Quantum computing is radically different from the conventional approach of transforming bit-strings from one set of zeros and ones to another. With quantum computing, everything changes. The physics used to understand bits of information and the devices that manipulate them are vastly different. Quantum engineering is a revolutionary approach to quantum technology. Technology Road Mapping for Quantum Computing and Engineering explores all the aspects of quantum computing concepts, engineering, technologies, operations, and applications from the basics to future advancements. Covering topics such as machine learning, quantum software technology, and technology road mapping, this book is an excellent resource for data scientists, engineers, students and professors of higher education, computer scientists, researchers, and academicians.

Today, computation is an essential component of every technology. However, there has not been much research on quantum computing, even though it has the capability to solve complex problems in an efficient way. Further study is required to fully understand the uses and benefits of this technology. The Handbook of Research on Quantum Computing for Smart Environments presents investigating physical realizations of quantum computers, encoders, and decoders, including photonic quantum realization, cavity quantum electrodynamics, and many more topics on Bits to Qubits. Covering key topics such as machine learning, software, quantum algorithms, and neural networks, this major reference work is ideal for engineers, computer scientists, physicists, mathematicians, researchers, academicians, scholars, practitioners, instructors, and students.

Today's supply chains are becoming more complex and interconnected. As a result, traditional optimization engines struggle to cope with the increasing demands for real-time order fulfillment and inventory management. With the expansion and diversification of supply chain networks, these engines require additional support to handle the growing complexity effectively. This poses a significant challenge for supply chain professionals who must find efficient and cost-effective solutions to streamline their operations and promptly meet customer demands. Quantum Computing and Supply Chain Management: A New Era of Optimization offers a transformative solution to these challenges. By harnessing the power of quantum computing, this book explores how supply chain planners can overcome the limitations of traditional optimization engines. Quantum computing's ability to process vast amounts of data from IoT sensors in real time can revolutionize inventory management, resource allocation, and logistics within the supply chain. It provides a theoretical framework and practical examples to illustrate how quantum algorithms can enhance transparency, optimize dynamic inventory allocation, and improve supply chain resilience.

Almost every element of life, from commerce and agriculture to communication and entertainment, has been profoundly altered by computing. Around the world, people rely on computers for the creation of systems for energy, transportation, and military use. Additionally, computing fosters scientific advancements that advance our basic understanding of the world and assist in finding answers to pressing health and environmental issues. Novel Research and Development Approaches in Heterogeneous Systems and Algorithms addresses novel research and developmental approaches in heterogenous systems and algorithms for information-centric networks of the future. Covering topics such as image identification and segmentation, materials data extraction, and wireless sensor networks, this premier reference source is a valuable resource for engineers, consultants, practitioners, computer scientists, students and educators of higher education, librarians, researchers, and academicians.

Cyber-professionals recognize that some defensive measures could exacerbate cyber-defense challenges by motivating attackers to adapt—unintentionally inspiring attackers to develop more potent and resilient capabilities. Further study in this area is required to ensure defense and security practices are up to date. Adaptive Security and Cyber Assurance for Risk-Based Decision Making explores decision making in the context of software-based systems and discusses why it is difficult to achieve. It also identifies a discipline termed cyber-assurance, which considers the interactions of assurance-enhancing technology, system architecture, and the development life cycle. Covering key topics such as cyber assurance, security, and defensive operations, this premier reference source is ideal for industry professionals, computer scientists, academicians, engineers, researchers, scholars, practitioners, librarians, instructors, and students.

Innovation is the key to maintain competitive advantage. Innovation in products, processes, and business models help companies to provide economic value to their customers. Identifying the innovative ideas, implementing those ideas, and absorbing them in the market requires investing many resources that could incur large costs. Technology encourages companies to foster innovation to remain competitive in the marketplace. Emerging Technologies for Innovation Management in the Software Industry serves as a resource for technology absorption in companies supporting innovation. It highlights the role of technology to assist software companies—especially small start-ups—to innovate their products, processes, and business models. This book provides the necessary guidelines of which tools to use and under what situations. Covering topics such as risk management, prioritization approaches, and digitally-enabled innovation processes, this premier reference source is an ideal resource for entrepreneurs, software developers, software managers, business leaders, engineers, students and faculty of higher education, researchers, and academicians.

It has become clear that managing and maintaining state-of-the-art healthcare facilities is more important than ever before. Healthcare consists of many different institutions and supports personnel ranging from laboratories of universities, public and private hospitals, research centers of health institutions, public health institutes, institutions, and organizations engaged in research and development in the field of medicine. For all these entities to be successful, there needs to be coordination among the bodies and quality must be kept at a very high level. The Handbook of Research on Quality and Competitiveness in the Healthcare Services Sector considers the current state of the healthcare services sector and examines future directions. Covering topics such as quality excellence models, accreditation, and e-health, this major reference work is an essential resource for economists, healthcare specialists, government officials, consultants, business leaders and executives, healthcare professionals, IT managers, students and educators of higher education, researchers, and academicians.

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.

Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.