• Journal of Physiology & Pathology in Korean Medicine
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• v.19 no.6
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• pp.1471-1474
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• 2005

Sasang constitution medicine is to do different treatment accordining to sasang constitution. Therefore, the constitution diagnosis in the Sasang constitution medicine is very important thing. The Process of Sasang constitution diagnosis Is difficult thing, because of consuming much time, making every effort. It is apt to be subjective tendency. So it need to make objective method. The QSCC II (Questionnaire of Sasang Constitution Classification II ) have several problems- can't do diagnosis of Taeyangin, the accuracy rate of Sasang constitution diagnosis is not high (probably 60%), and so on. So, we need the new methods for the Sasang constitution Diagnosis. We will modify the problems of QSCC II. The First is the problems of the study execution process, not-multicenter study, a low data, the absent of Taeyangin cases. So, we have to do the multicenter study. The Second is the problems of a query and the method of statistics analysis. We will modify the problems of self-report Questionnaire. That is the problems of self-report Questionnaire, the lack of objective estimation( body type, personal appearance, etc), the absent of the estimation on typical or non-typical type constitution. We modified the problems of QSCC II. Therefore we made the new self-report Questionnaire for patients. We modified the problems of self-report Questionnaire. Therefore we made the new Constituion diagnosis Questionnaire for doctors. We develop the Questionnaire of two ways for the Sasang constitution Diagnosis. The one is the new self-report Questionnaire for patients. The other is the new Constitution diagnosis Questionnaire for doctors. We have to melt down the Questionnaire of two ways for the Sasang constitution Diagnosis.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.4
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• pp.192-200
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• 2001

As the high density memory is widely used in the various applications, the need for reproduction of memory is increased. In this paper we propose an efficient fault diagnosis algorithm of linear order O(n) that enables the reproduction of memory. The new algorithm can distinguish various fault models and identify all the cells related to the faults. In addition, a new BIST architecture for fault diagnosis is developed. Using the new algorithm, fault diagnosis can be performed efficiently. And the performance evaluation with previous approaches proves the efficiency of the new algorithm.

• JSTS:Journal of Semiconductor Technology and Science
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• v.7 no.4
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• pp.221-228
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• 2007

In this paper, we propose a new symbolic simulation for scan chain diagnosis to solve the diagnosis resolution problem. The proposed scan chain fault simulation, called the SF-simulation, is able to analyze the effects caused by faulty scan cells in good scan chains. A new scan chain fault simulation is performed with a modified logic ATPG pattern. In this simulation, we consider the effect of errors caused by scan shifting in the faulty scan chain. Therefore, for scan chain diagnosis, we use the faulty information in good scan chains which are not contaminated by the faults while unloading scan out responses. The SF-simulation can tighten the size of the candidate list and achieve a high diagnosis resolution by analyzing fault effects of good scan chains, which are ignored by most previous works. Experimental results demonstrate the effectiveness of the proposed method.

• Journal of TMJ Balancing Medicine
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• v.11 no.1
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• pp.1-11
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• 2021

Dystonia is a neurological disorder characterized by involuntary and uncontrollable muscle tonus abnormalities. It is a huge burden not only to the patients and their families, but also to the field of medicine, in that there has hardly been any substantial change in the concept of and approach to this intractable disorder and therefore no breakthrough to its diagnosis, evaluation and treatment. As an effort to solve the current impasse, this review briefly summarizes the current concept, etiology, diagnosis, treatment and management, and then suggests a rather new therapeutic approach to this disorder, based on the concept of neurological balance and TMJ integrative approach. These new approaches will provide a platform for the clinicians and researchers to have a leap in the concept, diagnosis and therapeutics.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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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.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1705-1711
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• 1991

On-line fault detection and diagnosis has an increasing interest in a chemical process industry, especially for a process control and automation. The chemical process needs an intelligent operation-aided workstation which can do such tasks as process monitoring, fault detection, fault diagnosis and action guidance in semiautomatic mode. These tasks can increase the performance of a process operation and give merits in economics, safety and reliability. Aiming these tasks, series of researches have been done in our lab. Main results from these researches are building appropriate knowledge representation models and a diagnosis mechanism for fault detection and diagnosis in a chemical process. The knowledge representation schemes developed in our previous research, the symptom tree model and the fault-consequence digraph, showed the effectiveness and the usefulness in a real-time application, of the process diagnosis, especially in large and complex plants. However in our previous approach, the diagnosis speed is its demerit in spite of its merits of high resolution, mainly due to using two knowledge models complementarily. In our current study, new knowledge representation scheme is developed which integrates the previous two knowledge models, the symptom tree and the fault-consequence digraph, into one. This new model is constructed using a material balance, energy balance, momentum balance and equipment constraints. Controller related constraints are included in this new model, which possesses merits of the two previous models. This new integrated model will be tested and verified by the real-time application in a BTX process or a crude unit process. The reliability and flexibility will be greatly enhanced compared to the previous model in spite of the low diagnosis speed. Nexpert Object for the expert system shell and SUN4 workstation for the hardware platform are used. TCP/IP for a communication protocol and interfacing to a dynamic simulator, SPEEDUP, for a dynamic data generation are being studied.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.283-286
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• 1996

This study suggests a new methodology for the fault diagnosis based on the signed digraph in developing the fault diagnosis system of a boiler plant. The suggested methodology uses the new model, fault-effect tree. The SDG has the advantage, which is simple and graphical to represent the causal relationship between process variables, and therefore is easy to understand. However, it cannot handle the broken path cases arisen from data uncertainty as it assumes consistent path. The FET is based on the SDG to utilize the advantages of the SDG, and also covers the above problem. The proposed FET model is constructed by clustering of measured variables, decomposing knowledge base and searching the fault propagation path from the possible faults. The search is performed automatically. The fault diagnosis system for a boiler plant, ENDS was constructed using the expert system shell G2 and the advantages of the presented method were confirmed through case studies.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.264-267
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• 1998

We are dealing with the preliminary diagnosis from the information of headache interview chart. We quantify the qualitative information based on the interview chart by dual scaling. Prototype of fuzzy diagnostic sets and the neural linear regression methods are established with these quantified data, These new methods can be used to classify new patient's tone of diseases with certain degrees of belief and its concerned symptoms. We call these procedures as neural Fuzzy Differential Diagnosis of Headache (NFDDH-1). Also we investigate three measures to medical diagnosis, where relations between symptoms and diseases are described by intutionistic fuzzy set (IFS) data. Two measures are described by nin-max and max-min IFS operators, respectively. Another measure is the similarity degree, i.e., IFS distance between patient's symptoms and prototypes of diseases. We consider some reasonable criteria for three measures in order to determine the label of headache, We will establish hree measures in NFDDH-2 and combine two packages as NFDDH

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.963-968
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• 2003

The continuous process systems usually consists of various components: driven rollers. idle rolls, load-cell and so on. Even a simple fault in a single component in the line may cause a catastrophic damage on the final products. Therefore it is absolutely necessary to diagnosis the components of the continuous systems. In this paper, an adaptive eccentricity compensation method is presented. And a new diagnosis method for transverse roll shape defects on rolling process is developed. The new method was induced from analyzing the rolling mechanism by using rolling force model, tension model, Hitchcock's equation, and measured delivery thickness of materials etc. Computer simulation results also show that the proposed diagnosis methods is very effective in the diagnosis of 3-D roll shape

• Quality Improvement in Health Care
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• v.10 no.2
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• pp.204-215
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• 2003

Background : ICD-10 Classification, which is used domestically as well as internationally, has limited use in the clinical practice since it is developed for at disease statistics and epidemiology. Therefore, the purposes of this study were to improve the quality of diagnosis by constructing a new disease classification based on the diagnoses doctors currently make in the clinical setting and connecting this classification with OCS and EMR, and to meet the demands of doctors for high quality medical study data in medical research. Methods : The specialists in each ophthalmic subfield collected clinical diagnoses and abbreviations based on the ophthalmology textbooks and confirmed the classifications. Total number of clinical diagnoses collected was totaled 672, for which ideal diagnoses had been selected and a new model of disease classification model in connection with ICD-10 was constructed. The constructed classification of clinical diagnoses consisted of six steps: the first step was the classification by ophthalmic subspecialty field; the second to fifth steps were the detailed classification by each specialty field; the sixth step was the classification by site. Results : After introducing the new disease classification, research on the use and a pre-post comparison was conducted. The result from the research on the use of the clinical diagnoses in inpatient and outpatient care has shown a gradually increasing tendency. From the pre-post comparison of EMR discharge summary diagnoses, the result demonstrated that the diagnosis was stated correctly and in detail. Since the diagnosis was stated correctly, code classification became correct as well, which makes it possible to construct high quality medical DB. Conclusion : This construction of clinical diagnoses provides the medical team with high quality medical information. It is also expected to increase the accuracy and efficiency of service in the department of medical record and department of insurance investigation. In the future, if hospitals wish to construct a classification of clinical diagnosis and a standard proposal of clinical diagnosis is presented by a medical society, the standardization of diagnosis seems to be possible.