• International Journal of Safety
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• 제6권2호
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• pp.27-32
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• 2007

For last several decades with the achievement of fast economic development, the electrical fires occupies over 30 percent of total fire incidents almost every year in Korea and not decreased in spite of much times and efforts. Electrical fire cause diagnostics are to confirm a cause for the fire by examination of fire scene. Cause diagnosis methods haven't been systematized yet, because of limits for available information, investigator's biased knowledge, etc. Therefore, in order to assist the investigators and to find out the exact causes of electrical fires, required is research for an electrical fire cause diagnosis system using DB, computer programming and some mathematical tools. The electrical fire cause diagnosis system has two functions of DB and electrical fire cause diagnosis. The cause diagnosis is conducted by a case-based reasoning on a case base and rule-based reasoning on a rule base. For the diagnosis with high reliability, a mixed reasoning approach of a case-based reasoning and fuzzy rule-based reasoning has been adopted. The electrical fire cause diagnosis system proposes the electrical fire causes inferred from the diagnosis processes, and possibility of the causes as well.

• 한국안전학회지
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• 제21권3호
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• pp.16-21
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• 2006

This paper presents a knowledge-based electrical fire cause diagnosis system using the fuzzy reasoning. The cause diagnosis of electrical fires may be approached either by studying electric facilities or by investigating cause using precision instruments at the fire site. However, cause diagnosis methods for electrical fires haven't been systematized yet. The system focused on database(DB) construction and cause diagnosis can diagnose the causes of electrical fires easily and efficiently. The cause diagnosis system for the electrical fire was implemented with entity-relational DB systems using Access 2000, one of DB development tools. Visual Basic is used as a DB building tool. The inference to confirm fire causes is conducted on the knowledge-based by combined approach of a case-based and a rule-based reasoning. A case-based cause diagnosis is designed to match the newly occurred fire case with the past fire cases stored in a DB by a kind of pattern recognition. The rule-based cause diagnosis includes intelligent objects having fuzzy attributes and rules, and is used for handling knowledge about cause reasoning. A rule-based using a fuzzy reasoning has been adopted. To infer the results from fire signs, a fuzzy operation of Yager sum was adopted. The reasoning is conducted on the rule-based reasoning that a rule-based DB system built with many rules derived from the existing diagnosis methods and the expertise in fire investigation. The cause diagnosis system proposes the causes obtained from the diagnosis process and showed possibility of electrical fire causes.

• 한국안전학회지
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• 제18권1호
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• pp.50-55
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• 2003

This paper presents an intelligent computer system, which can easily diagnose electrical fire causes, without the help of human experts of electrical fires diagnosis. For this system, a database is built with facts and rules driven from real electrical fires, and an intellectual database system which even a beginner can diagnose fire causes has been developed, named as an Electrical Fire Causes Diagnosis System : EFCDS. The database system has adopted, as an inference engine, a mixed reasoning approach which is constituted with the rule-based reasoning and the case-based reasoning. The system for a reasoning model was implemented using Delphi 3, one of program development tools, and Paradox is used as a database building tool. To verify effectiveness and performance of this newly developed diagnosis system, several simulated fire examples were tested and the causes of fire examples were detected effectively by this system. Additional researches will be needed to decide the minimal significant level of the solution and the weighting level of important factors.

• International Journal of Safety
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• 제4권2호
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• pp.12-17
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• 2005

This paper aims at the development of an knowledge base for an electrical fire cause diagnosis system using the entity relation database. The relation database which provides a very simple but powerful way of representing data is widely used. The system focused on database construction and cause diagnosis can diagnose the causes of electrical fires easily and efficiently. In order to store and access to the information concerned with electrical fires, the key index items which identify electrical fires uniquely are derived out. The knowledge base consists of a case base which contains information from the past fires and a rule base with rules from expertise. To implement the knowledge base, Access 2000, one of DB development tools under windows environment and Visual Basic 6.0 are used as a DB building tool. For the reasoning technique, a mixed reasoning approach of a case based inference and a rule based inference has been adopted. Knowledge-based reasoning could present the cause of a newly occurred fire to be diagnosed by searching the knowledge base for reasonable matching. The knowledge-based database has not only searching functions with multiple attributes by using the collected various information(such as fire evidence, structure, and weather of a fire scene), but also more improved diagnosis functions which can be easily wed for the electrical fire cause diagnosis system.

• The Plant Pathology Journal
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• 제34권3호
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• pp.191-198
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• 2018

Fast and accurate diagnosis is needed to eradicate and manage economically important and invasive diseases like fire blight. Loop-mediated isothermal amplification (LAMP) is known as the best on-site diagnostic, because it is fast, highly specific to a target, and less sensitive to inhibitors in samples. In this study, LAMP assay that gives more consistent results for on-site diagnosis of fire blight than the previous developed LAMP assays was developed. Primers for new LAMP assay (named as DS-LAMP) were designed from a histidine-tRNA ligase gene (EAMY_RS32025) of E. amylovora CFBP1430 genome. The DS-LAMP amplified DNA (positive detection) only from genomic DNA of E. amylovora strains, not from either E. pyrifoliae (causing black shoot blight) or from Pseudomonas syringae pv. syringae (causing shoot blight on apple trees). The detection limit of DS-LAMP was 10 cells per LAMP reaction, equivalent to $10^4$ cells per ml of the sample extract. DS-LAMP successfully diagnosed the pathogens on four fire-blight infected apple and pear orchards. In addition, it could distinguish black shoot blight from fire blight. The $B{\ddot{u}}hlmann$-LAMP, developed previously for on-site diagnosis of fire blight, did not give consistent results for specificity to E. amylovora and on-site diagnosis; it gave positive reactions to three strains of E. pyrifoliae and two strains of P. syringae pv. syringae. It also, gave positive reactions to some healthy sample extracts. DS-LAMP, developed in this study, would give more accurate on-site diagnosis of fire blight, especially in the Republic of Korea, where fire blight and black shoot blight coexist.

• 한국안전학회지
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• 제7권4호
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• pp.105-114
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• 1992

This paper presents an study on the knowledge based system for diagnosing the fire causes using the Fuzzy Possibility Measure( FPM ) about the electric-fire ignition. The Ignition values needed for causes diagnosis is computed as FPM for electric-fire ignition based on the internal scale technique that assigns numerically the characteristic difference of facts to the-tin-ear scale. For the convinience of inference, ignition sources are classified into seven types : short, ground fault, leakge of electricity, overcurrent, cord junction overheating, bad Insulation and spark. The system for causes diagnosis of electric-fire is composed of Knowledge Acquisition System, Inference Engine and Man-Machine Interface, The diagnosis system is wrritten in an artificial intelligence langusge “PROLOG” which uses depth-first search and backward chaining schemes in reasoning process.

• 한국화재소방학회논문지
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• 제21권2호
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• pp.42-47
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• 2007

본 연구는 객체 관계형 DB를 이용한 전기화재 원인을 진단할 수 있는 사례기반 시스템을 개발하였다. 시스템은 간편하고 그리고 효율적으로 DB를 구축 및 전기화재의 원인 진단에 중점을 두고 있다. 전기화재와 관련된 정보를 저장하고 접근하기 위해서 전기화재를 분별할 수 있는 주요한 항목들을 도출하였다. 사례기반 시스템은 과거의 전기화재 사례로부터 정보를 추출하여 구성하고, 새롭게 발생된 화재의 원인은 패턴매칭을 통해 사례기반 DB를 검색함으로써 진단될 수 있다. 사례기반 시스템은 수집된 다양한 정보를 이용하여 다중 속성에 대한 검색 기능뿐만 아니라 원인진단을 쉽게 사용될 수 있도록 향상된 진단 기능을 갖고 있다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2017년도 춘계 학술논문 발표대회
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• pp.46-47
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• 2017

Korea rapidly arranged urbanization and overpopulation with high growth of economy and all kinds of decrepit facilities are scattered all over the downtown. If there is a strong wind in fire, fire is rapidly increased by various fire spread factors. And Korea cannot build prediction model of urban fire combustion phenomena because there is no studies that physically explains the suitable flame phenomena for its real state. In this study, based on the Japanese Urban fire simulation to target the traditional market area and suitability of fire risk assessment were reviewed.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2013년도 추계 학술논문 발표대회
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• pp.226-227
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• 2013

Korea rapidly arranged urbanization and overpopulation with high growth of economy and all kinds of decrepit facilities are scattered all over the downtown. If there is a strong wind in fire, fire is rapidly increased by various fire spread factors. And Korea cannot build prediction model of urban fire combustion phenomena because there is no studies that physically explains the suitable flame phenomena for its real state. In this study, based on the Japanese Urban fire simulation to target the building congested Area and suitability of fire risk assessment were reviewed.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2013년도 춘계 학술논문 발표대회
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• pp.87-88
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• 2013

Korea rapidly arranged urbanization and overpopulation with high growth of economy and all kinds of decrepit facilities are scattered all over the downtown. If there is a strong wind in fire, fire is rapidly increased by various fire spread factors. And Korea cannot build prediction model of urban fire combustion phenomena because there is no studies that physically explains the suitable flame phenomena for its real state. In this study, based on the Japanese Urban fire simulation to target the wooden building congested Area and suitability of fire risk assessment were reviewed.