• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1183-1193
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• 2010

The pyramid graph is well known in parallel processing as a interconnection network topology based on regular square mesh and tree architectures. The enhanced pyramid graph is an alternative architecture by exchanging mesh into the corresponding torus on the base for upgrading performance than the pyramid. In this paper, we adopt a strategy of classification into two disjoint groups of edges in regular square torus as a basic sub-graph constituting of each layer in the enhanced pyramid graph. Edge set in the torus graph is considered as two disjoint sub-sets called NPC(represents candidate edge for neighbor-parent) and SPC(represents candidate edge for shared-parent) whether the parents vertices adjacent to two end vertices of the corresponding edge have a relation of neighbor or sharing in the upper layer of the enhanced pyramid graph. In addition, we also introduce a notion of shrink graph to focus only on the NPC-edges by hiding SPC-edges within the shrunk super-vertex on the resulting shrink graph. In this paper, we analyze that the lower and upper bounds on the number of NPC-edges in a Hamiltonian cycle constructed on $2^n{\times}2^n$ torus is $2^{2n-2}$ and $3{\cdot}2^{2n-2}$ respectively. By expanding this result into the enhanced pyramid graph, we also prove that the maximum number of NPC-edges containable in a Hamiltonian cycle is $4^{n-1}$-2n+1 in the n-dimensional enhanced pyramid.

• Journal of KIISE
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• v.44 no.2
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• pp.139-147
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• 2017

Most of the information prevailing in the Internet space consists of textual information. So one of the main topics regarding the huge document analyses that are required in the "big data" era is the development of an automated understanding system for textual data; accordingly, the automation of the keyword extraction for text summarization and abstraction is a typical research problem. But the simple listing of a few keywords is insufficient to reveal the complex semantic structures of the general texts. In this paper, a text-visualization method that constructs a graph by computing the related degrees from the selected keywords of the target text is developed; therefore, two construction models that provide the edge relation are proposed for the computing of the relation degree among keywords, as follows: influence-interval model and word- distance model. The finally visualized graph from the keyword-derived edge relation is more flexible and useful for the display of the meaning structure of the target text; furthermore, this abstract graph enables a fast and easy understanding of the target text. The authors' experiment showed that the proposed abstract-graph model is superior to the keyword list for the attainment of a semantic and comparitive understanding of text.

• Journal of KIISE
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• v.44 no.2
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• pp.179-185
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• 2017

Document summarization aims to generate a summary that is consistent and contains the highly related sentences in a document. In this study, we implemented for document summarization that extracts highly related sentences from a whole document by considering both similarities and entailment relations between sentences. Accordingly, we proposed a new algorithm, TextRank-NLI, which combines a Recurrent Neural Network based Natural Language Inference model and a Graph-based ranking algorithm used in single document extraction-based summarization task. In order to evaluate the performance of the new algorithm, we conducted experiments using the same datasets as used in TextRank algorithm. The results indicated that TextRank-NLI showed 2.3% improvement in performance, as compared to TextRank.

• Journal of the Korean School Mathematics Society
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• v.4 no.1
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• pp.103-114
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• 2001

The purpose of this study is to develop learning materials for functional concept on variable and to verify the effect of how well students could learn functional concept after they studied with those materials. To accomplish the purpose of this study, I developed learning materials and after teaching students with them. I have concluded the followings : First, there was little effect in teaching functional concept on variable between two experimental groups, whereas teaching functional concept had greater effect on forming functional concept in high level groups in those two experimental groups. Second, teaching functional concept on variable had little effect on students' understanding of functional concept and perfecting tables in Black box, graph, and mathematical problems, whereas there was much effect in students' understanding functional concept and solving relation formula, image, and range problems related to everyday life or general things. On the basis of the problems which appeared in the process of this study, the following can be suggested : First, we should develop learning materials fit for low level students so that they could understand functional concept. Second, we should continue to teach the basic problems like solving relation formula, image, and range, and understanding functional concept in graph until students are able to understand them exactly. Third, since the goals of Unit Function in a middle school textbook is to solve problems related to everyday life through functional thinking, there should be change in constructing systematic contents of Unit Function in a middle school textbook.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.1-10
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• 2007

Many types of information provided through the web including news contents contain unnecessary clutters. These clutters make it difficult to build automated information processing systems such as the summarization, extraction and retrieval of documents. We propose a system that extracts and summarizes news contents from the web. The extraction system receives news contents in HTML as input and builds an element tree similar to DOM tree, and extracts texts while removing clutters with the hyperlink attribute in the HTML tag from the element tree. Texts extracted through the extraction system are transferred to the summarization system, which extracts key sentences from the texts. We implement the summarization system using co-occurrence relation graph. The summarized sentences of this paper are expected to be transmissible to PDA or cellular phone by message services such as SMS.

• Journal of KIISE:Databases
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• v.32 no.5
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• pp.498-508
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• 2005

A shape data is used one oi most important feature for image retrieval as data to reflect meaning of image. Especially, structural feature of shape is widely studied because it represents primitive properties of shape and relation information between basic units well. However, most structural features of shape have the problem that it is not able to guarantee an efficient search time because the features are expressed as graph or tree. In order to solve this problem, we generate curvature-based morphological graph, End design key to cluster shapes from this graph. Proposed this graph have contour features and morphological features of a shape. Shape retrieval is accomplished by stages. We reduce a search space through clustering, and determine total similarity value through pattern matching of external curvature. Various experiments show that our approach reduces computational complexity and retrieval cost.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2D
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• pp.171-179
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• 2010

The purpose of the present study is to suggest composing the graph topology of sketch drawing element and the recognition of the shape pattern for the earthwork quantity calculation. The algorithm which can extract the topology element such as vertex, edge, face and establish the relation between each topology was developed. The model which can define earthwork graph and recognize the shape pattern of earthwork was presented. As a result of the study, the shape pattern of earthwork that can't be calculated by existing earthwork calculation program could be recognized as expanding this model. The earthwork shape recognition automation using the graph topology model can be applied to the automation for the earthwork quantity estimation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.11-22
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• 2004

Conventional algorithms of separating overlapped objects are mostly based on template matching methods and thus their application domain is restricted to 2D objects and the processing time increases when the number of templates (object models) does. To solve these problems, this paper proposes a new approach of separating the occluding object from the stack of 3D objects using the relationship between surfaces without any information on the objects. The proposed algorithm considers an object as a combination of surfaces which are consisted with a set of boundary edges. Overlap of 3D objects appears as overlap of surfaces and thus as crossings of edges in 2D image. Based on this observation, the types of edge crossings are classified from which the types of overlap of 3D objects can be identified. The relationships between surfaces are represented by an attributed graph where the types of overlaps are represented by relation values. Using the relation values, the surfaces pertained to the same object are discerned and the overlapping object on the top of the stack can be separated. The performance of the proposed algorithm has been proved by the experiments using the overlapped images of 3D objects selected among the standard industrial parts.

• Journal of KIISE:Software and Applications
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• v.37 no.6
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• pp.464-469
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• 2010

In this paper, we propose a method to extract isa/instanceOf relation from category structure. Existing researches use lexical patterns to get isa/instanceOf relation from the category structure, e.g. head word matching, to determine whether the given category link is isa/instanceOf relation or not. In this paper, we propose a new approach which analyzes other category links related to the given category link to determine whether the given category link is isa/instanceOf relation or not. The experimental result shows that our algorithm can cover many cases which the existing algorithms were not able to deal with.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.183-191
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• 2001

We develop the new data s]ice representation, called the data value flow graph(VFG), for modeling the information flow oil data slices. Then we define a slice complexity measure by using the existing flow complexity measure in order to measure the complexity of the information flow on VFG. We show relation of the slice complexity on a slice with the slice complexity on a procedure. We also demonstrate the measurement scale factors through a set of atomic modifications and a concatenation operator on VFG.