81. Turbulence & Complex Systems Page Atmosphere etc), Distribution networks etc. Turbulence and complex systems. Group Members. Name. Research Interests. Contact Information. http://ffden-2.phys.uaf.edu/tacs.html

Turbulence and Complex Systems Group Members Name Research Interests Contact Information David Newman Dynamics and Control of SOC Systems (Sandpiles, Power Transmission, Communications, Traffic, Plasmas) Basic Plasma and Fluid Turbulence The Interaction Between Sheared Flows and Turbulence Modeling Transitions in Plasma Transport Dynamics of Atomistic Flows in Carbon Nanotubes Development of Higher Order Characteristic Measures of Dynamical Systems Phone: (907) 474-7858 Fax: (907) 474-6130 Address University of Alaska-Fairbanks Physics Department P.O. Box 755920 Fairbanks, AK 99775-5920 USA Office Rm.: 112 Natural Science Facility E-mail: ffden@uaf.edu Renate Wackerbauer Complex temporal and spatiotemporal dynamics Modeling of biological systems neuron dynamics coupled oscillators circadian rhythms population dynamics Stochastic dynamical systems Influence of noise/perturbations on nonlinear dynamical systems Nonlinear time series analysis Phone: (907) 474-6108 Fax: (907) 474-6130 Address University of Alaska-Fairbanks Physics Department P.O. Box 755920

82. Large Scale Complex System - Home Large Scale complex system (TC 5.4). The IFAC Technical Committee on LargeScale complex systems has already a significant tradition. http://media.ici.ro/academia/ifac/ifac_tc54.htm

A Technical Committee of the Coordinating Committee on Large Scale Complex System (TC 5.4) Welcoming Message from the Chair Large-scale systems have been traditionally characterized by a large number of variables, nonlinearities and uncertainties. Their decomposition into smaller, more manageable subsystems, possibly organized in a hierarchical form, has been associated with intense and time-critical information exchange and with the need for efficient co-ordination mechanisms. The last decade of the past century and the beginning of the 21 st century have revealed new characteristic features of industrial and non-industrial large-scale systems. The enterprise of the present time are to operate in a highly networked environment and there is an ever more increased concern for integration of various technologies and for economic, environmental and social aspects. Consequently the design of control systems must take into account more aspects and needs additional skills and tools. At the same time, the recent advances in computer and communication technologies can provide effective tools and adequate technical infrastructures to support the design and implementation of control systems for the large-scale applications of the present time.

83. ENGnetBASE: Engineering Handbooks Online Framework for complex system Development, A. Paul B. Adamsen II. http://www.engnetbase.com/ejournals/books/book_summary/summary.asp?id=591

84. THE PLEXUS INSTITUTE bibliography, news, THE PLEXUS INSTITUTE, Canada http://www.plexusinstitute.org/

85. When Complex Systems Fail: New Roles For Leaders -- Margaret J. Wheatley Full-te The study of complex systems and past experience with more isolated network breakdowns suggests that complex system failures share several distinguishing http://www.pfdf.org/leaderbooks/l2l/winter99/wheatley.html

Share this Page Subscribe Contact Us Links ... Home Mission: To strengthen the leadership of the social sector Articles, Books, Resources Collaboration Self-Assessment Thought Leaders Forum ... Subscribe When Complex Systems Fail: New Roles for Leaders by Margaret J. Wheatley Leader to Leader, No. 11 Winter 1999 Thought Leaders Forum: Margaret J. Wheatley Margaret J. Wheatley Leadership and the New Science , and co-author of A Simpler Way . She speaks and consults internationally to a wide variety of organizations. Her work focuses on developing increased organizational capacity, intelligence, and humaneness through applying natural science principles of self-organization. (12/98) More on Margaret J. Wheatley From Leader to Leader, No. 11 Winter 1999 Table of Contents From the Editors Resources Additional resources for this article he Year 2000 (Y2K) problem the inability of many computer systems to process dates after 1999, and the operational breakdowns that will likely result is presenting us with some new and startling realizations. It is making visible the ways in which we have woven the world together through technology. It is showing how both local and global systems are dependent and interdependent on the smooth functioning of computers. While we cannot predict which of these systems will fail, we do know that few nations or systems will remain unaffected. The unprecedented global scope of Y2K represents a new breed of systemic problems. When complex systems fail, prevailing models of leadership offer little help. What we learn now with Y2K can prepare us for a future where more and more failures of complex systems will confront us. It can also help us look beyond the confines of in-house systems and structures, and to see new, more effective ways to lead our business and social institutions.

86. Complex Adaptive Systems Research CSCS at UMichigan The Center for the Study of complex systems NECSI The New England complex systems Institute SFI Santa Fe Institute COSI Complexity in the http://www.casresearch.com/

Complex Adaptive Systems Research Symmetry Groups by Hans Kuiper Fun Links for Complex Thinkers CSCS at UMichigan The Center for the Study of Complex Systems NECSI The New England Complex Systems Institute SFI Santa Fe Institute COSI Complexity in the Social Sciences Heinz Georg Schuster Complex Adaptive Systems COMPLEXITY AND THE UNIVERSE I Spend Hours Here! Swarm Intelligence Distributed Problem Solving Z Pinch - for thinkers Magnetized Target Fusion Experiments at LANL Visualization Gallery SPaSM Parallel Molecular Dynamics CALResCo Self-Organizing Systems Structural Biology Collection Theoretical Biophysics Group Plasma Turbulence Pictures and Movies Visualization Gallery Visualizing Social Networks Imagery in Social Network Analysis Physicomimetics Emergent Phenomena and Artificial Physics MSV Argonne National Laboratory Complex Adaptive Systems Publications Swarm Tools Julie Dugdale - GRIC-IRIT, Toulouse, France An Evaluation of Seven Software Simulation Tools for Use in the Social Sciences Repast RePast is a software framework for creating agent based simulations using the Java language Swarm Swarm is a software package for multi-agent simulation of complex systems (Java, Objective-C)

87. INTERNATIONAL CONFERENCE ON COMPLEX SYSTEMS IN E-BUSINESS (CSeB ’03) With respect to a complex interplay of IT and human factor, every business system has to be treated accordingly, ie using a systems thinking approach. http://epos.ijs.si/cseb03/

(part of I N F O R M A T I O N S O C I E T Y 2003) “Jozef Stefan” Institute, Institute for Innovation and Technology, Ljubljana, SLOVENIA, October 15, 2003 ( CLICK HERE FOR FINAL PROGRAM Electronic business has exposed the importance of multi and inter-disciplinary approaches to efficiently manage changes in modern organizations. As business is being driven significantly by information technology (IT) even on strategic level, the research in this area has to take it seriously into account. However, technology is just a necessary condition for successful business, and it has to be adequately supported by organizational measures. With respect to a complex interplay of IT and human factor, every business system has to be treated accordingly, i.e. using a systems thinking approach. This will be a common denominator of novel research done in the area of e-business related issues, which will be presented at CSeB ’03 International Conference. Topics of interest include (but are not limited to): New technologies: - grid computing

88. Complex Systems Modeling A complex system is any system featuring a large number of interacting components (agents, processes, etc.) whose aggregate activity is nonlinear (not http://www.c3.lanl.gov/~rocha/complex/csm.html

Complex Systems Modeling: Using Metaphors From Nature in Simulation and Scientific Models Based on Rocha, Luis M. [1999]. BITS: Computer and Communications News . Computing, Information, and Communications Division. Los Alamos National Laboratory. November 1999. 1. What are complex systems? "A system comprised of a (usually large) number of (usually strongly) interacting entities, processes, or agents, the understanding of which requires the development, or the use of, new scientific tools, nonlinear models, out-of equilibrium descriptions and computer simulations ." [Advances in Complex Systems Journal] "A system that can be analyzed into many components having relatively many relations among them, so that the behavior of each component depends on the behavior of others. [Herbert Simon]" "A system that involves numerous interacting agents whose aggregate behaviors are to be understood. Such aggregate activity is nonlinear, hence it cannot simply be derived from summation of individual components behavior." [Jerome Singer] A complex system is any system featuring a large number of interacting components (agents, processes, etc.) whose aggregate activity is nonlinear (not derivable from the summations of the activity of individual components) and typically exhibits hierarchical self-organization under selective pressures. This definition applies to systems from a wide array of scientific disciplines. Indeed, the sciences of complexity are necessarily based on interdisplinary research. Not surprisingly, the heart of this research area is the

89. LIFE - Discontinued Services Page complex systems resources and links http://complex.csu.edu.au/complex/library/

About This Service Australia Complexity Education ... LIFE Publications Centre This service has been discontinued. We apologise for any inconvenience. Services that have been moved are listed at the bottom of this page. Visit the Top 50 AussieSites EMail the Life Manager See below for services that have been moved to other Web Servers. If the service you are looking for is not listed below then it has definitely been discontinued! AEU APEN ESA FireNet ... IOPI

90. Complex Systems Modeling Research Focus Area By complex system we refer to any system featuring a large number of interacting components (agents, processes, etc.) whose aggregate activity is nonlinear http://www.c3.lanl.gov/~rocha/complex/complexHP.html

Description and Goals The Complex Systems Modeling Research Area is concerned with basic and applied research on simulations of complex systems and development of applications to understand and control such systems. By complex system we refer to any system featuring a large number of interacting components (agents, processes, etc.) whose aggregate activity is nonlinear (not derivable from the summations of the activity of individual components) and typically exhibits hierarchical self-organization. The research area's focus is on Network and Multi-Agent Modeling , as well as Computational Biology . Our research applies to complex systems such as social networks, gene and protein networks, knowledge networks, infrastructure networks, etc. News and Events Here we announce group events, meetings, and other relevant information periodically. Use the research area's distribution list (c3-complex@lanl.gov) to post relevant announcements. You can subscribe to this list by sending a "subscribe c3-complex" request to listmanager@lanl.gov

91. Woodward Research - Home Consultants in customised mathematical analysis, complex systems modelling, decision analysis and optimisation, decision support tool design and development, and spreadsheet services to researchers and managers. http://www.woodwardresearch.co.nz/

Mathematical and Spreadsheet Modelling Services Since 1991 we have provided customised mathematical analysis, complex systems modelling, decision analysis and optimisation, decision support tool design and development, and spreadsheet services to researchers and managers. . . . proudly New Zealand owned . . . Home Who We Are What We Do Samples ... Componic Webdesign

92. Complex Systems Notebooks complex systems. 03 Oct 1994 1200 Notebooks Hosted, but not endorsed, by the Center for the Study of complex systems. http://bactra.org/notebooks/complex-systems.html

Notebooks Complex Systems 03 Oct 1994 12:00 complexity. permanent link for this note RSS feed for this note Notebooks Hosted, but not endorsed, by the Center for the Study of Complex Systems

93. Center For Complex Systems Studies @ Kalamazoo College KCollege Home Page. last revised September 23, 2003 web@kzoo.edu Comments for CCSS specific pages. http://www.kzoo.edu/physics/ccss/

last revised: September 23, 2003 web@kzoo.edu Comments for CCSS specific pages

94. Complex Systems And Artificial Life, Dortmund Welcome to the Artificial Life and complex systems Page at the Chair of System Analysis, Department of Computer Science, University of Dortmund, Germany. http://ls11-www.cs.uni-dortmund.de/alife/

Artificial Life Chair of Systems Analysis Department of Computer Science ... Homepage W elcome to the Artificial Life and Complex Systems Page at the Chair of System Analysis, Department of Computer Science, University of Dortmund, Germany. H ere you can find an overview of our research and academic activities concerning Complex Adaptive Systems (CAS) Artificial Life (AL) and Emergent Computation as well as collection of links to related places. AL-Activities at Dortmund Overview BinSys Project Socionics Project Other Projects ... Academic Getting Started with AL Introduction The Artificial Life FAQ Books to start with ... The web-page to start with ... ... An applet as "first contact" AL-Links Artificial life in germany Resource-Lists Unmaintained collected links AL-Dates German Workshop on AL Artificial Life Treff This page has been last recently mofified by: Peter Dittrich dittrich@LS11.informatik.uni-dortmund.de duentgen@ls11.uni-dortmund.de

95. Positive Interaction Inc - Software Design A software tool designed by human factors specialists for hierarchical task analysis. Suitable for complex system design, documentation or training materials. http://positiveinteraction.com

Positive Interaction Inc. TaskArchitect Task Analysis System The TaskArchitect system is a powerful and easy to use tool for Hierarchical Task Analysis, developed in part by Positive Interaction Inc. under the code name PITAS. For more details see the Task Architect website. Consulting Services This area of the site is under construction. Please excuse the mess. Consulting Services Dick Penn's Resume ©2004, Positive Interaction Inc.

96. Complex Systems, Neutral Networks, Etc. complex systems, Neutral Evolution, etc. Mitchell, M. (1993) Computer Models of Adaptive complex systems New Scientist, February 13, 1993. http://www.cogs.susx.ac.uk/users/ezequiel/alife-page/complexity.html

Complex Systems, Neutral Evolution, etc Adami, C., (1995) Learning and Complexity in Genetic Auto-Adaptive Systems Physica D , vol. 80, p l54, 1995 Adami, C., Self-organized Criticality in Living Systems Adami, C., On Modelling Life Artificial Life IV: Fourth International Workshop on the Synthesis and Simulation of Living Systems ,p 269. Adami, C., Brown, C. T., Evolutionary Learning in the 2D Artificial Life System "Avida" Artificial Life IV: Fourth International Workshop on the Synthesis and Simulation of Living Systems ,p 377. Adami, C., Brown, C. T., Haggerty, M. R., (1995) Abundance-Distributions in Artificial Life and Stochastic Models: "Age and Area" revisited Third European Conference on Artificial Life. Ancel, L.W., Fontana, W. (1999) Plasticity, Evolvability and Modularity in RNA SFI Working Paper 99-12-077 Balbi de Oliveira, P.P., An empirical exploration of computations with a cellular-automata-based artificial life world Cognitive Science Research Paper 373 School of Cognitive and Computing Sciences, University of Sussex. Balkenius, C., (1994)

97. GMDH Method For Data Mining, Forecasting, Polynomial Neural Network Algorithms, Books. The three books in russian and the book of Madala HR, Ivakhnenko AG Inductive Learning Algorithms for complex systems Modeling. can be downloaded; http://www.gmdh.net/

Group Method of Data Handling * was applied in a great variety of areas for data mining and knowledge discovery, forecasting and systems modeling, optimization and pattern recognition. Inductive GMDH algorithms give possibility to find automatically interrelations in data, to select optimal structure of model or network and to increase the accuracy of existing algorithms. This original self-organizing approach is substantially different from deductive methods used commonly for modeling. It has inductive nature - it finds the best solution by sorting-out of possible variants. By sorting of different solutions GMDH networks aims to minimize the influence of the author on the results of modeling. Computer itself finds the structure of the model and the laws which act in the system. Group Method of Data Handling is a set of several algorithms for different problems solution. It consists of parametric, clusterization, analogues complexing, rebinarization and probability algorithms. This inductive approach is based on sorting-out of gradually complicated models and selection of the best solution by minimum of external criterion characteristic. Not only polynomials but also non-linear, probabilistic functions or clusterizations are used as basic models. GMDH approach can be useful because: The optimal complexity of model structure is found, adequate to level of noise in data sample. For real problems solution with noised or short data, simplified forecasting models are more accurate.

98. Complex System Group The summary for this Japanese page contains characters that cannot be correctly displayed in this language/character set. http://www.cmplx.cse.nagoya-u.ac.jp/

99. Robert Rosen - Complexity And Life The Modeling Relation as a complex system Rosennean Complexity Defined Rosen Modeling Relation http://www.panmere.com/rosen/

"Perhaps the first lesson to be learned from biology is that there are lessons to be learned from biology." - Robert Rosen, Essays on Life Itself "I do not accept a priori subjective conditions, imposed in advance, as constituting "scientific knowledge", or as bounding either the external world, or our capabilities of comprehending it. The history of science has always gone in precisely the other direction; the imposition of such conditions has always proved to be wrong. This is essentially what I have called complexity ; a system (mathematical or physical) is complex to the extent that it does not let itself be exhausted within a given set of (subjective) limitations." - Robert Rosen, The Limits of the Limits of Science The purpose of this site is to provide information and links regarding the work of the theoretical biologist Robert Rosen (1934-1998), who showed that biological systems exhibit complexities and physics beyond the strictures of Newtonian mechanics. In doing so, I shall attempt to represent his ideas and intentions as faithfully as possible. In cases where I wish to state my own opinion or speculation, I intend to mark the text so as to make the distinction clear. - T. Gwinn What's New About Robert Rosen Rosennean Complexity Defined Effective Processes, Computation and Complexity

100. Complex System Home WELCOME TO COMPLEXSYSTEM ENGINEERING LABORATORY. japanese. Introduction. Research Projects Laboratory Staff Where to Contact How to Access. Back to http://www.cmplx.cse.nagoya-u.ac.jp/index-e.html

WELCOME TO COMPLEX-SYSTEM ENGINEERING LABORATORY Introduction Back to ... Any Question? www-admin@cmplx.cse.nagoya-u.ac.jp

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