Danilo Pelusi – författare

Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical electronics, protein structure prediction, and biomedical data analysis. The book provides the reader with a comprehensive guide to advanced computational intelligence, spanning deep learning, fuzzy logic, connectionist systems, evolutionary computation, cellular automata, self-organizing systems, soft computing, and hybrid intelligent systems in biomedical and healthcare applications. Sections focus on important biomedical engineering applications, including biosensors, enzyme immobilization techniques, immuno-assays, and nanomaterials for biosensors and other biomedical techniques.

Other sections cover gene-based solutions and applications through computational intelligence techniques and the impact of nonlinear/unstructured data on experimental analysis.

Computational Intelligence in Cancer Diagnosis: Progress and Challenges provides insights into the current strength and weaknesses of different applications and research findings on computational intelligence in cancer research. The book improves the exchange of ideas and coherence among various computational intelligence methods and enhances the relevance and exploitation of application areas for both experienced and novice end-users. Topics discussed include neural networks, fuzzy logic, connectionist systems, genetic algorithms, evolutionary computation, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems.

The book's chapters are written by international experts from both cancer research, oncology and computational sides to cover different aspects and make it comprehensible for readers with no background on informatics.

With the increasing use of e-learning, technology has not only revolutionized the way businesses operate but has also impacted learning processes in the education sector. E-learning is slowly replacing traditional methods of teaching and security in e-learning is an important issue in this educational context. With this book, you will be familiarized with the theoretical frameworks, technical methodologies, information security, and empirical research findings in the field to protect your computers and information from threats. Secure Data Management for Online Learning Applications will keep you interested and involved throughout.

With the increasing use of e-learning, technology has not only revolutionized the way businesses operate but has also impacted learning processes in the education sector. E-learning is slowly replacing traditional methods of teaching and security in e-learning is an important issue in this educational context. With this book, you will be familiarized with the theoretical frameworks, technical methodologies, information security, and empirical research findings in the field to protect your computers and information from threats. Secure Data Management for Online Learning Applications will keep you interested and involved throughout.

This book explores the applications and advancements of federated learning across diverse sectors, focusing on its integration with cutting- edge technologies like Internet of Things (IoT), artificial intelligence (AI), blockchain, and digital twins. Real-world examples and case studies illustrate federated learning’s role in healthcare, smart cities, and maritime applications while addressing critical concerns such as security. It provides insights into federated learning’s transformative potential, offering practical strategies for intelligent systems and sustainable environments.

The book particularly:

• Focuses on the federated learning–based model optimization, addressing the significance of IoT and federated learning in the evolution of intelligent systems for various applications;

• Describes the different optimization techniques of federated learning systems from a practical point of view;

• Highlights economic, social, and environmental impacts of smart technologies and provides insights into IoT, 5G/ 6G communication, and computing standards;

• Provides analysis of the use cases of federated learning regarding the development of IoT, AI, blockchain, digital twins;

• Offers strategies for overcoming challenges associated with federated learning systems, including connectivity, computation, threats, privacy, and security issues.

It covers fundamental concepts, practical implementations, and trends, to serve as a reference resource for professionals and researchers in the field.

This book explores the applications and advancements of federated learning across diverse sectors, focusing on its integration with cutting- edge technologies like Internet of Things (IoT), artificial intelligence (AI), blockchain, and digital twins. Real-world examples and case studies illustrate federated learning’s role in healthcare, smart cities, and maritime applications while addressing critical concerns such as security. It provides insights into federated learning’s transformative potential, offering practical strategies for intelligent systems and sustainable environments.

The book particularly:

• Focuses on the federated learning–based model optimization, addressing the significance of IoT and federated learning in the evolution of intelligent systems for various applications;

• Describes the different optimization techniques of federated learning systems from a practical point of view;

• Highlights economic, social, and environmental impacts of smart technologies and provides insights into IoT, 5G/ 6G communication, and computing standards;

• Provides analysis of the use cases of federated learning regarding the development of IoT, AI, blockchain, digital twins;

• Offers strategies for overcoming challenges associated with federated learning systems, including connectivity, computation, threats, privacy, and security issues.

It covers fundamental concepts, practical implementations, and trends, to serve as a reference resource for professionals and researchers in the field.

This book is essential for anyone eager to understand the groundbreaking advancements in generative AI and its transformative effects across industries, making it a valuable resource for both professional growth and creative inspiration.

Generative AI: Disruptive Technologies for Innovative Applications delves into the exciting and rapidly evolving world of generative artificial intelligence and its profound impact on various industries and domains. This comprehensive volume brings together leading experts and researchers to explore the cutting-edge advancements, applications, and implications of generative AI technologies. This volume provides an in-depth exploration of generative AI, which encompasses a range of techniques such as generative adversarial networks, recurrent neural networks, and transformer models like GPT-3. It examines how these technologies enable machines to generate content, including text, images, and audio, that closely mimics human creativity and intelligence. Readers will gain valuable insights into the fundamentals of generative AI, innovative applications, ethical and social considerations, interdisciplinary insights, and future directions of this invaluable emerging technology. Generative AI: Disruptive Technologies for Innovative Applications is an indispensable resource for researchers, practitioners, and anyone interested in the transformative potential of generative AI in revolutionizing industries, unleashing creativity, and pushing the boundaries of what’s possible in artificial intelligence.

Audience

AI researchers, industry professionals, data scientists, machine learning experts, students, policymakers, and entrepreneurs interested in the innovative field of generative AI.

This book is essential for anyone eager to understand the groundbreaking advancements in generative AI and its transformative effects across industries, making it a valuable resource for both professional growth and creative inspiration.

Generative AI: Disruptive Technologies for Innovative Applications delves into the exciting and rapidly evolving world of generative artificial intelligence and its profound impact on various industries and domains. This comprehensive volume brings together leading experts and researchers to explore the cutting-edge advancements, applications, and implications of generative AI technologies. This volume provides an in-depth exploration of generative AI, which encompasses a range of techniques such as generative adversarial networks, recurrent neural networks, and transformer models like GPT-3. It examines how these technologies enable machines to generate content, including text, images, and audio, that closely mimics human creativity and intelligence. Readers will gain valuable insights into the fundamentals of generative AI, innovative applications, ethical and social considerations, interdisciplinary insights, and future directions of this invaluable emerging technology. Generative AI: Disruptive Technologies for Innovative Applications is an indispensable resource for researchers, practitioners, and anyone interested in the transformative potential of generative AI in revolutionizing industries, unleashing creativity, and pushing the boundaries of what’s possible in artificial intelligence.

Audience

AI researchers, industry professionals, data scientists, machine learning experts, students, policymakers, and entrepreneurs interested in the innovative field of generative AI.

This book highlights the potential research areas of Information and Communication Technologies (ICT), such as the research in the field of modern computing and communication technologies that deal with different aspects of data analysis and network connectivity to develop solution for the emerging real-time information system challenges; contains a brief discussion about the progression from information systems to intelligent information systems, development of autonomous systems, real-time implementation of Internet of Things (IoT) and Cyber Physical Systems (CPS), fundamentals of intelligent information systems and analytical activities; helps to gain a significant research knowledge on modern communication technologies from the novel research contributions dealing with different aspects of communication systems, which showcase effective technological solutions that can be used for the implementation of novel distributed wireless communication systems. The individual chapters included in this book will provide a valuable resource for the researchers, scientists, scholars, and research enthusiasts, who have more interest in Information and Communication Technologies (ICT).

Encompassing the contributions of professors and researchers from Indian and other foreign universities, this book will be of interest to students, researchers, and practitioners, as well as members of the general public interested in the realm of Internet of Things (IoT) and Cyber Physical Systems (CPS).

The two-volume proceedings set CCIS 2121 and 2122 constitutes the refereed proceedings of the First International Conference on Intelligent Computing for Sustainable Development, ICICSD 2023, which took place in Hyderabad, India, during August 25–26, 2023.

The 46 papers included in these proceedings were carefully reviewed and selected from 138 submissions. They focus on digital healthcare, renewable energy, smart cities, digital farming, and autonomous systems.

The two-volume proceedings set CCIS 2121 and 2122 constitutes the refereed proceedings of the First International Conference on Intelligent Computing for Sustainable Development, ICICSD 2023, which took place in Hyderabad, India, during August 25–26, 2023.

The 46 papers included in these proceedings were carefully reviewed and selected from 138 submissions. They focus on digital healthcare, renewable energy, smart cities, digital farming, and autonomous systems.

This proceeding discuss the latest solutions, scientific findings and methods for solving intriguing problems in the fields of data mining, computational intelligence, big data analytics, and soft computing. This gathers outstanding papers from the fifth International Conference on “Computational Intelligence in Data Mining” (ICCIDM), and offer a “sneak preview” of the strengths and weaknesses of trending applications, together with exciting advances in computational intelligence, data mining, and related fields.

This book presents practical development experiences in different areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.