• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1295-1309
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• 2016

This paper is to reproduce the result of Kim et al. (2014) by deriving a benchmark dose lower bound (BMDL) of lead based on the 2005 cohort data set of Children's Health and Environmental Research (CHEER) data set. The ADHD rating scales in the 2005 cohort were not consistent along the three follow-ups since two different ADHD rating scales were used in the cohort. We first unified the ADHD rating scales in the 2005 cohort by deriving a conversion formula using a penalized linear spline. We then constructed two linear mixed models for the 2005 cohort which reflected the longitudinal characteristics of the data set. The first model introduced the random intercept and the random slope terms and the second model assumed the first order autoregressive structure of the error term. Using these two models, we derived the BMDLs of lead and reconfirmed the "regression to the mean" nature of the ADHD score discovered by Kim et al. (2014). We also noticed that there was a definite difference between the sampling distributions of the two cohorts. As a result, taking this difference into account, we were able to obtain the consistent result with Kim et al. (2014).

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.543-559
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• 2019

Data often include missing values due to various reasons. If the missing data mechanism is not MCAR, analysis based on fully observed cases may an estimation cause bias and decrease the precision of the estimate since partially observed cases are excluded. Especially when data include many variables, missing values cause more serious problems. Many imputation techniques are suggested to overcome this difficulty. However, imputation methods using parametric models may not fit well with real data which do not satisfy model assumptions. In this study, we review imputation methods using nonlinear models such as kernel, resampling, and spline methods which are robust on model assumptions. In addition, we suggest utilizing imputation classes to improve imputation accuracy or adding random errors to correctly estimate the variance of the estimates in nonlinear imputation models. Performances of imputation methods using nonlinear models are compared under various simulated data settings. Simulation results indicate that the performances of imputation methods are different as data settings change. However, imputation based on the kernel regression or the penalized spline performs better in most situations. Utilizing imputation classes or adding random errors improves the performance of imputation methods using nonlinear models.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1133-1137
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• 1995

This paper presents a numerical method of the global search for an optimal geometric path for a manipulator arm amid obstacles. Finite term quintic B-splines are used to describe an arbitrary point-to-point manipulator motion with fixed moving time. The coefficients of the splines span a linear vector space, a point in which uniquely represents the manipulator motion. All feasible geometric paths are searched by adjusting the seed points of the obstacle models in the penetration growth distances. In the numerical implementation using nonlinear programming, the globally optimal geometric path is obtained for a spatial 3-link(3-revolute joints) manipulator amid several hexahedral obstacles without simplifying any dynamic or geometric models.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.116-126
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• 2001

This paper suggests a numerical method to find optimal geometric path and minimum-time motion for a spatial 6-link manipulator arm (PUMA 560 type). To find a minimum-time motion, the optimal geometric paths minimizing 2 different dynamic performance indices are searched first, and the minimum-time motions are searched on these optimal paths. In the algorithm to find optimal geometric paths, the objective functions (performance indices) are selected to minimize joint velocities, actuator forces or the combinations of them as well as to avoid one static obstacle. In the minimum-time algorithm the traveling time is expressed by the power series including 21 terms. The coefficients of the series are obtained using nonlinear programming to minimize the total traveling time subject to the constraints of velocity-dependent actuator forces.

• 한국공간정보시스템학회:학술대회논문집
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• 2003.11a
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• pp.104-109
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• 2003

이동 통신과 무선 단말기의 보급이 보편화되면서 사용자의 위치정보를 이용한 위치 기반 서비스(Location Based Service)에 대한 관심이 높아지고 있다. 이러한 위치 기반 서비스를 제공하기 위해서는 이동객체 위치 정보의 효율적인 저장 및 관리가 필요하며 이를 위해 일정 시간 간격을 두고 위치 정보를 획득하여 저장, 관리하는 방법이 연구되어 왔다. 본 논문에서는 이동 객체의 이동경로에 대응되는 위상 정보(Topology)를 이용하여 이동 객체의 위치 정보를 관리하는 기법을 제안한다. 본 기법은 이동 객체가 위상 정보의 노드에 해당하는 위치에 도착할 예상 시점을 계산하고, 그 시점을 위치 획득 시점으로 결정하여 위치 정보를 갱신하며, 또한 명시적으로 저장되지 않은 불확실한 위치 정보의 요청에 대해 위상 정보 노드의 속성 정보와 선형 함수를 이용해 위치 정보를 추정하여 제공한다. 본 기법은 위상 정보의 노드에 대응되는 위치를 획득하여 저장하기 때문에 갱신 횟수와 데이터의 양을 감소시키고, 불확실한 위치 정보에 대한 위치를 추정할 경우, 명시적으로 저장된 위치 정보에서 유추된 이동 객체의 정보와 더불어 이동 객체의 이동 경로를 고려한 위상 정보 속성을 사용하므로, 선형 함수나 스플라인 함수만을 적용하는 것보다 적은 오차를 발생시켜 위치 정보의 정확성을 향상시킬 수 있다.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.204-213
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• 1999

This paper suggests a numerical method of finding optimal geometric path and minimum-time motion for a manipulator arm. To find the minimum-time motion, the optimal geometric path is searched first, and the minimum-time motion is searched on this optimal path. In the algorithm finding optimal geometric path, the objective function is minimizing the combination of joint velocities, joint-jerks, and actuator forces as well as avoiding several static obstacles, where global search is performed by adjusting the seed points of the obstacle models. In the minimum-time algorithm, the traveling time is expressed by the linear combinations of finite-term quintic B-splines and the coefficients of the splines are obtained by nonlinear programming to minimize the total traveling time subject to the constraints of the velocity-dependent actuator forces. These two search algorithms are basically similar and their convergences are quite stable.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.1-10
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• 2001

In the reverse engineering, surfaces are modeled for new products by interpolating the digitized data points obtained by measuring the existing shapes. However, many measuring or deviation errors are happened during the measuring process. If these errors are ignored, designers could get undesirable results. Therefore, it is important to handle such errors and fairing procedure with the esthetics criteria is needed during surface modeling process. This paper presents algorithms for the fairing of B-spline surfaces. The algorithms are based on automatic repositioning of control points for B-spline surfaces. New positions of the control points are determined by solving a non-linear programming of which the objective functions are derived variously using derived surfaces and constraints are established by distance measures between the original and the modified control points. Changes in surface shapes are analyzed by illustrations of their shapes and continuous plotting of gaussian and mean curvatures.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.78-86
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• 1998

This paper presents a numerical method of the minimum-time trajectory planning for a robot manipulator amid obstacles. Each joint displacement is represented by the linear combination of the finite-term quintic B-splines which are the known functions of the path parameter. The time is represented by the linear function of the same path parameter. Since the geometric path is not fixed and the time is linear to the path parameter, the coefficients of the splines and the time-scale factor span a finite-dimensional vector space, a point in which uniquely represents the manipulator motion. The displacement, the velocity and the acceleration conditions at the starting and the goal positions are transformed into the linear equality constraints on the coefficients of the splines, which reduce the dimension of the vector space. The optimization is performed in the reduced vector space using nonlinear programming. The total moving time is the main performance index which should be minimized. The constraints on the actuator forces and that of the obstacle-avoidance, together with sufficiently large weighting coefficients, are included in the augmented performance index. In the numerical implementation, the minimum-time motion is obtained for a planar 3-1ink manipulator amid several rectangular obstacles without simplifying any dynamic or geometric models.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.793-796
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• 2017

Image signal can be damaged by a variety of noises during the signal processing, and multiple studies have been conducted to restore these signals. The representative noises to be added in the image are salt and pepper noise, additive white Gaussian noise(AWGN), and the composite noise which two noises are combined. Therefore, the algorithms were proposed to process with quadratic spline interpolation and median filter in case of salt and pepper noise with the central pixel of the local mask, and to process with weight filter by pixel changes in case of AWGN, upon noise determination to restore the damaged image in the composite noise environment, in this article.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.9A
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• pp.2345-2354
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• 1998

There have been many researches to yield higher resolution image quality from the low resolution CCD device. The resolution of it is primary factor for the image quality of digital still camera and in manufacturing price. IN this paper, image enlargement algorithm, which reduces blocking effect of enlarged low resolution image and minimizes ringing and blur effect occurring around edge in linear interpolation, is proposed. This algorithm is composed of gaussian low pass filter which eliminates aliasing, least square spline interpolation and non-linear interpolation based on step edge model.