Author
John Brandon
Bio: John Brandon is an academic researcher from University of Wales. The author has contributed to research in topics: Expert system & System under test. The author has an hindex of 6, co-authored 17 publications receiving 3636 citations.
Papers
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TL;DR: In this paper, the authors describe the rules of the ring, the ring population, and the need to get off the ring in order to measure the movement of a cyclic clock.
Abstract: 1980 Preface * 1999 Preface * 1999 Acknowledgements * Introduction * 1 Circular Logic * 2 Phase Singularities (Screwy Results of Circular Logic) * 3 The Rules of the Ring * 4 Ring Populations * 5 Getting Off the Ring * 6 Attracting Cycles and Isochrons * 7 Measuring the Trajectories of a Circadian Clock * 8 Populations of Attractor Cycle Oscillators * 9 Excitable Kinetics and Excitable Media * 10 The Varieties of Phaseless Experience: In Which the Geometrical Orderliness of Rhythmic Organization Breaks Down in Diverse Ways * 11 The Firefly Machine 12 Energy Metabolism in Cells * 13 The Malonic Acid Reagent ('Sodium Geometrate') * 14 Electrical Rhythmicity and Excitability in Cell Membranes * 15 The Aggregation of Slime Mold Amoebae * 16 Numerical Organizing Centers * 17 Electrical Singular Filaments in the Heart Wall * 18 Pattern Formation in the Fungi * 19 Circadian Rhythms in General * 20 The Circadian Clocks of Insect Eclosion * 21 The Flower of Kalanchoe * 22 The Cell Mitotic Cycle * 23 The Female Cycle * References * Index of Names * Index of Subjects
3,424 citations
TL;DR: This book introduces chaos and economics in a continuous-time model of inventory business cycles and applications to Economics, and discusses the role of software in this transformation.
Abstract: Preface Part I. Theory: 1. General introduction: chaos and economics 2. Basic mathematical concepts 3. A user's guide 4. Surfaces of sections and Poincare maps 5. Spectral analysis 6. Lyapunov characteristic exponents 7. Dimensions 8. Symbolic dynamics 9. Transition to chaos: theoretical predictive criteria 10. Analysis of experimental signals: some theoretical problems Part II. Applications to Economics: 11. Discrete and continuous chaos 12. Cycles and chaos in overlapping generations models with production 13. Chaos in a continuous-time model of inventory business cycles 14. Analysis of experimental signals Part III. Software: 15. DMC manual 16. MODEL 17. EVAL 18. PLOT 19. STAT 20. FILES 21. UTIL 22. OPTS 23. QUIT 24. Internal menu commands 25. DMC internal compiler.
152 citations
TL;DR: In this paper, the sensitivity method is applied to update finite element models of welded joints and the boundary condition of a cantilever plate, and the results show an improvement on the analytical natural frequencies.
101 citations
TL;DR: In this article, a quality criterion based on the Cauchy ratio test for convergence of infinite series is proposed to examine the liability of systems to perform poorly under extrapolation, and the quality criterion is used to evaluate the performance of systems.
Abstract: A quality criterion, based on the Cauchy ratio test for convergence of infinite series, is suggested to examine the liability of systems to perform poorly under extrapolation.
36 citations
TL;DR: The AGENTS system is described, a domain-independent general-purpose Object-Oriented Prolog language for cooperating expert systems in concurrent engineering design and emphasis is placed on demonstrating the use of the AGENTS constructs for distributed knowledge representation and the cooperation strategies for communication, collaboration, conflict resolution, and control.
Abstract: A main theme of concurrent engineering is the effective communication between relevant disciplines. Any computer tools for concurrent engineering must provide sufficient constructs and strategies for this purpose. This paper describes the AGENTS system, a domain-independent general-purpose Object-Oriented Prolog language for cooperating expert systems in concurrent engineering design. Emphasis is placed on demonstrating the use of the AGENTS constructs for distributed knowledge representation and the cooperation strategies for communication, collaboration, conflict resolution, and control. A simple case study is presented to illustrate the balance between simplicity and flexibility.
14 citations
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TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Abstract: Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.
39,297 citations
TL;DR: Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Abstract: Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
17,647 citations
TL;DR: This work aims to understand how an enormous network of interacting dynamical systems — be they neurons, power stations or lasers — will behave collectively, given their individual dynamics and coupling architecture.
Abstract: The study of networks pervades all of science, from neurobiology to statistical physics. The most basic issues are structural: how does one characterize the wiring diagram of a food web or the Internet or the metabolic network of the bacterium Escherichia coli? Are there any unifying principles underlying their topology? From the perspective of nonlinear dynamics, we would also like to understand how an enormous network of interacting dynamical systems-be they neurons, power stations or lasers-will behave collectively, given their individual dynamics and coupling architecture. Researchers are only now beginning to unravel the structure and dynamics of complex networks.
7,665 citations
TL;DR: Recent findings indicate that network oscillations bias input selection, temporally link neurons into assemblies, and facilitate synaptic plasticity, mechanisms that cooperatively support temporal representation and long-term consolidation of information.
Abstract: Clocks tick, bridges and skyscrapers vibrate, neuronal networks oscillate. Are neuronal oscillations an inevitable by-product, similar to bridge vibrations, or an essential part of the brain’s design? Mammalian cortical neurons form behavior-dependent oscillating networks of various sizes, which span five orders of magnitude in frequency. These oscillations are phylogenetically preserved, suggesting that they are functionally relevant. Recent findings indicate that network oscillations bias input selection, temporally link neurons into assemblies, and facilitate synaptic plasticity, mechanisms that cooperatively support temporal representation and long-term consolidation of information.
5,512 citations
TL;DR: This work used three transcriptional repressor systems that are not part of any natural biological clock to build an oscillating network, termed the repressilator, in Escherichia coli, which periodically induces the synthesis of green fluorescent protein as a readout of its state in individual cells.
Abstract: Networks of interacting biomolecules carry out many essential functions in living cells, but the 'design principles' underlying the functioning of such intracellular networks remain poorly understood, despite intensive efforts including quantitative analysis of relatively simple systems Here we present a complementary approach to this problem: the design and construction of a synthetic network to implement a particular function We used three transcriptional repressor systems that are not part of any natural biological clock to build an oscillating network, termed the repressilator, in Escherichia coli The network periodically induces the synthesis of green fluorescent protein as a readout of its state in individual cells The resulting oscillations, with typical periods of hours, are slower than the cell-division cycle, so the state of the oscillator has to be transmitted from generation to generation This artificial clock displays noisy behaviour, possibly because of stochastic fluctuations of its components Such 'rational network design may lead both to the engineering of new cellular behaviours and to an improved understanding of naturally occurring networks
4,488 citations