• 한국정보통신학회논문지
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• 제3권4호
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• pp.907-914
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• 1999

This paper studies on the model identification of electro-hydraulic servo systems, which are composed of servo valves, double-rod cylinder and load mass. The identified plant is described as a discrete-time ARX or ARMAX model which is respectively obtained from the identification algorithms of least square error method, instrumental variable method and prediction error method. where a nominal model and the variation of model parameters are quantitatively evaluated.

• 아시아태평양코퍼스연구
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• 제4권1호
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• pp.61-71
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• 2023

This study examines the effects of data-driven learning (DDL)-an approach employing corpora for inductive language pattern learning-on error identification in second language (L2) writing. The data consists of error identification instances from fifty-five participants, compared across different reference materials: the Corpus of Contemporary American English (COCA), dictionaries, and no use of reference materials. There are three significant findings. First, the use of COCA effectively identified collocational and form-related errors due to inductive inference drawn from multiple example sentences. Secondly, dictionaries were beneficial for identifying lexical errors, where providing meaning information was helpful. Finally, the participants often employed a strategic approach, identifying many simple errors without reference materials. However, while maximizing error identification, this strategy also led to mislabeling correct expressions as errors. The author has concluded that the strategic selection of reference materials can significantly enhance the effectiveness of error identification in L2 writing. The use of a corpus offers advantages such as easy access to target phrases and frequency information-features especially useful given that most errors were collocational and form-related. The findings suggest that teachers should guide learners to effectively use appropriate reference materials to identify errors based on error types.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 정기총회 및 추계학술대회 논문집 학회본부
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• pp.290-292
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• 1993

This paper investigates the identification of discrete time nonlinear system using neural networks with two hidden layers. A New learning method of both NNI and NNC is proposed. For control of the dynamical system we use two neural networks, one for identification and the other for control, and proposed NN control system is based on a framework of MRC. We define a closed loop error. In the proposed learning method, the identification error and the closed loop error are utilized to train the NNI, whareas the control error and the closed loop error are used to train the NNC, The simulation results show that the identification and control schemes suggested are practically feasible and effective.

• 대한기계학회논문집A
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• 제24권12호
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• pp.2899-2908
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• 2000

Methodology of volumetric error identification is presented to improve the accuracy of NC machine tools by using a reference artifact and a touch trigger probe. Homogeneous transformation matrix and kinematic chain are used for modeling the geometric and thermal errors of a three-axis vertical machining center. The reference artifact is designed and fabricated to identify the model parameters by machine tool metrology. Parameters in the error model are able to be identified and updated by direct measurement of the reference artifact on the machine tool under the actual conditions which include the thermal interactions of error sources. The proposed method can speed up and simplify volumetric error identification processes.

• 한국자동차공학회논문집
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• 제10권5호
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• pp.29-34
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• 2002

This study presents the process of the continuous-time system identification for unknown nonlinear systems. The Radial Basis Function(RBF) error filtering identification model is introduced at first. This identification scheme includes RBF network to approximate unknown function of nonlinear system which is structured by affine form. The neural network is trained by the adaptive law based on Lyapunov synthesis method. The identification scheme is applied to engine and the performance of RBF error filtering Identification model is verified by the simulation with a three-state engine model. The simulation results have revealed that the values of the estimated function show favorable agreement with the real values of the engine model. The introduced identification scheme can be effectively applied to model-based nonlinear control.

• 한국생산제조학회지
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• 제9권2호
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• pp.102-111
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• 2000

Methodology of volumetric error identification and compensation is presented to improve the accuracy of NC machine tools by using a reference artifact and a touch trigger probe. Homogeneous transformation matrix and kinematic chain are used for modeling the geo-metric and thermal errors of a three-axis vertical machining center. The reference artifact is designed and fabricated to identify the model parameters by machine tool metrology. Parameters in the error model are able to be identified and updated by direct measurement of the reference artifact on the machine tool under the actual conditions which include the thermal interactions of error sources. A volumetric error compensation system based on IBM/PC is linked with a FANUC CNC controller to compensate for the identified volumetric error in machining workspace.

• 한국안전학회지
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• 제29권3호
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• pp.79-84
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• 2014

Human error is one of the major contributors to the accidents. A lot of risk assessment techniques have been developed for prevention of accidents. Nevertheless, most of them were interested in physical factors, because quantitative evaluation of human errors was difficult quantitatively. According to lack of risk assessment techniques about human errors, most of industrial risk assessment for human errors were based on data of accident analysis. In order to develop an effective countermeasure to reduce the risk caused by human errors, a systematic analysis is needed. Generally, risk assessment system is composed of 5 step(classification of work activity, identification of hazards, risk estimation, evaluation and improvement). This study aimed to develop a risk identification technique for human errors that could mainly be applied to industrial fields. In this study, Ergo-HAZOP and Comprehensive Human Error Analysis Technique were used for developing the risk identification technique. In the proposed risk identification technique, Ergo-HAZOP was used for broad-brush risk identification. More critical risks were analysed by Comprehensive Human Error Analysis Technique. In order to verify applicability, the proposed risk identification technique was applied to the work of pile head cutting. As a consequence, extensive hazards were identified and fundamental countermeasures were established. It is expected that much attention would be paid to prevent accidents by human error in industrial fields since safety personnel can easily fint out hazards of human factors if utilizing the proposed risk identification technique.

• 한국산업정보학회논문지
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• 제25권6호
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• pp.1-13
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• 2020

본 논문에서는 원전 비상 상황 발생 시 다수의 신호 오류가 발생했을 때 어떤 신호에 오류가 발생했는지를 추정하는 신호 오류 식별 (Fault identification) 방법론을 개발하였다. 변분 오토인 코더 (Variational autoencoder; VAE) 기반 모델은 기존의 이상 탐지 방법론과 같이 정상 신호 데이터만을 이용하여 훈련이 진행되며, 이후 각 신호에 대한 복원 오차 (Reconstruction error)와 복원 오차를 입력의 특정 부분으로 미분한 값을 이용하여 어떤 부분에 오류가 포함되어 있는지를 예측한다. 데이터 취득을 위하여 시뮬레이션을 수행하였으며, 일련의 실험으로부터 제시한 신호 오류 식별 방법이 적절한 오차 범위 내에서 오류가 발생한 신호를 특정할 수 있음을 확인하였다.

• 한국정밀공학회지
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• 제10권2호
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• pp.126-137
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• 1993

This paper presents an efficient method for the identification of motion error sources in NC machine tools by making use of the circular interpolation test, which is often used in estimating the motion accuracy of NC machine tools. Mathematical formulae are described for motion errors due to various kinds of error sources. Two identification formulae are proposed: one is based on the frequency analysis and the other is formulated with the weithted residual method. Motion error signal is classified into two patterns, mean errors(mean of CW and CCW test signals from mean errors). The sources of the mean errors are identified by using the frequency analysis technique and the sources of the deviation errors by the weighted residual formulaltion. A menu driven, user oriented, computer program is written to realize the full steps of the proposed identificationprocedure. Then, the identification method is applied to two NC machine tools.

• 대한치과교정학회지
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• 제49권1호
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• pp.32-40
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• 2019

Objective: Precise identification of landmarks on posteroanterior (PA) cephalograms is necessary when evaluating lateral problems such as facial asymmetry. The aim of the present study was to investigate whether the use of lateral (LA) cephalograms can reduce errors in landmark identification on PA cephalograms. Methods: Five examiners identified 16 landmarks (Cg, N, ANS, GT, Me, RO, Lo, FM, Z, Or, Zyg, Cd, NC, Ms, M, and Ag) on 32 PA cephalograms with and without LA cephalograms at the same time. The positions of the landmarks were recorded and saved in the horizontal and vertical direction. The mean errors and standard deviation of landmarks location according to the use of LA cephalograms were compared for each landmark. Results: Relatively small errors were found for ANS, Me, Ms, and Ag, while relatively large errors were found for N, GT, Z, Or, and Cd. No significant difference was found between the horizontal and vertical errors for Z and Or, while large vertical errors were found for N, GT, and Cd. The value of identification error was lower when the landmarks were identified using LA cephalograms. Statistically significant error reductions were found at N and Cd with LA cephalograms, especially in the vertical direction. Conclusions: The use of LA cephalograms during identification of landmarks on PA cephalograms could help reduce identification errors.