On the self-organizing process of large scale shear flows

2013 ◽  
Vol 20 (9) ◽  
pp. 092306 ◽  
Author(s):  
Andrew P. L. Newton ◽  
Eun-jin Kim ◽  
Han-Li Liu
Keyword(s):  
Large Scale ◽  
Shear Flows ◽  
The Self ◽  
Scale Shear ◽  
Self Organizing ◽  
Organizing Process

scholarly journals Study on the Self–Growth of the Internet Communication System

2011 ◽  
Vol 9 (2) ◽  
pp. 535-542
Author(s):  
Yun-Feng Xia
Keyword(s):  
Communication System ◽  
Large Scale ◽  
The Self ◽  
The Internet ◽  
Internet Communication ◽  
Information Communication ◽  
Internet Users ◽  
Evolving System ◽  
Tion System ◽  
Self Organizing

In this essay, I mainly discuss the self-organizing property of the Internet communication system. As an important part of the human information communication system, Internet communication has progressively become a system with large scale, complex constructions, and perfect functions through the complicated interactions among many sub-systems and their elements. In this process, which is mainly promoted by Internet users, the self-growth of the Internet communica- tion system not only increases the amount of its sub-systems and its elements, it also strengthens its constructions and functions. At the same time, the self-growth of the Internet communication system indicates that the system is an evolving system with self-organizing property.

scholarly journals Study on the Self–Growth of the Internet Communication System

2011 ◽  
Vol 9 (2) ◽  
pp. 535-542
Author(s):  
Yun-Feng Xia
Keyword(s):  
Communication System ◽  
Large Scale ◽  
The Self ◽  
The Internet ◽  
Internet Communication ◽  
Information Communication ◽  
Internet Users ◽  
Evolving System ◽  
Tion System ◽  
Self Organizing

In this essay, I mainly discuss the self-organizing property of the Internet communication system. As an important part of the human information communication system, Internet communication has progressively become a system with large scale, complex constructions, and perfect functions through the complicated interactions among many sub-systems and their elements. In this process, which is mainly promoted by Internet users, the self-growth of the Internet communica- tion system not only increases the amount of its sub-systems and its elements, it also strengthens its constructions and functions. At the same time, the self-growth of the Internet communication system indicates that the system is an evolving system with self-organizing property.

Pèlerinages barrésiens

2013 ◽  
pp. 116-123
Author(s):  
Claire Bompaire-Evesque
Keyword(s):  
Large Scale ◽  
The Self ◽  
Joan Of Arc ◽  
The Third ◽  
National Importance ◽  
The Earth ◽  
Third Stage ◽  
The Dead

This article is a inquiry about how Barrès (1862-1923) handles the religious rite of pilgrimage. Barrès stages in his writings three successive forms of pilgrimage, revealing what is sacred to him at different times. The pilgrimage to a museum or to the birthplace of an artist is typical for the egotism and the humanism of the young Barrès, expressed in the Cult of the Self (1888-1891). After his conversion to nationalism, Barrès tries to unite the sons of France and to instill in them a solemn reverence for “the earth and the dead” ; for that purpose he encourages in French Amities (1903) pilgrimages to historical places of national importance (battlefields; birthplace of Joan of Arc), building what Nora later called the Realms of Memory. The third stage of Barrès’ intellectual evolution is exemplified by The Sacred Hill (1913). In this book the writer celebrates the places where “the Spirit blows”, and proves open to a large scale of spiritual forces, reaching back to paganism and forward to integrative syncretism, which aims at unifying “the entire realm of the sacred”.

scholarly journals An Intelligent Evaluation Method to Analyze the Competitiveness of Airlines

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Jun Zhao ◽  
Xumei Chen
Keyword(s):  
Neural Network ◽  
Prior Knowledge ◽  
Evaluation Method ◽  
Standard Sample ◽  
Reference Value ◽  
The Self ◽  
Index Data ◽  
Som Neural Network ◽  
Simulation Results ◽  
Self Organizing

An intelligent evaluation method is presented to analyze the competitiveness of airlines. From the perspective of safety, service, and normality, we establish the competitiveness indexes of traffic rights and the standard sample base. The self-organizing mapping (SOM) neural network is utilized to self-organize and self-learn the samples in the state of no supervision and prior knowledge. The training steps of high convergence speed and high clustering accuracy are determined based on the multistep setting. The typical airlines index data are utilized to verify the effect of the self-organizing mapping neural network on the airline competitiveness analysis. The simulation results show that the self-organizing mapping neural network can accurately and effectively classify and evaluate the competitiveness of airlines, and the results have important reference value for the allocation of traffic rights resources.

scholarly journals Self-exciting multifractional processes

2021 ◽  
Vol 58 (1) ◽  
pp. 22-41
Author(s):  
Fabian A. Harang ◽  
Marc Lagunas-Merino ◽  
Salvador Ortiz-Latorre
Keyword(s):  
Stochastic Process ◽  
Brownian Motion ◽  
Rate Of Convergence ◽  
Existence And Uniqueness ◽  
Volterra Equation ◽  
The Self ◽  
The Past ◽  
Stochastic Volterra Equation ◽  
Multifractional Brownian Motion ◽  
Self Organizing

AbstractWe propose a new multifractional stochastic process which allows for self-exciting behavior, similar to what can be seen for example in earthquakes and other self-organizing phenomena. The process can be seen as an extension of a multifractional Brownian motion, where the Hurst function is dependent on the past of the process. We define this by means of a stochastic Volterra equation, and we prove existence and uniqueness of this equation, as well as giving bounds on the p-order moments, for all $p\geq1$. We show convergence of an Euler–Maruyama scheme for the process, and also give the rate of convergence, which is dependent on the self-exciting dynamics of the process. Moreover, we discuss various applications of this process, and give examples of different functions to model self-exciting behavior.

scholarly journals The Spread of the COVID-19 Outbreak in Brazil: An Overview by Kohonen Self-Organizing Map Networks

Medicina ◽  
2021 ◽  
Vol 57 (3) ◽  
pp. 235
Author(s):  
Diego Galvan ◽  
Luciane Effting ◽  
Hágata Cremasco ◽  
Carlos Adam Conte-Junior
Keyword(s):  
The Self ◽  
Self Organizing Map ◽  
Virus Spread ◽  
Self Organizing Maps ◽  
The North ◽  
Som Clustering ◽  
Unsupervised Neural Networks ◽  
Mining Tools ◽  
Temporal Spread ◽  
Self Organizing

Background and objective: In the current pandemic scenario, data mining tools are fundamental to evaluate the measures adopted to contain the spread of COVID-19. In this study, unsupervised neural networks of the Self-Organizing Maps (SOM) type were used to assess the spatial and temporal spread of COVID-19 in Brazil, according to the number of cases and deaths in regions, states, and cities. Materials and methods: The SOM applied in this context does not evaluate which measures applied have helped contain the spread of the disease, but these datasets represent the repercussions of the country’s measures, which were implemented to contain the virus’ spread. Results: This approach demonstrated that the spread of the disease in Brazil does not have a standard behavior, changing according to the region, state, or city. The analyses showed that cities and states in the north and northeast regions of the country were the most affected by the disease, with the highest number of cases and deaths registered per 100,000 inhabitants. Conclusions: The SOM clustering was able to spatially group cities, states, and regions according to their coronavirus cases, with similar behavior. Thus, it is possible to benefit from the use of similar strategies to deal with the virus’ spread in these cities, states, and regions.

scholarly journals Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Adeoluwa Akande ◽  
Ana Cristina Costa ◽  
Jorge Mateu ◽  
Roberto Henriques
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Northern Region ◽  
Extreme Weather Events ◽  
Self Organizing Map ◽  
Spatial And Temporal Patterns ◽  
Self Organizing Maps ◽  
The North ◽  
Precipitation Regimes ◽  
Self Organizing

The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.

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