• 대한상한금궤의학회지
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• 제10권1호
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• pp.47-55
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• 2018

Objective : This case report presents the effect of Galgunhwangryunhwanggum-tang and Galgunhwangryunhwanggum-tang gagambang on hypertension. The patient was diagnosed with Taeyang-byung based on Shanghanlun provisions. Methods : According to Shanghanlun seven meridian patterns diagnostic system, we diagnosed the patient as Taeyang-byung and he has been suffering from hypertension. The patient was treated with Galgunhwangryunhwanggum-tang & Galgunhwangryunhwanggum-tang gagambang and it was provided for 40days Results : After the treatment, the degree of hypertension reduced from BP 138-90 to 130-80 Conclusions : This case study show an effectiveness of using Galgunhwangryunhwanggumtang and Galgunhwangryunhwanggum-tang gagambang according to Diagnostic system based on Shanghanlun provisions on hypertension.

• 대한상한금궤의학회지
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• 제10권1호
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• pp.57-67
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• 2018

Objective : This case report presents the effect of Daecheongryong-tang on Impulse Control Disorder. The patient was diagnosed with Taeyang-byung based on Shanghanlun provisions. Methods : According to Shanghanlun six meridian patterns diagnostic system, we diagnosed the patient as Taeyang-byung and she has been suffering from impulse control disorder. The patient was treated with Daecheongryong-tang. And it was provided for 60 days.The changing symptom was estimated by Global Assessment of Functioning and Visual Analogue Scale. Results : After the treatment, the patient's functioning got better from 65 to 85 on GAF. And the degree of pain was reduced from 10 to 2 on VAS. Conclusions :This case study shows an effectiveness of using Daecheongryong-tang according to Diagnostic system based on Shanghanlun provisions on Impulse Control Disorder.

• 지능정보연구
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• 제8권1호
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• pp.1-13
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• 2002

비상장기업이나 신규상장기업의 경우 주식거래량과 거래가격이 없거나 불충분하므로 최근 활발히 연구되고 있는 VaR(Value-at-Risk)를 파악하지 못한다. 본 연구에서는 비상장기업 및 신규상장기업의 미래 가격위험의 척도인 VaR를 추정하는 방법론을 제시하고, 이를 시스템(VAS-CBR)으로 구현하였다. 구체적으로는 사례기반추론(Case Based Reasoning: CBR) 기법을 이용하여 기존의 상장회사들 중에서 신규 및 비상장기업과 유사한 재무적, 비재무적 특성을 갖는 상장기업을 찾아내고, 유사기업의 VaR를 근거로 신규 및 비상장기업의 VaR를 간접적으로 추정하였다. 또한 개발 시스템의 예측력 제고를 위한 운용방안 및 시스템의 예측력을 실험을 통하여 밝혔다.

• 대한상한금궤의학회지
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• 제10권1호
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• pp.115-124
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• 2018

Objective : The purpose of this paper is to report the improvements of a patient who has suffered from aftereffects following stroke such as dysgraphia and articulation disorder, which is treated by herbal medication based on Shanghanlun disease pattern identification diagnostic system. Methods : According to 'Disease Pattern Identification Diagnostic System based on Shanghanlun Provisions', the patient was diagnosed as Taeyang-byung Gyeolhyung and number 138 provision, and was administered Sohamhyung-tang for 90 days. We recorded the progress of improvements based on the patient's statement and documented the patient's writing Results : The patient can write the letters such as U, 2, ㄹ,ㅇ more clearly and become confident on both writing and speaking. Conclusions : This case shows the effects of Sohamhyung-tang on aftereffects following stroke such as dysgraphia and articulation disorder. It was induced according to the 'Disease Pattern Identification Diagnostic System based on Shanghanlun Provisions' so that it suggest a potential interpretation, which is different with it of the text books Herbal Formula Science and Sanghallonjeonghae, on the provision no. 138. Also the usage of Sohamhyung-tang in this case may support the way far from the diagnosis of oriental neurological medicine, which explain the pathology of stroke as fire-heat(火熱), dampness-phlegm(濕痰), static blood(瘀血) and dual deficiency of qi and blood(氣血兩虛).

• 지능정보연구
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• 제17권3호
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• pp.43-61
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• 2011

본 연구는 사용자의 정적, 외부환경과 연관된 동적 상황정보와 사회적 관계와 연관된 개인적 상황정보들을 의사결정 요소로서 고려한 의사결정의 동적 변환(Dynamic Adaptation)을 제안한다. 즉, 의사결정자의 정적, 외재적 정보보다 과거의 경험, 주관적 선호도 및 사회적 관계와 연관된 상황정보(Social Context)를 의사결정에 동적으로 반영하고 동시에 의사결정 해의 사용시점에서의 가용성에 따라 유용 가능한 대안을 추출하는 방법론을 제안하고자 한다. 이를 위해, 정적, 외재적 및 사회적 상황정보를 이용하여 의사결정 추론한다. 추론은 의사결정자의 과거 경험에 기반한 사례기반 추론과 해당 의사결정 결과가 가용하지 않을 경우 수정을 위한 제약식 만족추론으로 이루어진다. 이를 위해 개인적 경험 등의 정보에 기반한 '문제상황 온톨로지'(Problem Context Ontology)와 집단의 경험적 지식에 기반한 '솔루션 온톨로지'(Solution Ontology)를 구축하였다. 의사결정단계는 상황정보 인식 및 문제상황 온톨로지에 매핑하는 단계, 경험적 사례로부터 문제상황에 가장 적합한 사례를 선택하는 단계, 생성된 솔루션이 가용하지 않을 경우 솔루션 온톨로지와 제약식 만족추론을 통해 새로운 대안을 생성하는 단계로 이루어진다. 본 방법론을 모임에 적합한 식당을 제안하는 예제를 적용함으로써 타당성을 검증하였다. 또한 실험을 통해 사회적 상황정보를 고려하여 생성된 의사결정대안이 그렇지 않은 경우보다 의사결정자의 만족도를 향상시켰으며, 생성된 의사결정대안이 가용하지 않은 경우 제약조건식과 솔루션 온톨로지를 이용해 생성한 대안이 유의미함을 검증하였다.

• 한국정보시스템학회지:정보시스템연구
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• 제26권3호
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• pp.63-90
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• 2017

Purpose This study proposes a novel system trading model using case-based reasoning (CBR) based on absolute similarity threshold. The proposed model is designed to optimize the absolute similarity threshold, feature selection, and instance selection of CBR by using genetic algorithm (GA). With these mechanisms, it enables us to yield higher returns from stock market trading. Design/Methodology/Approach The proposed CBR model uses the absolute similarity threshold varying from 0 to 1, which serves as a criterion for selecting appropriate neighbors in the nearest neighbor (NN) algorithm. Since it determines the nearest neighbors on an absolute basis, it fails to select the appropriate neighbors from time to time. In system trading, it is interpreted as the signal of 'hold'. That is, the system trading model proposed in this study makes trading decisions such as 'buy' or 'sell' only if the model produces a clear signal for stock market prediction. Also, in order to improve the prediction accuracy and the rate of return, the proposed model adopts optimal feature selection and instance selection, which are known to be very effective in enhancing the performance of CBR. To validate the usefulness of the proposed model, we applied it to the index trading of KOSPI200 from 2009 to 2016. Findings Experimental results showed that the proposed model with optimal feature or instance selection could yield higher returns compared to the benchmark as well as the various comparison models (including logistic regression, multiple discriminant analysis, artificial neural network, support vector machine, and traditional CBR). In particular, the proposed model with optimal instance selection showed the best rate of return among all the models. This implies that the application of CBR with the absolute similarity threshold as well as the optimal instance selection may be effective in system trading from the perspective of returns.

• 전자공학회논문지CI
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• 제48권5호
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• pp.49-54
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• 2011

사례기반 추론(Case-Based Reasoning, CBR)은 새로운 문제가 주어질 때 과거의 유사한 문제해결 사례를 기반으로 그 해법을 적절히 변용함으로써 새로운 문제에 적합한 해결책을 효율적으로 도출하고자 하는 문제해결 방법으로 인간이 문제를 해결해 나가는 절차와 매우 유사하여 일상생활 속에 널리 사용되고 있다. 본 연구에서는 이러한 사례기반 추론을 국방 전술 시스템에 적용하여, 전투행위 시 과거의 유사한 사례를 기반으로 현재의 상황에 가장 적절한 전술을 사용할 수 있도록 하는 시스템을 설계하고자 한다. 국방 전술 시스템의 경우, 분대원(Non-Player Character, NPC)들이 모여 분대 규모의 작전을 수행할때, 분대는 최종 목표에 도달하기 위해 정해진 작전에 따라서 행동하게 된다. 이 과정에서 공격, 매복, 전술적 이동 등의 행위를 위한 전술이 구성되어야 한다. 다시 말해 주변 환경, 엄폐물의 위치, 적의 위치에 따라 상황에 맞는 새로운 전술이 필요하며 이러한 전술은 분대장 혹은 소대장 등이 교범에서 배운 과정과 경험에서 축적된 지식을 토대로 생성된다. 본 연구는 사례기반 추론을 사용하여 각 지휘통제 에이전트를 통해 정보가 전달되면 사례기반 데이터베이스에 저장되어 있는 사례와 유사도를 측정하고 가장 적절한 사례를 선택하여 사용하며 새로운 사례는 사례 데이터베이스에 저장하여 다음 번 사례검색 시 사용될 수 있도록 시스템을 설계한다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2003년도 춘계학술대회
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• pp.338-346
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• 2003

Information Technology (IT) and the internet have been major drivers the changes in all aspects of the business processes and activities. They have brought major changes to the financial statements audit environment as well, which in turn has required modifications in audit procedures. There exist, however, certain difficulties with current audit procedures especially for the assessment of the level of control risk. This assessment is primarily based on the auditors' professional judgment and experiences, not based on the objective hies or criteria. To overcome these difficulties, this paper proposes a prototype decision support model named CRAS-CBR using case based reasoning (CBR) to support auditors in making their professional judgment on the assessment of the level of control risk of the general accounting system in the manufacturing industry. To validate the performance, we compare our proposed model with benchmark performances in terms of classification accuracy for the level of control risk. Our experimental results showed CRAS-CBR outperforms a statistical model (MDA) and staff auditor performance in average hit ratio.

• 대한상한금궤의학회지
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• 제11권1호
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• pp.125-138
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• 2019

Objective : This study was intended to evaluate if treatment with Osuyu-Tang following the disease pattern identification diagnostic system based on Shanghanlun provisions (DPIDS) worked analyzing the progress of patients with migraine and restless legs syndrome and to reinterpret the provision of 309 Soyinbing Osuyu-Tang based on the analysis of whether it worked. Methods : Two cases treated with Soyinbing Osuyu-Tang were analyzed using DPIDS. The migraine and restless legs syndrome in both cases were evaluated using the migraine disability assessment (MIDAS) and the Korean versions of the international restless legs scale (K-IRLS), respectively. Results : In the first case, during 45 days of treatment, the MIDAS decreased from 10 days to 3 days. In the second case, during 30 days of treatment, the K-IRLS decreased from 30 to 9. In both cases, Soyinbing was associated with the disease, although the activity was less; and Leng (冷) was associated with numbness in the kneeling position. Conclusions : It was confirmed that treatment with Osuyu-Tang was effective against migraine and restless legs syndrome and that Leng could be associated with numbness in the kneeling position. The etymological analysis of the Shanghanlun characters suggested the possibility of further clarifying the clinical significance and interpretation of Shanghanlun.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2006년도 춘계학술대회
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• pp.327-335
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• 2006

Case Based Reasoning (CBR) has come to be considered as an appropriate technique for diagnosis, prognosis and prescription in medicine. However, canventional CBR has a limitation in that it cannot incorporate asymmetric misclassification cast. It assumes that the cast of type1 error and type2 error are the same, so it cannot be modified according ta the error cast of each type. This problem provides major disincentive to apply conventional CBR ta many real world cases that have different casts associated with different types of error. Medical diagnosis is an important example. In this paper we suggest the new knowledge extraction technique called Cast-Sensitive Case Based Reasoning (CSCBR) that can incorporate unequal misclassification cast. The main idea involves a dynamic adaptation of the optimal classification boundary paint and the number of neighbors that minimize the tatol misclassification cast according ta the error casts. Our technique uses a genetic algorithm (GA) for finding these two feature vectors of CSCBR. We apply this new method ta diabetes datasets and compare the results with those of the cast-sensitive methods, C5.0 and CART. The results of this paper shaw that the proposed technique outperforms other methods and overcomes the limitation of conventional CBR.