• Journal of Environmental Science International
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• v.27 no.7
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• pp.509-518
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• 2018

Weather is the most influential factor for crop cultivation. Weather information for cultivated areas is necessary for growth and production forecasting of agricultural crops. However, there are limitations in the meteorological observations in cultivated areas because weather equipment is not installed. This study tested methods of predicting the daily mean temperature in onion fields using geostatistical models. Three models were considered: inverse distance weight method, generalized additive model, and Bayesian spatial linear model. Data were collected from the AWS (automatic weather system), ASOS (automated synoptic observing system), and an agricultural weather station between 2013 and 2016. To evaluate the prediction performance, data from AWS and ASOS were used as the modeling data, and data from the agricultural weather station were used as the validation data. It was found that the Bayesian spatial linear regression performed better than other models. Consequently, high-resolution maps of the daily mean temperature of Jeonnam were generated using all observed weather information.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.197-197
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• 2020

기후변화 연구의 주요 요소 중 하나는 온도, 강수량 및 증발과 같은 기후 요인의 변화를 연구하는 것이다. General Circulation Model(GCM)은 다양한 기후 요인의 변화를 연구하는 데 일반적으로 사용되고 있다. Coupled Model Intercomparison Project(CMIP)는 전 세계의 30여 개 이상의 기관에서 개발한 GCM의 모의 결과를 연구 및 공유하기 위해 개발되었다. 기후 연구에서 대표적으로 사용하고 있는 CMIP5의 GCM은 미래 시나리오인 Representative Concentration Pathway(RCP)를 기반으로 전망 기간의 기후요소를 예측한다. 현재 개발하고 있는 CMIP6의 미래 시나리오인 Shared Socioeconomic Pathways(SSP)는 인구, 경제개발, 생태계, 자원, 제도 및 사회적 요인에 대한 미래의 사회적, 경제적 변화에 따른 기후변화에 대한 대응을 포함하고 있으며, CMIP6의 미래 시나리오는 사회적 및 경제적 결합을 통해 기후변화에 대한 정책 영향에 대한 증진된 결과를 도출할 것으로 예측하고 있다. 따라서 본 연구는 CMIP5의 INM-CM4와 CMIP6의 INM-CM5를 사용하여 대한민국의 과거 기간(1970-2005)의 월 강수량에 대한 성능을 비교하였다. 격자형 자료인 GCM을 Inverse distance weight를 사용하여 대한민국 22개 관측소로 거리 보간을 수행하였으며, 편이보정 방법으로는 분위사상법(Quantile mapping) 방법 중 Smoothing Spline 방법을 사용하여 관측소와의 오차를 수정하였다. 산정된 강수량을 토대로 6개의 평가지표(NRMSE, Pbias, NSE, PRCP100, PRCP200, PRCP300)를 사용하여 GCM의 성능을 평가하여 INM-CM4와 INM-CM5의 성능을 비교하였다.

• Geophysics and Geophysical Exploration
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• v.21 no.1
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• pp.1-7
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• 2018

In the two-dimensional (2D) modeling of electrical method, the potential in the space domain is reconstructed with the calculated potentials in the wavenumber domain using inverse Fourier transform. The inverse Fourier integral is numerically evaluated using the transformed potential at different wavenumbers. In order to improve the precision of the integration, either the logarithmic or exponential approximation has been used depending on the size of wavenumber. Two numerical methods have been generally used to evaluate the integral; interval integration and Gaussian quadrature. However, both methods do not consider the distance from the current source. Thus the resulting potential in the space domain shows some error. Especially when the distance from the current source is very small or large, the error increases abruptly and the evaluated potential becomes extremely unstable. In this study, we developed a new method to calculate the integral accurately by introducing the distance from the current source to the rescaled Gauss abscissa and weight. The numerical tests for homogeneous half-space model show that the developed method can yield the error level lower than 0.4 percent over the various distances from the current source.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.42-54
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• 2012

The main purpose of this study is to suggest the spatial statistical approach suitable for the delimitation of Busan CBD. For this purpose, Getis-Ord $G_i^*$ and both of IDW (Inverse Distance Weight) and FDB(Fixed Distance Band) were applied to delimit the CBD boundary. And then, the results of the CBD boundary were compared and verified with the methodologies of the previous studies. The result of IDW accorded with the previous study relating to the delimitation of the boundary of CBD, and the result of FDB was reflecting the characteristics of the mixed-use residential of a transition zone. As a result of the land use quotient, the mixed land use of residential and commercial was highly specialized in the boundary of FDB. These results will be able to support the understanding of urban spatial structure and the effective CBD management.

• 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.

• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.612-624
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• 2005

In this paper, we propose a surface-based registration using a gaussian weighted distance map for PET-CT brain image fusion. Our method is composed of three main steps: the extraction of feature points, the generation of gaussian weighted distance map, and the measure of similarities based on weight. First, we segment head using the inverse region growing and remove noise segmented with head using region growing-based labeling in PET and CT images, respectively. And then, we extract the feature points of the head using sharpening filter. Second, a gaussian weighted distance map is generated from the feature points in CT images. Thus it leads feature points to robustly converge on the optimal location in a large geometrical displacement. Third, weight-based cross-correlation searches for the optimal location using a gaussian weighted distance map of CT images corresponding to the feature points extracted from PET images. In our experiment, we generate software phantom dataset for evaluating accuracy and robustness of our method, and use clinical dataset for computation time and visual inspection. The accuracy test is performed by evaluating root-mean-square-error using arbitrary transformed software phantom dataset. The robustness test is evaluated whether weight-based cross-correlation achieves maximum at optimal location in software phantom dataset with a large geometrical displacement and noise. Experimental results showed that our method gives more accuracy and robust convergence than the conventional surface-based registration.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.161-171
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• 2018

This study set out to identify crime vulnerable areas with the GIS spatial analysis technique for the prediction of crimes. Crime vulnerable areas were extracted from the statistics of crimes with the GIS hotspot analysis technique and the inverse distance weighted(IDW) method applied to different crimes according to places and use districts. The scope of surveillance and weight were calculated for each of CPTED surveillance elements including CCTV, streetlamp, patrol division, and police substation. Maps of crime vulnerable areas were overlapped one after another to make a CPTED-based one expressed in four grades(safety, attention, warning, and risk).

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.5
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• pp.80-86
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• 2000

The Tailor Welded Blanks(TWB) are using various materials (different thickness, strength and different materials) can be welded together prior to the forming process. Therefore, TWB applications have become little by little important in automobile industries, because it has more light weight and process reduction. A burnish area is very important for TWB using laser welding. In this paper, evaluated failure criterion, effect of clearance and distance of between pad and punch by computer simulation. We used element separation method for fracture. And applied a plastic strain to failure criterion. According to the analysis results, we obtain failure criterion, when plastic strain is 2.0. The burnish area and clearance were inverse proportional.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.188-202
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• 2011

Due to emissions of greenhouse gases caused by increased use of fossil fuels, the climate change has been detected and this phenomenon would affect even larger changes in temperature and precipitation of South Korea. Especially, the increase of temperature by climate change can affect the amount and pattern of snowfall. Accordingly, we tried to predict future snowfall and the snowfall pattern changes by using the downscaled GCM (general circulation model) scenarios. Causes of snow varies greatly, but the information provided by GCM are maximum / minimum temperature, rainfall, solar radiation. In this study, the possibility of snow was focused on correlation between minimum temperatures and future precipitation. First, we collected the newest fresh snow depth offered by KMA (Korea meteorological administration), then we estimate the temperature of snow falling conditions. These estimated temperature conditions were distributed spatially and regionally by IDW (Inverse Distance Weight) interpolation. Finally, the distributed temperature conditions (or boundaries) were applied to GCM, and the future snowfall was predicted. The results showed a wide range of variation for each scenario. Our models predict that snowfall will decrease in the study region. This may be caused by global warming. Temperature rise caused by global warming highlights the effectiveness of these mechanisms that concerned with the temporal and spatial changes in snow, and would affect the spring water resources.

• Journal of Astronomy and Space Sciences
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• v.22 no.3
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• pp.283-292
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• 2005

Ionosphere is deeply coupled to the space environment and introduces the perturbations to radio signal because of its electromagnetic characteristics. Therefore, the status of ionosphere can be estimated by analyzing the GPS signal errors which are penetrating the ionosphere and it can be the key to understand the global circulation and change in the upper atmosphere, and the characteristics of space weather. We used 9 GPS Continuously Operating Reference Stations (CORS), which have been operated by Korea Astronomy and Space Science Institute (KASI) , to determine the high precision of Total Electron Content (TEC) and the pseudorange data which is phase-leveled by a linear combination with carrier phase to reduce the inherent noise. We developed the method to model a regional ionosphere with grid form and its results over South Korea with $0.25^{\circ}\;by\;0.25^{\circ}$ spatial resolution. To improve the precision of ionosphere's TEC value, we applied IDW (Inverse Distance Weight) and Kalman Filtering method. The regional ionospheric model developed by this research was compared with GIMs (Global Ionosphere Maps) preduced by Ionosphere Working Group for 8 days and the results show $3\~4$ TECU difference in RMS values.