• Journal of the Korean Mathematical Society
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• v.38 no.5
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• pp.937-954
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• 2001

This paper is a natural continuation of [2], [3], [4] and [5]. Localization techniques for modular lattices are developed. These techniques are applied to study liftings of linear order types from quotient lattices and to find Г-dense sets in certain lattices without Г-deviation in the sense of [4], where Г is a set of indecomposable linear order types.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.673-683
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• 2017

The least absolute shrinkage and selection operator (LASSO) has been a popular regression estimator with simultaneous variable selection. However, LASSO does not have the oracle property and its robust version is needed in the case of heavy-tailed errors or serious outliers. We propose a robust penalized regression estimator which provide a simultaneous variable selection and estimator. It is based on the rank regression and the non-convex penalty function, the smoothly clipped absolute deviation (SCAD) function which has the oracle property. The proposed method combines the robustness of the rank regression and the oracle property of the SCAD penalty. We develop an efficient algorithm to compute the proposed estimator that includes a SCAD estimate based on the local linear approximation and the tuning parameter of the penalty function. Our estimate can be obtained by the least absolute deviation method. We used an optimal tuning parameter based on the Bayesian information criterion and the cross validation method. Numerical simulation shows that the proposed estimator is robust and effective to analyze contaminated data.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.813-821
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• 2020

Recently, research using unstructured data such as images and videos has been actively conducted in various fields. Edge detection is one of the most useful image enhancement techniques to improve the quality of the image process. However, it is very difficult to perform edge detection in noise images because the edges and noise having high frequency components. This paper uses a linear model and standard deviation as an effective edge detection method for noise images. The edge is detected by the difference between the standard deviation of the pixels included in the pixel block and the standard deviation of the residual obtained by fitting the linear model. The results of edge detection are compared with the results of the Sobel edge detector. In the original image, the Sobel edge detection result and the proposed edge detection result are similar. Proposed method was confirmed that the edge with reduced noise was detected in the various levels of noise images.

• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.29-36
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• 2015

In this paper, we propose the horizontal line detection using the Haar-like features and linear regression in infrared images. In the marine environment horizon image is very useful information on a variety of systems. In the proposed method Haar-like features it was noted that the standard deviation be calculated in real time on a static area. Based on the pixel position, calculating the standard deviation of the around area in real time and, if the reaction is to filter out the largest pixel can get the energy map of the area containing the straight horizontal line. In order to select a horizontal line of pixels from the energy map, we applied the linear regression, calculating a linear fit to the transverse horizontal line across the image to select the candidate optimal horizontal. The proposed method was carried out in a horizontal line detecting real infrared image experiment for day and night, it was confirmed the excellent detection results than the legacy methods.

• Journal of Periodontal and Implant Science
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• v.44 no.4
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• pp.184-193
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• 2014

Purpose: The aim of the present study was to evaluate the in vivo accuracy of flapless, computer-aided implant placement by comparing the three-dimensional (3D) position of planned and placed implants through an analysis of linear and angular deviations. Methods: Implant position was virtually planned using 3D planning software based on the functional and aesthetic requirements of the final restorations. Computer-aided design/computer-assisted manufacture technology was used to transfer the virtual plan to the surgical environment. The 3D position of the planned and placed implants, in terms of the linear deviations of the implant head and apex and the angular deviations of the implant axis, was compared by overlapping the pre- and postoperative computed tomography scans using dedicated software. Results: The comparison of 14 implants showed a mean linear deviation of the implant head of 0.56 mm (standard deviation [SD], 0.23), a mean linear deviation of the implant apex of 0.64 mm (SD, 0.29), and a mean angular deviation of the long axis of $2.42^{\circ}$ (SD, 1.02). Conclusions: In the present study, computer-aided flapless implant surgery seemed to provide several advantages to the clinicians as compared to the standard procedure; however, linear and angular deviations are to be expected. Therefore, accurate presurgical planning taking into account anatomical limitations and prosthetic demands is mandatory to ensure a predictable treatment, without incurring possible intra- and postoperative complications.

• Journal of applied mathematics & informatics
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• v.18 no.1_2
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• pp.649-656
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• 2005

In this paper we consider a fuzzy least absolute deviation method in order to construct fuzzy linear regression model with fuzzy input and fuzzy output. We also consider two numerical examples to evaluate an effectiveness of the fuzzy least absolute deviation method and the fuzzy least squares method.

• Journal of Korean Society for Quality Management
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• v.21 no.1
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• pp.161-170
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• 1993

This study attempts to present the linear regression analysis that involves more than one regressor variable, because regression analysis is the most widely used statistical technique for describing, predicting and estimating the relationships between given data. The model of multiple linear regression may be solved directly by the two linear programming methods, i.e., to minimize the sum of the absolute deviation (MSD) and to minimize the maximum deviation(MMD). In addition, some results was compared to each techniques for accuracy and tested to the validity of statistical meaning.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.21 no.4
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• pp.353-359
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• 1999

Purpose : A new method of lateral cephalometric analysis for midface, focusing on zygomatic bone, was created in this study, and measured in Korean adults. The purposes of this study are understanding about new approach for midfacial depression, especially zygomatic bone, and using to make adequate diagnosis and treatment plan. Materials and methods : In this study, esthetic Korean adults, 25 males and 25 females who were between $0^{\circ}$ and $4^{\circ}$ in ${\angle}ANB$, and between 62% and 70% in P/A facial height ratio, and had normal overbite and overjet, were used. Orbitale(Or) and Soft tissue orbitale(Or') were used for indicators of anteroposterior position of zygomatic area. And, mean value and standard deviation of linear and angular measurements, and ratio about each linear measurements, were obtained. then, standard deviation diagram - wiggle diagram - was made for visualization of results. Results : Mean values, standard deviations and ranges of 19 measurements were obtained, and among them, 5 linear measurements that had large standard deviation were excluded and the others were used for making standard deviation diagram. In standard deviation diagram, the following results were obtained. 1. If the measurements are located on more left side of mean-value-vertical -line, the potential of midfacial hypoplasia are stronger, especially zygomatic area. 2. If the measurements are located on more right side of mean-value-vertical-line, the potential of midfacial hypoplasia are decreased. Conclusion : This study presented a new method of lateral cephalometric analysis focusing on zygomatic bone in Korean adults. We expect that the results of this study can be used as parameter when clinicians make decisions about diagnosis and treatment plan for rehabilitation of esthetics and function. But, it is necessary to prove its usefulness, and to further evaluate the results.

• Journal of Mechanical Science and Technology
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• v.19 no.6
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• pp.1329-1337
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• 2005

The OLED (Organic Light Emitting Diodes) display recently used for the information indicating device has many advantages over the LCD (Liquid Crystal Display), and its demand will be increased highly. The linear cell should be designed carefully considering the uniformity of thin film on the substrate. Its design needs to compute the temperature field analytically because the uniformity for the thin film thickness depends on the temperature distribution of the source (organic material). In the present study, the design of the linear cell will be modified or improved on the basis of the temperature profiles obtained for the simplified linear cell. The temperature distributions are numerically calculated through the STAR-CD program, and the grids are generated by means of the ICEM CFD program. As the results of the simplified linear cell, the temperature deviation was shown in the parabolic form among the both ends and the center of the source. In order to reduce the temperature deviation, the configuration of the rectangular ends of the crucible was modified to the circular type. In consequence, the uniform temperature is maintained in the range of about 90 percent length of the source. It is expected that the present methods and results on the temperature analysis can be very useful to manufacture the vapor deposition device.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.733-739
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• 2011

The linear absolute shrinkage and selection operator(Lasso) method improves the low prediction accuracy and poor interpretation of the ordinary least squares(OLS) estimate through the use of $L_1$ regularization on the regression coefficients. However, the Lasso is not robust to outliers, because the Lasso method minimizes the sum of squared residual errors. Even though the least absolute deviation(LAD) estimator is an alternative to the OLS estimate, it is sensitive to leverage points. We propose a robust Lasso estimator that is not sensitive to outliers, heavy-tailed errors or leverage points.