• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.221-228
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• 2005

The paper proposes the improved error diffusion halftoning system to enhance the edges using the spatial perceptual characteristics of the human visual system. The proposed method computes a spatial variation(SV), which is the difference between a pixel luminance and the average of its $3{\times}3$ neighborhood pixels' luminances weighted according to the spatial positioning. Information of edge enhancement(IEE) Is computed using the SV and the local average luminance. The IEE is added to the quantizer's input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. The performance of the proposed method is compared with conventional methods by measuring the edge correlation. The halftone images by using the proposed method show better quality due to the enhanced edge. And the detailed edge is preserved in the halftone images by using the proposed method.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.313-321
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• 2005

Digital halftoning is a process to produce a binary image so that the original image and its binary counterpart appear similar when observed from a distance. Among digital halftoning methods, error diffusion is a procedure for generating high quality bilevel images from continuous-tone images but blurs the edge information in the bilevel images. To solve this problem, we propose the improved error diffusion using local spatial information of the original images. Based on the fact that the human vision perceives not a pixel but local mean of input image, we compute edge enhancement information(EEI) by appling the ratio of a pixel and its adjacent pixels to local mean. The weights applied to local means is computed using the ratio of local activity measure(LAM) to the difference between input pixels of 3$\times$3 blocks and theirs mean. LAM is the measure of luminance changes in local regions and is obtained by adding the square of the difference between input pixels of 3$\times$3 blocks and theirs mean. We add the value to a input pixel of quantizer to enhance edge. The performance of the proposed method is compared with conventional methods by measuring the edge correlation. The halftone images by using the proposed method show better quality due to the enhanced edge. And the detailed edge is preserved in the halftone images by using the proposed method. Also the proposed method improves the quality of halftone images because unpleasant patterns for human visual system are reduced.

• Journal of Navigation and Port Research
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• v.29 no.5 s.101
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• pp.403-408
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• 2005

The techniques of estimating angle of arrival(AOA) have played a key role for enhancement of wireless communications using array antennas. Among those techniques, the superresolution algorithms, such as MUSIC and ESPRIT, calculate the covariance matrix of the array output vectors which are observed at the array antennas, and then by using eigen-decomposition of the covariance matrix, they estimate AOAs of the received signals with high accuracy. However, superresolution algorithms based eigenvalue decomposition fails to estimate AOAs under multipath environments. Under multipath environments, it is difficult to estimate AOAs of the received signals due to coherency and high-correlation. To resolve coherent signals, the covariance matrix is calculated by using the conventional spatial smoothing technique, and then the techniques based on eigen-descomposition is applied. The result of the conventional spatial smoothing technique, however, is obtained at the cost of losing effective spatial aperture. Moreover, the conventional technique ignores any information in the cross-correlations of the array outputs the subarrays. As the result, the performance for AOA estimation is degraded. In this paper, we propose a new spatial smoothing technique, which consider the cross-correlation for subarrays. By computer simulation, the AOA estimation performance of the proposed method is compared with the conventional method and evaluated.

• Spatial Information Research
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• v.19 no.4
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• pp.81-89
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• 2011

This paper presents a multivariate kriging algorithm that integrates categorical data as secondary data for spatial interpolation of sparsely sampled ground survey data. Instead of using constant mean values in each attribute of categorical data, disaggregated local mean values at target grid points are first estimated by area-to-point kriging and then are used as local mean values in simple kriging with local means. This algorithm is illustrated through a case study of spatial interpolation of a geochemical copper element with geological map data. Cross validation results indicates that the presented algorithm leads to significant respective improvement of 15% and 25% in prediction capability, compared with univariate ordinary kriging and conventional simple kriging with constant mean values. It is expected that the multivariate kriging algorithm applied in this study would be effectively applied for spatial interpolation with categorical data.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.916-920
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• 2007

ADCP(Acoustic Doppler Current Profiler)는 유수의 흐름을 방해하지 않으면서 물 속으로 일정 주파수의 초음파를 전송하고, 부유하는 입자들에 의해 산란되어 돌아오는 반향을 수집, 도플러효과를 이용하여 유속을 측정하는 장비이다. ADCP는 하천을 횡단하면서 순간적인 유속을 측정하므로 시간평균한 평균유속과의 차이가 발생하지만 1초에 1회 이상의 빠른 속도로 연직유속분포를 수집하면서 이를 공간적으로 평균함으로써 순간유속이 갖는 변동성을 완화시키는 특징을 갖는다. 본 연구에서는 ADCP를 활용하여 사행하천에서 수평방향 2차원 유속분포를 측정하고자 하였다. 만곡부가 교호적으로 나타나는 사행하천의 흐름구조는 매우 복잡하다. 특히 주 흐름의 수직인 단면에 나선형의 2차류가 관찰되는데, 이는 원심력과 횡방향의 수면경사 및 난류의 상호작용으로 발생된다. 주 흐름의 유속과 다른 분포를 나타낸다. 본 연구에서는 이찬주 등(2005)이 제시한 공간평균기법과 이동경로 수정을 통하여 측선별 2차원 유속분포를 측정하여 기 개발된 RAMS(서울대학교, 2007)를 적용하고 이를 검증하기 위한 자료를 확보하고자 하였다.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.40 no.3
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• pp.28-40
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• 2011

본 논문에서는 열섬완화대책에 관한 수치목표를 설정했을 때, 각 지역에 필요 대기 열부하 삭감량과 구체기술의 필요투입량 파악을 목적으로, 대기 열부하 삭감 포텐셜과 목표설정의 관계에 대해 검토하였다. 먼저, mesoscale 기상모델에 의해 과거회귀로부터 구체적인 수치목표를 구한 결과, 열대야 DH의 필요저감량은 대판평야(大阪平野)부의 공간평균으로 $10.7^{\circ}C{\cdot}h$, 인구 중첩평균으로 $12.5^{\circ}C{\cdot}h$가 산출되었다. 또한, 필요열부하 삭감량은 대판평야부(大阪平野部) 전체에서 일률삭감시에는 공간평균으로 11.5 $W/m^2$, 인구 중첩평균으로 12.0 $W/m^2$인 한편, 열부하 삭감 포텐셜이 큰 도심부를 중심으로 삭감을 행한 지역배분조건에서는 개략적으로 같은 양의 열부하 삭감으로 목표를 달성함을 나타내었다. 대판부(大阪府)내의 어떤 시구를 대상으로, 논문에서 뽑은 각종 열섬완화대책을 도입률 100%로 실시한 경우, 목표를 달성한 시구가 존재함을 나타내었다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.208-210
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• 2001

예외자는 공간색인의 성능을 떨어뜨리는 요소가 될 수 있다. 예를 들어, R-tree 계열의 색인 방법은 예외자 때문에 MBR의 넓이나, MBR사이의 겹치는 공간이 넓어져 성능이 떨어진다. 따라서, 공간색인을 구축할 때, 적절하게 예외자를 처리하면 성능을 향상시킬 수 있다. 본 논문에서는 예외자와 공간색인의 성능과 관계를 관찰하고 적절한 방법으로 예외자를 처리하여 공간색인의 성능을 향상시키는 방법을 확인한다. 실험의 결과에 따르면, 예외자를 적절하게 처리할 경우 성능을 평균적으로 15% 향상시킬 수 있다.

• 한국해양학회지
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• v.22 no.4
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• pp.228-235
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• 1987

Based on the hydrographic data for 19 years (1968-1984) at 65 stations in the West Sea of Korea, we investigate the relationships between the sea surface temperature (SST) in winter and the bottom water temperature (BWT) in summer. The spatially-averaged anomalies of BBT are highly correlated with those of SST during the preceding winter. However, due to advection of heat by ocean currents, the spatial pattern of BWT anomaly in summer does not closely resemble that of SST anomaly in the preceding winter.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.42-55
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• 2006

We propose a single Index approach for subsequence matching that supports moving average transform of arbitrary order in time-series databases. Using the single index approach, we can reduce both storage space overhead and index maintenance overhead. Moving average transform is known to reduce the effect of noise and has been used in many areas such as econometrics since it is useful in finding overall trends. However, the previous research results have a problem of occurring index overhead both in storage space and in update maintenance since tile methods build several indexes to support arbitrary orders. In this paper, we first propose the concept of poly-order moving average transform, which uses a set of order values rather than one order value, by extending the original definition of moving average transform. That is, the poly-order transform makes a set of transformed windows from each original window since it transforms each window not for just one order value but for a set of order values. We then present theorems to formally prove the correctness of the poly-order transform based subsequence matching methods. Moreover, we propose two different subsequence matching methods supporting moving average transform of arbitrary order by applying the poly-order transform to the previous subsequence matching methods. Experimental results show that, for all the cases, the proposed methods improve performance significantly over the sequential scan. For real stock data, the proposed methods improve average performance by 22.4${\~}$33.8 times over the sequential scan. And, when comparing with the cases of building each index for all moving average orders, the proposed methods reduce the storage space required for indexes significantly by sacrificing only a little performance degradation(when we use 7 orders, the methods reduce the space by up to 1/7.0 while the performance degradation is only $9\%{\~}42\%$ on the average). In addition to the superiority in performance, index space, and index maintenance, the proposed methods have an advantage of being generalized to many sorts of other transforms including moving average transform. Therefore, we believe that our work can be widely and practically used in many sort of transform based subsequence matching methods.

• Proceedings of the KGS Conference
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• 2003.11a
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• pp.247-252
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• 2003

최근 원격탐사기법과 지리정보시스템들이 급격하게 발달하면서, 공간상의 각종 지리사상들의 시계열적인 자료들이 증가하고 있다. 일반적으로 지리학계의 관심은 특정 지리사상의 시간적인 변화(Time series analyses)와 공간상의 분포 (Spatial statistics)로 크게 대별되어 왔으며, 이 두 가지의 요인들을 종합적으로 고려하는 경우는 극히 드물다고 하겠다. (중략)