• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.993-1001
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• 2003

A RDB Storage Model based on the Edge-Labeled Graph is suggested for store the XML instance in Relational Databases(RDB). The XML instance being stored is represented by Data Graph based on the Edge-Labeled Graph. Data Path Table, Element, Attribute, and Table Index Table values are extracted. Then Database Schema is defined, and the extracted values are stored using the Mapper. In order to support querry, Repository Model offers the translator translating XQL which is used as query language under XPATH, into SQL. In addition, it creates DBtoXML generator restoring the stored XML instance. As a result, storage relationship between the XML instance and proposed model structure can be expressed in terms of Graph-based Path, and it shows the possibility of easy search of random Element and Attribute information.

• Journal of The Korean Association For Science Education
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• v.39 no.5
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• pp.655-668
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• 2019

In this study, we investigated the middle school students' processes of scientific graph construction from the perspective of the problem solving process. Ten 9th graders participated in this study. They constructed a scientific graph based on pictorial data depicting precipitation reaction. The think-aloud method was used in order to investigate their thinking processes deeply. Their activities were videotaped, and semi-structured interviews were also conducted. The analysis of the results revealed that their processes of scientific graph construction could be classified into four types according to the problem solving strategy and the level of representations utilized. Students using the structural strategy succeeded in constructing scientific graph regardless of the level of representation utilized, by analyzing the data and identifying the trend based on the propositional knowledge about the target concept of the graph. Students of random strategy-higher order representation type were able to succeed in constructing scientific graph by systematically analyzing the characteristics of the data using various representations, and considering the meaning of the graph constructed in terms of the scientific context. On the other hand, students of random strategy-lower order representation type failed to construct correct scientific graph by constructing graph in a way of simply connecting points, and checking the processes of graph construction only without considering the scientific context. On the bases of the results, effective methods for improving students' ability to construct scientific graphs are discussed.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2002.09a
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• pp.25.2-25
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• 2002

• ETRI Journal
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• v.38 no.4
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• pp.714-723
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• 2016

Considerable attention has been given to processing graph data in recent years. An efficient method for computing the node proximity is one of the most challenging problems for many applications such as recommendation systems and social networks. Regarding large-scale, mutable datasets and user queries, top-k query processing has gained significant interest. This paper presents a novel method to find top-k answers in a node proximity search based on the well-known measure, Personalized PageRank (PPR). First, we introduce a distribution state transition graph (DSTG) to depict iterative steps for solving the PPR equation. Second, we propose a weight distribution model of a DSTG to capture the states of intermediate PPR scores and their distribution. Using a DSTG, we can selectively follow and compare multiple random paths with different lengths to find the most promising nodes. Moreover, we prove that the results of our method are equivalent to the PPR results. Comparative performance studies using two real datasets clearly show that our method is practical and accurate.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.25-31
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• 2016

There are many methods to describe the importance of a node, centrality, in a graph. In this paper, we focus on the eigenvector centrality. In this paper, an analytical method to estimate the difference of centrality with an additional edge in a graph is proposed. In order to validate the analytical method to estimate the centrality, two problems, to decide an additional edge that maximizes the difference of all centralities of all nodes in the graph and to decide an additional edge that maximizes the centrality of a specific node, are solved using three kinds of random graphs and the results of the estimated edge and observed edge are compared. Though the estimated centrality difference is slightly different from the observed real centrality in some cases, it is shown that the proposed method is effective to estimate the centrality difference with a short running time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1712-1731
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• 2016

In this paper, we propose a novel saliency detection framework via multiple random walks (MRW) which simulate multiple agents on a graph simultaneously. In the MRW system, two agents, which represent the seeds of background and foreground, traverse the graph according to a transition matrix, and interact with each other to achieve a state of equilibrium. The proposed algorithm is divided into three steps. First, an initial segmentation is performed to partition an input image into homogeneous regions (i.e., superpixels) for saliency computation. Based on the regions of image, we construct a graph that the nodes correspond to the superpixels in the image, and the edges between neighboring nodes represent the similarities of the corresponding superpixels. Second, to generate the seeds of background, we first filter out one of the four boundaries that most unlikely belong to the background. The superpixels on each of the three remaining sides of the image will be labeled as the seeds of background. To generate the seeds of foreground, we utilize the center prior that foreground objects tend to appear near the image center. In last step, the seeds of foreground and background are treated as two different agents in multiple random walkers to complete the process of salient object detection. Experimental results on three benchmark databases demonstrate the proposed method performs well when it against the state-of-the-art methods in terms of accuracy and robustness.

• Industry Promotion Research
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• v.9 no.2
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• pp.45-58
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• 2024

This study modelled the social network structure characteristics between Innopolis Start-ups located in Daejeon and Innopolis Start-ups' customers scattered across the country as a tendency of regional clustering among homogeneous technologies, and the observed values were included within the 95% confidence interval of the ERGM(Exponential Random Graph Model) analysis model. If both the research institute and the customer company are located in Yuseong-gu, Daejeon, the probability of being connected is about 13 times higher than if they are located in other administrative districts, and there is a strong tendency of connection between firms with the same technology with a negative value of assortment and homogeneity (0.1904), especially among the six technology sectors, with a P value of 0.035. There was a negative value (-0.0035) among firms not located in Yuseong-gu, with less clustering tendency. This confirms that Yuseong-gu, Daejeon, where the Daedeok Innopolis is located, is forming the centre of an innovation cluster.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.306-311
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• 2007

본 논문에서는 Wireless Sensor Network상에서 전체 노드들의 lifetime을 증대시키기 위하여 "random한" 방식으로 cluster-head를 선출하는 LEACH 알고리즘이 가지고 있는 cluster-head 선출 과정에서 선출되는 수와 선출되는 노드들의 위치가 적절히 분산되지 않는 문제를 해결하기 위해 변형된 Graph Coloring 문제를 기반으로 노드의 위치 정보를 사용하지 않고 cluster-head를 적절히 분산하여 선출함으로써 효율적인 clustering을 하는 중앙처리 방식의 새로운 알고리즘 "GCCA : Graph Coloring based Clustering Algorithm for Wireless Sensor Networks" 을 제안한다. GCCA는 cluster-head가 선출되는 수를 일정하게 유지하고 선출되는 노드의 위치가 전체 network area에 적절히 분산되는 효과를 가져 옴으로 LEACH 알고리즘보다 에너지 효율이 증대됨을 실험을 통하여 보인다.

• The Pure and Applied Mathematics
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• v.31 no.1
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• pp.57-81
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• 2024

We introduce a new degree reduction method for homogeneous symmetric polynomials on binary variables that generalizes the conventional degree reduction methods on monomials introduced by Freedman and Ishikawa. We also design an degree reduction algorithm for general polynomials on binary variables, simulated on the graph coloring problem for random graphs, and compared the results with the conventional methods. The simulated results show that our new method produces reduced quadratic polynomials that contains less variables than the reduced quadratic polynomials produced by the conventional methods.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.741-757
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• 2000

In may experimental situations, whenever a block design is used, the block effect is usually considered to be fixed. There are, however, experimental situations in which it should be treated as random. The choice of a blocking arrangement for a response surface design can have a considerable effect on estimating the mean response and on the size of he prediction variance even if the experimental runs re the same. Therefore, care should be exercised in the selection of blocks. In this paper, in the presence of a random block effect, we propose a graphical method or evaluating the effect of blocking in response surface designs using cuboidal regions. This graphical method can be used to investigate how the blocking has influence on the prediction variance throughout all experimental regions of interest when this region is cuboidal, and compare the block effects in the cases of the orthogonal and non-orthogonal block designs, respectively.