• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.2 s.117
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• pp.199-205
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• 2007

In this paper, a novel hexagonal-shaped electromagnetic bandgap(EBG) power plane for the suppression of the ground bounce noise(GBN) in high-speed circuits is proposed. The proposed structure consists of hexagonal-shaped unit cells and detoured bridges connecting the unit cells. The hexagonal-shaped unit cells could omni-directionally suppress the GBN in digital circuits. The fabricated power plane's omni-directional -30 dB suppression bandwidth is from 330 MHz to 5.6 GHz. Then the proposed structure suppresses electromagnetic interference(EMI) caused by the GBN within the stopband. As a result, the proposed structure is expected to be conducive solving EMI problem in high-speed circuits.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.2 s.117
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• pp.206-212
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• 2007

In this paper, a novel power/ground plane using the hybrid-cell electromagnetic band-gap(EBG) structure is proposed for the wide-band suppression of the ground bound noise(GBN) or simultaneous switching noise(SSN). The -30 dB stopband of the proposed structure starts from a few hundred MHz where the GBN/SSN energy is dominant. The distinctive features of this new structure are the thin spiral strip line and hybrid-cells. They realize the enhanced inductance and the shorter period of the EBG lattice. As a result, the lower cut-off frequency and bandwidth of the -30 dB stopband becomes lower and wider, respectively. In addition, the proposed structure has smaller number of resonance modes between power/ground planes and performs a low EMI behavior compared with the reference board.

• Journal of Korea Multimedia Society
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• v.16 no.3
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• pp.269-280
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• 2013

In this paper, we suggested the possibility of using an efficient classifier for the dependency analysis of retinal disease. First, we analyzed the classification performance and the prediction accuracy of GBN (General Bayesian Network), GBN with reduced features by Markov Blanket and TAN (Tree-Augmented Naive Bayesian Network) among the various bayesian networks. And then, for the first time, we applied TAN showing high performance to the dependency analysis of the clinical data of retinal disease. As a result of this analysis, it showed applicability in the diagnosis and the prediction of prognosis of retinal disease.

• 대한치주과학회:학술대회논문집
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• 2001.12a
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• pp.67-68
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• 2001

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.1
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• pp.26-35
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• 1995

Bo-Back-N ARQ is widely used in packet networks for error and flow control methanisms. This paper analyzes the network throughput under the go-back-N schem. Contrast to other analytic methods which assume independent frame losses or the first order Markov frame analytic methods which assume independent frame losses or the first order Markov frame losses concoptually, the proposed method takes into account the correlation between successive frame losses in a congested node. Computer simulation shows that our method generates more accurate performance results that independent assumption method. We apply the proposed method to analyze the performance of BWM in high speed networs. Our results show that BWM maintains the independence between traffic streams.

• Management & Information Systems Review
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• v.34 no.5
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• pp.71-92
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• 2015

This study analyzes the impact of Corporate Social Responsibility (CSR) activities on financial performances using Bayesian Network. The research tries to overcome the issues of the uniform assumption of a linear function between financial performance and CSR activities in multiple regression analysis widely used in previous studies. It is required to infer a causal relationship between activities of CSR which have an impact on the financial performances. Identifying the relationship would empower the firms to improve their financial performance by informing the decision makers about the different CSR activities that influence the financial performance of the firms. This research proposes General Bayesian Network (GBN) and presents Markov Blanket induced from GBN. It is empirically demonstrated that all the proposals presented in this study are statistically significant by the results of the research conducted by Korean Economic Justice Institute (KEJI) under Citizen's Coalition for Economic Justice (CCEJ) which investigated approximately 200 companies in Korea based on Korean Economic Justice Institute Index (KEJI index) from 2005 to 2011. The Bayesian Network to effectively infer the properties affecting financial performances through the probabilistic causal relationship. Moreover, I found that there is a causal relationship among CSR activities variable; that is Environment protection is related to Customer protection, Employee satisfaction, and firm size; Soundness is related to Total CSR Evaluation Score, Debt-Assets Ratio. Though the what-if analysis, I suggest to the sensitive factor among the explanatory variables.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.625-634
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• 2002

In this paper, we conducted various experiments with Bayesian networks in order to analyze clinical data of infertility patients. With these experiments, we tried to find out inter-dependencies among important factors playing the key role in clinical pregnancy, and to compare 3 different kinds of Bayesian network classifiers (including NBN, BAN, GBN) in terms of classification performance. As a result of experiments, we found the fact that the most important features playing the key role in clinical pregnancy (Clin) are indication (IND), stimulation, age of female partner (FA), number of ova (ICT), and use of Wallace (ETM), and then discovered inter-dependencies among these features. And we made sure that BAN and GBN, which are more general Bayesian network classifiers permitting inter-dependencies among features, show higher performance than NBN. By comparing Bayesian classifiers based on probabilistic representation and reasoning with other classifiers such as decision trees and k-nearest neighbor methods, we found that the former show higher performance than the latter due to inherent characteristics of clinical domain. finally, we suggested a feature reduction method in which all features except only some ones within Markov blanket of the class node are removed, and investigated by experiments whether such feature reduction can increase the performance of Bayesian classifiers.

• 한국ITS학회:학술대회논문집
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• v.2007 no.10
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• pp.334-337
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• 2007

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11B
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• pp.953-959
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• 2006

This paper provides optimum TCP/IP packet size that maximizes the throughput efficiency of ATM layer as a function of TCP/IP packet length for several values of channel BER over wireless ATM LAN links applying data link error control schemes to reduce error problems encountered in using wireless links. For TCP/IP delay-insensitive traffc requiring reliable delivery, it is necessary to adopt data link layer ARQ protocol. So ARQ error control schemes considered in this paper include GBN ARQ, SR ARQ and type-I Hybrid ARQ, which ARQ is needed, but FEC can be used to reduce the number of retransmissions. Especially adaptive type-I Hybrid ARQ scheme is necessary for a variable channel condition to make the physical layer as SONET-like as possible.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.595-597
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• 2004

본 연구에서는 베이지안망을 기초로 불임환자의 임상 데이터에 대한 다양한 실험을 전개한다. 실험을 통해 임신여부에 영향을 주는 요인들간의 상호 의존성을 분석하고. 또 제약조건이 다른 다양한 베이지안망의 대표적 유형으로 나이브 베이지안망(NBN), 베이지안망으로 확장한 나이브 베이지안망(BAN), 일반 베이지안앙(GBN) 분류기들의 분류성능을 서로 비교 분석한다. 베이지안망을 적응할 때 변수의 수가 많아짐에 따라 베이지안망의 구조를 학습하는데 탐색공간이 넓어져 시간의 요구량이 급격히 많아진다. 따라서 이런 탐색공간을 효율적으로 줄이기 위하여 클래스 노드의 Markov blanket에 속한 특징들로 집합을 축소하는 것을 제안하고, 실험을 통해 이 특징 축소 방법이 베이지안망 분류기들의 성능을 높여 줄 수 있는지 알아본다.