In recent years, substantial efforts are being made in the development of reliability theory including fuzzy reliability theories and their applications to various real-life problems. Fuzzy set theory is widely used in decision making and multi criteria such as management and engineering, as well as other important domains in order to evaluate the uncertainty of real-life systems. Fuzzy reliability has proven to have effective tools and techniques based on real set theory for proposed models within various engineering fields, and current research focuses on these applications. Advancements in Fuzzy Reliability Theory introduces the concept of reliability fuzzy set theory including various methods, techniques, and algorithms. The chapters present the latest findings and research in fuzzy reliability theory applications in engineering areas. While examining the implementation of fuzzy reliability theory among various industries such as mining, construction, automobile, engineering, and more, this book is ideal for engineers, practitioners, researchers, academicians, and students interested in fuzzy reliability theory applications in engineering areas.

This book presents the most commonly used techniques for the most statistical inferences based on fuzzy data. It brings together many of the main ideas used in statistical inferences in one place, based on fuzzy information including fuzzy data. This book covers a much wider range of topics than a typical introductory text on fuzzy statistics. It includes common topics like elementary probability, descriptive statistics, hypothesis tests, one-way ANOVA, control-charts, reliability systems and regression models. The reader is assumed to know calculus and a little fuzzy set theory. The conventional knowledge of probability and statistics is required. Key Features: Includes example in Mathematica and MATLAB. Contains theoretical and applied exercises for each section. Presents various popular methods for analyzing fuzzy data. The book is suitable for students and researchers in statistics, social science, engineering, and economics, and it can be used at graduate and P.h.D level.

Smart grid is a new generation of power grids that is expected to enhance its reliability and reduce carbon footprint by integrating distributed resources. Microgrid technology allows the integration of renewable energies, which come in three modes: AC, DC, or hybrid. The increasing number of DC loads, the need to reduce power loss in converting DC power to AC, and the existence of DC storage units have favored the adoption of DC microgrids. The electrification of the transportation sector has further supported the adoption of DC microgrids. A DC microgrid system comprises renewable resources, DC storage elements, DC loads, and intelligent electrical devices. It has gained interest due to its efficiency, scalability, and cost-effectiveness. DC microgrids play a crucial role in powering diverse applications such as data centers, residential areas, base stations, and electric vehicle charging stations. This book covers the design, control, and management of DC microgrids in both islanded and grid-connected modes. It focuses on ICT infrastructure, security, sensors, embedded systems, machine learning algorithms, edge/fog computing, and the socio-economic impact.

Exploring Ethical Dimensions of Environmental Sustainability and Use of AI is a comprehensive and insightful book that delves into the ethical implications and challenges that emerge at the intersection of environmental sustainability and the utilization of artificial intelligence (AI). With a focus on key ethical dimensions such as transparency, equity, privacy, autonomy, unintended consequences, and trade-offs, this book aims to provide a thorough understanding of the responsible deployment and development of AI in the realm of environmental sustainability. By addressing the ethical aspects and challenges involved, this book contributes to the development of ethical guidelines and frameworks that align AI technologies with the vision of a sustainable and equitable future. Researchers will find immense value in this book as it offers a holistic exploration of the ethical implications, filling a critical gap in the existing literature. Policymakers can gain valuable insights to inform the creation of ethical guidelines and regulations governing AI use in sustainable initiatives. Practitioners, including professionals working in environmental organizations or technology companies, will acquire practical knowledge to guide their decision-making and implementation of AI-driven solutions.

We are currently witnessing a significant transformation in the development of education on all levels and especially in post-secondary education. To face these challenges, higher education must find innovative ways to quickly respond to these new needs. These were the aims connected with the 25th International Conference on Interactive Collaborative Learning (ICL2022), which was held in Vienna, Austria, from September 27 to 30, 2022. Since its beginning in 1998, this conference is devoted to new approaches in learning with a focus on collaborative learning in higher education. This book contains papers in the fields of: • New Learning Models and Applications• Project-Based Learning• Engineering Pedagogy Education• Research in Engineering Pedagogy• Teaching Best Practices• Real World Experiences• Academia-Industry Partnerships• Trends in Master and Doctoral Research. Interested readership includes policymakers, academics, educators, researchers in pedagogy and learning theory, school teachers, the learning industry, further and continuing education lecturers, etc.

In real management situations, uncertainty is inherently present in decision making. As such, it is increasingly imperative to research and develop new theories and methods of fuzzy sets. Theoretical and Practical Advancements for Fuzzy System Integration is a pivotal reference source for the latest scholarly research on the importance of expressing and measuring fuzziness in order to develop effective and practical decision making models and methods. Featuring coverage on an expansive range of perspectives and topics, such as fuzzy logic control, intuitionistic fuzzy set theory, and defuzzification, this book is ideally designed for academics, professionals, and researchers seeking current research on theoretical frameworks and real-world applications in the area of fuzzy sets and systems.

Cyber-physical systems (CPS) can be defined as systems in which physical objects are represented in the digital world and integrated with computation, storage, and communication capabilities and are connected to each other in a network. The goal in the use of the CPS is integrating the dynamics of the physical processes with those of the software and networking, providing abstractions and modelling, design, and analysis techniques for the integrated whole. The notion of CPS is linked to concepts of robotics and sensor networks with intelligent systems proper of computational intelligence leading the pathway. Recent advances in science and engineering improve the link between computational and physical elements by means of intelligent systems, increasing the adaptability, autonomy, efficiency, functionality, reliability, safety, and usability of cyber-physical systems. The potential of cyber-physical systems will spread to several directions, including but not limited to intervention, precision manufacturing, operations in dangerous or inaccessible environments, coordination, efficiency, Maintenance 4.0, and augmentation of human capabilities. Design, Applications, and Maintenance of Cyber-Physical Systems gives insights about CPS as tools for integrating the dynamics of the physical processes with those of software and networking, providing abstractions and modelling, design, and analysis techniques for their smart manufacturing interoperation. The book will have an impact upon the research on robotics, mechatronics, integrated intelligent multibody systems, Industry 4.0, production systems management and maintenance, decision support systems, and Maintenance 4.0. The chapters discuss not only the technologies involved in CPS but also insights into how they are used in various industries. This book is ideal for engineers, practitioners, researchers, academicians, and students who are interested in a deeper understanding of cyber-physical systems (CPS), their design, application, and maintenance, with a special focus on modern technologies in Industry 4.0 and Maintenance 4.0.

Among the wide range of programming tools available, the technical analysis and calculations are realized by MATLAB®, which is recognized as a convenient and effective tool for modern science and technology. Thus, mastering its latest versions and practical solutions is increasingly essential for the creation of new products in mechanics, electronics, chemistry, life sciences, and modern industry. Modern mechanical and tribology sciences specialists widely use computers and some special programs, but need a universal tool for solving, simulating, and modeling specific problems from their area. There is plenty of information available on MATLAB® for the general engineer, but there is a gap in the field for research that applies MATLAB® to two wide, interdisciplinary, and topical areas: tribology and mechanics. MATLAB® With Applications in Mechanics and Tribology explores how MATLAB® is used as a tool for subsequent computer solutions, applying it to both traditional and modern problems of mechanics and materials sciences. The problem solving in this book includes calculations of the mechanical parts, machine elements, production process, quality assurance, fluid mechanics parameters, thermodynamic and rheological properties of the materials as well as the state equations, descriptive statistics, and more. This book is ideal for scientists, students and professors of engineering courses, self-instructing readers, programmers, computer scientists, practitioners, and researchers looking for concise and clear information on learning and applying MATLAB® software to mechanics, tribology, and material physics.

There is no doubt that there has been much excitement regarding the pioneering contributions of artificial intelligence (AI), the internet of things (IoT), and blockchain technologies and tools in visualizing and realizing smarter as well as sophisticated systems and services. However, researchers are being bombarded with various machine and deep learning algorithms, which are categorized as a part and parcel of the enigmatic AI discipline. The knowledge discovered gets disseminated to actuators and other concerned systems in order to empower them to intelligently plan and insightfully execute appropriate tasks with clarity and confidence. The IoT processes in conjunction with the AI algorithms and blockchain technology are bound to lay out a stimulating foundation for producing and sustaining smarter systems for society. Advancing Smarter and More Secure Industrial Applications Using AI, IoT, and Blockchain Technology articulates and accentuates various AI algorithms, fresh innovations in the IoT, and blockchain spaces. The domain of transforming raw data to information and to relevant knowledge is gaining prominence with the availability of data ingestion, processing, mining, analytics algorithms, platforms, frameworks, and other accelerators. Covering topics such as blockchain applications, Industry 4.0, and cryptography, this book serves as a comprehensive guide for AI researchers, faculty members, IT professionals, academicians, students, researchers, and industry professionals.

With the field of computational statistics growing rapidly, there is a need for capturing the advances and assessing their impact. Advances in simulation and graphical analysis also add to the pace of the statistical analytics field. Computational statistics play a key role in financial applications, particularly risk management and derivative pricing, biological applications including bioinformatics and computational biology, and computer network security applications that touch the lives of people. With high impacting areas such as these, it becomes important to dig deeper into the subject and explore the key areas and their progress in the recent past. Methodologies and Applications of Computational Statistics for Machine Intelligence serves as a guide to the applications of new advances in computational statistics. This text holds an accumulation of the thoughts of multiple experts together, keeping the focus on core computational statistics that apply to all domains. Covering topics including artificial intelligence, deep learning, and trend analysis, this book is an ideal resource for statisticians, computer scientists, mathematicians, lecturers, tutors, researchers, academic and corporate libraries, practitioners, professionals, students, and academicians.