• Journal of The Korean Astronomical Society
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• v.38 no.2
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• pp.175-178
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• 2005

We show that next-generation galaxy surveys such as KAOS (the Kilo-Aperture Optical Spectro-graph)will constrain dark energy even if the baryon oscillations are missing from the monopole power spectrum and the bias is scale- and time-dependent KAOS will accurately measure the quadrupole power spectrum which gives the leading anisotropies in the power spectrum in redshift space due to peculiar velocities, the finger of God effect, as well as the Alcock-Paczynski effect. The combination of monopole and quadrupole power spectra powerfully breaks the degeneracy between the bias parameters and dark energy and, in the complete absence of baryon oscillations ($\Omega$b = 0), leads to a roughly $500\%$ improvement in constraints on dark energy compared with the monopole spectrum alone. As a result, for KAOS the worst case with no oscillations has dark energy errors only mildly degraded relative to the ideal case, providing insurance on the robustness of KAOS constraints on dark energy. We show that nonlinear effects are crucial in correctly evaluating the quadrupole and significantly improving the constraints on dark energy when we allow for multi-parameter scale-dependent bias.

• Journal of the Korean Data and Information Science Society
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• v.22 no.1
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• pp.19-27
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• 2011

Recommendation systems are developed to overcome the problems of selection and to promote intention to use. In this study, we propose a recommendation system using adjacency data according to user's behavior over time. For this, the product adjacencies are identified from the adjacency matrix based on graph theory. This research finds that there is a trend in the users' behavior over time though product adjacency fluctuates over time. The system is tested on its usability. The tests show that implementing this recommendation system increases users' intention to purchase and reduces the search time.

• Journal of Environmental Impact Assessment
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• v.21 no.3
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• pp.391-407
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• 2012

The loss of connectivity and fragmentation of forest landscapes are seriously hindering dispersal of many forest-dwelling species, which may be critical for their viability and conservation by decreasing habitat area and increasing distance among habitats. For understanding their environmental impacts, numerous spatial models exist to measure landscape connectivity. However, general relationships between functional connectivity and landscape structure are lacking, there is a need to develop landscape metrics that more accurately measure landscape connectivity in whole landscape and individual patches. We reviewed functional and structural definition of landscape connectivity, explained their mathematical connotations, and applied representative 13 indices in 3 districts of Seoul having fragmented forest patches with tits, the threshold distance was applied 500m by considering the dispersal of tits. Results of correlation and principal component analysis showed that connectivity indices could be divided by measurement methods whether they contain the area attribute with distance or not. Betweenness centrality(BC), a representative index measuring distance and distribution among patches, appreciated highly stepping stone forest patches, and difference of probability of connectivity(dPC), an index measuring including area information, estimated integrated connectivity of patches. Therefore, for evaluating landscape connectivity, it is need to consider not only general information of a region and species' characteristics but also various measuring methods of landscape connectivity.

• The Korean Journal of Applied Statistics
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• v.33 no.2
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• pp.115-122
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• 2020

K-means clustering uses a spherical or elliptical metric to group data points; however, it does not work well for non-convex data such as the concentric circles. Spectral clustering, based on graph theory, is a generalized and robust technique to deal with non-standard type of data such as non-convex data. Results obtained by spectral clustering often outperform traditional clustering such as K-means. In this paper, we review spectral clustering and show important issues in spectral clustering such as determining the number of clusters K, estimation of scale parameter in the adjacency of two points, and the dimension reduction technique in clustering high-dimensional data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.6
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• pp.1137-1147
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• 1997

I propose a RZETA network consisted of switching elements(SEs) that have regular links and alternate links. A modified Zeta nework used for the RZETA network's regular links and a MIN used for its alternate links are generated using the graph theory. The RZETA network is driven from merging the formaer and latter MINs. A necessary and sufficient condition for modified Zeta network to be a nonblocking network is also presented. This condition is a ufficient condition for RZETA network with a faulty link or a faulty SE to be nonblocked. Performance of the RZETA network is analyzed by modification of the model of 2-dilated Banyan network and its performance is compared with existing redundant path networks, when packet arrival rate of each source is 1.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.6
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• pp.301-309
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• 2001

본 논문에서는 RSA 암호 시스템의 핵심 과정인 모듈로 멱승 연산에 대한 새로운 하드웨어 구조를 제시한다. 본 방식은 몽고메리 곱셈 알고리즘을 사용하였으며 기존의 방법들이 데이터 종속 그래프(DG : Dependence Graph)를 수직으로 매핑한 것과는 달리 여기서는 수평으로 매핑하여 1차원 선형 어레이구조를 구성하였다. 그 결과로 멱승시에 중간 결과값이 순차적으로 나와서 바로 다음 곱셈을 위한 입력으로 들어갈 수 있기 때문에 100%의 처리율(throughput)을 이룰 수 있고, 수직 매핑 방식에 비해 절반의 클럭 횟수로 연산을 해낼 수 있으며 컨트롤 또한 단순해지는 장점을 가진다. 각 PE(Processing Element)는 2개의 전가산기와 3개의 멀티플렉서로 이루어져 있고, 암호키의 비트수를 k비트라 할 때 k+3개의 PE만으로 파이프라인구조를 구현하였다. 1024비트 RSA데이터의 암호 똔느 복호를 완료하는데 2k$^2$+12k+19의 클럭 수가 소요되며 클럭 주파수 100Mhz에서 약 50kbps의 성능을 보인다. 또한, 제안된 하드웨어는 내부 계산 구조의 지역성(locality), 규칙성(regularity) 및 모듈성(modularity) 등으로 인해 실시간 고속 처리를 위한 VLSI 구현에 적합하다.

• Industrial Engineering and Management Systems
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• v.7 no.3
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• pp.245-256
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• 2008

In order to cope with the ill-defined problem of human behavior being immanent uncertainty, several methodologies have been studied in game theoretic, social psychological and political science frameworks. As methods to arrange system elements systematically and draw out the consenting structural model concretively, ISM, FSM and DEMATEL based on graph theory etc. have been proposed. In this paper, we propose a modified structural modeling method to recognize the nature of problem. We introduce the statistical method to adjust the establishment levels in group decision situation. From this, it will become possible to obtain effectively and smoothly the structural model of group members in comparison with the traditional methods. Further we propose a procedure for achieving the consenting structural model of group members based on the structural modeling method. By applying the method to recognize the nature of ill-defined problems, it will be possible to solve the given problem effectively and rationally. In order to inspect the effectiveness of the method, we conduct a practical problem as an empirical study: "Behavior analysis of passengers for the Joban line of East Japan Railway Company after new railway service of Tsukuba Express opened".

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.1_2
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• pp.86-94
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• 2004

In this paper, we show that $ G(2^m, 4), m{\geq}3$with at most m-2 faulty elements has a fault-free cycle of length 1 for every ${\leq}1{\leq}2^m-f_v$ is the number of faulty vertices. To achieve our purpose, we define a graph G to be k-fault hypohamiltonian-connected if for any set F of faulty elements, G- F has a fault-free path joining every pair of fault-free vertices whose length is shorter than a hamiltonian path by one, and then show that$ G(2^m, 4), m{\geq}3$ is m-3-fault hypohamiltonian-connected.

• Genomics & Informatics
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• v.3 no.1
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• pp.30-34
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• 2005

Microarray technology makes it possible to measure the expressions of tens of thousands of genes simultaneously under various experimental conditions. Identifying differentially expressed genes in each single experimental condition is one of the most common first steps in microarray gene expression data analysis. Reasonable choices of thresholds for determining differentially expressed genes are used for the next-stap-analysis with suitable statistical significances. We present a supervised model for identifying DEGs using pathway information based on the global connectivity structure. Pathway information can be regarded as a collection of biological knowledge, thus we are trying to determine the optimal threshold so that the consequential connectivity structure can be the most compatible with the existing pathway information. The significant feature of our model is that it uses established knowledge as a reference to determine the direction of analyzing microarray dataset. In the most of previous work, only intrinsic information in the miroarray is used for the identifying DEGs. We hope that our proposed method could contribute to construct biologically meaningful structure from microarray datasets.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.10
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• pp.565-572
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• 2004

This paper proposes an expert system which can enhance the accuracy of real-time bus reconfiguration strategy by adopting local minimum tree search method and minimize the spreading effect of the fault by considering totally the operating condition when a main transformer fault occurs in the automated substation. The local minimum tree search method to expand the best-first search method. This method has an advantage which can improve the performance of solution within the limits of the real-time condition. The inference strategy proposed expert system consists of two stages. The first stage determines the switching candidate set by searching possible switching candidates starting from the main transformer or busbar related to the event. And, second stage determines the rational real-time bus reconfiguration strategy based on heuristic rules for the obtained switching candidate set. Also, this paper studies the generalized distribution substation modelling using graph theory and a substation database is designed based on the study result. The inference engine of the expert system and the substation database is implemented in MFC function of Visual C++. Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and local minimum tree search solution based on diversity event simulations for typical distribution substation.