• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.180-184
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• 2009

The memory is very sensitive to the soft error because the integration of the memory increases under low power environment. Error correcting codes (ECCs) are commonly used to protect against the soft errors. This paper proposes a new genetic ECC design method which reduces power consumption. Power is minimized using the degrees of freedom in selecting the parity check matrix of the ECCs. Therefore, the genetic algorithm which has the novel genetic operators tailored for this formulation is employed to solve the non-linear power optimization problem. Experiments are performed with Hamming code and Hsiao code to illustrate the performance of the proposed method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.150-158
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• 2018

In this paper, we introduce an electric vehicle charging system using power line communication and propose a method to correct the error by applying a deep learning algorithm when an error occurs in the control signal of an electric vehicle charging system using power line communication. The error detection and correction of the control signal can be solved through the conventional error correcting code schemes, but the error is detected and corrected more efficiently by using the deep learning based error correcting code scheme. Therefore, we introduce deep learning based error correction code scheme and apply this scheme to electric vehicle charging system using power line communication. we proceed simulation and confirm performance with bit error rate. we judge whether the deep learning based error correction code scheme is more effective than the conventional schemes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.1-13
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• 2020

There are several methods of peak-shaving, which reduces grid power demand, electricity bought from electricity utility, through lowering "demand spike" during On-Peak period. An optimization method using linear programming is proposed, which can be used to perform peak-shaving of grid power demand for grid-connected PV+ system. Proposed peak shaving method is based on the forecast data for electricity load and photovoltaic power generation. Results from proposed method are compared with those from On-Off and Real Time methods which do not need forecast data. The results also compared to those from ideal case, an optimization method which use measured data for forecast data, that is, error-free forecast data. To see the effects of forecast error 36 error scenarios are developed, which consider error types of forecast, nMAE (normalizes Mean Absolute Error) for photovoltaic power forecast and MAPE (Mean Absolute Percentage Error) for load demand forecast. And the effects of forecast error are investigated including critical error scenarios which provide worse results compared to those of other scenarios. It is shown that proposed peak shaving method are much better than On-Off and Real Time methods under almost all the scenario of forecast error. And it is also shown that the results from our method are not so bad compared to the ideal case using error-free forecast.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.675-676
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• 2007

This Paper presents circuit improvement of 345kV Bus bar protection panel by using VDD (Voltage disturbance detection) relay with distinctive ability between human error in the field test and real facility faults. Therefore, We expect that this improvement of circuit helps decrease of blackout coming from human error. In order to guarantee electric power system reliability, consistent study of human error prevention in the event of field test is necessarily required

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2528-2530
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• 2000

In general, Diode makes a major role in electronic circuit. For example, switching of rectifier, cross current of switching rectifier, energy transfer of electronic element and reverse charge of capacitor, voltage insulation, energy feedback from load to power supply, and such as recovery of storaged energy. Generally, We regard power diode as ideal element, but it has a certain boundary actually, specially, We use diode for detecting circuit peak hold voltage signal. It has cut in voltage. It occurs error of measurement value namely. This error, below in region diode voltage drop (0.7v) measurement value is wholesome signal, Specially, We can not get precision data. Therefore, precision level is low between theoretical and measurement data because of error in actual circuit. Conclusionally, In this paper, We define the error concerning to the power diode characteristics which is used detecting of the minute signal, and recommend the method that minimize measurement error.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.229-231
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• 2002

The digital current differential relaying scheme is widely used for primary protection of 765(kV) power transformer. The current differential relay pickup the internal fault at the threshold which is set at 30% of rating current. Margin of 30% include current transformer error 5%, relay error 5%, on load tap changer error 7% and margin factor 140% obtained from the field experience. In this paper transformer protection relay and relay setting rule of high voltage power system are discussed. And we verify the correctness of relay setting rule with current differential relay using Matlab simulation.

• Journal of the Ergonomics Society of Korea
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• v.26 no.1
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• pp.93-97
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• 2007

As many as 111 reactor trips have occurred for recent 5 years('01-'05), and 26 cases of them have occurred due to human error. The trend of human error rate didn't decrease in 2004, so KHNP started to make efforts to decrease human errors. In 2006 KHNP bench marked excellent foreign nuclear power plants and introduced human error prevention tools. In addition, KHNP created as many as 40 posters for human performance improvement. The posters are based on the about 500 real incident reports collected through K-HPES from 1995. Therror preventive tols for the poster. This paper explains design of the posters and their application.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.64-72
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• 2016

In this paper, we utilize a Gaussian process to predict the power consumption in the air-conditioning system. As the power consumption in the air-conditioning system takes a form of a time-series and the prediction of the power consumption becomes very important from the perspective of the efficient energy management, it is worth to investigate the time-series model for the prediction of the power consumption. To this end, we apply the Gaussian process to predict the power consumption, in which the Gaussian process provides a prior probability to every possible function and higher probabilities are given to functions that are more likely consistent with the empirical data. We also discuss how to estimate the hyper-parameters, which are parameters in the covariance function of the Gaussian process model. We estimated the hyper-parameters with two different methods (marginal likelihood and leave-one-out cross validation) and obtained a model that pertinently describes the data and the results are more or less independent of the estimation method of hyper-parameters. We validated the prediction results by the error analysis of the mean relative error and the mean absolute error. The mean relative error analysis showed that about 3.4% of the predicted value came from the error, and the mean absolute error analysis confirmed that the error in within the standard deviation of the predicted value. We also adopt the non-parametric Wilcoxon's sign-rank test to assess the fitness of the proposed model and found that the null hypothesis of uniformity was accepted under the significance level of 5%. These results can be applied to a more elaborate control of the power consumption in the air-conditioning system.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.485-490
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• 2014

The purpose of this Study investigated corneal power, corneal astigmatism and corneal axis according to spherical equivalent of refractive error. We measured spherical equivalent, corneal power and corneal astigmatism in 100 subjects from January 2014 to July 2014. Measured spherical equivalent of refractive error were $-3.01{\pm}3.79D$, corneal power of $43.79{\pm}1.60D$ and corneal astigmatism of $-1.17{\pm}0.79D$ respectively. Prevalence of spherical equivalent of refractive error were as follows : myopes (61%), emmetropes (22%), hyperopes(17%). Corneal astigmatism of refractive error greater than +0.75D was 63% and prevalence of corneal astigmatism were as follows : with-the-rlue astigmatism (84.13%), against-the-rule astigmatism(9.52%) respectively. Corneal power by spherical equivalent increased from hyperopia to myopia. Between spherical equivalent of refractive error and the mean corneal power was significant correlation(r=-0.25, p=0.01). A correlation were found between corneal power and spherical equivalent of refractive error in adults. They have the highest distribution of prevalence myopia among the refractive error. When the refractive error was increased, we found that corneal power was steeper. It is recognized that this can be refractive error factor and correct visual function is considered.

• Journal of International Academy of Physical Therapy Research
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• v.9 no.4
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• pp.1602-1607
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• 2018

This study examined the correlation between power error (PE) and velocity error (VE) according to the condition and frequency of self-controlled feedback (SCF) during knee extension. One hundred participants were randomly assigned to 30% SCF, 70% SCF, 30% yoked feedback (YF), 70% YF and control group, respectively. The SCF group was provided with feedback when they requested it, whereas the YF group did not influence the feedback schedule. Participants in the control group were not given any visual feedback during the experiment. The isotonic, isometric, and isokinetic dynamometer (PRIMUS RS, BTE, USA) was used to measure the power and velocity error during knee extension. The collected data was analyzed using a Pearson test and SPSS 21.0. The correlation between PE and VE according to the condition and frequency of feedback on each phase during knee extension was significant. Both PE and VE were significantly higher when the feedback was provided with high frequency, passive, and no feedback. Our study suggests that application of SCF can help to improve the proprioception of the healthy person while reducing errors through low frequency and active feedback.