• Journal of Environmental Science International
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• v.22 no.2
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• pp.151-161
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• 2013

The assessment of personal exposure is a critical component in population-based epidemiologic studies of air pollution. This study was conducted to apply and compare the four exposure estimation methods of individual-level to air pollution concentration in a cohort including 2,283 subjects in Gwangyang, Korea. Individual-level exposure of air pollution were estimated using multiple approaches, including average across all monitors, nearest monitor, and spatial interpolation by inverse distance weighting and kriging. The mean concentrations of $PM_{10}$, $NO_2$, $SO_2$, CO, $O_3$ by four exposure estimation methods were slightly different but not significantly different from each other. Cross-validation showed that kriging was more accurate than other exposure estimation methods because kriging has probably predicted individual exposure levels equivalent to residential locations after estimating the parameters of a model according to the spatial surface of air pollution concentration. These data support that spatial interpolation methods may provide better estimates than selecting the value from the nearest monitor and averaging across values from all monitors by reflecting spatial attributes of air pollution on personal level.

• International Journal of Highway Engineering
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• v.16 no.3
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• pp.119-129
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• 2014

PURPOSES : This investigational survey is to observe a proper spatial aggregation method for path travel time estimation using the hi-pass DSRC system. METHODS : The links which connect the nodes of section detectors location are used for path travel time estimation traditionally. It makes some problem such as increasing accumulation errors and processing times. In this background, the new links composition methods for spatial aggregation are considered by using some types of nodes as IC, JC, RSE combination. Path travel times estimated by new aggregation methods are compared with PBM travel times by MAE, MAPE and statistical hypothesis tests. RESULTS : The results of minimum sample size and missing rate for 5 minutes aggregation interval are satisfied except for JC link path travel time in Seoul TG~Kuemho JC. Thus, it was additionally observed for minimum sample size satisfaction. In 15, 30 minutes and 1 hour aggregation intervals, all conditions are satisfied by the minimum sample size criteria. For accuracy test and statistical hypothesis test, it has been proved that RSE, Conzone, IC, JC links have equivalent errors and statistical characteristics. CONCLUSIONS : There are some errors between the PBM and the LBM methods that come from dropping vehicles by rest areas. Consequently, this survey result means each of links compositions are available for the estimation of path travel time when PBM vehicles are missed.

• Atmosphere
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• v.25 no.2
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• pp.283-294
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• 2015

For urban flash flood simulation, we need the higher resolution radar rainfall than radar rainfall of KMA, which has 10 min time and 1km spatial resolution, because the area of subbasins is almost below $1km^2$. Moreover, we have to secure the high quantitative accuracy for considering the urban hydrological model that is sensitive to rainfall input. In this study, we developed the quantitative precipitation estimation (QPE), which has 250 m spatial resolution and high accuracy using KMA AWS and SK Planet stations with Mt. Gwangdeok radar data in Seoul area. As the results, the rainfall field using KMA AWS (QPE1) is showed high smoothing effect and the rainfall field using Mt. Gwangdeok radar is lower estimated than other rainfall fields. The rainfall field using KMA AWS and SK Planet (QPE2) and conditional merged rainfall field (QPE4) has high quantitative accuracy. In addition, they have small smoothed area and well displayed the spatial variation of rainfall distribution. In particular, the quantitative accuracy of QPE4 is slightly less than QPE2, but it has been simulated well the non-homogeneity of the spatial distribution of rainfall.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.999-1002
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• 2002

In this paper, we proposes an adaptive method for reducing the computational overhead of fine-to-coarse MRME at the finest resolution level by considering for the spatial and spectral characteristics between wavelet decomposition levels simultaneously. As we know, there is high correlation between the adjacent blocks and it can give the very important clue to estimate motion at finest level. So, in this paper, using the initial motion vector and the adjacent motion vector in the coarsest level, we determine the optimal direction that will be minimized the estimation error in the finest level. In that direction, we define the potential searching region within the full searching region that is caused to increase much computational overhead in the FtC method. Last, in that region, we process the efficient 2-step motion estimation. and estimate the motion vector at finest resolution level. And then, this determined motion vector is scaled to coarser resolutions. As simulation result, this method is similar to computational complexity of the CtF MRME method and very significantly reduces that of the FtC MRME method. In addition, they provide higher quality than CtF MRME, both visually and quantitatively

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.137-142
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• 2013

Direction of arrival is estimating for desire signal direction among received signal on antenna in spatial. In this paper, we were an estimation a receiving signal direction of arrival using multi beam forming in radar. We proposed, by signal direction of arrival estimation method, an algorithm which combine spatial correlation matrix weight value and beam steering algorithm in this paper. Through simulation, we were analysis a performance to compare general algorithm and proposal algorithm. In direction of arrival estimation, proposed algorithm is effectivity to decrease processing time because it is not doing an eigen decomposition. We showed that proposal algorithm improve more target estimation than general algorithm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.400-404
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• 2015

In this paper, we study for direction of arrival MUSIC spatial spectrum algorithm in order to desired signal estimation in spatial. Proposal MUSIC spatial spectrum algorithm in paper use model error and Bayesian method to estimation on correct target position. Receiver array response vector using adaptive array antenna use Bayesian method, and target position estimate to update weight value with model error method. Target's signal estimation of desired direction of arrival in this paper apply weight value of signal covariance matrix for array response vector after removing incident signal interference and noise, respectively. Though simulation, we analyze to compare proposed method with general method.

• Communications for Statistical Applications and Methods
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• v.27 no.5
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• pp.547-568
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• 2020

Modeling the statistical autocorrelations in spatial data is often achieved through the estimation of the variograms, where the selection of the appropriate valid variogram model, especially for small samples, is crucial for achieving precise spatial prediction results from kriging interpolations. To estimate such a variogram, we traditionally start by computing the empirical variogram (traditional Matheron or robust Cressie-Hawkins or kernel-based nonparametric approaches). In this article, we conduct numerical studies comparing the performance of these empirical variograms. In most situations, the nonparametric empirical variable nearest-neighbor (VNN) showed better performance than its competitors (Matheron, Cressie-Hawkins, and Nadaraya-Watson). The analysis of the spatial groundwater dataset used in this article suggests that the wave variogram model, with hole effect structure, fitted to the empirical VNN variogram is the most appropriate choice. This selected variogram is used with the ordinary kriging model to produce the predicted pollution map of the nitrate concentrations in groundwater dataset.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.691-695
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• 2004

In recent years, mary studies for efact estimation of groudwater recharge has been performed. They can be categorized into three groups : analytical method by means of groundwater recession curve, water budget analysis based on watershed, and the method using groundwater model. Since groundwater recharge rate shows the spatial-temporal variability due to hydrogeological heterogeneity, existing studies have various limits to deal with these characteristics. The method of estimating daily recharge rate with spatial-temporal variation based on rainfall-runoff model is suggested in this study for this purpose. This method is expected to enhance existing indirect method by means of reflecting climatic conditions, land use and hydrogeological heterogeneity.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.157-168
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• 2006

Spatial detection system such as AVI, GPS, and Beacon etc. can provide spatial travel time only after a vehicle Passes through a road section. In this context, majority of the existing studies on the link travel time estimation area has focused on the arrival time-based link travel time estimation. rather than departure time-based link travel time estimation. Even if some of the researches on this area have developed departure time-based link travel time estimation algorithms, they are limited in that they are not applicable in a real-time mode. The objective of this study is to develop an departure time-based link travel time estimation algorithm which is applicable in a real-tine mode. Firstly, this study discussed the tradeoff between accuracy and timeliness of the departure time-based on-line link travel time estimates. Secondly, this study developed an departure time-based on-line link travel time estimation algorithm which utilizes the Baysian inference logic. It was found that the proposed approach could estimate departure time-based link travel times in a real-time context with an acceptable accuracy and timeliness.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.191-201
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• 2018

In this present study, we, for the first time, retrieved total column of ozone ($O_3$) and tropospheric ozone vertical profile using the Optimal Estimation (OE) method based on the MAX-DOAS measurement at the Yonsei University in Seoul, Korea. The optical density fitting is carried out using the OE method to calculate ozone columns. The optical density between the MAX-DOAS data obtained by dividing the measured intensities for each viewing elevated angle by those at the zenith angle. The retrieved total columns of the ozone are 375.4 and 412.6 DU in the morning (08:13) and afternoon (17:55) on 23 May, 2017, respectively. In addition, under 10 km altitude, the $O_3$ vertical profile was retrieved with about 5% of retrieval uncertainty. However, above 10 km altitude, the $O_3$ vertical profile retrieval uncertainty was increased (>10%). The spectral fitting errors are 16.8% and 19.1% in the morning and afternoon, respectively. The method suggested in this present study can be useful to measure the total ozone column using the ground-based hyper-spectral UV sensors.