• Nuclear Engineering and Technology
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• v.38 no.2
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• pp.155-162
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• 2006

It is necessary to monitor periodically the operability of safety-related motor-operated valves (MOVs) in nuclear power plants. However, acquiring diagnostic signals for MOVs is very difficult, and doing so requires an excessive amount of time, effort, and expenditure. This paper introduces an accurate and economical method to evaluate the performance of MOVs remotely. The technique to be utilized includes electrical measurements and signal processing to estimate the motor torque and the stem thrust, which have been cited as the two most effective parameters in diagnosing MOVs by the US Nuclear Regulatory Commission. The motor torque is calculated by using electrical signals, which can be measured in the motor control center (MCC). Some advantages of using the motor torque signature over other signatures are examined. The stem thrust is calculated considering the characteristics of the MOV and the estimated motor torque. The basic principle of estimating stem thrust is explained. The developed method is implemented in diagnostic equipment, namely, the Motor Operated Valve Intelligent Diagnostic System (MOVIDS), which is used to obtain the accuracy of and to validate the applicability of the developed method in nuclear power plants. Finally, the accuracy of the developed method is presented and some examples applied to field data are discussed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.90-93
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• 2014

In this paper, we have developed a new fault detection method based on vibration signal for rotor machinery. Generally, many methods related to detection of rotor fault exist and more advanced methods are continuously developing past several years. However, there are some problems with existing methods. Oftentimes, the accuracy of fault detection is affected by vibration signal change due to change of operating environment since the diagnostic model for rotor machinery is built by the data obtained from the system. To settle a this problems, we build a rotor diagnostic model by using feature residual based on vibration signal. To prove the algorithm's performance, a comparison between proposed method and the most used method on the rotor machinery was conducted. The experimental results demonstrate that the new approach can enhance and keeps the accuracy of fault detection exactly although the algorithm was applied to various systems.

• Korean Journal of Bronchoesophagology
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• v.17 no.1
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• pp.9-13
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• 2011

Endobronchial ultrasound (EBUS), which enables visualization of lesions beyond the bronchus, broadens the fields of bronchoscopy. Two types of ultrasound, radial and linear, are used for bronchoscopy. Radial EBUS is performed by inserting an ultrasound mini-probe through the working channel of a flexible bronchoscope. Evaluation of the depth of invasion of early endobronchial lung cancers using radial EBUS is useful in deciding endobronchial treatment. A central tumor limited to within the cartilaginous layer is a good indication for endobronchial photodynamic therapy. EBUS-guide sheath (GS) technique is a sampling method assisted by localization of peripheral lesions using EBUS. The diagnostic yield of EBUS-GS method is higher than that of conventional transbronchial biopsy. High diagnostic values of EBSU-GS method are reported even in small (${\leq}2cm$) peripheral tumors. Linear EBUS is used for endobronchial ultrasound guided transbronchial needle aspiration (EBUS-TBNA). EBUS-TBNA has high diagnostic yields in mediastinal staging of lung cancer even in patients having radiologically early stage lung cancers with normal CT or PET findings in the mediastinum. EBUS is a valuable method in evaluating early endobronchial tumors and peripheral small lung cancers and as well as in mediastinal staging.

• Journal of Korean Society for Quality Management
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• v.28 no.1
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• pp.119-131
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• 2000

This paper suggests a new diagnostic measure for detecting influential observations in linear discriminant analysis (LDA). It is developed from a Bayesian point of view using a default Bayes factor obtained from the imaginary training sample methodology. The Bayes factor is taken as a criterion for testing homogeneity of covariance matrices in LDA model. It is noted that the effect of an observation over the criterion is fully explained by the diagnostic measure. We suggest a graphical method that can be taken as a tool for interpreting the diagnostic measure and detecting influential observations. Performance of the measure is examined through an illustrative example.

• Journal of Physiology & Pathology in Korean Medicine
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• v.27 no.2
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• pp.167-172
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• 2013

In order to establish the diagnostic indices of skin diseases, some physiological and pathological concepts of interstices(腠理) were researched based on , and western dermatology with etymological analysis. As physiological indices for diagnosis of skin diseases, measurement of epidermis and dermis using ultrasonogram in the zhongwan and dachui's location. And for grading looseness and fineness of interstices with 3 unsound groups, measuring numbers and sizes of sweat pores in each point's 1 cm diameter circular area using comparative method and palpation assessment. Another index is superficial temperature. As pathological indices for diagnosis, validating volumes of dead skin cells and grading degrees of atrophy and degeneration of skin lesion. And as supplementary measures, absorptive degrees of cosmetics on face should be recorded according to 3 grades. These diagnostic indices can contribute to establishment of standard pattern identification and prescription of skin diseases through converting anatomical cognizance into classical concepts of interstices objectively.

• Journal of radiological science and technology
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• v.10 no.1
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• pp.91-104
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• 1987

Computerization for the work of diagnostic radiology department is needed to manage the department efficiently, to deal with the information increasing gradually, and to provide qualified care for patients. There is few computerized management system for diagnostic radiology department in our country. Foreign systems were developed commercially and academically, but almost failed to meet the needs of demands. So in this paper, to help the exploitation of soft ware suitable for the information system of diagnostic radiology department of our country; 1) foreign systems were introduced. 2) Data flow of diagnositc radiology department was analysised by SSA method. 3) Composition of computer system centered on the functions of terminals was presented.

• Genomics & Informatics
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• v.15 no.3
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• pp.82-86
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• 2017

Chromosomal microarray (CMA) is a high-resolution, high-throughput method of identifying submicroscopic genomic copy number variations (CNVs). CMA has been established as the first-line diagnostic test for individuals with developmental delay (DD), intellectual disability (ID), autism spectrum disorders (ASDs), and multiple congenital anomalies (MCAs). CMA analysis was performed in 42 Korean patients who had been diagnosed with unexplained DD, ID, ASDs, and MCAs. Clinically relevant CNVs were discovered in 28 patients. Variants of unknown significance were detected in 13 patients. The diagnostic yield was high (66.7%). CMA is a superior diagnostic tool compared with conventional karyotyping and fluorescent in situ hybridization.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.28 no.3
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• pp.201-207
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• 2015

In this paper, in order to avoid equipment malfunction due to electromagnetic waves, which can occur when high-voltage live line diagnostic device fabrication, the enclosure structure of the diagnostic device with power lines that can minimize the EMI (electromagnetic interference) was modeled using the FEM (finite element method). Simulation examined the strength of the electric field in the required thickness, material and regions where there is a control board while changing the curvature radius of the corner making the enclosure, and By applying a mechanical design and simulation results that occur during the actual production has been designed for the final design. Most of the simulation results for the electric field is concentrated in the final model, the inner edge of the enclosure could be confirmed that the stable structure.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.62-68
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• 1999

FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. Authors have already proposed a diagnostic system based on FCM to utilized to identify the true origin of fault by on-line pattern diagnosis. In FCM based fault diagnosis, Temporal Associative Memories (TAM) recall of FCM is utilized to identify the true origin of fault by on-line pattern match where predicted pattern sequences obtained from TAM recall of fault FCM models are compared with actually observed ones. In engineering processes, the propagation delays are induced by the dynamics of processes and may vary with variables involved. However, disregarding such propagation delays in FCM-based fault diagnosis may lead to erroneous diagnostic results. To solve the problem, a concept of FTCM(Fuzzy Time Cognitive Map) is introduced into FCM-based fault diagnosis in this work. Expecially, translation method of FTCM makes it possible to diagnose the fault for some discrete time. Simulation studies through two-tank system is carried out to verify the effectiveness of the proposed diagnostic scheme.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.849-855
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• 2008

The Diagnostic Unit of CLINAID can infer working diagnoses for general diseases from the information provided by a user. This user-provided information in the form of signs and symptoms, however, is usually not sufficient to make a final decision on a working diagnosis. In order for the Diagnostic Unit to reach a diagnostic conclusion, it needs to select suitable clinical investigations for the patients. Because different investigations can be selected for the same patient, we need a process that can optimize the selection procedure employed by the Diagnostic Unit. This process, called a selection algorithm, must work with the fuzzy relational method because CLINAID uses fuzzy relational structures extensively for its knowledge bases and inference mechanism. In this paper we present steps of the selection algorithm along with simulation results on this algorithm using fuzzy relational products, both harsh product and mean product. The computation results of applying several different fuzzy implication operators are compared and analyzed.