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Self Engineering: Learning From Failures (SpringerBriefs in Applied Sciences and Technology)

This book demonstrates how the creation of emotional satisfaction will change in tomorrow’s connected, IoT world. The importance of emotional satisfaction will increase in the IoT Connected Society of World 2.0, in which humans and machines work together as members of the same team with no walls between the two, and where production is also team-based. Developing emotional satisfaction in such a diverse team and in a very different environment is a major challenge and needs to be studied from a broad perspective. This book describes the emerging issues and how they can be to tackled, introducing paths for moving beyond static value toward developing dynamic value.

Self-Healing Systems and Wireless Networks Management

Do you believe in open-source development? Would you like to see your security system grow and learn by itself? Are you sick of paying for software license fees every year that produce little return on investment? And, would you prefer to invest in something you could sell later on to other IT security departments? If you answered yes to these ques

Self-Improving Teaching Systems: An Application of Artificial Intelligence to Computer Assisted Instruction (Interdisciplinary Systems Research)

Self-Learning and Adaptive Algorithms for Business Applications: A Guide to Adaptive Neuro-Fuzzy Systems for Fuzzy Clustering Under Uncertainty Conditions (Emerald Points)

In today’s data-driven world, more sophisticated algorithms for data processing are in high demand, mainly when the data cannot be handled with the help of traditional techniques. Self-learning and adaptive algorithms are now widely used by such leading giants that as Google, Tesla, Microsoft, and Facebook in their projects and applications. In this guide designed for researchers and students of computer science, readers will find a resource for how to apply methods that work on real-life problems to their challenging applications, and a go-to work that makes fuzzy clustering issues and aspects clear. Including research relevant to those studying cybernetics, applied mathematics, statistics, engineering, and bioinformatics who are working in the areas of machine learning, artificial intelligence, complex system modeling and analysis, neural networks, and optimization, this is an ideal read for anyone interested in learning more about the fascinating new developments in machine learning.

Self-Learning and Adaptive Algorithms for Business Applications: A Guide to Adaptive Neuro-Fuzzy Systems for Fuzzy Clustering Under Uncertainty Conditions (Emerald Points)

In today’s data-driven world, more sophisticated algorithms for data processing are in high demand, mainly when the data cannot be handled with the help of traditional techniques. Self-learning and adaptive algorithms are now widely used by such leading giants that as Google, Tesla, Microsoft, and Facebook in their projects and applications. In this guide designed for researchers and students of computer science, readers will find a resource for how to apply methods that work on real-life problems to their challenging applications, and a go-to work that makes fuzzy clustering issues and aspects clear. Including research relevant to those studying cybernetics, applied mathematics, statistics, engineering, and bioinformatics who are working in the areas of machine learning, artificial intelligence, complex system modeling and analysis, neural networks, and optimization, this is an ideal read for anyone interested in learning more about the fascinating new developments in machine learning.

Self-Learning Optimal Control of Nonlinear Systems: Adaptive Dynamic Programming Approach (Studies in Systems, Decision and Control #103)

This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum.With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering.

Self-Learning Speaker Identification: A System for Enhanced Speech Recognition (Signals and Communication Technology)

Current speech recognition systems are based on speaker independent speech models and suffer from inter-speaker variations in speech signal characteristics. This work develops an integrated approach for speech and speaker recognition in order to gain space for self-learning opportunities of the system. This work introduces a reliable speaker identification which enables the speech recognizer to create robust speaker dependent models In addition, this book gives a new approach to solve the reverse problem, how to improve speech recognition if speakers can be recognized. The speaker identification enables the speaker adaptation to adapt to different speakers which results in an optimal long-term adaptation.

The Self-Made Program Leader: Taking Charge in Matrix Organizations (Best Practices in Portfolio, Program, and Project Management)

Almost all leadership books assume that the leader has authority over their team members. The challenge of project management in a matrix-structured environment is that this is not always the case. A whole new plan of attack has to be executed for the project manager to deliver in an organization where they do not have formal authority. This book t

The Self-Made Program Leader: Taking Charge in Matrix Organizations (Best Practices in Portfolio, Program, and Project Management)

Almost all leadership books assume that the leader has authority over their team members. The challenge of project management in a matrix-structured environment is that this is not always the case. A whole new plan of attack has to be executed for the project manager to deliver in an organization where they do not have formal authority. This book t

Self-Managed Networks, Systems, and Services: Second IEEE International Workshops, SelfMan 2006, Dublin, Ireland, June 16, 2006, Proceedings (Lecture Notes in Computer Science #3996)

This book constitutes the refereed proceedings of the Second IEEE International Workshop on Self-Managed Networks, Systems, and Services, SelfMan 2006, held in Dublin, Ireland in June 2006. The 12 revised full papers presented together with 3 work-in-progress papers were carefully reviewed and selected from 51 submissions. The papers are organized in topical sections on middleware and infrastructure for self-management, peer-to-peer and overlay networks, self-adaptation, self-managed mobile systems, and networking.

Self-Managing Distributed Systems: 14th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management, DSOM 2003, Heidelberg, Germany, October 20-22, 2003, Proceedings (Lecture Notes in Computer Science #2867)

This book constitutes the refereed proceedings of the 14th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management, DSOM 2003, held in Heidelberg, Germany in October 2002. The 20 revised full papers and 6 revised short papers presented together with a keynote paper were carefully reviewed and selected from a total of 105 submissions. The papers are organized in topical sections on self-configuration, peer-to-peer management, self-optimization and performance management, utility management, self-protection and access control, manageability and instrumentation, and context-awareness.

Self-Modifying Systems in Biology and Cognitive Science: A New Framework for Dynamics, Information and Complexity (IFSR International Series on Systems Science and Engineering #Volume 6)

The theme of this book is the self-generation of information by the self-modification of systems. The author explains why biological and cognitive processes exhibit identity changes in the mathematical and logical sense. This concept is the basis of a new organizational principle which utilizes shifts of the internal semantic relations in systems. There are mathematical discussions of various classes of systems (Turing machines, input-output systems, synergetic systems, non-linear dynamics etc), which are contrasted with the author's new principle. The most important implications of this include a new conception on the nature of information and which also provides a new and coherent conceptual view of a wide class of natural systems. This book merits the attention of all philosophers and scientists concerned with the way we create reality in our mathematical representations of the world and the connection those representations have with the way things really are.

Self-Organising Neural Networks: Independent Component Analysis and Blind Source Separation (Perspectives in Neural Computing)

The conception of fresh ideas and the development of new techniques for Blind Source Separation and Independent Component Analysis have been rapid in recent years. It is also encouraging, from the perspective of the many scientists involved in this fascinating area of research, to witness the growing list of successful applications of these methods to a diverse range of practical everyday problems. This growth has been due, in part, to the number of promising young and enthusiastic researchers who have committed their efforts to expanding the current body of knowledge within this field of research. The author of this book is among one of their number. I trust that the present book by Dr. Mark Girolami will provide a rapid and effective means of communicating some of these new ideas to a wide international audience and that in turn this will expand further the growth of knowledge. In my opinion this book makes an important contribution to the theory of Independent Component Analysis and Blind Source Separation. This opens a range of exciting methods, techniques and algorithms for applied researchers and practitioner engineers, especially from the perspective of artificial neural networks and information theory. It has been interesting to see how rapidly the scientific literature in this area has grown.

Self-organising Software: From Natural to Artificial Adaptation (Natural Computing Series)

Self-organisation, self-regulation, self-repair and self-maintenance are promising conceptual approaches for dealing with complex distributed interactive software and information-handling systems. Self-organising applications dynamically change their functionality and structure without direct user intervention, responding to changes in requirements and the environment. This is the first book to offer an integrated view of self-organisation technologies applied to distributed systems, particularly focusing on multiagent systems. The editors developed this integrated book with three aims: to explain self-organisation concepts and principles, using clear definitions and a strong theoretical background; to examine how self-organising behaviour can be modelled, analysed and systematically engineered into agent behaviour; and to assess the types of problems that can be solved using self-organising multiagent systems. The book comprises chapters covering all three dimensions, synthesising up-to-date research work and the latest technologies and applications. The book offers dedicated chapters on concepts such as self-organisation, emergence in natural systems, software agents, stigmergy, gossip, cooperation and immune systems. The book then explains how to engineer artificial self-organising software, in particular it examines methodologies and middleware infrastructures. Finally, the book presents diverse applications of self-organising software, such as constraint satisfaction, trust management, image recognition and networking.The book will be of interest to researchers working on emergent phenomena and adaptive systems. It will also be suitable for use as a graduate textbook, with chapter summaries and exercises, and an accompanying website that includes teaching slides, exercise solutions and research project outlines.Self-organisation, self-regulation, self-repair and self-maintenance are promising conceptual approaches for dealing with complex distributed interactive software and information-handling systems. Self-organising applications dynamically change their functionality and structure without direct user intervention, responding to changes in requirements and the environment. This is the first book to offer an integrated view of self-organisation technologies applied to distributed systems, particularly focusing on multiagent systems. The editors developed this integrated book with three aims: to explain self-organisation concepts and principles, using clear definitions and a strong theoretical background; to examine how self-organising behaviour can be modelled, analysed and systematically engineered into agent behaviour; and to assess the types of problems that can be solved using self-organising multiagent systems. The book comprises chapters covering all three dimensions, synthesising up-to-date research work and the latest technologies and applications. The book offers dedicated chapters on concepts such as self-organisation, emergence in natural systems, software agents, stigmergy, gossip, cooperation and immune systems. The book then explains how to engineer artificial self-organising software, in particular it examines methodologies and middleware infrastructures. Finally, the book presents diverse applications of self-organising software, such as constraint satisfaction, trust management, image recognition and networking.The book will be of interest to researchers working on emergent phenomena and adaptive systems. It will also be suitable for use as a graduate textbook, with chapter summaries and exercises, and an accompanying website that includes teaching slides, exercise solutions and research project outlines.

Self-Organization and Associative Memory (Springer Series in Information Sciences #8)

While the present edition is bibliographically the third one of Vol. 8 of the Springer Series in Information Sciences (IS 8), the book actually stems from Vol. 17 of the series Communication and Cybernetics (CC 17), entitled Associative Memory - A System-Theoretical Approach, which appeared in 1977. That book was the first monograph on distributed associative memories, or "content-addressable memories" as they are frequently called, especially in neural-networks research. This author, however, would like to reserve the term "content-addressable memory" for certain more traditional constructs, the memory locations of which are selected by parallel search. Such devices are discussed in Vol. 1 of the Springer Series in Information Sciences, Content-Addressable Memories. This third edition of IS 8 is rather similar to the second one. Two new discussions have been added: one to the end of Chap. 5, and the other (the L VQ 2 algorithm) to the end of Chap. 7. Moreover, the convergence proof in Sect. 5.7.2 has been revised.

Self-Organization, Computational Maps, and Motor Control (ISSN #Volume 119)

In the study of the computational structure of biological/robotic sensorimotor systems, distributed models have gained center stage in recent years, with a range of issues including self-organization, non-linear dynamics, field computing etc. This multidisciplinary research area is addressed here by a multidisciplinary team of contributors, who provide a balanced set of articulated presentations which include reviews, computational models, simulation studies, psychophysical, and neurophysiological experiments.The book is divided into three parts, each characterized by a slightly different focus: in part I, the major theme concerns computational maps which typically model cortical areas, according to a view of the sensorimotor cortex as "geometric engine" and the site of "internal models" of external spaces. Part II also addresses problems of self-organization and field computing, but in a simpler computational architecture which, although lacking a specialized cortical machinery, can still behave in a very adaptive and surprising way by exploiting the interaction with the real world. Finally part III is focused on the motor control issues related to the physical properties of muscular actuators and the dynamic interactions with the world.The reader will find different approaches on controversial issues, such as the role and nature of force fields, the need for internal representations, the nature of invariant commands, the vexing question about coordinate transformations, the distinction between hierachiacal and bi-directional modelling, and the influence of muscle stiffness.

Self-Organization in Continuous Adaptive Networks

In the last years, adaptive networks have been discovered simultaneously in different fields as a universal framework for the study of self-organization phenomena. Understanding the mechanisms behind these phenomena is hoped to bring forward not only empirical disciplines such as biology, sociology, ecology, and economy, but also engineering disciplines seeking to employ controlled emergence in future technologies. This volume presents new analytical approaches, which combine tools from dynamical systems theory and statistical physics with tools from graph theory to address the principles behind adaptive self-organization. It is the first class of approaches that is applicable to continuous networks. The volume discusses the mechanisms behind three emergent phenomena that are prominently discussed in the context of biological and social sciences:• synchronization,• spontaneous diversification, and• self-organized criticality.Self-organization in continuous adaptive networks contains extended research papers. It can serve as both, a review of recent results on adaptive self-organization as well as a tutorial of new analytical methodsSelf-organization in continuous adaptive networks is ideal for academic staff and master/research students in complexity and network sciences, in engineering, physics and maths.

Self-Organization in Continuous Adaptive Networks

In the last years, adaptive networks have been discovered simultaneously in different fields as a universal framework for the study of self-organization phenomena. Understanding the mechanisms behind these phenomena is hoped to bring forward not only empirical disciplines such as biology, sociology, ecology, and economy, but also engineering disciplines seeking to employ controlled emergence in future technologies. This volume presents new analytical approaches, which combine tools from dynamical systems theory and statistical physics with tools from graph theory to address the principles behind adaptive self-organization. It is the first class of approaches that is applicable to continuous networks. The volume discusses the mechanisms behind three emergent phenomena that are prominently discussed in the context of biological and social sciences:• synchronization,• spontaneous diversification, and• self-organized criticality.Self-organization in continuous adaptive networks contains extended research papers. It can serve as both, a review of recent results on adaptive self-organization as well as a tutorial of new analytical methodsSelf-organization in continuous adaptive networks is ideal for academic staff and master/research students in complexity and network sciences, in engineering, physics and maths.

Self-Organization in Embedded Real-Time Systems

This book describes the emerging field of self-organizing, multicore, distributed and real-time embedded systems. Self‐organization of both hardware and software can be a key technique to handle the growing complexity of modern computing systems. Distributed systems running hundreds of tasks on dozens of processors, each equipped with multiple cores, requires self‐organization principles to ensure efficient and reliable operation. This book addresses various, so-called Self‐X features such as self-configuration, self‐optimization, self‐adaptation, self‐healing and self‐protection.

Self-Organized Lightwave Networks: Self-Aligned Coupling Optical Waveguides

This book gives a solution to the problem of constructing lightwave paths in free spaces by proposing the concept of a Self-Organized Lightwave Network (SOLNET). This concept enables us to form self-aligned coupling optical waveguides automatically. SOLNETs are fabricated by self-focusing of lightwaves in photosensitive media, in which the refractive index increases upon light beam exposure, to realize the following functions: 1) Optical solder: Self-aligned optical couplings between misaligned devices with different core sizes 2) Three-dimensional optical wiring 3) Targeting lightwaves onto specific objects SOLNETs are expected to reduce the efforts to implement lightwaves into electronic systems and allow us to create new architectures, thus reducing costs and energy dissipation and improving overall system performance. SOLNETs are also expected to be applied to a wide range of fields where lightwaves are utilized, for example, solar energy conversion systems and biomedical technologies, especially photo-assisted cancer therapies. Readers will systematically learn concepts and features of SOLNETs, SOLNET performance predicted by computer simulations, experimental demonstrations for the proof of concepts, and expected applications. They will also be prepared for future challenges of the applications. This book is intended to be read by scientists, engineers, and graduate students who study advanced optoelectronic systems such as optical interconnects within computers and optical networking systems, and those who produce new ideas or strategies on lightwave-related subjects.

Self-Organized Lightwave Networks: Self-Aligned Coupling Optical Waveguides

This book gives a solution to the problem of constructing lightwave paths in free spaces by proposing the concept of a Self-Organized Lightwave Network (SOLNET). This concept enables us to form self-aligned coupling optical waveguides automatically. SOLNETs are fabricated by self-focusing of lightwaves in photosensitive media, in which the refractive index increases upon light beam exposure, to realize the following functions: 1) Optical solder: Self-aligned optical couplings between misaligned devices with different core sizes 2) Three-dimensional optical wiring 3) Targeting lightwaves onto specific objects SOLNETs are expected to reduce the efforts to implement lightwaves into electronic systems and allow us to create new architectures, thus reducing costs and energy dissipation and improving overall system performance. SOLNETs are also expected to be applied to a wide range of fields where lightwaves are utilized, for example, solar energy conversion systems and biomedical technologies, especially photo-assisted cancer therapies. Readers will systematically learn concepts and features of SOLNETs, SOLNET performance predicted by computer simulations, experimental demonstrations for the proof of concepts, and expected applications. They will also be prepared for future challenges of the applications. This book is intended to be read by scientists, engineers, and graduate students who study advanced optoelectronic systems such as optical interconnects within computers and optical networking systems, and those who produce new ideas or strategies on lightwave-related subjects.

Self-Organized Quantum Dots for Memories: Electronic Properties and Carrier Dynamics (Springer Theses)

Today’s semiconductor memory market is divided between two types of memory: DRAM and Flash. Each has its own advantages and disadvantages. While DRAM is fast but volatile, Flash is non-volatile but slow. A memory system based on self-organized quantum dots (QDs) as storage node could combine the advantages of modern DRAM and Flash, thus merging the latter’s non-volatility with very fast write times.This thesis investigates the electronic properties of and carrier dynamics in self-organized quantum dots by means of time-resolved capacitance spectroscopy and time-resolved current measurements. The first aim is to study the localization energy of various QD systems in order to assess the potential of increasing the storage time in QDs to non-volatility. Surprisingly, it is found that the major impact of carrier capture cross-sections of QDs is to influence, and at times counterbalance, carrier storage in addition to the localization energy. The second aim is to study the coupling between a layer of self-organized QDs and a two-dimensional hole gas (2DHG), which is relevant for the read-out process in memory systems. The investigation yields the discovery of the many-particle ground states in the QD ensemble. In addition to its technological relevance, the thesis also offers new insights into the fascinating field of nanostructure physics.

Self-Organizing Architectures: First International Workshop, SOAR 2009, Cambridge, UK, September 14, 2009, Revised Selected and Invited Papers (Lecture Notes in Computer Science #6090)

Self-organizing Coalitions for Managing Complexity: Agent-based Simulation of Evolutionary Game Theory Models using Dynamic Social Networks for Interdisciplinary Applications (Emergence, Complexity and Computation #29)

This book provides an interdisciplinary approach to complexity, combining ideas from areas like complex networks, cellular automata, multi-agent systems, self-organization and game theory. The first part of the book provides an extensive introduction to these areas, while the second explores a range of research scenarios. Lastly, the book presents CellNet, a software framework that offers a hands-on approach to the scenarios described throughout the book. In light of the introductory chapters, the research chapters, and the CellNet simulating framework, this book can be used to teach undergraduate and master’s students in disciplines like artificial intelligence, computer science, applied mathematics, economics and engineering. Moreover, the book will be particularly interesting for Ph.D. and postdoctoral researchers seeking a general perspective on how to design and create their own models.

Self-Organizing Maps (Springer Series in Information Sciences #30)

The second, revised edition of this book was suggested by the impressive sales of the first edition. Fortunately this enabled us to incorporate new important results that had just been obtained. The ASSOM (Adaptive-Subspace SOM) is a new architecture in which invariant-feature detectors emerge in an unsupervised learning process. Its basic principle was already introduced in the first edition, but the motiva­ tion and theoretical discussion in the second edition is more thorough and consequent. New material has been added to Sect. 5.9 and this section has been rewritten totally. Correspondingly, Sect. 1.4, which deals with adaptive­ subspace classifiers in general and constitutes the prerequisite for the ASSOM principle, has also been extended and rewritten totally. Another new SOM development is the WEBSOM, a two-layer architecture intended for the organization of very large collections of full-text documents such as those found in the Internet and World Wide Web. This architecture was published after the first edition came out. The idea and results seemed to be so important that the new Sect. 7.8 has now been added to the second edition. Another addition that contains new results is Sect. 3.15, which describes the acceleration in the computing of very large SOMs. It was also felt that Chap. 7, which deals with 80M applications, had to be extended.