• Journal of KIISE
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• v.43 no.3
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• pp.304-313
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• 2016

We present a novel memory-efficient parallel ray casting algorithm for unstructured grid volume rendering on multi-core CPUs. Our method is based on the Bunyk ray casting algorithm. To solve the high memory overhead problem of the Bunyk algorithm, we allocate a fixed size local buffer for each thread and the local buffers contain information of recently visited faces. The stored information is used by other rays or replaced by other face's information. To improve the utilization of local buffers, we propose an image-plane based ray grouping algorithm that makes ray groups have high coherency. The ray groups are then distributed to computing threads and each thread processes the given groups independently. We also propose a novel hash function that uses the index of faces as keys for calculating the buffer index each face will use to store the information. To see the benefits of our method, we applied it to three unstructured grid datasets with different sizes and measured the performance. We found that our method requires just 6% of the memory space compared with the Bunyk algorithm for storing face information. Also it shows compatible performance with the Bunyk algorithm even though it uses less memory. In addition, our method achieves up to 22% higher performance for a large-scale unstructured grid dataset with less memory than Bunyk algorithm. These results show the robustness and efficiency of our method and it demonstrates that our method is suitable to volume rendering for a large-scale unstructured grid dataset.

• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.35-48
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• 2008

In this paper, we propose a Dynamic Heuristic to reduce the number of node accesses and improve quality of path in the client-based navigation service. The Dynamic Heuristic is to use heuristic data from server that is calculated with traffic data. The server-based navigation service provides a path searched on server and transmits it to client, but we propose that server only provide heuristic data to client. The proposed client searches a path with heuristic transmitted data from server. We present a new algorithm for using Dynamic Heuristic in the path-finding. The algorithm bases Grid Based Path-Finding, and has minimum speed data of edges in grid. It removes several grids whose minimum speed is less than limited speed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.22-27
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• 2012

Correct and fast detection of a micro-grid (MG) islanding is essential to the MG since operation, control and protection of the MG depend on an operating mode i.e., an interconnected mode or an islanding mode. When islanding occurs, the frequency of the point of common coupling (PCC) is not the nominal frequency during the transient state owing to the frequency rise or drop of generators in the MG. Thus, the active and reactive power calculated by the frequency domain based method such as Fourier Transform might contain some errors. This paper proposes an islanding detection algorithm for the MG based on the instantaneous active and reactive powers delivered to the dedicated line in the time domain. During the islanding mode, the instantaneous active and reactive powers delivered to the dedicated line are constants, which depend on the voltage of the PCC and the impedance of the dedicated line. In this paper, the instantaneous active and reactive powers are calculated in the time domain and used to detect islanding. The performance of the proposed algorithm is verified under various scenarios including islanding conditions, fault conditions and load variation using the PSCAD/EMTDC simulator. The results indicate that the algorithm successfully detects islanding for the MG.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.76-81
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• 2015

Research on top-k query processing algorithms for analyzing big data have been spotlighted recently. However, because existing top-k query processing algorithms do not provide an efficient index structure, they incur high query processing costs and cannot support various types of queries. To solve these problems, we propose a top-k query processing algorithm using a view selection method based on a grid index. The proposed algorithm reduces the query processing time by retrieving the minimum number of grid cells for the query range, by using a grid index-based view selection method. Finally, we show from our performance analysis that the proposed scheme outperforms an existing scheme, in terms of both query processing time and query result accuracy.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.3
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• pp.127-137
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• 2010

As large-scale computational applications in various scientific domains have been utilized over many integrated sets of grid computing resources, the difficulty of their execution management and control has been increased. It is beneficial to refer job history generated from many application executions, in order to identify application‘s characteristics and to decide selection policies of grid resource meaningfully. In this paper, we apply a statistical technique, Plackett-Burman design with fold-over (PBDF), for analyzing grid environments and execution history of applications. PBDF design identifies main factors in grid environments and applications, ranks based on how much they affect to their execution time. The effective factors are used for selecting reference job profiles and then preferable resource based on the reference profiles is chosen. An application is performed on the selected resource and its execution result is added to job history. Factor's credit is adjusted according to the actual execution time. For a proof-of-concept, we analyzed job history from an aerospace research grid system to get characteristics of grid resource and applications. We built JARS algorithm and simulated the algorithm with the analyzed job history. The simulation result shows good reliability and considerable performance in grid environment with frequently crashed resources.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.81-89
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• 2010

Biological data mining has been noticed as an issue as the volume of biological data is increasing extremely. Grid technology can share and utilize computing data and resources. In this paper, we propose a hybrid system that combines biological data mining with grid technology. Especially, we propose a decision range adjustment algorithm for processing efficiency of biological data mining. We obtain a reliable data mining recognition rate automatically and rapidly through this algorithm. And communication loads and resource allocation are key issues in grid environment because the resources are geographically distributed and interacted with themselves. Therefore, we propose a dynamic load balancing algorithm and apply it to the grid-based biological data mining method. For performance evaluation, we measure average processing time, average communication time, and average resource utilization. Experimental results show that this method provides many advantages in aspects of processing time and cost.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.04a
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• pp.129-133
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• 2000

It is reasonable to use the stereo vision and image processing technique to digitize 3D coordinates of grid points and to evaluate surface strains on a sheet metal parts. However this method has its intrinsic problems such as the difficulty in enhancement of bad images inevitable error due to digital image resolution of camera and frame grabber unreliability of strains and thickness evaluated from coarse grid on the corner area with large curvature and the limitation of the area that can be measured at a time. Therefore it is still hard to measure strain distribution over the entire surface of a medium,- or large-sized stamped part at a time even by using an automated strain measurement system. In this study the curvature correction algorithm based on the grid refinement and the geometry assembling algorithm based on the global error minimization (GEM) scheme are suggested. Several applications are presented to show the reliability and efficiency of these algorithms.

• ETRI Journal
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• v.32 no.4
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• pp.555-565
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• 2010

Parallel simulation is an efficient way to cope with long runtimes and high computational requirements in simulations of modern complex integrated electronic circuits and systems. This paper presents an algorithm for parallel simulation based on parallelization in equation formulation and simultaneous calculation of matrix contributions for nonlinear analog elements. In addition, the paper describes the development of a grid interface for a parallel simulator that enables a designer to perform simulations on distant computer clusters. Performances of the developed parallel simulation algorithm are evaluated by simulation of a microelectromechanical system.

• Journal of KIBIM
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• v.10 no.4
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• pp.32-39
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• 2020

In recent years, the construction industry is getting bigger and more complex, so it is becoming difficult to acquire point cloud data for construction equipments and workers. Point cloud data is measured using a drone and MMS(Mobile Mapping System), and the collected point cloud data is used to create a 3D digital map. In particular, the construction site is located at outdoors and there are many irregular terrains, making it difficult to collect point cloud data. For these reasons, adopting a noise reduction algorithm suitable for the characteristics of the construction industry can affect the improvement of the analysis accuracy of digital maps. This is related to various environments and variables of the construction site. Therefore, this study reviewed and analyzed the existing research and techniques on the noise reduction algorithm. And based on the results of literature review, performance evaluation of major noise reduction algorithms was conducted for digital maps of construction sites. As a result of the performance evaluation in this study, the voxel grid algorithm showed relatively less execution time than the statistical outlier removal algorithm. In addition, analysis results in slope, space, and earth walls of the construction site digital map showed that the voxel grid algorithm was relatively superior to the statistical outlier removal algorithm and that the noise removal performance of voxel grid algorithm was superior and the object preservation ability was also superior. In the future, based on the results reviewed through the performance evaluation of the noise reduction algorithm of this study, we will develop a noise reduction algorithm for 3D point cloud data that reflects the characteristics of the construction site.

• ETRI Journal
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• v.30 no.6
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• pp.853-855
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• 2008

This paper presents an energy-efficient spatial join algorithm for multiple sensor networks employing a spatial semijoin strategy. For optimization of the algorithm, we propose a GR-tree index and a grid-ID-based spatial approximation method, which are unique to sensor networks. The GR-tree is a distributed spatial index over the sensor nodes, which efficiently prunes away the nodes that will not participate in a spatial join result. The grid-ID-based approximation provides great reduction in communication cost by approximating many spatial objects in simpler forms. Our experiments demonstrate that the algorithm outperforms existing methods in reducing energy consumption at the nodes.