• 한국안전학회지
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• 제20권3호
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• pp.53-57
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• 2005

This paper presents development of a classification system for an electrical fire investigation. In order to reduce an electrical fires and establish detailed prevention plans, the collection of an electrical fire causes and base data are very important. Based on this data, a new classification system for an electrical fire investigation was developed and the direction to the classification system was suggested by fundamental analysis. All of the collected information is analyzed by bottom-up method. Criteria items which based on base data were categorized to classify items. The classification of items were found out as follows : basic condition fire scene condition, fire sign, fire cause. Particularly, the fire cause category is classified. A new developed classification system for an electrical fire investigation will be used to analyse electrical fires easily and efficiently.

• 한국화재소방학회논문지
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• 제23권2호
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• pp.36-40
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• 2009

본 논문은 전기화재 통계의 신뢰성을 향상시키고 효율적인 전기화재 자료를 수집하기 위한 전기화재 원인분류의 개발에 관한 연구이다. 전기화재에 대한 잘못되거나 편향된 지식은 전기화재에 대한 형태 분류를 바뀌게 한다. 전기화재 원인분석에 있어 화재조사자들이 올바르게 보고서를 작성할 수 있는 표준화된 형식을 개발하는 것이 필요하다. 본 연구에서는 원인들간의 인과관계를 고려한 계층구조로 새롭게 개발된 전기화재 원인분류체계를 제안하였다. 그리고 제안된 분류체계는 전기화재 조사 및 통계에 사용될 수 있으며, 전기화재 진단의 오류를 최소화할 수 있다.

• 한국산학기술학회논문지
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• 제8권3호
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• pp.466-471
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• 2007

전기화재는 전체 화재의 30% 이상을 차지하고 있지만 전기화재 통계의 신뢰성에 대한 검토가 제대로 이루어지지 못하였다. 전기화재는 원인분류 방법 또는 체계의 미흡으로 전기적 요인이 아닌 경우에도 전기화재로 분류되어 높은 점유율을 차지하게 되었고 그로 인한 전기화재 통계의 문제점이 제기되었다. 따라서 기존의 전기화재 원인 분류 방법의 개선을 통해 전기화재 통계의 신뢰성 확보가 필요하다. 본 논문에서는 기존의 전기화재 원인분류에 따른 전기화재 조사 및 통계의 문제점을 분석하였고 새로운 전기화재 원인분류 방법을 제시하였다.

• International Journal of Safety
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• 제6권2호
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• pp.17-21
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• 2007

This paper aims at the statistical analysis of electrical fire and classification of electrical fire causes to collect electrical fires data efficiently. Electrical fire statistics are produced to monitor the number and characteristics of fires attended by fire fighters, including the causes and effects of fire so that action can be taken to reduce the human and financial cost of fire. Electrical fires make up the majority of fires in Korea(including nearly 30% of total fires according to recent figures), The incorrect and biased knowledge for electrical fires changed the classification of certain types of fires, from non-electrical to electrical. It is convenient and required to develop the standardized form that makes, in the assessment of the cause of electrical fires, the fire fighters directly ticking the appropriate box on the fire report form or making an assessment of a text description. Therefore, it is highly recommended to develop electrical fire cause classification and electrical fire assessment on the fire statistics in order to categorize and assess electrical fires exactly. In this paper newly developed electrical fire cause classification structure, which is well-defined hierarchical structure so that there are not any relationship or overlap between cause categories, is suggested. Also fire statistics systems of foreign countries are introduced and compared.

• 한국컴퓨터정보학회논문지
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• 제10권5호
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• pp.77-86
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• 2005

본 논문에서는 분류오차를 추출하고 학습하여 분류성능을 개선하는 LVQ 학습 알고리즘을 설계하였다. 제안된 LVQ학습 알고리즘은 초기기준백터의 학습을 위해 SOM을 이용하고, LVQ 출력뉴런의 부류지정을 위하여 out-star 학습법을 사용하는 학습네트워크이다. 분류오차가 발생되는 패턴백터로 추출하기 위하여 오차유발조건을 제안하였고, 이 조건을 이용하여 분류오차를 유발시키는 입력패턴벡터로 구성되는 패턴백터공간을 구성하여 분류오차가 발생되는 패턴백터를 학습시키므로 분류오차수를 감소시키고, 패턴분류성능을 개선하였다. 제안된 학습알고리즘의 성능을 검증하기 위하여 Fisher의 Iris 데이터와 EMG 데이터를 학습백터 및 시험 백터로 사용하여 시뮬레이션 하였고, 제안된 학습방식의 분류 성능은 기존의 LVQ와 비교되어 기존의 학습방식보다 우수한 분류성공률을 확인하였다.

• 산업공학
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• 제25권2호
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• pp.170-177
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• 2012

Process control is essential to operate the semiconductor process efficiently. This paper consider fault classification of semiconductor based cyclic signal for process control. In general, process signal usually take the different pattern depending on some different cause of fault. If faults can be classified by cause of faults, it could improve the process control through a definite and rapid diagnosis. One of the most important thing is a finding definite diagnosis in fault classification, even-though it is classified several times. This paper proposes the method that one-class classifier classify fault causes as each classes. Hotelling T2 chart, kNNDD(k-Nearest Neighbor Data Description), Distance based Novelty Detection are used to perform the one-class classifier. PCA(Principal Component Analysis) is also used to reduce the data dimension because the length of process signal is too long generally. In experiment, it generates the data based real signal patterns from semiconductor process. The objective of this experiment is to compare between the proposed method and SVM(Support Vector Machine). Most of the experiments' results show that proposed method using Distance based Novelty Detection has a good performance in classification and diagnosis problems.

• 한국안전학회지
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• 제32권5호
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• pp.179-185
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• 2017

Accident analysis is an essential process to make basic data for accident prevention. Most researches depend on survey data and accident statistics to analyze accidents, but these kinds of data are not sufficient for systematic and detailed analysis. We, in this paper, propose an accident classification model that extracts task type, original cause materials, accident type, and the number of deaths from accident reports. The classification model is a support vector machine (SVM) with word occurrence features, and these features are selected based on mutual information. Experiment shows that the proposed model can extract task type, original cause materials, accident type, and the number of deaths with almost 100% accuracy. We also develop an accident ontology to express the information extracted by the classification model. Finally, we illustrate how the proposed classification model and ontology effectively works for the accident analysis. The classification model and ontology are expected to effectively analyze various accidents.

• 혜화의학회지
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• 제9권1호
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• pp.423-442
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• 2000

Objectives : The objectives of this study is to find out the classification methods of the cause of disease and the Acupuncture points on the cough(咳嗽, hae-soo) from the oriental medical literature. The results obtained as follows. Methods : We surveyed the oriental medical books from Hung-Ti-Nei-Ching $\ll$黃帝內經$\gg$ to recent books concerning the Acupuncture therapy for the cough(咳嗽, hae-soo). Results : 1. There are the classification methods of the cause of the cough(咳嗽, hae-soo) by affection by exopathogen and internal injury, by five zang-organs and six fu-organs, by time-belt, and by cold and heat. 2. The acupuncture points at P'yesu(肺兪, BL13), T'aeyon(太淵, LU9), Ch'okt'aek(尺澤, LU5), P'ungmun(風門, BL12), Yolgyol(列缺, LU7), Ch'ondol(天突, CV22), Taech'u(大椎, GV14), Hapkok(合谷, LI4), Kohwang(BL43), T'aegye(太谿, KI3), Chok-samni(足三里, ST36) are most frequently used on the acupuncture therapy for the cough(咳嗽, hae-soo). Conclusions : Among the classification methods of the cause of the cough(咳嗽, hae-soo), the classification methods by affection by exopathogen and internal injury may be most effective and the acupuncture points at Lung meridian(手太陰肺經, LU), Bladder mendian(足太陽膀胱經, BL) are most frequently used on the acupuncture therapy for the cough(咳嗽, hae-soo).

• 동의생리병리학회지
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• 제16권2호
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• pp.209-214
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• 2002

At this paper, I classified ‘tetanus’ in 『DongEuiBoGam』 and studied the concept, causes, symptoms, pathological mechanisms of that disease and then I had a new understanding that concept of tetanus in 『DongEuiBoGam』 is different with concept of tetanus in Western Medicine. In the mean time, I investigated the classification in 「Classification of Korean Standard Cause of Death(Oriental Medicine)」 (1995, The Korean Economic Planning Board), and concluded the concept of tetanus in "DongEuiBoGam".

• 한국안전학회지
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• 제34권3호
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• pp.42-49
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• 2019

This study statistically analyzed the laboratory accidents by investigating 806 laboratory accident survey reports which were officially submitted to government from 2013 to June 2017. After comparing domestic and foreign accident classification criteria, the laboratory accidents were classified using KCD7(Korean Standard Classification of Diseases) and OIICS(Occupational Injury and Illness Classification System) criteria. For the type and part of injury, KCD7 classification criteria was adopted. And, for the cause and occurrence type of accidents, OIICS was adopted to analyze the laboratory accidents. Most of injuries happened to the wrist and hand caused by sharp materials or chemical materials. The analysis of accident cause showed that accidents resulted in medical practice and accidents from handtools and chemical materials such as acid and alkali frequently occurred. The major occurrence types of laboratory accidents was body exposure to the chemical materials such as hydrochloric acid and sulfuric acid. In addition, the accidents resulted in destroy of grasped object or falling object were frequently reported.