• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.2
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• pp.99-112
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• 2013

This paper presents a subspace system identification for estimating the stiffness matrix and flexural rigidities of a shear building. System matrices are estimated by LQ decomposition and singular value decomposition from an input-output Hankel matrix. The estimated system matrices are converted into a real coordinate through similarity transformation, and the stiffness matrix is estimated from the system matrices. The accuracy and the stability of an estimated stiffness matrix depend on the size of the associated Hankel matrix. The estimation error curve of the stiffness matrix is obtained with respect to the size of a Hankel matrix using a prior finite element model of a shear building. The sizes of the Hankel matrix, which are consistent with a target accuracy level, are chosen through this curve. Among these candidate sizes of the Hankel matrix, more proper one can be determined considering the computational cost of subspace identification. The stiffness matrix and flexural rigidities are estimated using the Hankel matrix with the candidate sizes. The validity of the proposed method is demonstrated through the numerical example of a five-story shear building model with and without damage.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.4
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• pp.259-267
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• 2013

GIS-based web map service is all the more accessible to the public. Among others, location query services are most frequently utilized, which are currently restricted to only one keyword search. Although there increases the demand for the service for querying multiple keywords corresponding to sequential activities(banking, having lunch, watching movie, and other activities) in various locations POI, such service is yet to be provided. The objective of the paper is to develop the k-IPS algorithm for quickly and accurately querying multiple POIs that internet users input and locating the search outcomes on a web map. The algorithm is developed by utilizing hierarchical tree structure of $R^*$-tree indexing technique to produce overlapped geometric regions. By using recursive $R^*$-tree index based spatial join process, the performance of the current spatial join operation was improved. The performance of the algorithm is tested by applying 2, 3, and 4 multiple POIs for spatial query selected from 159 keyword set. About 90% of the test outcomes are produced within 0.1 second. The algorithm proposed in this paper is expected to be utilized for providing a variety of location-based query services, of which demand increases to conveniently support for citizens' daily activities.

• Journal of Korea Game Society
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• v.12 no.3
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• pp.69-76
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• 2012

At MMORPGs that has the numerous game users with many interactions at the same virtual world, massive loading that results in delays, resource shortages, and other such problems occur. To solve this, many developers devote research to load-balancing servers, yet due to steady and dynamic map divisions, such research is unreliable. This paper proposes a game user-oriented load balancing scheme for the load balancing of MMORPG servers. This scheme shows effectiveness at dealing with hot-spots and other gatherings of game users at specific servers compared to previous methods.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.331-342
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• 2005

In this paper, we propose an efficient watermarking algorithm using block indexing. The proposed algorithm is a novel blind watermarking scheme using the indexed watermark value based on the spread spectrum method. The watermark insertion is allocated into index value of each block after dividing original image into sub-blocks. The watermark embedded in mappinged with index values of blocks, And the mappinged blocks convert to DCT and then the PN sequence embedded to middle frequency band. Consequently the watermark is expressed by index value of sub-blocks. The watermark extracted from the correlation of between PN sequence and watermarked image. Experimental results demonstrate that the watermarked image has a good quality in terms of imperceptibility and is robust against various attacks.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.737-741
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• 2012

본 연구에서는 2011년 7월 27일 집중호우로 인한 서울시 우면산 산사태 지역을 대상으로 뿌리의 보강효과와 분포형 습윤지수를 고려한 GIS기반의 무한사면안 해석기법을 이용하여 사면안정해석을 실시하였다. 사면안정해석을 위한 지형 지질학적 매개변수는 수치지도, 정밀토양도 및 임상도(임상도와 영급도)로부터 추출하여 $10m{\times}10m$ 해상도의 공간분 포형 데이터베이스로 변환하였다. 또한, 분포형 습윤지수의 산정을 위한 비집수면적(specific catchment area)은 무한방향흐름 기법(IFD, infinity flow direction)을 이용하여 결정하였으며, 모형의 입력 강우자료는 서울시 서초와 남현 AWS의 산사태 발생초기와 종기시의 평균 일강우량을 적용하였다. 대상유역의 사면안정해석을 위해 격자별 안전률은 4개의 등급(unstable, quasi stable, moderately stable, stable)으로 구분하여 도시하였다. 산사태 발생인자별 분석결과, 무한사면안정해석기법을 이용하여 산정된 사면안전률은 사면경사에 매우 민감하게 반응하는 것으로 분석되었으며, 거주지 주변의 절개지 부근과 산지정상부근의 급경사지에서 불안정 지역이 집중적으로 분포하고 있음을 확인하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.481-489
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• 2019

Change detection, one of the main applications of multi-temporal satellite images, is an indicator that directly reflects changes in human activity. Change detection can be divided into pixel-based change detection and object-based change detection. Although pixel-based change detection is traditional method which is mostly used because of its simple algorithms and relatively easy quantitative analysis, applying this method in VHR (Very High Resolution) images cause misdetection or noise. Because of this, pixel-based change detection is less utilized in VHR images. In addition, the sensor of acquisition or geographical characteristics bring registration noise even if co-registration is conducted. Registration noise is a barrier that reduces accuracy when extracting spatial information for utilizing VHR images. In this study object-based change detection of VHR images was performed considering registration noise. In this case, object-based change detection results were derived considering various pixel-based change detection methods, and the major voting technique was applied in the process with segmentation image. The final object-based change detection result applied by the proposed method was compared its performance with other results through reference data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.293-303
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• 2011

An efficient diagonalized approximate factorization algorithm (DAF) is developed for the solution of three-dimensional incompressible viscous flows. The pressure-based, artificial compressibility (AC) method is used for calculating steady incompressible Navier-Stokes equations. The AC form of the governing equations is discretized in space using a second-order-accurate finite volume method. The present DAF method is applied to derive a second-order accurate splitting of the discrete system of equations. The primary objective of this study is to investigate the computational efficiency of the present DAF method. The solutions of the DAF method are evaluated relative to those of well-known four-stage Runge-Kutta (RK4) method for fully developed and developing laminar flows in curved square ducts and a laminar flow in a cavity. While converged solutions obtained by DAF and RK4 methods on the same computational meshes are essentially identical because of employing the same discrete schemes in space, both algorithms shows significant discrepancy in the computing efficiency. The results reveal that the DAF method requires substantially at least two times less computational time than RK4 to solve all applied flow fields. The increase in computational efficiency of the DAF methods is achieved with no increase in computational resources and coding complexity.

• The Journal of the Acoustical Society of Korea
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• v.39 no.2
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• pp.120-130
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• 2020

This paper solves the problem in underdetermined convolutive mixture by improving the disadvantages of the multichannel nonnegative matrix factorization technique widely used in blind source separation. In conventional researches based on Spatial Covariance Matrix (SCM), each element composed of values such as power gain of single channel and correlation tends to degrade the quality of the separated sources due to high variance. In this paper, level and frequency normalization is performed to effectively cluster the estimated sources. Therefore, we propose a novel SCM and an effective distance function for cluster pairs. In this paper, the proposed SCM is used for the initialization of the spatial model and used for hierarchical agglomerative clustering in the bottom-up approach. The proposed algorithm was experimented using the 'Signal Separation Evaluation Campaign 2008 development dataset'. As a result, the improvement in most of the performance indicators was confirmed by utilizing the 'Blind Source Separation Eval toolbox', an objective source separation quality verification tool, and especially the performance superiority of the typical SDR of 1 dB to 3.5 dB was verified.

• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.91-105
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• 1999

Spatial data integration using multiple geo-based data sets has been regarded as one of the primary GIS application issues. As for this issue, several integration schemes have been developed as the perspectives of mathematical geology or geo-mathematics. However, research-based approaches for statistical/quantitative assessments between integrated layer and input layers are not fully considered yet. Related to this niche point, in this study, spatial data integration using multiple geoscientific data sets by known integration algorithms was primarily performed. For spatial integration by using raster-based GIS functionality, geological, geochemical, geophysical data sets, DEM-driven data sets and remotely sensed imagery data sets from the Ogdong area were utilized for geological thematic mapping related by mineral potential mapping. In addition, statistical/quantitative information extraction with respective to relationships among used data sets and/or between each data set and integrated layer was carried out, with the scope of multiple data fusion and schematic statistical assessment methodology. As for the spatial integration scheme, certainty factor (CF) estimation and principal component analysis (PCA) were applied. However, this study was not aimed at direct comparison of both methodologies; whereas, for the statistical/quantitative assessment between integrated layer and input layers, some statistical methodologies based on contingency table were focused. Especially, for the bias reduction, jackknife technique was also applied in PCA-based spatial integration. Through the statistic analyses with respect to the integration information in this case study, new information for relationships of integrated layer and input layers was extracted. In addition, influence effects of input data sets with respect to integrated layer were assessed. This kind of approach provides a decision-making information in the viewpoint of GIS and is also exploratory data analysis in conjunction with GIS and geoscientific application, especially handing spatial integration or data fusion with complex variable data sets.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.7
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• pp.650-664
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• 2000

NOW(Network of Workstations) is considered as a platform for running parallel programs by many people. One of the fundamental problems that must be addressed to achieve good performance for parallel programs on NOW is the determination of efficient job scheduling policies. Currently most research on NOW assumes that all the workstations in the NOW have the same processing power. In this paper we consider a NOW in which workstations may have different computing power. We introduce 10 classes of space sharing-based scheduling policies that can be applied to the NOW with heterogeneous computing power. We compare the performance of these scheduling policies by using the simulator which accepts synthetically generated sequential and parallel workloads and generates the response time and waiting time of parallel jobs as performance indices of various scheduling strategies. Through the experiments the case when a parallel program is partitioned heterogeneously in proportion to the computing power of workstations is shown to have better performance than when a parallel program is partitioned into parallel processes of the same size. When the owner returns to the workstation which is executing a parallel process, the policy which just lowers the priority of the parallel process shows better performance than the one which migrates the parallel process to a new idle workstation. Among the policies which use heterogeneous partitioning and process priority lowering, the adaptive policy performed best across the wide range of inter-arrival time of parallel programs but when the load imbalance among parallel processes becomes very high, the modified adaptive policy performed better.