• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.760-763
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• 2005

Optimum design of the tooth surface for the reduction of transmission error is very difficult to determine analytically due to nonlinearity of transmission error under the several load condition. The design of tooth surface that can give a low noise under the various load condition is very important. Therefore, this study proposes the method to determine the optimal lead curve and robust design of the tooth surface by using the response surface method. To do so, the design variables are selected by a screening experiment. Then the fitted regression model Is built with the check of the usefulness of the model. The model with constraints is solved to obtain the optimum values for the lead curve and the robust design fur the tooth surface.

• Nuclear Engineering and Technology
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• 제44권4호
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• pp.355-362
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• 2012

The aim of this study was to develop a bundle position-wise linear model (BPLM) to predict Pressure Tube (PT) diametral creep employing the previously measured PT diameters and operating conditions. There are twelve bundles in a fuel channel, and for each bundle a linear model was developed by using the dependent variables, such as the fast neutron fluences and the bundle coolant temperatures. The training data set was selected using the subtractive clustering method. The data of 39 channels that consist of 80 percent of a total of 49 measured channels from Units 2, 3, and 4 of the Wolsung nuclear plant in Korea were used to develop the BPLM. The data from the remaining 10 channels were used to test the developed BPLM. The BPLM was optimized by the maximum likelihood estimation method. The developed BPLM to predict PT diametral creep was verified using the operating data gathered from Units 2, 3, and 4. Two error components for the BPLM, which are the epistemic error and the aleatory error, were generated. The diametral creep prediction and two error components will be used for the generation of the regional overpower trip setpoint at the corresponding effective full power days. The root mean square (RMS) errors were also generated and compared to those from the current prediction method. The RMS errors were found to be less than the previous errors.

• Nuclear Engineering and Technology
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• 제53권8호
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• pp.2708-2715
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• 2021

The Multi-Purpose Overload Robot (CMOR) is a key subsystem of China Fusion Engineering Test Reactor (CFETR) remote handling system. Due to the long cantilever and large loads of the CMOR, it has a large rigid-flexible coupling deformation that results in a poor position accuracy of the end-effector. In this study, based on the Levenberg-Marquardt algorithm, the spatial grid, and the linearized variable load principle, a variable parameter compensation model was designed to identify the parameters of the CMOR's kinematics models under different loads and at different poses so as to improve the trajectory tracking accuracy. Finally, through Adams-MATLAB/Simulink, the trajectory tracking accuracy of the CMOR's rigid-flexible coupling model was analyzed, and the end position error exceeded 0.1 m. After the variable parameter compensation model, the average position error of the end-effector became less than 0.02 m, which provides a reference for CMOR error compensation.

• Nuclear Engineering and Technology
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• 제54권4호
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• pp.1439-1448
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• 2022

Background: We investigated the feasibility of in vitro radiosensitivity prediction with gene expression using deep learning. Methods: A microarray gene expression of the National Cancer Institute-60 (NCI-60) panel was acquired from the Gene Expression Omnibus. The clonogenic surviving fractions at an absorbed dose of 2 Gy (SF2) from previous publications were used to measure in vitro radiosensitivity. The radiosensitivity prediction model was based on the convolutional neural network. The 6-fold cross-validation (CV) was applied to train and validate the model. Then, the leave-one-out cross-validation (LOOCV) was applied by using the large-errored samples as a validation set, to determine whether the error was from the high bias of the folded CV. The criteria for correct prediction were defined as an absolute error<0.01 or a relative error<10%. Results: Of the 174 triplicated samples of NCI-60, 171 samples were correctly predicted with the folded CV. Through an additional LOOCV, one more sample was correctly predicted, representing a prediction accuracy of 98.85% (172 out of 174 samples). The average relative error and absolute errors of 172 correctly predicted samples were 1.351±1.875% and 0.00596±0.00638, respectively. Conclusion: We demonstrated the feasibility of a deep learning-based in vitro radiosensitivity prediction using gene expression.

• 천문학회보
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• 제40권2호
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• pp.40.1-40.1
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• 2015

Off-axis reflective optical systems have attractive advantages relative to their on-axis or refractive counterparts, for example, zero chromatic aberration, no obstruction, and a wide field of view. For the efficient operation of off-axis reflective system, the surface accuracy of freeform mirrors should be higher than the order of wavelengths at which the reflective optical systems operate. Especially for applications in shorter wavelength regions, such as visible and ultraviolet, higher surface accuracy of freeform mirrors is required to minimize the light scattering. In this work, we propose the error compensation algorithm (ECA) for the correction of wavefront errors on freeform mirrors. The ECA converts a form error pattern into polynomial expression by fitting a least square method. The error pattern is measured by using an ultra-high accurate 3-D profilometer (UA3P, Panasonic Corp.). The measured data are fitted by two fitting models: Sag (Delta Z) data model and form (Z) data model. To evaluate fitting accuracy of these models, we compared the fitted error patterns with the measured error pattern.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 춘계학술대회 논문집
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• pp.75-80
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• 1999

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcome limitation of accuracy in the linear regression model or the engineering judgment model. And this model is compared with the engineering judgment model. It is not necessary complex process such like multi-regression analysis of the engineering judgment model. A fuzzy model does not need to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Like a regression model, this model can be applied to any machine, but it delivers greater accuracy and robustness.

• 한국산학기술학회논문지
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• 제20권2호
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• pp.200-209
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• 2019

미래 값을 예측할 때, 학습 오차(training error)를 최소화하여 추정된 모형은 보통 많은 테스트 오차(test error)를 야기할 수 있다. 이것은 추정 모델이 주어진 데이터 집합에만 집중하여 발생하는 모델 복잡성에 따른 과적합(overfitting) 문제이다. 일부 정규화 및 리샘플링 방법은 이 문제를 완화하여 테스트 오차를 줄이기 위해 도입되었지만, 이 방법들 또한 주어진 데이터 집합에서만 국한 되도록 설계되었다. 본 논문에서는 테스트 오차 최소화 문제를 학습 오차 최소화 문제로 변환하여 테스트 오차를 줄이기 위한 새로운 최적화 방법을 제안한다. 이 변환을 수행하기 위해 주어진 데이터 집합에 대해 의사(pseudo) 데이터라고 하는 새로운 데이터를 추가하였다. 그리고 적절한 의사 데이터를 만들기 위해 결측 데이터 보정법의 세 가지 유형을 사용하였다. 예측 모델로서 선형회귀모형, 자기회귀모형, ridge 회귀모형을 사용하고 이 모형들에 의사 데이터 방법을 적용하였다. 또한, 의사 데이터로 조정된 최적화 방법을 활용하여 환경 데이터 및 금융 데이터에 적용한 사례를 제시하였다. 결과적으로 이 논문에서 제시된 방법은 원래의 예측 모형보다 테스트 오차를 감소시키는 것으로 나타났다.

• Journal of Positioning, Navigation, and Timing
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• 제5권4호
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• pp.213-219
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• 2016

Most existing studies on the wide-area differential global positioning system (WADGPS) employed a grid ionosphere model for error correction in the ionospheric delay. The present study discusses the application of satellite-based ionospheric delay model that provides an error model as a plane function with regard to individual satellites in order to improve accuracy in the WADGPS. The satellite-based ionospheric delay model was developed by Stanford University in the USA. In the present study, the algorithm in the model is applied to the WADGPS system and experimental results using measurements in the Korean Peninsula are presented. Around 1 m horizontal accuracy was exhibited in the existing planar fit grid model but when the satellite-based model was applied, correction performance within 1 m was verified.

• 한국항행학회논문지
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• 제11권1호
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• pp.31-36
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• 2007

TCP(Transmission Control Protocol)는 인터넷 환경에서 널리 사용되고 있는 프로토콜의 하나이다. TCP는 흐름제어를 통해 데이터의 손실 및 재전송을 줄여 효율성을 높일 수 있으며, 이러한 흐름제어는 데이터 패킷 크기의 제한을 두는 윈도우 기법을 통해 이루어지고 있다. 흐름제어 방식에 의해 TCP는 다양한 버전으로 구분되어 있는데, 본 논문에서는 대표적인 Tahoe, Reno와 Reno의 개량형인 Newreno에 에러모델을 적용한 시뮬레이션 결과를 통해 그 성능을 분석하였다.

• 응용통계연구
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• 제27권3호
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• pp.419-430
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• 2014

전력수급의 정확한 예측은 국민들의 일상적 생활 유지, 산업활동, 그리고 국가경영을 위하여 매우 중요하다. 본 연구에서는 시계열모형화에 의해 전력판매량을 예측한다. 실제 자료분석을 통하여 입력시계열로서 냉난방도일과 개입변수로 펄스함수를 사용한 전이함수모형이 다른 시계열모형에 비해서 제곱근평균제곱오차 및 평균절대오차의 의미에서 더 우수하였다.