• Title/Summary/Keyword: 거리가중

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Analyzing Spatio-temporal Variability of Temperature and Precipitation in Seoul (서울시 기온 및 강수량의 시공간변이성 분석)

  • Choi, Hyun-Ah;Song, Chul-Chul;Lee, Woo-Kyun;Kwak, Han-Bin
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2008.06a
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    • pp.455-460
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    • 2008
  • 본 연구에서는 1997년 1월부터 2006년 12월까지의 기상청에서 제공하는 31개 자동기상관측망(AWS: Automatic Weather Stations)에 의한 지표 근처 기온($^{\circ}C$) 및 강수(mm) 자료를 이용하여 서울 지역 기상인자의 시 공간 구조 분석 및 변화경향과 변이성을 도출하였다. 미관측지점의 값을 추정하기 위하여 주변 관측지점들을 고려하여, 그 영향은 거리에 반비례함을 반영하는 공간통계학적 방법 중 IDSW(Inverse Distance Squared Weighing:거리자승역산가중)를 적용하여 보관하였다. 그 결과 서울시의 기온과 강수량 모두 1997년에 비해 2006년의 기온이 약 $1.03^{\circ}C$, 강수량이 약 483mm 증가한 것으로 나타났다. 기후변이성의 특성은 과거 10년 동안 기온의 경우 산림지역에서는 변화의 폭이 높게 나타났으며, 시간이 지나면서 감소하는 경향을 보였다. 주거 지역의 경우 변화이 폭이 낮게 나타났으며, 시간이 지나면서 증가하는 경향을 보였다. 그러나 강수량의 경우 산림지역과 주거지역의 변이성의 차이가 나타나지 않았다.

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Development of an Automatic 3D Coregistration Technique of Brain PET and MR Images (뇌 PET과 MR 영상의 자동화된 3차원적 합성기법 개발)

  • Lee, Jae-Sung;Kwark, Cheol-Eun;Lee, Dong-Soo;Chung, June-Key;Lee, Myung-Chul;Park, Kwang-Suk
    • The Korean Journal of Nuclear Medicine
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    • v.32 no.5
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    • pp.414-424
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    • 1998
  • Purpose: Cross-modality coregistration of positron emission tomography (PET) and magnetic resonance imaging (MR) could enhance the clinical information. In this study we propose a refined technique to improve the robustness of registration, and to implement more realistic visualization of the coregistered images. Materials and Methods: Using the sinogram of PET emission scan, we extracted the robust head boundary and used boundary-enhanced PET to coregister PET with MR. The pixels having 10% of maximum pixel value were considered as the boundary of sinogram. Boundary pixel values were exchanged with maximum value of sinogram. One hundred eighty boundary points were extracted at intervals of about 2 degree using simple threshold method from each slice of MR images. Best affined transformation between the two point sets was performed using least square fitting which should minimize the sum of Euclidean distance between the point sets. We reduced calculation time using pre-defined distance map. Finally we developed an automatic coregistration program using this boundary detection and surface matching technique. We designed a new weighted normalization technique to display the coregistered PET and MR images simultaneously. Results: Using our newly developed method, robust extraction of head boundary was possible and spatial registration was successfully performed. Mean displacement error was less than 2.0 mm. In visualization of coregistered images using weighted normalization method, structures shown in MR image could be realistically represented. Conclusion: Our refined technique could practically enhance the performance of automated three dimensional coregistration.

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Construction of Super-Resolution Convolutional Neural Network Model for Super-Resolution of Temperature Data (기온 데이터 초해상화를 위한 Super-Resolution Convolutional Neural Network 모델 구축)

  • Kim, Yong-Hoon;Im, Hyo-Hyuk;Ha, Ji-Hun;Park, Kun-Woo;Kim, Yong-Hyuk
    • Journal of the Korea Convergence Society
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    • v.11 no.8
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    • pp.7-13
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    • 2020
  • Meteorology and climate are closely related to human life. By using high-resolution weather data, services that are useful for real-life are available, and the need to produce high-resolution weather data is increasing. We propose a method for super-resolution temperature data using SRCNN. To evaluate the super-resolution temperature data, the temperature for a non-observation point is obtained by using the inverse distance weighting method, and the super-resolution temperature data using interpolation is compared with the super-resolution temperature data using SRCNN. We construct an SRCNN model suitable for super-resolution of temperature data and perform super-resolution of temperature data. As a result, the prediction performance of the super-resolution temperature data using SRCNN was about 10.8% higher than that using interpolation.

Extraction of Crime Vulnerable Areas Using Crime Statistics and Spatial Big Data (공간 빅데이터와 범죄통계자료를 이용한 범죄취약지 추출)

  • Park, So-Rang;Park, Jae-Kook
    • 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).

Comparison and Evaluation of Root Mean Square for Parameter Settings of Spatial Interpolation Method (공간보간법의 매개변수 설정에 따른 평균제곱근 비교 및 평가)

  • Lee, Hyung-Seok
    • Journal of the Korean Association of Geographic Information Studies
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    • v.13 no.3
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    • pp.29-41
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    • 2010
  • In this study, the prediction errors of various spatial interpolation methods used to model values at unmeasured locations was compared and the accuracy of these predictions was evaluated. The root mean square (RMS) was calculated by processing different parameters associated with spatial interpolation by using techniques such as inverse distance weighting, kriging, local polynomial interpolation and radial basis function to known elevation data of the east coastal area under the same condition. As a result, a circular model of simple kriging reached the smallest RMS value. Prediction map using the multiquadric method of a radial basis function was coincident with the spatial distribution obtained by constructing a triangulated irregular network of the study area through the raster mathematics. In addition, better interpolation results can be obtained by setting the optimal power value provided under the selected condition.

Seasonal Trend of Elevation Effect on Daily Air Temperature in Korea (일별 국지기온 결정에 미치는 관측지점 표고영향의 계절변동)

  • 윤진일;최재연;안재훈
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.3 no.2
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    • pp.96-104
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    • 2001
  • Usage of ecosystem models has been extended to landscape scales for understanding the effects of environmental factors on natural and agro-ecosystems and for serving as their management decision tools. Accurate prediction of spatial variation in daily temperature is required for most ecosystem models to be applied to landscape scales. There are relatively few empirical evaluations of landscape-scale temperature prediction techniques in mountainous terrain such as Korean Peninsula. We derived a periodic function of seasonal lapse rate fluctuation from analysis of elevation effects on daily temperatures. Observed daily maximum and minimum temperature data at 63 standard stations in 1999 were regressed to the latitude, longitude, distance from the nearest coastline and altitude of the stations, and the optimum models with $r^2$ of 0.65 and above were selected. Partial regression coefficients for the altitude variable were plotted against day of year, and a numerical formula was determined for simulating the seasonal trend of daily lapse rate, i.e., partial regression coefficients. The formula in conjunction with an inverse distance weighted interpolation scheme was applied to predict daily temperatures at 267 sites, where observation data are available, on randomly selected dates for winter, spring and summer in 2000. The estimation errors were smaller and more consistent than the inverse distance weighting plus mean annual lapse rate scheme. We conclude that this method is simple and accurate enough to be used as an operational temperature interpolation scheme at landscape scale in Korea and should be applicable to elsewhere.

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Selecting Target Sites for Non-point Source Pollution Management Using Analytic Hierarchy Process (계층분석적 의사결정기법을 이용한 비점원오염 관리지역의 선정)

  • Shin, Jung-Bum;Park, Seung-Woo;Kim, Hak-Kwan;Choi, Ra-Young
    • Proceedings of the Korea Water Resources Association Conference
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    • 2007.05a
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    • pp.976-980
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    • 2007
  • 본 논문에서는 비점원오염 관리를 위한 지역선정을 위하여 계층분석적 의사결정기법에 의한 접근 방법을 제시하였다. 주어진 유역 내에서의 비점원오염의 중요기여 인자간의 관계를 반영한 것이 본 연구의 특징이다. 주요인자로는 경사도, 유달거리, 유효강우비, 불투수면적비, 토양유실량이다. 각 인자의 가중치는 계층분석적 의사결정기법(AHP)으로 구하였으며 각 인자의 가중값과 속성 값의 단순 부가가중 합으로 표현되는 비점원오염 영향지수를 정의하였다. 높은 영향지수를 가지는 지역을 비점원오염 관리지역으로 제안하였으며, 시험유역으로 발안HP#6유역을 선정하여 적용해보았다. 관리지역 결과를 비교하기 위하여 AGNPS 모의를 통한 비점원오염 부하량간의 분석을 시도하였다. 비교 및 분석을 위해 Moran's I를 이용하였으며, T-N은 $0.38{\sim}0.45$, T-P는 $0.15{\sim}0.22$의 범위를 보였다. 이는 두 접근 방법이 상이함에도 공간적으로 유사한 경향을 보인다는 것을 말한다. 본 연구에서 제시하는 방법은 비점원오염 관리지역 선정에 있어서 적용가능 함을 의미한다.

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A Empirical Study on Recommendation Schemes Based on User-based and Item-based Collaborative Filtering (사용자 기반과 아이템 기반 협업여과 추천기법에 관한 실증적 연구)

  • Ye-Na Kim;In-Bok Choi;Taekeun Park;Jae-Dong Lee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2008.11a
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    • pp.714-717
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    • 2008
  • 협업여과 추천기법에는 사용자 기반 협업여과와 아이템 기반 협업여과가 있으며, 절차는 유사도 측정, 이웃 선정, 예측값 생성 단계로 이루어진다. 유사도 측정 단계에는 유클리드 거리(Euclidean Distance), 코사인 유사도(Cosine Similarity), 피어슨 상관계수(Pearson Correlation Coefficient) 방법 등이 있고, 이웃 선정 단계에는 상관 한계치(Correlation-Threshold), 근접 N 이웃(Best-N-Neighbors) 방법 등이 있다. 마지막으로 예측값 생성 단계에는 단순평균(Simple Average), 가중합(Weighted Sum), 조정 가중합(Adjusted Weighted Sum) 등이 있다. 이처럼 협업여과 추천기법에는 다양한 기법들이 사용되고 있다. 따라서 본 논문에서는 사용자 기반 협업여과와 아이템 기반 협업여과 추천기법에 사용되는 유사도 측정 기법과 예측값 생성 기법의 최적화된 조합을 알아보기 위해 성능 실험 및 비교 분석을 하였다. 실험은 GroupLens의 MovieLens 데이터 셋을 활용하였고 MAE(Mean Absolute Error)값을 이용하여 추천기법을 비교 하였다. 실험을 통해 유사도 측정 기법과 예측값 생성 기법의 최적화된 조합을 찾을 수 있었고, 사용자 기반 협업여과와 아이템 기반 협업여과의 성능비교를 통해 아이템 기반 협업여과의 성능이 보다 우수했음을 확인 하였다.

Research on the Development of Distance Metrics for the Clustering of Vessel Trajectories in Korean Coastal Waters (국내 연안 해역 선박 항적 군집화를 위한 항적 간 거리 척도 개발 연구)

  • Seungju Lee;Wonhee Lee;Ji Hong Min;Deuk Jae Cho;Hyunwoo Park
    • Journal of Navigation and Port Research
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    • v.47 no.6
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    • pp.367-375
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    • 2023
  • This study developed a new distance metric for vessel trajectories, applicable to marine traffic control services in the Korean coastal waters. The proposed metric is designed through the weighted summation of the traditional Hausdorff distance, which measures the similarity between spatiotemporal data and incorporates the differences in the average Speed Over Ground (SOG) and the variance in Course Over Ground (COG) between two trajectories. To validate the effectiveness of this new metric, a comparative analysis was conducted using the actual Automatic Identification System (AIS) trajectory data, in conjunction with an agglomerative clustering algorithm. Data visualizations were used to confirm that the results of trajectory clustering, with the new metric, reflect geographical distances and the distribution of vessel behavioral characteristics more accurately, than conventional metrics such as the Hausdorff distance and Dynamic Time Warping distance. Quantitatively, based on the Davies-Bouldin index, the clustering results were found to be superior or comparable and demonstrated exceptional efficiency in computational distance calculation.

An Adaptive Control of Symmetry Contribution Based Generalized Symmetry Transform (적응적 대칭기여도 제어 기반 일반화 대칭변환)

  • Jeon, Joon-Hyung;Lee, Seung-Hee;Park, Kil-Houm
    • Journal of Korea Multimedia Society
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    • v.17 no.2
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    • pp.208-217
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    • 2014
  • This paper propose an adaptive control of symmetry contribution based generalized symmetry transform. which can be controlled symmetry contribution according to the intensity orientation of two pixels. In the proposed method, we define the C-D(convergent and divergent)plane which represents convergence and divergence region of gradient pairs. and used the gaussian phase wight function, with respect to the distance from the gradient pair to an extreme point, in calculating the symmetry contribution. The proposed method can be detect the object more efficiently by adaptive controlling the cut-off frequency of the gaussian phase wight function. To evaluate a performance of the proposed method, we compare the proposed method and conventional GST method in various images including IR image. we prove that the proposed method have better performance in object detection.