• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.160-166
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• 2024

The inversion of radiation field distribution is of great significance in the decommissioning sites of nuclear facilities. However, the radiation fields often contain multiple mixtures of radionuclides, making the inversion extremely difficult and posing a huge challenge. Many radiation field reconstruction methods, such as Kriging algorithm and neural network, can not solve this problem perfectly. To address this issue, this paper proposes an optimized inverse distance weighted (IDW) interpolation algorithm for reconstructing the gamma radiation field. The algorithm corrects the difference between the experimental and simulated scenarios, and the data is preprocessed with normalization to improve accuracy. The experiment involves setting up gamma radiation fields of three Co-60 radioactive sources and verifying them by using the optimized IDW algorithm. The results show that the mean absolute percentage error (MAPE) of the reconstruction result obtained by using the optimized IDW algorithm is 16.0%, which is significantly better than the results obtained by using the Kriging method. Importantly, the optimized IDW algorithm is suitable for radiation scenarios with multiple radioactive sources, providing an effective method for obtaining radiation field distribution in nuclear facility decommissioning engineering.

• 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 Acoustical Society of Korea
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• v.21 no.6
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• pp.552-558
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• 2002

Recently, based on the human speech recognition (HSR) model of Fletcher, the multi-band speech recognition has been intensively studied by many researchers. As a new automatic speech recognition (ASR) technique, the multi-band speech recognition splits the frequency domain into several sub-bands and recognizes each sub-band independently. The likelihood scores of sub-bands are weighted according to reliabilities of sub-bands and re-combined to make a final decision. This approach is known to be robust under noisy environments. When the noise is stationary a sub-band SNR can be estimated using the noise information in non-speech interval. However, if the noise is non-stationary it is not feasible to obtain the sub-band SNR. This paper proposes the inverse sub-band distance (ISD) weighting, where a distance of each sub-band is calculated by a stochastic matching of input feature vectors and hidden Markov models. The inverse distance is used as a sub-band weight. Experiments on 1500∼1800㎐ band-limited white noise and classical guitar sound revealed that the proposed method could represent the sub-band reliability effectively and improve the performance under both stationary and non-stationary band-limited noise environments.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.465-474
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• 2009

Convective/stratiform radar echo classification schemes by Steiner et al. (1995) and Biggerstaff and Listemaa (2000) are examined on a monsoonal front during the summer monsoon-Changma period, which is organized as a cloud cluster with mesoscale convective complex. Target radar is S-band with wavelength of 10cm, spatial resolution of 1km, elevation angle interval of 0.5-1.0 degree, and minimum elevation angle of 0.19 degree at Jindo over the Korean Peninsula. For verification of rainfall amount retrieved from the echo classification, ground-based rain gauge observations (Automatic Weather Stations) are examined, converting the radar echo grid data to the station values using the inverse distance weighted method. Improvement from the echo classification is evaluated based on the correlation coefficient and the scattered diagram. Additionally, an optimal use method was designed to produce combined rainfalls from the radar echo and Tropical Rainfall Measuring Mission Precipitation Radar (TRMM/PR) data. Optimal values for the radar rain and TRMM/PR rain are inversely weighted according to the error variance statistics for each single station. It is noted how the rainfall distribution during the summer monsoon frontal system is improved from the classification of convective/stratiform echo and the use of the optimal use technique.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.5
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• pp.1-7
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• 2011

The objective of this study is to decide a spatial interpolation method on temperature data for the suitability analysis of garlic cultivation. In Korea, garlic is the second most cultivated condiment vegetable after red pepper. Nowadays warm-temperate garlic faces potential shift of its arable area according to warmer temperature in the Korean Peninsula, and the change can be drawn with the precise temperature map derived from interpolation on point-measured data. To find the preferable interpolation method in cases of germination and vegetative period of the garlic, different approaches were tested as follows: Inverse Distance Weighted (IDW), Spline, Ordinary Kriging (OK), and Universal Kriging (UK). As a result, IDW and UK show the lowest root mean square errors as for the germination and vegetative seasons, respectively. However, statistically significant difference was not revealed among the applied methods regarding the germinating period. Eventually this will contribute to mapping the suitable lands for the cultivation of warm-temperate garlic reasonably.

• Journal of Environmental Impact Assessment
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• v.18 no.1
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• pp.31-39
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• 2009

A lot of data which are used in environment analysis of air pollution have characteristics that are distributed continuously in space. In this point, the collected data value such as precipitation, temperature, altitude, pollution density, PM10 have spatial aspect. When geostatistical data analysis are needed, acquisition of the value in every point is the best way, however, it is impossible because of the costs and time. Therefore, it is necessary to estimate the unknown values at unsampled locations based on observations. In this study, spatial interpolation method such as local trend surface model, IDW(inverse distance weighted), RBF(radial basis function), Kriging were applied to PM10 annual average concentration of Seoul in 2005 and the accuracy was evaluated. For evaluation of interpolation accuracy, range of estimated value, RMSE, average error were analyzed with observation data. The Kriging and RBF methods had the higher accuracy than others.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1520-1524
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• 2010

지상에 설치된 우량관측소를 통해서 자료가 수집되는 강우자료는 공간적으로 분포하고 있는 공간자료(spatial data)이며, 지점자료(point data)이다. 공간자료(spatial data)는 공간적으로 분포되지 않는 일반 데이터와는 다른 속성을 가지고 있으며 공간적인 위치가 데이터 발생의 중요한 변수로 적용될 수 있고, 인접 데이터와의 상관관계가 고려되어야 한다. 본 연구는 공간분석기법을 이용하여 보다 효과적인 강우분석을 하기 위한 것으로서, 우리나라 총 679개 우량관측소의 2008년 강우자료를 바탕으로 티센(Thiessen) 기법, IDW(Inverse Distance Weighted), 스플라인(Spline) 등과 공간통계학적 방법인 크리깅(Kriging)을 이용하여 주요 유역별 면적 강우량 산정 및 미계측 지역의 강우량 추정을 모의하였다. 본 연구결과 유역별 면적강우량 추정시 티센 및 경향면 분석법, Natural Neighbor 방법은 일부 과다 추정되는 것으로 나타났고, IDW, RBF, 크리깅의 방법은 큰 차이를 보이지 않았으나, 미계측 지역의 강우량 추정에는 일반크리깅의 정확도가 비교적 높은 것으로 나타났다.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.6
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• pp.463-474
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• 1997

Metallic elements in dustfall have been known as notable air pollutants directly or indirectly influencing human health and wealth. The first aim of this study was to obtain precise spatial distribution patterns of 5 elements (Pb, Zn, K, Cr, and Al) in dustfall around Suwon area. To predict isometric lines of metal fluxes deposited on unsupervised random sites, the study has applied both spatial statistics as a receptor model and a GIS (geographic information system). Total of 31 sampling sites were selected in the study area (roughly 3 by 3 km grid basis) and dustfall samples were then collected monthly basis by the British deposit gauges from Dec., 1995 to Nov., 1996. The metallic elements in the dustfall were then analyzed by an atomic absorption spectrometer (AAS). On the other hand, a base map overlapped by 7 layers was constructed by using the AutoCAD R13 and ARC/INFO 3.4D. Four different spatial interpolation and expolation techniques such as IDW (inverse distance weighted averaging), TIN (triangulated irregular network), polynomial regression, and kriging technique were examined to compare spatial distribution patterns. Each pattern obtained by each technique was substantally different as varing pollutant types, land of use types, and topological conditions, etc. Thus, our study focused intensively on uncertainty analysis based on a concept of the jackknife and the sum of error distance. It was found that a kriging technique was the best applicalbe in this study area.

• Korean Journal of Remote Sensing
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• v.26 no.4
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• pp.373-385
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• 2010

A new method to mosaic reflectivity over the overlapped coverage of two radars was developed. The method mosaics the radar reflectivity with weights after adjustment of reflectivity differences on overlapped coverage of neighboring two radars. Their weights are inverse proportion to the difference between the height of an interpolated reflectivity and the level of CAPPI (Constant Altitude PPI). The performance of this method was compared to different mosaic methods (Mosaics by maximum value, averaged value, nearest value and distance weighted value) using the reflectivity fields of a typhoon event observed by two radar. New method was better than any other methods either as a continuity and as a bias analysis of reflectivity at the boundaries in overlapped coverage by two radars.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.15 no.2
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• pp.77-84
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• 2012

This study suggested the planting model of Zelkova serrata communities in the areas with the warmth index of both 80~100 and $100{\sim}120^{\circ}C{\cdot}month$. Warmth index was calculated with 449 weather points using inverse distance weighted interpolation method. The planting species were selected by correlation analysis between Z. serrata and each species of four or more frequency among the 36 relev$\acute{e}$ surveyed for this study. The result of this study is summarized as follows : Warmth index of Z. serrata communities was among $74{\sim}118^{\circ}C{\cdot}month$. Results of the correlation analysis between Z. serrata and each species observed that the Z. serrata belongs to the tree layer with warmth index of 80~100 and $100{\sim}120^{\circ}C{\cdot}month$. On the other hand, the species of Carpinus laxiflora, Quercus serrata, Prunus sargentii and Platycarya strobilacea appeared only in the tree layer with warmth index of $80{\sim}100^{\circ}C{\cdot}month$. Z. serrata and Styrax japonica appeared in the subtree layer with the warmth index of 80~100 and $100{\sim}120^{\circ}C{\cdot}month$, while Acer pseudosieboldianum, Lindera erythrocarpa, Acer mono, Quercus serrata, etc. appeared in the subtree layer with the warmth index of $80{\sim}100^{\circ}C{\cdot}month$. Z. serrata, Ligustrum obtusifolium, Lindera obtusiloba, Callicarpa japonica and Zanthoxylum schinifolium all appeared in the shrub layer with the warmth index of 80~100 and $100{\sim}120^{\circ}C{\cdot}month$. Lindera erythrocarpa, Orixa japonica, Staphylea bumalda, Akebia quinata and Sorbus alnifolia appeared in the shrub layer with the warmth index of $80{\sim}100^{\circ}C{\cdot}month$ and Styrax japonica and Stephanandra incisa appeared in the shrub layer with the warmth index of $100{\sim}120^{\circ}C{\cdot}month$, The numbers of each species planted in a $100m^2$ area of the Z. serrata community were suggested as follows : five in tree layer, five in subtree layer and nine in shrub layer. The average area of canopy are suggested to be about $86m^2$ for tree layer, $34m^2$ for subtree layer and $34m^2$ for shrub layer.