• Journal of IKEEE
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• v.6 no.1 s.10
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• pp.102-110
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• 2002

An effective scheme to detect and diagnose multiple failures in a dynamic system is described for the case where the measurement noise is correlated sequentially in time. It is based on the modified interacting multiple model (MIMM) estimation algorithm in which a generalized decorrelation process is developed by employing the autoregressive (AR) model for the colored noise and applying measurement difference method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1C
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• pp.79-85
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• 2008

Dirty Paper Coding(DPC) can achieve the sum capacity of a multiuser multiple-input multiple-output(MU MIMO) broadcast channels. However, due to the high computational complexity of the successive encoding and decoding, deploying DPC in real systems is impractical. As one of practical alternatives to DPC, Block Diagonalization(BD) was researched. BD is an extension of the zero-forcing preceding technique that eliminates interuser interference(IUI) in downlink MIMO systems. Though BD has lower complexity than DPC, BD shows poor sum capacity performance. We show that sum capacity performance of BD is degraded due to no IUI constraint. Then, we modify BD to improve its sum capacity performance with relaxing the constraint and sub optimal channel set searching. With simulation results, it can be verified that our modification in BD induces some improvement in sum capacity performance.

• Journal of the Korean Geotechnical Society
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• v.19 no.6
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• pp.371-378
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• 2003

The compression index of clay distributed in the west and south coast of the Korean Peninsula had been studied. Compression index was obtained from the conventional consolidation test, and was conducted accordingly to obtain the field virgin compression curve by means of Schmertmann's graphical correction. To examine a correlation closely between physical properties of soils($e_o$, LL, w) and compression index(Cc), linen. and non-linear regression analysis were employed based on the data collected from tests. The conclusions are as follows. The compression index obtained by means of Schmereann's graphical correction is about 1.16 times for the value of original oedometer test curve for U/D samples. Non-liner regression curve was preferable to establish a correlation equation rather than linear regression curve. All derived equations so far achieved have been summarized and given. However, linear equation is better for practical use so that part by part simplified linear equations were also suggested alternatively together with their own non-linear regression curve.

• The Journal of the Korea Contents Association
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• v.12 no.10
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• pp.330-339
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• 2012

The purpose of this study was to examine the relationship among children's ADHD symptoms, parenting stress and behavior regarding nurturing. The data were provided by 59 mothers of children with ADHD who is aged between 4 and 12. Mothers of children with ADHD were recruited through 3 departments of child psychiatry. The Korean version of Parenting Stress Index-Short Form, the Korean version of revised Maternal Behavior research Instrument(MBRI) and ADHD Rating Scale(K-ARS) was used to assess parenting stress, behavior regarding nurturing and ADHD symptoms respectively. Significant correlation was found between parental distress and warmth, rejection behavior. Parental distress is significant influence on behavior regarding nurturing through multiple regression analysis. Significant correlation was found between ADHD symptom and rejection behavior. ADHD symptom is significant influence on behavior regarding nurturing through multiple regression analysis. Behavior regarding nurturing is related to ADHD symptom, parental distress. Therefore, it is needed for not only treatment related to ADHD symptom but also interventions for behavior regarding nurturing for mothers of children with ADHD.

• Fire Science and Engineering
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• v.28 no.2
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• pp.69-75
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• 2014

This study derives the factors which affect the occurrence of arson from statistical data (population, economic, and social factors) by multiple regression analysis. Multiple regression analysis applies to 4 forms of functions, linear functions, semi-log functions, inverse log functions, and dual log functions. Also analysis respectively functions by using the stepwise progress which considered selection and deletion of the independent variable factors by each steps. In order to solve a problem of multiple regression analysis, autocorrelation and multicollinearity, Variance Inflation Factor (VIF) and the Durbin-Watson coefficient were considered. Through the analysis, the optimal model was determined by adjusted Rsquared which means statistical significance used determination, Adjusted R-squared of linear function is scored 0.935 (93.5%), the highest of the 4 forms of function, and so linear function is the optimal model in this study. Then interpretation to the optimal model is conducted. As a result of the analysis, the factors affecting the arson were resulted in lines, the incidence of crime (0.829), the general divorce rate (0.151), the financial autonomy rate (0.149), and the consumer price index (0.099).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1B
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• pp.9-20
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• 2012

Recently to overcome limitations of conceptual, hydrological and physics based models for flood stage forecasting, multiple linear regression model as one of data-driven models have been widely adopted for forecasting flood streamflow(stage). The objectives of this study are to compare performance of different multiple linear regression models according to regression coefficient estimation methods and determine most effective multiple linear regression flood stage forecasting models. To do this, the time scale was determined through the autocorrelation analysis of input data and different flood stage forecasting models developed using regression coefficient estimation methods such as LS(least square), WLS(weighted least square), SPW(stepwise) was applied to flood events in Jungrang stream. To evaluate performance of established models, fours statistical indices were used, namely; Root mean square error(RMSE), Nash Sutcliffe efficiency coefficient (NSEC), mean absolute error (MAE), adjusted coefficient of determination($R^{*2}$). The results show that the flood stage forecasting model using SPW(stepwise) parameter estimation can carry out the river flood stage prediction better in comparison with others, and the flood stage forecasting model using LS(least square) parameter estimation is also found to be slightly better than the flood stage forecasting model using WLS(weighted least square) parameter estimation.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.511-513
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• 2004

위성의 부분체 또는 탑재컴퓨터 및 탑재소프트웨어에 대한 검증시험을 수행하기 위해서는 위성개발에 사용하며 그 기능이 검증된 상용프로그램을 사용하는 것이 일반적이다. 그러나 위성 영령의 전송 및 텔레메트리 데이터의 전송과 분석을 위한 프로그램은 위성에 사용되는 종류 및 포맷에 따라 다양한 형태로 수정되어야 하기 때문에 자체 제작한 프로그램을 사용하게 된다. 99년에 발사되어 성공적으로 임무를 수행하고 있는 다목적실용위성 1호 및 현재 개발이 진행 중인 다목적실용위성 2호의 개발과정에서는 LEX와 YACC이라는 구문분석기를 이용한 VTSP(Verification Test Script Parser) 프로그램이 탑재소프트웨어의 검증시험에 사용되었다. VT5P는 실시간 데이터 전송 및 분석이 가능하지만 UNIX 환경에서만 실행되므로 윈도우 환경에서 작업하던 일반 사용자들에게는 익숙하지 않은 시험환경을 제공하여 텍스트 기반의 작업이 필요하므로 시험 수행에 여러 어려움들이 발생한다. 이러한 단점들을 보완하기 위하여 윈도우 기반의 검증시험 프로그램인 SATS(Spacecraft Automatic Test Script)를 개발하였다. 본 논문에서는 대부분의 사용자들에게 익숙한 윈도우 환경을 제공하며 이더넷을 통하여 장소에 상관없이 다중의 개발자가 시험을 수행할 수 있는 SATS의 개발현황과 수행환경에 대하며 소개한다.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.11
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• pp.1535-1542
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• 2001

A high resolution digital cinematic Particle Image Velocimetry(PIV) has been developed. The system consists of a high speed CCD camera, a continuous Ar-ion laser and a computer with camera controller. To improve the spatial resolution, we adopt a Recursive Technique for velocity interrogation. At first, we obtain a velocity vector fur a larger interrogation window size based on the conventional two-frame cross-correlation PIV analysis using the FFT algorithm. Based on the knowing velocity information, more spatially resolved velocity vectors are obtained in the next iteration step with smaller interrogation windows. When the correct velocity vector at the first step is found to be critical, a Multiple Correlation Validation(MCV) technique is applied to decrease the spurious vectors. The MCV technique turns out to improve SNR(Signal to Noise Ratio) of the correlation table. The developed cinematic PIV method has been applied to the measurement of the unsteady flow characteristics of a Rushton turbine mixer. A total of 3,245 instantaneous velocity vectors were successfully obtained with 4 ms time resolution. The acquired spatial resolution corresponds to the conventional high resolution digital PIV system using a 1K ${\times}$ 1K CCD camera.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.39-44
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• 2008

Wireless channel exists interference by multipath a component. Adaptation array antenna that remove this interference a component forms null point about interference signal and maximizes gains about target signal. If target signal and correlative coherent interference signal are received, there is problem that is removed from arrangement output to target signal. And, adaptation array antenna is shortcoming that is sensitive in directivity error. Therefore, in this paper, introduce each existing algorithm to solve directivity error about coherent interference, and proposed beam forming technique that minimize degree of freedom loss and damage because analyzes the problem and reduces coherent interference and directivity error.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.6 no.1
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• pp.35-39
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• 2001

Multibeam echosounder data, collected to investigate seabed features and topography, are usually subject to outliers resulting from the ship's irregular movements and insufficient correction for pressure calibration to the positions of beams. We introduce a statistical method which adjusts the outliers using the ARMA (Autoregressive Moving Average) technique. Our method was applied to a set of real data acquired in the East Sea. In our approach, autocorrelation of the data is modeled by an AR (1) model. If an observation is substantially different from that obtained from the estimated AR (1) model, it is declared as an outlier and adjusted using the estimated AR (1) model. This procedure is repeated until no outlier is found. The result of processing shows that outliers that are far greater than signals in amplitude were successfully removed.