• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1463-1471
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• 2016

The indoor localization algorithm using the Difference Means based on Fingerprint (DMFPA) to improve the performance of indoor localization in moving Wi-Fi environment is proposed in this paper. In addition to this, the performance of the proposed algorithm is also compared with the Original Fingerprint Algorithm (OFPA) and the Gaussian Distribution Fingerprint Algorithm (GDFPA) by our developed indoor localization simulator. The performance metrics are defined as the accuracy of the average localization accuracy; the average/maximum cumulative distance of the occurred errors and the average measurement time in each reference point.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.64-76
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• 2014

This study identified the causes of errors that could take place in the estimation process of vehicle miles traveled and quantified the effects of each of those causes on the estimation accuracy of vehicle miles traveled via error rate to propose an efficient way to estimate vehicle miles traveled. The study proceeded as follows: first, the study established survey data of vehicle miles traveled in the pilot test areas to test the accuracy of a method to estimate vehicle miles traveled. Second, the causes of errors with the estimation of vehicle miles traveled were categorized into errors with the sample size, sampling methods, and homogeneous link setting methods. In addition, many different methodologies were set to minimize errors with the estimation of vehicle miles traveled according to each of the causes. Third, error rates of estimation of vehicle miles traveled were compared and analyzed according to each of the methodologies. Finally, a toy network was established to propose a way of estimating vehicle miles traveled by taking the local characteristics into consideration. The study finds its significance in that it proposed an efficient way to estimate vehicle miles traveled through an experiment and planning approach and made use of survey data of vehicle miles traveled to test estimation accuracy. The proposed way of estimating vehicle miles traveled by taking into account the local characteristics will make a contribution to the estimation of vehicle miles traveled by the areas in future along with the level of data offered in the study.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.03a
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• pp.61-64
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• 1998

도로의 건설을 위해서는 통상 타당성조사, 기본계획, 기본설계 및 시공의 여러 가지 단계를 밟는다. 이들 각 단계를 거치면서 일반적으로 투자비 추정액은 실제 공사비와 더욱 근접하게 되게 되나, 타당성조사 등 계획단계에서의 추정액은 실제 공사비와 상당한 차이를 보이는 것이 일반적이다. 이러한 차이는 계획물량의 추정이나, 단가의 추정 등에서도 발생할 수도 있고, 구체적인 지질조사 등이 없는 상태에서 가정한 지질조건이나 공사조건 등에 대한 불확실성으로 인해 발생한다. 현재의 일반적인 관행은 이러한 투자비 추정단계에 작용하는 불확실성을 명시적으로 고려하여 투자비 추정치의 확률적인 분포를 산정하지 않고, 하나의 확정적인 추정치만 제시하고 있어 제시된 추정치의 신뢰도를 확인하기가 곤란하다. 본 연구에서는 현재의 관행과는 달리 투자비추정에서 관여하는 불확실성을 확률분포를 사용하여 명시적으로 고려하여 추정된 투자비에 대한 확률분포를 명시적으로 파악하려는 노력을 하였다. 추정된 투자비에 대한 확률분포는 Mont Carlo 시뮬레이션 방법을 이용하여 분석하였으며, 연구의 결과와 현재 각 계획단계에서 일반적으로 용인되는 추정오차와의 관계도 분석하였다. 결과에 근거하여 도로사업에 대한 투자비 추정을 효율적으로 할 수 있는 방법을 제시하였으며, 추가적인 연구방향도 제시하였다.

• Journal of Korean Society of Transportation
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• v.23 no.4 s.82
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• pp.57-69
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• 2005

The goal of this paper is to develop freeway Origin-Destination (OD) demand estimation model using real-time traffic data collected from Freeway Traffic Management System (FTMS). In existing research, the micro-simulation models had been used to get a link distribution proportion by time process. Because of hi-level problem between the traffic flow model and the optimal OD solution algorithm, it is difficult for the existing models to be loaded at FTMS. The formulation of methodology proposed in this paper includes traffic flow technique to be able to remove the bi-level problem and optimal solution algorithm using a genetic algorithm. The proposed methodology is evaluated by using the real-time data of SOHAEAN freeway, South Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.175-182
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• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.17-32
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• 2022

This study explored an approach to estimate a flow-density diagram(FD) on a link in highway traffic environment by utilizing probe vehicles' time headway records. To study empirical flow-density diagram(EFD), the probe vehicles with vision sensors were recruited for collecting driving records for nine months and the vision sensor data pre-processing and GIS-based map matching were implemented. Then, we examined the new EFDs to evaluate validity with reference diagrams which is derived from loop detection traffic data. The probability distributions of time headway and distance headway as well as standard deviation of flow and density were utilized in examination. As a result, it turned out that the main factors for estimation errors are the limited number of probe vehicles and bias of flow status. We finally suggest a method to improve the accuracy of EFD model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2D
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• pp.319-327
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• 2009

In order to estimate accurate position by GPS observations, it is prerequisite to define both of the correct function model and the realistic stochastic model. In the case that un-modeled outliers exist in observations, estimates become biased, and their standard deviations are unable to be used as a measure which represents their accuracy. Hence, such outliers should be appropriately removed from the observations before estimating final solutions, so that the accuracy can be maximized with the improvement of the reliability. For this purpose, this research deals with quality control and quality measure computation algorithms for GPS stand-alone positioning. After theoretical studies, all the algorithms have been implemented and tested with real observations. Results of the tests indicate that the reliability of the estimated position is improved by increasing redundancy as well as using good satellite geometry and more realistic stochastic model. Moreover, the adaptation of the quality control procedure enable to improve positioning reliability and accuracy by appropriately excluding outlier in observations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5585-5593
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• 2014

This study tested the hypothesis that the significance of the heterogeneous dispersion parameter in safety performance function (SPF) used to estimate the expected crashes is affected by the endogenous heterogeneous prior distributions, and analyzed the impacts of the mis-specified dispersion parameter on the evaluation results for traffic safety countermeasures. In particular, this study simulated the Poisson means based on the heterogeneous dispersion parameters and estimated the SPFs using both the negative binomial (NB) model and the heterogeneous negative binomial (HNB) model for analyzing the impacts of the model mis-specification on the mean and dispersion functions in SPF. In addition, this study analyzed the characteristics of errors in the crash reduction factors (CRFs) obtained when the two models are used to estimate the posterior means and variances, which are essentially estimated through the estimated hyper-parameters in the heterogeneous prior distributions. The simulation study results showed that a mis-estimation on the heterogeneous dispersion parameters through the NB model does not affect the coefficient of the mean functions, but the variances of the prior distribution are seriously mis-estimated when the NB model is used to develop SPFs without considering the heterogeneity in dispersion. Consequently, when the NB model is used erroneously to estimate the prior distributions with heterogeneous dispersion parameters, the mis-estimated posterior mean can produce large errors in CRFs up to 120%.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.3
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• pp.266-273
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• 2007

The change patterns of the water quanity, water quality(WQ, exclusively COD in this study) and monthly / annual pollutant loads(PL) estimated using the daily effluent discharges and WQ measurement data are analyzed in the Nakdong river estuarine seadike. The contribution factor defined by the ratio of the water quantity range and WQ range shows that the PL pattern in this estuary is classified as the strongly flow(water quantity)-dominated situation. The estimated PL(EPL)s with respect to the increasing sampling periods, e.g., 2-days, 5-days, 7-days, and so on, show that the mean values of the EPLs remain nearly same, whereas the standard deviations of the EPLs have an obvious increasing trend. The PL values using the monthly-averaged water quantity and WQ measurement data could have approximately 100% estimation error in annual mean and $300\sim400%$ estimation errors in summer season because its confidence level is relatively low. It is recommended that the PL should be estimated using at least $10\sim20$ day interval data sets and also the water quantity(river discharges) and WQ should be measured at the intervals of at least 1 day interval and 5 to 7 days, respectively in summer.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.395-407
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• 2016

This study aims to apply the G-theory for estimation of reliability of evaluation scores between raters on Taekwondo Poomsae rating categories. Selecting a number of game days and raters as multiple error sources, we analyzed the error sources caused by relative magnitude of error variances of interaction between the factors and proceeded with D-study based on the results of G-study for optimal determination of measurement condition. The results showed below. The estimated outcomes of variance component for accuracy among the Taekwondo Poomsae categories with G-theory showed that impact of error was the biggest influence factor in raters conditions and in order of interaction in subjects and between subjects, also impact of variance component estimation error on expression category was the major influence factor in interaction and in order of the between subjects and raters. Finally, the result of generalizability coefficient estimation via D-study showed that measurement condition of optimal level depend on the number of raters was 8 persons of raters on accuracy category, and stable reliability on expression category was gained when the raters were 7 persons.