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This book highlights applications that include machine learning methods to enhance new developments in complex and unmanned systems. The contents are organized from the applications requiring few methods to the ones combining different methods and discussing their development and hardware/software implementation. The book includes two parts: the first one collects machine learning applications in complex systems, mainly discussing developments highlighting their modeling and simulation, and hardware implementation. The second part collects applications of machine learning in unmanned systems including optimization and case studies in submarines, drones, and robots. The chapters discuss misce...
Artificial Intelligence (AI) and Machine Learning (ML) are set to revolutionize all industries, and the Intelligent Transportation Systems (ITS) field is no exception. While ML, especially deep learning models, achieve great performance in terms of accuracy, the outcomes provided are not amenable to human scrutiny and can hardly be explained. This can be very problematic, especially for systems of a safety-critical nature such as transportation systems. Explainable AI (XAI) methods have been proposed to tackle this issue by producing human interpretable representations of machine learning models while maintaining performance. These methods hold the potential to increase public acceptance and trust in AI-based ITS. FEATURES: Provides the necessary background for newcomers to the field (both academics and interested practitioners) Presents a timely snapshot of explainable and interpretable models in ITS applications Discusses ethical, societal, and legal implications of adopting XAI in the context of ITS Identifies future research directions and open problems
This book summarizes the work developed over more than two decades in the field of advanced calibration techniques for vector network analyzers, by the RF and Microwave Group at The Center for Scientific Research and Higher Education of Ensenada, Baja California, Mexico, which is led by Dr. J. Apolinar Reynoso-Hernández, author of this book. This book is written so that every electrical engineer, with knowledge of electrical circuits and linear algebra basics, can understand the principles of VNA calibration techniques. Vector network analyzers are normally used by engineers and researchers working in the RF and microwave field, which usually requires advanced and specialized courses at gra...
World-wide trends such as globalization, demographic shifts, increased customer demands, and shorter product lifecycles present a significant challenge to the road freight transport industry: meeting the growing road freight transport demand economically while striving for sustainability. Artificial intelligence, particularly machine learning, is expected to empower transport planners to incorporate more information and react quicker to the fast-changing decision environment. Hence, using machine learning can lead to more efficient and effective transport planning. However, despite the promising prospects of machine learning in road freight transport planning, both academia and industry struggle to identify and implement suitable use cases to gain a competitive edge. In her dissertation, Sandra Lechtenberg explores how machine learning can enhance decision-making in operational and real-time road freight transport planning. She outlines an implementation guideline, which involves identifying decision tasks in planning processes, assessing their suitability for machine learning, and proposing steps to follow when implementing respective algorithms.
This book gathers a collection of the latest research, applications, and proposals, introducing readers to innovations and concepts from diverse environments and systems. As such, it will provide students and professionals alike with not only cutting-edge information, but also new inspirations and potential research directions. Each chapter focuses on a specific aspect of applied decision making, e.g. in complex systems, computational intelligence, security, and ubiquitous computing.
This book reports on fundamental research, cutting-edge technologies and industrially-relevant applications in biomedical engineering. It covers methods for analysis, modeling and simulation of biological systems, reporting on the development and design of advanced biosensors, nanoparticles and wearable devices. It covers applications in disease monitoring and therapy, tissue engineering, sport and rehabilitation, and telehealth. It also reports on engineering methods for improving and monitoring medical service, and on advanced robotic applications. Gathering the proceedings of the XLV Congreso Nacional de Ingeniería Biomédica (CNIB2022), organised by the Mexican Society of Biomedical Engineering, this book offers a timely snapshot on technologies and methods in bioengineering, and on challenges related to their practical implementation in the health sector.
Christoph Jan Bartodziej examines by means of an empirical study which potential Industry 4.0 technologies do have regarding end-to-end digital integration in production logistics based on their functions. According to the relevance of the concept Industry 4.0 and its early stage of implementation it is essential to clarify terminology, explain relations and identify drivers and challenges for an appropriate use of Industry 4.0 technologies. The results will constitute a profound basis to formulate recommendations for action for technology suppliers and technology users.
Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constraint satisfaction and machine learning. While no previous familiarity with heuristic search is necessary the reader should have a basic knowledge of algorithms, data structures, and calculus. Real-world case studies and chapter ending exercises help to create a full and realized picture of how search fits into the world of artificial intelligence and the one around us. - Provides real-world success stories and case studies for heuristic search algorithms - Includes many AI developments not yet covered in textbooks such as pattern databases, symbolic search, and parallel processing units
Modern cryptology, which is the basis of information security techniques, started in the late 70's and developed in the 80's. As communication networks were spreading deep into society, the need for secure communication greatly promoted cryptographic research. The need for fast but secure cryptographic systems is growing bigger. Therefore, dedicated systems for cryptography are becoming a key issue for designers. With the spread of reconfigurable hardware such as FPGAs, hardware implementations of cryptographic algorithms become cost-effective. The focus of this book is on all aspects of embedded cryptographic hardware. Of special interest are contributions that describe new secure and fast hardware implementations and new efficient algorithms, methodologies and protocols for secure communications. This book is organised in two parts. The first part is dedicated to embedded hardware of cryptosystems while the second part focuses on new algorithms for cryptography, design methodologies and secure protocols.