Analysis and Visualization of Japanese Law Networks Based on Granular Computing -Visual Law: Visualization System of Japanese Law-

2010 ◽  
Vol 14 (2) ◽  
pp. 150-154
Author(s):  
Tetsuya Toyota ◽  
◽  
Hajime Nobuhara
Keyword(s):  
Network Structure ◽  
Granular Computing ◽  
Network Science ◽  
Closeness Centrality ◽  
Network Visualization ◽  
Hierarchical Network ◽  
Hierarchical Networks ◽  
Visualization System ◽  
The Hierarchical Structure ◽  
Japanese Law

In order to grasp a perspective of the over 7,000 laws in Japan, and to find the relationships between law and laws, a method of creating a hierarchical network of laws using granular computing, is proposed. The proposed method analyze hierarchical networks by using an index of network science such as degree distribution and closeness centrality. Furthermore, it visualizes the hierarchical structure within the setting of granular computing. Using the JAVA-based language ‘Prefuse,’ a law network visualization system ‘Visual Law’ is implemented, and it is confirmed that users can easily analyze/understand the law network structure using our proposal.

The Property of Hierarchical Structure in Manufacturing

2013 ◽  
Vol 748 ◽  
pp. 1188-1193
Author(s):  
Ying Xin Zhang ◽  
Chao Chen ◽  
Jian Mai Shi
Keyword(s):  
Complex Systems ◽  
Network Model ◽  
Hierarchical Structure ◽  
Real Life ◽  
Small World ◽  
Hierarchical Network ◽  
Hierarchical Networks ◽  
Scale Free ◽  
The Hierarchical Structure ◽  
Simulation Results

Hierarchical structure is one of the most ubiquitous structures in various networked complex systems. In order to investigate the properties of the hierarchical structure, a deterministic hierarchical network model is first proposed. The statistical properties of the constructed networks are also discussed. The simulation results prove that the artificial networks simultaneously possess the small-world and scale-free properties well. This may be useful in furthering study of the topology properties of the hierarchical networks in real life.

Network visualization system for computational chemistry

2003 ◽  
Vol 24 (13) ◽  
pp. 1678-1687
Author(s):  
Mikhail Kozhin ◽  
Ilya Yanov ◽  
Jerzy Leszczynski
Keyword(s):  
Computational Chemistry ◽  
Network Visualization ◽  
Visualization System

Cellulose as an Adhesive for the Synthesis of Carbon Aerogel with a 3D Hierarchical Network Structure for Capacitive Energy Storage

2019 ◽  
Vol 6 (9) ◽  
pp. 2586-2594 ◽  
Author(s):  
Tailong Cai ◽  
Liwen Kuang ◽  
Chao Wang ◽  
Chunde Jin ◽  
Zhe Wang ◽  
...  
Keyword(s):  
Energy Storage ◽  
Network Structure ◽  
Carbon Aerogel ◽  
Hierarchical Network ◽  
Capacitive Energy Storage

scholarly journals Network-driven differences in mobility and optimal transitions among automatable jobs

2019 ◽  
Vol 6 (7) ◽  
pp. 182124 ◽  
Author(s):  
Jordan D. Dworkin
Keyword(s):  
Network Structure ◽  
Potential Benefit ◽  
Network Science ◽  
Job Transitions ◽  
Job Growth ◽  
New Jobs

The potential for widespread job automation has become an important topic of discussion in recent years, and it is thought that many American workers may need to learn new skills or transition to new jobs to maintain stable positions in the workforce. Because workers’ existing skills may make such transitions more or less difficult, the likelihood of a given job being automated only tells part of the story. As such, this study uses network science and statistics to investigate the links between jobs that arise from their necessary skills, knowledge and abilities. The resulting network structure is found to enhance the burden of automation within some sectors while lessening the burden in others. Additionally, a model is proposed for quantifying the expected benefit of specific job transitions. Its optimization reveals that the consideration of shared skills yields better transition recommendations than automatability and job growth alone. Finally, the potential benefit of increasing individual skills is quantified, with respect to facilitating both job transitions and within-occupation skill redefinition. Broadly, this study presents a framework for measuring the links between jobs and demonstrates the importance of these links for understanding the complex effects of automation.

Random walk and first passage time on a weighted hierarchical network

2014 ◽  
Vol 25 (09) ◽  
pp. 1450037 ◽  
Author(s):  
Feng Zhu ◽  
Meifeng Dai ◽  
Yujuan Dong ◽  
Jie Liu
Keyword(s):  
Random Walk ◽  
First Passage Time ◽  
Passage Time ◽  
Scale Factor ◽  
Hierarchical Network ◽  
Self Similarity ◽  
First Passage ◽  
Hierarchical Networks ◽  
Average Value ◽  
Peripheral Node

This paper reports a weighted hierarchical network generated on the basis of self-similarity, in which each edge is assigned a different weight in the same scale. We studied two substantial properties of random walk: the first-passage time (FPT) between a hub node and a peripheral node and the FPT from a peripheral node to a local hub node over the network. Meanwhile, an analytical expression of the average sending time (AST) is deduced, which reflects the average value of FPT from a hub node to any other node. Our result shows that the AST from a hub node to any other node is related to the scale factor and the number of modules. We found that the AST grows sublinearly, linearly and superlinearly respectively with the network order, depending on the range of the scale factor. Our work may shed some light on revealing the diffusion process in hierarchical networks.

Research and Realization of Power System SVG 3D Render Engine Named PSSRE

2014 ◽  
Vol 1049-1050 ◽  
pp. 562-567
Author(s):  
Li Jie Pan ◽  
Yu Fang
Keyword(s):  
Virtual Reality ◽  
Power System ◽  
Network Visualization ◽  
Power Network ◽  
Simulation Environment ◽  
Grid Structure ◽  
Visualization System ◽  
Design And Implementation ◽  
The Poor ◽  
Representation Method

According to the problem of power network visualization system which has the poor effect in 2D style and the limitation of visual effect in 3D style, setting geographical SVG as research target, and introducing virtual reality platform as basic simulation environment, designing and realizing power system SVG 3D render engine named PSSRE. The design and implementation of parsing module and rendering module are analyzed as well as three-layer render architecture and representation method of layered grid structure. The results show the efficiency of PSSRE.

scholarly journals Compressive closeness in networks

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Hamidreza Mahyar ◽  
Rouzbeh Hasheminezhad ◽  
H Eugene Stanley
Keyword(s):  
Computational Complexity ◽  
Compressive Sensing ◽  
Distributed Algorithms ◽  
Real World ◽  
Topological Structure ◽  
Network Science ◽  
State Of The Art ◽  
Closeness Centrality ◽  
Local Interactions ◽  
Better Than

Abstract Distributed algorithms for network science applications are of great importance due to today’s large real-world networks. In such algorithms, a node is allowed only to have local interactions with its immediate neighbors; because the whole network topological structure is often unknown to each node. Recently, distributed detection of central nodes, concerning different notions of importance, within a network has received much attention. Closeness centrality is a prominent measure to evaluate the importance (influence) of nodes, based on their accessibility, in a given network. In this paper, first, we introduce a local (ego-centric) metric that correlates well with the global closeness centrality; however, it has very low computational complexity. Second, we propose a compressive sensing (CS)-based framework to accurately recover high closeness centrality nodes in the network utilizing the proposed local metric. Both ego-centric metric computation and its aggregation via CS are efficient and distributed, using only local interactions between neighboring nodes. Finally, we evaluate the performance of the proposed method through extensive experiments on various synthetic and real-world networks. The results show that the proposed local metric correlates with the global closeness centrality, better than the current local metrics. Moreover, the results demonstrate that the proposed CS-based method outperforms state-of-the-art methods with notable improvement.

Sign in / Sign up

Export Citation Format

Share Document