• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.538-547
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• 2016

With respect to the factors affecting information security awareness and behavior, the study of the relevance of the concept of optimistic bias is actively used in psychology. In other words, this study examines whether the optimistic bias of individuals affects information security in the field. In this sense, this study attempted to demonstrate the relevance of optimistic bias in information security behavior and awareness. A questionnaire survey was conducted targeting 111 people engaged in domestic private enterprises. The survey results showed that this personalized optimistic bias exists because of empirical factors related to personal security. Optimistic bias affects the security awareness information. The greater the optimistic bias, the lower the awareness and recognition of information security. In other words, optimistic bias affects information security awareness. Reducing the effects of optimistic bias is expected to reduce information security incidents, such as information leakages. However, the variety of information related ethical activities of a company did not have any effect on the information security awareness. Most previous studies have only examined the effect optimistic bias in the field of health. Therefore, this study fills an important gap in research in IT.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.4
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• pp.561-570
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• 2018

This study defined the changes of mechanical properties of silk fabric according to bias angles and investigated the influence of bias angles and fabric characteristics on hand value. For the experiments, 4 types of commercial silk plain weave fabrics were chosen. All fabrics had the same density, but different yarn characteristics. Fabric samples were cut into 12 different bias angles between $0^{\circ}$ and $165^{\circ}$ with $15^{\circ}$ gap and measured for tensile, shear, bending, surface properties by the KES-FB system. As a result, most mechanical parameters showed an asymmetry shape with $90^{\circ}$. The most flexible and easiest angles are $45^{\circ}$, $135^{\circ}$. Furthermore, the bias angles of silk fabrics were classified into three clusters with mechanical properties such as WT, 2HG, 2HG5, B, and SMD. The parameters according to fabric samples showed significant differences at WT, RT, B, 2HB, and MIU. It showed bigger effects as yarn fineness; in addition, twists were higher except RT. The results of hand value indicated that Koshi and Hari were highest with a bias angle of $75^{\circ}$; however, Shinayakasa was highest at bias angle of $45^{\circ}$. Finally, Shari was lowest at $45^{\circ}$.

• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.4
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• pp.384-393
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• 2013

In this paper, a design of planar microwave bias-tee using lumped elements was presented. The bias-tee is composed of 2 blocks; DC block and RF choke. For this design of the bias-tee, a wideband capacitor was used for DC block. For a RF choke, a series connection of inductors which have different SRFs is used for a RF choke. In the RF choke, a series connection of resistor and capacitor was added in shunt to eliminate a loss from a series resonance. The designed bias-tee was implemented by using 1608 SMT chip components. The fabricated bias-tee was measured using Anritsu 3680K fixture which enables to remove an effect of a connector. The fabricated bias-tee presented -15 dB of return loss and -1.5 dB insertion loss at 10 MHz~18 GHz.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.637-648
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• 2007

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.

• Atmosphere
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• v.30 no.2
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• pp.155-167
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• 2020

In order to produce more detailed and accurate information of river discharge and freshwater discharge, global high-resolution hydrodynamic model (CaMa-Flood) is applied to an operational land surface model of global seasonal forecast system. In addition, bias correction to grid runoff for the hydrodynamic model is attempted. CaMa-Flood is a river routing model that distributes runoff forcing from a land surface model to oceans or inland seas along continentalscale rivers, which can represent flood stage and river discharge explicitly. The runoff data generated by the land surface model are bias-corrected by using composite runoff data from UNH-GRDC. The impact of bias-correction on the runoff, which is spatially resolved on 0.5° grid, has been evaluated for 1991~2010. It is shown that bias-correction increases runoff by 30% on average over all continents, which is closer to UNH-GRDC. Two experiments with coupled CaMa-Flood are carried out to produce river discharge: one using this bias correction and the other not using. It is found that the experiment adapting bias correction exhibits significant increase of both river discharge over major rivers around the world and continental freshwater discharge into oceans (40% globally), which is closer to GRDC. These preliminary results indicate that the application of CaMa-Flood as well as bias-corrected runoff to the operational global seasonal forecast system is feasible to attain information of surface water cycle from a coupled suite of atmospheric, land surface, and hydrodynamic model.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.30 no.2
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• pp.1-18
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• 2017

Objectives : This review aims to evaluate a risk of bias by risk of bias tool and RoBANS(Risk of Bias Assessment tool for Non-randomized Study) tool for clinical trial papers proving treatment effect of Korean medicines to alopecia and provides the newest reason of effectiveness of herbs to alopecia. Methods : Data were collected through electronic database including NDSL, KISS, KMBASE, Koreantk, OASIS, KoreaMed, KISTI, Pubmed, Cochrane CENTRAL and CINAHL. Two experts in Oriental Medicine assessed risk of bias of randomized controlled trials by Cochrane group's Risk of Bias tool and non-randomized controlled trials by RoBANS tool after searching, reviewing and selecting papers. Results : Total number of selected trials is 20 including 4 randomized controlled trial, 13 non-randomized controlled trials and 3 case reports. This study evaluate the risk of bias of 17 papers including 4 randomized controlled trials and 13 non-randomized controlled trials except 3 case reports by risk of bias tool and RoBANS tool. All papers of randomized controlled trials are evaluated unclear for random sequence generation and allocation concealment as there are no word on them. And all papers of non-randomized controlled trials are evaluated unclear for blinding of outcome assessments and relatively low for others. Conclusions : Korean medicine intervention can be an effective for treatment in alopecia. It was evaluated by hair density, thickness and expert panel assessment of photographs and all results are statistically significant. But enhancing levels of evidence, we must try to reduce bias in researches and report a safety, protocol and IRB.

• Wind and Structures
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• v.30 no.4
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• pp.393-403
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• 2020

One of the growing concerns of the wind energy production is wind ramp events. To improve the wind ramp event forecasts, the nonlinear Kalman filter bias correction method was applied to 24-h wind speed forecasts issued from the WRF model at 70-m height in Zhangbei wind farm, Hebei Province, China for a two-year period. The Kalman filter shows the remarkable ability of improving forecast skill for real-time wind speed forecasts by decreasing RMSE by 32% from 3.26 m s_-1 to 2.21 m s_-1, reducing BIAS almost to zero, and improving correlation from 0.58 to 0.82. The bias correction improves the forecast skill especially in wind speed intervals sensitive to wind power prediction. The fact shows that the Kalman filter is especially suitable for wind power prediction. Moreover, the bias correction method performs well under abrupt weather transition. As to the overall performance for improving the forecast skill of ramp events, the Kalman filter shows noticeable improvements based on POD and TSS. The bias correction increases the POD score of up-ramps from 0.27 to 0.39 and from 0.26 to 0.38 for down-ramps. After bias correction, the TSS score is significantly promoted from 0.12 to 0.26 for up-ramps and from 0.13 to 0.25 for down-ramps.

• Journal of the Korean Vacuum Society
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• v.7 no.2
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• pp.94-103
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• 1998

We investigated a bias effect for diamond films deposited by a HFCVD(Hot Filament Chemical Vapor Deposition) method using a methane-hydrogen gas mixture. During deposition total chamber pressure, methane concentration, filament temperature and substrate temperature was 20 torr, 1.0%, $2100^{\circ}C$ and $980^{\circ}C$ respectively. Also DC bias was applied during both the nucleation stage and the growth stage systematically. We found that negative bias enhanced the nucleation density at the nucleation stage, but it made a bad influence on the morpholohy of films at the growth stage. Positive bias enhanced the growth rate and resulted in a good morpholohy of films. Therefore we concluded that it was effective to apply the negative bias during the nucleation stage and then to switch into the positive bias during the growth stage in the fabrication of diamond films.

• Journal of Korea Water Resources Association
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• v.52 no.9
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• pp.589-601
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• 2019

Various applications of radar rainfall data have been actively employed in the field of hydro-meteorology. Since radar rainfall is estimated by using predefined reflectivity-rainfall intensity relationships, they may not have sufficient reproducibility of observations. In this study, a generalized linear model is introduced to better capture the Z-R relationship in the context of bias correction within a Bayesian regression framework. The bias-corrected radar rainfall with the generalized linear model is more accurate than the widely used mean field bias correction method. In addition, we analyzed variability of the bias correction parameters under various geomorphological conditions such as the height of the weather station and the separation distance from the radar. The identified relationship is finally used to derive a regionalized formula which can provide bias correction factors over the entire watershed. It can be concluded that the bias correction parameters and regionalized method obtained from this study could be useful in the field of radar hydrology.