Research on Self-Organized Evolution of P2P Network Structure

2006 ◽  
Author(s):  
Dong Pan ◽  
Zhu Peidong
Keyword(s):  
Network Structure ◽  
P2p Network ◽  
Self Organized

The Ordered Network Structure of M≥8 Great Earthquakes and their Prediction in Mainland China

2012 ◽  
Vol 67 (5) ◽  
pp. 308-316
Author(s):  
Kepei Men
Keyword(s):  
Network Structure ◽  
Mainland China ◽  
Practical Method ◽  
Great Earthquake ◽  
Self Organized ◽  
Great Earthquakes ◽  
Chinese Characteristics ◽  
Unique Effect ◽  
Network Feature ◽  
Long Term Prediction

China is one of the countries which have the most earthquake disasters in the world. A total of 23 M ≥ 8 earthquakes occurred in Mainland China from 1303 to 2010. The seismic activity of M ≥ 8 earthquakes has had an obvious self-organized orderliness. The main ordered values are 252~258 a, 108~112 a, 94~98 a, 44~47 a, 24~25 a, 16~19 a, and 11~14 a. According to the information forecasting theory of Wen-Bo Weng and combining ordered analysis with complex network technology, we build an informational ordered network structure of M ≥ 8 great earthquakes in Mainland China and try to explore the practical method for M ≥ 8 great earthquake prediction with Chinese characteristics. In this paper, we have summarized the prediction research on two great earthquakes (the 2001 Kunlunshan M8.1 and the 2008 Wenchuan M8.0 earthquake) during the beginning of the 21st century in western Mainland China. At last, with the method of ordered network structure, we present a new prediction opinion: the future M ≥ 8 great earthquakes will happen in 2026 and 2065 pre and post in Mainland China. The results show that a M ≥ 8 great earthquake could be predicted and the network feature is the formation mechanism of great earthquakes. The ordered network method has a unique effect on moderate term and long term prediction for M ≥ 8 great earthquakes.

The Ordered Network Structure of M≥8 Earthquakes and its Prediction for the Ordered Pair Great Earthquakes in Mainland China

2014 ◽  
Vol 69 (3-4) ◽  
pp. 145-154 ◽  
Author(s):  
Ke-Pei Men ◽  
Kai Zhao
Keyword(s):  
Network Structure ◽  
Mainland China ◽  
Time Interval ◽  
Self Organized ◽  
Great Earthquakes ◽  
New Information ◽  
History Of ◽  
Rare Earthquake ◽  
2D And 3D ◽  
Forecasting Theory

According to the statistical data, a total of 23 M ≥ 8 earthquakes occurred in Mainland China from 1303 to 2012. The seismic activity of M ≥ 8 earthquakes has showed an obvious self-organized orderliness. It should be remarked especially that there were three ordered pairs of M ≥8 earthquakes occurred in West China during 1902 - 2001, of which the time interval in each pair of two earthquakes was four years. This is a unique and rare earthquake example in earthquake history of China and the world. In the guidance of the information forecasting theory of Wen-Bo Weng, based on previous research results, combining ordered analysis with complex network technology, this paper focuses on the summary of the ordered network structure of M ≥ 8 earthquakes, supplements new information, constructs and further optimizes the 2D- and 3D-ordered network structure of M ≥ 8 earthquakes to make prediction research. At last, a new prediction opinion is presented that the future ordered pair of great earthquakes will probably occur around 2022 and 2026 in Mainland China.

scholarly journals Self-Organized Micro-Honeycomb Network Structure of Single-Walled Carbon Nanotubes for Photovoltaic Devices

2013 ◽  
Author(s):  
Shigeo Maruyama ◽  
Kehang Cui ◽  
Takaaki Chiba ◽  
Erik Einarsson ◽  
Shohei Chiashi
Keyword(s):  
Carbon Nanotubes ◽  
Solar Cells ◽  
Solar Cell ◽  
Water Vapor ◽  
Network Structure ◽  
Single Walled Carbon Nanotubes ◽  
Self Organized ◽  
Vertically Aligned ◽  
Walled Carbon Nanotubes ◽  
Honeycomb Network

Single-walled carbon nanotubes (SWNTs) are expected to be a promising nanomaterial because of their outstanding electronic, mechanical, and thermal properties. For macroscopic device applications, an assembly of SWNTs is a critical issue. We propose a self-organized micro-honeycomb network structure of SWNTs obtained by water vapor treatment of as-synthesized vertically-aligned SWNTs (VA-SWNT) for solar cell devices with higher performance. The micro-honeycomb structure was realized by simply exposing VA-SWNT to water vapor and drying in ambient condition. Honeycomb cell walls consist of capillary-aggregated vertically aligned SWNTs with heavily bundled top part. Within each cell, collapsed spaghetti-like SWNTs make contact to the substrate. The SWNT/n-Si heterojunction solar cell was built by placing the micro-honeycomb SWNTs network film on top of the substrate which has a 3 mm × 3 mm bare n-type silicon contact window in the center. The contact window is surrounded by SiO2 as insulating layer and Pt as electrode. Our preliminary tests showed that optimal photovoltaic conversion efficiency (PCE) under AM1.5 was 5.91%, with the fill factor of 72%. The open-circuit voltage and short-circuit current are 0.53V and 15.5 mA/cm2, respectively. This showed a substantial improvement compared with heterojunction solar cells using spaghetti-like SWNTs. Furthermore, the superior performance of dye-sensitized solar cells with the micro-honeycomb SWNTs was demonstrated.

A Network Model of P2P Extending to Private Network

2014 ◽  
Vol 513-517 ◽  
pp. 2464-2467
Author(s):  
Wen Hao Wang ◽  
Miao Zhou
Keyword(s):  
Network Model ◽  
P2p Network ◽  
Research Subject ◽  
Shared Resource ◽  
Network Nodes ◽  
Public Network ◽  
Organization Mode ◽  
Self Organized ◽  
Internal Network ◽  
Private Network

With the expansion of private network scale, the shared resource is very rich in its internal. How does the P2P network extend to the private network, and conduct good integration of the resources becomes a much valuable research subject. The paper puts forward a new P2P network model, and describes the network organization mode, the cooperation relations between the nodes, and node join and exit algorithm in detail. The model has highly self-organized and scalability in private internal network; it does not need public network nodes involved in.

scholarly journals Self-Organized Structuring of Recurrent Neuronal Networks for Reliable Information Transmission

Biology ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 577
Author(s):  
Daniel Miner ◽  
Florentin Wörgötter ◽  
Christian Tetzlaff ◽  
Michael Fauth
Keyword(s):  
Long Range ◽  
Network Structure ◽  
Network Architecture ◽  
Metabolic Cost ◽  
Network Activity ◽  
Self Organization ◽  
Stimulus Information ◽  
Hierarchical Network ◽  
Self Organized ◽  
Input And Output

Our brains process information using a layered hierarchical network architecture, with abundant connections within each layer and sparse long-range connections between layers. As these long-range connections are mostly unchanged after development, each layer has to locally self-organize in response to new inputs to enable information routing between the sparse in- and output connections. Here we demonstrate that this can be achieved by a well-established model of cortical self-organization based on a well-orchestrated interplay between several plasticity processes. After this self-organization, stimuli conveyed by sparse inputs can be rapidly read out from a layer using only very few long-range connections. To achieve this information routing, the neurons that are stimulated form feed-forward projections into the unstimulated parts of the same layer and get more neurons to represent the stimulus. Hereby, the plasticity processes ensure that each neuron only receives projections from and responds to only one stimulus such that the network is partitioned into parts with different preferred stimuli. Along this line, we show that the relation between the network activity and connectivity self-organizes into a biologically plausible regime. Finally, we argue how the emerging connectivity may minimize the metabolic cost for maintaining a network structure that rapidly transmits stimulus information despite sparse input and output connectivity.

An Efficient and Reliable Anonymous Solution for a Self-organized P2P Network

2007 ◽  
pp. 25-36
Author(s):  
J. P. Muñoz-Gea ◽  
J. Malgosa-Sanahuja ◽  
P. Manzanares-Lopez ◽  
J. C. Sanchez-Aarnoutse ◽  
J. Garcia-Haro
Keyword(s):  
P2p Network ◽  
Self Organized
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