Decision making :: a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 10-13 January 2010 /
This invaluable book captures the proceedings of a workshop that brought together a group of distinguished scientists from a variety of disciplines to discuss how networking influences decision making. The individual lectures interconnect psychological testing, the modeling of neuron networks and br...
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| Weitere Verfasser: | , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New Jersey :
World Scientific,
©2011.
|
| Schriftenreihe: | Studies of nonlinear phenomena in life sciences ;
v. 15. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | This invaluable book captures the proceedings of a workshop that brought together a group of distinguished scientists from a variety of disciplines to discuss how networking influences decision making. The individual lectures interconnect psychological testing, the modeling of neuron networks and brain dynamics to the transport of information within and between complex networks. Of particular importance was the introduction of a new principle that governs how complex networks talk to one another - the Principle of Complexity Management (PCM). PCM establishes that the transfer of information fr. |
| Beschreibung: | 1 online resource (ix, 196 pages) : illustrations |
| Bibliographie: | Includes bibliographical references. |
| ISBN: | 9789814365826 9814365823 |
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| 245 | 0 | 0 | |a Decision making : |b a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 10-13 January 2010 / |c editors, Paolo Grigolini, Bruce J. West. |
| 260 | |a New Jersey : |b World Scientific, |c ©2011. | ||
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| 490 | 1 | |a Studies of nonlinear phenomena in life science ; |v v. 15 | |
| 504 | |a Includes bibliographical references. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Preface; CONTENTS; 1. Overview of ARO program on network science for human decision making B.J. West; 1. Introduction; 2. Background; 2.1. What we know about networks; 2.2. What we do not know about the linking of physical and human networks; 3. What We Have Been Doing; 3.1. Complexity theory and modeling without scales; 3.2. Information propagation in complex adaptive networks; 4. Preliminary Conclusions; References; 2. Viewing the extended mind hypothesis (Clark & Chambers) in terms of complex systems dynamics G. Werner; 1. Background; 2. On the Extended Mind Hypothesis. | |
| 505 | 8 | |a 3. Brain and World as ONE Complex Dynamical System4. Praxis Ahead of Theory; 5. Conclusion; References; 3. Uncertainty in psychophysics: Deriving a network of psychophysical equations K.H. Norwich; 1. Introduction; 2. Philosophical Underpinnings; 3. Mathematical Representation of the Psychophysical Law (Weber-Fechner and Stevens); 4. A Network of Equations Issuing from the Entropic Form of the Psychophysical Law; 4.1. The differential threshold (DH from Fechner's conjecture) and Weber's fraction; 4.2. The hyperbolic law governing the magnitude of n (DH from Miller's magical number). | |
| 505 | 8 | |a 4.3. Simple reaction time (DH is the minimum quantity of information needed to react)5. Searching for Support within Thermodynamics and Statistical Physics; 5.1. Emergence of the Weber-Fechner law from thermodynamics; 6. Discussion; 6.1. Review; 6.2. Quantum Sufficiat; Acknowledgements; References; 4. The collective brain E. Tagliazucchi and D.R. Chialvo; 1. Introduction; 2. Emergent Complex Dynamics is always Critical; 3. The Collective Large-scale Brain Dynamics; 4. Neuronal Avalanching in Small Scale is Critical; 5. Psychophysics and Behavior; 6. An Evolutionary Perspective. | |
| 505 | 8 | |a 7. Noise or Critical Fluctuations? Equilibrium vs Non-equilibrium8. Outlook; Acknowledgements; References; 5. Acquiring long-range memory through adaptive avalanches S. Boettcher; 1. Introduction; 2. Motivation from Self-organized Criticality; 3. Spin Glass Ground States with Extremal Optimization; 4. EO Dynamics; 5. Annealed Optimization Model; 6. Evolution Equations for Local Search Heuristics; 6.1. Extremal optimization algorithm; 6.2. Update probabilities for extremal optimization; 6.3. Update probabilities for metropolis algorithms; 6.4. Evolution equations for a simple barrier model. | |
| 505 | 8 | |a 6.5. Jamming model for -EOReferences; 6. Random walk of complex networks: From infinitely slow to instantaneous transition to equilibrium N.W. Hollingshad, P. Grigolini and P. Allegrini; 1. Introduction; 2. Preliminary Remarks on the Size of a Complex Network; 3. On the Master Matrix A; 4. Transition to Equilibrium in Hierarchical Networks; 5. Return to the Origin in a Scale-free Network; 5.1. Ad hoc scale-free network; 5.2. Hierarchical network; 6. Conclusions; Acknowledgements; References; 7. Coherence and complexity M. Bologna, E. Geneston, P. Grigolini, M. Turalska and M. Lukovic. | |
| 520 | |a This invaluable book captures the proceedings of a workshop that brought together a group of distinguished scientists from a variety of disciplines to discuss how networking influences decision making. The individual lectures interconnect psychological testing, the modeling of neuron networks and brain dynamics to the transport of information within and between complex networks. Of particular importance was the introduction of a new principle that governs how complex networks talk to one another - the Principle of Complexity Management (PCM). PCM establishes that the transfer of information fr. | ||
| 650 | 0 | |a Neural networks (Neurobiology) |v Congresses. | |
| 650 | 0 | |a Psychophysics |v Congresses. | |
| 650 | 0 | |a Chaotic behavior in systems |v Congresses. | |
| 650 | 0 | |a Complexity (Philosophy) |v Congresses. | |
| 650 | 0 | |a Decision making |x Physiological aspects |v Congresses. | |
| 650 | 0 | |a Decision making. |0 http://id.loc.gov/authorities/subjects/sh85036199 | |
| 650 | 0 | |a Neural networks (Computer science) |0 http://id.loc.gov/authorities/subjects/sh90001937 | |
| 650 | 0 | |a Psychophysics. |0 http://id.loc.gov/authorities/subjects/sh85108501 | |
| 650 | 1 | 2 | |a Decision Making |
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| 650 | 6 | |a Réseaux neuronaux (Neurobiologie) |v Congrès. | |
| 650 | 6 | |a Psychophysique |v Congrès. | |
| 650 | 6 | |a Chaos |v Congrès. | |
| 650 | 6 | |a Complexité (Philosophie) |v Congrès. | |
| 650 | 6 | |a Prise de décision |x Aspect physiologique |v Congrès. | |
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| contents | Preface; CONTENTS; 1. Overview of ARO program on network science for human decision making B.J. West; 1. Introduction; 2. Background; 2.1. What we know about networks; 2.2. What we do not know about the linking of physical and human networks; 3. What We Have Been Doing; 3.1. Complexity theory and modeling without scales; 3.2. Information propagation in complex adaptive networks; 4. Preliminary Conclusions; References; 2. Viewing the extended mind hypothesis (Clark & Chambers) in terms of complex systems dynamics G. Werner; 1. Background; 2. On the Extended Mind Hypothesis. 3. Brain and World as ONE Complex Dynamical System4. Praxis Ahead of Theory; 5. Conclusion; References; 3. Uncertainty in psychophysics: Deriving a network of psychophysical equations K.H. Norwich; 1. Introduction; 2. Philosophical Underpinnings; 3. Mathematical Representation of the Psychophysical Law (Weber-Fechner and Stevens); 4. A Network of Equations Issuing from the Entropic Form of the Psychophysical Law; 4.1. The differential threshold (DH from Fechner's conjecture) and Weber's fraction; 4.2. The hyperbolic law governing the magnitude of n (DH from Miller's magical number). 4.3. Simple reaction time (DH is the minimum quantity of information needed to react)5. Searching for Support within Thermodynamics and Statistical Physics; 5.1. Emergence of the Weber-Fechner law from thermodynamics; 6. Discussion; 6.1. Review; 6.2. Quantum Sufficiat; Acknowledgements; References; 4. The collective brain E. Tagliazucchi and D.R. Chialvo; 1. Introduction; 2. Emergent Complex Dynamics is always Critical; 3. The Collective Large-scale Brain Dynamics; 4. Neuronal Avalanching in Small Scale is Critical; 5. Psychophysics and Behavior; 6. An Evolutionary Perspective. 7. Noise or Critical Fluctuations? Equilibrium vs Non-equilibrium8. Outlook; Acknowledgements; References; 5. Acquiring long-range memory through adaptive avalanches S. Boettcher; 1. Introduction; 2. Motivation from Self-organized Criticality; 3. Spin Glass Ground States with Extremal Optimization; 4. EO Dynamics; 5. Annealed Optimization Model; 6. Evolution Equations for Local Search Heuristics; 6.1. Extremal optimization algorithm; 6.2. Update probabilities for extremal optimization; 6.3. Update probabilities for metropolis algorithms; 6.4. Evolution equations for a simple barrier model. 6.5. Jamming model for -EOReferences; 6. Random walk of complex networks: From infinitely slow to instantaneous transition to equilibrium N.W. Hollingshad, P. Grigolini and P. Allegrini; 1. Introduction; 2. Preliminary Remarks on the Size of a Complex Network; 3. On the Master Matrix A; 4. Transition to Equilibrium in Hierarchical Networks; 5. Return to the Origin in a Scale-free Network; 5.1. Ad hoc scale-free network; 5.2. Hierarchical network; 6. Conclusions; Acknowledgements; References; 7. Coherence and complexity M. Bologna, E. Geneston, P. Grigolini, M. Turalska and M. Lukovic. |
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| dewey-ones | 612 - Human physiology |
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| discipline | Medizin |
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| genre | Congress proceedings (reports) aat Conference papers and proceedings fast Conference papers and proceedings. lcgft http://id.loc.gov/authorities/genreForms/gf2014026068 Actes de congrès. rvmgf |
| genre_facet | Congress proceedings (reports) Conference papers and proceedings Conference papers and proceedings. Actes de congrès. |
| id | ZDB-4-EBA-ocn777561001 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:18:16Z |
| institution | BVB |
| isbn | 9789814365826 9814365823 |
| language | English |
| oclc_num | 777561001 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (ix, 196 pages) : illustrations |
| psigel | ZDB-4-EBA |
| publishDate | 2011 |
| publishDateSearch | 2011 |
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| publisher | World Scientific, |
| record_format | marc |
| series | Studies of nonlinear phenomena in life sciences ; |
| series2 | Studies of nonlinear phenomena in life science ; |
| spelling | Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 10-13 January 2010 / editors, Paolo Grigolini, Bruce J. West. New Jersey : World Scientific, ©2011. 1 online resource (ix, 196 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Studies of nonlinear phenomena in life science ; v. 15 Includes bibliographical references. Print version record. Preface; CONTENTS; 1. Overview of ARO program on network science for human decision making B.J. West; 1. Introduction; 2. Background; 2.1. What we know about networks; 2.2. What we do not know about the linking of physical and human networks; 3. What We Have Been Doing; 3.1. Complexity theory and modeling without scales; 3.2. Information propagation in complex adaptive networks; 4. Preliminary Conclusions; References; 2. Viewing the extended mind hypothesis (Clark & Chambers) in terms of complex systems dynamics G. Werner; 1. Background; 2. On the Extended Mind Hypothesis. 3. Brain and World as ONE Complex Dynamical System4. Praxis Ahead of Theory; 5. Conclusion; References; 3. Uncertainty in psychophysics: Deriving a network of psychophysical equations K.H. Norwich; 1. Introduction; 2. Philosophical Underpinnings; 3. Mathematical Representation of the Psychophysical Law (Weber-Fechner and Stevens); 4. A Network of Equations Issuing from the Entropic Form of the Psychophysical Law; 4.1. The differential threshold (DH from Fechner's conjecture) and Weber's fraction; 4.2. The hyperbolic law governing the magnitude of n (DH from Miller's magical number). 4.3. Simple reaction time (DH is the minimum quantity of information needed to react)5. Searching for Support within Thermodynamics and Statistical Physics; 5.1. Emergence of the Weber-Fechner law from thermodynamics; 6. Discussion; 6.1. Review; 6.2. Quantum Sufficiat; Acknowledgements; References; 4. The collective brain E. Tagliazucchi and D.R. Chialvo; 1. Introduction; 2. Emergent Complex Dynamics is always Critical; 3. The Collective Large-scale Brain Dynamics; 4. Neuronal Avalanching in Small Scale is Critical; 5. Psychophysics and Behavior; 6. An Evolutionary Perspective. 7. Noise or Critical Fluctuations? Equilibrium vs Non-equilibrium8. Outlook; Acknowledgements; References; 5. Acquiring long-range memory through adaptive avalanches S. Boettcher; 1. Introduction; 2. Motivation from Self-organized Criticality; 3. Spin Glass Ground States with Extremal Optimization; 4. EO Dynamics; 5. Annealed Optimization Model; 6. Evolution Equations for Local Search Heuristics; 6.1. Extremal optimization algorithm; 6.2. Update probabilities for extremal optimization; 6.3. Update probabilities for metropolis algorithms; 6.4. Evolution equations for a simple barrier model. 6.5. Jamming model for -EOReferences; 6. Random walk of complex networks: From infinitely slow to instantaneous transition to equilibrium N.W. Hollingshad, P. Grigolini and P. Allegrini; 1. Introduction; 2. Preliminary Remarks on the Size of a Complex Network; 3. On the Master Matrix A; 4. Transition to Equilibrium in Hierarchical Networks; 5. Return to the Origin in a Scale-free Network; 5.1. Ad hoc scale-free network; 5.2. Hierarchical network; 6. Conclusions; Acknowledgements; References; 7. Coherence and complexity M. Bologna, E. Geneston, P. Grigolini, M. Turalska and M. Lukovic. This invaluable book captures the proceedings of a workshop that brought together a group of distinguished scientists from a variety of disciplines to discuss how networking influences decision making. The individual lectures interconnect psychological testing, the modeling of neuron networks and brain dynamics to the transport of information within and between complex networks. Of particular importance was the introduction of a new principle that governs how complex networks talk to one another - the Principle of Complexity Management (PCM). PCM establishes that the transfer of information fr. Neural networks (Neurobiology) Congresses. Psychophysics Congresses. Chaotic behavior in systems Congresses. Complexity (Philosophy) Congresses. Decision making Physiological aspects Congresses. Decision making. http://id.loc.gov/authorities/subjects/sh85036199 Neural networks (Computer science) http://id.loc.gov/authorities/subjects/sh90001937 Psychophysics. http://id.loc.gov/authorities/subjects/sh85108501 Decision Making Neural Networks, Computer Psychophysics Réseaux neuronaux (Neurobiologie) Congrès. Psychophysique Congrès. Chaos Congrès. Complexité (Philosophie) Congrès. Prise de décision Aspect physiologique Congrès. Prise de décision. Réseaux neuronaux (Informatique) Psychophysique. decision making. aat MEDICAL Neuroscience. bisacsh PSYCHOLOGY Neuropsychology. bisacsh Neural networks (Computer science) fast Decision making fast Chaotic behavior in systems fast Complexity (Philosophy) fast Decision making Physiological aspects fast Neural networks (Neurobiology) fast Psychophysics fast Congress proceedings (reports) aat Conference papers and proceedings fast Conference papers and proceedings. lcgft http://id.loc.gov/authorities/genreForms/gf2014026068 Actes de congrès. rvmgf Grigolini, Paolo. West, Bruce J. Print version: Decision making. New Jersey : World Scientific, ©2011 9789814365819 (OCoLC)767854123 Studies of nonlinear phenomena in life sciences ; v. 15. http://id.loc.gov/authorities/names/n96010377 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=426402 Volltext |
| spellingShingle | Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 10-13 January 2010 / Studies of nonlinear phenomena in life sciences ; Preface; CONTENTS; 1. Overview of ARO program on network science for human decision making B.J. West; 1. Introduction; 2. Background; 2.1. What we know about networks; 2.2. What we do not know about the linking of physical and human networks; 3. What We Have Been Doing; 3.1. Complexity theory and modeling without scales; 3.2. Information propagation in complex adaptive networks; 4. Preliminary Conclusions; References; 2. Viewing the extended mind hypothesis (Clark & Chambers) in terms of complex systems dynamics G. Werner; 1. Background; 2. On the Extended Mind Hypothesis. 3. Brain and World as ONE Complex Dynamical System4. Praxis Ahead of Theory; 5. Conclusion; References; 3. Uncertainty in psychophysics: Deriving a network of psychophysical equations K.H. Norwich; 1. Introduction; 2. Philosophical Underpinnings; 3. Mathematical Representation of the Psychophysical Law (Weber-Fechner and Stevens); 4. A Network of Equations Issuing from the Entropic Form of the Psychophysical Law; 4.1. The differential threshold (DH from Fechner's conjecture) and Weber's fraction; 4.2. The hyperbolic law governing the magnitude of n (DH from Miller's magical number). 4.3. Simple reaction time (DH is the minimum quantity of information needed to react)5. Searching for Support within Thermodynamics and Statistical Physics; 5.1. Emergence of the Weber-Fechner law from thermodynamics; 6. Discussion; 6.1. Review; 6.2. Quantum Sufficiat; Acknowledgements; References; 4. The collective brain E. Tagliazucchi and D.R. Chialvo; 1. Introduction; 2. Emergent Complex Dynamics is always Critical; 3. The Collective Large-scale Brain Dynamics; 4. Neuronal Avalanching in Small Scale is Critical; 5. Psychophysics and Behavior; 6. An Evolutionary Perspective. 7. Noise or Critical Fluctuations? Equilibrium vs Non-equilibrium8. Outlook; Acknowledgements; References; 5. Acquiring long-range memory through adaptive avalanches S. Boettcher; 1. Introduction; 2. Motivation from Self-organized Criticality; 3. Spin Glass Ground States with Extremal Optimization; 4. EO Dynamics; 5. Annealed Optimization Model; 6. Evolution Equations for Local Search Heuristics; 6.1. Extremal optimization algorithm; 6.2. Update probabilities for extremal optimization; 6.3. Update probabilities for metropolis algorithms; 6.4. Evolution equations for a simple barrier model. 6.5. Jamming model for -EOReferences; 6. Random walk of complex networks: From infinitely slow to instantaneous transition to equilibrium N.W. Hollingshad, P. Grigolini and P. Allegrini; 1. Introduction; 2. Preliminary Remarks on the Size of a Complex Network; 3. On the Master Matrix A; 4. Transition to Equilibrium in Hierarchical Networks; 5. Return to the Origin in a Scale-free Network; 5.1. Ad hoc scale-free network; 5.2. Hierarchical network; 6. Conclusions; Acknowledgements; References; 7. Coherence and complexity M. Bologna, E. Geneston, P. Grigolini, M. Turalska and M. Lukovic. Neural networks (Neurobiology) Congresses. Psychophysics Congresses. Chaotic behavior in systems Congresses. Complexity (Philosophy) Congresses. Decision making Physiological aspects Congresses. Decision making. http://id.loc.gov/authorities/subjects/sh85036199 Neural networks (Computer science) http://id.loc.gov/authorities/subjects/sh90001937 Psychophysics. http://id.loc.gov/authorities/subjects/sh85108501 Decision Making Neural Networks, Computer Psychophysics Réseaux neuronaux (Neurobiologie) Congrès. Psychophysique Congrès. Chaos Congrès. Complexité (Philosophie) Congrès. Prise de décision Aspect physiologique Congrès. Prise de décision. Réseaux neuronaux (Informatique) Psychophysique. decision making. aat MEDICAL Neuroscience. bisacsh PSYCHOLOGY Neuropsychology. bisacsh Neural networks (Computer science) fast Decision making fast Chaotic behavior in systems fast Complexity (Philosophy) fast Decision making Physiological aspects fast Neural networks (Neurobiology) fast Psychophysics fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85036199 http://id.loc.gov/authorities/subjects/sh90001937 http://id.loc.gov/authorities/subjects/sh85108501 http://id.loc.gov/authorities/genreForms/gf2014026068 |
| title | Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 10-13 January 2010 / |
| title_auth | Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 10-13 January 2010 / |
| title_exact_search | Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 10-13 January 2010 / |
| title_full | Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 10-13 January 2010 / editors, Paolo Grigolini, Bruce J. West. |
| title_fullStr | Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 10-13 January 2010 / editors, Paolo Grigolini, Bruce J. West. |
| title_full_unstemmed | Decision making : a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 10-13 January 2010 / editors, Paolo Grigolini, Bruce J. West. |
| title_short | Decision making : |
| title_sort | decision making a psychophysics application of network science center for nonlinear science university of north texas usa 10 13 january 2010 |
| title_sub | a psychophysics application of network science, Center for Nonlinear Science, University of North Texas, USA, 10-13 January 2010 / |
| topic | Neural networks (Neurobiology) Congresses. Psychophysics Congresses. Chaotic behavior in systems Congresses. Complexity (Philosophy) Congresses. Decision making Physiological aspects Congresses. Decision making. http://id.loc.gov/authorities/subjects/sh85036199 Neural networks (Computer science) http://id.loc.gov/authorities/subjects/sh90001937 Psychophysics. http://id.loc.gov/authorities/subjects/sh85108501 Decision Making Neural Networks, Computer Psychophysics Réseaux neuronaux (Neurobiologie) Congrès. Psychophysique Congrès. Chaos Congrès. Complexité (Philosophie) Congrès. Prise de décision Aspect physiologique Congrès. Prise de décision. Réseaux neuronaux (Informatique) Psychophysique. decision making. aat MEDICAL Neuroscience. bisacsh PSYCHOLOGY Neuropsychology. bisacsh Neural networks (Computer science) fast Decision making fast Chaotic behavior in systems fast Complexity (Philosophy) fast Decision making Physiological aspects fast Neural networks (Neurobiology) fast Psychophysics fast |
| topic_facet | Neural networks (Neurobiology) Congresses. Psychophysics Congresses. Chaotic behavior in systems Congresses. Complexity (Philosophy) Congresses. Decision making Physiological aspects Congresses. Decision making. Neural networks (Computer science) Psychophysics. Decision Making Neural Networks, Computer Psychophysics Réseaux neuronaux (Neurobiologie) Congrès. Psychophysique Congrès. Chaos Congrès. Complexité (Philosophie) Congrès. Prise de décision Aspect physiologique Congrès. Prise de décision. Réseaux neuronaux (Informatique) Psychophysique. decision making. MEDICAL Neuroscience. PSYCHOLOGY Neuropsychology. Decision making Chaotic behavior in systems Complexity (Philosophy) Decision making Physiological aspects Neural networks (Neurobiology) Congress proceedings (reports) Conference papers and proceedings Conference papers and proceedings. Actes de congrès. |
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