• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.139-147
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• 2009

The memory based reasoning just stores in the memory in the form of the training pattern of the representative pattern. And it classifies through the distance calculation with the test pattern. Because it uses the techniques which stores the training pattern whole in the memory or in which it replaces training patterns with the representative pattern. Due to this, the memory in which it is a lot for the other machine learning techniques is required. And as the moreover stored training pattern increases, the time required for a classification is very much required. In this paper, We propose the EAS(Evaluation And Selection) algorithm in order to minimize memory usage and to improve classification performance. After partitioning the training space, this evaluates each partitioned space as MDL and PM method. The partitioned space in which the evaluation result is most excellent makes into the representative pattern. Remainder partitioned spaces again partitions and repeat the evaluation. We verify the performance of Proposed algorithm using benchmark data sets from UCI Machine Learning Repository.

• Journal of KIISE:Databases
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• v.34 no.5
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• pp.420-436
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• 2007

The choice of an effective indexing method is crucial to guarantee the performance of the spatial join operator which is heavily used in geographical information systems. The $R^*$-tree based method is renowned as one of the most representative indexing methods. In this paper, we propose an efficient spatial join technique based on the DOT(Double Transformation) index, and compare it with the spatial Join technique based on the $R^*$-tree index. The DOT index transforms the MBR of an spatial object into a single numeric value using a space filling curve, and builds the $B^+$-tree from a set of numeric values transformed as such. The DOT index is possible to be employed as a primary index for spatial objects. The proposed spatial join technique exploits the regularities in the moving patterns of space filling curves to divide a query region into a set of maximal sub-regions within which space filling curves traverse without interruption. Such division reduces the number of spatial transformations required to perform the spatial join and thus improves the performance of join processing. The experiments with the data sets of various distributions and sizes revealed that the proposed join technique is up to three times faster than the spatial join method based on the $R^*$-tree index.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.505-509
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• 2004

본 논문에서는 비디오 스트림 서버에서 의미 기반 검색을 가능하게 하기 위하여 대용량 스트림 데이터를 효과적으로 표현하고 저장하는 기법을 제시한다. 비디오 스트림 내의 각 프레임을 다차원 공간상의 점으로 사상함으로써 비디오 스트림은 다차원 시퀀스(multidimensional sequence)로 표현되고, 이 시퀀스는 다시 비디오 세그먼트로 분할된다. 분할된 세그먼트로부터 정적인 특성과 연속된 프레임의 움직임을 나타내는 트랜드 벡터(trend vector)등의 의미 정보를 추출하여 모델링 함으로서 스트림 데이터를 효과적으로 표현한다. 또한 제안된 기법은 효율적인 검색을 위하여 비디오 세그먼트를 인덱싱하고 저장하는 방법을 제공함으로써 공간 사용의 효율성을 높이고 신속한 검색을 가능하게 한다.

• The KIPS Transactions:PartD
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• v.12D no.2 s.98
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• pp.233-246
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• 2005

To enhance the user response time of content-based retrieval service for multimedia information, several multi-dimensional index schemes have been proposed. M-tree, a well-known multidimensional index scheme is of metric space access method, and is based on the distance between objects in the metric space. However, since the overlap between index spaces of nodes might enlarge the number of nodes of M-tree accessed for query processing, the user response time for content-based multimedia information retrieval grows longer. In this paper, we propose a node split algorithm which is able to reduce the sire of overlap between index spaces of nodes in M-tree. In the proposed scheme, we choose a virtual center point as the routing object and entry redistribution as the postprocessing after node split in order to reduce the radius of index space of a node, and finally in order to reduce the overlap between the index spaces of routing nodes. From the experimental results, we can see the proposed split algorithm reduce the overlap between index space of nodes and finally enhance the user response time for similarity-based query processing.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06b
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• pp.45-50
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• 1999

이진 영상의 압축은 디지털 도서관, 팩시밀리 전송, 문서 입출력 시스템과 같이 한정된 대역폭과 저장 공간을 가진 응용 분야에서 절실히 요구되고 있다. 현재 많은 영상 압축 알고리즘이 채택하고 있는 대역분할 기법을 문서와 같은 이진 영상의 압축에 적용한다면, 점진적 전송, 축소영상을 통한 빠른 검색 등의 장점을 얻을 수 있다. 그러나, 이진 영상 신호가 두 단계의 휘도 값을 가지므로, 이에 적합한 대역분할 방법과 산술부호기를 선택하여야 한다. 본 논문에서는 표본화-XOR 대역분할 기법을 선택하여, 알파벳 수의 증가를 막고 공간영역에서 국부적인 성질을 얻을 수 있다 또한, 넓은 단일-색 영역을 Zerotree로 대표하여 부호화 되는 신호의 수를 줄이고, 대역분할 구조에서 예측성의 저하를 막기 위한 적절한 조건화문맥과 새로운 부호를 선택한다. 이진 영상에 적합한 대역분할 방법과 산술부호기를 선택하여, 대역분할의 장점과 우수한 압축 성능을 달성할 수 있다.

• Journal of the Korean Society of Radiology
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• v.12 no.1
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• pp.85-91
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• 2018

Computed tomography, which obtains section images from reconstruction process using projection images, has been applied to various fields. The spatial resolution of the reconstructed image depends on the device used in CT system, the object, and the reconstruction process. In this paper, we investigates the effect of the number of projection images and the pixel size of the detector on the spatial resolution of the reconstructed image under the parallel beam geometry. The reconstruction program was written in Visual C++, and the matrix size of the reconstructed image was $512{\times}512$. The numerical bar phantom was constructed and the Min-Max method was introduced to evaluate the spatial resolution on the reconstructed image. When the number of projections used in reconstruction process was small, artifact like streak appeared and Min-Max was also low. The Min-Max showed upper saturation when the number of projections is increased. If the pixel size of the detector is reduced to 50% of the pixel size of the reconstructed image, the reconstructed image was perfectly recovered as the original phantom and the Min-Max decreased as increasing the detector pixel size. This study will be useful in determining the detector and the accuracy of rotation stage needed to achieve the spatial resolution required in the CT system.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.471-478
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• 2013

This paper proposes a black-box based test case generation method for Simulink/Stateflow model utilizing the RRT algorithm which is a method to efficiently solve the path planning for complicated systems. The proposed method in the paper tries to solve the reachability problem with the RRT algorithm, which has to be solved for black-box based test case generations. A major problem of the RRT based test case generation algorithms is that the cost such as running time and required memory size is too much for complicated Stateflow model. The typical RRT algorithm expands rapidly-exploring random tree (RRT) in a single state space. But the proposed method expands it in dynamic state space based on the state of Simulink model, consequently reducing the cost. In the paper, a new definition of RRT state space, a distance measure and a test case generation algorithm are proposed. The performance of proposed method is verified through the experiment against Stateflow model.

• Annual Conference of KIPS
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• 2001.10a
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• pp.615-618
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• 2001

본 논문은 기존의 3D 게임 엔진에 실시간으로 상호 작용이 가능하고 3D MMORPG(Massive Multi-play Online Role flaying Game) 게임에 적합한 가상 공간을 표현하기 위한 필요한 기술을 분석하고 이를 활용하려 한다. 기존의 머드 게임에 3 차원 기술을 적용하고, 3 차원 물체를 모델링 하는데 있어서 메쉬나 버텍스, 혹은 폴리곤으로 사실적인 지형 처리와 렌드링 속도 향상을 위하여 3 차원 개체의 폴리곤을 동적으로 생성시키고 가시성 판단이나 충돌 검출을 위한 방법으로 Height field 처리 기법과 거리에 변화에 따라 다르게 모델링 된 데이터를 선택적으로 사용하는 CLOD(Continuous Level of Detail) 처리 기법과 입체 컬링 방법으로 옥트리를 이용하여 가상공간을 분해하기 위한 자료 구조로 사용한다. 거리의 변화에 따라 지형을 표현하는 vertex 들을 병합 또는 삭제함으로써 그 표현의 정도를 동적으로 달리 할 수 있는 CLOD 를 이용하여 카메라의 위치와 방향에 따라 적절한 폴리곤을 생성해 낼 수 있다. 본 논문은 기존의 3 차원 공간을 표현하기 위하여 사용되고 있는 옥트리 구조를 이용하여 공간을 분할하고, 이를 세부 수준으로 나누어 처리하기 위한 LOD(Level of Detail)와 CLOD 개념을 이용하여 외부지형을 폴리곤으로 표현하는 방법에 대한 처리 기법과 가시성 판단이나 충돌 검출을 위한 방법을 제시하려 한다.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.29-36
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• 2017

In this paper, we implement a spatial big data analysis prototype based on Spark which is an in-memory system and compares the performance by the spatial split algorithm on this basis. In cluster computing environments, big data is divided into blocks of a certain size order to balance the computing load of big data. Existing research showed that in the case of the Hadoop based spatial big data system, the split method by spatial is more effective than the general sequential split method. Hadoop based spatial data system stores raw data as it is in spatial-divided blocks. However, in the proposed Spark-based spatial analysis system, there is a difference that spatial data is converted into a memory data structure and stored in a spatial block for search efficiency. Therefore, in this paper, we propose an in-memory spatial big data prototype and a spatial split block storage method. Also, we compare the performance of existing spatial split algorithms in the proposed prototype. We presented an appropriate spatial split strategy with the Spark based big data system. In the experiment, we compared the query execution time of the spatial split algorithm, and confirmed that the BSP algorithm shows the best performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.7
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• pp.580-583
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• 2017

To compensate the degraded SAR image due to the residual errors and the spatial variant errors remaining after the motion compensation in the airborne SAR, we have introduced the autofocus method based on the partition processing. Thus, after we perform the spatial partition for the spotlight SAR data and the time partition for the stripmap SAR data, we reconstruct the subpatch images for the partitioned data. Then, we perform the local autofocus with the suitability analysis process for the phase errors estimated by the autofocus. Moreover, if the estimated phase errors are not properly compensated for the subpatch images, we perform the phase compensation method with the weight to the estimated phase error close to the degraded subpatch image to increase the SAR image quality.