• 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 Contents Association
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• v.13 no.8
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• pp.11-19
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• 2013

This paper presents a simple method to estimate center of distortion and correct radial distortion from fish-eye lens. If the center of image is not locate that of lens in a straight line, the disadvantage of FOV model is low accurate because of correcting distortion without estimated centre of distortion. We propose a method accurately estimating Distortion center using FOV model and 2D pattern from wide angle lens. Our method determines the center of distortion in least error between straight lines and curves with FOV model. The results of experimental measurements on synthetic and real data are presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.715-722
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• 2016

In this paper, by applying the linear least squared error algorithm, we derive an estimation technique for three dimensional target location when a number of radars are used in detecting a target. The proposed technique is then enhanced by combining GPS information and by assigning variable weights to information sources. The enhanced performance of proposed techniques is confirmed via simulation. It is also observed from simulation results that the performance is robust to the uncertainty of information.

• The Transactions of the Korean Institute of Power Electronics
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• v.8 no.5
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• pp.375-380
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• 2003

In a conventional speed sensorless stator flux-oriented (SFO) induction motor drive, when the estimated speed is transformed into the sample-data model using the first-forward difference approximation, the sampled data model has a modeling error which, in turn, produces an error in the rotor speed estimation. The error is removed by the use of a low pass filter (LPF). As a result, the delay of the estimated speed occurs in transients by the use of the LPF. This paper proposes a method to estimate exactly the speed by using Luenberger observer to solve the problem of a conventional method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.61-68
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• 2012

In this paper, a closed-loop sensorless stroke control system for a linear compressor has been designed. In order to estimate the piston position accurately, motor parameters are identified as a function of the piston position and the motor current. These parameters are stored in ROM table and used later for the accurate estimation of piston position. The identified motor parameters are approximated to the several surface functions in order to decrease memory size. They can also be divided into 2 or 4 subsections to decrease identification errors. The effect of the order of surface functions and division of subsections on identification errors and computation time is analyzed.

• Journal of Korea Water Resources Association
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• v.47 no.12
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• pp.1227-1237
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• 2014

Dual-polarization can distinguish precipitation type and dual-polarization is provide not only meteorological phenomena in the atmosphere but also non-precipitation echoes. Therefore dual-polarization radar can improve radar estimates of rainfall. However polarimetric measurements by transmitting vertically vibration waves and horizontally vibrating waves simultaneously is contain systematic bias of the radar itself. Thus the calibration bias is necessary to improve quantitative precipitation estimation. In this study, the calibration bias of reflectivity (Z) and differential reflectivity ($Z_{DR}$) from the Bislsan dual-polarization radar is calculated using the 2-Dimensional Video Disdrometer (2DVD) data. And an improvement in rainfall estimation is investigated by applying derived calibration bias. A total of 33 rainfall cases occurring in Daegu from 2011 to 2012 were selected. As a results, the calibration bias of Z is about -0.3 to 5.5 dB, and $Z_{DR}$ is about -0.1 dB to 0.6 dB. In most cases, the Bislsan radar generally observes Z and $Z_{DR}$ variables lower than the simulated variables. Before and after calibration bias, compared estimated rainfall from the dual-polarization radar with AWS rain gauge in Daegu found that the mean bias has fallen by 1.69 to 1.54 mm/hr, and the RMSE has decreased by 2.54 to 1.73 mm/hr. And estimated rainfall comparing to the surface rain gauge as ground truth, rainfall estimation is improved about 7-61%.

• Journal of Korea Water Resources Association
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• v.35 no.1
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• pp.1-12
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• 2002

This study was intended to investigate the rainfall-runoff relationship with spatially distributed rainfall data, and then, to analyze and quantify the uncertainty induced by spatially averaging rainfall data. For constructing spatially distributed rainfall data, several historical rainfall events were extended spatially by simple kriging method based on the semivariogram as a function of the relative distance. Runoff was computed by two models; one was the modified Clark model with spatially distributed rainfall data and the other was the conventional Clark model with spatially averaged rainfall data. Rainfall errors and discharge errors occurred through this process were defined and analyzed with respect to various rain-gage network densities. The following conclusions were derived as the results of this work; 1) The conventional Clark parameters could be appropriate for translating spatially distributed rainfall data. 2) The parameters estimated by the modified Clark model are more stable than those of the conventional Clark model. 3) Rainfall and discharge errors are shown to be reduced exponentially as the density of rain-gage network is increased. 4) It was found that discharge errors were affected largely by rainfall errors as the rain-gage network density was small.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.57-66
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• 2003

Because the Logit model easily calculates probabilities for choice alternatives and estimates parameters for explanatory variables, it is widely used as a traffic mode choice model. However, this model includes an assumption which is independently and identically distributed to the error component distribution of the mode choice utility function. This paper is a study on the estimation of the Heteroscedastic Logit Model. which mitigates this assumption. The purpose of this paper is to estimate a Logit model that more accurately reflects the mode choice behavior of passengers by resolving the homoscedasticity of the model choice utility error component. In order to do this, we introduced a scale factor that is directly related to the error component distribution of the model. This scale factor was defined so as to take into account the heteroscedasticity in the difference in travel time between using public transport and driving a car, and was used to estimate the travel time parameter. The results of the Logit Model estimation developed in this study show that Heteroscedastic Logit Models can realistically reflect the mode choice behavior of passengers, even if the difference in travel time between public and private transport remains the same as passenger travel time increases, by identifying the difference in mode choice probability of passengers for public transportation.

• Journal of the Earthquake Engineering Society of Korea
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• v.1 no.2
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• pp.1-15
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• 1997

This paper presents substructural identification methods for the assessment of local damages in complex and large structural systems. For this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for a substructure to process the measurement data impaired by noises. Using the substructural methods, the number of unknown parameters for each identification can be significantly reduced, hence the convergence and accuracy of estimation can be improved. Secondly, the damage index is defined as the ratio of the current stiffness to the baseline value at each element for the damage assessment. The indirect estimation method was performed using the estimated results from the identification of the system matrices from the substructural identification. To demonstrate the proposed techniques, several simulation and experimental example analyses are carried out for structural models of a 2-span truss structure, a 3-span continuous beam model and 3-story building model. The results indicate that the present substructural identification method and damage estimation methods are effective and efficient for local damage estimation of complex structures.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.277-282
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• 2012

When wind speed exceeds a certain threshold, daily minimum temperature does not drop as predicted by the geospatial model in a cold pooling catchment. A linear regression equation was derived to explain the warming effect of wind speed on daily minimum temperature by analyzing observations at a low lying location within an enclosed catchment. The equation, Y=2X+0.4 ($R^2$=0.76) where Y stands for the warming ($^{\circ}C$) and X for the mean horizontal wind speed (m/s) at 2m height, was combined to an existing model to predict daily minimum temperature across an enclosed catchment on cold pooling days. The adjusted model was applied to 3 locations submerged in a cold air pool to predict daily minimum temperature on 25 cold pooling days with the input of simulated wind speed at each location. Results showed that bias (mean error) was reduced from -1.33 to -0.37 and estimation error (RMSE) from 1.72 to 1.20, respectively, in comparison with those from the unadjusted model.