• The Korean Journal of Applied Statistics
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• v.14 no.2
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• pp.357-367
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• 2001

Huber의 M-추정함수의 형태는 조율상수가 주어질 때 비로소 그 형태가 결정된다. 조율상수를 커널밀도함수추정량의 평활계수를 이용하여 구하여 보았고, 모의실험을 통해 기존에 상요되는 조율상수들과 그 성능을 비교하여 보았다. 그 결과 새로운 방법에 의해 구해진 조율상수가 기존의 조율상수를 사용하는 경우 보다 모의실험을 통해 얻은 추정치의 분산이 작게되는 경우가 있음을 알았다.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.993-1000
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• 2016

Semi-supervised learning makes it easy to use an unlabeled data in the supervised learning such as classification. Applying the semi-supervised learning on the regression analysis, we propose two methods for a better regression function estimation. The proposed methods have been assumed different marginal densities of independent variables and different smoothing parameters in unlabeled and labeled data. We shows that the overfitted pilot estimator should be used to achieve the fastest convergence rate and unlabeled data may help to improve the convergence rate with well estimated smoothing parameters. We also find the conditions of smoothing parameters to achieve optimal convergence rate.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.733-745
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• 2017

Local composite quantile regression is a useful non-parametric regression method widely used for its high efficiency. Data smoothing methods using kernel are typically used in the estimation process with performances that rely largely on the smoothing parameter rather than the kernel. However, $L_2$-norm is generally used as criterion to estimate the performance of the regression function. In addition, many studies have been conducted on the selection of smoothing parameters that minimize mean square error (MSE) or mean integrated square error (MISE). In this paper, we explored the optimality of selecting smoothing parameters that determine the performance of non-parametric regression models using local linear composite quantile regression. As evaluation criteria for the choice of smoothing parameter, we used mean absolute error (MAE) and mean integrated absolute error (MIAE), which have not been researched extensively due to mathematical difficulties. We proved the uniqueness of the optimal smoothing parameter based on MAE and MIAE. Furthermore, we compared the optimal smoothing parameter based on the proposed criteria (MAE and MIAE) with existing criteria (MSE and MISE). In this process, the properties of the proposed method were investigated through simulation studies in various situations.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.311-311
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• 2023

파형강관은 아연도금강판을 물결모양으로 성형하여 나선형으로 조관한 연성관으로 콘크리트 흄관을 대체하여 각종 토목공사의 우수 및 하수관으로 주로 사용되고 있다. 파형강관은 강판에 물결 형상을 성형하여 내하력을 부여하였기 때문에 높은 강도를 지니고 있고, 경량이고 유연성이 있어 기초공사가 쉽고 현장에서의 운반 및 보관이 용이하여 그 활용이 점차 확대되고 있다. 이러한 파형강관의 내/외부에 기능성 고분자 복합 Polymer(다중필름)을 코팅하여 일반 파형강관 대비 더 높은 내식성 및 내마모성을 구현한 제품을 NPE 피복 파형강관이라 하며, 내부에 평판을 2중으로 결합하여 일반 파형강관 대비 통수능력을 개선한 파형강관을 내부평활 파형강관이라고 한다. 최근 파형강관의 활용이 점차 확대되고 있음에도 불구하고, 파형강관에 국한된 수리역학적 특성에 관한 연구는 미흡한 실정이며, 그마저도 주로 만관 혹은 만관에 가까운 상태에서의 흐름만이 고려되어 왔다. 하지만 대구경의 파형 강관이 우수 배관 및 하수 처리를 위하여 설치될 경우 개수로 흐름이 발생하게 된다. 이에, NPE 피복 파형강관과 내부평활 파형강관 내에서의 개수로 흐름을 다양한 유량 및 수심 변화를 통하여 생성하였으며, 각각의 수리학적 조건에서 통수능을 결정하는데 중요한 상수인 조도계수를 수리 실험을 실시하여 결정하였다. 이는 현재 국내에서 생산되고 있는 NPE 피복 파형강관과 내부 평활강관의 활용에 있어서 국제 경쟁력을 높이는데 큰 도움이 될 것이라 사료된다.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.971-980
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• 2017

The varying coefficient regression model has gained lots of attention since it is capable to model dynamic changes of regression coefficients in many regression problems of science. In this paper we propose a varying coefficient regression model that effectively considers the errors on both input and response variables, which utilizes the kernel method in estimating the varying coefficient which is the unknown nonlinear function of smoothing variables. We provide a generalized cross validation method for choosing the hyper-parameters which affect the performance of the proposed model. The proposed method is evaluated through numerical studies.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.504-511
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• 2014

This paper presents a hybrid recognition method, which is based on the nonlinear histogram equalization and the multidimensional intensity variation of an images. The nonlinear histogram equalization based on a adaptively modified function is applied to improve the quality by adjusting the brightness of the image. The multidimensional intensity variation by considering the a extent of 4-step changes in brightness between the adjacent pixels is also applied to reflect accurately the attributes of image. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to comprehensively measure the similarity between the images. The NCC is considered by the intensity variation of each 2-direction(x-axis and y-axis) image. The proposed method has been applied to the problem for recognizing the 50-face images of 40*40 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the histogram equalization, or the linear histogram equalization, respectively.

• Journal of the Korean Data and Information Science Society
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• v.7 no.2
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• pp.211-217
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• 1996

본 논문은 확률밀도함수의 l 번째 도함수의 커널추정법에 관하여 다루고 있다. 확률밀도함수 도함수의 커널추정에 사용될 수 있는 두가지 평활량의 선택법, 교차타당성방법과 삽입방법에 의한 평활량의 점근분포를 규명하고 이들의 상대적 수렴속도를 각각 밝히고 삽입방법의 우수성을 소표본 모의실험을 통하여 확인하였다.

• Journal of the Microelectronics and Packaging Society
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• v.5 no.1
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• pp.83-90
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• 1998

LPCVD를 이용하여 증착한 SiN과 ECR plasma CVD를 이용하여 증착한 SiC의 물 성과 적용가능성을 시험하였다. LPCVD로 증착된 SiN은 열처리 없이 저 응력의 박막형성이 가능했으며 가시광투과도 표면 평활도 역시 우수하였다. 탄성계수 값이 크지 않아 자성센서 의 지지구조로 사용할 경우 자기공명에 의한 진동을 크게 구속하지 않아 유리할것으로 기대 된다. 반면 ECR plasma CVD로 증착된 SiC는 SiN보다는 못하지만 다른 방법에 의해 증착 된 SiC에 비해서는 가시광 투과도 및 표면 평활도가 후수하므로 X-선 조사에 대한 안정성 과 더불어 X-선 마스크용 membrane으로서 사용이 적절할 것으로생각된다.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.555-562
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• 2012

This paper presents a hybrid method for improving the recognition performance, which is based on the nonlinear histogram equalization, features extraction, and statistical correlation of images. The nonlinear histogram equalization based on a logistic function is applied to adaptively improve the quality by adjusting the brightness of the image according to its intensity level frequency. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to rapidly and accurately express the similarity between the images. The local features based on independent component analysis(ICA) that is used to calculate the NCC, is also applied to statistically measure the correct similarity in each images. The proposed method has been applied to the problem for recognizing the 30-face images of 40*50 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the preprocessing, or the methods of conventional and adaptively modified histogram equalization, respectively.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.6 no.3
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• pp.43-49
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• 1992

Forecasting of electric power demand has been a basic element for electric power system operation and system development, and it's accuracy has very strong influence on reliability and economical efficience of power supply. So, in this paper, long―term maximum electric power demand has been forecasted by using the triple exponential smoothing method initiated R.G.Brown. It has been regarded this method as high accuracy and operational convenience. The smoothing function is a liner combination of all past observations and the weight given to previous observations decreases geometrically with age.