• Proceedings of the Korean Institute of Industrial Safety Conference
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• 2003.05a
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• pp.114-119
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• 2003

원자력발전소를 비롯한 위험 시설물의 확률론적 안전성 평가(Probabilistic Safety Assessment: PSA)는 고장수목(Fault Tree) 및 사건수목(Event Tree) 분석으로 이루어지며, 분석 결과로 그 시설물의 위험도(Risk)는 최소단절집합(Minimal Cutsets)들의 합으로 구성 된다.(중략)

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1845-1850
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• 2006

적절한 벤치마킹 대상의 선정은 조직 계획 및 통제에 있어 중요한 요소로 인식되고 있으며, 이에 대한 많은 연구가 이루어져 왔다. 특히, 조직의 상대적 성과 평가와 이를 바탕으로 벤치마킹 대상을 결정하는 DEA(data envelopment analysis)의 출현은 벤치마킹에 대한 연구를 증대시켜왔다. 하지만, 벤치마킹 대상 선정은 기술적 생산 가능성 측면 외에도 조직의 정책적 고려, 관리적 우위 그리고 외부 제약 등을 고려해야 한다. 따라서 수리적 결과에 바탕을 둔 기술적 생산 가능성만을 가지고 벤치마킹 대상을 제공하는 현재의 DEA 접근 방법에는 한계가 있다. 즉, 고려하는 모든 대상을 기반으로 한 global efficiency 관점에서 제공하는 해가 비 효율적 조직 입장에서는 바람직하지 않을 수도 있다. 이에 따라 본 연구에서는 local efficiency 개념을 도입하여, 다양한 관점에서 벤치마킹 대안들을 살펴 볼 수 있는 방법을 제공하고자 한다. 이는 다음과 같은 과정에 의해 수행된다. 먼저, DEA를 이용하여 비교하고자 하는 모든 DMU(decision making unit)의 투입/산출물을 바탕으로 각 DMU의 효율성 값과 비효율적 DMU의 참조집합 (reference set)을 도출한다. 다음으로, 도출된 참조집합이 조직 운영 관점에서 적절한 벤치마킹 대상이며, 이러한 목표를 달성할 수 있는가를 평가한다. 이때 도출된 벤치마킹 대상이 적절하다면 분석과정을 종료하고, 적절하지 않을 경우 다음과 같은 추가적인 분석을 수행한다. 우선, 각 참조 집합을 중심으로 DMU를 그룹핑하고, 각 그룹별로 효율성 값 및 참조집합을 도출한다. 이때 도출된 효율성 값이 local efficiency 값에 해당된다. 다음으로, 참조 집합 그룹을 중심으로 도출된 비효율적 DMU의 참조집합이 적절한 벤치마킹 대상인가를 판단한다. 적절한 벤치마킹 대상을 도출하였으면 분석을 종료하고, 그렇지 않을 경우 적절한 벤치마킹 대상을 도출할 때까지 추가적인 분석과정을 반복한다. 제안한 방법을 통하여 조직은 기술적 생산 가능성 외에도 다양한 조직 운영 관점에서 적절한 벤치마킹 대상을 선정할 수 있으며, 이에 따른 목표를 수립할 수 있을 것으로 기대한다. 또한 더 나아가 global efficiency 관점에서 효율적 조직이 되기 위하여 단계적인 벤치마킹 대상 선정과 이에 따른 목표를 수립하는데도 유용하리라 판단된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.486-492
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• 2019

The system-based approach is needed to select an optimal mix of weapon systems and ship platform among a variety of design alternatives with the uncertainties of the initial required operational capability. In the early-phase design, which included a feasibility study and concept design, it is possible to cause problems when a review of the operational concept, database development, and systematic design are not done, thereby producing uncertain and unstable requirements. To select the best solution without trial-and-error, the U.S. navy has applied the set-based method for the early-phase design of a new ship-to-shore connector. The ship synthesis model plays an important role in applying the set-based method, but only a few countries possess this model and have prohibited this model from being transferred to other countries. This paper suggests a set-based method using a genetic algorithm and decision-making theory through benchmarking existing ship data. The algorithm was verified using the DDG-51 class ship synthesis model to optimize the weapon system design, which has been released for research purposes.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.65-77
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• 2016

As respecting one's privacy becomes an important issue in mobile device data analysis, on-device analysis is getting attention, in which the data analysis is conducted inside a mobile device without sending data from the device to outside. One possible application of the on-device analysis is gender prediction using text data in mobile devices, such as text messages, search keyword, website bookmarks, and contact, which are highly private, and the limited computing power of mobile devices can be addressed by utilizing the word comparison method, where words are selected beforehand and delivered to a mobile device of a user to determine the user's gender by matching mobile text data and the selected words. Moreover, it is known that performing prediction after filtering instances using definite evidences increases accuracy and reduces computational complexity. In this regard, we propose a two-phase approach to on-device gender prediction, where both discriminability and popularity of a word are sequentially considered. The proposed method performs predictions using a few highly discriminative words for all instances and popular words for unclassified instances from the previous prediction. From the experiments conducted on real-world dataset, the proposed method outperformed the compared methods.

• Korean Journal of Construction Engineering and Management
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• v.4 no.4 s.16
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• pp.201-211
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• 2003

Considering about construction projects characteristics, there Is an existing uncertainty which causes inaccuracy or invalidity under decision making situation. Therefore, cost risk analysis of numerous construction projects are Inclined to depend on expert's experiences and subjective judgements. In Korean domestic construction works, however, there is no reasonable method or process for applying subjective elements. Only probabilistic analysis using objective calculation are being used now. This research suggests a cost risk analysis method to analyze quantitatively Cost Impact by risk, and it appraises expert's subjective elements for the purpose of enhancing validity of cost estimation. Moreover, a new cost risk analysis method is introduced for providing convenient user interface in practical business.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.6
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• pp.72-84
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• 2000

The test patterns for path delay faults consist of two patterns. So in order to test the delay faults, a new weight generation algorithm that is different from the weight generation algorithm for stuck-at faults must be applied. When deterministic test patterns for weight calculation are used, the deterministic test patterns must be divided into several subsets, so that Hamming distances between patterns are not too long. But this method makes the number of weight sets too large in delay testing, and may generate inaccurate weights. In this pater, we perform fault simulation without pattern partition. Experimental results for ISCAS 89 benchmark circuits prove the effectiveness of the new weight generation algorithm proposed in this paper.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.11-18
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• 2006

The logical analysis of data(LAD) is a Boolean-logic based data mining tool. A critical step in analyzing data by LAD is the pattern generation stage where useful knowledge and hidden structural information in data is discovered in the form of patterns. A conventional method for pattern generation in LAD is based on term enumeration that renders the generation of higher degree patterns practically impossible. In this paper, we present a novel optimization-based pattern generation methodology and propose two mathematical programming models, a mixed 0-1 integer and linear programming (MILP) formulation and a well-studied set covering problem (SCP) formulation for the generation of optimal and heuristic patterns, respectively. With benchmark datasets, we demonstrate the effectiveness of our models by automatically generating with ease patterns of high complexity that cannot be generated with the conventional approach.

• Spatial Information Research
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• v.7 no.2
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• pp.223-236
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• 1999

Recently, the need of wast incineratory has been recognized. However, the waste incinerator is considered the typical example of NYMB syndrome as a locally unwanted facilities. Therefore, the site selection of waste incineratory should be determined very carefully with consideration of various location factors. The purpose of this study is to provide a new decision-making process model for site selection that provides a rational and a systematic way. The fuzzy set theory and AHP theory, which have merits to overcome uncertainly and complexity of spatial data, are applied to select candidate sites for the waste incineratory. The method is able to produce a more flexible and objective solution for selecting suitability sites in comparison to rigid boolean logic. The result of this study shows that geographic information systems have clear implication for informing the spatial decision making process.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.382-385
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• 2012

이 논문에서는 영상 검색(image retrieval) 및 영상 부류(image categorization)을 위하여 영상을 기술할 때 영상의 클레스(class)별로 서로 다른 주요 특징량(feature)에 가중치 를 주는 방법론을 제안한다. 기존에 연구되어온 영상의 특징량 벡터에 가중치를 주는 방식은 모든 영상 클레스에 대하여 동일하게 가중치를 적용하기 때문에 영상이 클레스별로 서로 다른 특징량이 중요하다는 성질을 이용할 수 없다. 영상이 클레 별로 서로 다른 특징량이 중요하다는 성질을 이용하기 위하여 영상의 클레스별로 특징량 벡터에 서로 다른 가중치 벡터(weight vector)를 학습하였다. 그 후 질의 영상(query image)이 입력되면, 기존의 영상 검색 프레임워크(framework)를 통해 데이터베이 스(database)로 부터 미리 정의된 서브 클레스(sub-class)의 수에 해당하는 영상부 집합(subset)을 만들었다. 그리고 영상부 집합의 특징량 벡터들에 클레스별로 각각 학습된 가중치 벡터를 적용하여 특징량 벡터들 간의 거리를 다시 계산하여 리랭킹(re-ranking)하였다. 이 방법론을 UKBench Dataset에 적용하여 실험을 해보았으며 가중치를 주기 전과 비교 하였을 때 더 높은 정확도를 보였다.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1090-1102
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• 2006

This paper suggests a new algorithm for detecting the plagiarism among a set of source codes, constrained to be functionally equivalent, such are submitted for a programming assignment or for a programming contest problem. The typical algorithms largely exploited up to now are based on Greedy-String Tiling, which seeks for a perfect match of substrings, and analysis of similarity between strings based on the local alignment of the two strings. This paper introduces a new method for detecting the similar interval of the given programs based on an adaptive similarity matrix, each entry of which is the logarithm of the probabilities of the keywords based on the frequencies of them in the given set of programs. We experimented this method using a set of programs submitted for more than 10 real programming contests. According to the experimental results, we can find several advantages of this method compared to the previous one which uses fixed similarity matrix(+1 for match, -1 for mismatch, -2 for gap) and also can find that the adaptive similarity matrix can be used for detecting various plagiarism cases.