Spatial Networking in the United Physical, Virtual, and Mental World (Studies in Systems, Decision and Control 533) (2025. xv, 224 S. XV, 224 p. 159 illus., 81 illus. in color. 235 mm)

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Spatial Networking in the United Physical, Virtual, and Mental World (Studies in Systems, Decision and Control 533) (2025. xv, 224 S. XV, 224 p. 159 illus., 81 illus. in color. 235 mm)

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Full Description

The current book chooses graphs and networks as primary and global research objectives after reviewing different types and areas of networking and existing works on graph and network operations. The ideas of this book originate from the WAVE approach which allowed us, more than half a century ago, to implement citywide heterogeneous computer networks and solve distributed problems on them in flexible and mobile way. The invented management paradigm evolved into Spatial Grasp Technology resulted in European patent and nine previous books oriented on concrete applications in social and defense systems, security, crises management, collective robotics, space research, and others. Many obtained results were dealing with graph and network structures and problems which were extremely important in the researched areas. It aims at development of higher-level social infrastructures effectively integrating different types of networking under the same universal approach, also application of networking in new areas like organoids and brain research. This book is oriented toward system scientists, application programmers, industry managers, university students, philosophers, psychologists, and United Nations personnel too.

Contents

Introduction.- The Use of Networks in Physical Virtual and Mental Domains.- Spatial Grasp Model and Technology Basics.- Spatial Grasp Language SGL.- Organization and Components of SGL Interpreter.- Basic Network Operations in Different Worlds under SGT.- Network Centrality Solutions in SGL.- Examples of Networking Solutions in Combined Worlds.- Active Spatial Patterns in SGL versus Traditional Algorithms.- Networks as Models of Organoid Cultures and Brain Research.- Conclusions.

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