Analyses of aggregate fluctuations of firm production network based on the self-organized criticality model

2016 ◽  
Vol 13 (2) ◽  
pp. 383-396 ◽  
Author(s):  
Hiroyasu Inoue
Keyword(s):  
The Self ◽  
Production Network ◽  
Aggregate Fluctuations ◽  
Self Organized ◽  
Self Organized Criticality

Problem behavior in autism spectrum disorders: A paradigmatic self-organized perspective of network structures

2019 ◽  
Vol 42 ◽  
Author(s):  
Lucio Tonello ◽  
Luca Giacobbi ◽  
Alberto Pettenon ◽  
Alessandro Scuotto ◽  
Massimo Cocchi ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Problem Behaviors ◽  
Autism Spectrum ◽  
The Self ◽  
Network Structures ◽  
Self Organized ◽  
Critical Equilibrium ◽  
Self Organized Criticality ◽  
Acute Agitation ◽  
Spectrum Disorders

AbstractAutism spectrum disorder (ASD) subjects can present temporary behaviors of acute agitation and aggressiveness, named problem behaviors. They have been shown to be consistent with the self-organized criticality (SOC), a model wherein occasionally occurring “catastrophic events” are necessary in order to maintain a self-organized “critical equilibrium.” The SOC can represent the psychopathology network structures and additionally suggests that they can be considered as self-organized systems.

scholarly journals Transition from Self-Organized Criticality into Self-Organization during Sliding Si3N4 Balls against Nanocrystalline Diamond Films

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1055
Author(s):  
Bogatov ◽  
Podgursky ◽  
Vagiström ◽  
Yashin ◽  
Shaikh ◽  
...  
Keyword(s):  
Friction Force ◽  
Power Law ◽  
Early Stage ◽  
Nanocrystalline Diamond ◽  
The Self ◽  
Self Organization ◽  
Power Law Distribution ◽  
Reciprocating Sliding ◽  
Self Organized ◽  
Self Organized Criticality

The paper investigates the variation of friction force (Fx) during reciprocating sliding tests on nanocrystalline diamond (NCD) films. The analysis of the friction behavior during the run-in period is the focus of the study. The NCD films were grown using microwave plasma-enhanced chemical vapor deposition (MW-PECVD) on single-crystalline diamond SCD(110) substrates. Reciprocating sliding tests were conducted under 500 and 2000 g of normal load using Si3N4 balls as a counter body. The friction force permanently varies during the test, namely Fx value can locally increase or decrease in each cycle of sliding. The distribution of friction force drops (dFx) was extracted from the experimental data using a specially developed program. The analysis revealed a power-law distribution f-µ of dFx for the early stage of the run-in with the exponent value (µ) in the range from 0.6 to 2.9. In addition, the frequency power spectrum of Fx time series follows power-law distribution f-α with α value in the range of 1.0–2.0, with the highest values (1.6–2.0) for the initial stage of the run-in. No power-law distribution of dFx was found for the later stage of the run-in and the steady-state periods of sliding with the exception for periods where a relatively extended decrease of coefficient of friction (COF) was observed. The asperity interlocking leads to the stick-slip like sliding at the early stage of the run-in. This tribological behavior can be related to the self-organized criticality (SOC). The emergence of dissipative structures at the later stages of the run-in, namely the formation of ripples, carbonaceous tribolayer, etc., can be associated with the self-organization (SO).

scholarly journals Research on MAS-Based Supply Chain Resilience and Its Self-Organized Criticality

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Liang Geng ◽  
Renbin Xiao ◽  
Xing Xu
Keyword(s):  
Supply Chain ◽  
Fitness Function ◽  
The Self ◽  
Self Organization ◽  
Neighborhood Structure ◽  
Supply Chain System ◽  
Supply Chain Resilience ◽  
Self Organized ◽  
Agglomeration Effect ◽  
Self Organized Criticality

Building resilient supply chain is an effective way to deal with uncertain risks. First, by analyzing the self-organization of supply chain, the supply chain resilience is described as a macroscopic property that generates from self-organizing behavior of each enterprise on the microlevel. Second, a MAS-based supply chain resilience model is established and its local fitness function, neighborhood structure, and interaction rules that are applicable to supply chain system are designed through viewing the enterprise as an agent. Finally, with the help of a case, we find that there is an agglomeration effect and a SOC characteristic in supply chain and the evolution of supply chain is controlled by parameters of MAS. Managers can control the supply chain within the resilient range and choose a good balance between interest and risk by controlling enterprises’ behavior.

scholarly journals SELF-ORGANIZED CRITICAL BEHAVIOR: THE EVOLUTION OF FROZEN SPIN NETWORKS MODEL IN QUANTUM GRAVITY

2008 ◽  
Vol 23 (24) ◽  
pp. 3891-3899 ◽  
Author(s):  
JIAN-ZHEN CHEN ◽  
JIAN-YANG ZHU
Keyword(s):  
Quantum Gravity ◽  
The Self ◽  
Spin Networks ◽  
Spin Network ◽  
Underlying Graph ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Propagation Rule ◽  
First Time ◽  
The Universe

In quantum gravity, we study the evolution of a two-dimensional planar open frozen spin network, in which the color (i.e. the twice spin of an edge) labeling edge changes but the underlying graph remains fixed. The mainly considered evolution rule, the random edge model, is depending on choosing an edge randomly and changing the color of it by an even integer. Since the change of color generally violate the gauge invariance conditions imposed on the system, detailed propagation rule is needed and it can be defined in many ways. Here, we provided one new propagation rule, in which the involved even integer is not a constant one as in previous works, but changeable with certain probability. In random edge model, we do find the evolution of the system under the propagation rule exhibits power-law behavior, which is suggestive of the self-organized criticality (SOC), and it is the first time to verify the SOC behavior in such evolution model for the frozen spin network. Furthermore, the increase of the average color of the spin network in time can show the nature of inflation for the universe.

scholarly journals Numerical statistical analysis on self-organizing behavior of microfracturing events in rock failure

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771876899 ◽  
Author(s):  
Houquan Zhang ◽  
Hao Shi ◽  
Yu Wu ◽  
Hai Pu
Keyword(s):  
Long Range ◽  
Failure Process ◽  
Rock Failure ◽  
The Self ◽  
In Situ Monitoring ◽  
Power Exponent ◽  
Self Organized ◽  
Rescaled Range Analysis ◽  
Rock Failure Process ◽  
Self Organized Criticality

Current experimental investigations on microfracturing (or acoustic emission) events mainly focus on their location and distribution. A new function in rock failure process analysis (RFPA2D) code was developed to capture the size and number of damage element groups in each loading step. The rock failure process evolving from the initiation, propagation, and nucleation of microcracks was visually simulated by RFPA2D in this research. Based on the newly developed function, the statistical quantitative analysis of microfracturing events in rock was effectively conducted. The results show that microfracturing (failed element) events in the whole failure process accord with negative power law distribution, showing fractal features. When approaching a self-organized criticality state, the power exponent does not vary drastically, which ranges around 1.5 approximately. The power exponent decreases correspondingly as the stress increases. Through the analysis of the frequency and size of damaged element groups by rescaled range analysis method, the time series of microfracturing events exhibits the self-similar scale-invariant properties. Through the analysis by the correlation function method, the absolute value of the self-correlation coefficient of microfracturing sequence demonstrates a subsequent precursory increase after a long time delay, exhibiting long-range correlation characteristics. These fractal configuration and long-range correlations are two fingerprints of self-organized criticality, which indicates the occurrence of self-organized criticality in rock failure. Compared with the limited in situ monitoring data, this simulation can supply more sufficient information for the prediction of unstable failure and good understanding of the failure mechanism.

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