• Journal of Sasang Constitutional Medicine
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• v.8 no.2
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• pp.191-202
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• 1996

Sasang constitution classification is very important subject, so many medical men studied the Sasang constitution classification but there is no certain method to classify objectively. And the purpose of this study is to help classifying Sasang constitution through correlation with sound spectrogram. This study was done it under the suppose that Sasang costitution hag correlation with sound spectrogram. The following results were obtained about correlation between sound spectrogram and Sasang constitution by comparison and analysis the pitch and reading speed of Sasang constitutions; 1. There was a similar tendency in the composition reading speed between taeeumin, soeumin and soyangin. 2. Taeeumin's center was lower measured more than soeumin's and soyangin's in the pitch graph and graph by normal curve fit and there was a similar tendency between soeumin and soyangin. 3. There was a similar tendency in the pitch graph's width between all constitutions. 4. There was a significant difference between taeeumin and soeum in the mean of three constitution's pitch, this means that taeeumin uses lower voice more than soeumin. According to the results, it is considered that there is a correlation between pitch of sound spectrogram and Sasang constitution. And method of Sasang constitution classification through sound spectrogram analysis can be one method as assistant for the objectification of Sasang constitution classification.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.409-419
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• 1993

This paper concerns graphical methods for discriminant analysis. We discuss Sammon's graph, MV graph and possibility of an alternative. The properties of the three graphs are investigated using real data and simulation studies. Dimensionality reduction for an alternative and robust procedure are discussed.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.534-537
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• 2024

Single-machine-based 그래프 엔진은 단일 머신을 이용해 고성능의 그래프 분석을 가능하게 하지만 distributed-system-based 그래프 엔진보다 확장성이 낮다. 본 논문은 single-machine-based 그래프 엔진 중 state-of-the-art 인 RealGraph 에 NVMe-oF 기술을 이용한 고성능 원격 스토리지를 연결해 성능을 확인했다. 실험으로 우리는 고성능 원격 스토리지를 이용한 single-machine-based 그래프 엔진의 확장가능성이 있음을 확인하고 향후 연구에서 고성능 원격 스토리지를 사용할 경우 구조개선이 필요함을 제시한다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04a
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• pp.53-55
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• 2000

VRML은 상호 작용을 하는 3D 객체와 세계를 기술하는 파일 형식이다. OO-VRML은 VRML을 객체 지향 언어로 확장하여 정보 은닉, 상속 그리고 동적 바인딩 등을 가능하게 한 언어이다. OO-VRML의 이런 특징들은 더 동적인 가상 세계를 섬세하게 조정할 수 있도록 해준다. 이 논문에서는 OO-VRML의 표현 능력을 잘 활용하기 위해 OO-VRML 언어를 사용하는 전용 브라우저를 설계하고 구현한다. 부라우저는 파싱 및 인스턴스화 모듈, 실행 모듈, 브라우저 모듈의 세 부분으로 나누어진다. 파싱 및 인스턴스화 모듈은 OO-VRML 형식의 가상 세계를 읽어들여서 객체로 바꾸어주고 그객체들을 인스턴스화하여 OO-VRML장면 그래프로 바꾸어준다. 장면 그래프는 실행 모듈은 발생한 이벤트들을 처리하여 인스턴스의 필드 값을 바꾸어준다. 브라우저 모듈은 가상 세계를 화면에 나타내 주고 사용자 입력과 네비게이션을 처리한다.

• The KIPS Transactions:PartA
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• v.13A no.3 s.100
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• pp.253-260
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• 2006

In this paper, we analyze the Hamiltonian property of Pyramid graphs. We prove that it is always possible to construct a Hamiltonian cycle of length $(4^N-1)/3$ by applying the proposed algorithm to construct series of cycle expansion operations into two adjacent cycles in the Pyramid graph of height N.

• Journal of KIISE:Databases
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• v.29 no.5
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• pp.347-357
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• 2002

Graphs have provided a powerful methodology to solve a lot of real-world problems, and therefore there have been many proposals on the graph representations and algorithms. But, because most of them considered only memory-based graphs, there are still difficulties to apply them to large-scale problems. To cope with the difficulties, this paper proposes a graph representation and graph algorithms based on the well-developed relational database theory. Graphs are represented in the form of relations which can be visualized as relational tables. Each vertex and edge of a graph is represented as a tuple in the tables. Graph algorithms are also defined in terms of relational algebraic operations such as projection, selection, and join. They can be implemented with the database language such as SQL. We also developed a library of basic graph operations for the management of graphs and the development of graph applications. This database approach provides an efficient methodology to deal with very large- scale graphs, and the graph library supports the development of graph applications. Furthermore, it has many advantages such as the concurrent graph sharing among users by virtue of the capability of database.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.974-983
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• 2005

In genetic algorithms with lotus-based encoding, static gene reordering is to locate the highly related genes closely together. It helps the genetic algorithms to create and preserve the schema of high-quality effectively. In this paper, we propose a static reordering framework for linear locus-based encoding. It differs from existing reorderings in that it is independent of problem-specific knowledge. It makes a complete graph where weights represent the interelationship between each pair of genes. And, it transforms the graph into a unweighted sparse graph by choosing the edges having relatively high weight. It finds a gene reordering by graph search method. Through the wide experiments about several problems, the method proposed in this paper shows significant performance improvement as compared with the genetic algorithm that does not rearrange genes.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.10
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• pp.539-554
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• 2007

In this Paper, we investigate conditions for proper interval graphs to have k-disjoint path covers of three types each: one-to-one, one-to-many, and many-to-many. It was proved that for $k{\geq}2$, a proper interval graph is one-to-one k-disjoint path coverable if and only if the graph is k-connected, and is one-to-many k-disjoint path coverable if and only if the graph is k+1-connected. For $k{\geq}3$, a Proper interval graph is (paired) many-to-many k-disjoint path coverable if and only if the graph is 2k-1-connected.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.35-46
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• 2022

Recently, with the development of network technologies, as IoT and social network service applications have been actively used, a lot of graph stream data is being generated. In this paper, we propose a graph compression scheme that considers the stream graph environment by applying graph mining to the existing compression technique, which has been focused on compression rate and runtime. In this paper, we proposed Incremental frequent pattern based compression technique for graph streams. Since the proposed scheme keeps only the latest reference patterns, it increases the storage utilization and improves the query processing time. In order to show the superiority of the proposed scheme, various performance evaluations are performed in terms of compression rate and processing time compared to the existing method. The proposed scheme is faster than existing similar scheme when the number of duplicated data is large.

• Smart Media Journal
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• v.12 no.1
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• pp.9-16
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• 2023

Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.