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With the advent of digital computers and rapidly developing computational techniques, computer simulations are widely used as predictive tools to supplement experimental techniques in engineering and technology. Computational biomechanics is a field where the movements of biological systems are assessed in the light of computer algorithms describing solid and fluid mechanical principles. This rapidly developing field must be constantly studied and updated as it continues to expand. Advances in Computational Approaches in Biomechanics examines the current trends and applications of intelligent computational techniques used to analyze a multitude of phenomena in the field of biomechanics and elaborates a series of sophisticated techniques used for computer simulation in solid mechanics, fluid mechanics, and fluid-solid interface. Covering a range of topics such as injury prevention, element analysis, and soft tissues, this publication is ideal for industry professionals, practitioners, researchers, academicians, instructors, and students.

"This book explores current trends in the development of energy supply systems associated with the use of concentrated solar radiation"--

"The purpose of this reference book is to serve as a compendium of all available knowledge of Science of Water and Society, complete with a detailed index, as well as numerous adjuncts such as bibliographies, illustrations, lists of abbreviations and foreign expressions"--

"The purpose of this reference book is to serve as a compendium of all available knowledge of Science of Water and Society, complete with a detailed index, as well as numerous adjuncts such as bibliographies, illustrations, lists of abbreviations and foreign expressions"--

Internet of things (IoT) applications employed for healthcare generate a huge amount of data that needs to be analyzed to produce the expected reports. To accomplish this task, a cloud-based analytical solution is ideal in order to generate faster reports in comparison to the traditional way. Given the current state of the world in which every day IoT devices are developed to provide healthcare solutions, it is essential to consider the mechanisms used to collect and analyze the data to provide thorough reports. Integrating AI in IoT Analytics on the Cloud for Healthcare Applications applies artificial intelligence (AI) in edge analytics for healthcare applications, analyzes the impact of tools and techniques in edge analytics for healthcare, and discusses security solutions for edge analytics in healthcare IoT. Covering topics such as data analytics and next generation healthcare systems, it is ideal for researchers, academicians, technologists, IT specialists, data scientists, healthcare industries, IoT developers, data security analysts, educators, and students.

The Sustainable Development Goals are a collection of 17 interlinked global goals designed to be a blueprint to achieve a better and more sustainable future for all. Sustainable development is a long-term solution to how we plan our indefinite progress in the future, and the concept covers a broad scope of environmental, social, and economic developments. Sustainable development is the ideal vision of the future and requires further study and consideration. Innovative Economic, Social, and Environmental Practices for Progressing Future Sustainability explores the current practices in economic, social, and environmental sustainable development. Covering topics such as digital economies, community development, and equality, this reference work is ideal for academicians, researchers, practitioners, policymakers, government officials, decision makers, instructors, and students.

Data science has been playing a vital role in almost all major fields. Many researchers are interested in the development of IT applications, which are user-driven with a focus on issues. This can be addressed using data science. User-driven research and data science have gained much attention from many private, public, and government organizations and research institutions. Designing User Interfaces With a Data Science Approach promotes the inclusion of more diversified users for user-centered designs of applications across domains and analyzes user data with a data science approach for effective and user-friendly user interface designs. It introduces the foundations of advanced topics of human-computer interaction, particularly with user-centered designs and techniques. Covering topics such as artificial neural networks, natural dialog systems, and machine learning, this book is an essential resource for faculty, research scholars, industry professionals, students of higher education, mathematicians, data scientists, interaction designers, visual designers, software engineers, user experience researchers, accessibility engineers, cognitive system engineers, academicians, and libraries.

"This research-based reference discusses the issues that the agricultural industry currently faces and the technological opportunities that can be explored to help protect and predict crop growth and achieve more resilient agricultural processes"--

"This research-based reference discusses the issues that the agricultural industry currently faces and the technological opportunities that can be explored to help protect and predict crop growth and achieve more resilient agricultural processes"--

"This research-based reference discusses the issues that the agricultural industry currently faces and the technological opportunities that can be explored to help protect and predict crop growth and achieve more resilient agricultural processes"--

Technological advancements of recent decades have reshaped the way people socialize, work, learn, and ultimately live. The use of cyber-physical systems (CPS) specifically have helped people lead their lives with greater control and freedom. CPS domains have great societal significance, providing crucial assistance in industries ranging from security to healthcare. At the same time, machine learning (ML) algorithms are known for being substantially efficient, high performing, and have become a real standard due to greater accessibility, and now more than ever, multidisciplinary applications of ML for CPS have become a necessity to help uncover constructive solutions for real-world problems. Real-Time Applications of Machine Learning in Cyber-Physical Systems provides a relevant theoretical framework and the most recent empirical findings on various real-time applications of machine learning in cyber-physical systems. Covering topics like intrusion detection systems, predictive maintenance, and seizure prediction, this book is an essential resource for researchers, machine learning professionals, independent researchers, scholars, scientists, libraries, and academicians.

"This reference book covers emerging trends of software development and testing, discussing the newest developments in agile software and its usage spanning multiple industries, covering topics such as global software engineering, knowledge management, and product development"--

"This reference book covers emerging trends of software development and testing, discussing the newest developments in agile software and its usage spanning multiple industries, covering topics such as global software engineering, knowledge management, and product development"--

"This reference book covers emerging trends of software development and testing, discussing the newest developments in agile software and its usage spanning multiple industries, covering topics such as global software engineering, knowledge management, and product development"--

"This reference book covers emerging trends of software development and testing, discussing the newest developments in agile software and its usage spanning multiple industries, covering topics such as global software engineering, knowledge management, and product development"--