Biologically Inspired Approaches to Advanced Information Technology

Biologically Inspired Approaches to Advanced Information Technology PDF Author: Auke Jan Ijspeert
Publisher: Springer Science & Business Media
ISBN: 3540312536
Category : Computers
Languages : en
Pages : 401

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Book Description
The refereed proceedings of the Second International Workshop on Biologically Inspired Approaches to Advanced Information Technology, BioADIT 2006. The contributions range from basic research in biology and in information technology, to more application-oriented developments in software and in hardware. The papers are organized in topical sections on robotics, networking, biological systems, self-organization, evolutionary computation, and modeling and imaging.

Biologically Inspired Approaches to Advanced Information Technology

Biologically Inspired Approaches to Advanced Information Technology PDF Author: Auke Jan Ijspeert
Publisher: Springer Science & Business Media
ISBN: 3540312536
Category : Computers
Languages : en
Pages : 401

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Book Description
The refereed proceedings of the Second International Workshop on Biologically Inspired Approaches to Advanced Information Technology, BioADIT 2006. The contributions range from basic research in biology and in information technology, to more application-oriented developments in software and in hardware. The papers are organized in topical sections on robotics, networking, biological systems, self-organization, evolutionary computation, and modeling and imaging.

Biologically Inspired Optimization Methods

Biologically Inspired Optimization Methods PDF Author: Mattias Wahde
Publisher: WIT Press
ISBN: 1845641485
Category : Mathematics
Languages : en
Pages : 241

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Book Description
Biologically inspired optimization methods constitute a rapidly expanding field of research, with new applications appearing on an almost daily basis, as optimization problems of ever-increasing complexity appear in science and technology. This book provides a general introduction to such optimization methods, along with descriptions of the biological systems upon which the methods are based. The book also covers classical optimization methods, making it possible for the reader to determine whether a classical optimization method or a biologically inspired one is most suitable for a given problem.

Organic Computing

Organic Computing PDF Author: Rolf P. Würtz
Publisher: Springer Science & Business Media
ISBN: 3540776575
Category : Science
Languages : en
Pages : 362

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Book Description
In this book, the major ideas behind Organic Computing are delineated, together with a sparse sample of computational projects undertaken in this new field. Biological metaphors include evolution, neural networks, gene-regulatory networks, networks of brain modules, hormone system, insect swarms, and ant colonies. Applications are as diverse as system design, optimization, artificial growth, task allocation, clustering, routing, face recognition, and sign language understanding.

Biomimetic Neural Learning for Intelligent Robots

Biomimetic Neural Learning for Intelligent Robots PDF Author: Stefan Wermter
Publisher: Springer
ISBN: 3540318968
Category : Technology & Engineering
Languages : en
Pages : 390

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Book Description
This state-of-the-art survey contains selected papers contributed by researchers in intelligent systems, cognitive robotics, and neuroscience including contributions from the MirrorBot project and from the NeuroBotics Workshop 2004. The research work presented demonstrates significant novel developments in biologically inspired neural models for use in intelligent robot environments and biomimetic cognitive behavior.

Self-Organization in Sensor and Actor Networks

Self-Organization in Sensor and Actor Networks PDF Author: Falko Dressler
Publisher: John Wiley & Sons
ISBN: 9780470724453
Category : Technology & Engineering
Languages : en
Pages : 386

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Book Description
Self-Organization in Sensor and Actor Networks explores self-organization mechanisms and methodologies concerning the efficient coordination between intercommunicating autonomous systems.Self-organization is often referred to as the multitude of algorithms and methods that organise the global behaviour of a system based on inter-system communication. Studies of self-organization in natural systems first took off in the 1960s. In technology, such approaches have become a hot research topic over the last 4-5 years with emphasis upon management and control in communication networks, and especially in resource-constrained sensor and actor networks. In the area of ad hoc networks new solutions have been discovered that imitate the properties of self-organization. Some algorithms for on-demand communication and coordination, including data-centric networking, are well-known examples. Key features include: Detailed treatment of self-organization, mobile sensor and actor networks, coordination between autonomous systems, and bio-inspired networking. Overview of the basic methodologies for self-organization, a comparison to central and hierarchical control, and classification of algorithms and techniques in sensor and actor networks. Explanation of medium access control, ad hoc routing, data-centric networking, synchronization, and task allocation issues. Introduction to swarm intelligence, artificial immune system, molecular information exchange. Numerous examples and application scenarios to illustrate the theory. Self-Organization in Sensor and Actor Networks will prove essential reading for students of computer science and related fields; researchers working in the area of massively distributed systems, sensor networks, self-organization, and bio-inspired networking will also find this reference useful.

Mapping Biological Systems to Network Systems

Mapping Biological Systems to Network Systems PDF Author: Heena Rathore
Publisher: Springer
ISBN: 3319297821
Category : Technology & Engineering
Languages : en
Pages : 200

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Book Description
The book presents the challenges inherent in the paradigm shift of network systems from static to highly dynamic distributed systems – it proposes solutions that the symbiotic nature of biological systems can provide into altering networking systems to adapt to these changes. The author discuss how biological systems – which have the inherent capabilities of evolving, self-organizing, self-repairing and flourishing with time – are inspiring researchers to take opportunities from the biology domain and map them with the problems faced in network domain. The book revolves around the central idea of bio-inspired systems -- it begins by exploring why biology and computer network research are such a natural match. This is followed by presenting a broad overview of biologically inspired research in network systems -- it is classified by the biological field that inspired each topic and by the area of networking in which that topic lies. Each case elucidates how biological concepts have been most successfully applied in various domains. Nevertheless, it also presents a case study discussing the security aspects of wireless sensor networks and how biological solution stand out in comparison to optimized solutions. Furthermore, it also discusses novel biological solutions for solving problems in diverse engineering domains such as mechanical, electrical, civil, aerospace, energy and agriculture. The readers will not only get proper understanding of the bio inspired systems but also better insight for developing novel bio inspired solutions.

Fluctuation-Induced Network Control and Learning

Fluctuation-Induced Network Control and Learning PDF Author: Masayuki Murata
Publisher: Springer Nature
ISBN: 981334976X
Category : Computers
Languages : en
Pages : 239

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Book Description
From theory to application, this book presents research on biologically and brain-inspired networking and machine learning based on Yuragi, which is the Japanese term describing the noise or fluctuations that are inherently used to control the dynamics of a system. The Yuragi mechanism can be found in various biological contexts, such as in gene expression dynamics, molecular motors in muscles, or the visual recognition process in the brain. Unlike conventional network protocols that are usually designed to operate under controlled conditions with a predefined set of rules, the probabilistic behavior of Yuragi-based control permits the system to adapt to unknown situations in a distributed and self-organized manner leading to a higher scalability and robustness. The book consists of two parts. Part 1 provides in four chapters an introduction to the biological background of the Yuragi concept as well as how these are applied to networking problems. Part 2 provides additional contributions that extend the original Yuragi concept to a Bayesian attractor model from human perceptual decision making. In the six chapters of the second part, applications to various fields in information network control and artificial intelligence are presented, ranging from virtual network reconfigurations, a software-defined Internet of Things, and low-power wide-area networks. This book will benefit those working in the fields of information networks, distributed systems, and machine learning who seek new design mechanisms for controlling large-scale dynamically changing systems.

Data Mining X

Data Mining X PDF Author: A. Zanasi
Publisher: WIT Press
ISBN: 1845641841
Category : Computers
Languages : en
Pages : 209

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Book Description
Since the end of the Cold War, the threat of large-scale wars has been substituted by new threats: terrorism, organised crime, trafficking, smuggling, proliferation of weapons of mass destruction. To react to them, a security strategy is necessary, but in order to be effective it requires several instruments, including technological tools. Consequently, research and development in the field of security is proving to be an ever-expanding field all over the world. Data mining is seen more and more not only as a key technology in business, engineering and science but as one of the key features in security. To stress that all these technologies must be seen as a way to improve not only the security of citizens but also their freedom, special attention will be given to data protection research issues. The 10th International Conference on Data Mining is part of the successful series and the topics include: Text mining and text analytics; Data mining applications; Data mining methods.

Self-Organizing Systems

Self-Organizing Systems PDF Author: Hermann De Meer
Publisher: Springer
ISBN: 3540376690
Category : Computers
Languages : en
Pages : 268

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Book Description
This book constitutes the refereed proceedings of the First International Workshop on Self-Organizing Systems, IWSOS 2006. The book offers 16 revised full papers and 6 revised short papers together with 2 invited talks and 3 poster papers. The papers are organized in topical sections on dynamics of structured and unstructured overlays, self-organization in peer-to-peer networks, self-organization in wireless environments, self-organization in distributed and grid computing, self-managing and autonomic computing, and more.

Towards an Integrated Approach to Measurement, Analysis and Modeling of Cortical Networks

Towards an Integrated Approach to Measurement, Analysis and Modeling of Cortical Networks PDF Author: A. Ravishankar Rao
Publisher: Frontiers Media SA
ISBN: 288919762X
Category : Neurosciences. Biological psychiatry. Neuropsychiatry
Languages : en
Pages : 266

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Book Description
The amount of data being produced by neuroscientists is increasing rapidly, driven by advances in neuroimaging and recording techniques spanning multiple scales of resolution. The availability of such data poses significant challenges for their processing and interpretation. To gain a deeper understanding of the surrounding issues, the Editors of this e-Book reached out to an interdisciplinary community, and formed the Cortical Networks Working Group, and the genesis of this e-Book thus began with the formation of this Working Group, which was supported by the National Institute for Mathematical and Biological Synthesis in the USA. The Group consisted of scientists from neuroscience, physics, psychology and computer science, and meetings were held in person. (A detailed list of the group members is presented in the Editorial that follows.) At the time we started, in 2010, the term “big data” was hardly in existence, though the volume of data we were handling would certainly have qualified. Furthermore, there was significant interest in harnessing the power of supercomputers to perform large scale neuronal simulations, and in creating specialized hardware to mimic neural function. We realized that the various disciplines represented in our Group could and should work together to accelerate progress in Neuroscience. We searched for common threads that could define the foundation for an integrated approach to solve important problems in the field. We adopted a network-centric perspective to address these challenges, as the data are derived from structures that are themselves network-like. We proposed three inter-twined threads, consisting of measurement of neural activity, analysis of network structures deduced from this activity, and modeling of network function, leading to theoretical insights. This approach formed the foundation of our initial call for papers. When we issued the call for papers, we were not sure how many papers would fall into each of these threads. We were pleased that we found significant interest in each thread, and the number of submissions exceeded our expectations. This is an indication that the field of neuroscience is ripe for the type of integration and interchange that we had anticipated. We first published a special topics issue after we received a sufficient number of submissions. This is now being converted to an e-book to strengthen the coherence of its contributions. One of the strong themes emerging in this e-book is that network-based measures capture better the dynamics of brain processes, and provide features with greater discriminative power than point-based measures. Another theme is the importance of network oscillations and synchrony. Current research is shedding light on the principles that govern the establishment and maintenance of network oscillation states. These principles could explain why there is impaired synchronization between different brain areas in schizophrenics and Parkinson’s patients. Such research could ultimately provide the foundation for an understanding of other psychiatric and neurodegenerative conditions. The chapters in this book cover these three main threads related to cortical networks. Some authors have combined two or more threads within a single chapter. We expect the availability of related work appearing in a single e-book to help our readers see the connection between different research efforts, and spur further insights and research.