• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.175-186
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• 2003

Mobile clients like a PDA need a cache and a spatial index to search and access map data efficiently. When a server transmits spatial objects to a mobile client which has a low storage capacity, some of them can be duplicated in a cache of the mobile client. Moreover, the cost for strong added data in the cache and reconfiguring spatial index is very high in the mobile client with low computing power. The scheme for processing duplicated objects and disturbing tasks of the mobile client which has low computing power is needed. In this paper, we classfy the method for strorng duplicated objects and present the scheme for the both caching objects and reconfiguring a spatial index of cached objects using the clipping technique. We propose the caching system based on an agent in order to distribute the overhead of a mobile client as well as to provide efficiently map services. We design and implement it, and evaluate the performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.270-274
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• 2015

We suggest that HSV Color Space may be used to detect a vehicle detecting system at nighttime. It is essential that a licence plate should be extracted when a vehicle is under surveillance. To do so, a licence plate may be enlarged to certain size after the aimed vehicle is taken picture from a distance by using Pan-Tilt-Zoom Camera. Either Mean-Shift or Optical Flow Algorithm is generally used for the purpose of a vehicle detection and trace, even though those algorithms have tendency to have difficulty in detection and trace a vehicle at night. By utilizing the fact that a headlight or taillight of a vehicle stands out when an input image is converted in to HSV Color Space, we are able to achieve improvement on those algorithms for the vehicle detection and trace. In this paper, we have shown that at night, the suggested method is efficient enough to detect a vehicle 93.9% from the front and 97.7% from the back.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.67-78
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• 2008

With the rapid development of wireless communication and mobile equipment, many applications for location-based services have been emerging. Moving objects such as vehicles and ships change their positions over time. Moving objects have their moving path, called the trajectory, because they move continuously. To monitor the trajectory of moving objects in a large scale database system, an efficient Indexing scheme to processed queries related to trajectories is required. In this paper, we focus on the issues of minimizing the dead space of index structures. The Minimum Bounding Boxes (MBBs) of non-leaf nodes in trajectory-preserving indexing schemes have large amounts of dead space since trajectory preservation is achieved at the sacrifice of the spatial locality of trajectories. In this thesis, we propose entry relocating techniques to reduce dead space and overlaps in non-leaf nodes. we present performance studies that compare the proposed index schemes with the TB-tree and the R*-tree under a varying set of spatio-temporal queries.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.228-230
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• 1999

공간 인덱스를 이용한 공간 질의 처리의 과정은 여과와 정제 단계로 이뤄진다. 여과 단계에서 후보 객체의 수를 줄이며, 정제 단계에서의 false-hit이 낮아지므로 불필요한 디스크 접근과 공간연산으로 인한 질의 처리 비용의 증대를 방지할 수 있다. 본 논문에서는 여과 단계에서 후보 객체를 최소화하기 위해 DTVF가 추가된 확장 R-tree를 제안한다. 제안된 기법에서는 n차원 상에 존재하는 공간 객체의 대표 정점들을 구석점 변환 기법을 이용하여 2n차원의 점으로 변환하고, 이 값을 확장된 R-tree라는 리프 노드의 DTVF에 유지한다. 공간 질의 처리시 여과 단계에서 DTVF를 이용하면 후보 객체 수를 최소화할 수 있으며, DTVF에 유지된 차원 변환된 값을 통해 후보 객체 선정에도 빠른 성능을 나타낸다. 제안된 기법은 공간 질의 처리시 여과 효율을 극대화하여 질의 처리 성능을 향상시킨다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1307-1310
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• 2012

최근 도시화가 급격히 진행되면서 도심 공간의 효율적인 이용을 위하여 지하공간의 개발이 새로운 대안으로 주목 받고 있다. 지하공간은 일반적으로 건축 구조상 자연채광의 유입이 불가능한 구조로서 지하 거주자의 심리적, 환경적 문제를 초래하므로 이의 활성화를 위해서는 공간의 질적 제고가 선행되어야 한다. 빛과 조명은 공간의 질을 결정하는 중요한 요소로서 거주자를 위해 건강하고 편안한 환경을 제공하기 위해서는 거주자의 생체리듬과 부합하는 자연광과 유사한 광 환경(색온도, 조도) 서비스를 제공해야 한다. 본 논문은 지하공간을 대상으로 인공조명의 광 환경을 시간의 흐름에 따라 변화하는 자연의 빛과 유사하게 서비스하기 위한 LED제어시스템을 개발한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.64-65
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• 2020

With the modernization fund of the government, construction of new passenger ships make the level of interior design is improved, but the space where the crew is working is still inadequate. This study is to investigate the color environment of the Bridge Deck and Engine Room among working spaces of passenger ships. It aims to improve the mental health of crews and set up a safe working environment by presenting color design, and suggest the specificity of ship's working space and color value with matching the color environment.

• 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.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.21-26
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• 2004

Color image quantization is a process of selecting a set of colors to display an image with some representative colors without noticeable perceived difference. It is very important in many applications to display a true color image in a low cost color monitor or printer. The basic problem is how to display 256 colors or less colors, called color palette, In this paper, we propose improved binary tree vector quantization based on spatial sensitivity which is one of the human visual properties. We combine the weights based on the responsibility of human visual system according to changes of three Primary colors in blocks of images with the process of splitting nodes using eigenvector in binary tree vector quantization. The test results show that the proposed method generates the quantized images with fine color and performs better than the conventional method in terms of clustering the similar regions. Also the proposed method can get the better result in subjective quality test and WSNR.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.961-973
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• 2020

In this manuscript, a new pansharpening model based on Convolutional Neural Network (CNN) was developed. Dilated convolution, which is one of the representative convolution technologies in CNN, was applied to the model by making it deep and complex to improve the performance of the deep learning architecture. Based on the dilated convolution, the residual network is used to enhance the efficiency of training process. In addition, we consider the spatial correlation coefficient in the loss function with traditional L1 norm. We experimented with Dilated Residual Networks (DRNet), which is applied to the structure using only a panchromatic (PAN) image and using both a PAN and multispectral (MS) image. In the experiments using KOMPSAT-3A, DRNet using both a PAN and MS image tended to overfit the spectral characteristics, and DRNet using only a PAN image showed a spatial resolution improvement over existing CNN-based models.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.122-131
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• 2004

Traditional works on indexing have been suggested for low dimensional data under dynamic environments. But recent database applications require efficient processing of huge sire of high dimensional data under static environments. Thus many indexing strategies suggested especially in partitioning ones do not adapt to these new environments. In our study, we point out these facts and propose a new partitioning strategy, which complies with new applications' requirements and is derived from analysis. As a preliminary step to propose our method, we apply a packing technique on the one hand and exploit observations on the Minkowski-sum cost model on the other, under uniform data distribution. Observations predict that unbalanced partitioning strategy may be more query-efficient than balanced partitioning strategy for high dimensional data. Thus we propose our method, called CSP (Cyclic Spliced Partitioning method). Analysis on this method explicitly suggests metrics on how to partition high dimensional data. By the cost model, simulations, and experiments, we show excellent performance of our method over balanced strategy. By experimental studies on other indices and packing methods, we also show the superiority of our method.