• Journal of Distribution Science
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• v.18 no.4
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• pp.79-85
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• 2020

Purpose: This study explores how cognitive impairment caused by social exclusion experience can be explained through cognitive narrowing and how it influences consumer's judgment and reasoning and results pseudodiagnosticity bias towards distribution brands. This study examines the characteristics of cognitive narrowing, which is one of the strategies for overcoming the negative emotions resulting from social exclusion, and how cognitive errors called pseudodiagnosticity bias occur due to cognitive narrowing in the evaluation of distribution brands. Research design, data and methodology: Present study was performed with 77 college students in Seoul. Participants were randomly assigned to the group who experienced social exclusion and the group who did not experience social exclusion. The analysis has been made of how the degree of bias of pseudodiagnosticity differs according to the experience of social exclusion by t-test. Results: The group who experienced social exclusion had a higher level of pseudodiagnosticity bias towards distribution brands than the group who did not experience social exclusion. Conclusions: This study confirmed what characteristics of cognitive narrowing, which is one of the strategies for overcoming the negative emotions resulting from social exclusion, and how cognitive errors called pseudodiagnosticity bias occur due to cognitive narrowing. Implications and future research directions were discussed and suggested.

• Journal of Forest and Environmental Science
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• v.13 no.1
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• pp.81-89
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• 1997

Urban river needs continuous observation for the river conservation because river surrounding environment sensitivly is changed by human activity. In order to grasp the effect of human activity against Taebaek river in Chunchon city, this research analysed the channel shape change, fluctuation volume and bias degree over five times, for June, 1993 to June, 1996. The results were as follows : 1. The change of channel shape on each surveying time mainly occurred in June, 1996 and maximum deposition. $1,247m^3$ occurred on 19~20 section, maximum scouring, $340m^3$ occurred on 6~7 section, 2. When comparing with June, 1993, increased deposition volume of channelbed was about $4,600m^3$ in June, 1996, 3. The bias degree of channel mainly occurred in June, 1996 of surveying times and at 6, 7, 15, 16, 17, 18, 19, 20 line of surveying lines.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.159-165
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• 2020

With respect to the cause of asymmetric cost behavior, there are two streams of the literature. One stream focused on effect of managerial expectation and the other explained using agency system. In this study, we aim to investigate the determinants of asymmetric cost behavior in these streams. We first examine the impact of managerial overconfidence and optimistic bias on asymmetric cost. We also examine ownership ratio as a proxy of the quality of corporate governance effects on asymmetric cost. The results are as follows. First, firms have the anti-sticky asymmetric cost behavior. Second, we find that the firms with managerial optimistic bias mitigate the degree of asymmetric cost. This finding implies that managerial optimism is a factor that alters asymmetric cost behavior. Third, the degree of asymmetric cost is weaker in case of firms with higher manager's ownership. This result provides an important empirical evidence for understanding the role of corporate governance in cost behavior.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.7
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• pp.612-615
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• 2009

We need to control the growth orientation of CNTs on a substrate for applications to various electric devices. Generally, the flow direction of feed gases and electric field between two electrode affect to growth orientations of CNTs. In this paper, we varied tilt degrees $(0^{\circ},\;20^{\circ},\;35^{\circ},\;50^{\circ},\;65^{\circ},\;90^{\circ})$ of substrates on a cathode and DC bias voltages (0, 500, 700 V) applied between two electrodes in order to change growth orientations of CNTs. We confirmed that tilt degrees of the substrate and variation of DC bias voltages affected to the shape and orientation of the grown CNTs on the substrate.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1557-1567
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• 2014

In this paper, I propose a general hypothesis that after the enactment of the Sarbanes-Oxley Act (SOA) financial statements convey more accurate and reliable corporate information to investors who in turn reflect such improvements in stock prices and test four practical hypotheses that simultaneously feature the degree of information asymmetry, forecast bias, and investor reaction to biased earnings information. The empirical results unanimously suggest that the post-SOA investors take advantage of the improvement in informational efficiency and accuracy and actively adjust for analyst forecast bias in earnings forecasts. The SOA indeed appears to achieve its primary goal of investor protection.

• Journal of the Microelectronics and Packaging Society
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• v.12 no.3 s.36
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• pp.207-212
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• 2005

Al, Ti, Ta, and Cr thin films were deposited on a polyimide substrate using DC magnetron sputter to study the adhesion characteristics of metal films on polyimide substrates, while RF bias of 0 - 400 W was applied to the substrate during DC sputtering. The adhesion strength was evaluated using a 90-degree peel test. The peel tests showed that the adhesion strength was enhanced by applying the RF bias to the substrate in all specimens. Scanning electron microscopy and Auger depth profile of the fractured surfaces indicate that the polyimide underwent cohesive failure during peeling and heavy deformation was also observed in the metal films peeled from the polyimide substrate when the RF bias applied during the deposition. Cross-sectional transmission electron microscopy revealed that the metal/polyimide interface was not clear and complicated. This complicated interface, likely formed due to the RF bias applied to the substrate, was attributed to the adhesion enhancement observed during the bias sputtering.

• Korean Journal of Culture and Social Issue
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• v.26 no.3
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• pp.329-349
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• 2020

Confirmation bias is well known to be the cause of widespread misjudgment in the field of forensic decision-making. In this study, we examined the psychological mechanisms by which confirmation bias affects intentionality judgment in serious injury and death cases that combine the moral characteristics of the perpetrator and victim differently. As a result, participants perceived the case as a more typical criminal case when both the perpetrator and victim were bad people, and gave higher intention to perpetrators' actions in these typical crimes. In particular, it was found that people with a high degree of confirmation bias highly judge the intention of the offenders in a consistent way with the stereotype of criminal cases. However, in serious criminal cases, the moderate effect of confirmation bias has disappeared and only the effect of crime typicality has existed. Finally, we discussed implications of this study and ways to reduce bias in intentionality judgment.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.69-82
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• 2017

R-indicator (representativeness indicator) is used to check the representativeness of samples when non-responses occur. The representativeness is related with the accuracy of parameter estimator and the accuracy is related with bias of the estimator. Hence, unbiased estimator generates high accuracy. Therefore, high value of R-indicator guarantees the accuracy of parameter estimation with a small bias. R-indicator is calculated through propensity scores obtained by logit or probit modeling. In this paper we investigate the degree of relation between R-indicator and different non-response rates in strata using simulation studies. We also analyze a modified Korea Economic Census data for real data analysis.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.251-261
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• 2022

As AI has a wide range of influence on human social life, issues of transparency and ethics of AI are emerging. In particular, it is widely known that due to the existence of historical bias in data against ethics or regulatory frameworks for fairness, trained AI models based on such biased data could also impose bias or unfairness against a certain sensitive group (e.g., non-white, women). Demographic disparities due to AI, which refer to socially unacceptable bias that an AI model favors certain groups (e.g., white, men) over other groups (e.g., black, women), have been observed frequently in many applications of AI and many studies have been done recently to develop AI algorithms which remove or alleviate such demographic disparities in trained AI models. In this paper, we consider a problem of using the information in the sensitive variable for fair prediction when using the sensitive variable as a part of input variables is prohibitive by laws or regulations to avoid unfairness. As a way of reflecting the information in the sensitive variable to prediction, we consider a two-stage procedure. First, the sensitive variable is fully included in the learning phase to have a prediction model depending on the sensitive variable, and then an imputed sensitive variable is used in the prediction phase. The aim of this paper is to evaluate this procedure by analyzing several benchmark datasets. We illustrate that using an imputed sensitive variable is helpful to improve prediction accuracies without hampering the degree of fairness much.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.177-186
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• 2017

Recently, Autonomous vehicles are getting hot attention. Amazon, the biggest online shopping service provider is developing a delivery system that uses drones. This kinds of platforms are need accurate attitude information for navigation. In this paper, a structure design of AHRS using low-cost inertia sensor is proposed. To estimate attitudes a Kalman filter which uses a quaternion based dynamic model, bias-removed measurements from MEMS Gyro, raw measurements from MEMS accelerometer and magnetometer, is designed. To remove bias from MEMS Gyro, an additional Kalman filter which uses raw Gyro measurements and attitude estimates, is designed. The performance of implemented AHRS is compared with high price off-the-shelf 3DM-GX3-25 AHRS from Microstrain. The Gyro bias was estimated within 0.0001[deg/s]. And from the estimated attitude, roll and pitch angle error is smaller than 0.2 and 0.3 degree. Yaw angle error is smaller than 6 degree.