• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.3-3
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• 2003

With biomedical literature expanding so rapidly, there is an urgent need to discover and organize knowledge extracted from texts. Although factual databases contain crucial information the overwhelming amount of new knowledge remains in textual form (e.g. MEDLINE). In addition, new terms are constantly coined as the relationships linking new genes, drugs, proteins etc. As the size of biomedical literature is expanding, more systems are applying a variety of methods to automate the process of knowledge acquisition and management. In my talk, I focus on the project, GENIA, of our group at the University of Tokyo, the objective of which is to construct an information extraction system of protein - protein interaction from abstracts of MEDLINE. The talk includes (1) Techniques we use fDr named entity recognition (1-a) SOHMM (Self-organized HMM) (1-b) Maximum Entropy Model (1-c) Lexicon-based Recognizer (2) Treatment of term variants and acronym finders (3) Event extraction using a full parser (4) Linguistic resources for text mining (GENIA corpus) (4-a) Semantic Tags (4-b) Structural Annotations (4-c) Co-reference tags (4-d) GENIA ontology I will also talk about possible extension of our work that links the findings of molecular biology with clinical findings, and claim that textual based or conceptual based biology would be a viable alternative to system biology that tends to emphasize the role of simulation models in bioinformatics.

• Computers and Concrete
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• 제9권5호
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• pp.389-402
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• 2012

In this study, the modulus of elasticity of low, normal and high strength steel fiber reinforced concrete has been predicted by developing a fuzzy logic model. The fuzzy models were formed as simple rules using only linguistic variables. A fuzzy logic algorithm was devised for estimating the elastic modulus of SFRC from compressive strength. Fibers used in all of the mixes were made of steel, and they were in different volume fractions and aspect ratios. Fiber volume fractions of the concrete mixtures have changed between 0.25%-6%. The results of the proposed approach in this study were compared with the results of equations in standards and codes for elastic modulus of SFRC. Error estimation was also carried out for each approach. In the study, the lowest error deviation was obtained in proposed fuzzy logic approach. The fuzzy logic approach was rather useful to quickly and easily predict the elastic modulus of SFRC.

• Journal of Computing Science and Engineering
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• 제2권2호
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• pp.109-136
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• 2008

In this survey paper, we discuss biomedical ontologies and major text mining techniques applied to biomedicine and healthcare. Biomedical ontologies such as UMLS are currently being adopted in text mining approaches because they provide domain knowledge for text mining approaches. In addition, biomedical ontologies enable us to resolve many linguistic problems when text mining approaches handle biomedical literature. As the first example of text mining, document clustering is surveyed. Because a document set is normally multiple topic, text mining approaches use document clustering as a preprocessing step to group similar documents. Additionally, document clustering is able to inform the biomedical literature searches required for the practice of evidence-based medicine. We introduce Swanson's UnDiscovered Public Knowledge (UDPK) model to generate biomedical hypotheses from biomedical literature such as MEDLINE by discovering novel connections among logically-related biomedical concepts. Another important area of text mining is document classification. Document classification is a valuable tool for biomedical tasks that involve large amounts of text. We survey well-known classification techniques in biomedicine. As the last example of text mining in biomedicine and healthcare, we survey information extraction. Information extraction is the process of scanning text for information relevant to some interest, including extracting entities, relations, and events. We also address techniques and issues of evaluating text mining applications in biomedicine and healthcare.

• 대한음성학회지:말소리
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• 제53호
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• pp.75-92
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• 2005

Prosody Generation Based on C-ToBI Representation for Text-to-SpeechSeungwon Kim, Yu Zheng, Gary Geunbae Lee, Byeongchang KimProsody modeling is critical in developing text-to-speech (TTS) systems where speech synthesis is used to automatically generate natural speech. In this paper, we present a prosody generation architecture based on Chinese Tone and Break Index (C-ToBI) representation. ToBI is a multi-tier representation system based on linguistic knowledge to transcribe events in an utterance. The TTS system which adopts ToBI as an intermediate representation is known to exhibit higher flexibility, modularity and domain/task portability compared with the direct prosody generation TTS systems. However, the cost of corpus preparation is very expensive for practical-level performance because the ToBI labeled corpus has been manually constructed by many prosody experts and normally requires a large amount of data for accurate statistical prosody modeling. This paper proposes a new method which transcribes the C-ToBI labels automatically in Chinese speech. We model Chinese prosody generation as a classification problem and apply conditional Maximum Entropy (ME) classification to this problem. We empirically verify the usefulness of various natural language and phonology features to make well-integrated features for ME framework.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2001년도 학술대회지
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• pp.519-524
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• 2001

국내·외적으로 건설공사의 리스크관리에 대한 중요성은 더욱 커져가고 있지만, 합리적인 리스크인자의 구축방법과 개별 리스크인자의 분석 및 정량화가 용이하지 않기 때문에 실무적 운용이 가능한 리스크분석시스템을 구축한 경우는 극히 미흡한 실정이다. 본 연구에서는 전문가의 주관적 판단과 언어적 변량을 이용하여 리스크를 정량화하기 위한 퍼지분석방법을 제시한다. 본 퍼지분석방법은 건설공사의 리스크인자를 발생확률 발생강도, 발생빈도로 구분하여 평가하게 함으로서 그 적용성과 정확성을 높일 수 있도록 하였고, 언어적 변량을 이용하여 리스크를 정량화하기 때문에 복잡한 자료의 구축과 분석시간을 단축하였으며, 그 적용이 매우 쉽다는 장점을 갖게 된다.

• 대한안전경영과학회지
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• 제16권4호
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• pp.229-236
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• 2014

Failure modes and effects analysis (FMEA) is a widely used engineering tool in the fields of the design of a product or a process to improve its quality or performance by prioritizing potential failure modes in terms of three risk factors-severity, occurrence, and detection. In a classical FMEA, the risk priority number is obtained by multiplying the three values in 10 score scales which are evaluated for the three risk factors. However, the drawbacks of the classical FMEA have been mentioned by many previous researchers. As a way to overcome these difficulties, this paper suggests the ELECTRE III that is a representative technique among outranking models. Furthermore, fuzzy linguistic variables are included to deal with ambiguous and imperfect evaluation process. In addition, when the importances for the three risk factors are obtained, the entropy method is applied. The numerical example which was previously studied by Kutlu and Ekmekio$\breve{g}$lu(2012), who suggested the fuzzy TOPSIS method along with fuzzy AHP, is also adopted so as to be compared with the results of their research. Finally, after comparing the results of this study with that of Kutlu and Ekmekio$\breve{g}$lu(2012), further possible researches are mentioned.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1997년도 가을 학술발표회 논문집
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• pp.24-31
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• 1997

Recently, in Korea, demand for establishment of systematic risk assessment techniques for construction projects has increased, especially after the large construction failures occurred during construction such as New Haengju Bridge construction projects, subway construction projects, gas explosion accidents etc. Most of existing risk analysis modeling techniques such as Event Tree Analysis and Fault Tree Analysis may not be available for realistic risk assessment of construction projects because it is very complex and difficult to estimate occurrence frequency and failure probability precisely due to a lack of data related to the various risks inherent in construction projects like natural disasters, financial and economic risks, political risks, environmental risks as well as design and construction-related risks. Therefor the main objective of this paper is to suggest systematic probabilistic risk assessment model and demonstrate an approach for probabilistic risk assessment using advanced Event Tree Analysis introducing Fuzzy set theory concepts. It may be stated that the Fuzzy Event Tree AnaIysis may be very usefu1 for the systematic and rational risk assessment for real constructions problems because the approach is able to effectively deal with all the related construction risks in terms of the linguistic variables that incorporate systematically expert's experiences and subjective judgement.

• Earthquakes and Structures
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• 제3권5호
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• pp.695-717
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• 2012

Seismic resiliency of new buildings has improved over the years due to better seismic codes and design practices. However, there is still large number of vulnerable and seismically deficient buildings. It is not economically feasible to retrofit and upgrade all vulnerable buildings, thus there is a need for rapid screening tool. Many factors contribute to the damageability of buildings; this makes seismic evaluation a complex multi-criteria decision making problem. Many of these factors are noncommensurable and involve subjectivity in evaluation that highlights the use of fuzzy-based method. In this paper, a risk-based framework earlier proposed by Tesfamariam and Saatcioglu (2008a) is extended using Fuzzy-TOPSIS method and applied to develop an evaluation and ranking scheme for steel buildings. The ranking is based on damageability that can help decision makers interpret the results and take appropriate decision actions. Finally, the application of conceptual model is demonstrated through a case study of 1994 Northridge earthquake data on seismic damage of steel buildings.

• 대한전기학회논문지:전력기술부문A
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• 제48권11호
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• pp.1382-1387
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• 1999

This paper presents an optimal fuzzy power system stabilizer to damp out low frequency oscillation. So far fuzzy controllers have been applied to power system stabilizing controllers due to its excellent properties on the nonlinear systems. But the design process of fuzzy logic power system stabilizer requires empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This paper presents and optimal design method of the fuzzy logic stabilizer using the genetic algorithm. Non-symmetric membership functions are optimally tuned over an evaluation function. The present inputs of fuzzy stabilizer are torque angle error and the change of torque angle error without loss of generality. The coding method used in this paper is concatenated binary mapping. Each linguistic fuzzy variable, defined as the peak of a membership function, is assigned by the mapping from a minimum value to a maximum value using eight bits. The tournament selection and the elitism are used to keep the worthy individuals in the next generation. The proposed system is applied to the one-machine infinite-bus model of a power system, and the results showed a promising possibility.

• 한국지능시스템학회논문지
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• 제17권5호
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• pp.701-706
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• 2007

최근 고층건물의 방진시스템 및 자동차의 현가장치 분야에 MR 유체를 이용한 반능동 진동제어에 관한 연구가 활발히 진행되면서 MR 유체의 밸브모드 특성을 이용한 선형 MR 댐퍼가 널리 사용되고 있다. 그러나 전단모드를 이용한 회전형 MR 댐퍼에 관한 연구는 초기단계에 머물고 있다. 본 연구에서는, 주행로봇의 무한회전형 액츄에이터용 회전형 댐퍼의 진동제어에 관한 연구를 수행하였으며, 퍼지 로직을 기반으로 한 회전형 MR 댐퍼용 진동제어 알고리즘을 제안하였다. 퍼지제어기의 입출력 이득과 멤버쉽 함수의 모양은 유전자 알고리즘을 이용하여 조정하였다. 시뮬레이션 결과는 MR 댐퍼에 충격력이 가해질 때 퍼지 스카이-훅 제어의 제어성능을 보여준다.