• Title/Summary/Keyword: response bias

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Equivalent-Circuit Analysis of Organic Light-Emitting Diodes using Frequency-dependent Response of $ITO/Alq_3/Al$ Device ($ITO/Alq_3/Al$ 소자의 주파수 의존 응답을 이용한 유기 발광소자의 등가회 로 분석)

  • Ahn, Joon-Ho;Chung, Dong-Hoe;Hur, Sung-Woo;Lee, Joon-Ung;Song, Min-Jong;Lee, Won-Jae;Kim, Tae-Wan
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2004.04a
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    • pp.5-8
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    • 2004
  • We have investigated equivalent-circuit analysis of organic light-emitting diodes using frequency-dependent response of $ITO/Alq_3(60nm)/Al$ device at two different bias voltages. Complex impedance Z of the device was measured in the frequency range of 40Hz~1MHz. A Cole-Cole plot shows that there are two dielectric relaxations at the bias below turn-on voltage, and one relaxation at the bias above turn-on voltage. We are able to interpret the frequency-dependent response in terms of equivalent-circuit model of contact resistance $R_s$ in series with parallel combination of resistance $R_p$ and capacitance $C_p$. We have obtained contact resistance $R_s$ around $90{\Omega}$, mainly from the ITO anode.

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Systematic Forecasting Bias of Exit Poll: Analysis of Exit Poll for 2010 Local Elections (출구조사의 체계적인 예측 편향에 대한 분석: 2010년 지방선거 출구조사를 중심으로)

  • Kim, Young-Won;Choi, Yun-Jung
    • Survey Research
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    • v.12 no.3
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    • pp.25-48
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    • 2011
  • In this paper, we overview the sample design, sampling error, non-response rate and prediction errors of the exit poll conducted for 2010 local elections and discusses how to detect a prediction bias in exit poll. To investigate the bias problem in exit poll in regional(Si-Do) level, we analyze exit poll data for 2007 presidential election and 2006 local elections as well as 2010 local elections in Korea. The measure of predictive accuracy A proposed by Martin et al.(2005) is used to assess the exit poll bias. The empirical studies based on three exit polls clearly show that there exits systematic bias in exit poll and the predictive bias of candidates affiliated to conservative party (such as Hannara-Dang) is serious in the specific regions. The result of this study on systematic bias will be very useful to improving the exit poll methodology in Korea.

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Effect of Attention Feedback Awareness and Control Training on Attention Bias and Generalized Anxiety Symptoms in college students (주의 피드백 인식 및 조절 훈련이 대학생의 주의편향 및 범불안에 미치는 효과)

  • Kim, Su Jung;Shim, Eun-Jung
    • Korean Journal of School Psychology
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    • v.16 no.2
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    • pp.207-230
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    • 2019
  • This study examined the effect of Attention Feedback Awareness and Control Training(A-FACT) on attention bias and generalized anxiety symptoms in college students. A total of 31 college students with at least 10 points on the Generalized Anxiety Disorder 7-item (GAD-7) scale or at least 56 points on the Korean version of the Penn State Worry Questionnaire (K-PSWQ) with attention bias were randomly assigned to one of three groups: A-FACT( n = 11), Attention Bias Modification (ABM)(n = 10) and Active Placebo Control (APC)(n = 10). Participants in A-FACT group received real-time feedback on attention bias based on their Baseline Neutral Response time(BNR) during A-FACT using a dot probe task. Participants in the ABM group received standard ABM, and those in the APC performed a dot probe task that they were informed was a program to reduce attention bias, but feedback was not provided. A total of eight sessions was conducted twice a week over a 4-week period. After every two sessions, GAD-7, K-PSWQ and K-STAI were rated. The effect of attention bias modification training was rated by changes in the Attention Bias Score(ABS), and in GAD-7, K-PSWQ and K-STAI scores. The results of repeated measure ANOVA indicated that the A-FACT group showed a significant decrease in ABS as well as in GAD-7, K-PSWQ and K-STAI scores compared to the other groups. Current results suggest that self-regulatory control of attention, that is, recognition of bias through feedback in A-FACT, may be effective in alleviating attention bias and generalized anxiety symptoms by recognizing bias through feedback on bias in attention bias modification training.

A Suggestion for Randomized Response Technique using Fuzzy Logic

  • Choi, Kyung-Ho
    • Communications for Statistical Applications and Methods
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    • v.8 no.2
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    • pp.465-471
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    • 2001
  • Randomized response technique is a survey technique for eliminating evasive answer bias. But this technique has a problem. This procedure suffers from linguistic expression in randomizing device. Thus for solving the problem, in this paper, we suggested the randomized response technique using fuzzy logic.

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Several Sources of Bias in Consumer Sensory Tests (소비자 관능검사 결과에 영향을 미치는 인자)

  • Seo, Dong-Sun;Sin, Yong-Guk;Baek, Seung-Cheon;Kim, Su-Gwang
    • Journal of Dairy Science and Biotechnology
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    • v.16 no.2
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    • pp.154-160
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    • 1998
  • The purpose of consumer sensory tests is to assess the personal response by current or potential customers of a product or specific product characteristics. There are several sources of bias in obtaining consumer response than often lead to misleading results. These biases include the situational variables of the testing environment, the products and the subjects. This paper discusses the sources of bias in consumer testing, need to be controlled when conducting consumer test.

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Determining the Relative Weights of Bias and Variance in Dual Response Surface Optimization (쌍대반응표면 최적화에서 편차와 분산의 가중치 결정에 관한 연구)

  • Jeong, In-Jun;Kim, Gwang-Jae;Jang, Su-Yeong;Lin, Dennis K.J.
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2004.05a
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    • pp.294-297
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    • 2004
  • Mean squared error (MSE) is an effective criterion to combine the mean and the standard deviation responses in dual response surface optimization. The bias and variance components of MSE need to be weighted properly in the given problem situation. This paper proposes a systematic method to determine the relative weights of bias and variance in accordance with a decision maker's prior and posterior preference structure.

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A performance improvement method in the gun fire control system compensating for measurement bias error of the target tracking sensor (표적추적센서의 측정 바이어스 오차 보상에 의한 사격통제장치 성능 향상 기법)

  • Kim, Jae-Hun;Lyou, Joon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.3 no.2
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    • pp.121-130
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    • 2000
  • A practical method is proposed to improve hit probability of the digital gun fire control system, when the measured rate of the tracking sensor becomes biased under some operational situation. For ground moving target it is shown that the well-known Kalman filter which uses position measurement only can be optimally used to eliminate the rate bias error. On the other hand, for 3D moving aircraft we present a new algorithm which incorporate FIR-type filter, which uses position and rate measurement at the same time, and the fixed-lag smoother using position measurement only, and show that it has the optimal performance in terms of both estimation accuracy and response time.

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Bayesian estimation for finite population proportion under selection bias via surrogate samples

  • Choi, Seong Mi;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1543-1550
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    • 2013
  • In this paper, we study Bayesian estimation for the finite population proportion in binary data under selection bias. We use a Bayesian nonignorable selection model to accommodate the selection mechanism. We compare four possible estimators of the finite population proportions based on data analysis as well as Monte Carlo simulation. It turns out that nonignorable selection model might be useful for weekly biased samples.

A Procedure for Fitting Nonadditive Models

  • Seo, Han-Son
    • Communications for Statistical Applications and Methods
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    • v.7 no.2
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    • pp.393-401
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    • 2000
  • Many graphical methods have been suggested for obtaining an impression of a curvature in regression problem in which some covariates enter nonlinearly. However when true model does not belong to the class of additive models, graphical methods may contain a serious bias. A method is suggested which can avoid such bias in the fitting of nonaddive models.

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