• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1333-1353
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• 2012

The robustness of a network is usually measured by error tolerance and attack vulnerability. Significant research effort has been devoted to determining the network design with optimal robustness. However, little attention has been paid to the problem of how to improve the robustness of existing networks. In this paper, we investigate how to optimize attack tolerance and communication efficiency of an existing network under the limited link addition. A survival fitness metric is defined to measure both the attack tolerance and the communication efficiency of the network. We show that network topology reconfiguration optimization with limited link addition (NTRLA) problem is NP-hard. Two approximate solution methods are developed. First, we present a degree-fitness parameter to guide degree-based link addition method. Second, a preferential configuration node-protecting cycle (PCNC) method is developed to do trade-off between network robustness and efficiency. The performance of PCNC method is demonstrated by numerical experiments.

• Archives of design research
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• v.15 no.1
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• pp.81-92
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• 2002

Through network draft, it′s possible to describe curve draft with main motive in a lobby loom and to fulfill draft design more conveniently thanks to the development of computer device. Network draft was introduced by Alice Schlein, who is an American weaving artist, and I had ever published research paper on "The unfolding and development of network draft using computer dobby system" . The purpose of the next study was to develop the design of network draft while do make a design network draft in a dobby loom with 16 shafts, and could reach follow conclusion as a result of designing a variety of drafts. The initial of 4-end in a loom with 16 shafts was a basic condition to describe more perfect shape in comparison with draft in 8 shafts through the development of network. The development of draft line was essential to deride the pattern of fabric, and the pattern of draft is decided according to selecting key peg plan. Thereby, could get a variety of draft patterns derive from mix key peg plan with initial selected by developing the kind of draft line and applying diverse key peg plan. As for the variation and diversification of draft line, the shape of patters varied depending col the curve extent and connectivity of draft line and the size of curve. The pattern of network draft can be changed infinitely by free round curve of draft line. In addition, a variety of draft designs shall be developed by increasing the number of shaft, enlarging the scale of draft line, and developing more creative draft line.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.227-240
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• 2011

New concepts and ideas often result from extensive recombination of existing concepts or ideas. Both researchers and developers build on existing concepts and ideas in published papers or registered patents to develop new theories and technologies that in turn serve as a basis for further development. As the importance of patent increases, so does that of patent analysis. Patent analysis is largely divided into network-based and keyword-based analyses. The former lacks its ability to analyze information technology in details while the letter is unable to identify the relationship between such technologies. In order to overcome the limitations of network-based and keyword-based analyses, this study, which blends those two methods, suggests the keyword network based analysis methodology. In this study, we collected significant technology information in each patent that is related to Light Emitting Diode (LED) through text mining, built a keyword network, and then executed a community network analysis on the collected data. The results of analysis are as the following. First, the patent keyword network indicated very low density and exceptionally high clustering coefficient. Technically, density is obtained by dividing the number of ties in a network by the number of all possible ties. The value ranges between 0 and 1, with higher values indicating denser networks and lower values indicating sparser networks. In real-world networks, the density varies depending on the size of a network; increasing the size of a network generally leads to a decrease in the density. The clustering coefficient is a network-level measure that illustrates the tendency of nodes to cluster in densely interconnected modules. This measure is to show the small-world property in which a network can be highly clustered even though it has a small average distance between nodes in spite of the large number of nodes. Therefore, high density in patent keyword network means that nodes in the patent keyword network are connected sporadically, and high clustering coefficient shows that nodes in the network are closely connected one another. Second, the cumulative degree distribution of the patent keyword network, as any other knowledge network like citation network or collaboration network, followed a clear power-law distribution. A well-known mechanism of this pattern is the preferential attachment mechanism, whereby a node with more links is likely to attain further new links in the evolution of the corresponding network. Unlike general normal distributions, the power-law distribution does not have a representative scale. This means that one cannot pick a representative or an average because there is always a considerable probability of finding much larger values. Networks with power-law distributions are therefore often referred to as scale-free networks. The presence of heavy-tailed scale-free distribution represents the fundamental signature of an emergent collective behavior of the actors who contribute to forming the network. In our context, the more frequently a patent keyword is used, the more often it is selected by researchers and is associated with other keywords or concepts to constitute and convey new patents or technologies. The evidence of power-law distribution implies that the preferential attachment mechanism suggests the origin of heavy-tailed distributions in a wide range of growing patent keyword network. Third, we found that among keywords that flew into a particular field, the vast majority of keywords with new links join existing keywords in the associated community in forming the concept of a new patent. This finding resulted in the same outcomes for both the short-term period (4-year) and long-term period (10-year) analyses. Furthermore, using the keyword combination information that was derived from the methodology suggested by our study enables one to forecast which concepts combine to form a new patent dimension and refer to those concepts when developing a new patent.

• Journal of Navigation and Port Research
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• v.39 no.3
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• pp.217-222
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• 2015

In this research, sea routes of domestic coaster liners between 2005 and 2013 were studied via social network analysis. Study of the sea routes revealed that they follow power-law in a scale-free form, a characteristic found often in social network. We have looked into centrality, which is a major standard in the field of social network analysis. We have also analyzed the annual changing trend in the centrality of the connectivity, examined the effect of quantity through the comparison with the original quantitative analysis method, and lastly, verified the relationship between the centrality of connectivity and mediation. Then, we were able to identify ports according to priority using these factors. This research assumed and interpreted the coaster liners route as a single network and suggested useful results. Based on these results, directing of development of domestic coaster liners route development and other factors will be achieved more smoothly. And if we utilize social network analysis method in other various fields - for example, the centrality of airport and the diplomatic realations analysis of the neighboring country - we will be able to effectively analyze events in diverse perspectives.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.151-157
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• 1998

Free-space optical interconnection networks can be classified into two types, space variant and space invariant, according to the degree of space variance. In terms of physical implementations, the degree of space variance can be interpreted as the degree of sharing beam steering optics among the nodes of a given network. This implies that all nodes in a totally space-invariant network can share a single beam steering optics to realize the given network topology, whereas, in a totally space variant network, each node requires a distinct beam steering optics. However, space invariant networks require mechanisms for distinguishing the origins of incoming signals detected at the node since several signals may arrive at the same time if the node degree of the network is greater than one. This paper presents a signal source encoding scheme for distinguishing incoming signals efficiently, in terms of the number of detectors at each node or the number of unique wavelengths. The proposed scheme is solved by developing a new parallel genetic algorithm called distributed asynchronous genetic algorithm (DAGA). Using the DAGA, we solved signal distinction schemes for various network sizes of several topologies such as hypercube, the mesh, and the de Brujin.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1266-1275
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• 2004

Bioinformatics is concerned with the creation and development of advanced information and computational technologies for problems in biology. It is divided into genomics, proteomics and metabolimics. In metabolimics, an organism is represented by metabolic pathway, i.e., well-displayed graph, and so the graph drawing tool to draw pathway well is necessary to understand it comprehensively. In this paper, we design an improved drawing algorithm. It enhances the readability by making use of the bipartite graph. Also it is possible to draw large graph properly by considering the facts that metabolic pathway graph is scale-free network and is composed of circular components, hierarchic components and linear components.

• Journal of Korean Society of Rural Planning
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• v.23 no.1
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• pp.1-10
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• 2017

The community bridge node finder, based on the stochastic method of network analysis, can compute hubs spot, which would enable the use of network structures with limited information. However, applying this node finder to heterogeneity networks, which are efficient to analyze the main farm complex in fields and the spread of infectious disease, is difficult. These problems, The most connected point that is called hub is often a major role in the heterogeneity network. In this study, we therefore improved the community bridge node finder to enable it to be applied to heterogeneity networks. We attempted to calculate the bridge node quantitatively by using the modularity of cohesion analysis method and the community bridge node finder. Application of the improved method to the HPAI(Highly Pathogenic Avian Influenza) spread in Korea 2008 produced a quarantine coefficient that was 4 - 37% higher than the quarantine coefficient obtained with the centrality method for the first 14 days after the HPAI outbreak. We concluded that the improved method has the ability to successfully calculate the bridge node in heterogeneity networks based on network structures with scant information, such as those describing the spread of infectious disease in domestic animals. And Our method should be capable to find main farm complex in fields.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.4
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• pp.166-171
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• 2008

We studied the variety and affinity between the successive words in the text document A number of groups were defined by the frequency of a following word in the whole text (corpus). In the previous studies, the Zipf's power law was explained by Chinese restaurant process and hub node was searched after by examining the edge number profile in scale free network. We have observed both a power law and a hub profile at the same time by studying the conditional frequency and degeneracy of a group. A symmetry between the affinity and the variety between words were found during the data analysis. And this phenomenon can be explained within a viewpoint of "exploitation and exploration." We also remark on a small symmetry breaking phenomenon in TIPSTER data.

• Genomics & Informatics
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• v.6 no.3
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• pp.147-152
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• 2008

The basic graph layout technique, one of many visualization techniques, deals with the problem of positioning vertices in a way to maximize some measure of desirability in a graph. The technique is becoming critically important for further development of the field of systems biology. However, applying the appropriate automatic graph layout techniques to the genomic scale flow of metabolism requires an understanding of the characteristics and patterns of duplicate and shared vertices, which is crucial for bioinformatics software developers. In this paper, we provide the results of parsing KEGG XML files from a graph-theoretical perspective, for future research in the area of automatic layout techniques in biological pathway domains.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.571-576
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• 1999

We consider a class of auto-associative memories namely N-Cubes (Neural-network Cubes) in which 2-D gray-level images and hidden sinusoidal 1-D wavelets are stored in cubical memories. First we develop a learning procedure based upon the least-squares algorithm, Therefore each 2-D training image is mapped into the associated 1-D waveform in the training phase. Second we show how the recall procedure minimizes errors among the orthogonal basis functions in the hidden layer. As a 2-D images ould be retrieved in the recall phase. Simulation results confirm the efficiency and the noise-free properties of N-Cubes.