Tien Anh Tran - Böcker

Recent Advancement of IoT Devices in Pollution Control and Health Applications covers current developments in Internet of Things (IoT)-based pollution control, solid waste management, transportation, and healthcare systems. Because of its effects on physical and biological entities of the environment, the issue of environmental pollution and action has become a global concern. This guide highlights how environmental and health data from connected devices can be stored, analyzed, and eventually used-from developing indices for the state of environmental pollution, to diagnosing and treating patients and the role of IoT-based technology for pollution control. Covers current developments in the field of Internet of Things (IoT)-based pollution control Discusses the application of the Internet of Things (IoT) to monitoring industrial pollution from emissions, solid waste, and healthcare Offers solutions for managing and mitigating the causes of pollution

Harnessing the Potential of Blockchain Technology in the Smart Healthcare explores a groundbreaking shift in how healthcare data are managed, shared, and secured. This book is an essential guide for anyone seeking a deep understanding of the intersection between blockchain and healthcare. It breaks down complex blockchain concepts and reveals their transformative impact on the industry.Across 27 insightful chapters, the readers will discover how blockchain can not only revolutionize electronic health records, strengthen data security and privacy, and streamline healthcare operations, but also empower patients with greater control over their health information.Through real-world case studies, expert insights, and practical strategies, the book equips healthcare professionals, technologists, and policymakers with the tools to leverage blockchain for a more efficient, transparent, and patient-centered healthcare system.By examining real-world applications and implementations, this book not only informs but also inspires action-paving the way for a future where healthcare is smarter, safer, and more equitable.Illuminates how blockchain technology enhances data security and privacy, assuaging concerns about patient information breachesExplores concrete strategies for interoperability, facilitating seamless data exchange among healthcare providers, and promoting a patient-centric approach to healthcareDelves into the complexities of regulatory compliance and suggests pathways for healthcare organizations to navigate the evolving regulatory landscape successfully

The development of intelligent transportation systems, especially autonomous underwater vehicles, has become significant in marine engineering, with an aim to enhance energy efficiency management and communication systems. This book covers different aspects of optimization of autonomous underwater vehicles and their propulsion systems via machine learning techniques. It further analyses hydrodynamic characteristics including the study of experimental investigation combined with hydrodynamic characteristics backed by MATLAB® codes and simulation study results. Features: Covers utilization of machine learning techniques with a focus on marine science and ocean engineering. Details effect of the intelligent transportation system (ITS) into the sustainable environment and ecology system. Evaluates performance of particle swarm intelligence-based optimization techniques. Reviews propulsion performance of the remote-controlled vehicles based on machine learning techniques. Includes MATLAB® examples and simulation study results.This book is aimed at graduate students and researchers in marine engineering and technology, computer science, and control system engineering.

The development of intelligent transportation systems, especially autonomous underwater vehicles, has become significant in marine engineering, with an aim to enhance energy efficiency management and communication systems. This book covers different aspects of optimization of autonomous underwater vehicles and their propulsion systems via machine learning techniques. It further analyses hydrodynamic characteristics including the study of experimental investigation combined with hydrodynamic characteristics backed by MATLAB® codes and simulation study results. Features: Covers utilization of machine learning techniques with a focus on marine science and ocean engineering. Details effect of the intelligent transportation system (ITS) into the sustainable environment and ecology system. Evaluates performance of particle swarm intelligence-based optimization techniques. Reviews propulsion performance of the remote-controlled vehicles based on machine learning techniques. Includes MATLAB® examples and simulation study results.This book is aimed at graduate students and researchers in marine engineering and technology, computer science, and control system engineering.

Wastewater Treatment Using Green Synthesis discusses advances in wastewater treatment with a focus on biological processes. Major topics discussed include bioremediation through microorganisms, green and iron-based nanoparticles in wastewater treatment, TiO2 Doped Lignocellulosic Biopolymer with an emphasis on their photodegradation potential for a variety of pollutants, and permanent film growth. It further includes remediation of industrial sludges/effluents with a particular emphasis on biological treatment, phytoremediation, and de-ballasting water treatment technology. Features:Focuses on the implementation of effective wastewater treatment with orientation towards biological processes Covers both biological and physico-chemical waste and wastewater treatment processes, focusing on emerging techniquesReviews computational method approaches, the application of TiO2-doped biopolymers, iron nanoparticles, and the use of molecular techniques for wastewater treatmentIllustrates molecular docking, molecular dynamics simulation, homology modelling, and biodegradation pathways predictionIncludes dedicated chapters on biological wastewater treatmentThis book is aimed at graduate students and researchers in environmental and chemical engineering with a focus on wastewater treatment.

Wastewater Treatment Using Green Synthesis discusses advances in wastewater treatment with a focus on biological processes. Major topics discussed include bioremediation through microorganisms, green and iron-based nanoparticles in wastewater treatment, TiO2 Doped Lignocellulosic Biopolymer with an emphasis on their photodegradation potential for a variety of pollutants, and permanent film growth. It further includes remediation of industrial sludges/effluents with a particular emphasis on biological treatment, phytoremediation, and de-ballasting water treatment technology. Features:Focuses on the implementation of effective wastewater treatment with orientation towards biological processes Covers both biological and physico-chemical waste and wastewater treatment processes, focusing on emerging techniquesReviews computational method approaches, the application of TiO2-doped biopolymers, iron nanoparticles, and the use of molecular techniques for wastewater treatmentIllustrates molecular docking, molecular dynamics simulation, homology modelling, and biodegradation pathways predictionIncludes dedicated chapters on biological wastewater treatmentThis book is aimed at graduate students and researchers in environmental and chemical engineering with a focus on wastewater treatment.

This book focuses on different applications of multimedia with supervised and unsupervised data engineering in the modern world. It includes AI-based soft computing and machine techniques in the field of medical diagnosis, biometrics, networking, manufacturing, data science, automation in electronics industries, and many more relevant fields.Multimedia Data Processing and Computing provides a complete introduction to machine learning concepts, as well as practical guidance on how to use machine learning tools and techniques in real-world data engineering situations. It is divided into three sections. In this book on multimedia data engineering and machine learning, the reader will learn how to prepare inputs, interpret outputs, appraise discoveries, and employ algorithmic strategies that are at the heart of successful data mining. The chapters focus on the use of various machine learning algorithms, neural net- work algorithms, evolutionary techniques, fuzzy logic techniques, and deep learning techniques through projects, so that the reader can easily understand not only the concept of different algorithms but also the real-world implementation of the algorithms using IoT devices. The authors bring together concepts, ideas, paradigms, tools, methodologies, and strategies that span both supervised and unsupervised engineering, with a particular emphasis on multimedia data engineering. The authors also emphasize the need for developing a foundation of machine learning expertise in order to deal with a variety of real-world case studies in a variety of sectors such as biological communication systems, healthcare, security, finance, and economics, among others. Finally, the book also presents real-world case studies from machine learning ecosystems to demonstrate the necessary machine learning skills to become a successful practitioner.The primary users for the book include undergraduate and postgraduate students, researchers, academicians, specialists, and practitioners in computer science and engineering.

This book focuses on different applications of multimedia with supervised and unsupervised data engineering in the modern world. It includes AI-based soft computing and machine techniques in the field of medical diagnosis, biometrics, networking, manufacturing, data science, automation in electronics industries, and many more relevant fields.Multimedia Data Processing and Computing provides a complete introduction to machine learning concepts, as well as practical guidance on how to use machine learning tools and techniques in real-world data engineering situations. It is divided into three sections. In this book on multimedia data engineering and machine learning, the reader will learn how to prepare inputs, interpret outputs, appraise discoveries, and employ algorithmic strategies that are at the heart of successful data mining. The chapters focus on the use of various machine learning algorithms, neural net- work algorithms, evolutionary techniques, fuzzy logic techniques, and deep learning techniques through projects, so that the reader can easily understand not only the concept of different algorithms but also the real-world implementation of the algorithms using IoT devices. The authors bring together concepts, ideas, paradigms, tools, methodologies, and strategies that span both supervised and unsupervised engineering, with a particular emphasis on multimedia data engineering. The authors also emphasize the need for developing a foundation of machine learning expertise in order to deal with a variety of real-world case studies in a variety of sectors such as biological communication systems, healthcare, security, finance, and economics, among others. Finally, the book also presents real-world case studies from machine learning ecosystems to demonstrate the necessary machine learning skills to become a successful practitioner.The primary users for the book include undergraduate and postgraduate students, researchers, academicians, specialists, and practitioners in computer science and engineering.

Artificial Intelligence (AI) is reshaping our urban landscapes and healthcare systems. From enhancing efficiency in smart cities to delivering personalized healthcare solutions, AI holds the key to a transformative future.Comprising seven insightful chapters, this book offers a comprehensive overview of key topics shaping the future of healthcare systems and smart cities. This book is a combination of the smart healthcare system and the intelligent transportation system based on AI. From telemedicine’s global accessibility to the application of data-mining techniques in predicting cardiac diseases and detecting anti-malaria drug resistance, each chapter presents cutting-edge research and practical applications.Furthermore, this book explores the integration of advanced AI technologies into healthcare systems, paving the way for cost-effective solutions and innovative approaches. It also delves into the challenges associated with analyzing electroencephalogram data and predicting anxiety and depression among elderly patients, offering promising solutions and insights.This book discusses the realms of smart cities and healthcare, where AI promises to revolutionize efficiency, sustainability, and personalized care delivery. Researchers/scholars and graduate students at universities/research institutes and research engineers in computer science, transportation, and engineering industries will find this book beneficial.

Recently, the fields of Artificial Intelligence (AI) and the Internet of Things (IoT) have revolutionized numerous industries, including healthcare. The convergence of AI and IoT has given birth to smart healthcare systems, transforming the way we deliver, receive, and experience healthcare services. This book explores the profound impact of these technologies on healthcare and presents a comprehensive overview of their applications, challenges, and prospects.Smart Healthcare Systems: AI and IoT Perspectives addresses various aspects of how smart healthcare can be used to detect and analyze diseases, the underlying methodologies, and related security concerns. It also discusses healthcare as a multidisciplinary field that involves a range of sectors such as the financial system, social factors, health technologies, and organizational structures that affect individuals, families, institutions, organizations, and populations’ healthcare. The book presents the goals of healthcare services which include patient safety, timeliness, effectiveness, efficiency, and equity. An outline of what smart healthcare consists of which is m-health, e-health, electronic resource management, smart and intelligent home services, and medical devices is included. Along with highlights on how AI and IoT-enabled healthcare technologies are suitable for remote health monitoring, including rehabilitation, and assisted ambient living. Rounding the offers of this book out is that it also covers how healthcare analytics can be applied to the data gathered from different areas to improve healthcare at a minimum expense.Researchers, Academicians, Industry, R&D Organizations, medical professionals, PG students, and policymakers in the fields of artificial intelligence, the internet of things, healthcare informatics, biomedical engineering, medical informatics, and related subjects can use this book to assist them in making appropriate decisions regarding these emerging disciplines.

Recently, the fields of Artificial Intelligence (AI) and the Internet of Things (IoT) have revolutionized numerous industries, including healthcare. The convergence of AI and IoT has given birth to smart healthcare systems, transforming the way we deliver, receive, and experience healthcare services. This book explores the profound impact of these technologies on healthcare and presents a comprehensive overview of their applications, challenges, and prospects.Smart Healthcare Systems: AI and IoT Perspectives addresses various aspects of how smart healthcare can be used to detect and analyze diseases, the underlying methodologies, and related security concerns. It also discusses healthcare as a multidisciplinary field that involves a range of sectors such as the financial system, social factors, health technologies, and organizational structures that affect individuals, families, institutions, organizations, and populations’ healthcare. The book presents the goals of healthcare services which include patient safety, timeliness, effectiveness, efficiency, and equity. An outline of what smart healthcare consists of which is m-health, e-health, electronic resource management, smart and intelligent home services, and medical devices is included. Along with highlights on how AI and IoT-enabled healthcare technologies are suitable for remote health monitoring, including rehabilitation, and assisted ambient living. Rounding the offers of this book out is that it also covers how healthcare analytics can be applied to the data gathered from different areas to improve healthcare at a minimum expense.Researchers, Academicians, Industry, R&D Organizations, medical professionals, PG students, and policymakers in the fields of artificial intelligence, the internet of things, healthcare informatics, biomedical engineering, medical informatics, and related subjects can use this book to assist them in making appropriate decisions regarding these emerging disciplines.

This book provides an understanding of the significant applications of IoT technologies in renewable energy. It explores their integration with various renewable energy sources, including solar, wind, bioenergy, piezoelectric materials, and solutions addressing water shortage challenges, highlighting advancements and practical implementations in each area. A comparative analysis of recent techniques is presented to evaluate the efficiency of IoT‑based renewable energy systems. The book also focuses on the economic feasibility of IoT-enabled renewable energy solutions.Features:Addresses multiple renewable energy technologies with IoT-based monitoring and controlExplores solar, wind, and hybrid energy systems, including energy storage and microgrid integrationInvestigates renewable energy microgrid systemsFocuses on climate goals and the Sustainable Development Goals (SDGs)Includes discussions of marine renewable energies and offshore wind turbine generationThis book is aimed at graduate students and researchers in renewable energy engineering, IoT and embedded systems, and electrical engineering.

SUPERVISED and UNSUPERVISED DATA ENGINEERING for MULTIMEDIA DATA Explore the cutting-edge realms of data engineering in multimedia with Supervised and Unsupervised Data Engineering for Multimedia Data, where expert contributors delve into innovative methodologies, offering invaluable insights to empower both novices and seasoned professionals in mastering the art of manipulating multimedia data with precision and efficiency. Supervised and Unsupervised Data Engineering for Multimedia Data presents a groundbreaking exploration into the intricacies of handling multimedia data through the lenses of both supervised and unsupervised data engineering. Authored by a team of accomplished experts in the field, this comprehensive volume serves as a go-to resource for data scientists, computer scientists, and researchers seeking a profound understanding of cutting-edge methodologies. The book seamlessly integrates theoretical foundations with practical applications, offering a cohesive framework for navigating the complexities of multimedia data. Readers will delve into a spectrum of topics, including artificial intelligence, machine learning, and data analysis, all tailored to the challenges and opportunities presented by multimedia datasets. From foundational principles to advanced techniques, each chapter provides valuable insights, making this book an essential guide for academia and industry professionals alike. Whether you’re a seasoned practitioner or a newcomer to the field, Supervised and Unsupervised Data Engineering for Multimedia Data illuminates the path toward mastery in manipulating and extracting meaningful insights from multimedia data in the modern age.

This book covers the sustainability issues of a green environment towards economics and society in terms of alteration in industrial pollution levels, effect of reduced carbon emissions, changes in water bodies characteristics with respect to heavy metal contamination, monitoring of associated impact with respect to ecology and biodiversity, impact of reduced noise levels and air quality influences on human health, handling and management of biomedical waste. According to WHO, 80% of people living in urban areas are exposed to air exceeding safe limits. The advent of "sustainability‟ in development science has led planners to apply evolving notions of "sustainability‟ to the contemporary debate over how cities and regions should be revitalized, redeveloped, and reformed. Market allocation of resources, sustained levels of growth and consumption, an assumption that natural resources are unlimited and a belief that economic growth will „trickle down‟ to the poor have been its hallmarks. The recent advance technology helps to promote green and clean modern societies continuously. The Internet of things will be playing an important role in the upcoming years in environment protection and sustainable development.There is a focus on paradigm shift in the sustainable development for the green environment during the period of isolation of COVID-19. This is the moment for the mobilization against the climate crisis. The sudden fall in pollutants and subsequent blue skies signifies a dramatic shift for India and also other affected countries during this period. Fighting climate change requires a collaborative approach between all spheres of society unlike the former. It must heavily redirect resources towards local, sustainable activities, including education, health, sustainable agriculture and circular management of resources. The impact of COVID-19 pandemic which has resulted in the dramatic change in the different aspects of the environment. The global lockdown has led to a rejuvenation of nature, ecosystems, biodiversity. Even urban environments are discovering a degree of peace and serenity, which led to decrease in greenhouse gas emission.

This book covers the sustainability issues of a green environment towards economics and society in terms of alteration in industrial pollution levels, effect of reduced carbon emissions, changes in water bodies characteristics with respect to heavy metal contamination, monitoring of associated impact with respect to ecology and biodiversity, impact of reduced noise levels and air quality influences on human health, handling and management of biomedical waste. According to WHO, 80% of people living in urban areas are exposed to air exceeding safe limits. The advent of "sustainability‟ in development science has led planners to apply evolving notions of "sustainability‟ to the contemporary debate over how cities and regions should be revitalized, redeveloped, and reformed. Market allocation of resources, sustained levels of growth and consumption, an assumption that natural resources are unlimited and a belief that economic growth will „trickle down‟ to the poor have been its hallmarks. The recent advance technology helps to promote green and clean modern societies continuously. The Internet of things will be playing an important role in the upcoming years in environment protection and sustainable development.There is a focus on paradigm shift in the sustainable development for the green environment during the period of isolation of COVID-19. This is the moment for the mobilization against the climate crisis. The sudden fall in pollutants and subsequent blue skies signifies a dramatic shift for India and also other affected countries during this period. Fighting climate change requires a collaborative approach between all spheres of society unlike the former. It must heavily redirect resources towards local, sustainable activities, including education, health, sustainable agriculture and circular management of resources. The impact of COVID-19 pandemic which has resulted in the dramatic change in the different aspects of the environment. The global lockdown has led to a rejuvenation of nature, ecosystems, biodiversity. Even urban environments are discovering a degree of peace and serenity, which led to decrease in greenhouse gas emission.

This book focuses on industrial wastes that either join the streams or other natural water bodies directly, or are emptied into the municipal sewers, and their characteristics vary widely depending on the source of production and the raw material used by the industry, even during pre-industrial, industrial period and prospect of wastewater treatment for water resource conservation. The treatment of industrial wastewater can be done in part or as a whole either by the biological or chemical processes. Advanced treatment methods like membrane separation, ultra-filtration techniques and adsorption are elaborated. It would emphasize and facilitate a greater understanding of all existing available research, i.e., theoretical, methodological, well-established and validated empirical work, associated with the environment and climate change aspects.

This book focuses on industrial wastes that either join the streams or other natural water bodies directly, or are emptied into the municipal sewers, and their characteristics vary widely depending on the source of production and the raw material used by the industry, even during pre-industrial, industrial period and prospect of wastewater treatment for water resource conservation. The treatment of industrial wastewater can be done in part or as a whole either by the biological or chemical processes. Advanced treatment methods like membrane separation, ultra-filtration techniques and adsorption are elaborated. It would emphasize and facilitate a greater understanding of all existing available research, i.e., theoretical, methodological, well-established and validated empirical work, associated with the environment and climate change aspects.

Artificial Intelligence and Edge Computing for Sustainable Ocean Health explores the transformative role of AI and edge computing in preserving and enhancing ocean health. The growing influence of Artificial Intelligence (AI), along with the Internet of Things (IoT) in generating wide coverage of sensor networks, and Edge Computing (EC) has paved the way for investigation of underwater as well as massive marine data, thereby generating huge potential for credible research opportunities for these domains. This book’s journey begins with a broad overview of Artificial Intelligence for Sustainable Ocean Health, setting the foundation for understanding AI's potential in marine conservation. The subsequent chapter, Role of Artificial Intelligence and Technologies in Improving Ocean Health in Promoting Tourism, illustrates the synergy between technological advancements and sustainable tourism practices, demonstrating how AI can enhance the attractiveness and preservation of marine destinations. The identification, restoration, and monitoring of marine resources along with the utilization of technology continues in Utilization of Underwater Wireless Sensor Network through Supervising a Random Network Environment in the Ocean Environment has been extensively dealt with. The technical challenges of underwater imaging, essential for accurate data collection and analysis has been discussed.The importance of Explainable AI is discussed in chapters like Sustainable Development Goal 14: Explainable AI (XAI) for Ocean Health, Explainable AI (XAI) for Ocean Health: Exploring the Role of Explainable AI in Enhancing Ocean Health, and A Comprehensive Study of AI (XAI) for Ocean Health Monitoring, which emphasize transparency and trust in AI systems. Further, Revolutionizing Internet of Underwater Things with Federated Learning, Underwater Drone, Underwater Imagery with AI/ML and IoT in ROV Technology and Ocean Cleanup has been demonstrated using innovative approaches to addressing underwater challenges. The book also includes a Review on the Optics and Photonics in Environmental Sustainability, focusing on the role of optics in marine conservation. Security issues are tackled in Intelligent Hash Function Based Key-Exchange Scheme for Ocean Underwater Data Transmission, and the overarching potential of AI in marine resource management is discussed in Artificial Intelligence as Key-enabler for Safeguarding the Marine Resources.

Artificial Intelligence and Edge Computing for Sustainable Ocean Health explores the transformative role of AI and edge computing in preserving and enhancing ocean health. The growing influence of Artificial Intelligence (AI), along with the Internet of Things (IoT) in generating wide coverage of sensor networks, and Edge Computing (EC) has paved the way for investigation of underwater as well as massive marine data, thereby generating huge potential for credible research opportunities for these domains. This book’s journey begins with a broad overview of Artificial Intelligence for Sustainable Ocean Health, setting the foundation for understanding AI's potential in marine conservation. The subsequent chapter, Role of Artificial Intelligence and Technologies in Improving Ocean Health in Promoting Tourism, illustrates the synergy between technological advancements and sustainable tourism practices, demonstrating how AI can enhance the attractiveness and preservation of marine destinations. The identification, restoration, and monitoring of marine resources along with the utilization of technology continues in Utilization of Underwater Wireless Sensor Network through Supervising a Random Network Environment in the Ocean Environment has been extensively dealt with. The technical challenges of underwater imaging, essential for accurate data collection and analysis has been discussed.The importance of Explainable AI is discussed in chapters like Sustainable Development Goal 14: Explainable AI (XAI) for Ocean Health, Explainable AI (XAI) for Ocean Health: Exploring the Role of Explainable AI in Enhancing Ocean Health, and A Comprehensive Study of AI (XAI) for Ocean Health Monitoring, which emphasize transparency and trust in AI systems. Further, Revolutionizing Internet of Underwater Things with Federated Learning, Underwater Drone, Underwater Imagery with AI/ML and IoT in ROV Technology and Ocean Cleanup has been demonstrated using innovative approaches to addressing underwater challenges. The book also includes a Review on the Optics and Photonics in Environmental Sustainability, focusing on the role of optics in marine conservation. Security issues are tackled in Intelligent Hash Function Based Key-Exchange Scheme for Ocean Underwater Data Transmission, and the overarching potential of AI in marine resource management is discussed in Artificial Intelligence as Key-enabler for Safeguarding the Marine Resources.

This book is considered as an essential medium to introduce the up-to-date findings, new level research, and developing fields in the area of technology and computing for First International Conference on Emerging Technologies and Computing Innovations (ICETCI-2025). The objective of the ICETCI-2025 is to provide a platform to highlight state-of-the-art research work and innovative findings in technology and computing. The conference is focused on filling the gap between modern theoretical improvements and real-life issues by providing a platform for discussions among experts in different areas concerning innovative fields like AI, ML, big data, blockchain, IoT giant computing, etc. ICETCI-2025 benefits from being a multidisciplinary approach for a broad set of emerging technologies. The conference aims to foster the exchange of ideas and experiences by bringing together leaders, researchers, academics, industry practitioners as well as policymakers. Much of the diversity they provide aids unconventional thinking, applicable implementation, and strategic growth that tackles current as well as future technology hurdles. ICETCI-2025 proceedings present high quality research papers, case studies and reviews focusing on state of the art developments in domains like artificial intelligence, big data analytics, cybersecurity and privacy, IoT and blockchain and cloud computing. By collaborating with academia, industry leaders, and policymakers, these proceedings are essential for bringing attention to emerging trends and best practices. They play a critical role in promoting knowledge, stimulating innovation, and providing cross-disciplinary support to help drive technological development. This book is aimed at researchers, academics, graduate students, industry professionals, and policymakers who have an interest in the field of computing, information technologies, and their application.

This book presents the groundbreaking ways artificial intelligence (AI) is revolutionizing the healthcare industry and delves into how AI technologies are enhancing patient care, improving diagnostic accuracy, and streamlining healthcare operations.

This book provides a thorough introduction to graph mining and addresses foundational concepts and advanced techniques along with practical applications across various fields.

This book provides an in-depth examination of the advanced computational and mathematical techniques crucial for the development and optimization of Wave Energy Converter (WEC) systems. As global warming and climate change continue to impact ocean engineering, the need for sustainable and renewable energy sources becomes increasingly urgent. Wave energy, with its vast and largely untapped potential, stands out as a key player in clean power generation. This volume serves as a focal point in marine renewable energies, aligning with the Sustainable Development Goals (SDG-14).The chapters in this book cover a wide array of topics, showcasing the multifaceted applications of computation and hydrodynamic simulation in ocean engineering. Key concepts include the use of multi-criteria decision-making (MCDM) techniques combined with fuzzy logic theory for optimizing ocean wave energy. The book also presents a systematic assessment of WECs using spherical fuzzy multi-criteria group decision-making techniques. Readers will gain insights into the latest advancements in Computational Fluid Dynamics (CFD) and multi-objective optimization algorithms, which are essential for enhancing wave energy harvesting efficiency. Furthermore, the integration of Artificial Intelligence (AI) for predictive maintenance and fault diagnosis in hybrid solar-wind microgrid systems is thoroughly explored.This book is designed for researchers, engineers, and practitioners in the fields of marine renewable energies and ocean engineering. It offers cutting-edge insights into the computational and optimization strategies necessary for advancing sustainable maritime transportation and achieving the Sustainable Development Goals (SDG-14). Whether you are a seasoned professional or a newcomer to the field, this book provides the knowledge and tools needed to harness the power of wave energy and contribute to a sustainable future.

This book provides a deep dive into how Generative Artificial Intelligence is fostering innovation apart from being impactful, and key problems that affect the healthcare ecosystem as a whole are now being solved. With the rapid rise of Generative Artificial Intelligence (AI), industries are changing rapidly, and healthcare is no exception. Generative AI, as a transformative subset of AI, has the extraordinary ability to create new data, simulate scenarios, and optimize complex processes. Its potential for medical diagnostics and drug development is beyond doubt and it is born to revolutionize medical research and Personalized treatment. Reasoning subtitled Generative AI for Healthcare, this exploratory volume on cutting-edge technology's profound impact on modern medicine is based on years of dedicated research. Key highlights include:·         Using Generative AI to actually produce synthetic teaching sets and consequently re-armed medical-solving equipment will in turn enhance diagnosis and accuracy·         Reducing the amount of time and costs for developing drugs by means of artificial intelligence, by iterating through virtual compounds and simulating molecular environments·         Creating personalized treatment strategies out of specific patient profiles that embrace precision medicine, improving outcomes·         Simulating medical scenarios to measure the effectiveness of a cure in advance expensive, high-risk trials, the profound secrets behind complex diseases are slowly coming to light.This book is designed to help the next generation of healthcare practices address research gaps, regulatory challenges, ethical considerations, and other concerns. Balancing rich case studies with practical insights and forward -looking ideas, this book aims to link up the promise of technological innovation in healthcare with its real application. The book also highlights the need for responsible AI adoption, addressing issues such as data privacy, bias reduction in models, explainable and reliable AI systems. The goal is to provide healthcare professionals, researchers and policy makers with knowledge and tools needed to use Generative AI responsibly and effectively. Whether you are a healthcare provider, AI researcher or industry innovator, Generative AI for Healthcare gives you an essential primer on how AI can be applied to transform patient care outcomes, drive medical research forward -- and even shape the future of healthcare itself.