• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.101-109
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• 2015

SMRs (standardized mortality rates) for major diseases, accidents, cancer are considered in small areas of administrative units such as Eup/Myeon/Dong from years 2005 to 2008. Due to small sample issue in small areas, the precision of directly estimated crude SMR for each area can be low. In this study, we consider the HGLM (hierarchical generalized linear model) with MRF (Markov random field) to account for the spatial correlations among the small areas. The effects of covariates for cause of mortality by Dongs in Seoul and disease maps based on the estimated SMR are presented. The results suggest how we analyze and interpret the difference in mortalities by small areas such as Dongs by revealing the spatial patterns.

• Journal of Korean Society on Water Environment
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• v.29 no.1
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• pp.97-106
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• 2013

The temporal and spatial variations of water quality in a stratified reservoir are fully dependent on the characteristics of inflow loading from its watershed and the transport regimes of pollutants after entering the reservoir. Because of the meteorological and hydrological conditions in Korea, the pollutants loading to reservoirs are mostly occur during rainfall events. Therefore it is important to understand the characteristics of pollutants loading from upstream rivers and their spatial propagation through the stratified reservoir during the rainfall events. The objectives of this study were to characterize the water quality variations in upstream rivers of Imha Reservoir during a rainfall event, and the transport and spatial variations of pollutants in the reservoir through extensive field monitoring and laboratory analysis. The results showed that the event mean concentration (EMC) of SS, BOD, $COD_{Mn}$, T-N, T-P, $PO_4-P$ are 8.6 ~ 362.1, 2.5 ~ 5.1, 1.5 ~ 5.1, 1.1 ~ 1.9, 8.3 ~ 57.1, 5.6 ~ 25.7 times greater than the mean concentrations of these parameters during non-rainfall period. The turbidity and SS data showed good linear correlations, but the relationships between flow and SS showed large variations because of hysteresis effect during rising and falling periods of the flood. The ratio of POC to TOC were 12.6 ~ 14.7% during the non-rainfall periods, but increased up to 28.2 ~ 41.7% during the flood event. The turbid flood flow formed underflow and interflow after entering the reservoir, and delivered a great amount of non-point pollutants such as labile and refractory organic matters and nutrients to the metalimnion layer of reservoir, which is just above the thermocline. Spatially, the lateral variations of most water quality parameters were marginal but the vertical variations were significant.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.147-154
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• 2009

Antenna grouping algorithm is hybrid of beamforming and spatial multiplexing. In antenna grouping system, we partition $N_t$ transmit antennas into $N_r$ groups and use beamforming in a group, spatial multiplexing between groups. We can transmit $N_r$ data streams in the $N_t{\times}N_r$ antenna grouping system. With antenna grouping, we can achieve diversity gain through beamforming, and high spectral efficiency through spatial multiplexing. But if channel is ill-conditioned or there are some correlations between antennas, the performance of antenna grouping is seriously degraded and in that case, beamforming is the best transmit strategy. By selecting the antenna grouping mode when channel is well-conditioned and by selecting the beamforming mode when channel is ill-conditioned, we can prevent serious fluctuation of BER performance caused by varying channel condition and achieve the best BER performance. In this paper, we investigate mode selection algorithm which can select antenna grouping mode or beamforming mode. we also propose a simple mode selection criterion.

• Journal of Soil and Groundwater Environment
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• v.18 no.3
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• pp.33-51
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• 2013

Spatial and temporal characteristics of nitrate contamination and hydrogeochemical parameters were investigated for springs and surficial and bedrock groundwaters in northeastern part of Hongseong. Two field investigations were conducted at dry and wet seasons in 2011 for 120 sites including measurement of field parameters with chemical analyses of major dissolved constituents. Nitrate concentrations were at background levels in springs while 45% of bedrock groundwater and 49% of surficial groundwater exceeded the drinking water standard of nitrate (10 mg/L as $NO_3$-N). The difference in nitrate concentrations between surficial and bedrock groundwater was statistically insignificant. Cumulative frequency distribution of nitrate concentrations revealed two inflection points of 2 and 16 mg/L as $NO_3$-N. Correlation analysis of hydrogeochemical parameters showed that nitrate had higher correlations with Sr, Mg, Cl, Na, and Ca, in surficial groundwater in both dry and wet season. In contrast, nitrate had much weaker correlations with other hydrogeochemical parameters in bedrock groundwater compared to surficial groundwater and had significant correlations only in wet season. Temporally, nitrate and chloride concentrations decreased and dissolved oxygen (DO) increased from dry season to wet season, which indicates that increased recharge during the wet season affected groundwater quality. Aerobic conditions were predominant for both surficial and bedrock groundwater indicating low natural attenuation potential of nitrate in the aquifers of the study area.

• Ocean and Polar Research
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• v.24 no.3
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• pp.267-278
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• 2002

This study investigated the spatial characteristics of warming trends and the dipole-like pattern of temperature field in the Antarctic Peninsula using surface air temperature (SAT) of 10 stations in the vicinity of the Antarctic Peninsula. SAT data for the 1962-2001 period at 6 stations (Rothera, Faraday/Vernadsky, Bellingshausen, Orcadas, Esperanza, Halley) revealed in general the larger warming trends in autumn and winter except for Halley. The largest warming was shown for August in the west side of the Peninsula (more than $0.9^{\circ}C/decade$). On the other hand, the recent 14-year SAT data showed the strong warming trends at 9 stations except for Halley in the earlier period (April-June) than August for the 1962-2001 period. The largest warming appeared in May at Esperanza and Butler Island. SAT of the two sides showed significant positive correlations over most of the period except for the mid- and the late 1970s, in which significant negative correlations were found. In the correlation analysis between SAT and sea surface temperature (SST) anomalies in the NINO 3.4 region, strong negative correlation was found in the west side of the Peninsula. Details of the correlation analysis exhibited that the negative correlation was significantly strong from the early 1980s to the mid-1990s. However, it was difficult to find significant correlations of ENSO with SAT in the east side of the Peninsula. So, in this study it failed to find out clearly the out-of-phase relationship of SAT across the Antarctic Peninsula.

• Korean Journal of Radiology
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• v.22 no.7
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• pp.1142-1151
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• 2021

Objective: To evaluate microstructural damage in high myopia (HM) patients using 3T diffusion kurtosis imaging (DKI). Materials and Methods: This prospective study included 30 HM patients and 33 age- and sex-matched healthy controls (HCs) with DKI. Kurtosis parameters including kurtosis fractional anisotropy (FA), mean kurtosis (MK), axial kurtosis (AK), and radial kurtosis (RK) as well as diffusion metrics including FA, mean diffusivity, axial diffusivity (AD), and radial diffusivity derived from DKI were obtained. Group differences in these metrics were compared using tract-based spatial statistics. Partial correlation analysis was used to evaluate correlations between microstructural changes and disease duration. Results: Compared to HCs, HM patients showed significantly reduced AK, RK, MK, and FA and significantly increased AD, predominately in the bilateral corticospinal tract, right inferior longitudinal fasciculus, superior longitudinal fasciculus, inferior fronto-occipital fasciculus, and left thalamus (all p < 0.05, threshold-free cluster enhancement corrected). In addition, DKI-derived kurtosis parameters (AK, RK, and MK) had negative correlations (r = -0.448 to -0.376, all p < 0.05) and diffusion parameter (AD) had positive correlations (r = 0.372 to 0.409, all p < 0.05) with disease duration. Conclusion: HM patients showed microstructural alterations in the brain regions responsible for motor conduction and vision-related functions. DKI is useful for detecting white matter abnormalities in HM patients, which might be helpful for exploring and monitoring the pathogenesis of the disease.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.221-237
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• 2005

For developing the site-specific fertilizer management strategies of crop, it is essential to know the spatial variability of soil factors and to assess their influence on the variability of crop growth and yield. In 2002 and 2003 cropping seasons within-field spatial variability of rice growth and yield was examined in relation to spatial variation of soil properties in the· two paddy fields having each area of ca. $6,600m^2$ in Suwon, Korea. The fields were managed without fertilizer or with uniform application of N, P, and K fertilizer under direct-seeded and transplanted rice. Stable soil properties such as content of clay (Clay), total nitrogen (TN), organic mater (OM), silica (Si), cation exchange capacity (CEC), and rice growth and yield were measured in each grid of $10\times10m$. The two fields showed quite similar spatial variation in soil properties, showing the smallest coefficient of variation (CV) in Clay $(7.6\%)$ and the largest in Si $(21.4\%)$. The CV of plant growth parameters measured at panicle initiation (PIS) and heading stage (HD) ranged from 6 to $38\%$, and that of rice yield ranged from 11 to $21\%$. CEC, OM, TN, and available Si showed significant correlations with rice growth and yield. Multiple linear regression model with stepwise procedure selected independent variables of N fertilizer level, climate condition and soil properties, explaining as much as $76\%$ of yield variability, of which $21.6\%$ is ascribed to soil properties. Among the soil properties, the most important soil factors causing yield spatial variability was OM, followed by Si, TN, and CEC. Boundary line response of rice yield to soil properties was represented well by Mitcherich equation (negative exponential equation) that was used to quantify the influence of soil properties on rice yield, and then the Law of the Minimum was used to identify the soil limiting factor for each grid. This boundary line approach using five stable soil properties as limiting factor explained an average of about $50\%$ of the spatial yield variability. Although the determination coefficient was not very high, an advantage of the method was that it identified clearly which soil parameter was yield limiting factor and where it was distributed in the field.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.52-65
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• 2012

The net biomass accumulation (or net primary production, NPP) and gross primary production (GPP) have closely related with carbon accumulations(or carbon exchange) in vegetation. There are many approaches to estimate biomass using remote sensing techniques. The vegetation indices (VIs) can be a methodology to estimate biomass which assumes total chlorophyll contents. Various VIs were characterized with difference development conditions as vegetation species, input datasets. The hyperspectral data have also different spatial/spectral resolutions for aerial surveying. Additionally they need particular spectral bands selection difficulty to calculate the VIs. The objective of this study is to evaluate the correlations with airborne hyperspectral data (compact airborne spectrographic imager, CASI) and spectral unmixing model (or spectral mixture analysis, SMA) to characterize vegetation indices in forest area. The spectral mixture analysis was used to model the spectral purity of each pixel as an endmember. The endmembers are the fraction components derived from hyperspectral data through the SMA. In this study, we choose three endmembers represented vegetation pixels in the hyperspectral data. These endmembers were compared with 9 VIs by the Pearson's correlation coefficient. The results show MTVI1 and TVI have same correlation coefficient with 0.877. The MCARI, especially has very high relationship with vegetation endmembers as 0.9061 at less vegetation and soil distributed site. The MTVI1 and TVI have high correlations with the vegetation endmembers as 0.757 in whole test sites.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.291-302
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• 2017

Radiometric calibration is a prerequisite to quantitative remote sensing, and its accuracy has a direct impact on the reliability and accuracy of the quantitative application of remotely sensed data. This paper presents absolute radiometric calibration of the KOMPSAT-3 (KOrea Multi Purpose SATellite-3) and cross calibration using the Landsat-8 OLI (Operational Land Imager). Absolute radiometric calibration was performed using a reflectance-based method. Correlations between TOA (Top Of Atmosphere) radiances and the spectral band responses of the KOMPSAT-3 sensors in Goheung, South Korea, were significant for multispectral bands. A cross calibration method based on the Landsat-8 OLI was also used to assess the two sensors using near simultaneous image pairs over the Libya-4 PICS (Pseudo Invariant Calibration Sites). The spectral profile of the target was obtained from EO-1 (Earth Observing-1) Hyperion data over the Libya-4 PICS to derive the SBAF (Spectral Band Adjustment Factor). The results revealed that the TOA radiance of the KOMPSAT-3 agree with Landsat-8 within 5.14% for all bands after applying the SBAF. The radiometric coefficient presented here appears to be a good standard for maintaining the optical quality of the KOMPSAT-3.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1605-1614
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• 2013

This paper presents a probabilistic methodology for small signal stability analysis of power system with correlated wind sources. The approach considers not only the stochastic characteristics of wind speeds which are treated as random variables with Weibull distributions, while also the wind speed spatial correlations which are characterized by a correlation matrix. The approach based on the 2m+1 point estimate method and Cornish Fisher expansion, the orthogonal transformation technique is used to deal with the correlation of wind farms. A case study is carried out on IEEE New England system and the probabilistic indexes for eigenvalue analysis are computed from the statistical processing of the obtained results. The accuracy and efficiency of the proposed method are confirmed by comparing with the results of Monte Carlo simulation. The numerical results indicate that the proposed method can actually capture the probabilistic characteristics of mode properties of the power systems with correlated wind sources and the consideration of spatial correlation has influence on the probability of system small signal stability.