• Communications for Statistical Applications and Methods
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• 제6권1호
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• pp.285-292
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• 1999

In this paper we propose the several estimators of the Lorenz curve in the Pareto distribution and obtain the bias and the mean squared error for each estimator. We compare the proposed estimators with the uniformly minimum variance unbiased estimator (UMVUE) and the maximum likelihood estimator (MLE) in terms of the mean squared error (MSE) through Monte Carlo methods and discuss the results.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1095-1098
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• 1996

In this work, attitude determination with Inertial Reference Unit as attitude sensor is considered. Usually, the attitude error from IRU increases because of gyro rate bias and noise. Therefore, other attitude sensors(sun sensor, horizon sensor, star tracker) are needed to compensate for error from IRU. In this paper, we use the extended Kalman filter for attitude estimation of spacecraft with IRU and star tracker.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.710-713
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• 1996

This paper deals with the fault detection problem in uncertain linear multivariable systems having both model mismatch and noise. A robust detection presented by Kwon et al.(1994) for SISO systems has been here extended to the multivariable systems are derived. The model mismatch includes here linearization error as well as undermodelling. Comparisons are made with alternative fault detection method which do not account noise. The new method is shown to have good performance.

• Journal of the Korean Data and Information Science Society
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• 제20권5호
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• pp.895-903
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• 2009

The penalized partial likelihood based on restricted maximum likelihood method has been widely used for the inference of frailty models. However, the standard-error estimate for frailty parameter estimator can be downwardly biased. In this paper we show that such underestimation can be corrected by using hierarchical likelihood. In particular, the hierarchical likelihood gives a statistically efficient procedure for various random-effect models including frailty models. The proposed method is illustrated via a numerical example and simulation study. The simulation results demonstrate that the corrected standard-error estimate largely improves such bias.

• Journal of the Optical Society of Korea
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• 제11권1호
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• pp.10-17
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• 2007

We need two operation modes to obtain the complex hologram without bias and the conjugate image in the modified triangular interferometer (MTI). To solve the problem, we proposed the optimized MTI with one wave plate, which can obtain cosine and sine functions by the combination of one wave plate and one linear polarizer. In the extraction of phase term using the combination of polarization components, the phase error occurs, and we analyzed such potential phase errors in the optimized MTI.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2345-2347
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• 2001

본 연구에서는 반도체형으로 생산된 가속도센서를 적용하여 거리를 측정하는데 있어 문제점에 대해 언급하고, bias drift error에 따른 적분 누적오차를 줄이기 위한 방법으로 random noise를 감소시키고 위치추정을 위한 데이터 융합에 가장 일반적으로 적용되는 Kalman Filter 알고리즘을 적용하여 가속도 데이터를 상대적 위치 데이터로 변환하여 거리측정에 적용하였다. 또한 가속도센서를 관절형 로봇에 부착시켜 실험하여 이동거리를 산출하는 실험을 수행하였다. 실험 결과 보상 알고리즘을 사용했을 때의 zero drift error과 누적오차가 감소됨을 알 수 있었다.

• ETRI Journal
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• 제34권6호
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• pp.885-891
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• 2012

This paper proposes a high-efficiency power amplifier (PA) with uneven bias. The proposed amplifier consists of a driver amplifier, power stages of the main amplifier with class AB bias, and an auxiliary amplifier with class C bias. Unlike other CMOS PAs, the amplifier adopts a current-mode transformer-based combiner to reduce the output stage loss and size. As a result, the amplifier can improve the efficiency and reduce the quiescent current. The fully integrated CMOS PA is implemented using the commercial Taiwan Semiconductor Manufacturing Company 0.18-${\mu}m$ RF-CMOS process with a supply voltage of 3.3 V. The measured gain, $P_{1dB}$, and efficiency at $P_{1dB}$ are 29 dB, 28.1 dBm, and 37.9%, respectively. When the PA is tested with 54 Mbps of an 802.11g WLAN orthogonal frequency division multiplexing signal, a 25-dB error vector magnitude compliant output power of 22 dBm and a 21.5% efficiency can be obtained.

• ETRI Journal
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• 제34권3호
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• pp.379-387
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• 2012

In this paper, an error compensation technique for a dead reckoning (DR) system using a magnetic compass module is proposed. The magnetic compass-based azimuth may include a bias that varies with location due to the surrounding magnetic sources. In this paper, the DR system is integrated with a Global Positioning System (GPS) receiver using a finite impulse response (FIR) filter to reduce errors. This filter can estimate the varying bias more effectively than the conventional Kalman filter, which has an infinite impulse response structure. Moreover, the conventional receding horizon Kalman FIR (RHKF) filter is modified for application in nonlinear systems and to compensate the drawbacks of the RHKF filter. The modified RHKF filter is a novel RHKF filter scheme for nonlinear dynamics. The inverse covariance form of the linearized Kalman filter is combined with a receding horizon FIR strategy. This filter is then combined with an extended Kalman filter to enhance the convergence characteristics of the FIR filter. Also, the receding interval is extended to reduce the computational burden. The performance of the proposed DR/GPS integrated system using the modified RHKF filter is evaluated through simulation.

• Quantitative Bio-Science
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• 제37권2호
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• pp.133-141
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• 2018

Graphical lasso is one of the most popular methods to estimate a sparse precision matrix, which is an inverse of a covariance matrix. The objective function of graphical lasso imposes an ${\ell}_1$-penalty on the (vectorized) precision matrix, where a tuning parameter controls the strength of the penalization. The selection of the tuning parameter is practically and theoretically important since the performance of the estimation depends on an appropriate choice of tuning parameter. While information criteria (e.g. AIC, BIC, or extended BIC) have been widely used, they require an asymptotically unbiased estimator to select optimal tuning parameter. Thus, the biasedness of the ${\ell}_1$-regularized estimate in the graphical lasso may lead to a suboptimal tuning. In this paper, we propose a two-staged bias-correction procedure for the graphical lasso, where the first stage runs the usual graphical lasso and the second stage reruns the procedure with an additional constraint that zero estimates at the first stage remain zero. Our simulation and real data example show that the proposed bias correction improved on both edge recovery and estimation error compared to the single-staged graphical lasso.

• 한국과학교육학회지
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• 제36권6호
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• pp.935-946
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• 2016

이 연구의 목적은 과학교육과 관련된 인지편향을 확인하고 과학교육을 통하여 인지편향을 줄일 수 있는 방법을 확인하기 위하여 계획되었다. 문헌조사를 통하여 연구되어진 인지편향을 수집하였고, 과학학습의 관련성이 높은 인지편향을 과학교육전문가와의 토론을 통하여 추출하였다. 연구 결과 합리적 인과관계추론을 방해하는 인지편향, 다양한 정보와 결론 생성을 방해하는 인지편향, 자기반성적 학습을 방해하는 인지편향, 자기 주도적 의사결정을 방해하는 인지편향, 범주 제한적 사고를 조장하는 인지편향의 다섯 가지로 분류하였고, 총 29개의 인지편향들을 조사하였다. 합리적 인과관계추론의 방해하는 인지편향은 목적론적 사고, 가용성 편향, 착각적 상관, 클러스터 착각이었다. 문제해결에서 다양한 정보의 탐색을 방해하는 인지편향은 선택적 지각, 실험자 편향, 확증편향, 단순 사고 효과, 주의 편향, 신념편향, 실용 오류, 기능적 고착, 틀 효과가 있었다. 자기반성적 학습을 방해하는 인지편향은 과도한 자신감 편향, 우월성 편향, 계획 오류, 기본적 귀인 오류, 더닝-크루거 효과, 사후확신편향, 맹점편향을 확인하였다. 자기 주도적 의사결정을 방해하는 인지편향은 동조효과, 편승효과, 집단사고, 권위에 호소, 정보편향이 있다. 마지막으로 범주 제한적 사고를 조장하는 인지편향으로는 심리학적 본질주의, 고정관념, 의인화, 외집단 동질성 편향이 있었다. 연구된 인지편향에 대한 심리학적 특징들과 과학교수-학습방법들을 토대로 인지편향을 줄이고 역량을 향상시킬 수 있는 수업 방법에 대해서 논의한다.