• International Journal of Safety
• /
• v.6 no.2
• /
• pp.27-32
• /
• 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.

• Journal of the Korean Society of Safety
• /
• v.21 no.3 s.75
• /
• pp.16-21
• /
• 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.

• International Journal of Safety
• /
• v.4 no.2
• /
• pp.12-17
• /
• 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.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.2
• /
• pp.159-167
• /
• 2003

This study suggests the hybrid fault diagnosis method of signed digraph (SDG) and partial least squares (PLS). SDG offers a simple and graphical representation for the causal relationships between process variables. The proposed method is based on SDG to utilize the advantage that the model building needs less information than other methods and can be performed automatically. PLS model is built on local cause-effect relationships of each variable in SDG. In addition to the current values of cause variables, the past values of cause and effect variables are inputted to PLS model to represent the Process armies. The measured value and predicted one by dynamic PLS are compared to diagnose the fault. The diagnosis example of CSTR shows the proposed method improves diagnosis resolution and facilitates diagnosis of masked multiple-fault.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2004.10a
• /
• pp.292-297
• /
• 2004

The conventional computerized numerical controller (CNC) of machine tools has been increasingly replaced by a PC-based open architecture CNC (OAC) which is independent of the CNC vendor. The OAC and machine tools with OAC led the convenient environment where it is possible to implement user-defined application programs efficiently within CNC. Tis paper proposes a method of operational fault cause diagnosis which is based on the status of programmable logic controller (PLC) in machine tools with OAC. The operational fault is defined as a disability state occurring during normal operation of machine tools. The faults are occupied by over 70% of all faults and are also unpredictable as most of them occur without any warning. Two diagnosis models, the switching function (SF) and the step switching function (SSF), are propose in order to diagnose the fault cause quickly and exactly. The cause of an occurring fault is logically diagnosed through a fault diagnosis system (FDS) using the diagnosis models. A suitable interface environment between CNC and develope application modules is constructed in order to implement the diagnostic functions in the CNC domain. The diagnosed results were displayed on a CNC monitor for machine operators and provided to a remote site through a web browser. The result of his research could be a model of the fault cause diagnosis and the remote monitoring for machine tools with OAC.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.23 no.9
• /
• pp.91-97
• /
• 2009

We have constructed the it's cause diagnosis system of power cable by Failure Mode Effect Analysis(FMEA) method because we have to cause analysis when the cable accident happened. This system was composed of data input of accident condition, presentation of the shape through pictograph and accident probability by FMEA method. According to each selection, the accident cause comments are showed by the accident occurrence possibility. Also, the verification of the it's diagnosis system through the cause analysis of the cable accident cases, the system agreed well with results that analyzed actual state.

• Fire Science and Engineering
• /
• v.21 no.2 s.66
• /
• pp.42-47
• /
• 2007

This paper presents the development of a case-based system 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 case-based system consists of a case which contains information from the past fires. The case-based system could present the cause of a newly occurred fire to be diagnosed by searching the case-based database for reasonable matching. The case-based system 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 used for the electrical fire cause diagnosis system.

• Nuclear Medicine and Molecular Imaging
• /
• v.41 no.2
• /
• pp.102-111
• /
• 2007

Dementia is a major burden for many countries including South Korea, where life expectancy is continuously growing and the proportion of aged people is rapidly growing. Neurodegenerative disorders, such as, Alzheimer disease, dementia with Lewy bodies, frontotemporal dementia, Parkinson disease, progressive supranuclear palsy, corticobasal degeneration, Huntington disease, can cause dementia, and cerebrovascular disease also can cause dementia. Depression or hypothyroidism also can cause cognitive deficits, but they are reversible by management of underlying cause unlike the forementioned dementias. Therefore these are called pseudodementia. We are entering an era of dementia care that will be based upon the identification of potentially modifiable risk factors and early disease markers, and the application of new drugs postpone progression of dementias or target specific proteins that cause dementia. Efficient pharmacologic treatment of dementia needs not only to distinguish underlying causes of dementia but also to be installed as soon as possible. Therefore, differential diagnosis and early diagnosis of dementia are utmost importance. F-18 FDG PET is useful for clarifying dementing diseases and is also useful for early detection of the diseases. Purpose of this article is to review the current value of FDG PET for dementing diseases including differential diagnosis of dementia and prediction of evolving dementia.

• Journal of Korea Association of Health Promotion
• /
• v.1 no.1
• /
• pp.21-25
• /
• 2003

Vomiting in pediatric patient is frequently encountered problem in emergency room or outpatient clinic. In differential diagnosis, age of the patient or accompanying symptoms should be considered in the differential diagnosis. Accurate diagnosis is very important because surgical treatment is necessary in some of the conditions. Imaging diagnosis of conservative modality such as upper gastrointestinal series or colon study is still important radiological examination in the initial differential diagnosis, but recently ultrasonography offers accurate diagnosis in many situations. The cause of vomiting in pediatric are diverse according to the age group :neonatal sepsis, necrotizing enterocolitis, or hypertrophic pyloric stenosis in neonates : gastroesophageal reflux, viral enteritis, or intussusception in infant: midgut volvulus, appendicitis, metabolic disorders, or increased intracranial pressure also an be the cause. knowledge of radiological findings of normal gastrointestinal tract is important to recognize abnormalities. A discussion of radiological findings in variable surgical conditions to present as vomiting in pediatric patients is offered.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2009.05a
• /
• pp.59-62
• /
• 2009

When happen the electrical facilities accident the one's diagnosis system of fault cause was constructed by FMEA method Cable accident cause is given by accident cause that can happen in each one's diagnosis and accident probability value. From the verification of system, the one's diagnosis system agreed well with result that analyzed actual state. Thus, the system is judged to be used effectively examine for accident cause of electrical facilities.