In the dynamic landscape of bioinformatics and blockchain technology, a profound challenge is evident: ensuring secure exchange and analysis of complex biological data while maintaining data integrity and ownership. Traditional methods fall short in seamlessly transferring genomic data, spurring the fusion of blockchain innovation and optimization algorithms as a groundbreaking solution. Biology-Inspired Optimization Techniques in Blockchain Systems directly addresses the data integrity and ownership dilemma in bioinformatics and blockchain. Despite the intricacies of genomic data, blockchain's potential solution faces obstacles like data volume and slow transactions. These challenges are adeptly overcome through optimization algorithms. The book, authored by experts in bioinformatics, blockchain, and optimization, offers a comprehensive guide, showcasing how blockchain architecture and biological data intricacies can harmonize. It provides a blueprint for using blockchain to store genomic variants and aligned reads. This work empowers developers, data scientists, and researchers to overcome technological barriers, redefining the landscape of bioinformatics and beyond.

The amalgamation of artificial intelligence (AI), optimization techniques, and blockchain is revolutionizing how to conceptualize, design, and operate aerospace systems. While optimization techniques are pivotal in streamlining aerospace processes, security challenges have recently surfaced. AI and Blockchain Optimization Techniques in Aerospace Engineering delves into the transformative impact of technologies on various facets of the aerospace industry, offering a multidimensional solution to overcome security concerns and enhance the overall efficiency of aerospace systems The book explores how machine learning reshapes aerospace systems by automating complex tasks through self/reinforced learning methods. From air traffic data analysis to flight scheduling, geographical information, and navigation, machine learning has become an indispensable tool, offering valuable insights that enhance aerospace operations. Simultaneously, blockchain technology, with its inherent characteristics of decentralization and tamper-proof ledgers, ensures transparency, accountability, and security in transactions, providing an innovative approach to data integrity and system resilience. Designed for technology development professionals, academicians, data scientists, industrial experts, researchers, and students, the book offers a panoramic view of the latest innovations in the field.

The academic community is currently facing the challenge of navigating the complexities of swarm robotics. This field demands understanding the design, control, and coordination of autonomous robotic swarms. The intricacies of developing algorithms that facilitate communication, cooperation, and adaptation among simple individual agents remain a formidable obstacle. Addressing issues like task allocation, formation control, path planning, and decentralized decision-making are pivotal to unlocking the true potential of swarm robotics. Bio-inspired Swarm Robotics and Control: Algorithms, Mechanisms, and Strategies immerses readers in the cutting-edge realm of swarm robotics, a discipline inspired by the intricate choreography observed in biological systems like insect colonies, bird flocks, and fish schools. Encompassing a rich array of bio-inspired algorithms, mechanisms, and strategies, the text elucidates how robots can communicate, cooperate, and adapt within dynamic environments. The book propels robotics, automation, and artificial intelligence advancements by fostering interdisciplinary connections and charting a course toward more efficient and resilient multi-robot systems. This book is ideal for biologists, engineers, and computer scientists to join forces in unlocking the full potential of swarm robotics.

As organizations navigate the complexities of modern information systems management (ISM), they face many challenges. Rapid technological advancements, changing workplace structures, and mainstreaming remote work have underscored the need for clear roles, responsibilities, and methods for interaction within ISM groups and with external stakeholders. This lack of clarity can lead to inefficiencies, inconsistencies, and even breakdowns in communication, hindering the organization's ability to manage its information systems effectively. Essential Information Systems Service Management serves as a comprehensive solution to the challenges of modern ISM. It uniquely compiles critical roles, responsibilities, workflows, processes, functions, and methods for successfully managing contemporary information systems. By providing a clear roadmap, this book empowers practitioners and students to navigate the evolving professional landscape confidently and competently, ensuring they can contribute effectively to their organizations.

The convergence of Augmented Reality (AR) and Virtual Reality (VR) has transcended the boundaries of gaming and entertainment, emerging as tools in healthcare and wellbeing. At the heart of recent research-driven exploration lies the recognition of a critical gap in healthcare education. However, amid the promising potential of AR and VR, a need for more comprehensive research has thus far limited the capacity of these technologies to optimize physical, psychological, and social wellbeing. Through the ingenious use of AR, Applications of Virtual and Augmented Reality for Health and Wellbeing spotlights the fusion of virtual learning experiences with tangible real-world scenarios, addressing the educational challenges that have long hindered the development of effective healthcare competencies. This book embarks on an academic journey into this transformative landscape, delving into the intricate tapestry of AR and VR technologies and their applications. It unfurls an inclusive discourse encompassing accessibility considerations, the integration of artificial intelligence within AR/VR paradigms, cross-disciplinary applications, and tangible real-world use cases that underscore the transformational impact of these technologies. As a compendium of solutions to real-world challenges, the book channels the collective wisdom of researchers, offering an invaluable reference guide to professionals at the vanguard of AR/VR innovation. Distinguished voices from academia, industry, and gaming converge within the pages, catering to an eclectic audience, including research scholars, educators, industry practitioners, and gaming enthusiasts.

The integration of Augmented Reality (AR) and Virtual Reality (VR) with Artificial Intelligence (AI) has immense potential to have beneficial effects for institutions of healthcare and medical education. However, this integration has become so complex, it presents numerous challenges across various domains. Researchers and practitioners often need help to keep pace with the rapid advancements of technologies and applications. Issues such as privacy, security, scalability, and optimization of AR/VR setups remain critical concerns for healthcare industry professionals and academics alike. There needs to be a comprehensive resource that addresses these challenges, if we expect the field to grow in an effective and responsible manner. Modern Technology in Healthcare and Medical Education: Blockchain, IoT, AR, and VR offers a solution to these challenges. By providing insights from researchers and experts in the field, this book serves as a valuable reference for addressing real-world problems. This book is a must-have resource for doctoral and post-doctoral researchers, undergraduate and postgraduate students, industry professionals, and government agencies working in AR/VR. It provides a roadmap for future research and development in this rapidly evolving field. It covers a wide range of topics, including enhancements in AR/VR, AI integration, task-specific training, and applications in healthcare and education.

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.

The rapid proliferation of connected devices in our daily lives, from smart homes to industrial sensors, has led to an explosion of data that requires processing before it is useful to experts. However, modern devices often have limited resources, making it challenging to decode and utilize this data effectively. Additionally, the need for real-time decision-making further complicates this issue, as traditional data processing methods take far too long to be able to keep up with the required volume and speed. Developments Towards Next Generation Intelligent Systems for Sustainable Development offers a comprehensive solution to these challenges by integrating novel technologies such as AI, edge computing, federated learning, quantum computing, and more. The book shows how intelligent systems can maximize computing power by leveraging these technologies to process large volumes of data efficiently and autonomously and make real-time decisions. The proposed architectures and frameworks focus on real-time analysis, faster decision-making, enhanced privacy, and efficient data processing.

Digital Technologies in Modeling and Management: Insights in Education and Industry explores the use of digital technologies in the modeling and control of complex systems in various fields, such as social networks, education, technical systems, and their protection and security. The book consists of two parts, with the first part focusing on modeling complex systems using digital technologies, while the second part deals with the digitalization of economic processes and their management. The book results from research conducted by leading universities' teaching staff and contains the results of many years of scientific experiments and theoretical conclusions. The book is for a wide range of readers, including the teaching staff of higher educational institutions, graduate students, students in computer science and modeling, and management technologies, including economics. It is also a valuable resource for IT professionals and business analysts interested in using digital technologies to model and control complex systems.

Technological Advancements in Data Processing for Next Generation Intelligent Systems presents an in-depth exploration of cutting-edge data processing technologies that drive the development of next-generation intelligent systems in the context of the digital transformation era. This comprehensive book delves into the role data plays as a critical asset for organizations across diverse industries, and how recent technological breakthroughs have unlocked unprecedented potential for handling vast data volumes and real-time analysis. The book begins by providing a thorough overview of novel technologies such as artificial intelligence (AI) or machine learning (ML), edge computing, federated learning, quantum computing, and more. These revolutionary technologies, when integrated with big data frameworks, in-memory computing, and AI/ML algorithms, have transformed data processing capabilities, enabling the creation of intelligent systems that fuel innovation, optimize operations, and deliver personalized experiences. The ultimate aim of this integration is to empower devices with the ability to make autonomous intelligent decisions, maximizing computing power. This book serves as a valuable resource for research scholars, academicians, and industry professionals working towards the future advancement of optimized intelligent systems and intelligent data processing approaches. The chapters encompass a wide range of topics, including architecture and frameworks for intelligent systems, applications in diverse domains, cloud-based solutions, quantum processing, federated learning, in-memory data processing, real-time stream processing, trustworthy AI for Internet of Things (IoT) sensory data, and more.