• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.333-337
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• 2003

열악한 환경에서 동작해야 하거나 물리적 접근이 어려운 곳에 장착되는 센서 시스템의 경우, 유선에 의한 정보전달이 어려울 뿐만 아니라 센서 내 전원설비가 제한적일 수도 있다. 따라서, 본 논문에서는 이러한 문제점에 대한 해결책으로서 밧데리 없이 유도결합에 의하여 원격 센서로부터 정보 취득이 가능한 한 방법을 제안하였다. 이 방법은 전원공급에 의한 유도 결합식의 원격센서 시스템과는 달리, 원격 센서의 정전용량을 변ㆍ복조 과정 없이 재귀적 최소 자승 추정법에 의해 센서의 정전용량을 고정도로 추정하는 것이다. 이를 위하여 시스템의 유도결합 모델을 사용하여 정확도가 높은 원격 센서 시스템을 구현할 수 있었다.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.57-58
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• 2016

MOR(Metal-Only Reflectarray) 안테나와 같은 밀리미터파용 대형 안테나 계산을 병렬화하기 위해 사용하는 MPI 특성을 예측하기 위한 방법으로 최소자승법 활용을 제안한다. 기존의 Amdahl 법칙에 Compute Node 간의 통신 속도를 추가한 수정된 Amdahl 법칙을 사용하여 9개의 Compute Node의 MPI 특성을 예측하였다. 이를 이용해 현재 구조에 적합한 최적의 Compute Node 개수도 제시하였다.

• Proceedings of the KIPE Conference
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• 2019.11a
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• pp.100-101
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• 2019

본 논문은 유도전동기 고정자 자속 기준 벡터제어에서, 슬립 관계식과 순환 최소자승법을 이용하여 회전자 저항 및 고정자 과도 인덕턴스를 동시에 추정하는 알고리즘을 제안한다. 모의실험을 수행하여, 추정 회전자 저항과 고정자 과도 인덕턴스가 제안된 방법에 의해 각각 실제 값에 수렴함을 보인다.

• Economic and Environmental Geology
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• v.50 no.6
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• pp.517-523
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• 2017

A linear relationship between two stable water isotopes, oxygen and hydrogen, has been used to understand the water cycle as a basic tool. A slope and intercept from the linear relationship indicates what kind of physical processes occur during movement of water. Traditionally, ordinary least squares (OLS) method has been utilized for the linear relationship, but total least squares (TLS) method provides more accurate slope and intercept theoretically because isotopic compositions of both oxygen and hydrogen have uncertainties. In this work, OLS and TLS were compared with isotopic compositions of snow and snowmelt collected from the King Sejong Station, Antarctica and isotopic compositions of water vapor observed by Lee et al. (2013) in the western part of Korea. The slopes from the linear relationship of isotopic compositions of snow and snowmelt at the King Sejong Station were estimated to be 7.00 (OLS) and 7.16(TLS) and the slopes of stable water vapor isotopes were 7.75(OLS) and 7.87(TLS). There was a melting process in the snow near the King Sejong Station and the water vapor was directly transported from the ocean to the study area based on the slope calculations. There is no significant difference in two slopes to interpret the physical processes. However, it is necessary to evaluate the slope differences from the two methods for studies for example, groundwater recharge processes, using the absolute slope values.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.1
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• pp.9-16
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• 2014

The localization compensation algorithm for moving objects using the least-squares method is suggested and the performance of the algorithm is analyzed in this paper. The suggested compensation algorithm measures the distance values of the mobile object moving as a constant speed by the TMVS (TWR Minimum Value Selection) method, estimates the location of the mobile node by the trilateration scheme based on the values, and the estimated location is compensated using the least-squares method. By experiments, it is confirmed that the localization performance of the suggested compensation algorithm is largely improved to 58.84% and 40.28% compared with the conventional trilateration method in the scenario 1 and 2, respectively.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.53-56
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• 2000

본 논문에서는 컬러이미지의 스케일링(scaling)을 위해 경사투영방법을 사용하여 기본적인 보간방법, 최소자승근사(least square approximation)의 결과들과 비교하여 보았다. 경사투영방법은 최소의 근사오차(approximation error)를 제공하는 수직투영(orthogonal projection)방법과 유사한 결과를 제공하며 전처리 필터 디자인에 자유성을 부여하고, 좀 더 일반화된 형태의 보간 방법이다. 사용된 방법을 기본적인 보간법들과 비교하여 보았을 때 더 좋은 PSNR의 결과를 얻을 수 있었으며 최소자승근사 방법과 유사한 결과들을 얻을 수가 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.5
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• pp.747-753
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• 2018

In the license-plate recognition systems for automobile black Image, the license-plate image frequently has a shadow due to outdoor environments which are frequently changing. Such a shadow makes unpredictable errors in the segmentation process of individual characters and numbers of the license plate image, and reduces the overall recognition rate. In this paper, to improve the recognition rate in these circumstance, a license-plate image binarization algorithm is proposed removing the shadow effectively. The propose algorithm splits the license-plate image into the regions with the shadow and without. To find out the boundary of two regions, the algorithm estimates the curve for shadow boundary using the least-squares method. The simulation is performed for the license-plate image having its shadow, and the results show much higher recognition rate than the previous algorithm.

• Journal of Korean Society of Forest Science
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• v.79 no.3
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• pp.260-268
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• 1990

Two types of ridge regression estimators were compared with the ordinary least squares (OLS) estimator in order to select the "best" estimator when multicollinearitc existed. The ridge estimators were Mallows's (1973) $C_P$-like statistic, and Allen's (1974) PRESS-like statistic. The evaluation was conducted based on the predictive ability of a yield model developed by Matney et al. (1988). A total of 522 plots from the data of the Southwide Loblolly Pine Seed Source study was used in this study. All of ridge estimators were better in predictive ability than the OLS estimator. The ridge estimator obtained by using Mallows's statistic performed the best. Thus, ridge estimators can be recommended as an alternative estimator when multicollinearity exists among independent variables.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.219-224
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• 2020

Binary classification has been broadly investigated in machine learning. In addition, binary classification can be easily extended to multi class problems. To successfully utilize machine learning methods for classification tasks, preprocessing and feature extraction steps are essential. These are important steps to improve their classification performances. In this paper, we propose a new learning method based on weighted least squares. In the weighted least squares, designing weights has a significant role. Due to this necessity, we also propose a new technique to obtain weights that can achieve feature transformation. Based on this weighting technique, we also propose a method to combine the learning and feature extraction processes together to perform both processes simultaneously in one step. The proposed method shows the promising performance on five UCI machine learning data sets.

• Tunnel and Underground Space
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• v.15 no.2 s.55
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• pp.137-144
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• 2005

An estimation technique of the joint diameter distribution using the least square method is suggested. When utilizing the technique by Song and Lee, the diameter distribution would be obtained only from the trace length distribution defined in an infinite window after the trace length distribution is estimated from the contained trace length distribution. With the new technique, however, the diameter distribution can be directly obtained from the sample histogram of the contained trace lengths. Compared with the previous technique, it shows a more accurate result for small sizes of joint samples and provides the joint geometry parameter of volumetric frequency. Verification of this new technique was completed by using Monte Carlo simulations.