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Bibliografie tematiche / Self-organized criticality

Letteratura scientifica selezionata sul tema "Self-organized criticality"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 14 marzo 2023

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Articoli di riviste sul tema "Self-organized criticality"

1

Turcotte, Donald L. "Self-organized criticality". Reports on Progress in Physics 62, n. 10 (28 settembre 1999): 1377–429. http://dx.doi.org/10.1088/0034-4885/62/10/201.

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2

Bak, Per, Chao Tang e Kurt Wiesenfeld. "Self-organized criticality". Physical Review A 38, n. 1 (1 luglio 1988): 364–74. http://dx.doi.org/10.1103/physreva.38.364.

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3

Bak, Per, e Kan Chen. "Self-Organized Criticality". Scientific American 264, n. 1 (gennaio 1991): 46–53. http://dx.doi.org/10.1038/scientificamerican0191-46.

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4

Tang, Chao. "Self-Organized Criticality". IFAC Proceedings Volumes 27, n. 1 (marzo 1994): 29–30. http://dx.doi.org/10.1016/s1474-6670(17)46153-2.

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5

Bak, Per. "Self-organized criticality". Physica A: Statistical Mechanics and its Applications 163, n. 1 (febbraio 1990): 403–9. http://dx.doi.org/10.1016/0378-4371(90)90348-v.

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6

Sornette, Didier, Anders Johansen e Ivan Dornic. "Mapping Self-Organized Criticality onto Criticality". Journal de Physique I 5, n. 3 (marzo 1995): 325–35. http://dx.doi.org/10.1051/jp1:1995129.

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De Menech, Mario, e Attilio L. Stella. "Turbulent self-organized criticality". Physica A: Statistical Mechanics and its Applications 309, n. 3-4 (giugno 2002): 289–96. http://dx.doi.org/10.1016/s0378-4371(02)00745-8.

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8

Tainaka, Kei-ichi, e Yoshiaki Itoh. "Apparent self-organized criticality". Physics Letters A 220, n. 1-3 (settembre 1996): 58–62. http://dx.doi.org/10.1016/0375-9601(96)00492-6.

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9

Ďuran, I., J. Stöckel, M. Hron, J. Horácek, K. Dakubka e L. Kryŝka. "Self-Organized Criticality paradigm". Czechoslovak Journal of Physics 50, S3 (marzo 2000): 42–46. http://dx.doi.org/10.1007/bf03165853.

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10

Creutz, Michael. "On self organized criticality". Nuclear Physics B - Proceedings Supplements 26 (gennaio 1992): 252–56. http://dx.doi.org/10.1016/0920-5632(92)90245-n.

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Tesi sul tema "Self-organized criticality"

1

Hasty, Jeff. "A renormalization group study of self-organized criticality". Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/29887.

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2

Neuß, Marius [Verfasser]. "Stochastic partial differential equations arising in self-organized criticality / Marius Neuß". Bielefeld : Universitätsbibliothek Bielefeld, 2021. http://d-nb.info/1231994762/34.

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Харченко, Дмитро Олегович, Дмитрий Олегович Харченко, Dmytro Olehovych Kharchenko e I. R. Vernyhora. "Simulation of self-organized criticality within the framework of sandpile model". Thesis, Видавництво СумДУ, 2005. http://essuir.sumdu.edu.ua/handle/123456789/17177.

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4

Marsili, Matteo. "From Interface Growth to Dynamics in Disordered Media and Self Organized Criticality". Doctoral thesis, SISSA, 1994. http://hdl.handle.net/20.500.11767/4536.

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Warren, Keith Leverett. "Scaling, self-organized criticality and trend persistence in state psychiatric hospital admissions and discharges /". Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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6

Westrin, Pontus. "External Conditions Effects on the Self-Organised Criticality of the Calving Glacier Front of Tunabreen, Svalbard". Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-255867.

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Mass balance processes in glaciers are important for determining the growth or retreat of ice. Calving, the mechanical breakage of ice bergs from a glacier front, is a poorly understood phenomenon. This process has great importance to the mass balance of many glaciers, for example on Antarctica and in the Arctic. A recent paper by Åström et al. (2014) compare calving fronts to Self-Organized Critical (SOC) systems, especially the Abelian sand pile model, meaning that the calving front will stay at a critical state at all times. Fluctuations in external conditions will cause the glacier front to either retreat or advance. The calving frequency and size distribution of Tunabreen, a tidewater glacier in Svalbard, was studied during August and September, 2014, with the use of a time-lapse camera set up in front of the calving front. An 11-day period is studied in detail and compared to certain external factors, i.e. tide, air temperature, humidity, atmospheric pressure, wind speed and wind direction. The results are also compared to the relationships found by Åström et al. (2014). The results vary: tide relationships are found as the amplitude reaches above 1 meter, but seize to correlate as the tide falls off. Temperature trends are found for certain periods, but are of low credibility. Humidity, atmospheric pressure, wind speed and wind direction show low to no correlation with the calving size distribution. Fragment size distribution and calving rates show good correlation with the results from Åström et al. (2014). This helps to confirm the theory of SOC applied to calving fronts. Time-lapse photography is deemed as a good way to observe calving fronts, but have certain problems which are mostly related to the weather. Longer time periods would be needed to find better long term relationships between external conditions and calving frequencies, but data is hard to acquire and time consuming to process. The theory of SOC applied to calving fronts is promising and opens up new discussions for the research community.
Massbalansprocesser för glaciärer är viktiga för att bestämma om isen drar sig tillbaka eller avancerar. Den mekaniska brytningen av isberg från glaciärer kallas kalvning. Kalvning är väldigt viktig för ett flertal glaciärers massbalans, exempelvis för landisen på Antarktis och glaciärer i Arktis. Ny forskning visar att kalvande glaciärfronter alltid försöker befinna sig i ett kritiskt läge, liknande ett så kallat Self-Organized Critical (SOC) system. Detta kan liknas vid hur en sandhög försöker befinna sig vid sin kritiska sluttningsvinkel när ett konstant flöde av sandkorn adderas. Adderandet av sandkorn kan jämföras med hur externa förhållanden, så som temperatur och tidvatten, ändras. När dessa värden ändras med tid så kommer fronten kalva, mycket likt hur sandhögen rasar när sandkorn tillförs. Externa förhållanden kommer alltså styra om glaciären kalvar eller inte, och när.En time-lapse-kamera installerades framför Tunabreen, en tidvatten glaciär på Svalbard, under Augusti-September, 2014. Bilderna över Tunabreens kalvningsfront, som varade över en 11-dagars period, användes för att ta ut varje enskild kalvingshändelse. Denna data jämfördes sedan med tidvatten, temperatur, luftfuktighet, atmosfäriskt tryck, vindhastighet och vindriktning. Resultaten jämfördes även med de förhållanden som visades i den nya studien som beskrevs tidigare.Resultaten är blandade. När tidvattnets amplitud var större än 1 meter så följer kalvningen tidvattnets mönster, men detta avtar när amplituden är mindre. Temperaturen visar viss korrelation, men endast för kortare perioder. Då temperaturens förhållande till kalvningen inte följer under de högsta och lägsta värden som fanns så bedöms temperaturen ha låg trovärdighet som kontrollerande faktor. Luftfuktighet, atmosfäriskt tryck, vindhastighet och vindriktning visar låg, till ingen, korrelation med kalvning. Storleksfördelningen av fragment och kalvningshastigheten har god korrelation med forskningen kring SOC, resultaten hjälper till att bekräfta denna teori. Time-lapse-fotografi bedöms som en bra metod för att observera kalvningsfronter, men har ett flertal problem som relaterar till det lokala vädret.Längre tidsperioder behövs för att bedöma om förhållanden stämmer på lång sikt. Data är svår att förvärva och tidskrävande att behandla. SOC stämmer bra in på kalvningsfronter vilket öppnar upp nya diskussioner inom forskningsvärlden.

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Mahmoodi, Korosh. "Emergence of Cooperation and Homeodynamics as a Result of Self Organized Temporal Criticality: From Biology to Physics". Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1248467/.

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This dissertation is an attempt at establishing a bridge between biology and physics leading naturally from the field of phase transitions in physics to the cooperative nature of living systems. We show that this aim can be realized by supplementing the current field of evolutionary game theory with a new form of self-organized temporal criticality. In the case of ordinary criticality, the units of a system choosing either cooperation or defection under the influence of the choices done by their nearest neighbors, undergo a significant change of behavior when the intensity of social influence has a critical value. At criticality, the behavior of the individual units is correlated with that of all other units, in addition to the behavior of the nearest neighbors. The spontaneous transition to criticality of this work is realized as follows: the units change their behavior (defection or cooperation) under the social influence of their nearest neighbors and update the intensity of their social influence spontaneously by the feedback they get from the payoffs of the game (environment). If units, which are selfish, get higher benefit with respect to their previous play, they increase their interest to interact with other units and vice versa. Doing this, the behavior of single units and the whole system spontaneously evolve towards criticality, thereby realizing a global behavior favoring cooperation. In the case when the interacting units are oscillators with their own periodicity, homeodynamics concerns, the individual payoff is the synchronization with the nearest neighbors (i.e., lowering the energy of the system), the spontaneous transition to criticality generates fluctuations characterized by the joint action of periodicity and crucial events of the same kind as those revealed by the current analysis of the dynamics of the brain. This result is expected to explain the efficiency of enzyme catalyzers, on the basis of a new non-equilibrium statistical physics. We argue that the results obtained apply to sociological and psychological systems as well as to elementary biological systems.

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Costa, Ariadne de Andrade. "Quasi-criticalidade auto-organizada em avalanches neuronais". Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/59/59135/tde-17112011-204509/.

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Experimentos têm revelado que redes de neurônios, tanto in vitro como in vivo, mantêm atividade descrita por avalanches e se organizam em um estado crítico no qual essas avalanches são distribuídas de acordo com leis de potência. Mostramos no presente trabalho que um modelo de rede de elementos excitáveis com sinapses dinâ- micas é capaz de exibir criticalidade auto-organizada para ampla região do espaço de parâmetros. Nossos resultados estão de acordo com outros estudos que indicam que a depressão sináptica de curto prazo constitui mecanismo suciente para produzir criticalidade em avalanches neuronais. No entanto, segundo diversos pesquisadores, embora o ajuste de parâmetros seja grosso para que haja criticalidade no modelo, é mais preciso dizer que o sistema não apresenta criticalidade auto-organizada genu ína, mas sim quasi-criticalidade auto-organizada, como os demais modelos não conservativos presentes na literatura.
Experiments have shown that neuronal networks, both in vitro and in vivo, maintain activity described by avalanches and they are organized into a critical state in which these avalanches are distributed according to power laws. We have demonstrated that a model based on a network of excitable elements with dynamical synapses is able to exhibit self-organized criticality for a wide range of the parameter\'s space. Our results are consistent with other studies that suggest short-term synaptic depression is enough to produce criticality in neuronal avalanches. However, according to several researchers, in spite of the tuning to be gross to ensure that there is criticality in the model, it is more accurate do not say that the system presents genuine self-organized criticality, but self-organized quasi-criticality as the other non-conservative models in the literature.

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Wu, Jingwei. "Open Source Software Evolution and Its Dynamics". Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/1095.

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This thesis undertakes an empirical study of software evolution by analyzing open source software (OSS) systems. The main purpose is to aid in understanding OSS evolution. The work centers on collecting large quantities of structural data cost-effectively and analyzing such data to understand software evolution dynamics (the mechanisms and causes of change or growth).

We propose a multipurpose systematic approach to extracting program facts (e. g. , function calls). This approach is supported by a suite of C and C++ program extractors, which cover different steps in the program build process and handle both source and binary code. We present several heuristics to link facts extracted from individual files into a combined system model of reasonable accuracy. We extract historical sequences of system models to aid software evolution analysis.

We propose that software evolution can be viewed as Punctuated Equilibrium (i. e. , long periods of small changes interrupted occasionally by large avalanche changes). We develop two approaches to study such dynamical behavior. One approach uses the evolution spectrograph to visualize file level changes to the implemented system structure. The other approach relies on automated software clustering techniques to recover system design changes. We discuss lessons learned from using these approaches.

We present a new perspective on software evolution dynamics. From this perspective, an evolving software system responds to external events (e. g. , new functional requirements) according to Self-Organized Criticality (SOC). The SOC dynamics is characterized by the following: (1) the probability distribution of change sizes is a power law; and (2) the time series of change exhibits long range correlations with power law behavior. We present empirical evidence that SOC occurs in open source software systems.

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Russo, Elena Tea. "Fluctuation properties in random walks on networks and simple integrate and fire models". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/9565/.

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In questa tesi si è studiato l’insorgere di eventi critici in un semplice modello neurale del tipo Integrate and Fire, basato su processi dinamici stocastici markoviani definiti su una rete. Il segnale neurale elettrico è stato modellato da un flusso di particelle. Si è concentrata l’attenzione sulla fase transiente del sistema, cercando di identificare fenomeni simili alla sincronizzazione neurale, la quale può essere considerata un evento critico. Sono state studiate reti particolarmente semplici, trovando che il modello proposto ha la capacità di produrre effetti "a cascata" nell’attività neurale, dovuti a Self Organized Criticality (auto organizzazione del sistema in stati instabili); questi effetti non vengono invece osservati in Random Walks sulle stesse reti. Si è visto che un piccolo stimolo random è capace di generare nell’attività della rete delle fluttuazioni notevoli, in particolar modo se il sistema si trova in una fase al limite dell’equilibrio. I picchi di attività così rilevati sono stati interpretati come valanghe di segnale neurale, fenomeno riconducibile alla sincronizzazione.

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Libri sul tema "Self-organized criticality"

1

Aschwanden, Markus. Self-Organized Criticality in Astrophysics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-15001-2.

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Hergarten, Stefan. Self-Organized Criticality in Earth Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04390-5.

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Newman, M. E. J. Self-organized criticality, evolution, and extinction. Ithaca, N.Y: Cornell Theory Center, Cornell University, 1996.

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Selvam, Amujuri Mary. Self-organized Criticality and Predictability in Atmospheric Flows. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54546-2.

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5

Bak, P. How nature works: The science of self-organized criticality. New York, NY, USA: Copernicus, 1996.

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Bak, Per. How Nature Works: The Science of Self-Organized Criticality. S.l: Springer, 1996.

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Jensen, Henrik Jeldtoft. Self-organized criticality: Emergent complex behavior in physical and biological systems. Cambridge: Cambridge University Press, 1998.

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Vincent, Jansen, a cura di. Population biology and criticality: From critical birth-death processes to self-organized criticality in mutation pathogen systems. London: Imperial College Press, 2011.

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service), SpringerLink (Online, a cura di. Self-Organized Criticality in Astrophysics: The Statistics of Nonlinear Processes in the Universe. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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Manna, Subhrangshu Sekhar, Attilio L. Stella, Peter Grassberger e Ronald Dickman, a cura di. Self-Organized Criticality, Three Decades Later. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-88974-219-6.

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Capitoli di libri sul tema "Self-organized criticality"

1

Sornette, Didier. "Self-Organized Criticality". In Critical Phenomena in Natural Sciences, 321–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-04174-1_15.

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Hergarten, Stefan. "Self-Organized Criticality". In Self-Organized Criticality in Earth Systems, 87–108. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04390-5_5.

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Do, Anne-Ly Jabusch, e Thilo Gross. "Self-organized criticality". In Self-Organization in Continuous Adaptive Networks, 53–73. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003339458-4.

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Aschwanden, Markus. "Self-Organized Criticality Phenomena". In Self-Organized Criticality in Astrophysics, 1–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15001-2_1.

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Bak, Per, e Michael Creutz. "Fractals and Self-Organized Criticality". In Fractals in Science, 27–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-662-11777-4_2.

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Bak, Per, e Michael Creutz. "Fractals and Self-Organized Criticality". In Fractals in Science, 27–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-77953-4_2.

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Aschwanden, Markus. "SOC-Like Models". In Self-Organized Criticality in Astrophysics, 321–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15001-2_10.

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Aschwanden, Markus. "Numerical SOC Models". In Self-Organized Criticality in Astrophysics, 37–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15001-2_2.

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Aschwanden, Markus. "Analytical SOC Models". In Self-Organized Criticality in Astrophysics, 83–110. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15001-2_3.

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Aschwanden, Markus. "Statistics of Random Processes". In Self-Organized Criticality in Astrophysics, 111–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15001-2_4.

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Atti di convegni sul tema "Self-organized criticality"

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Caruso, Filippo, Alessandro Pluchino, Vito Latora, Andrea Rapisarda, Sergio Vinciguerra, Sumiyoshi Abe, Hans Herrmann, Piero Quarati, Andrea Rapisarda e Constantino Tsallis. "Self-Organized Criticality and earthquakes". In COMPLEXITY, METASTABILITY, AND NONEXTENSIVITY: An International Conference. AIP, 2007. http://dx.doi.org/10.1063/1.2828746.

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Stollenwerk, Nico. "Self-organized criticality in human epidemiology". In MODELING COOPERATIVE BEHAVIOR IN THE SOCIAL SCIENCES. AIP, 2005. http://dx.doi.org/10.1063/1.2008613.

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Fernandes, Carlos Miguel, Juan Merelo, Agostinho Rosa e Francisco Fernández. "Particle swarm with self-organized criticality". In the fourteenth international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2330784.2330950.

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Abramenko, V. I. "SELF-ORGANIZED CRITICALITY OF SOLAR MAGNETISM". In All-Russia Conference on Solar and Solar-Terrestrial Physics. The Central Astronomical Observatory of the Russian Academy of Sciences at Pulkovo, 2019. http://dx.doi.org/10.31725/0552-5829-2019-3-6.

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Makarenkov, Vladimir I., e A. B. Kirillov. "Self-organized criticality in neural networks". In SPIE Proceedings, a cura di Steven K. Rogers. SPIE, 1991. http://dx.doi.org/10.1117/12.45022.

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Merelo, J. J., Pedro A. Castillo, Antonio M. Mora, Mario García-Valdez, Carlos Cotta e Carlos Fernandes. "Self-organized criticality in code repositories". In Proceedings of the 14th European Conference on Artificial Life ECAL 2017. Cambridge, MA: MIT Press, 2017. http://dx.doi.org/10.7551/ecal_a_087.

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Yang, Chun-xia, Shi-mei Jiang, Tao Zhou, Bing-hong Wang e Pei-ling Zhou. "Self-organized Criticality of Computer Network Traffic". In 2006 International Conference on Communications, Circuits and Systems. IEEE, 2006. http://dx.doi.org/10.1109/icccas.2006.285010.

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Dobson, I. "HICSS minitrack session on self-organized criticality". In 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the. IEEE, 2003. http://dx.doi.org/10.1109/hicss.2003.1173907.

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Quan Lu, Jing Chen e Xiaopeng Yu. "Co-evolution of agents in self-organized criticality". In Proceedings of ICSSSM '05. 2005 International Conference on Services Systems and Services Management, 2005. IEEE, 2005. http://dx.doi.org/10.1109/icsssm.2005.1500141.

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Dhar, Deepak. "The abelian sandpile model of self-organized criticality". In Computer-aided statistical physics. AIP, 1992. http://dx.doi.org/10.1063/1.41946.

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Rapporti di organizzazioni sul tema "Self-organized criticality"

1

Glazier, J. A. Fingering Instabilities, Collapse, Avalanches and Self-Organized Criticality in Liquid Foams. Office of Scientific and Technical Information (OSTI), novembre 2002. http://dx.doi.org/10.2172/837077.

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Krommes, J. A. Self-organized criticality, long-time correlations, and the standard transport paradigm. Office of Scientific and Technical Information (OSTI), febbraio 2000. http://dx.doi.org/10.2172/751200.

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Krommes, J. A. Recent results on analytical plasma turbulence theory: Realizability, intermittency, submarginal turbulence, and self-organized criticality. Office of Scientific and Technical Information (OSTI), gennaio 2000. http://dx.doi.org/10.2172/750257.

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Bak, Peter, Kan Chen, Jose Scheinkman e Michael Woodford. Aggregate Fluctuations from Independent Sectoral Shocks: Self-Organized Criticality in a Model of Production and Inventory Dynamics. Cambridge, MA: National Bureau of Economic Research, dicembre 1992. http://dx.doi.org/10.3386/w4241.

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Krommes, J. A., e M. Ottaviani. Long-time tails do not necessarily imply self-organized criticality or the breakdown of the standard transport paradigm. Office of Scientific and Technical Information (OSTI), gennaio 2000. http://dx.doi.org/10.2172/750264.

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