• Title/Summary/Keyword: relative bias

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Relative Magneto-current of Magnetic Tunnel Transistor with Amorphous n-type Si Film

  • Lee, Sang-Suk;Lee, Jin-Yong;Hwang, Do-Guwn
    • Journal of Magnetics
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    • v.9 no.1
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    • pp.23-26
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    • 2004
  • A magneto-current (MC) was investigated for magnetic tunnel transistor (MTT) with amorphous n-type Si film. A relative MC (more than 49.6%) was observed at an emitter-base bias voltage ($V_{EB}$) of 0.65 V at room temperature. Above a $V_{EB}$ of 0.70 V, however, a rapid decrease in MC was observed in the amorphous Si-based MTT. The collector current increasing and transfer ratio as emitter-base voltage were mainly due to the rapid creation electrons of conduction band states in the Si collector. This approach would make integration in various components and systems easier than a MTT grown on a semiconductor wafer.

New Calibration Methods with Asymmetric Data

  • Kim, Sung-Su
    • The Korean Journal of Applied Statistics
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    • v.23 no.4
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    • pp.759-765
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    • 2010
  • In this paper, two new inverse regression methods are introduced. One is a distance based method, and the other is a likelihood based method. While a model is fitted by minimizing the sum of squared prediction errors of y's and x's in the classical and inverse methods, respectively. In the new distance based method, we simultaneously minimize the sum of both squared prediction errors. In the likelihood based method, we propose an inverse regression with Arnold-Beaver Skew Normal(ABSN) error distribution. Using the cross validation method with an asymmetric real data set, two new and two existing methods are studied based on the relative prediction bias(RBP) criteria.

Pooling shrinkage estimator of reliability for exponential failure model using the sampling plan (n, C, T)

  • Al-Hemyari, Z.A.;Jehel, A.K.
    • International Journal of Reliability and Applications
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    • v.12 no.1
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    • pp.61-77
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    • 2011
  • One of the most important problems in the estimation of the parameter of the failure model, is the cost of experimental sampling units, which can be reduced by using any prior information available about ${\theta}$, and devising a two-stage pooling shrunken estimation procedure. We have proposed an estimator of the reliability function (R(t)) of the exponential model using two-stage time censored data when a prior value about the unknown parameter (${\theta}$) is available from the past. To compare the performance of the proposed estimator with the classical estimator, computer intensive calculations for bias, mean squared error, relative efficiency, expected sample size and percentage of the overall sample size saved expressions, were done for varying the constants involved in the proposed estimator (${\tilde{R}}$(t)).

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Improvement of Target Motion Analysis for a Passive Sonar System with Measurement Bias Estimation (측정각 Bias 보상을 통한 수동소나체계의 표적기동분석 성능 향상 연구)

  • Yoo, Phil-Hoon;Song, Taek-Lyul
    • Proceedings of the KIEE Conference
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    • 2001.07d
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    • pp.2011-2013
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    • 2001
  • In this paper the MMAE(Multiple Model Adaptive Estimation) algorithm using the MGEKF(Modified Gain Extended Kalman Filter) of which modes are set to be measurement biases is proposed to enhance the performance of target tracking with bearing only measurements. The state are composed of relative position, relative velocity and taregt acceleration. The mode probability is calculated from the bearing only measurements from the HMS(Hull-Mounted Sonar). The proposed algorithm is tested in a series of computer simulation runs.

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Comparison of Statistic Methods for Evaluating Crop Model Performance (작물모형 평가를 위한 통계적 방법들에 대한 비교)

  • Kim, Junhwan;Lee, Chung-Kuen;Shon, Jiyoung;Choi, Kyung-Jin;Yoon, Younghwan
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.14 no.4
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    • pp.269-276
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    • 2012
  • The objective of this short communication is to introduce several evaluation methods to crop model users because the evaluation of crop model performance is an important step to develop or select crop model. In this paper, mean error, mean absolute error, index of agreement, root mean square error, efficiency of model, accuracy factor and bias factor were explained and compared in terms of dimension and observed number. Efficiency of model and index of agreement are dimensionless and independent of number of observation. Relative root mean square, accuracy factor and bias factor are dimensionless and not independent of number of observation. Mean error and mean absolute error are affected by dimension and number of observation.

The Study on the SPICE Model Parameter Extraction Method for the Schottky Diode Under DC Forward Bias (DC 순방향 바이어스 인가조건에서 Schottky 다이오드의 SPICE 모델 파라미터 추출 방법에 관한 연구)

  • Lee, Un-Gu
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.3
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    • pp.439-444
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    • 2016
  • The method for extracting the SPICE model parameter of Schottky diode under DC forward bias is proposed. A method for improving the accuracy of the SPICE model parameter at various temperatures is proposed. Three analysis steps according to the magnitude of the current is used in order to extract the parameters effectively. At each analysis step, initial parameters are calculated by using the current-voltage equations and the Levenberg-Marquardt analysis is proceeded. To verify the validity of the proposed method, the SPICE model parameters for the BAT45 and FSV1045 under DC forward bias is extracted. Schottky diode currents obtained from the proposed method shows the average relative error of 6.1% and 9% compared with the measured data for the BAT45 and FSV1045 sample at various temperatures.

Acceptable Values of Kappa for Comparison of Two Groups

  • Seigel Daniel G.;Podgor Marvin J.;Remaley Nancy A.
    • 대한예방의학회:학술대회논문집
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    • 1994.02b
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    • pp.129-136
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    • 1994
  • A model was developed for a simple clinical trial in which graders had defined probabilities of misclassifying pathologic material to disease present or absent. The authors compared Kappa between graders, and efficiency and bias in the clinical trial in the presence of misclassification. Though related to bias and efficiency, Kappa did not predict these two statistics well. These results pertain generally to evaluation of systems for encoding medical information, and the relevance of Kappa in determining whether such systems are ready for use in comparative studies. The authors conclude that, by itself, Kappa is not informative Enough to evaluate the appropriateness of a grading scheme for comparative studies. Additional, and perhaps difficult, questions must be addressed for such evaluation.

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Fast Speaker Adaptation and Environment Compensation Based on Eigenspace-based MLLR (Eigenspace-based MLLR에 기반한 고속 화자적응 및 환경보상)

  • Song Hwa-Jeon;Kim Hyung-Soon
    • MALSORI
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    • no.58
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    • pp.35-44
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    • 2006
  • Maximum likelihood linear regression (MLLR) adaptation experiences severe performance degradation with very tiny amount of adaptation data. Eigenspace- based MLLR, as an alternative to MLLR for fast speaker adaptation, also has a weak point that it cannot deal with the mismatch between training and testing environments. In this paper, we propose a simultaneous fast speaker and environment adaptation based on eigenspace-based MLLR. We also extend the sub-stream based eigenspace-based MLLR to generalize the eigenspace-based MLLR with bias compensation. A vocabulary-independent word recognition experiment shows the proposed algorithm is superior to eigenspace-based MLLR regardless of the amount of adaptation data in diverse noisy environments. Especially, proposed sub-stream eigenspace-based MLLR with bias compensation yields 67% relative improvement with 10 adaptation words in 10 dB SNR environment, in comparison with the conventional eigenspace-based MLLR.

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Methods for On-Line Determination of Truncation Point in Steady-State Simulation Outputs (안정상태 시뮬레이션 출력 데이터의 온라인 제거 시점 결정 방법)

  • 이영해
    • Journal of the Korea Society for Simulation
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    • v.7 no.1
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    • pp.27-37
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    • 1998
  • Simulation output is generally stochastic and autocorrelated, and includes the initial condition bias. To exclude the bias, the determination of truncation point has been one of important issues for the steady-state simulation output analysis. In this paper, two methods are presented for detection of truncation point in order to estimate efficiently the steady-state measure of simulation output. They are based on the Euclidean distance equation, and the backpropagation algorithm in Neural Networks. The experimental results obtained by M/M/1 and M/M/2 show that the proposed methods are very promising with respect to coverage and relative bias. The methods could be used for the on-line analysis of simulation outputs.

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Domain formation characteristics during thermomagnetic recording for amorphous TbFe and TbFeCo alloy thin films

  • Kim, Soon-Gwang
    • Proceedings of the Optical Society of Korea Conference
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    • 1989.02a
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    • pp.235-241
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    • 1989
  • Static according tests were carried out on a series of amorphous TbFe thin films of various composition under a constant laser irradiation condition. Examination of recorded domain configurations by using polarizing microscope led to the categorization of domain characteristics into 3 distinctly different types; i.c., type A: circular domains with smooth boundaries, the size not sensitive to variation of bias field, type B: domains of irregular shape at low bias, the size increasing and the boundaries getting smoother and more circular with increasing bias field and type C: not recordable. Critical factor which distinguishes among each types was fond to be the relative magnitude of H and H of the film near T, regardless of constituent atomic species. Micromagnetical process of thermomagnetic recording cycle was analyzed scheniatically for each type.

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