• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1817-1839
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• 2024

To solve the problem of insufficient recognition of key nodes in the existing software defect detection process, this paper proposes a key node recognition algorithm based on node expansion degree and improved K-shell position, shortened as SDD_KNR. Firstly, the calculation formula of node expansion degree is designed to improve the degree that can measure the local defect propagation capability of nodes in the software network. Secondly, the concept of improved K-shell position of node is proposed to obtain the improved K-shell position of each node. Finally, the measurement of node defect propagation capability is defined, and the key node recognition algorithm is designed to identify the key function nodes with large defect impact range in the process of software defect detection. Using real software systems such as Nano, Cflow and Tar to design three sets of experiments. The corresponding directed weighted software function invoke networks are built to simulate intentional attack and defect source infection. The proposed SDD_KNR algorithm is compared with the BC algorithm, K-shell algorithm, KNMWSG algorithm and NMNC algorithm. The changing trend of network efficiency and the strength of node propagation force are analyzed to verify the effectiveness of the proposed SDD_KNR algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1373-1382
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• 2011

Zigbee is communication technology most ideal because Zigbee support low power communication and wide expansion in wireless home network. However, Zigbee is not popular, because of Zigbee always has Hidden Node Problem and Transit Delay Problem. We propose new Beacon Frame structure to solve the two problem in Zigbee. New Beacon Frame structure reduces a Super Frame Duration and add a same space of a Control Frame Duration. We expect to solved method of Hidden Node Problem that exchange terminal information to using RTS/CTS. Also, We expect to solved method of Transit Delay Problem that put Beacon between Control Frame Duration and Super Frame Duration for synchronization. We confirm new Beacon Frame to solved two problem in OPNET simulation at Zigbee QoS Parameters. We measure Delay(sec) for solution degree of Transit Delay Problem, and measure Throughput(bits/sec) and Load (bits/sec) for solution degree of Hidden Node Problem.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.8
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• pp.361-371
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• 2008

In this paper, the hypercube, hyperpetersen networks, whose degree is increasing in accordance with expansion of number of node and complete binary tree are one-to-one embedded into peterson-torus(PT) network which has fixed degree. The one-to-one embedding has less risk of overload or idle for the processor comparative to one-to-many and many-to-one embedding. For the algorithms which were developed on hypercube or hyperpetersen are used for PT network, it is one-to one embedded at expansion ${\doteqdot}1$, dilation 1.5n+2 and link congestion O(n) not to generate large numbers of idle processor. The complete binary tree is embedded into PT network with link congestion =1, expansion ${\doteqdot}5$ and dilation O(n) to avoid the bottleneck at the wormhole routing system which is not affected by the path length.

• Journal of Korea Multimedia Society
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• v.17 no.6
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• pp.725-732
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• 2014

The Pancake graph is node symmetric and useful interconnection network in the field of data sorting algorithm. The Half Pancake graph is a new interconnection network that reduces the degree of the Pancake graph by approximately half and improves the network cost of the Pancake graph. In this paper, we analyze topological properties of the Half Pancake graph $HP_n$. Fist, we prove that $HP_n$ has maximally fault tolerance and recursive scalability. In addition, we show that in $HP_n$, there are isomorphic graphs of low-dimensional $HP_n$. Also, we propose that the Bubblesort $B_n$ can be embedded into Half Pancake $HP_n$ with dilation 5, expansion 1. These results mean that various algorithms designed for the Pancake graph and the Bubble sort graph can be executed on $HP_n$ efficiently.

• Journal of the Korean Society of Costume
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• v.65 no.6
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• pp.25-35
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• 2015

The purpose of this study is to investigate the characteristics of members and communities that have significant influence in the online fashion community through their word-of-mouth activities. In order to identify the influence and the diffusion of word-of-mouth in fashion community, the study selected one online fashion community. Then, the study sorted the online posts and comments made on fashion information and put them into the matrix form to perform social network analysis. The result of the analysis is as follows: First, the fashion community network used in the study has many active members that relay information very quickly. Average time for information diffusion is very short, taking only one or two days in most cases. Second, the influence of word-of-mouth is led by key information produced from only a few members. The number of influential members account for less than 20% of the total number of community members, which indicate high level of degree centrality. The diffusion of word-of-mouth is led by even fewer members, which represent high level of betweenness centrality, compared to the case of degree centrality. Third, component characteristic shares similar information with about 70% of all members being linked to maximize information influence and diffusion. Fourth, a node with high degree centrality and betweenness centrality shares similar interests, presenting strain effect to particular information. Specially, members with high betweenness centrality show similar interests with members of high degree centrality. The members with high betweenness centrality also help expansion of related information by actively commenting on posts. The result of this research emphasizes the necessity of creation and management of network to efficiently convey fashion information by identifying key members with high level of information influence and diffusion to enhance the outcome of online word-of-mouth.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.10
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• pp.20-28
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• 2007

Zigbee sensor network base on IEEE802.15.4 has local address of 2 byte on transmit packet data which is pick up the address for each sensor node. Sensor network is requested low power, low cost, many nodes at hues physical area. There for Zigbee is very good solution supporting for next Ubiquitous generation but the Zigbee sensor network has address allocation problem of each sensor node. Is established standard from Zigbee Alliance, to the address allocation method uses Cskip algorithm. The Cskip algorithm use the hazard which allocates an address must blow Hop of the maximum modification and child node number. There is to address allocation and from theoretically it will be able to compose a personal 65536 sensor nodes only actual with concept or space, only 500 degree will be able to compose expansion or the low Zigbee network. We proposed an address allocation method using coordinate value for Zigbee sensor network.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.135-146
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• 2004

For improving the effectiveness of travel information, some rational paths are needed to provide them to users driving in real road network. To meet it, k-shortest path algorithms have been used in general. Although the k-shortest path algorithm can provide several alternative paths, it has inherent limit of heavy overlapping among derived paths, which nay lead to incorrect travel information to the users. In case of considering the network consisting of several turn prohibitions popularly adopted in real world network, it makes difficult for the traditional network optimization technique to deal with. Banned and penalized turns are not described appropriately for in the standard node/link method of network definition with intersections represented by nodes only. Such problem could be solved by expansion technique adding extra links and nodes to the network for describing turn penalties, but this method could not apply to large networks as well as dynamic case due to its overwhelming additional works. This paper proposes a link-based shortest path algorithm for the travel information in real road network where exists turn prohibitions. It enables to provide efficient alternative paths under consideration of overlaps among paths. The algorithm builds each path based on the degree of overlapping between each path and stops building new path when the degree of overlapping ratio exceeds its criterion. Because proposed algorithm builds the shortest path based on the link-end cost instead or node cost and constructs path between origin and destination by link connection, the network expansion does not require. Thus it is possible to save the time or network modification and of computer running. Some numerical examples are used for test of the model proposed in the paper.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.6
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• pp.1439-1450
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• 1995

Bellows is a familiar component in piping systems as it provides a relatively simple means of absorbing thermal expansion and providing system flexibility. In routine piping flexibility analysis by finite element methods, bellows is usually considered to be straight pipe runs modified by an appropriate flexibility factor; maximum stresses are evaluated using a corresponding stress concentration factor. The aim of this study is to develop a bellows finite element, which similarly includes more complex shell type deformation patterns. This element also does not require flexibility or stress factors, but evaluates more detailed deformation and stress patterns. The proposed bellows element is a 3-D, 2-noded line element, with three degrees of freedom per node and no bending. It is formulated by including additional 'internal' degrees of freedom to account for the deformation of the bellows corrugation; specifically a quarter toroidal section of the bellows, loaded by axial force, is considered and the shell type deformation of this is include by way of an approximating trigonometric series. The stiffness of each half bellows section may be found by minimising the potential energy of the section for a chosen deformation shape function. An experiment on the flexibility is performed to verify the reliability for bellows finite element.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.189-194
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• 2012

In this paper, we propose a query expansion method based on word graphs using pseudo-relevant and pseudo non-relevant documents to achieve performance improvement in information retrieval. The initially retrieved documents are classified into a core cluster when a document includes core query terms extracted by query term combinations and the degree of query term proximity. Otherwise, documents are classified into a non-core cluster. The documents that belong to a core query cluster can be seen as pseudo-relevant documents, and the documents that belong to a non-core cluster can be seen as pseudo non-relevant documents. Each cluster is represented as a graph which has nodes and edges. Each node represents a term and each edge represents proximity between the term and a query term. The term weight is calculated by subtracting the term weight in the non-core cluster graph from the term weight in the core cluster graph. It means that a term with a high weight in a non-core cluster graph should not be considered as an expanded term. Expansion terms are selected according to the term weights. Experimental results on TREC WT10g test collection show that the proposed method achieves 9.4% improvement over the language model in mean average precision.