Perspectives On Artificial Intelligence In Times Of Turbulence Theoretical Background To Applications

Perspectives on Artificial Intelligence in Times of Turbulence: Theoretical Background to Applications offers a comprehensive exploration of the intricate relationship between artificial intelligence (AI) and the ever-changing landscape of our society. The book defines AI as machines capable of performing tasks that were once exclusive to human cognition. However, it emphasizes the current limitations of AI, dispelling the notion of sophisticated cyborgs depicted in popular culture. These machines lack self-awareness, struggle with understanding context—especially in language—and are constrained by historical data and predefined parameters. This distinction sets the stage for examining AI's impact on the job market and the evolving roles of humans and machines. Rather than portraying AI as a threat, this book highlights the symbiotic relationship between humans and machines. It recognizes that while certain jobs may become obsolete, new opportunities will emerge. The unique abilities of human beings—such as relational skills, emotional intelligence, adaptability, and understanding of differences—will continue to be indispensable in a rapidly transforming society. Its perspectives cover a wide range of topics such as business sustainability, change management, cybersecurity, digital economy and transformation, information systems management, management models and tools, and continuous improvement are comprehensively addressed. Additionally, the book delves into healthcare, telemedicine, Health 4.0, privacy and security, knowledge management, learning, and presents real-world case studies. Designed for researchers and professionals seeking to enhance their knowledge and research capabilities, this book offers a consistent theoretical and practical foundation. It serves as a springboard for further studies, supports change management initiatives within organizations, and facilitates knowledge sharing among experts. This book is an essential companion for colleges with master's and Ph.D. degree investigators, and researchers across a wide range of disciplines.

Applications of Machine Learning in UAV Networks presents a pioneering exploration into the symbiotic relationship between machine learning techniques and UAVs. In an age where UAVs are revolutionizing sectors as diverse as agriculture, environmental preservation, security, and disaster response, this meticulously crafted volume offers an analysis of the manifold ways machine learning drives advancements in UAV network efficiency and efficacy. This book navigates through an expansive array of domains, each demarcating a pivotal application of machine learning in UAV networks. From the precision realm of agriculture and its dynamic role in yield prediction to the ecological sensitivity of biodiversity monitoring and habitat restoration, the contours of each domain are vividly etched. These explorations are not limited to the terrestrial sphere; rather, they extend to the pivotal aerial missions of wildlife conservation, forest fire monitoring, and security enhancement, where UAVs adorned with machine learning algorithms wield an instrumental role. Scholars and practitioners from fields as diverse as machine learning, UAV technology, robotics, and IoT networks will find themselves immersed in a confluence of interdisciplinary expertise. The book's pages cater equally to professionals entrenched in agriculture, environmental studies, disaster management, and beyond.

In the world of academia, scholars and researchers are confronted with a rapidly expanding knowledge base in Artificial Intelligence (AI) and nanotechnology. The integration of these two groundbreaking fields presents an intricate web of concepts, innovations, and interdisciplinary applications that can overwhelm even the most astute academic minds. Staying up to date with the latest developments and effectively navigating this complex terrain has become a pressing challenge for those striving to contribute meaningfully to these fields. Artificial Intelligence in the Age of Nanotechnology is a transformative solution meticulously crafted to address the academic community's knowledge gaps and challenges. This comprehensive book serves as the guiding light for scholars, researchers, and students grappling with the dynamic synergy between AI and Nanotechnology. It offers a structured and authoritative exploration of the core principles and transformative applications of these domains across diverse fields. By providing clarity and depth, it empowers academics to stay at the forefront of innovation and make informed contributions.

The rapid advancements in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and Generative AI, pose a challenge for academic scholars. Staying current with the latest techniques and applications in these fields is difficult due to their dynamic nature, while the lack of comprehensive resources hinders scholars' ability to effectively utilize these technologies. Advanced Applications of Generative AI and Natural Language Processing Models offers an effective solution to address these challenges. This comprehensive book delves into cutting-edge developments in NLP and Generative AI. It provides insights into the functioning of these technologies, their benefits, and associated challenges. Targeting students, researchers, and professionals in AI, NLP, and computer science, this book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI. By providing real-world examples and practical applications, scholars can apply their learnings to solve complex problems across various domains. Embracing Advanced Applications of Generative AI and Natural Language Processing Modelsequips academic scholars with the necessary knowledge and insights to explore innovative applications and unleash the full potential of generative AI and NLP models for effective problem-solving.

The ever-evolving industrial landscape poses challenges for businesses, particularly in robotics, where performance optimization and data security are paramount. AI and Blockchain Applications in Industrial Robotics, edited by esteemed scholars Mihai Lazarescu, Rajashekhar Biradar, Geetha Devanagavi, Nikhath Tabassum, and Nayana Hegde, presents the transformative potential of combining AI and blockchain technologies to revolutionize the field. This exceptional book provides comprehensive insights into how AI enhances predictive models and pattern recognition, while blockchain ensures secure and immutable data transactions. By synergizing these technologies, businesses can achieve enhanced transparency, trust, and efficiency in their robotic processes. With practical applications, use cases, and real-world examples, the book caters to a wide range of readers, empowering them to embrace the possibilities of AI and blockchain in industrial robotics. AI and Blockchain Applications in Industrial Robotics equip industries with the tools and understanding to overcome challenges in optimizing performance, ensuring data security, and harnessing emerging technologies. Serving as a beacon of knowledge, this book drives innovation, efficiency, and competitiveness in the industrial sector. Whether for postgraduate students, researchers, industry professionals, undergraduate students, or freelance developers, the book provides valuable insights and practical guidance for implementing AI and blockchain solutions. By embracing the transformative potential of these technologies, industries can unlock new possibilities and propel themselves forward in the ever-advancing world of industrial robotics.

The field of medical imaging is rapidly evolving, with new technologies and techniques constantly emerging. However, this fast-paced advancement brings challenges such as the complexity of imaging modalities, the need for continuous education and training, and the integration of emerging technologies like AI and robotics into existing healthcare systems. Healthcare professionals and technology enthusiasts often need help to keep pace with these changes and may feel overwhelmed by the vast amount of information and possibilities in the field. Enhancing Medical Imaging with Emerging Technologies offers a comprehensive solution to these challenges. By providing a thorough introduction to medical imaging systems, including the fundamentals of system theory and image processing, the book serves as a foundational resource for understanding the complex world of medical imaging. It covers various imaging modalities, from conventional camera systems to advanced techniques like magnetic resonance imaging and optical coherence tomography, offering readers a holistic view of the field. This book is a valuable resource that inspires hope, sparks curiosity, and paints a vivid picture of the limitless potential of medical imaging.

Women encounter multifaceted threats, ranging from personal safety hazards to discrimination deeply embedded in societal structures. The existing landscape demands innovative strategies to ensure women can participate fully in society without fear or impediment. Traditional systems often fall short, necessitating a paradigm shift in our approach to women's safety. Impact of AI on Advancing Women's Safety emerges as a groundbreaking solution to address the pervasive challenges they face. From the shadows of harassment to systemic biases in justice systems, women navigate a complex landscape. This book delves into the pressing issues, unveiling a visionary approach that leverages artificial intelligence to create tangible, transformative solutions.

In an age defined by the transformative ascent of cloud computing and the Internet of Things (IoT), our technological landscape has undergone a revolutionary evolution, enhancing convenience and connectivity in unprecedented ways. This convergence, while redefining how we interact with data and devices, has also brought to the forefront a pressing concern – the susceptibility of these systems to security breaches. As cloud services integrate further into our daily lives and the IoT saturates every aspect of our routines, the looming potential for cyberattacks and data breaches necessitates immediate and robust solutions to fortify the protection of sensitive information, ensuring the privacy and integrity of individuals, organizations, and critical infrastructure. Emerging Technologies for Securing the Cloud and IoT emerges as a comprehensive and timely solution to address the multifaceted security challenges posed by these groundbreaking technologies. Edited by Amina Ahmed Nacer from the University of Lorraine, France, and Mohammed Riyadh Abdmeziem from Ecole Nationale Supérieur d’Informatique, Algeria, this book serves as an invaluable guide for both academic scholars and industry experts. Its content delves deeply into the intricate web of security concerns, elucidating the potential ramifications of unaddressed vulnerabilities within cloud and IoT systems. With a pragmatic focus on real-world applications, the book beckons authors to explore themes like security frameworks, integration of AI and machine learning, data safeguarding, threat modeling, and more. Authored by esteemed researchers, practitioners, and luminaries, each chapter bridges the divide between theory and implementation, aiming to be an authoritative reference empowering readers to adeptly navigate the complexities of securing cloud-based IoT systems. A crucial resource for scholars, students, professionals, and policymakers striving to comprehend, confront, and surmount contemporary and future security challenges, this book stands as the quintessential guide for ushering in an era of secure technological advancement.