• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.501-508
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• 2009

In this paper, we prove that folded hyper-star network FHS(2n,n) is node-symmetric and a bipartite network. We show that FHS(2n,n) can be embedded into odd network On+1 with dilation 2, congestion 1 and Od can be embedded into FHS(2n,n) with dilation 2 and congestion 1. Also, we show that $2n{\time}n$ torus can be embedded into FHS(2n,n) with dilation 2 and congestion 2.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.469-477
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• 2000

본 연구에서는 부도예측용 인공신경망 모형의 입력노드를 선정하기 위한 방법론으로 연결강도판별분석(Link Weight Discrimination Analysis)에 의한 약체뉴론제거법(Weak-Linked Neuron Elimination)과 강체뉴론선택법 (Strong-Linked Neurons Selection)을 제안한다. 연결강도판별분석이란 적절한 학습이 끝난 인공신경망 모형에서 입력노드와 연결되는 가중치의 합에 대한 절대값인 연결강도 판별식(Link Weight Discrimination)에 의해 해당 입력노 드가 출력노드에 미치는 영향정도를 분석하는 것이다. 한편 강체연결뉴론선택법은 선처리를 통해 얻어진 학습된 인공신경망의 입력노드 가운데서 연결강도판별식이 큰 뉴론만을 본처리의 입력노드로 선정하는 것인데 비해 약체연결뉴론제거법은 연결강도판별식이 일정 값 즉, 연결강도 판별임계치(Link Weight Discrimination Cut off Value) 보다 낮은 입력노드를 제외하고 나머지 입력노드만을 본처리의 입력노드로 선정하는 것이다. 본 연구에서는 강체연결뉴론선택법과 약체연결뉴론제거법을 각각 정형적인 방법론으로 정립하고 이 방법론에 의해 부도예측용 인공신경망을 구축하여 각각의 모형을 의사결정트리에 의해 선정된 인공신경망 모형 및 선처리 과정을 거치지 않은 인공신경망 모형과 성능을 비교, 분석하여 본 연구에서 제안한 방법론의 타당성을 제시하였다.

• Korean Journal of Social Welfare
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• v.61 no.4
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• pp.61-84
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• 2009

This study is to analyze the nature of mentoring network of single mothers with dependent children and to show the mentoring network effect on mentoring function and empowerment applying social network approach. 439 single mothers with dependent children in Busan and Gyeongsangnam-do have been surveyed about mentoring network properties. The results are 1. The mentoring relationships between single mothers have been shown in various size and relationship characters. The out-degree of Their network is low, the range is narrow, and the tie-strength is weak. 2. When the effect of mentoring network characteristics on mentoring function has been analyzed, in career functions, the range of network and the strength of relationships are represented as significant variables among the mentoring network characteristics, in psychosocial functions, the size of network and the strength of relationships are shown as significant variables, and the inverted-U-shaped relationship according to the size of network has not been revealed. In role modeling function only the size of network is represented as a significant variable. 3. The direct effect of mentoring network of single mothers with dependent children has not been much on empowerment and the career related function among mentoring functions has been revealed as the variable, which affect on empowerment. Based on these results the suggestions and implementations are mentioned in this paper.

• The KIPS Transactions:PartA
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• v.15A no.6
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• pp.345-350
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• 2008

Recently, a HyperStar network HS(2n,n) has been introduced as a new interconnection network of new topology for parallel processing. HyperStar network has properties of hypercube and star graph, further improve the network cost of a hypercube with the same number of nodes. In this paper, we show a construction algorithm of edge-disjoint spanning trees in HyperStar network HS(2n,n). Also, we prove that edge-disjoint spanning tree by the algorithm is optimal.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.178-188
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• 2009

A blog is a personal website where its owner publishes his/her articles for others. A blog can have relationships with other blogs. In this paper, we define a network that is composed of blogs connected together with such relationships as a blog network. Blog networks can have two different propensities characterized by the articles published in the blogs: information-valued propensity and friendship-valued propensity. The degree of each propensity of a blog network plays an important role in deciding business policies for blog networks. In this paper, we address the problem of determining the degrees of two propensities of a given blog network. First, we determine the degree of the propensity of every relationship, a basic unit of a blog network, by using classification that is one of data mining functionalities. Then, by utilizing the result thus obtained, we compute the degrees of two propensities of the whole blog network. Also, we propose a method to solve the problem that the degree of propensities depends on the size of blog networks. To verify the superiority of the proposed approach, we perform extensive experiments using a huge volume of real-world blog data. The results show that our approach provides high accuracy of around 93% in determining the degrees of both propensities of relationships between arbitrary two blogs. We also verify the applicability of the proposed approach by showing that if determines the degrees of the information-valued and friendship-valued propensities correctly in real-world blog networks.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.111-114
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• 2002

임베딩은 어떤 연결망이 다른 연결망 구조에 포함 혹은 어떻게 연관되어 있는지를 알아보기 위해 어떤 특정한 연결망을 다른 연결망에 사상하는 것으로, 특정한 연결망에서 사용하던 여러 가지 알고리즘을 다른 연결망에서 효율적으로 이용할 수 있도록 한다. 본 논문에서는 $2^{2n-k}\times2^k$ 토러스를 HFN(n,n)에 연장율 3, 밀집율 4 로 임베딩 가능함을 보이고, HFN(n,n)을 $2^{2n-k}\times2^k$ 토러스에 연장율 O(N)으로 임베딩됨을 보인다($N=2^n$).

• The Journal of Korean Association of Computer Education
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• v.17 no.2
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• pp.115-124
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• 2014

Hypercube and star graph are widely known as interconnection network. The embedding of an interconnection network is a mapping of a network G into other network H. The possibility of embedding interconnection network G into H with a low cost, has an advantage of efficient algorithms usage in network H, which was developed in network G. In this paper, we provide an embedding algorithm between HCN and HON. HCN(n,n) can be embedded into HON($C_{n+1},C_{n+1}$) with dilation 3 and HON($C_d,C_d$) can be embedded into HCN(2d-1,2d-1) with dilation O(d). Also, star graph can be embedded to half pancake's value of dilation 11, expansion 1, and average dilation 8. Thus, the result means that various algorithms designed for HCN and Star graph can be efficiently executed on HON and half pancake, respectively.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.7
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• pp.318-326
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• 2008

In this paper, we will analyze embedding among Folded Hypercube, Even Network and Odd Network to further improve the network cost of Hypercube. We will show Folded Hypercube $FQ_n$ can be embedded into Even Network $E_{n-1}$ with dilation 2, congestion 1 and Even Network $E_d$ can be embedded into Folded Hypercube $FQ_{2d-3}$ with dilation 1. Also, we will prove Folded Hypercube $FQ_n$ can be embedded into Odd Network $O_{n-1}$ with dilation 2, congestion 1 and Odd Network $O_d$ can be embedded into Folded Hypercube $FQ_{2d-3}$ with dilation 2, congestion 1. Finally, we will show Even Network $E_d$ can be embedded into Odd Network $O_d$ with dilation 2, congestion 1 and Odd Network $O_d$ can be embedded into Folded Hypercube $E_{d-1}$ with dilation 2, congestion 1.

• ETRI Journal
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• v.14 no.1
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• pp.118-125
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• 1992

다중 컴퓨터 연결망의 성능은 그 위상에 따라 크게 좌우되는데 현재까지 연구된 많은 연결망중에서 특히 하이퍼큐브 연결망은 노드수에 비해 비교적 적은 차수와 지름을 갖고 symmetric 하며 순환적 구성 (recursive decomposition structure) 특성을 갖고 있어 여러가지 알고리즘의 사상이 용이하여 많이 사용되고 있다. 여기서는 $Akers^2$ 등에 의해 제안되어 스타 그래프 (star graph) 에 대해 성능분석을 하였다. 분석 척도로는 노드간 평균거리를 사용하였으며 메시지 분포는 $Reed^(1)$가 사용한 분포를 사용하였다. 분석결과 스타 그래프 연결망은 하이퍼큐브와 비슷한 성능을 보였으며 노드 수가 많아질수록 더 나은 성능을 보였다.

• Information and Communications Magazine
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• v.29 no.5
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• pp.37-41
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• 2012

본고에서는 수많은 구성요소가 하나의 계를 이루면서 단순하지 않은 방식으로 서로 얽혀있는 상호작용을 하는 복잡계 연결망에서의 정보 확산에 관한 연구 동향을 살펴보고자 한다. 특히 복잡계 연결망 이론은 실생활에서 나타나는 다양한 연결구조와 이와 관련된 사회현상을 자연과학의 이론을 통해 분석 및 해석하는 분야로, 다양한 학제간의 융합연구로 각광받고 있다. 특히 복잡계 연결망의 최근 연구 결과를 비롯하여 실생활에 존재하는 다양한 대용량 자료를 활용한 사회 동역학과 정보 확산에 관한 최근 연구 동향 분석을 통해 재해의 확산 및 재난 상황에서의 행동 양상 형성 및 전파 등의 연구에 활용하고자 한다.