• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.164-164
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• 2016

Radar rainfall estimates have been widely used in calculating rainfall amount approximately and predicting flood risks. The radar rainfall estimates have a number of error sources such as beam blockage and ground clutter hinder their applications to hydrological flood forecasting. Moreover, it has been reported in paper that those errors are inter-correlated spatially and temporally. Therefore, in the current study, we tested influence about spatio-temporal errors in radar rainfall estimates. Spatio-temporal errors were simulated through a stochastic simulation model, called Multivariate Autoregressive (MAR). For runoff simulation, the Nam River basin in South Korea was used with the distributed rainfall-runoff model, Vflo. The results indicated that spatio-temporal dependent errors caused much higher variations in peak discharge than spatial dependent errors. To further investigate the effect of the magnitude of time correlation among radar errors, different magnitudes of temporal correlations were employed during the rainfall-runoff simulation. The results indicated that strong correlation caused a higher variation in peak discharge. This concluded that the effects on reducing temporal and spatial correlation must be taken in addition to correcting the biases in radar rainfall estimates. Acknowledgements This research was supported by a grant from a Strategic Research Project (Development of Flood Warning and Snowfall Estimation Platform Using Hydrological Radars), which was funded by the Korea Institute of Construction Technology.

• Journal of the Korean Society of Safety
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• v.22 no.1 s.79
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• pp.61-66
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• 2007

Car crashes are the leading cause of death for persons of every age. Specially, human-related factor has been known to be the primary causal factor of such crashes than vehicle-and environmental-related factors. There are various studies to analyze driver's behavior and characteristics in driving for reducing the car crashes in many areas of car engineering, psychology, human factor, etc. However, there are almost no studies which analyze mainly the human errors in driving and estimate their probabilities in terms of human reliability analysis. This study estimates the probability of human error in driving, i.e. driver error probability. First, fifty driver errors are investigated through DBQ (Driver Behavior Questionnaire) revision and the error likelihoods in driving are collected which are judged by skillful drivers using revised DBQ. Next, these likelihoods are converted into driver error probabilities using the results that verbal probabilistic expressions are changed into quantitative probabilities. Using these probabilities we can improve the warning effects on drivers by indicating their driving error likelihoods quantitatively. We can also expect the reduction effects of car accident through controlling especially dangerous error groups which have higher probabilities. Like these, the results of this study can be used as the primary materials of safety education on drivers.

• Asia-Pacific Journal of Business
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• v.13 no.4
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• pp.163-175
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• 2022

Purpose - This study introduces a methodology for finding the optimal tracking error of active stock funds. Tracking error is commonly used in risk budgeting techniques as a concept of cost for alpha creation. Design/methodology/approach - This study uses a post-optimal smart beta portfolio that maximizes alpha under the given tracking error constraint. Findings - As a result of the analysis, the smart beta strategy that maximized alpha under the constraint of 0.15% daily tracking error shows the highest IR. This means the maximum theoretically achievable efficiency. In this regard, a fixed-effect panel regression analysis is conducted to evaluate the active efficiency of domestic stock funds. In addition to control variables based on previous studies, the effect of tracking error on alpha is analyzed. The alpha used in this model is calculated using the smart beta portfolio according to the size of the constraint of the tracking error as a benchmark. Contrary to theoretical estimates, in Korea, the alpha performance is maximized under a daily tracking error of 0.1%. This indicates that the active efficiency of domestic equity funds is lower than the theoretical maximum. Research implications or Originality - Based on this study, it is expected that it can be used for active risk management of pension funds and performance evaluation of active strategies.

• Progress in Superconductivity
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• v.7 no.1
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• pp.36-40
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• 2005

The problem of fluctuation-induced digital errors in a rapid single flux quantum (RSFQ) circuit has been a very important issue. In this work, we calculated the bit error rate of an RSFQ switch used in superconductive arithmetic logic unit (ALU). RSFQ switch should have a very low error rate in the optimal bias. Theoretical estimates of the RSFQ error rate are on the order of $10^{-50}$ per bit operation. In this experiment, we prepared two identical circuits placed in parallel. Each circuit was composed of 10 Josephson transmission lines (JTLs) connected in series with an RSFQ switch placed in the middle of the 10 JTLs. We used a splitter to feed the same input signal to both circuits. The outputs of the two circuits were compared with an RSFQ exclusive OR (XOR) to measure the bit error rate of the RSFQ switch. By using a computerized bit-error-rate test setup, we measured the bit error rate of $2.18{\times}10^{-12}$ when the bias to the RSFQ switch was 0.398 mA that was quite off from the optimum bias of 0.6 mA.

• Journal of Industrial Technology
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• v.20 no.A
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• pp.159-167
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• 2000

In the study rainfall frequency analysis attemped the many specific property data record duration it is differance from occur to error-term and probability ditribution of concern manifest. error-term analysis of method are fact sample data using method in other hand it is not appear to be fault that sample data of number to be small random variates. Therefore, day-rainfall data: to randomicity consider of this study sample data to the Monte Carlo method by randomize after data recode duration of form was choice method which compared an assumed maternal distribution from splitting frequency analysis consequence. In the conclusion, frequency analysis of chuncheon region rainfall appeared samll RMSE to the Gamma II distribution. In the rainfall frequency analysis estimate RMSE using random variates great transform, RMSE is appear that return period increasing little by little RMSE incresed and data number incresing to RMSE decreseing.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.944-952
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• 2001

Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it is desired to combine INS with external aids such as GPS. However GPS informations have a randomly abrupt jump due to a sudden corruption of the received satellite signals and environment, and moreover GPS can\`t provide navigation solutions. In this paper, smoothing and prediction schemes are proposed for GPS`s jump or unavailable GPS. The smoothing algorithm which is designed as a scalar adaptive filter, smooths abrupt jump. The prediction algorithm which is proved by Schuler error model of INS, estimates INS error in appropriate time. The outputs of proposed algorithm apply stable measurements to GPS aided INS Kalman filter. Simulations show that the proposed algorithm can effectively remove measurement jump and predict INS error.

• The Journal of Korea Robotics Society
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• v.7 no.1
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• pp.45-56
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• 2012

This paper proposes how to improve the performance of CSS-based indoor localization system. CSS based localization utilizes signal flight time between anchors and tag to estimate distance. From the distances, the 3-dimensional position is calculated through trilateration. However the error in distance caused from multi-path effect transfers to the position error especially in indoor environment. This paper handles a problem of reducing error in raw distance information. And, we propose the new localization method by pattern matching instead of the conventional localization method based on trilateration that is affected heavily on multi-path error. The pattern matching method estimates the position by using the fact that the measured data of near positions possesses a high similarity. In order to gain better performance of localization, we use EKF(Extended Kalman Filter) to fuse the result of CSS based localization and robot model.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.139.4-139
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• 2001

The thesis propose the sensorless vector control method that estimates the rotor speed using stator current. The estimated speed is used as feedback in a vector control system. The conventional MRAS structure has a problem the error output is decreasing as estimated speed error is increasing and the estimation performance is not robust when mutual inductance has been changed. In the proposed method, error output is proportional to estimated speed error. The described technique is less complex, robust to variations of mutual inductance. This new method can achieve much wider bandwidth speed control than that of the conventional MRAS structure.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.9
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• pp.1849-1858
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• 2002

An h-adaptive scheme of first-order least-squares meshfree method is presented. A posteriori error estimates, which can be readily computed from the residual, are also presented. For elliptic problem the error indicators are further improved by applying the Aubin-Nitsche method. In the proposed refinement scheme, Voronoi cells are utilized to insert nodes at appropriate positions. Through numerical examples, it is demonstrated that the error indicators reveal good correlations with the actual errors and the adaptive first-order least-squares meshfree method is effectively applied to the localized problems such as the shock formation in fluid dynamics.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.273-277
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• 2009

A compressed video stream is very sensitive to transmission errors that may severely degrade the reconstructed image. Therefore, error resilience is an essential problem in video communications. In this paper, we propose novel temporal error concealment techniques for recovering lost or erroneously received macroblock (MB). To reduce the computational complexity, the proposed method adaptively determines the search range for each lost MB to find best matched block in the previous frame. And the original corrupted MB split into for $8{\times}8$ sub-MBs, and estimates motion vector (MV) of each sub-MB using its boundary information. Then the estimated MVs are utilized to reconstruct the damaged MB. In simulation results, the proposed method shows better performance than conventional methods in both aspects of PSNR.