• The Journal of the Korean bone and joint tumor society
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• v.4 no.2
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• pp.99-102
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• 1998

Sarcoidosis is a multi systemic granulomatous disease of unknown etiology and pathogenesis. The granulomas are non-caseating, and the organs that are affected most frequently are the lungs, the skin, and the eyes. However it may also involve the liver, spleen, bone, nervous system, and other organs. The diagnosis is based on the identification of noncaseating granuloma in the tissues involved, excluding other granulomatous conditions. The diagnosis of sarcoid joint disease is often made in retrospect and only when the lung or eye is involved. We report a case of sarcoid synovitis in knee joint with review of literature.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2758-2768
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• 2014

A research on differential effects of task and relationship conflicts claims positive effects of task conflict on innovation performance and negative effects of relation conflict on innovation performance. Yet, given the intimate interconnectedness of task conflict and relation conflict, task conflict, which has a beneficial impact on innovation performance, may have adverse effects on innovation performance as it goes through the process of being transferred to relation conflict. That necessitates the need for a way of management that can undermine the process of transference of task conflict to relation conflict, and team identification, which is a social identity of an individual and also a sort of positive, affective or cognitive bonds of such individual toward the team, can be an effective way of managing conflict. The research, which was conducted based on materials collected from 213 employees, confirms that such theory holds true for the real-life business environment. Based on the findings, this study suggested implications and directions for future research.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.49 no.2
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• pp.214-223
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• 2016

Joint time-frequency images of the broadband acoustic echoes of six fish species were obtained using the smoothed pseudo-Wigner-Ville distribution (SPWVD). The acoustic features were extracted by changing the sliced window widths and dividing the time window by a 0.02-ms interval and the frequency window by a 20-kHz bandwidth. The 22 spectrum amplitudes obtained in the time and frequency domains of the SPWVD images were fed as input parameters into an artificial neural network (ANN) to verify the effectiveness for species-dependent features related to fish species identification. The results showed that the time-frequency approach improves the extraction of species-specific features for species identification from broadband echoes, compare with time-only or frequency-only features. The ANN classifier based on these acoustic feature components was correct in approximately 74.5% of the test cases. In the future, the identification rate will be improved using time-frequency images with reduced dimensions of the broadband acoustic echoes as input for the ANN classifier.

• Tunnel and Underground Space
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• v.15 no.1 s.54
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• pp.47-54
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• 2005

One of the standard procedures of discontinuity survey is the joint set identification from the population of field orientation data. Discontinuity set identification is fundamental to rock engineering tasks such as rock mass classification, discrete element analysis, key block analysis. and discrete fracture network modeling. Conventionally, manual method using contour plot had been widely used for this task, but this method has some short-comings such as yielding subjective identification results, manual operations, and so on. In this study, the method of discontinuity set identification using genetic algorithm was introduced, but slightly modified to handle the orientation data. Finally, based on the genetic algorithm, we developed a FORTRAN program, Genetic Algorithm based Clustering(GAC) and applied it to two different discontinuity data sets. Genetic Algorithm based Clustering(GAC) was proved to be a fast and efficient method for the discontinuity set identification task. In addition, fitness function based on variance showed more efficient performance in finding the optimal number of clusters when compared with Davis - Bouldin index.

• Smart Structures and Systems
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• v.13 no.2
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• pp.257-280
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• 2014

In this paper, a novel PARAllel FACtor (PARAFAC) decomposition based Blind Source Separation (BSS) algorithm is proposed for modal identification of structures equipped with tuned mass dampers. Tuned mass dampers (TMDs) are extremely effective vibration absorbers in tall flexible structures, but prone to get de-tuned due to accidental changes in structural properties, alteration in operating conditions, and incorrect design forecasts. Presence of closely spaced modes in structures coupled with TMDs renders output-only modal identification difficult. Over the last decade, second-order BSS algorithms have shown significant promise in the area of ambient modal identification. These methods employ joint diagonalization of covariance matrices of measurements to estimate the mixing matrix (mode shape coefficients) and sources (modal responses). Recently, PARAFAC BSS model has evolved as a powerful multi-linear algebra tool for decomposing an $n^{th}$ order tensor into a number of rank-1 tensors. This method is utilized in the context of modal identification in the present study. Covariance matrices of measurements at several lags are used to form a $3^{rd}$ order tensor and then PARAFAC decomposition is employed to obtain the desired number of components, comprising of modal responses and the mixing matrix. The strong uniqueness properties of PARAFAC models enable direct source separation with fine spectral resolution even in cases where the number of sensor observations is less compared to the number of target modes, i.e., the underdetermined case. This capability is exploited to separate closely spaced modes of the TMDs using partial measurements, and subsequently to estimate modal parameters. The proposed method is validated using extensive numerical studies comprising of multi-degree-of-freedom simulation models equipped with TMDs, as well as with an experimental set-up.

• Journal of Acupuncture Research
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• v.26 no.3
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• pp.59-65
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• 2009

Objectives : This survey was done in order to find out how Korean medical doctors derive pattern identification for acupuncture prescriptions in treating knee pain in real clinical practice. Methods : The survey questionnaire was developed by the committee of experts who major in acupuncture & moxibustion or statistics for acupuncture clinical trial protocol development. The questionnaires were distributed via e-mail to 75 members of Korean Acupuncture & moxibustion society from March 26th to April 14th in 2009. 57 members completed answers, and the computerized data were analyzed by SPSS 17.0 statistical program. Results : 1.54 Korean medical doctors selected meridian pattern identification based on the course of the meridians(52.5%), visceral pattern identification(27.1%), pattern identification based on cause of disease(8.5%) as the most commonly used pattern identification methods for acupuncture prescription when treating knee pain patients in real clinical practice. 2. In meridian pattern identification based on the course of the meridians, liver meridian of the medial knee region(13.2%), bladder meridian of the posterior knee region(12.0%), spleen meridian of the lateral knee region(11.7%), stomach meridian of the anterior knee region(9.8%) and kidney meridian of the medial knee region(8.6%) were selected. 3. In visceral pattern identification, blood stasis of sinews due to liver and kidney deficiency(5.3%), damp joint with yang deficiency of liver and kidney(4.9%), kidney qi deficiency with congealing cold(4.5%), yin deficiency of liver and kidney(4.1%) were selected. Conclusions : In our e-mail survey, Korean medical doctors answered that Meridian Pattern Identification based on the course of the meridians is the most often used diagnosis method. Visceral pattern identification, pattern identification based on cause of disease, pattern identification based on symptom and pattern identification based on qi-blood-yin-yang theory in order of frequency used, were selected for knee pain diagnosis in real clinical practice.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.41-44
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• 1988

This paper represents the study of an effective self-tuning PID control for a robot manipulator to track a reference trajectory in spite of the presence of nonlinearities and parameters uncertainties in robot dynamic models. In this control scheme, an error model of the manipulator is established, for the first time, by difference between joint reference trajectory and tracked trajectory. It's model Parameters are estimated by the recursive least-square identification algorithm, and classical controller parameters are determined by pole placement method. A computer simulation study was conducted to demonstrate performance of the proposed self-tuning PID control in joint-based coordinates for a robot with payload.

• Journal of the Korean Society for Precision Engineering
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• v.6 no.3
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• pp.32-45
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• 1989

The positioning accuracy of robots depends upon a forward kinematics which relates the joint variables to the orientation and position of the robot extremity in the absolute coordinate system. The relationship between two connective joint coordi- nates of a robot, which is the basis of the kinematics, is defined by 4 Denavit-Hartenberg parameters. But manufacturing errors in machining and assembly process of robots lead to disctrepancies between the design parameters and the physical structure. Thus, improving the positioning accuracy of robots reguires the identification of the actual link parameters of each robot. In this study, the least-squares method is used to calibrate the link parameters and off-line parameter calibration software is developed. Computer simulation is done to study the dependence of the calibration performance upon the DOF of the robot and number of acquired data set used in the least-squares method. 3 DOF Robot/Controller and specially designed 3D coordinate measurer is made and experiment is carried out to verify the theoretical and computational analysis.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2004.06a
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• pp.95-98
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• 2004

본 논문에서는 결합변환상관기(joint transform correlator)와 위상 암호화된 영상들을 이용하여 영상의 인식 및 복호화가 가능한 광 암호화 시스템을 제안하였다. 그레이 값을 가지는 원 영상은 동일한 그레이 값을 가지는 이진 영상으로 나누어 표현할 있다. 이러한 이진 영상들을 각각의 다른 이진 무작위 영상과 위상 부호화한 XOR 연산을 이용해 암호화할 수 있으며. 암호화한 영상들을 결합한 후 위상 부호화 과정을 거쳐 최종 암호화 영상를 구한다. 키 영상은 암호화에 사용된 각각의 이진 무작위 영상들을 최종 암호와 영상를 얻을때의 과정처럼 결합하여 역시 하나의 영상으로 구할 수 있다. 최종 암호화 영상과 키 영상을 제안한 결합변환상관기의 입력으로 사용하여 구한 상관치는 높고 폭이 좁은 특성을 가지고 있으므로 분별성능이 좋은 인식 시스템을 구현할 수 있을 뿐만 아니라 복호화 영상도 구할 수 있다. 컴퓨터 모의 실험으로 제안한 방법을 확인해보았다.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.101-108
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• 2008

The transposed Jacobian is proposed to transform the control space from task space to joint space, in this paper. Instead of inverse Jacobian, the transposed Jacobian is preferred to avoid singularity problem, short real time calculations and its generality to apply for rectangular Jacobian. On-line Jacobian identification is proposed to cancel parametric errors produced by D-H parameters of manipulator. To identify Jacobian, the joint angles and the end-effector position are measured when tracking a desired trajectory in task space. Stability of control system is analyzed. The control system is simulated for position control of a two-link manipulator driven by permanent magnet dc motors. Simulation results are shown to compare the roles of inverse Jacobian and transposed Jacobian for transforming the control space.