• 한국지진공학회논문집
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• 제10권2호
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• pp.63-71
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• 2006

동반논문(II-지반분류 개선방법)에서는 지반의 고유주기를 기준으로 지반을 분류하는 방법이 국내 지반조건에 적합한 지반분류 방법으로 제시하였다. 그러나, 지반분류 방법을 개선하여도 해석결과의 평균 스펙트럼 가속도 값과 재산정된 응답스펙트럼과 차이가 나타나는 부분이 존재한다. 이는 설계응답스펙트럼을 작성에 필요한 증폭계수를 계산하는 방법을 변경해야 해결할 수 있다. 본 논문에서는 국내 지반조건에 적합하도록 증폭계수를 재산정하기 위한 적분구간 변경에 대하여 검토하였다. 검토 결과 장주기 영역의 증폭계수 $F_v$의 적분구간은 현재 주기 0.4초${\sim}$2.0초에서 주기 0.4초${\sim}$1.5초로 변경할 경우 해석결과의 평균 스펙트럼 가속도 값과 설계응답스펙트럼이 비교적 잘 일치하는 결과를 얻을 수 있었고, 기존의 방법보다 국내 지반특성에 더 적합한 설계응답스펙트럼을 작성할 수 있었다.

• 기술혁신학회지
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• 제10권3호
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• pp.531-554
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• 2007

본고는 그간 독립적으로 존재해 왔던 학문분류 연구분류 기술분류 산업분류 전공분류 및 취업 분류와 같은 지식활동과 관련된 분류체계를 상호 연계시켜 종합적으로 보는 새로운 모형을 제시하고 그를 구체적으로 구현하는 방법을 다룬 것이다. 중 분야 이상의 의미를 갖는 학문분류와 소 분야 이하의 의미를 갖는 연구분류를 통합시킨 학문/연구분류는, 자체가 연구분야와 적용분야로 구성되는 2차원형이지만, 한편으로는 다양한 기술분류와 산업분류로 연계되고, 다른 한편으로는 전공(교육)분류와 취업분류로 연계된다. 연계시키는 방법은 두 개 이상의 분류체계를 동시에 기재하도록 하고, 그러한 기재를 허용하는 정보시스템과 데이터베이스를 갖추고, 필요에 따라 몇 개의 분류체계를 선택하여 동시에 사용하면 된다. 본고는 새로운 분류체계를 보이고자 한 것이지만 기본적인 의도는 분류체계를 넘어선다. 지식사회의 기본적인 활동인 지식활동을 종합적으로 파악하기 위한 수단을 강구하고자 한 것이다.

• 전자공학회논문지C
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• 제35C권9호
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• pp.73-80
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• 1998

본 논문에서는 금융업무를 위한 오손 지폐 분류 시스템을 구현하였다. 제안한 시스템은 새 돈이 헌 돈으로 변화함에 따라 변하는 과정을 모델화하고 그 특징을 획득하기 위하여 감지센서들을 선택하였다. 센서들로부터 얻어진 데이터에서 4개의 특징벡터를 추출하고, 주성분해석을 통해 구해진 최대 고유벡터만을 이용하여 오손 지폐를 분류한다. 새 돈 또는 헌 돈으로 분류하는 기준 레벨은 사용자에 의해 결정된다. 실험결과에서 제안한 시스템은 초당 8매의 지폐 분류속도와 96%의 분류율을 가지는 신뢰성 있는 시스템임을 보여준다.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.830-839
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• 2017

Support vector machine (SVM) is introduced as an effective fault diagnosis technique based on dissolved gases analysis (DGA) for oil-immersed transformers with maximum generalization ability; however, the applicability of the SVM is highly affected due to the difficulty of selecting the SVM parameters appropriately. Therefore, a novel approach combing SVM with improved imperialist competitive algorithm (IICA) for fault diagnosis of oil-immersed transformers was proposed in the paper. The improved ICA, which is proved to be an effective optimization approach, is employed to optimize the parameters of SVM. Cross validation and normalizations were applied in the training processes of SVM and the trained SVM model with the optimized parameters was established for fault diagnosis of oil-immersed transformers. Three classification benchmark sets were studied based on particle swarm optimization SVM (PSOSVM) and IICASVM with four multiple classification schemes to select the best scheme for transformer fault diagnosis. The results show that the proposed model can obtain higher diagnosis accuracy than other methods. The comparisons confirm that the proposed model is an effective approach for classification problems.

• 한국멀티미디어학회논문지
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• 제23권11호
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• pp.1406-1417
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• 2020

Sounds that have been evaluated to be effective in inducing sleep are helpful to reduce sleep disorders. Generally, several sounds have been verified the effects by brainwave experiments, but it cannot be considered on all users because of individual variation for effects. Moreover, the effectiveness for inducing sleep is not known for all new sounds made by creative activities. Therefore, new classification system is required to collect new effective sounds with considering personal brainwave characteristics. In this paper, we propose a new sound classification method by applying improved MinHash cluster to brain waves. The proposed method will classify them through whether it is effective for sleep care by evaluation his brainwave during listening for each sound. In order to prove effectiveness of the proposed classification method, we conducted accuracy experiment for sleep sound classification using verified sleep induction sound. In addition, we have compared time for existing method and proposed method. The former is scored 85% accuracy in the experiment. We confirmed the latter one that the average processing time was reduced to 70%. It is expected to be one of method for pre-screening whether it is effective when a new sound is introduced as a sound for sleep induction.

• 센서학회지
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• 제18권5호
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• pp.385-392
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• 2009

This paper describes the algorithm development of a new body pressure detection sensor for occupant classification system. U.S. Government has required that advanced airbag system should be installed to every automobiles after 2006 according to FMVSS 208 regulation. Therefore, Occupant Classification System should be provided the passenger with safety in order to protect the infants or children that sit in the front passenger seat. When an occupant sits on the chair of the vehicle, deployment of the airbag depends on passenger's weigh distribution and postures. Authors have been developed a new pattern recognition of passenger and weight distribution at the same time by Force Sensing Resistor for the safety.

• 한국산업보건학회지
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• 제30권3호
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• pp.280-291
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• 2020

Objectives: Hazard classification is a controversial issue in the new MSDS system in which chemical companies have to prepare and submit MSDS for chemicals that they manufacture or import to the competent authorities according to the amended Occupational Safety and Health Act. The aim of this study is to suggest how to apply and manage harmonized hazard classification criteria and results by investigating current hazard classification systems and trends. Methods: The domestic issues about different hazard classification criteria and results were investigated by reviewing the literature and business outcomes regarding KOSHA. We also checked official and unofficial reports from the UN to understand international discussion about the topic. Chemical hazard classification results from agencies providing chemical information were analyzed to compare a harmonized rate between classifications. Furthermore, a field survey of a few chemical companies was conducted. Results: Under the related competent authorities, an integrated standard proposal was developed to harmonize the domestic hazard classification criteria. Although harmonized chemical information is strongly needed, we recognized the uncertainty and difficulty of harmonized hazard classification from the UN global list project review. In practice the harmonization rate of the classification was generally low between the classification in KOSHA, MoE, and EU CLP. Among hazard classes, health hazards largely led the disharmony. The field survey revealed a change of perception that the main body of chemical information production is manufacturers. Approaches and solutions about hazard classification issues differed depending on business size, types of chemical handling, and other factors. Conclusions: We proposed reasonable ways by time and step to apply hazard classification in the new MSDS system. Chemical manufacturers should make and offer chemical information including responsible hazard classifications. The government should primarily accept these classifications, evaluate them by priority, and support or supervise workplaces in order to communicate reliable chemical information.

• 지능정보연구
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• 제15권3호
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• pp.151-165
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• 2009

퍼지신경망 모형은 인공신경망의 네트워크 구조 표현방법 및 학습알고리듬과 퍼지시스템의 추론방법을 통합한 모형으로 제어 및 예측분야에 성공적으로 적용되고 있다. 본 연구에서는 퍼지신경망 모형 중 우수한 예측정확도로 인해 최근 각광받고 있는ANFIS (Adaptive Network-based Fuzzy Inference System)모형을 기반으로 하는 분류모형을 설계하고 기존의 분류기법(C5.0 의사결정나무)과 비교하여 분류 정확성 관점에서 평가한다. ANFIS 추론의 경우, 최종 결과값이 계급값이 아닌 연속형 변수값을 취하게 되므로 산출된 결과값을 이용하여 적절한 계급값을 할당하는 과정이 필요하다. 본 연구에서는 의사결정나무기법을 이용하여 계급값을 할당하는 방식과 군집분석을 이용하여 계급값을 할당하는 두 가지 방식을 제안하고 두 가지 데이터 세트에 적용하여 ANFIS를 기반으로 한 분류모형의 정확도를 평가하였다.

• 한국건축시공학회지
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• 제8권1호
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• pp.63-70
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• 2008

Management process of apartment buildings construction has increased because the after service of construction company meet the needs of customers. Many defect data, which was inspected by construction company or customers before moving into a new apartment house, were classified by field engineers and then communicated to corresponding subcontractors. The classification process needs to be performed by an expert engineer because there is so much data, it is unfeasible to complete in a short period of time. For this classification process, an automatic classification system using case base reasoning (CBR) should be considered. This research proposed a defect management system with automatic classification system using CBR. This constructed defect management system consists of cyber after service system for tenants and the whole defect management process of construction, preservation and management of apartment buildings. This system could improve the efficiency of expert work in terms of time and accuracy, as well as helping laymen users to conduct defect classification work as experts do.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1998년도 추계학술대회
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• pp.255-256
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• 1998

In this paper, we propose the multi-axial classification system using parallel coding method that is systemic and flexible properties for representing dental clinical behavior. The methodology and organization of this thesis as follows. First, an analysis of other classification systems. Second, the domain of medical behavior and axises using selected elements was were determined. Third, the new code system is constructed of these common factors in properties of prediction of hierarchy, brevity, simplicity, flexibility and mnemonic usage. Finally, the framework of classification system for dental was made using multi-axial code system. The result of the this study, the eight bases axis of multi-axial code system is composed and can be basic information of research for construction of classification system of all medical domain.