapes the experiences of today's youth and, in turn, how youth culture influences the development and application of AI technologies. With a collection of enlightening chapters covering topics from'Data-Driven Pedagogies'to'Ethical AI: Guiding Principles for Youth-Centric Development,'the book delves deep into the diverse dimensions of this intersection, providing actionable insights and fostering a nuanced understanding for those invested in the ethical, social, and educational implications of AI within the context of youth. As the reader embarks on this intellectual journey, Exploring Youth Studies in the Age of AI beckons as an active participant in shaping the future, not merely an observation of the current state of affairs. From uncovering the intricacies of AI's influence on education to exploring the socio-economic implications, the book serves as a visionary guide, offering insights into the present and the potential and responsibilities that come with molding the future in the crucible of innovation. With each chapter serving as a gateway into a specific facet of the intersection, this book stands as an indispensable resource for those seeking to navigate the transformative power of AI in the realm of youth studies, promising a richer and more informed engagement with the challenges and opportunities of the digital age.

A new challenge has become present in the field of generative artificial intelligence (AI). The fundamental nature of education, a vital element for advancing the United Nations'Sustainable Development Goals (SDGs), now grapples with the transformative impact of AI technologies. As we stand at this intersection of progress and pedagogy, critical questions surface about the future roles of educators and the integrity of assessment processes. AI's rapid progression prompts an exploration of the competencies our education systems must cultivate in a world where human and machine intelligence are becoming increasingly interconnected. Against this backdrop of transformative uncertainty, Integrating Generative AI in Education to Achieve Sustainable Development Goals addresses profound challenges and offers promising solutions at the crossroads of AI and education. This book assembles distinguished academics, researchers, and practitioners, forming a collective voice on the intersection of Generative AI and education. The three-part structure dissects the technical aspects of AI-powered innovations in educational design, explores multidisciplinary applications enhancing educational content, and highlights AI-driven solutions to address equality and inclusion concerns within educational systems. The book also underscores the importance of ethical considerations of generative AI to ensure a future where technology serves the broader goals of sustainability and equitable education. This book's primary objective is to serve as a resource for academicians, independent researchers, research scholars, students, scientists, libraries, and industry experts. Through a diverse range of topics, it investigates how generative AI can advance Sustainable Development Goals, making education more accessible, individualized, and effective. By harnessing the power of AI, the book argues, education can act as a catalyst for positive change, empowering individuals and fostering progress toward a sustainable and equitable future. The recommended topics within each part provide a structured framework for deepening the understanding of Generative AI's role in shaping the future of education, making this book a valuable reference for scholars and practitioners alike.

The digital age has ushered in an era where students must be equipped not only with traditional knowledge but also with the skills to navigate an increasingly interconnected and technologically driven world. As traditional teaching methods encounter the complexities of the 21st century, the demand for innovation becomes more apparent. This paves the way for the era of artificial intelligence (AI), a technological frontier that carries the potential to reshape education fundamentally. AI-Enhanced Teaching Methods recognizes the urgency of the ongoing technological shift and delves into an exploration of how AI can be effectively harnessed to redefine the learning experience. The book serves as a guide for educators, offering insights into navigating between conventional teaching methodologies and the possibilities presented by AI. It provides an understanding of AI's role in education, covering topics from machine learning to natural language processing. Ethical considerations, including privacy and bias, are thoroughly addressed with thoughtful solutions as well. Additionally, the book provides valuable support for administrators, aiding in the integration of these technologies into existing curricula. AI-Enhanced Teaching Methods presents a comprehensive perspective on the potential of AI in education. The book goes beyond theoretical discussions, providing educators, administrators, and researchers with a practical resource. Through in-depth case studies, best practices, and strategic guidance, it navigates the ethical nuances, legal considerations, and strategies for preparing educators for an AI-integrated future. This essential guide not only helps integrate AI into teaching but also empowers stakeholders to innovate and meet the diverse needs of students in the digital age, shaping the educational landscape.

With the constant evolution of technology, libraries must grapple with the urgent need to adapt or face obsolescence. The integration of artificial intelligence (AI) into library operations presents many new opportunities as well as a complex array of challenges. The traditional roles of libraries, as pillars of knowledge and information, are being reshaped by AI, compelling institutions to reassess their relevance in an ever-evolving digital landscape. The urgency of this intersection between libraries and AI is emphasized by the necessity to revolutionize outdated systems, and it is in this dynamic context that Applications of Artificial Intelligence in Libraries emerges as an essential guide. Applications of Artificial Intelligence in Libraries offers a comprehensive exploration of the multifaceted integration of AI into library operations and services. This book goes beyond theoretical discourse, providing real-world case studies, practical implementations, and research that illustrates how AI is reshaping cataloging, resource discovery, user interactions, and data management within library environments. For librarians and AI professionals alike, the challenges are diverse, ranging from ethical considerations and privacy concerns to the complex task of incorporating AI into the fabric of library services. The book addresses the ethical implications of AI-enabled libraries, offering strategies for navigating privacy concerns and potential challenges in the implementation of AI. It serves as a strategic guide for evaluating the impact and effectiveness of AI initiatives, developing policies and practices centered around AI, and training librarians for the inevitable integration of AI into their roles. By fostering collaboration between librarians, researchers, and AI experts, this book aims to empower professionals to navigate the transformative journey that AI is ushering in for libraries, fostering innovation, collaboration, and the creation of more effective and user-centric library services.

In the dynamic realm of generative artificial Intelligence (AI), the fusion of human creativity and machine intelligence has created a vibrant ecosystem of collaborative artmaking. However, this transformative process brings forth a myriad of concerns, ranging from ethical considerations and the need for originality to navigating the legal complexities surrounding intellectual property. As more and more online communities appear around the use of AI to aid in the creation of images, there arises a pressing need for a comprehensive guide that not only dissects the intricacies of artmaking with generative AI tools but also offers practical solutions to the evolving dilemmas faced by artists, researchers, and technologists. Making Art With Generative AI Tools emerges as an exploration of the challenges posed by this intersection of human expression and artificial intelligence. Artists engaging with generative AI find themselves grappling with issues of authenticity, social toxicity, and the commercial viability of their creations. From avoiding stereotypical visuals to ensuring proper crediting, the realm of generative AI is rife with these complexities. Furthermore, the blurred lines between human and machine authorship necessitate a deeper exploration of how these innovative tools impact creativity, representation, and the very fabric of the art world. Tailored for a diverse audience of researchers, artists, and instructional designers, the book navigates through the intricacies of large language models, provides case studies on the usage of generative AIs, and offers practical guidance on creating visuals for storytelling, teaching, and learning. With a keen focus on fostering human creativity, promoting ethical practices, and addressing the legal nuances of this evolving landscape, the book serves as an indispensable compass for those navigating the uncharted waters of artmaking with generative AI tools.

In the rapidly evolving landscape of industrial activities, artificial intelligence (AI) has emerged as a powerful force driving transformative change. Among its many applications, AI has proven to be instrumental in reducing processing costs associated with optimization challenges. The intersection of AI with optimization and multi-criteria decision making (MCDM) techniques has led to practical solutions in diverse fields such as manufacturing, transportation, finance, economics, and artificial intelligence. Using Traditional Design Methods to Enhance AI-Driven Decision Making delves into a wide array of topics related to optimization, decision-making, and their applications. Drawing on foundational contributions, system developments, and innovative techniques, the book explores the synergy between traditional design methods and AI-driven decision-making approaches. Offering valuable insights into leadership pathways within higher education contexts, the book presents a diverse collection of perspectives and experiences to inform readers about the complexities surrounding AI-driven decision-making. The book is ideal for higher education faculty and administrators, students of higher education, librarians, researchers, graduate students, and academicians. Contributors are invited to explore a wide range of topics, including the role of AI-driven decision-making in leadership, trends in AI-driven decision-making in Industry 5.0, applications in various industries such as manufacturing, transportation, healthcare, and banking services, as well as AI-driven optimization in mechanical engineering and materials.

Artificial intelligence (AI) and robotics have boomed in the 21st century. These emerging and disruptive technologies are immersed in our lives, from apps in mobile devices, the purchases we make on the internet streaming platforms, and even court decisions and predictive policing. Together with science and certain needs, relevant implementations of AI and robotics arise, related to its transparency, resulting in biases, the kinds of applications that can be implemented, and the degree of workforce replacement in decision-making assistance. It is essential to analyze the widely used AI techniques, the application of these technologies in different sectors, the implications of AI and robotics on society and welfare, and more. The Handbook of Research on Applied Artificial Intelligence and Robotics for Government Processes presents state-of-the-art research on AI and robotics in different fields of knowledge, its benefits, applications, and implications. It features chapters containing theoretical and practical research that analyzes the transparency and expandability of AI in different fields, as well as the analysis of unexpected results, biases, and cases of discrimination. Covering topics such as criminal intelligence, artificial intelligence-based chatbots, and gender violence, this major reference work is an excellent resource for government officials, practitioners in the public sector, business administrators and managers, IT professionals, law enforcement, federal agencies, students and faculty of higher education, researchers, and academicians.

'Investigating the Impact of AI on Ethics and Spirituality focuses on the spiritual implications of AI and its increasing presence in society. As AI technology advances, it raises fundamental questions about our spiritual relationship with technology. This study emphasizes the need to examine the ethical considerations of AI through a spiritual lens and to consider how spiritual principles can inform its development and use. This book covers topics such as data collection, ethical issues, and AI and is ideal for educators, teacher trainees, policymakers, academicians, researchers, curriculum developers, higher-level students, social activists, and government officials'--

'The goal of this book is to clearly define and emphasize various AI algorithms, as well as new IoT and blockchain breakthroughs in the field of e-governance. The discipline of data analytics, security is on the verge of reaching new heights, thanks to the introduction of AI capabilities. Every chapter will cover blockchain technology, ML and DL algorithms, their origins, problems and benefits and various government use cases, to clearly explain the growing power of AI and security algorithms for the development and operation of e-governance applications. A thorough in-depth understanding of AI algorithms through real use case application can help to kindle interest in research. Students, scholars, bureaucrats, industrialists in and scientists interested in AI, cybersecurity and blockchain can greatly benefit from this book'--

The field of cybersecurity is becoming increasingly important due to the continuously expanding reliance on computer systems, the internet, wireless network standards such as Bluetooth and wi-fi, and the growth of'smart'devices, including smartphones, televisions, and the various devices that constitute the internet of things (IoT). Cybersecurity is also one of the significant challenges in the contemporary world, due to its complexity, both in terms of political usage and technology. The Handbook of Research on Cybersecurity Risk in Contemporary Business Systems examines current risks involved in the cybersecurity of various business systems today from a global perspective and investigates critical business systems. Covering key topics such as artificial intelligence, hacking, and software, this reference work is ideal for computer scientists, industry professionals, policymakers, researchers, academicians, scholars, instructors, and students.

Generative AI in Teaching and Learning delves into the revolutionary field of generative artificial intelligence and its impact on education. This comprehensive guide explores the multifaceted applications of generative AI in both formal and informal learning environments, shedding light on the ethical considerations and immense opportunities that arise from its implementation. From the early approaches of utilizing generative AI in teaching to its integration into various facets of learning, this book offers a profound analysis of its potential. Teachers, researchers, instructional designers, developers, data analysts, programmers, and learners alike will find valuable insights into harnessing the power of generative AI for educational purposes. The book covers a wide range of topics, including generative AI applications in artwork, coding, writing, research, collaboration, and more. It examines the implications of public generative AI interfaces and explores how generative AI can be effectively utilized in formal education settings, such as accredited institutions. The roles of teachers, content creation, instructional design, research, community service, sports, policies, assignments, grading, student work, and programming are all examined in relation to generative AI. Furthermore, the book explores the use of generative AI in nonformal and informal teaching and learning, emphasizing the opportunities for self-learning, group learning, and social change that arise from its implementation. It also delves into the professional ethics surrounding the application of generative AI in education. While examining the potential benefits of generative AI, the book also addresses the risks associated with demotivation for skill acquisition, deskilling, and downskilling. It highlights the opportunities for upskilling and encourages educators and learners to engage in learning practices that leverage the power of generative AI.

'This book will provide chapters that include applications of artificial intelligence for the optimization of wireless communication systems, including channel models, channel state estimation, beamforming, codebook design, signal processing, etc. It will be extensive work in this particular domain rather than in abstract form. It will explore not just the theoretical aspects but also the practical implementation of this. The main objective of this book is to concise or to actually come up with something that should be a collection of recent research or advances in the research happening in the field. As per the recent advancement, this is one of the most exciting topic'--

Artificial intelligence (AI), the internet of things (IoT), and blockchain provide services to 6G in the form of radio resource management, mobility management, energy management, and network management. Moreover, 6G strengthens AI and blockchain-based applications. Further study on the benefits and potential opportunities of 6G for AI and blockchain is required to utilize the technology successfully. Role of 6G Wireless Networks in AI and Blockchain-Based Applications considers the role of the 6G wireless network deployed on AI and blockchain technology-based applications in fields such as the healthcare industry, agriculture, e-business, and transportation. The book specifically focuses on remote healthcare monitoring, online shopping preference, V2V communication, UAV, holographic application, and augmented and virtual reality as advanced services of 6G networks. Covering topics such as machine learning, smart cities, and virtual reality, this reference work is ideal for computer scientists, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.

'AI Tools for Protecting and Preventing Sophisticated Cyber Attacks illuminates the most effective and practical applications of artificial intelligence (AI) in securing critical cyber infrastructure and internet communities worldwide. The book presents a collection of selected peer-reviewed chapters addressing the most important issues, technical solutions, and future research directions in cyber security. Covering topics such as assessment metrics, information security, and toolkits, this premier reference source is an essential resource for cyber security experts, cyber systems administrators, IT experts, internet and computer network professionals, organizational leaders, students and educators of higher education, researchers, and academicians'--

It is crucial that forensic science meets challenges such as identifying hidden patterns in data, validating results for accuracy, and understanding varying criminal activities in order to be authoritative so as to hold up justice and public safety. Artificial intelligence, with its potential subsets of machine learning and deep learning, has the potential to transform the domain of forensic science by handling diverse data, recognizing patterns, and analyzing, interpreting, and presenting results. Machine Learning and deep learning frameworks, with developed mathematical and computational tools, facilitate the investigators to provide reliable results. Further study on the potential uses of these technologies is required to better understand their benefits. Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks provides an outline of deep learning and machine learning frameworks and methods for use in forensic science to produce accurate and reliable results to aid investigation processes. The book also considers the challenges, developments, advancements, and emerging approaches of deep learning and machine learning. Covering key topics such as biometrics, augmented reality, and fraud investigation, this reference work is crucial for forensic scientists, law enforcement, computer scientists, researchers, scholars, academicians, practitioners, instructors, and students.

The digital transformation of higher education institutions has accelerated in the last decade due to the confluent development of digital technologies. Understanding how artificial intelligence-enabled changes and improvements in universities in relation to teaching, management, sustainability, and research allows researchers to understand the advances and identify the challenges that may arise. This knowledge provides technological instruments as well as cognitive, philosophical, and epistemological tools to address different current issues. Strategy, Policy, Practice, and Governance for AI in Higher Education Institutions offers both empirical and theoretical information focused on artificial intelligence and its various applications in higher education institutions. It includes research results, authoritative overview articles, high quality analysis on trends, comparative studies, and analysis of cases that focus on issues including ethical issues and risks for applying AI in higher education, policies to introduce AI in curricula, and applications in teaching and learning. Covering topics such as artificial intelligence ethics, energy efficiency, and postsecondary administrative leadership, this premier reference source is an essential resource for computer scientists, AI scientists, administration of higher education institutions, educators and faculty of higher education, pre-service teachers, researchers, IT professionals, and academicians.

Modes and models of learning and instruction have shown a significant shift from yesterday's conventional learning and teaching given this era's current educational and social contexts. Learners are no longer learning and communicating with human-generated, computed, and mediated—or traditional—learning and instructional practices, paving the way for machine-facilitated communication, learning, and teaching tools. Learning and instruction, communication and information exchange, as well as gathering, coding, analyzing, and synthesizing data have proven to be in need of even more innovative technology-moderated tools. Applications of Machine Learning and Artificial Intelligence in Education focuses on the parameters of remote learning, machine learning, deep learning, and artificial intelligence under 21st-century learning and instructional contexts. Covering topics such as data coding and social networking technology, it is ideal for learners with an interest in the deep learning discipline, educators, educational technologists, instructional designers, and data evaluators, as well as special interest groups (SGIs) in the discipline.

The emergence of artificial intelligence has created a vast amount of advancements within various professional sectors and has transformed the way organizations conduct themselves. The implementation of intelligent systems has assisted with developing traditional processes including decision making, risk management, and security. An area that requires significant attention and research is how these companies are becoming accustomed to computer intelligence and applying this technology to their everyday practices. Transdisciplinary Perspectives on Risk Management and Cyber Intelligence is a pivotal reference source that provides vital research on the application of intelligent systems within various professional sectors as well as the exploration of theories and empirical findings. While highlighting topics such as decision making, cognitive science, and knowledge management, this publication explores the management of risk and uncertainty using training exercises, as well as the development of managerial intelligence competency. This book is ideally designed for practitioners, educators, researchers, policymakers, managers, developers, analysts, politicians, and students seeking current research on modern approaches to the analysis and performance of cyber intelligence.

Developing a knowledge model helps to formalize the difficult task of analyzing crime incidents in addition to preserving and presenting the digital evidence for legal processing. The use of data analytics techniques to collect evidence assists forensic investigators in following the standard set of forensic procedures, techniques, and methods used for evidence collection and extraction. Varieties of data sources and information can be uniquely identified, physically isolated from the crime scene, protected, stored, and transmitted for investigation using AI techniques. With such large volumes of forensic data being processed, different deep learning techniques may be employed. Confluence of AI, Machine, and Deep Learning in Cyber Forensics contains cutting-edge research on the latest AI techniques being used to design and build solutions that address prevailing issues in cyber forensics and that will support efficient and effective investigations. This book seeks to understand the value of the deep learning algorithm to handle evidence data as well as the usage of neural networks to analyze investigation data. Other themes that are explored include machine learning algorithms that allow machines to interact with the evidence, deep learning algorithms that can handle evidence acquisition and preservation, and techniques in both fields that allow for the analysis of huge amounts of data collected during a forensic investigation. This book is ideally intended for forensics experts, forensic investigators, cyber forensic practitioners, researchers, academicians, and students interested in cyber forensics, computer science and engineering, information technology, and electronics and communication.

Within higher education, there are enormous untapped opportunities for product/services companies, administrators, educators, start-ups. and technology professionals to begin embracing artificial intelligence (AI) across the student ecosystem and infuse innovation into traditional academic processes by leveraging disruptive technologies. This type of human-machine interface presents the immediate potential to change the way we learn, memorize, access, and create information. These solutions present new openings for education for all while fostering lifelong learning in a strengthened model that can preserve the integrity of core values and the purpose of higher education. Impact of AI Technologies on Teaching, Learning, and Research in Higher Education explores the phenomena of the emergence of the use of AI in teaching and learning in higher education, including examining the positive and negative aspects of AI. Recent technological advancements and the increasing speed of adopting new technologies in higher education are discussed in order to predict the future nature of higher education in a world where AI is part of the fabric of universities. The book also investigates educational implications of emerging technologies on the way students learn and how institutions teach and evolve. Finally, challenges for the adoption of these technologies for teaching, learning, student support, and administration are addressed. Highlighting such tools as machine learning, natural language processing, and self-learning systems, this scholarly book is of interest to university administrators, educational software developers, instructional designers, policymakers, government officials, academicians, researchers, and students, as well as international agencies, organizations, and professionals interested in implementing AI in higher education.

Immersive technology as an umbrella concept consists of multiple emerging technologies including augmented reality (AR), virtual reality (VR), gaming, simulation, and 3D printing. Research has shown immersive technology provides unique learning opportunities for experiential learning, multiple perspectives, and knowledge transfer. Due to its role in influencing learners'cognitive and affective processes, it is shown to have great potential in changing the educational landscape in the decades to come. However, there is a lack of general cognitive and affective theoretical framework to guide the diverse aspects of immersive technology research. In fact, lacking the cognitive and affective theoretical framework has begun to hamper the design and application of immersive technology in schools and related professional training. Cognitive and Affective Perspectives on Immersive Technology in Education is an essential research book that explores methods and implications for the design and implementation of upcoming immersive technologies in pedagogical and professional development settings. The book includes case studies that highlight the cognitive and affective processes in immersive technology as well as the successful applications of immersive technology in education. Featuring a wide range of topics such as curriculum design, K-12 education, and mobile learning, this book is ideal for academicians, educators, policymakers, curriculum developers, instructional designers, administrators, researchers, and students.

As the advancement of technology continues, cyber security continues to play a significant role in today's world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.

As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it's important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research.

Collecting and processing data is a necessary aspect of living in a technologically advanced society. Whether it's monitoring events, controlling different variables, or using decision-making applications, it is important to have a system that is both inexpensive and capable of coping with high amounts of data. As the application of these networks becomes more common, it becomes imperative to evaluate their effectiveness as well as other opportunities for possible implementation in the future. Sensor Technology: Concepts, Methodologies, Tools, and Applications is a vital reference source that brings together new ways to process and monitor data and to put it to work in everything from intelligent transportation systems to healthcare to multimedia applications. It also provides inclusive coverage on the processing and applications of wireless communication, sensor networks, and mobile computing. Highlighting a range of topics such as internet of things, signal processing hardware, and wireless sensor technologies, this multi-volume book is ideally designed for research and development engineers, IT specialists, developers, graduate students, academics, and researchers.

Information in today's modernized world has become much more attainable with the use of technology. A resource that has fallen victim to this are library services. What was once a staple of knowledge and communication has failed to keep pace with recent advancements in information service providers. Library practitioners need to learn how to manage change, build influence, and adapt their services to remain relevant within local communities. Libraries can continue to play a key role in future aspects of information provision, but proper research is a necessity. Managing and Adapting Library Information Services for Future Users is a collection of innovative research that encapsulates practices, concepts, ideas, and proposals that would chart pathways for libraries of all types to envision and understand how to thrive and remain relevant in the competitive information provision environment. It is expected to motivate librarians and information scientists to probe further into how libraries would better serve user communities of the 21st century who have options of accessing information from sources other than from libraries. While highlighting topics including artificial intelligence, human design thinking, and alternative finance, this book is ideally designed for librarians, information specialists, architects, data scientists, researchers, community development practitioners, policymakers, faculty members, and students seeking current research on emerging advancements in library optimization.

Link prediction is required to understand the evolutionary theory of computing for different social networks. However, the stochastic growth of the social network leads to various challenges in identifying hidden links, such as representation of graph, distinction between spurious and missing links, selection of link prediction techniques comprised of network features, and identification of network types. Hidden Link Prediction in Stochastic Social Networks concentrates on the foremost techniques of hidden link predictions in stochastic social networks including methods and approaches that involve similarity index techniques, matrix factorization, reinforcement, models, and graph representations and community detections. The book also includes miscellaneous methods of different modalities in deep learning, agent-driven AI techniques, and automata-driven systems and will improve the understanding and development of automated machine learning systems for supervised, unsupervised, and recommendation-driven learning systems. It is intended for use by data scientists, technology developers, professionals, students, and researchers.

As a movement, transhumanism aims to upgrade the human body through science, constantly pushing back the limits of a person by using cutting-edge technologies to fix the human body and upgrade it beyond its natural abilities. Transhumanism can not only change human habits, but it can also change learning practices. By improving human learning, it improves the human organism beyond natural and biological limits. The Handbook of Research on Learning in the Age of Transhumanism is an essential research publication that discusses global values, norms, and ethics that relate to the diverse needs of learners in the digital world and addresses future priorities and needs for transhumanism. The book will identify and scrutinize the needs of learners in the age of transhumanism and examine best practices for transhumanist leaders in learning. Featuring topics such as cybernetics, pedagogy, and sociology, this book is ideal for educators, trainers, instructional designers, curriculum developers, professionals, researchers, academicians, policymakers, and librarians.

New technological communication methods have created new kinds of interactions among us that have allowed people across the globe to become closer, but they have also created more complex global dynamics. These dynamics have expanded the workings of human behavior, making human-seeming artificial intelligence a more difficult goal to achieve. Human Behavior and Another Kind in Consciousness: Emerging Research and Opportunities is a crucial reference book that examines human consciousness and how it can translate into artificial intelligence. Covering important topics such as cloud computing, human behavior, and intelligent systems, this book is ideal for engineers, researchers, academicians, and students in the fields of computer science, artificial intelligence, operations research, and intelligent systems.

In the past few years, with the evolution of advanced persistent threats and mutation techniques, sensitive and damaging information from a variety of sources have been exposed to possible corruption and hacking. Machine learning, artificial intelligence, predictive analytics, and similar disciplines of cognitive science applications have been found to have significant applications in the domain of cyber security. Machine Learning and Cognitive Science Applications in Cyber Security examines different applications of cognition that can be used to detect threats and analyze data to capture malware. Highlighting such topics as anomaly detection, intelligent platforms, and triangle scheme, this publication is designed for IT specialists, computer engineers, researchers, academicians, and industry professionals interested in the impact of machine learning in cyber security and the methodologies that can help improve the performance and reliability of machine learning applications.

The expansion of digital data has transformed various sectors of business such as healthcare, industrial manufacturing, and transportation. A new way of solving business problems has emerged through the use of machine learning techniques in conjunction with big data analytics. Deep Learning Innovations and Their Convergence With Big Data is a pivotal reference for the latest scholarly research on upcoming trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. Featuring extensive coverage on a broad range of topics and perspectives such as deep neural network, domain adaptation modeling, and threat detection, this book is ideally designed for researchers, professionals, and students seeking current research on the latest trends in the field of deep learning techniques in big data analytics.

There are many different approaches to understanding human consciousness. By conducting research to better understand various biological mechanisms, these can be redefined and utilized for technological purposes. Advanced Research on Biologically Inspired Cognitive Architectures is an essential reference source for the latest scholarly research on the biological elements of human cognition and examines the applications of consciousness within computing environments. Featuring exhaustive coverage on a broad range of innovative topics and perspectives, such as artificial intelligence, bio-robotics, and human-computer interaction, this publication is ideally designed for academics, researchers, professionals, graduate students, and practitioners seeking current research on the exploration of the intricacies of consciousness and different approaches of perception.

Ongoing advancements in modern technology have led to significant developments in artificial intelligence. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Artificial Intelligence: Concepts, Methodologies, Tools, and Applications provides a comprehensive overview of the latest breakthroughs and recent progress in artificial intelligence. Highlighting relevant technologies, uses, and techniques across various industries and settings, this publication is a pivotal reference source for researchers, professionals, academics, upper-level students, and practitioners interested in emerging perspectives in the field of artificial intelligence.

The discovery and development of new computational methods have expanded the capabilities and uses of simulations. With agent-based models, the applications of computer simulations are significantly enhanced. Multi-Agent-Based Simulations Applied to Biological and Environmental Systems is a pivotal reference source for the latest research on the implementation of autonomous agents in computer simulation paradigms. Featuring extensive coverage on relevant applications, such as biodiversity conservation, pollution reduction, and environmental risk assessment, this publication is an ideal source for researchers, academics, engineers, practitioners, and professionals seeking material on various issues surrounding the use of agent-based simulations.

Modern society exists in a digital era in which high volumes of multimedia information exists. To optimize the management of this data, new methods are emerging for more efficient information retrieval. Web Semantics for Textual and Visual Information Retrieval is a pivotal reference source for the latest academic research on embedding and associating semantics with multimedia information to improve data retrieval techniques. Highlighting a range of pertinent topics such as automation, knowledge discovery, and social networking, this book is ideally designed for researchers, practitioners, students, and professionals interested in emerging trends in information retrieval.

Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.

The development of nature-inspired computational techniques has enhanced problem solving in dynamic and uncertain environments. By implementing effective computing strategies, this ensures adaptable, self-organizing, and decentralized behavioral techniques. Recent Developments in Intelligent Nature-Inspired Computing is an authoritative reference source for the latest scholarly material on natural computation methods and applications in diverse fields. Highlighting multidisciplinary studies on swarm intelligence, global optimization, and group technology, this publication is an ideal reference source for professionals, researchers, scholars, and engineers interested in the latest developments in computer science methodologies.

Developments in bio-inspired computation have impacted multiple fields and created opportunities for new applications. In recent years, these techniques have been increasingly integrated into robotic systems. Membrane Computing for Distributed Control of Robotic Swarms: Emerging Research and Opportunities is an innovative reference source for the latest perspectives on biologically-inspired computation techniques for robot design and control. Highlighting a range of pivotal topics such as software engineering, simulation tools, and robotic security, this book is ideally designed for researchers, academics, students, and practitioners interested in the role of membrane computing in mobile robots.

The growing presence of biologically-inspired processing has caused significant changes in data retrieval. With the ubiquity of these technologies, more effective and streamlined data processing techniques are available. Bio-Inspired Computing for Information Retrieval Applications is a key resource on the latest advances and research regarding current techniques that have evolved from biologically-inspired processes and its application to a variety of problems. Highlighting multidisciplinary studies on data processing, swarm-based clustering, and evolutionary computation, this publication is an ideal reference source for researchers, academics, professionals, students, and practitioners.

As technology continues to become more sophisticated, mimicking natural processes and phenomena also becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for man-made computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications takes an interdisciplinary approach to the topic of natural computing, including emerging technologies being developed for the purpose of simulating natural phenomena, applications across industries, and the future outlook of biologically and nature-inspired technologies. Emphasizing critical research in a comprehensive multi-volume set, this publication is designed for use by IT professionals, researchers, and graduate students studying intelligent computing.