Many techniques have been developed to control the variety of dynamic systems. To develop those control techniques, it is fundamental to know the mathematical relations between the system inputs and outputs. Incorporating Nature-Inspired Paradigms in Computational Applications is a critical scholarly resource that examines the application of nature-inspired paradigms on system identification. Featuring coverage on a broad range of topics such as biogeographic computation, evolutionary control systems, and natural computing, this book is geared towards IT professionals, engineers, computer scientists, academicians, researchers, and graduate-level students seeking current research on the application of nature-inspired paradigms.

In the swiftly evolving realm of technology, the challenge of classical computing's constraints in handling intricate problems has become pronounced. While classical computers excel in many areas, they struggle with complex issues in cryptography, optimization, and molecular simulation. Addressing these escalating challenges requires a disruptive solution to push the boundaries of computation and innovation. Principles and Applications of Quantum Computing Using Essential Math, authored by A. Daniel, M. Arvindhan, Kiranmai Bellam, and N. Krishnaraj. This guide pioneers the transformative potential of quantum computing by seamlessly blending rigorous mathematics with quantum theory. It equips scholars, researchers, and aspiring technologists with insights to grasp and harness quantum computing's capabilities. By delving into quantum gates, algorithms, and error correction techniques, the book demystifies quantum computing, inviting exploration of quantum machine learning, cryptography, and the dynamic interplay between classical and quantum computing. As the quantum landscape expands, this book acts as a vital companion, navigating readers through the converging realms of industry, academia, and innovation. Principles and Applications of Quantum Computing Using Essential Math arrives as a timely answer to the limitations of classical computing, providing scholars with an essential roadmap to navigate the quantum technology landscape. With its clear explanations, practical applications, and forward-looking perspectives, this book serves as an indispensable tool for unraveling quantum computing's mysteries and driving innovation into uncharted domains.

Genetic programming is a new and evolutionary method that has become a novel area of research within artificial intelligence known for automatically generating high-quality solutions to optimization and search problems. This automatic aspect of the algorithms and the mimicking of natural selection and genetics makes genetic programming an intelligent component of problem solving that is highly regarded for its efficiency and vast capabilities. With the ability to be modified and adapted, easily distributed, and effective in large-scale/wide variety of problems, genetic algorithms and programming can be utilized in many diverse industries. This multi-industry uses vary from finance and economics to business and management all the way to healthcare and the sciences. The use of genetic programming and algorithms goes beyond human capabilities, enhancing the business and processes of various essential industries and improving functionality along the way. The Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms covers the implementation, tools and technologies, and impact on society that genetic programming and algorithms have had throughout multiple industries. By taking a multi-industry approach, this book covers the fundamentals of genetic programming through its technological benefits and challenges along with the latest advancements and future outlooks for computer science. This book is ideal for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.

The results of computational model simulations allow researchers and clinicians to make predictions about what will happen in the biological systems that are being studied in response to changing conditions for a disease or disorder. With a well-developed computational model, researchers and clinicians can better understand the cause of a disease or a disorder and predict treatment results. Computational Models for Biomedical Reasoning and Problem Solving is a critical scholarly publication that provides insightful strategies to developing computational models that allow for the better understanding and treatment of various diseases and disorders. Featuring topics such as biomedicine, neuroscience, and artificial intelligence, this book is ideal for practitioners, clinicians, researchers, psychologists, and engineers.

As the healthcare industry continues to expand, it must utilize technology to ensure efficiencies are maintained. Healthcare needs to move in a direction where computational methods and algorithms can relieve the routine work of medical doctors, leaving them more time to carry out more important and skilled tasks such as surgery. Computational Methods and Algorithms for Medicine and Optimized Clinical Practice discusses some of the most interesting aspects of theoretical and applied research covering complementary facets of computational methods and algorithms to achieve greater efficiency and support medical personnel. Featuring research on topics such as healthcare reform, artificial intelligence, and disease detection, this book will particularly appeal to medical professionals and practitioners, hospitals, administrators, students, researchers, and academicians.

Different levels in health sciences, in particular public health, have acknowledged the significant role of epidemiology methods for early detection of emerging infections, alert systems, and preparedness interventions. Therefore, it is important to understand how epidemiological research is conducted and how it can be used at various levels to make exposure or incidence data on a general population available. In this, epidemiological research connected to both human and technology interactions is of primary importance. Epidemiological Research Applications for Public Health Measurement and Intervention provides relevant theoretical frameworks and the latest empirical research findings in the field of epidemiology. The chapters within this essential reference source enhance the knowledge of epidemiological research and measurement to investigate, detect, and monitor emerging pathological infections. While highlighting topics that include the history of epidemiology; the applications of epidemiology; and also the uses, principles, and roles of epidemiology, this book is ideally intended for professionals and researchers working in the field of health sciences in various disciplines and government officials, policymakers, practitioners, stakeholders, researchers, academicians, and students who are interested in epidemiological research and measurement for increasing the effectiveness of public health practice.

Each day, novel neuroscientific findings show that researchers are focusing on developing advanced smart hardware designs and intelligent computational models to imitate the human brain’s computational abilities. The advancements in smart materials provide a significant role in inventing intelligent bioelectronic device designs with smart features such as accuracy, low power consumption, and more. These advanced and intelligent computing models through machine and smart deep learning algorithms help to understand the information processing capabilities of the human brain with optimum accuracy. Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering highlights advanced computational models and hardware designs in neurology and integration of mathematical physical, biological, chemical, and engineering models to mimic brain functions; discovers new technological diagnosis techniques; and achieves high accuracy in learning models to better understand the functioning of the human brain. Providing rich information on brain-computer interfacing, gamification in children, and vestibular rehabilitation, this text acts as an essential resource for experts in electrophysiological studies, neurologists, neuro-physiotherapists, neuro-radiologists, intelligent system developers, bio-software and hardware developers, neuro database collectors, electro-physiologists, professors associated with neurology, psychiatrists, engineers, scientists, and students from academia and industry involved in interdisciplinary approaches to neurology.

Healthcare and pharmaceuticals are rapidly advancing with technological innovations, and the lack of understanding of AI algorithms poses a significant challenge in these fields. The need for more transparency in AI decision-making processes raises concerns about accountability, ethical implications, and regulatory compliance. As stakeholders in these critical sectors seek clarity and understanding, Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry provides a reliable resource to discover new solutions. This book serves as a comprehensive guide, unraveling the complexities of explainable artificial intelligence (XAI) and its pivotal role in transforming healthcare and pharmaceutical practices. Demystifying AI algorithms and revealing their decision-making mechanisms equips readers with the foundational knowledge needed to confidently navigate AI integration in these domains. From healthcare professionals to policymakers, its insights cater to a diverse audience, fostering cross-disciplinary collaboration and facilitating informed decision-making.

In today’s rapidly evolving world, it has never been more critical to consider key environmental issues such as climate change, pollution, and endangered species. Society faces an unknown future where the fate of the environment is continuously in flux based on current preservation initiatives that governments develop. In order to ensure the world is protected moving forward, further study on the importance of securing environments, ecosystems, and species is necessary to successfully implement change. The Research Anthology on Ecosystem Conservation and Preserving Biodiversity considers the best practices and strategies for protecting our current ecosystems as well as the potential ramifications of failing to implement policies. Society is at a crossroads where if we continue to ignore the danger and warning signs brought about by environmental issues, we will be unable to maintain a healthy environment. Covering essential topics such as extinction, climate change, and pollution, this major reference work is ideal for scientists, industry professionals, researchers, academicians, policymakers, scholars, practitioners, instructors, and students.

Exploring ideas of post-mortem existence through the lenses of complex systems and traditional cultural perspectives offers a deeper understanding about life, death, and the existence beyond. Self-organization theory provides a framework for examining how cultural systems evolve and adapt new concepts of post-mortem states, where individual consciousness and collective memory continue to evolve. Traditional cultures provide diverse and deep-rooted views on the afterlife, often envisioning a continued existence, spiritual transformation, or idea perpetuated by moral beliefs. Further research on integrating these perspectives is necessary to gain a more nuanced approach to post-mortem existence understanding and appreciation for evolving systems and cultural constructs. Post-Mortem Existence Within the Complex Systems Self-Organization Theory Framework and in Traditional Cultures explores the ideals of post-mortem existences in traditional cultures using a complex systems self-organization theory framework. Religious structures and cultural responses to death are outlined while examining various models and scenarios. This book covers topics such as biology, philosophy, and anthropology, and is a useful resource for scientists, biologists, medical professionals, philosophers, anthropologists, academicians, and researchers.