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This book includes research papers from the 11th National Technical Symposium on Unmanned System Technology. Covering a number of topics, including intelligent robotics, novel sensor technology, control algorithms, acoustics signal processing, imaging techniques, biomimetic robots, green energy sources, and underwater communication backbones and protocols, it will appeal to researchers developing marine technology solutions and policy-makers interested in technologies to facilitate the exploration of coastal and oceanic regions.
This book outlining the latest developments in engineering digital transformation gathers a selection of the best papers presented at the 11th International Conference on Industrial Engineering and Industrial Management (CIO 2017), held in Valencia, Spain, from July 5th to 6th, 2017. The papers discuss topics in the following areas: strategy and entrepreneurship, OR, modelling and simulation, production, logistics and supply chain management, information systems, quality and product management, knowledge and project management, service systems, and education.
This book comprises the proceedings of the 12th National Technical Symposium on Unmanned System Technology 2020 (NUSYS’20) held on October 27–28, 2020. It covers a number of topics, including intelligent robotics, novel sensor technology, control algorithms, acoustics signal processing, imaging techniques, biomimetic robots, green energy sources, and underwater communication backbones and protocols, and it appeals to researchers developing marine technology solutions and policy-makers interested in technologies to facilitate the exploration of coastal and oceanic regions.
This book is particularly concerned with heuristic state-space search for combinatorial optimization. Its two central themes are the average-case complexity of state-space search algorithms and the applications of the results notably to branch-and-bound techniques. Primarily written for researchers in computer science, the author presupposes a basic familiarity with complexity theory, and it is assumed that the reader is familiar with the basic concepts of random variables and recursive functions. Two successful applications are presented in depth: one is a set of state-space transformation methods which can be used to find approximate solutions quickly, and the second is forward estimation for constructing more informative evaluation functions.