Developments in Chaos and Complexity Research
Published on 26. February 2019
274 pages
978-1-5361-5428-3 (ISBN)
Description
This book presents the latest leading-edge international research on artificial life, cellular automata, chaos theory, cognition, complexity theory, synchronization, fractals, genetic algorithms, information systems, metaphors, neural networks, non-linear dynamics, parallel computation and synergetics. The unifying feature of this research is the tie to chaos and complexity.
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Franco F. Orsucci
Developments in Chaos & Complexity Research
Book
06/2008
Nova Science Publishers Inc
€126.26
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Content
- Intro
- DEVELOPMENTS INCHAOS AND COMPLEXITY RESEARCH
- DEVELOPMENTS INCHAOS AND COMPLEXITY RESEARCH
- CONTENTS
- PREFACE
- ACKNOWLEDGEMENTS
- PART 1: CHAOS AND COMPLEXITY IN MEDICINE
- Chapter 1ETHOS IN EVERYDAY ACTION: NOTES FOR AMINDSCAPE OF BIOETHICS
- 1. CONTROL
- 2. DISCIPLINE
- 3. EVOLUTION
- 4. LOCAL RULES
- 5. LANGUAGE AND CONSCIOUSNESS
- 6. TIMING ACTIONS
- 7. NEURODYNAMICS OF TIME
- 8. ETHOS IN ACTION
- REFERENCES
- Chapter 2DETECTION OF TRANSIENT SYNCHRONIZATIONIN MULTIVARIATE BRAIN SIGNALS APPLICATIONTO EVENT-RELATED POTENTIALS
- Abstract
- 1. Introduction
- 2. Methods
- 2.1. Clustering of Linear Data
- 2.2. Clustering of Circular Data
- 2.3. Statistical Analysis
- 2.4. Data Acquisition
- 3. Results
- 3.1. Application to Simulated Linear Data
- 3.2. Application to Simulated Circular Data
- 3.3. Application to Experimental Linear Data
- 3.4. Application to Empirical Circular Data
- 3.5. Comparison to an Existing Method
- 4. Discussion
- References
- Chapter 3ABRIEF NOTE ON RECURRENCE QUANTIFICATIONANALYSIS OF BIPOLAR DISORDER PERFORMED BYUSING A VAN DER POL OSCILLATOR MODEL
- ABSTRACT
- 1. INTRODUCTION
- 2. THE BIPOLAR DISORDER
- 3. QUALITATIVE MODELING OF BIPOLAR DISORDER BY THEVAN DER POL MATHEMATICAL SIMULATION
- 4. QUANTITATIVE ANALYSIS OF THE OBTAINED TIME SERIES DATA
- Gottschalk's Analysis of Correlation Dimension of Experimental Time Series
- Analysis of Correlation Dimension of Van Der Pol Model Generated TimeSeries
- Lyapunov Exponents Calculation
- Recurrence Quantification Analysis
- Coarse Graining Spectral Analysis
- 5. DISCUSSION
- REFERENCES
- Chapter 4COMPARISON OF EMPIRICAL MODEDECOMPOSITION AND WAVELET APPROACH FORTHE ANALYSIS OF TIME SCALE SYNCHRONIZATION
- ABSTRACT
- 1. INTRODUCTION
- 2.MODELS
- 3. EMPIRICAL MODE DECOMPOSITION
- 4. TIME SCALE SYNCHRONIZATION BETWEEN TWO DIFFERENTCHAOTIC SYSTEMS VIA EMDMETHOD:FROM PHASE TO LAG SYNCHRONIZATION
- 5.MEASURE OF SYNCHRONIZATION FOR EMD
- 6.WAVELET APPROACH (WA)
- 7.MEASURE OF SYNCHRONIZATION FOR WA
- SUMMARY AND CONCLUSION
- REFERENCES
- Chapter 5NON-INVASIVE ASSESSMENT OF RISK FOR SEVERETACHYARRHYTHMIAS BY MEANS OF NON-LINEARANALYSIS TECHNIQUES
- ABSTRACT
- 1. INTRODUCTION
- 2.METHODS
- 2.1 Non-Linear Analysis of ECG Signals
- 2.2 Recurrence Quantification Analysis
- Mutual Information
- Entropy
- Recurrence
- Determinism
- Ratio
- 2.3 Hierarchical Clustering
- 2.4 Artificial Neural Network analysis
- 2.5 Chaotic Attractors
- 3. RESULTS
- 3.1 Study Population
- 3.2 Electrophysiological Study
- 3.3 Non-linear Analysis of ECG Signals
- 3.4 Artificial Neural Networks results
- 3.5 Chaotic Attractors
- 3.6 Statistical Analysis
- 4. DISCUSSION AND CONCLUSIONS
- ACKNOWLEDGEMENTS
- REFERENCES
- Chapter 6RECURRENCE QUANTIFICATION ANALYSIS,VARIABILITY ANALYSIS, AND FRACTAL DIMENSIONESTIMATION IN 99MTC-HDPNUCLEARSCINTIGRAPHY OF MAXILLARY BONES IN SUBJECTSWITH OSTEOPOROSIS
- ABSTRACT
- 1. INTRODUCTION
- 2. THE METHODOLOGY
- 3. EXPERIMENTAL METHODS
- 4. RESULTS
- Example of Selected R.O.I.
- Controls
- Subject With Osteoporosis
- 5. CONCLUSION
- REFERENCES
- Chapter 7DETECTING LOW DIMENSIONAL CHAOSIN SMALL NOISY SAMPLE SETS
- ABSTRACT
- INTRODUCTION
- 2.METHODOLOGY
- 2.1. Reconstruction of Dynamics by the Method of Time Delays
- 2.2. A Measure of Determinism
- 3. NUMERICAL EXPERIMENTS
- 3.1. Applying Traditional Methods to Small Sample Set
- 3.2. A Method Adapted to Small Data Set
- 3.2.1. Convergence to Theoretical Value
- 3.2.2. Stochastic Processes
- 3.2.3. Chaotic Processes Infected with Additive Complex Noise
- 3.2.4. Real World Data
- Santa Fe Institute Prediction Competition
- Stock Market Prices: Dow Jones Yearly Returns
- CONCLUSION
- REFERENCES
- PART 2: CHAOS AND COMPLEXITY IN COMPUTERSCIENCE AND IN ENVIRONMENTAL STUDIES
- Chapter 8ALAN TURING MEETS THE SPHINX:SOME OLD AND NEW RIDDLES1
- ABSTRACT
- INTRODUCTION
- THE MYTH OF OEDIPUS
- NEW TWISTS TO AN OLD MYTH
- RIDDLE AS PARADOX
- METAPHORICAL THINKING AND COGNITIVE DEVELOPMENT
- SELF-REFERENCE AND UNIVERSAL TURING MACHINES
- THE RIDDLE AS MIRROR
- REFERENCES
- Chapter 9FORECASTING OF HYPERCHAOTIC RÖSSLERSYSTEM STATE VARIABLES USING ONE OBSERVABLE
- ABSTRACT
- 1. INTRODUCTION
- 2. CASE STUDY: THE RÖSSLER HYPERCHAOTIC SYSTEM
- 3. EXPERIMENTAL RESULTS
- 3.1 The Neural Model
- 3.2 Sensitivity Analysis
- 4. CONCLUSION
- REFERENCES
- Chapter 10PARALLEL IMPLEMENTATION OF SHORTEST PATHSPROBLEM ON WEIGHTED INTERVALAND CIRCULAR ARC GRAPHS
- ABSTRACT
- 1. INTRODUCTION
- 2. TERMINOLOGY
- Definition 1
- 3. PRELIMINARY ALGORITHM
- Definition 2
- Definition 3
- Lemma 1
- Proof
- Corollary 1
- Definition 4
- Lemma 2
- Proof
- Corollary 2
- Corollary 3
- Lemma 3
- Proof
- Lemma 4
- Proof
- 4. A LINEAR TIME IMPLEMENTATION
- Definition 5
- Example: Interval Operations
- Algorithm 1: Maxright
- Algorithm 2: Next
- 5. FURTHER EXTENSIONS
- 5.1. Zero- Weight Intervals
- 5.2. Implementation Note
- 5.3. Circular -Arcs
- 6. CONCLUSIONS
- ACKNOWLEDGEMENTS
- REFERENCES
- Chapter 11FRACTAL GEOMETRY IN COMPUTER GRAPHICSAND IN VIRTUAL REALITY
- ABSTRACT
- 1. INTRODUCTION
- 2. FRACTAL OBJECTS
- 2.1. The Self-Similarity
- 2.2. The Iterated Function System
- 2.3. L-Systems
- 3. FRACTAL GEOMETRY IN COMPUTER GRAPHICS
- 4. FRACTAL GEOMETRY FOR MODELLING VIRTUAL LANDSCAPES
- 5. CONCLUSIONS
- REFERENCES
- Chapter 12ASENSITIVITY STUDY ON THE HYDRODYNAMICS OFTHE VERBANO LAKE BY MEANS OF A CFD TOOL:THE 3D EFFECTS OF AFFLUENTS,EFFLUENT AND WIND
- ABSTRACT
- REFERENCES
- Chapter 13PROSPECTIVE HOME-BUYERS' PROPENSITY-TO-BUYIN THE HOUSING INDUSTRY
- ABSTRACT
- I. EXISTING LITERATURE
- II. PSYCHOLOGICAL BIASES AND EFFECTS IN HOUSING MARKETS
- Proposition 1 - Wealth Bias
- Proposition 2 - Financing Process Effect
- Proposition 3: Comparison Effects
- Proposition 4: Stability Bias (Stability of Wealth)
- Proposition 5: Price Justification Effect
- Proposition 6: Prior Knowledge Bias
- Proposition 7: Willingness to Accept Losses ("WTAL").
- Proposition 8: Negative Attachment Bias (positive attachment or negativeattachment)
- Proposition 9: Mortgage Bias
- Proposition 10: Property Type Bias
- Proposition 11: The Dual-Matching Differential Effect
- Proposition 12: Occupancy-Stress Bias
- Proposition 13: Quasi-Public Goods Conformity Effect
- Proposition 14: The Deferred-Disutility/Deferred-Pain Bias
- Proposition 15: Rapid-Profits Bias
- Proposition 16: Realization Bias
- Proposition 17: Materialism Effect
- Proposition 18: Pensions Inertia Effect
- III. THE PROSPECTIVE HOME-BUYER'S PROPENSITY-TO-BUY
- CONCLUSION
- REFERENCES
- Chapter 14ON THE CHOICE BETWEEN RENTING AND HOMEOWNERSHIPIN THE HOUSING INDUSTRY
- ABSTRACT
- I. INTRODUCTION
- II. EXISTING LITERATURE
- III. PSYCHOLOGICAL BIASES AND EFFECTS IN HOUSING MARKETS
- Proposition 1: Risk Shifting Bias
- Proposition 2: Income Bias
- Proposition 3: Real Estate And Housing Have Relatively Very Low Regret
- Proposition 4: Prioritization Bias
- Proposition 5: Rules Effect
- Proposition 6: Search Costs Bias
- Proposition 7: Reduced-Commitment Effect
- Proposition 8: Real Estate Broker Uniformity Effect
- Proposition-9: Expectations Bias
- Proposition 10: Size Effects
- Proposition 11: Comparison Effects
- IV. THE CHOICE BETWEEN RENTING AND HOME OWNERSHIP
- IV. CONCLUSION
- V. BIBLIOGRAPHY
- Chapter 15CLIMATIC MEMORY OF 5 ITALIAN DEEP LAKES:SECULAR VARIATION
- ABSTRACT
- REFERENCES
- INDEX
- Blank Page
