This book focuses on decision-making problems in engineering. It investigates the ranking aggregation problem and the related features, such as input/output data, simplification hypotheses, importance hierarchy of experts. In addition to a well-structured overview of several interesting, consolidated methodological approaches, it presents innovative approaches that can also be applied profitably in other fields. The fascinating selection of topics included is based on research that has been developed in the past twenty years. The descriptions are supported by figures, tables, flowcharts, diagrams, examples and practical case studies. The book is an ideal resource for engineering academics, practitioners, technicians and students, who do not necessarily have an in-depth knowledge of decision-making. It is also a thought-provoking read for engineers and academics looking for innovative ways to improve engineering processes in a variety of fields, such as conceptual design, quality improvement, reliability engineering. “Today, rankings are exercised in all spheres of life, products are ranked on Amazon and similar platforms; services such as restaurants and hotels on platforms such as TripAdvisor; and other services such as lectures or even medical treatment on different specialized platforms. We often make our daily decisions based on these rankings. The quality of our decisions depends on our ability to select appropriate methods to fit the context and needs. We need to be familiar with the theory and practice of these methods to make them useful. To this purpose, this book is an important addition to the bookshelves of academics and professionals, not only from engineering. The connection between theory and practice is weaved throughout the book, making it useful for practitioners also.” Prof. Yoram Reich, Full Professor and Head of Systems Engineering research Initiative at Tel Aviv University (Israel), Editor-in-Chief of “Research in Engineering Design”

"This handbook offers general guidance to help students do a self-assessment and select the top eight colleges that are the strongest fit for them. Establishing readers as anthropologists, students will learn to observe 20 campus cultures, assess each one, and research their options in American higher education"--

Image analysis is one of the most challenging areas in today's computer sci ence, and image technologies are used in a host of applications. This book concentrates on image textures and presents novel techniques for their sim ulation, retrieval, and segmentation using specific Gibbs random fields with multiple pairwise interaction between signals as probabilistic image models. These models and techniques were developed mainly during the previous five years (in relation to April 1999 when these words were written). While scanning these pages you may notice that, in spite of long equa tions, the mathematical background is extremely simple. I have tried to avoid complex abstract constructions and give explicit physical (to be spe cific, "image-based") explanations to all the mathematical notions involved. Therefore it is hoped that the book can be easily read both by professionals and graduate students in computer science and electrical engineering who take an interest in image analysis and synthesis. Perhaps, mathematicians studying applications of random fields may find here some less traditional, and thus controversial, views and techniques.