• 천문학논총
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• 제20권1호
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• pp.97-107
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• 2005

We developed a data reduction program (RX) to process BOES data automatically. It processes a whole set of data taken during one night automatically - preprocessing, extraction to one-dimensional spectra and wavelength calibration. The execution is very fast and the performance looks pretty good. We described the performance of this program, comparing its procedure with that of IRAF. RX does not have functions for continuum normalization yet. We will develop those functions in the next works.

• 한국정보통신학회논문지
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• 제23권1호
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• pp.13-19
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• 2019

기계학습의 정확도는 학습용 데이터의 양과 데이터의 품질에 많은 영향을 받는다. 기존의 웹을 기반으로 학습용 데이터를 수집하는 것은 실제 학습과 무관한 데이터가 수집 될 수 있는 위험성이 있으며 데이터의 투명성을 보장할 수가 없다. 본 논문에서는 블록체인구조에서 블록들이 직접 병렬적으로 데이터를 수집하게 하고 각 블록들이 수집한 데이터를 타 블록의 데이터와 비교하여 양질의 데이터만을 선별하는 방안을 제안한다. 제안하는 시스템은 각 블록들은 데이터를 서로 블록체인을 통해 공유하며 All-reduce 구조의 Parallel-SGD를 활용하여 다른 블록들의 데이터와 비교를 통해 양질의 데이터만을 선별하여 학습용 데이터셋을 구성할 수가 있다. 또한 본 논문에서는 제안한 구조의 성능을 확인하기 위해 실험을 통해 기존의 벤치마크용 데이터셋의 이미지를 활용하여 변조된 이미지 사이에서 원본 이미지만을 양질의 데이터로 판별함을 확인하였다.

• 한국멀티미디어학회논문지
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• 제7권12호
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• pp.1745-1753
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• 2004

A method of estimating the pose of a three-dimensional object from a set of two-dimensioal images based on parametric eigenspace method is proposed. A Gaussian blurred edge image is used as an input image instead of the original image itself as has been used previously. The set of input images is compressed using K-L transformation. By comparing the estimation errors for the original, blurred original, edge, and blurred edge images, we show that blurring with the Gaussian function and the use of edge images enhance the data compression ratio and decrease the resulting from smoothing the trajectory in the parametric eigenspace, thereby allowing better pose estimation to be achieved than that obtainable using the original images as it is. The proposed method is shown to have improved efficiency, especially in cases with occlusion, position shift, and illumination variation. The results of the pose angle estimation show that the blurred edge image has the mean absolute errors of the pose angle in the measure of 4.09 degrees less for occlusion and 3.827 degrees less for position shift than that of the original image.

• Communications for Statistical Applications and Methods
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• 제25권2호
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• pp.109-130
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• 2018

Several measures of multivariate skewness for scale mixtures of skew-normal distributions are derived. As a special case, those of multivariate skew-t distribution are considered in detail. Furthermore, the similarities, differences, and behavior of these measures are explored for cases of some specific members of the multivariate skew-normal and skew-t distributions using a simulation study. Since some measures are vectors, it is better to take all measures in the same scale when comparing them. In order to attain such a set of comparable indices, the sample version is considered for each of the skewness measures that are taken as test statistics for the hypothesis of t distribution against skew-t distribution. An application is reported for the data set consisting of 71 total glycerol and magnesium contents in Grignolino wine.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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• pp.457-461
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• 1996

An optimum design methodology for the power MOSFET's with a predetermined mask is proposed and verified by comparing with the results of MEDICI simulation and the data of commercially available devices. Optimization is completed by determining a doping concentration and a thickness of the epitaxial layer which satisfy a specific voltage and current rating requirements as well as a minimum on-resistance for the mask set. The commercial HEX-1 mask set with a die area of $40.4{\times}10^{-3}\;cm^2$ and a T0-220 package has the on-resistance of $1.5{\Omega}$ at 200 V/2.5 A rating while the M-1 mask from this study exhibits $0.6{\Omega}$ on-resistance at 200 V/6 A. The 60 % reduction in the on-resistance and 58 % enhancement in the current rating have been obtained by the proposed method.

• Journal of Positioning, Navigation, and Timing
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• 제10권1호
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• pp.49-54
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• 2021

Indoor positioning system becomes of increasing interests due to the demands for accurate indoor location information where Global Navigation Satellite System signal does not approach. Wi-Fi access points (APs) built in many construction in advance helps developing a Wi-Fi Received Signal Strength Indicator (RSSI) based indoor localization. This localization method first collects pairs of position and RSSI measurement set, which is called fingerprint database, and then estimates a user's position when given a query measurement set by comparing the fingerprint database. The challenge arises from nonlinearity and noise on Wi-Fi RSSI measurements and complexity of handling a large amount of the fingerprint data. In this paper, machine learning techniques have been applied to implement Wi-Fi based localization. However, most of existing indoor localizations focus on single position estimation. The main contribution of this paper is to develop multi-target localization by using deep neural, which is beneficial when a massive crowd requests positioning service. This paper evaluates the proposed multilocalization based on deep learning from a multi-story building, and analyses its learning effect as increasing number of target positions.

• Journal of Multimedia Information System
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• 제1권1호
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• pp.1-10
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• 2014

In this paper, we propose a new view synthesis technique for coding of multi-view color and depth data in arbitrary camera arrangements. We treat each camera position as a 3-D point in world coordinates and build clusters of those vertices. Color and depth data within a cluster are gathered into one camera position using a hierarchical representation based on the concept of layered depth image (LDI). Since one camera can cover only a limited viewing range, we set multiple reference cameras so that multiple LDIs are generated to cover the whole viewing range. Therefore, we can enhance the visual quality of the reconstructed views from multiple LDIs comparing with that from a single LDI. From experimental results, the proposed scheme shows better coding performance under arbitrary camera configurations in terms of PSNR and subjective visual quality.

• International Journal of Contents
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• 제17권4호
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• pp.79-90
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• 2021

With the deepening of population aging, pension has become an urgent problem in most countries. Community smart pension can effectively resolve the problem of traditional pension, as well as meet the personalized and multi-level needs of the elderly. To predict the pension intention of the elderly in the community more accurately, this paper uses the decision tree classification method to classify the pension data. After missing value processing, normalization, discretization and data specification, the discretized sample data set is obtained. Then, by comparing the information gain and information gain rate of sample data features, the feature ranking is determined, and the C4.5 decision tree model is established. The model performs well in accuracy, precision, recall, AUC and other indicators under the condition of 10-fold cross-validation, and the precision was 89.5%, which can provide the certain basis for government decision-making.

• 한국전자통신학회논문지
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• 제10권1호
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• pp.65-72
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• 2015

스크램블링 기술을 적용한 AMI/HDB-3 방식은 장거리 데이터전송 회선부호화에 주로 사용된다. 본 논문은 정보통신용 부호 표준(KS X 1001 ; 2014 확인)에 규정되어 있는 한글낱자, 한글고어낱자용 부호집합에 대하여 데이터 링크 계층에서 HDLC Flag의 비트 또는 문자 스터핑과 물리계층의 AMI/HDB-3 스크램블링 측면에서 데이터 전송효율을 높이는 새로운 한글낱자용 부호집합 체계를 제시하였다. 기존 부호집합 체계와 비교를 위해 ($4{\times}4$) 비트 원천부호화 규칙과 한글낱자 사용빈도 통계를 적용한 결과, 약 22.01%의 데이터 처리효율이 향상되는 것으로 나타났다.

• 한국물환경학회지
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• 제26권5호
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• pp.860-870
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• 2010

Long term monthly monitoring data showed that the water quality of streams flowing into Lake Paldang has been improved by various strategy for water. However, the effect of quality on Lake Paldang is still insufficient because of nonpoint source from watershed. In order to evaluate quantifying methods for pollution source and make a suggestion on improvements, Storm Water Management Model (SWMM) was constructed by using data set from the water quality and streamflow monitoring network in the Kyoungan watershed for Total Maximum Daily Loads (TMDLs). Load duration curve (LDC) based on the result of the Kyoungan watershed SWMM indicated that the water quality criterion on $BOD_5$ was often exceeded in up-stream than down-stream. From flowrate-load correlation curve, SS load significantly increased as streamflow increases. 75.3% of streamflow and 62.1% of $BOD_5$ loads is discharged especially in the zone of high flows, but monitoring data set didn't provide proper information about the conditions and the patterns associated with storm events. Therefore, it is necessary to acquire representative data set for comparing hydrograph and pollutograph through monitoring experimental watershed and to establish methods for quantifying point and nonpoint source pollutant loads.