Spatiotemporal Models in Biological and Artificial Systems (Frontiers in Artificial Intelligence and Applications, Vol. 37) (Frontiers in Artificial Intelligence and Applications, V. 37)

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  • Neural networks,
  • Neurosciences,
  • Neural Computing,
  • Mathematical Models In Biology,
  • Science,
  • Science/Mathematics,
  • Neural networks (Computer scie,
  • Artificial intelligence,
  • Life Sciences - Biology - General,
  • Congresses,
  • Neural networks (Computer science)

Edition Notes

Book details

ContributionsF. L. Silva (Editor), L. B. Almeida (Editor), Jose C. Principe (Editor)
The Physical Object
Number of Pages210
ID Numbers
Open LibraryOL9100921M
ISBN 109051993048
ISBN 109789051993042

Download Spatiotemporal Models in Biological and Artificial Systems (Frontiers in Artificial Intelligence and Applications, Vol. 37) (Frontiers in Artificial Intelligence and Applications, V. 37)

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Order Spatiotemporal Models in Biological and Artificial Systems ISBN @ € Qty: Spatiotemporal models are emerging as a very important topic in several disciplines, including neurobiology and artificial neural networks. Spatiotemporal Models in Biological and Artificial Systems (Frontiers in Artificial Intelligence and Applications, Vol.

37) [Silva, F. L., Almeida, L. B., Principe, Jose C.] on *FREE* shipping on qualifying offers. Spatiotemporal models are emerging as a very important topic in several disciplines, including neurobiology and artificial neural networks.

Spatiotemporal transition to epileptic seizures: A nonlinear dynamical analysis of scalp and intracranial eeg recordings. In J. Principe F. Silva and L. Almeida, editors, Spatiotemporal Models in Biological and Artificial by: 4.

SPATIOTEMPORAL MODELS IN BIOLOGICAL AND ARTIFICIAL SYSTEMS: Editors: FL Silva, JC Principe, LB Almeida: Place of Publication: AMSTERDAM: Publisher: I O S PRESS: Pages: Number of pages: 8: ISBN (Print) Publication status: Published - Event: Sintra Workshop on Spatiotemporal Models in Biological and Artificial Author: L Spaanenburg, Jag Nijhuis, A Ypma.

Abstract. In this paper approaches to conceptual modelling of spatio- temporal domains are identified and classified into five general cate- gories: location-based, object or feature-based, event-based, functional or behavioural and causal approaches.

Much work has bee directed to- wards handling the problem from the first four view points, but less from a Cited by: These observations support our hypotheses regarding the preictal transitions in temporal lobe epilepsy.

We anticipate that these observations will lead to a better understanding of the physiological processes involved in temporal lobe epilepsy. editors, Spatiotemporal Models in Biological and Artificial Systems.

IOS Press, Google Cited by: 4. A comprehensive review of spatiotemporal pattern formation in systems driven away from equilibrium is presented, with emphasis on comparisons between.

Abstract. The best understanding of complex biological systems ultimately comes from details of the underlying atomic structures within it. In the absence of known structures of all protein complexes and interactions in a system, structural bioinformatics or modeling fill an important niche in providing predicted mechanistic information which can guide experiments, aid the.

ISBN: X OCLC Number: Description: Seiten: Contents: Data Models, Queries, Evaluation Propositional Databases Relational Databases Constraint Databases Temporal Databases Geographic Databases Moving Objects Databases Image Databases Constraint Objects Databases Genome Databases Set.

For the system that uses ANN models only, the network is composed of a 6-neuron input layer and a 1-neuron output layer; for the systems that use AR and ANN models, there are 7 neurons in. Biological Intelligence.

For all computational models, the question of the emergence of intelligence is a basic one. Solving a specified problem, that often requires searching or generalization, is taken to be a sign of AI, which is assumed to have an all or none quality.

But biological intelligence has gradation. Neural Systems for Control represents the most up-to-date developments in the rapidly growing aplication area of neural networks and focuses on research in natural and artifical neural systems directly applicable to control or making use of modern control theory.

The book covers such important new developments in control systems such as. Models Provide a Coherent Framework for Interpreting Data. A biologist surveys the number of birds nesting on offshore islands and notices that the number depends on the size (e.g., diameter) of the island: the larger the diameter d, the greater is the number of nests N.A graph of this relationship for islands of various sizes reveals a by: 4.

Self-organization, also called (in the social sciences) spontaneous order, is a process where some form of overall order arises from local interactions between parts of an initially disordered process can be spontaneous when sufficient energy is available, not needing control by any external agent.

It is often triggered by seemingly random fluctuations, amplified by. Cellular and Systems Modeling The observed systems range over orders of magnitude, from tissue to cells to molecular assemblies.

Engineering tools are used along with genome-scale information in mathematical and/or computational models that usually adopt a top-down approach. Neural systems models are elegant conceptual tools that provide satisfying insight into brain function. The goal of this new book is to make these tools accessible.

It is written specifically for students in neuroscience, cognitive science, and related areas who want to learn about neural systems modeling but lack extensive background in mathematics and computer programming.

The design of artificial biological systems and the understanding of their natural counterparts are key objectives of the emerging discipline of synthetic biology. Toward both ends, research in synthetic biology has primarily focused on the construction of simple devices, such as transcription-based oscillators and switches.

Abstract. All cells of living organisms are separated from their surroundings and organized internally by means of flexible lipid membranes. In fact, there is consensus that the minimal requirements for self-replicating life processes include the following three features: (1) information carriers (DNA, RNA), (2) a metabolic system, and (3) encapsulation in a container structure [1].Cited by: 1.

Perceptual Organization for Artificial Vision Systems is an edited collection of invited contributions based on papers presented at The Workshop on Perceptual Organization in Computer Vision, held in Corfu, Greece, in September The theme of the workshop was `Assessing the State of the Community and Charting New Research Directions.'.

Mathematical Modeling of Artificial Neural Networks: /ch Models and algorithms have been designed to mimic information processing and knowledge acquisition of the human brain generically called artificial or formalAuthor: Radu Mutihac.

This milestone interdisciplinary work brings you to the cutting edge of emerging technologies inspired by human sight, ranging from semiconductor photoreceptors based on novel organic polymers and retinomorphic processing circuitry to low-powered devices that replicate spatial and temporal processing in the brain.

Moreover, it is the first work of its kind that integrates the full. The book first describes relevant phenomena in ecology and epidemiology, provides examples of pattern formation in natural systems, and summarizes existing modeling approaches. The authors then explore nonspatial models of population dynamics and epidemiology.

INTRODUCTION. Over the last half century, the hypothesis that the nervous system constructs predictive models of the physical world to guide behavior has become a major focus in neuroscience (1–3).In his book, Craik (4, p) was perhaps the first to suggest that organisms maintain internal representations of the external world and to provide a rationale for Cited by: 4.

1. Introduction. Systems biology seeks to understand how physiology emerges from molecular interactions (Ideker et al. ; Kirschner ).Mathematical models are increasingly used to shed light on this (Kitano ; Longabaugh et al. ; Aldridge et al. ).The construction of such models presents unusual challenges, not previously Cited by: Mitochondrial superoxide and aging: uncoupling-protein activity and superoxide production Book Mitochondrial superoxide: production, biological effects, and activation of uncoupling proteins Academic Article Mixture of time-dependent growth models with an application to blue swimmer crab length-frequency data Academic Article.

A fascinating subject, social insects are also a powerful metaphor for artificial intelligence, and the problems they solve - finding food, dividing labor among nestmates, building nests, responding to external challenges - have important counterparts in engineering and computer book provides a detailed look at models of social.

@article{osti_, title = {Neural fuzzy modeling of anaerobic biological wastewater treatment systems}, author = {Tay, J.H. and Zhang, X.}, abstractNote = {Anaerobic biological wastewater treatment systems are difficult to model because their performance is complex and varies significantly with different reactor configurations, influent characteristics, and operational.

Intelligent Engineering Systems through Artificial Neural Networks, Volume 16 Ultrasound-Induced Treatment of Neurodegenerative Diseases across the Blood-Brain Barrier Biomedical Applications of Vibration and Acoustics in Therapy, Bioeffect and Modeling.

() Rule-based modeling and simulation of biochemical systems with molecular finite automata. IET Syst. Biol. PMID: PMCID: PMC Download pdf ; Yang, J. and W. Hlavacek. () Yang J and WS Hlavacek () The efficiency of reactant site sampling in network-free simulation of rule-based models for biochemical.

The Self-Organizing Map, or Kohonen Map, is one of the most widely used neural network algorithms, with thousands of applications covered in the literature. It was one of the strong underlying factors in the popularity of neural networks starting in the early 80's. Currently this method has been included in a large number of commercial and public domain software.

The dynamical systems approach to neuroscience is a branch of mathematical biology that utilizes nonlinear dynamics to understand and model the nervous system and its functions.

In a dynamical system, all possible states are expressed by a phase systems can experience bifurcation (a qualitative change in behavior) as a function of its bifurcation. The appearance of consciousness in the universe remains one of the major mysteries unsolved by science or philosophy.

Absent an agreed-upon definition of consciousness or even a convenient system to test theories of consciousness, a. The present invention relates to a method and system for quantitative and semi-quantitative modeling of biological and physiological systems.

More specifically, the invention relates to the use of overlays to store and manipulate computational biological models. Also provided by the invention are methods and systems for preparing overlays, methods and systems for creating Cited by: This article tries to develop an integrated artificial neural network (ANN) model for spatial and temporal forecasting of daily suspended sediment discharge at multiple gauging stations in Eel River watershed in northwest California.

Complexity of runoff-sediment process and its variability in space and time and also lack of historical sediment data cause difficulties in spatiotemporal Cited by: These projects concern mathematical models of different biological systems, and in particular of the central metabolism of yeast and other simple organisms, of signalling pathways, and of the lipid metabolism and transport in blood.

While there. This volume is the first part of the two-volume proceedings of the International C- ference on Artificial Neural Networks (ICANN ), held on September 11–15, in Warsaw, Poland, with several accompanying workshops held on Septem at the Nicolaus Copernicus University, Toru.

Suggested Citation:"5 Computational Modeling and Simulation as Enablers for Biological Discovery."National Research Council. Catalyzing Inquiry at the Interface of Computing and gton, DC: The National Academies Press. doi: / Model scale – Systems of interest (e.g., Internet and compute grids) extend over large spatiotemporal extent, have global reach, consist of millions of components, and interact through many adaptive mechanisms over various -reduction techniques must be employed.

Which computational models can achieve sufficient spatiotemporal scaling properties. One of the key goals of the EMP is to map the spatiotemporal variability of microbial communities to capture the changes in important processes that need to be appropriately expressed in models to provide reliable forecasts of ecosystem phenotype across our changing planet.

and senior fellow of the Institute of Genomic and Systems Biology. The book series Frontiers in Artificial Intelligence and Applications (FAIA) covers all aspects of theoretical and applied Artificial Intelligence research in the form of monographs, selected doctoral dissertations, handbooks and proceedings volumes.

The FAIA series contains several sub-series, including 'Information Modelling and Knowledge Bases' and 'Knowledge-Based Intelligent .Initially, the field of Artificial Intelligence (AI) was aimed at constructing 'thinking machines', that is, computer systems with human-like, domain-independent intelligence.

But this task proved more difficult than expected. dynamical systems, biological processes in and structures of the brain, as well as robotics and large-scale systems. Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs.

engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological Cited by:

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