• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.127.1-127.1
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• 2013

Recent experimental evidence that fluorinated graphene creates local magnetic moments around F adatoms has not been supported by semilocal density-functional theory (DFT) calculations where the adsorption of an F adatom induces no magnetic moment in graphene. Here, we show that such an incorrect prediction of the nonmagnetic ground state is due to the self-interaction error inherent in semilocal exchange-correlation functionals. The present hybrid DFT calculation for an F adatom on graphene predicts not only a spin-polarized ground state with a spin moment of ${\sim}1{\mu}_B$, but also a long-range spin polarization caused by the bipartite nature of the graphene lattice as well as the induced spin polarization of the graphene states. The results provide support for the experimental observations of local magnetic moments in fluorinated graphene.

• Journal of Industrial Technology
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• v.28 no.B
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• pp.91-99
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• 2008

Applicability of existing methods of predicting consolidation settlement was assessed by analyzing results of centrifuge tests modelling self-weight consolidation of soft marine clay. From extensive literature review about self-weight consolidation of soft marine clays located in southern coast in Korea, constitutive relationships of void ratio-effective stress-permeability and typical self-weight consolidation curves with time were obtained by centrifuge model experiments. For the condition of surcharge loading, exact solution of consolidation settlement curve was obtained by Terzaghi's consolidation theory and was compared with the results predicted by currently available methods such as Hyperbolic method, Asaoka's method, Hoshino's method and ${\sqrt{S}}$ method. All methods were found to have their own inherent error to predict final consolidation settlement. From results of analyzing the self-weight consolidation with time by using those methods, Asaoka's method predicted the best. Hyperbolic method predicted relatively well in error range of 2~24% for the case of showing the linearity in the relationship between T vs T/S in the stage of consolidation degree of 60~90 %. For the case of relation curve of T vs $T/S^2$ showing the lineality after the middle stage, error range from Hoshino method was close to those from Hyperbolic method. However, Hoshino method is not able to predict the final settlement in the case of relation curve of T vs $T/S^2$ being horizontal. For the given data about self-weight consolidation after the middle stage, relation curve of T vs T/S from ${\sqrt{S}}$ method shows the better linearity than that of T vs $T/{\sqrt{s}}$ from Hyperbolic method.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.111-130
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• 1998

We propose an imperfect repair model which depends on external effects quantified by covariates. The model is based on the Brown-Proschan imperfect repair model wherefrom the probability of perfect repair is represented by a function of covariates. We are motivated by deficiency of the BP model whose stationarity prevents us from predicting dynamically the time to next failure according to external condition. Five types of function for the probability of perfect repair are proposed. This article also presents a procedure for estimating the parameter of the function for the probability of perfect repair, as well as the inherent lifetime distribution of the system, based on consecutive inter-failure times and the covariates. The estimation procedure is based on the expectation-maximization principle which is suitable to incomplete data problems. focusing on the maximization step, we derive some theorems which guarantee the existence of the solution. A Monte Carlo study is also performed to illustrate the prediction power of the model as well as to show reasonable properties of the estimates. The model reduces significantly the mean square error of the in-sample prediction. so it can be utilized in real fields for evaluating and maintaining repairable systems.

• ETRI Journal
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• v.22 no.2
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• pp.20-31
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• 2000

Much research on natural language processing (NLP), computational linguistics and lexicography has relied and depended on linguistic corpora. In recent years, many organizations around the world have been constructing their own large corporal to achieve corpus representativeness and/or linguistic comprehensiveness. However, there is no reliable guideline as to how large machine readable corpus resources should be compiled to develop practical NLP software and/or complete dictionaries for humans and computational use. In order to shed some new light on this issue, we shall reveal the flaws of several previous researches aiming to predict corpus size, especially those using pure regression or curve-fitting methods. To overcome these flaws, we shall contrive a new mathematical tool: a piecewise curve-fitting algorithm, and next, suggest how to determine the tolerance error of the algorithm for good prediction, using a specific corpus. Finally, we shall illustrate experimentally that the algorithm presented is valid, accurate and very reliable. We are confident that this study can contribute to solving some inherent problems of corpus linguistics, such as corpus predictability, compiling methodology, corpus representativeness and linguistic comprehensiveness.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.346-351
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• 1998

In design of a digital current controller for a 3-phase (3 ) voltage-source (VS) PWM converter, its conventional model, i.e., stationary or synchronous reference frame model, is used in obtaining its discretized version. It introduces, however, inherent errors since the following practical problems are not taken into consideration: the characteristics of the space vector-based pulse-width modulation (SVPWM) and the time delays in the process of sampling and computation. In this paper, the new hybrid reference frame model of the 3 VS PWM converter is proposed considering these problems. In addition, the direct digital current controller based on this model is designed without any prediction or extrapolation algorithm to compensate the time delay. So the control algorithm is made very simple. It represents no steady-state error in input current control and has the optimized transient responses. The validity of the proposed algorithm is proved by the computer simulation and experimental results.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.71-79
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• 2005

Existing arterial link travel time estimation methods relying on either aggregate point-based or individual section-based traffic data have their inherent limitations. This paper demonstrates the utility of data fusion for improving arterial link travel time estimation. If the data describe traffic conditions, an operator wants to know whether the situations are going better or worse. In addition, some traffic information providing strategies require predictions of what would be the values of traffic variables during the next time period. In such situations, it is necessary to use a prediction algorithm in order to extract the average trends in traffic data or make short-term predictions of the control variables. In this research. a multi-step ahead prediction algorithm using Data fusion was developed to predict a link travel time. The algorithm performance were tested in terms of performance measures such as MAE (Mean Absolute Error), MARE(mean absolute relative error), RMSE (Root Mean Square Error), EC(equality coefficient). The performance of the proposed algorithm was superior to the current one-step ahead prediction algorithm.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.701-712
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• 2005

The suppression for logistic regression models has been debated no longer than that for linear regression models since, among many other reasons, sum of squares for regression (SSR) or coefficient of determination ($R^2$) could be defined into various ways. Based on four kinds of $R^2$'s: two kinds are most preferred, and the other two are proposed by Liao & McGee (2003), four kinds of SSR's are derived so that the suppression for logistic models is explained. Many data fitted to logistic models are generated by Monte Carlo method. We explore when suppression happens, and compare with that for linear regression models.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.1
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• pp.97-106
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• 2011

In this study, viscoplastic material properties of solder alloy which is used in the electronics packages are inversely estimated. A specimen is fabricated to this end, and an experiment is conducted to examine deformation by Moir$\acute{e}$ interferometry. As a result of the experiment, bending displacement of the specimen and shear strain of the solder are obtained. A viscoplastic finite element analysis procedure is established, and the material parameters are determined to match closely with the experiments. The uncertainties which include inherent experimental error and insufficient data of experiments are addressed by using the method of computer model calibration. As a result, material parameters are identified in the form of confidence interval, and the displacements and strains using these parameters are predicted in the form the prediction interval.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.56-73
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• 2019

Probe-based systems have been gaining popularity in advanced traveler information systems. However, the high possibility of providing inaccurate travel-time information due to the inherent time-lag phenomenon is still an important issue to be resolved. To mitigate the time-lag problem, different prediction techniques have been applied, but the techniques are generally regarded as less effective for travel times with high variability. For this reason, current 5-min aggregated data have been commonly used for real-time travel-time provision on highways with high travel-time fluctuation. However, the 5-min aggregation interval itself can further increase the time-lags in the real-time travel-time information equivalent to 5 minutes. In this study, a new scheme that uses both individual probe and 5-min aggregated travel times is suggested to provide reliable real-time travel-time information. The scheme utilizes individual probe data under congested conditions and 5-min aggregated data under uncongested conditions, respectively. As a result of an evaluation with field data, the proposed scheme showed the best performance, with a maximum reduction in travel-time error of 18%.

• Journal of the Korea Society for Simulation
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• v.24 no.2
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• pp.31-39
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• 2015

Unemployment is related to social issues as well as personal economics activity so various policies have been made to reduce the unemployment rate in many countries. Because of delay inherent in the survey mechanism to collect unemployment data, it takes lots of time to acquire survey unemployment data. To develop proper policies for reducing unemployment rate at the right time, it is quite critical to obtain faster and more accurate information concerning about unemployment level. To remedy this problem, recently an advanced analytics utilizing internet queries is suggested. To examine the potential of Web query information, this research investigates the usefulness of internet activity data to predict Korean unemployment rate. One of selected web-query data(unemployment claim) has a quite strong correlation with unemployment rate. This research employes a time series approach of the ARIMA model that utilizes the information of keyword queries provided by the Naver(Korean representative portal site) trend together with unemployment rate data provisioned from Statistics Korea. With respect to model selection guidelines of mean squared error and prediction error, the model with utilizing the web query information shows better results than the model without such information. This suggests that there is a strong potential for the used method, which needs to be further explored.