• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.387-392
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• 2002

A portable mould oscillation analyzer with an integrated computer, developed by POSCO, records the movement of the mould in every spatial direction. The system uses the gap sensors to measure the mould movement (displacement) in two horizontal directions according to the mould narrow and broad faces and the vertical strokes in the four corners of mould. The gap sensor is a non-contacting minute displacement-measuring device using the principle of high frequency eddy current loss. The mould oscillation diagnostic system integrates the gap sensors, their converters and the industrial portable computer with plug-in data acquisition boards. In an own expert module, which is included in the diagnosis program, one can obtain much information about the mould oscillation equipment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.323-331
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• 1995

The role of equipment maintenance in manufacturing becomes important. As a method of overcoming this problems, diagnostic expert system has been introduced. If such a system is, however, based on the troubleshooter's knowledge, many difficult cases are occured in the real process of diagnosis using that kind of system. This paper suggests to use the designer's knowledge for diagnosing the malfunctions of production equipments. To do that, a method of knowledge represen-tation is also proposed, which is based on the concept of boundary factors. In addition, the disorder propagation in considered. As a results, one can simplify the process of reasoning and inspection.

• The Journal of Korean Medicine
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• v.17 no.1 s.31
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• pp.302-328
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• 1996

I . Objective and significance of the study To design a data acquisition chart, which facilitates data collection and analysis. The chart is also useful for solving problems that arise from personal variations in clinical symptoms and filling the knowledge base of an expert system. II. Content and scope 1. Collect the diagnosis knowledge of cerebrovacular diseases from doctors and analyze it. 2. Design a data acquisition chart. 3. Compare ODS and doctors with respect to their diagnosis results 4. Select patients who are determined to suffer from cerebrovascular diseases using CT(computed tomographic) scan, collect clinical data from them. III. Results and Application The chart be used for data collection and analysis in different medical hospitals, The results of data analysis facilitates collecting clinical data about other diseases and implementing the knowledge base. Also, the collected data serves as a tool for medical education, and cooperative diagnosis of oriental and western medical doctors.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1997.04a
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• pp.224-231
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• 1997

Microscopic examination for the morphological estimation of wear debris on the oil-lubrcated moving system is an accepted method for machine condition and fault diagnosis. However wear particle anaysis has not been widely accepted industry because it is dependent on expert interpretation of particle morphology and relies on subjective assessment criteria. This paper was undertaken to estimate the morphology of wear debris on the oil-lubricated movig system by computer image analysis. The wear test was performed under different sliding conditions using a wear test device made in our laboratory and wear testing specimen of the pin-on-disk-type was rubbed in pararline series base oil. In order to describe characteristics of debris of various shape and size, four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) have been developed and outlined in the paper. A system using such techniques promises to obviate the need for subjective, human interpretation of particle morphology in machine condition monitoring.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.4
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• pp.255-260
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• 2018

In recent years, increasing electricity use has led to considerable interest in green energy. In order to effectively supply, cut off, and operate an electric power system, many electric power facilities such as gas insulation switch (GIS), cable, and large substation facilities with higher densities are being developed to meet demand. However, because of the increased use of aging electric power facilities, safety problems are emerging. Electromagnetic wave and leakage current detection are mainly used as sensing methods to detect live-line partial discharges. Although electromagnetic sensors are excellent at providing an initial diagnosis and very reliable, it is difficult to precisely determine the fault point, while leakage current sensors require a connection to the ground line and are very vulnerable to line noise. The partial discharge characteristic in particular is accompanied by statistical irregularity, and it has been reported that proper statistical processing of data is very important. Therefore, in this paper, we present the results of analyzing ${\Phi}-q-n$ cluster distributions of partial discharge characteristics by using K-means clustering to develop an expert partial discharge diagnosis system generated in a GIS facility.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.703-715
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• 2017

Mammogram images are sensitive in nature and even a minor change in the environment affects the quality of the images. Due to the lack of expert radiologists, it is difficult to interpret the mammogram images. In this paper an algorithm is proposed for a computer-aided diagnosis system, which is based on the wavelet based adaptive sigmoid function. The cascade feed-forward back propagation technique has been used for training and testing purposes. Due to the poor contrast in digital mammogram images it is difficult to process the images directly. Thus, the images were first processed using the wavelet based adaptive sigmoid function and then the suspicious regions were selected to extract the features. A combination of texture features and gray-level co-occurrence matrix features were extracted and used for training and testing purposes. The system was trained with 150 images, while a total 100 mammogram images were used for testing. A classification accuracy of more than 95% was obtained with our proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.111-114
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• 2004

Management of human knowledge is an interesting concept that has attracted the attention of philosophers for thousands of years. Artificial intelligence and knowledge engineering has provided some degree of rigor to the study of knowledge systems and expert systems(ES) re able to use knowledge to solve the problems and answer questions. Therefore, the process of conceptualization and inference of knowledge are fundamental problem solving activities and hence, are essential activities for solving the problem of software ES construction Especially, the access to relevant, up-to-date and reliable knowledge is very important task in the daily work of physicians and nurses. In this study, we propose the conceptualization and inference mechanism for implicit knowledge management in medical diagnosis area. To this purpose, we combined the dynamic knowledge map(KM) and relational database(RDB) into a dynamic knowledge map(DKM). A graphical user-interface of DKM allows the conceptualization of the implicit knowledge of medical experts. After the conceptualization of implicit knowledge, we developed an RDB-based inference mechanism and prototype software ES to access and retrieve the implicit knowledge stored in RDB. Our proposed system allows the fast comfortable access to relevant knowledge fitting to the demands of the current task.

• Journal of Korean Academy of Nursing
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• v.23 no.4
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• pp.569-584
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• 1993

This study was done to verify validity of nursing diagnoses related to difficulty in respiratory function. First, content validity was examined by an expert group considering the etiology and the signs / symptoms of three nursing diagnoses - ineffective airway clearance, ineffective breathing pattern, impaired gas exchange. Second, clinical validity was examined by comparing the frequencies of the etiologies and signs / symptoms of the three nursing diagnoses in clinical case studies with the results of the content validity. This study was a descriptive study. The sample consisted of 23 experts (professors, head nurses and clinical instructors) who had had a variety of experiences using nursing diagnoses in clinical practice, and 102 case reports done by senior student nurses of the college of nursing of Y-university. These reports were part of their clinical practice in the ICU. The instrument used for this study was a checklist for etiologies and signs and symptoms based on the literature, Doenges and Moorhouse (1988), Kim, McFarland, McLane (1991), Lee Won Hee et al. (1987), Kim Cho Ja et at. (1988). The data was collected over four month period from May 1992 to Aug. 1992. Data were analyzed using frequencies done with the SPSS / PC＋ package. The results of this study are summarized as follows : 1. General Characteristics of the Expert Group A bachelor degree was held by 43.5% and a master or doctoral degree by 56.5% of the expert group. The average age of the expert group was 35.3 years. Their average clinical experience was 9.3 years and their average experience in clinical practice was 5.9 years. The general characteristics of the patients showed that there were more women than men, that the age range was from 1 to over 80. Most of their medical diagnoses were diagnoses related to the respiratory. system, circulation or neurologic system, and 50% or more of them had a ventilator with intubation or a tracheostomy. The number of cases for each nursing diagnoses was : · Ineffective airway clearance, 92 cases. · Ineffective breathing pattern, 18 cases. · Impaired gas exchange, 22 cases. 2. The opinion of the expert group as to the classification of the etiology, and signs and symptoms of the three nursing diagnoses was as follows : · In 31.8% of the cases the classification of etiology was clear. · In 22.7%, the classification of signs and symptoms was clear. · In 17.4%, the classification of nursing interventions was clear. 3. In the expert group 80% or mere agreed to ‘dysp-nea’as a common sign and symptom of the three nursing diagnoses. The distinguishing signs and symptoms of (Ineffective airway clearance) were ‘sputum’, ‘cough’, ‘abnormal respiratory sounds : rales’. The distinguishing sings and symptoms of (Ineffective breathing pattern) were ‘tachypnea’, ‘use of accessory muscle of respiration’, ‘orthopnea’ and for (Impaired gas exchange) it was ‘abnormal arterial blood gas’, 4. The distribution of etiology, and signs and symptoms of the three nursing diagnoses was as follows : · There was a high frequency of ‘increased secretion from the bronchus and trachea’ in both the expert group and the case reports as the etiology of ineffective airway clearance. · For the etiologies for ineffective breathing pat-tern, ‘rain’, ‘anxiety’, ‘fear’, ‘obstructions of the tract, ca and bronchus’ had a high ratio in the ex-pert group and ‘decreased expansion of lung’ in the case reports. · For the etiologies for impaired gas exchanges, ‘altered oxygen -carrying capacity of the blood’ and ‘excess accumulation of interstitial fluid in lung’ had a high ratio in the expert group and ‘altered oxygen supply’ in the case reports. · For signs and symptoms for ineffective airway clearance, ‘dyspnea’, ‘altered amount and character of sputum’ were included by 100% of the expert group. ‘Abnormal respiratory. sound(rate, rhonchi)’ were included by a high ratio of the expert group. · For the signs and symptoms for ineffective breathing pattern. ‘dyspnea’, ‘shortness of breath’ were included by 100% of the expert group. In the case reports, ‘dyspnea’ and ‘tachypnea’ were reported as signs and symptoms. · For the sign and symptoms for impaired gas exchange, ‘hypoxia’ and ‘cyanosis’ had a high ratio in the expert group. In the case report, ‘hypercapnia’, ‘hypoxia’ and ‘inability to remove secretions’ were reported as signs and symptoms. In summary, the similarity of the etiologies and signs and symptoms of the three nursing diagnoses related to difficulty in respiratory function makes it difficult to distinguish among them But the clinical validity of three nursing diagnoses was established through this study, and at last one sign and symp-tom was defined for each diagnosis.

• Korean Journal of Cognitive Science
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• v.9 no.1
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• pp.31-39
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• 1998

This paper describes an electronic performance support system called HELPS(Handler Electronic Learning Performence Support) for semiconductor testing e equipment. The purpose of this system is to improve productivity of operators by providing just-in-time, on-the-job, mutimedia-based system information for operational support, training, and knowledge-based trouble shooting and repair. HELPS is composed of a operation module and a trouble shooting module. The operation module uses multimedia and hypermedia to provide the detailed and easily accessible information about equipment to users. Multimedia incorporate multiple. media forms including still and video images. animations 'texts' graphics. and audio. Hypermedia a are provided through a hierarchical information structure which offers not only specific information which is needed to perform a task to experienced operators. but detailed system guidance and information to novice operators. The trouble shooting module is composed of an integrated mutimedia-supported expert system which assists operators in trouble shooting and equipment repair. After diagnosis through the use of the expert system. multimedia advice is presented to the user in either still images with text or motion sequences with sound HELPS is evaluated in term of training time and trouble shooting and repair time. It improved productivity by saving more than 30% of the total time used without the system. This s system has the potential to improve productivity when it is used with ICAIOntellignet Computer Aided Instruction) and virtual reality.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.367-372
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• 2008

In this paper we proposed a model of a fault diagnosis expert system with high reliability to compare identical well-functioning motors. The purpose of the survey was to determine if any differences exit among these identical motors and to identify exactly what these differences were, if in fact they were found. Using measured data for many identical brushless dc motors, this study attempted to find out whether normal and fault can be classified by each other. Measured data was analyzed using the State Transition Model (STM). Based on a proposed STM method, the effect of a different normal state is minimized and the detection of fault is improved in identical motor system. Experimental results are presented to prove that STM method could be a useful tool for diagnosing the condition of identical BLDE motors.