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Convergence of Cybersecurity and Cloud Computing
The convergence of cybersecurity and cloud computing is crucial for protecting data and ensuring the integrity of digital systems in an increasingly interconnected world. As cloud computing continues to grow, so does the need for robust security measures to address vulnerabilities in these environments. Understanding how to secure cloud deployments is essential for businesses, organizations, and individuals to safeguard sensitive information and maintain trust in digital services. By addressing the unique security challenges posed by cloud computing, society can better adapt to the evolving landscape of digital threats and ensure the safety of critical infrastructure. Convergence of Cybersecurity and Cloud Computing is a comprehensive resource to navigate the link between cybersecurity and cloud computing. It discusses the unique security challenges that arise from cloud environments. Covering topics such as artificial intelligence, data protection, and threat detection, this book is an excellent resource for academicians, research scholars, IT professionals, security experts, faculty, and more.
Challenges and Risks Involved in Deploying 6G and NextGen Networks
There is a need to be aware of the challenges awaiting us in next generation (NextGen) networks in order to take the proper steps to either minimize or eliminate issues as they present themselves. Incorporating artificial intelligence in NextGen networks for privacy and security policies will serve this purpose. It is essential to stay current with these emerging technologies and applications in order to maintain safe and secure communications in the future. Challenges and Risks Involved in Deploying 6G and NextGen Networks explores strategies for the design and deployment of more secured and user-centered NextGen networks through artificial intelligence to enrich user experience. It further...
Geometrical Enhancements Based on Data-Driven Design Decisions
The text presents various design and modelling solutions for effective decision-making that are grounded on the basics of data analytics. It further discusses important topics such as sustainable design and data-driven design synthesis, product analytics and its role in sustainable development, and descriptive models for the geometrical evaluation of product features. This book: Familiarize the readers with the numerous decision protocols that can be utilized for deducing geometrical qualities using data-driven design analysis Offers a more comprehensive approach to multidisciplinary engineering applications using data-driven modelling and analysis Discusses multi-objective optimization for ...
Revolution with Generative AI: Trends and Techniques
This book delves into the exciting and rapidly evolving world of generative artificial intelligence (AI) and its profound impact on various industries and domains. This comprehensive book brings together leading experts and researchers to explore the cutting-edge advancements, applications, and implications of generative AI technologies. It provides an in-depth exploration of generative AI, which encompasses a range of techniques such as generative adversarial networks (GANs), recurrent neural networks (RNNs), and transformer models like GPT-3. It examines how these technologies enable machines to generate content, including text, images, audio, and more, that closely mimics human creativity and intelligence. The book's multidisciplinary approach allows it to cater to a wide range of readers with varying levels of expertise and interests in generative AI.
Integrating AI-Driven Technologies Into Service Marketing
In an era marked by rapid technological advancements and the increasing integration of artificial intelligence (AI) into various sectors, the intersection of AI technologies with service marketing stands as a pivotal frontier. It is essential to explore the intricate nexus between AI technologies and service marketing strategies. Integrating AI-Driven Technologies Into Service Marketing elucidates the transformative impact of AI on key facets of service marketing, ranging from customer engagement and relationship management to market segmentation and product customization. It underscores the imperative for stakeholders in emerging economies to harness the power of AI technologies in crafting innovative and adaptive service marketing strategies. The book navigates the complexities of AI adoption while offering pragmatic recommendations for fostering responsible and inclusive AI-driven service marketing ecosystems. Covering topics such as customer engagement, influencer marketing, and sentiment analysis, this book is an excellent resource for scholars, researchers, educators, business professionals, managers, academicians, postgraduate students, and more.
Generative AI for Photonic Sensing
This book highlights the revolutionary effects of generative Artificial Intelligence (AI) on photonic sensing technologies, where intelligent systems might improve precision, effectiveness, and applicability of light-based sensors. This book covers the basics of photonic sensors and explains their significance for a variety of applications in healthcare, environmental monitoring, autonomous systems, and industrial process industries. Readers will learn how generative AI is being used in important fields including optical imaging, optical fiber sensors, spectroscopy, and LIDAR systems. It also provides a guidance for researchers, engineers, and professionals working in the fields of optical sensing and artificial intelligence by fusing the rapidly developing discipline of generative AI with sophisticated photonic sensing.
Smart IoT for Sustainable Development
This book explores the role of the Internet of Things (IoT) in achieving sustainable development goals (SDGs). It provides a comprehensive overview of how IoT technologies enhance energy efficiency, promote clean energy, support environmental monitoring, and facilitate sustainable practices across various sectors. It features real-world case studies, explores key challenges and opportunities, and additionally discusses the integration of machine learning and 5G technology for sustainable development. Discussion on the fundamental technologies driving smart IoT-based sustainable development, including sensors, data acquisition, and cloud computing Examination of various aspects of energy effi...
AI for Large Scale Communication Networks
Artificial Intelligence (AI) is rapidly becoming essential to large-scale communication networks. Driven by the need for greater efficiency, security, and optimization, AI has evolved into a powerful tool that processes vast data and delivers insights through real-time processing, predictive analysis, and adaptive learning. Because these advancements transform how we interact with data and services, applying AI to complex networks has never been more essential. AI for Large Scale Communication Networks explores how AI can enhance network performance, scalability, and security. With contributions from experts, this book covers topics such as algorithm optimization, machine learning improvements, and neural network applications. It also addresses critical challenges like fault tolerance and distributed computing, emphasizing the need for interdisciplinary collaboration. Designed for academics, practitioners, and students, this resource provides actionable insights and strategies to optimize communication networks using AI.
Computer-Assisted Learning for Engaging Varying Aptitudes: From Theory to Practice
Computer-assisted learning has completely modernized the way that students learn both in the average classroom as well as in language learning contexts. Through its ability to provide interactive and engaging learning resources, computer-assisted learning is a useful tool for engaging all learners. It is essential that educators stay current with the emerging learning technologies so that they can create more dynamic and engaging classrooms and pique the interest of even the most apathetic students. Computer-Assisted Learning for Engaging Varying Aptitudes: From Theory to Practice is an essential reference source that provides insights on the practical applications of technology-based learning and its measurement and explains the applicability of this method in various classrooms. Covering topics in facial recognition technology, big data technology, and learning challenges, this premier reference source is a dynamic resource for faculty and administrators of both K-12 and higher education, pre-service teachers, IT consultants, educational software developers, government officials, superintendents, researchers, and academicians.
Advanced Research in Materials and Engineering Applications
Selected, peer reviewed papers from the World Virtual Conference on Advanced Research in Materials and Engineering Applications, September 22-26, 2014, Kuala Lumpur, Malaysia
