• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.32-35
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• 1996

In this paper, it is shown that the dominant errors of baro-altimeters can be characterized by bias and scale factor errors. Also an optimal filter for estimating both bias and scale factor is derived based on the concept of model transition. The optimal filter is, however, not realizable because the model transition hypotheses increase exponentially. Therefore a realizable suboptimal filter using the interacting multiple model(IMM) technique is proposed. Computer simulation results show that the estimation errors of the proposed filter are smaller than those of the conventional least squares algorithm with a forgetting factor when both the bias and the scale factor are varying.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.355-360
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• 2021

In this study, the factors of confirmation bias that may occur in the initial user experience stage were analyzed using a honeycomb model by deriving user experience factors for each factor. In the initial user experience stage, confirmation bias occurs in the impression stage. At the processing stage of memory, sensory memory, working memory, and long-term memory, which stores and retrieves selective memory, were closely related. Confirmation bias was classified into visibility, correlation, memory, clarity, and universality in the usability part, and satisfaction, joy, and dissatisfaction were derived as emotional factors. As a result of the analysis with the honeycomb model, visuality, clarity, universality in the usability factor, and joy in the emotional factor had little effect on the confirmation bias, and satisfaction and dissatisfaction were analyzed as the main factors of the confirmation bias in the correlation, memory and emotional factors. This study is meaningful in that it can be usefully used as a reference material for companies that customize design patterns for the factor of confirmation bias.

• Journal of Magnetics
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• v.19 no.3
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• pp.215-220
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• 2014

This study investigates the dynamic magneto-mechanical behavior of magnetization-graded ferromagnetic materials Terfenol-D/FeCuNbSiB (MF). We measure the dynamic magneto-mechanical properties as a function of the DC bias magnetic field ($H_{dc}$). Our experimental results show that these dynamic magneto-mechanical properties are strongly dependent on the DC bias magnetic field. Furthermore, the dynamic strain coefficient, electromechanical resonance frequency, Young's moduli, and mechanical quality factor of Terfenol-D/FeCuNbSiB are greater than those of Terfenol-D under a lower DC bias magnetic field. The dynamic strain coefficient increases by a factor of between one and three, under the same DC bias magnetic field. In particular, the dynamic strain coefficient of Terfenol-D/FeCuNbSiB at zero bias achieves 48.6 nm/A, which is about 3.05 times larger than that of Terfenol-D. These good performances indicate that magnetization-graded ferromagnetic materials show promise for application in magnetic sensors.

• Research in Community and Public Health Nursing
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• v.32 no.2
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• pp.140-149
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• 2021

Purpose: This study aimed to identify factors (biological, psychological, interpersonal, and contextual factors) associated with the weight bias internalization of the Korean girls in early adolescence. Methods: This study used a cross-sectional design. Data was collected from 233 girls aged 12~14 years with a self-reported questionnaire. With multiple regression analysis, the factors associated with the weight bias internalization of the girls in early adolescence were analyzed. Results: Of psychosocial factors, fear to fat (anti-fat attitude) (β=.43, p<.001) was associated with the weight bias internalization of the girls in early adolescence. In addition, attachment with teachers (β=-.11, p=.029) of an interpersonal factor and perceived socio-cultural pressure regarding weight control (β=.34, p<.001) of a contextual factor were associated with the weight bias internalization of the girls in early adolescence. Conclusion: For releasing the weight bias internalization of the girls in early adolescence, decreasing anti-fat attitude and socio-cultural pressure regarding weight control should be primarily required through social efforts including community and school based interventions.

• Macromolecular Research
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• v.11 no.5
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• pp.393-397
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• 2003

By applying a configurational-bias Gibbs ensemble Monte Carlo algorithm, priority simulation results regarding the conformation of non-dilute polyelectrolytes in solvents are obtained. Solutions of freely-jointed chains are considered, and a new method termed strandwise configurational-bias sampling is developed so as to effectively overcome a difficulty on the transfer of polymer chains. The structure factors of polyelectrolytes in the bulk as well as in the confined space are estimated with variations of the polymer charge density.

• 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.

• Journal of Korean Society on Water Environment
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• v.31 no.3
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• pp.241-252
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• 2015

Runoff behaviors by five bias correction methods were analyzed, which were Change Factor methods using past observed and estimated data by the estimation scenario with average annual calibration factor (CF_Y) or with average monthly calibration factor (CF_M), Quantile Mapping methods using past observed and estimated data considering cumulative distribution function for entire estimated data period (QM_E) or for dry and rainy season (QM_P), and Integrated method of CF_M+QM_E(CQ). The peak flow by CF_M and QM_P were twice as large as the measured peak flow, it was concluded that QM_P method has large uncertainty in monthly runoff estimation since the maximum precipitation by QM_P provided much difference to the other methods. The CQ method provided the precipitation amount, distribution, and frequency of the smallest differences to the observed data, compared to the other four methods. And the CQ method provided the rainfall-runoff behavior corresponding to the carbon dioxide emission scenario of SRES A1B. Climate change scenario with bias correction still contained uncertainty in accurate climate data generation. Therefore it is required to consider the trend of observed precipitation and the characteristics of bias correction methods so that the generated precipitation can be used properly in water resource management plan establishment.

• Science of Emotion and Sensibility
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• v.4 no.1
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• pp.23-31
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• 2001

Psychological and physiological effects from simulator sickness could be an important bias factor for sensibility evaluation. The present experiment investigated the effects of simulator sickness on sensibility evaluation in the controlled condition of driving a car for 60 minutes on a constant speed (60km/h) in graphic simulator. The simulator sickness was measured and analysed for every five minutes using their subjective evaluation and physiological signals. Results of the subjective evaluation showed that there was significant difference between rest and driving condition at 10 minutes from the start of driving, and the level of difference was increased linearly with time. The analysis on central and autonomic nervous systems showed the significant difference between rest and driving conditions after 5 minutes from the start of the driving on the parameters $\alpha$/total and $\beta$/total, and increased level of sympathetic nervous system. But there was no significant difference between different time conditions. The results indicates that physiological changes from simulator sickness can be a bias factor in objective evaluation of human sensibility which also, uses physiological signals. That is, the changes on the parameter $\alpha$/total and $\beta$/total, and on activation level of sympathetic nervous system from simulator sickness can be a bias factor for evaluation of the level of pleasantness and tension. Therefore the effort on improving the analysis by minimizing or eliminating the bias factors should be done for better and accurate sensibility evaluation in simulator environments.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.424-433
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• 2001

We present a new electrostatic repulsive-force microactuator using a lateral repulsive force induced by an asymmetric distribution of electrostatic field. The lateral repulsive force has been characterized by a simple analytical equation, derived from a finite element simulation. A set of repulsive force polysilicon microactuators has been designed and fabricated by a 4-mask surface-micromachining process. Static and dynamic micromechanical behavior of the fabricated microactuators has been measured at the atmospheric pressure for a varying bias voltage. The static displacement of the fabricated microactuator, proportional to the square of the DC bias voltage, is obtained as 1.27 $\mu\textrm{m}$ for the DC bias voltage of 140V. The resonant frequency of the repulsive-force microactuator increases from 11.7 kHz to 12.7 kHz when the DC bias voltage increases from 60V to 140V. The measured quality-factor varies from 12 to 13 for the bias volatge range of 60V∼140V. The characteristics of the electrostatic repulsive-force have been discussed and compared and compared with those of the conventional electrostatic attractive-force.

• Journal of Magnetics
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• v.20 no.4
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• pp.347-352
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• 2015

The magnetoelectric (ME) characteristics for Terfenol-D/PZT laminate composite dependence on bias magnetic field is investigated. At low frequency, ME response is determined by the piezomagnetic coefficient $d_{33,m}$ and the elastic compliance $s_{33}^H$ of magnetostrictive material, $d_{33,m}$ and $s_{33}^H$ for Terfenol-D are inherently nonlinear and dependent on $H_{dc}$, leading to the influence of $H_{dc}$ on low-frequency ME voltage coefficient. At resonance, the mechanical quality factor $Q_m$ dependences on $H_{dc}$ results in the differences between the low-frequency and resonant ME voltage coefficient with $H_{dc}$. In terms of ${\Delta}E$ effect, the resonant frequency shift is derived with respect to the bias magnetic field. Considering the nonlinear effect of magnetostrictive material and $Q_m$ dependence on $H_{dc}$c, it predicts the low-frequency and resonant ME voltage coefficients as a function of the dc bias magnetic field. A good agreement between the theoretical results and experimental data is obtained and it is found that ME characteristics dependence on $H_{dc}$ are mainly influenced by the nonlinear effect of magnetostrictive material.