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Natural Computing 4th International Workshop on Natural Computing Himeji Japan September 2009 Proceedings 1st Edition by Ferdinand Peper, ‎Hiroshi Umeo, ‎Nobuyuki Matsui 4431538682 9784431538684

  • SKU: BELL-2169732
Natural Computing 4th International Workshop on Natural Computing Himeji Japan September 2009 Proceedings 1st Edition by Ferdinand Peper, ‎Hiroshi Umeo, ‎Nobuyuki Matsui 4431538682 9784431538684
$ 31.00 $ 45.00 (-31%)

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Natural Computing 4th International Workshop on Natural Computing Himeji Japan September 2009 Proceedings 1st Edition by Ferdinand Peper, ‎Hiroshi Umeo, ‎Nobuyuki Matsui 4431538682 9784431538684 instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 9.89 MB
Pages: 401
Author: Ferdinand Peper, Hiroshi Umeo, Nobuyuki Matsui, Teijiro Isokawa
ISBN: 4431538674
Language: English
Year: 2010

Product desciption

Natural Computing 4th International Workshop on Natural Computing Himeji Japan September 2009 Proceedings 1st Edition by Ferdinand Peper, ‎Hiroshi Umeo, ‎Nobuyuki Matsui 4431538682 9784431538684 by Ferdinand Peper, Hiroshi Umeo, Nobuyuki Matsui, Teijiro Isokawa 4431538674 instant download after payment.

Natural Computing 4th International Workshop on Natural Computing Himeji Japan September 2009 Proceedings 1st Edition by Ferdinand Peper, ‎Hiroshi Umeo, ‎Nobuyuki Matsui - Ebook PDF Instant Download/Delivery: 4431538682, 9784431538684

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Product details:

ISBN 10: 4431538682 

ISBN 13: 9784431538684

Author: Ferdinand Peper; ‎Hiroshi Umeo; ‎Nobuyuki Matsui

The complex behavior of systems in nature is rooted in intricate mechanisms of interaction that often supersede human-made systems in terms of reliability, power efficiency, and computational capacity. Researchers have begun to realize that natural systems are a great source of inspiration for novel algorithms in computation and communication systems. The International Workshop on Natural Computing (IWNC) is a platform that brings together computer scientists, biologists, mathematicians, electronic engineers, physicists, and social scientists to critically assess present findings in the field and to outline future developments in novel and emerging paradigms of computation and computing architectures. This compilation contains the papers from the most recent workshop, held in Himeji, Japan. Presented by scientists of worldwide reputation, the topics include DNA computation, cellular automata, physics and computation, evolutionary computing, neural networks, amoeba-based computing, artificial chemistry, noise-driven computing, chaotic systems, and unconventional models of communication.

Table of contents:

  1. Universality and Computability
  2. Molecular Cellular Automaton Rules
  3. Dirichlet Tessellation (DT) or Voronoi Decomposition
  4. Directed Propagation of Information
  5. Information Writing, Storage and Retrieval
  6. Logic Gate
  7. Coalescence and Giant Explosion
  8. Density Classification Task (DCT)
  9. Multi-agent Robotics
  10. Phase Ordering
  11. Ant Colony
  12. Chemotaxis
  13. References
  14. Noise-Based Logic and Computing: From Boolean Logic Gates to Brain Circuitry and Its Possible Hardwa
  15. Models and Mechanisms for Artificial Morphogenesis
  16. Background
  17. Embodied Computation
  18. Artificial Morphogenesis
  19. Requirements for a Formalism
  20. Approach
  21. Example
  22. References
  23. Biologically–Inspired Network Architecture for Future Networks
  24. Introduction
  25. Why Bio-inspired Approaches?
  26. Attractor Selection Principle and Its Application to Networking Problems
  27. Concluding Remarks
  28. References
  29. Foraging Behaviors and Potential Computational Ability of Problem-Solving in an Amoeba
  30. Introduction
  31. Foraging Behaviors in the Case of Spatially Distributed FSs
  32. Accumulation of Mass of Organism to FS in Relation to Amount of Nutrient at FS
  33. Time Course of Two Connections between Two FSs in Relation to Food Amount at FS
  34. Order of Tube Collapse in Five Connections with Different Length between Two FSs
  35. Maze-Solving
  36. Risk-Minimum Path in the Inhomogeneous Field of Risk
  37. Networking of Three and More FSs
  38. Not Only the Final Answer But Also Transient
  39. Mathematical Modeling for the Foraging Behaviors to Connect the Spatially Distributed FSs through a
  40. Mathematical Formulation of Network Dynamics Adaptable to Streaming
  41. Physarum Solver: A Biologically Inspired Method for Path-Finding
  42. Risk-Minimum Path in an Inhomogeneous Field
  43. Effect of Food Amount on Tube Selection between Two FSs
  44. Concluding Remarks: Possibility of Physarum Computing
  45. References
  46. Two Molecular Information Processing Systems Based on Catalytic Nucleic Acids
  47. Introduction
  48. Systems Based on Deoxyribozyme-Based Logic Gates
  49. Spider-Based System
  50. Conclusions
  51. References
  52. Invited Papers
  53. The Effect of Community on Distributed Bio-inspired Service Composition
  54. Introduction
  55. Bio-inspired Service Management
  56. Distributed Service Composition
  57. Community
  58. Community Structure and Formation
  59. Simulation and Results
  60. Conclusion
  61. References
  62. Efficient Computation in Brownian Cellular Automata
  63. Introduction
  64. A Brownian Cellular Automaton Model
  65. Embedding Delay-Insensitive Circuits into Brownian Cellular Automaton
  66. Implementing Ratchets with Various Configurations
  67. Conclusions
  68. References
  69. A Molecular Communication System
  70. Introduction
  71. Overview of a Molecular Communication System
  72. System Design and Initial Experimental Results
  73. Molecular Communication Interface
  74. Molecular Propagation System
  75. Sender and Receiver
  76. Conclusions
  77. References
  78. Properties of Threshold Coupled Chaotic Neuronal Maps
  79. Introduction
  80. The Model System: Neuronal Maps
  81. Relaxation Time
  82. Nonlocal Coupling
  83. Asynchronous Updating
  84. Dynamic Logic Cell
  85. Conclusion
  86. References
  87. Contributed Papers
  88. Implementation of Rotary Element with Quantum Cellular Automata
  89. Introduction
  90. RotaryElement
  91. Quantum Cellular Automata
  92. Implementation of Rotary Element
  93. Delay Element and C-JOIN
  94. Concluding Remarks
  95. References
  96. Universal 2-State Asynchronous Cellular Automaton with Inner-Independent Transitions
  97. Introduction
  98. On Delay Insensitive Circuits
  99. Implementing DI-Circuits on Asynchronous CA
  100. Conclusions and Discussion
  101. References
  102. Effect of Population Size in Extended Parameter-Free Genetic Algorithm
  103. Introduction
  104. Parameter-Free Genetic Algorithm
  105. Mutation Rate Coding
  106. Extended Selection Rule
  107. Experiments
  108. Conclusion and Discussion
  109. References
  110. Temperature Effects on Olive Fruit Fly Infestation in the FlySim Cellular Automata Model
  111. Introduction
  112. Description of the Model
  113. Elementary Processes and Transition Function
  114. Temperature
  115. Growth and Death Rate of Olive Fruit Flies
  116. Diffusion of Adult Olive Fruit Flies
  117. Results
  118. Conclusions
  119. References
  120. Computing by Observing Changes
  121. Computing by Observing
  122. Preliminaries
  123. Computing by Observing Changes
  124. The Power of Change-Observing Acceptors
  125. Conclusion
  126. References
  127. Robustness of the Critical Behaviour in a Discrete Stochastic Reaction-Diffusion Medium
  128. Introduction
  129. Model and Methods
  130. The Model
  131. Effect of Noise
  132. Robustness Studies
  133. Robustness to Variations of the Excitation Level
  134. Holes and Missing Links
  135. Changing the Topology
  136. The Inverse Proportionality Law
  137. Conclusion
  138. References
  139. Quantifying the Severity of the Permutation Problem in Neuroevolution
  140. Introduction
  141. The Permutation Problem
  142. Calculating the Probability of Genotypic Permutations
  143. Calculating the Probability of Phenotypic Permutations
  144. Discussion
  145. Conclusions and Future Work
  146. References
  147. Extending the Geometrical Design of DNA Nanostructures
  148. Introduction
  149. Interconnected Single-Duplex Junction (T-Junction)
  150. Structural Description
  151. Abstraction
  152. Designing Shapes and Patterns
  153. Experiments
  154. Conclusion
  155. References
  156. An Optical Solution for the Subset Sum Problem
  157. Introduction
  158. The Device
  159. The Modified Device
  160. Finding the Solution Subset
  161. Conclusion and Future Work
  162. References
  163. Design of True Random One-Time Pads in DNA XOR Cryptosystem
  164. Introduction
  165. DNA XOR One-Time-Pad Cryptosystem with Random Hybridization
  166. Message Encryption
  167. Random Tiling Operation
  168. Extraction of Cipher Strings and Key Strings
  169. Analysis on Error Tolerance
  170. Conclusion
  171. References
  172. On Designing Gliders in Three-Dimensional Larger than Life Cellular Automata
  173. Introduction
  174. Larger than Life Cellular Automata
  175. Bugs in Three-Dimensional Larger than Life
  176. Period 1 Bugs
  177. Bugs with Longer Period
  178. Experimental Results of Collisions of Bugs
  179. Conclusion
  180. References
  181. Instability of Collective Flow in Two-Dimensional Optimal Velocity Model
  182. Introduction
  183. Two-DimensionalOVModel
  184. Linear Analysis
  185. Longitudinal Mode along the x-Axis
  186. Transverse Mode along the x-Axis
  187. Transverse Mode along the y-Axis
  188. Longitudinal Mode along the y-Axis
  189. Elliptically Polarized Mode
  190. Phase Diagrams
  191. Summary
  192. References
  193. A New Differential Evolution for Multiobjective Optimization by Uniform Design and Minimum Reduce Hy
  194. Introduction
  195. UniformDesign
  196. Minimum Reduce Hypervolume
  197. Differential Evolution for MOPs by Uniform Design and Minimum Reduce Hypervolume
  198. Experiment Results
  199. Conclusion and Further Research
  200. References
  201. Noise Effects on Chaos in Chaotic Neuron Model
  202. Introduction
  203. Chaotic Neuron Model
  204. Noise-Induced Order in Chaotic Neuron Model
  205. Summary
  206. References
  207. Application of Improved Grammatical Evolution to Santa Fe Trail Problems
  208. Introduction
  209. Original Grammatical Evolution
  210. Function Identification Problem
  211. Problem Settings
  212. Syntax and Parameters
  213. Result
  214. Improved Schemes of Grammatical Evolution
  215. Difficulties of Original GE
  216. Improvement of GE
  217. Santa Fe Trail Problem
  218. Problem Setting
  219. Syntax and Parameters
  220. Result
  221. Conclusion
  222. References
  223. Limit Theorem for a Time-Dependent Coined Quantum Walk on the Line
  224. Introduction
  225. Time-Dependent QW
  226. Two-PeriodQW
  227. Special Cases in Time-Dependent QWs
  228. Case 1
  229. Case 2
  230. Conclusion and Discussion
  231. References
  232. Top-Predator Survivor Region Is Affected by Bottom-Prey Mortality Rate on the Monte-Carlo Simulation
  233. Introduction
  234. Model and Method
  235. Model
  236. Simulation Method
  237. Mean-Field Theory
  238. Simulation Results
  239. Steady-State Density
  240. Results of Simulation Experiment
  241. Discussions and Conclusion
  242. References
  243. Simulation and Theoretical Comparison between “Zipper” and “Non-Zipper” Merging
  244. Introduction
  245. Modeling
  246. Simulations and Theoretical Calculation
  247. Conclusive Discussion
  248. References
  249. Universality of 2-State 3-Symbol Reversible Logic Elements — A Direct Simulation Method of a Rotar
  250. Introduction
  251. Preliminaries
  252. Direct Simulation of an RE by 3-Symbol RLEMs
  253. Concluding Remarks
  254. References
  255. Pump Current as a Signal Transformation
  256. Introduction: Pump Current
  257. Stochastic Model
  258. Simple Model for the Pumping Phenomenon
  259. Counting Statistics
  260. Mathematical Structure Behind the Pumping Phenomenon
  261. Interpretation as a Shr¨odinger-Like Equation
  262. Geometrical Phase Interpretation
  263. Discussion: Pump Current as a Signal Transformation
  264. Concluding Remarks
  265. References
  266. Evaluation of Generation Alternation Models in Evolutionary Robotics
  267. Introduction
  268. Generation Alternation Models
  269. Evaluation of Generation Alternation Models by Experiment
  270. Experimental Settings
  271. Experimental Results
  272. Discussion
  273. Conclusions
  274. References
  275. Photonic Switching of DNA’s Position That Represents the Internal State in Photonic DNA Automaton
  276. Introduction
  277. Photonic DNA Automaton
  278. A Method for Controlling Position of DNA
  279. Experiments
  280. Conclusions
  281. References
  282. Fluctuation Induced Structure in Chemical Reaction with Small Number of Molecules
  283. Parallel Retrieval of Nanometer-Scale Light-Matter Interactions for Nanophotonic Systems
  284. Introduction
  285. Nanometric Optical Processing Based on Nanophotonics
  286. Nanophotonic Matching Utilizing Macro-scale Observation of Optical Near-Field Interactions
  287. Transcription Based on Photoinduced Phase Transition
  288. Conclusions
  289. References
  290. A Compressible Fluid Model for Traffic Flow and Nonlinear Saturation of Perturbation Growth
  291. Introduction
  292. New Compressible Fluid Model Based on Experimental Data
  293. Linear Stability Analysis
  294. Reductive Perturbation Analysis
  295. Conclusion
  296. References
  297. Functional Sized Population Magnetic Optimization Algorithm
  298. Introduction
  299. Functional Sized Population MOA (FSMOA)
  300. Finding the Best Parameters
  301. Experimental Results
  302. Conclusion
  303. References
  304. Emergence and Collapse of Order in Ad Hoc Cellular Automata
  305. Introduction
  306. Ad Hoc Cellular Automata with Intra-agent Dynamics
  307. Results
  308. Emergence and Collapse of Complex/Periodic Patterns
  309. Emergence and Collapse of Clusters in Rule-Entry Space
  310. Classifying ACA
  311. Power Law in Stationary State Distribution
  312. Discussion and Conclusion
  313. References
  314. A Transition Rule Set for the First 2-D Optimum-Time Synchronization Algorithm
  315. Introduction
  316. Firing Squad Synchronization Problem
  317. FSSP on Two-Dimensional Cellular Arrays
  318. Overview of Shinahr’s Time-Optimum Algorithm
  319. Constructionof Real-Coded Transition Rule Set for ABS
  320. Discussions
  321. References
  322. A Two-Dimensional Optimum-Time Firing Squad Synchronization Algorithm and Its Implementation
  323. Introduction
  324. Firing Squad Synchronization Problem on Two-Dimensional Arrays
  325. Delayed Synchronization Scheme for One-Dimensional Arrays
  326. New Optimum-Time Synchronization Algorithm
  327. Segmentation of Rectangular Array of Size m× n
  328. Starting Synchronization Process
  329. Synchronization of Lm
  330. Synchronization of Li
  331. Synchronization of Rectangle Longer Than Wide
  332. Conclusions
  333. References
  334. Quaternion Based Thermal Condition Monitoring System
  335. Introduction
  336. Machine Condition Monitoring System Model
  337. Log-Polar Mapping
  338. Quaternion Based Thermal Image Correlator
  339. Max-Product Fuzzy Neural Network Classifier
  340. Experimental Results
  341. Conclusion
  342. References
  343. Firing Correlation in Spiking Neurons with Watts–Strogatz Rewiring
  344. Introduction
  345. Izhikevich’s Neuron Model and Network Structure
  346. Izhikevich’s Spiking Neuron Model
  347. Network Structure and Neuron Ensembles
  348. Simulation Experiment with a WS Network Structure
  349. Summary
  350. References
  351. Methods for Shortening Waiting Time in Walking-Distance Introduced Queueing Systems
  352. Introduction
  353. Walking-Distance Introduced Queueing Theory
  354. Distance Introduced Fork-Type Queueing System: D-Fork
  355. Update Rules
  356. Stationary Equations
  357. Methods for Shortening Mean Waiting Time in D-Fork
  358. Set the Head of the Queue at the Center: D-Fork-Center
  359. Keep One Person Waiting at the Window: D-Fork-Wait
  360. Theoretical Analysis and Simulation
  361. Experiments
  362. Conclusion
  363. References
  364. Effect of Mutation to Distribution of Optimum Solution in Genetic Algorithm
  365. Introduction
  366. Mathematical Model
  367. Representations
  368. Linkage Equilibrium
  369. Stochastic Models
  370. Wright-FisherModel
  371. With Mutation
  372. Calculation of Success Probability
  373. Results
  374. Summary and Discussion

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