• Journal of Multimedia Information System
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• v.4 no.4
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• pp.263-270
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• 2017

Various security threats exist in the smart grid environment due to the fact that information and communication technology are grafted onto an existing power grid. In particular, smart metering data exposes a variety of information such as users' life patterns and devices in use, and thereby serious infringement on personal information may occur. Therefore, we are in a situation where a de-identification algorithm suitable for metering data is required. Hence, this paper proposes a new de-identification method for metering data. The proposed method processes time information and numerical information as de-identification data, respectively, so that pattern information cannot be analyzed by the data. In addition, such a method has an advantage that a query such as a direct range search and aggregation processing in a database can be performed even in a de-identified state for statistical processing and availability.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.640-652
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• 2012

Many studies have investigated the smart grid architecture and communication models in the past few years. However, the communication model and architecture for a smart grid still remain unclear. Today's electric power distribution is very complex and maladapted because of the lack of efficient and cost-effective energy generation, distribution, and consumption management systems. A wireless smart grid communication system can play an important role in achieving these goals. In this paper, we describe a smart grid communication architecture in which we merge customers and distributors into a single domain. In the proposed architecture, all the home area networks, neighborhood area networks, and local electrical equipment form a local wireless mesh network (LWMN). Each device or meter can act as a source, router, or relay. The data generated in any node (device/meter) reaches the data collector via other nodes. The data collector transmits this data via the access point of a wide area network (WAN). Finally, data is transferred to the service provider or to the control center of the smart grid. We propose a wireless cooperative communication model for the LWMN.We deploy a limited number of smart relays to improve the performance of the network. A novel relay selection mechanism is also proposed to reduce the relay selection overhead. Simulation results show that our cooperative smart grid (coopSG) communication model improves the end-to-end packet delivery latency, throughput, and energy efficiency over both the Wang et al. and Niyato et al. models.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.75-78
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• 2017

This paper compares operational and network analysis of centralized and distributed repository for big data solutions in the IoT enabled Smart Grid environment. The comparative analysis clearly depicts that centralize repository consumes less memory consumption while distributed locality-based repository reduce network complexity issues than centralize repository in state-of-the-art Big Data Solution.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.2
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• pp.207-213
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• 1997

The purpose of this study is to aim at presenting efficient technique of 3-D Terrain Modelling through multilateral approach methods and to compare with raw data, using low-densed randomly located point data. The subject religion of this study are selected two sites and take into consideration for degree of freedom about low-densed randomly located point data. The result of this study by precision analysis of digital cartographic map-ping using low-densed randomly located point data bave shown that . First, making digital cartographic map, the technique of making it using low-desned randomly located point data by TIN-based results to good and fast run-time in A and B sites all together. Second, the visualization analysis results of digital cartographic map using TIN and GRID-based terrain modeling techniqus similar exacts A and B sites, but the terrain modeling techniqus by TIN-based are small data size than GRID-based with the data with the data size of saving with DXF files. Third, making digital catographic map using terrain modeling techniques by Grid-based, the standard errors of low-densed randomly located point data and interpolated data using gridding method have more good results by radial basis function interpolation techniques at A and B sites all together.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04d
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• pp.10-12
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• 2003

GridFTP는 광대역의 WAN 상에 최적화된 고성능의 안전하고 신뢰할 수 있는 데이터 전송 프로토콜이다. 본 논문에서는 다음과 같은 세가지 측면에서 GridFTP의 성능 향상을 도모하였다. 1) GridFTP 서버 측에서는 성능 향상을 위해 커먼드 파이프라이닝 기법을 제시하고, 2) GridFTP 클라이언트 측에서는 데이터 채널 재사용 기법을 제안하며. 3) GridFTP 프로토콜은 third-party maltitransfer 메커니즘을 지원하기 위하여 수정이 이루어겼다. 이러한 성능 향상 기법을 통하여 그리드 상에서 대규모 데이터의 효율적인 전송이 가능할 것으로 판단된다.

• Proceedings of the Korean Biophysical Society Conference
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• 2003.06a
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• pp.65-65
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• 2003

After many genome projects, algorithms and software to process explosively growing biological information have been developed. To process huge amount of biological information, high performance computing equipments are essential. If we use the remote resources such as computing power, storages etc., through a Grid to share the resources in the Internet environment, we will be able to obtain great efficiency to process data at a low cost. Here we present the performance improvement of the protein secondary structure prediction (PSIPred) by using the Grid platform, distributing protein sequence data on the Grid where each computer node analyzes its own part of protein sequence data to speed up the structure prediction. On the Grid, genome scale secondary structure prediction for Mycoplasma genitalium, Escherichia coli, Helicobacter pylori, Saccharomyces cerevisiae and Caenorhabditis slogans were performed and analyzed by a statistical way to show the protein structural deviation and comparison between the genomes. Experimental results show that the Grid is a viable platform to speed up the protein structure prediction and from the predicted structures.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.1103-1106
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• 2008

Data Grid is a kind of Grid computing provides the cooperative environment through the distributed data sharing, and can manage the massive data easily and efficiently. We designed and implemented Globus Toolkit4 (GT4) based database access and integration service (GDAIS). This service was implemented as Grid service for run on the GT4 which is Grid middleware. And it provides functions which are automatic registration of database in virtual organization, distributed query service, and the unified user interface. Also this system can use components which are provided from GT4. Therefore it can improve the efficiency to distribute and manage databases, can easily access and integrate of the distributed heterogeneous data in Grid environments.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.143-156
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• 2008

Grid-based PACS can provide an advanced medical information services such as remote image file transfer, collaboration, remote diagnosis, and virtual hospital. In this paper, we have implemented Grid-PACS which guarantees both storage safety and extendability for virtual large scale storage system. The experimental results showed that the virtual storage system provided more efficient and faster data transfer than the conventional PACS. The proposed Grid data management system can be utilized to improve the effectiveness of the PACS data management and transmission between medical institutions.

• Nuclear Engineering and Technology
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• v.45 no.7
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• pp.895-910
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• 2013

The reflood test data from the rod bundle heat transfer (RBHT) test facility showed that the grids in the upper portion of the rod bundle could become wet well before the arrival of the quench front and that the sizes of liquid droplets downstream of a wet grid could not be predicted by the droplet breakup models for a dry grid. To investigate the water droplet generation from a wet grid spacer, a viscous linear temporal instability model of the water sheet issuing from the trailing edge of the grid with the surrounding steam up-flow is developed in this study. The Orr-Sommerfeld equations along with appropriate boundary conditions for the flow are solved using Chebyshev series expansions and the Tau-Galerkin projection method. The effects of several physical parameters on the water sheet oscillation are studied by determining the variation of the temporal growth rate with the wavenumber. It is found that a larger relative steam velocity to water velocity has a tendency to destabilize the water sheet with increased dynamic pressure. On the other hand, a larger ratio of steam boundary layer to the half water sheet thickness has a stabilizing effect on the water sheet oscillation. Droplet diameters downstream of the spacer grid predicted by the present model are found to compare reasonably well with the data obtained at the RBHT test facility as well as with other data recently reported in the literature.

• Journal of Korean Society for Quality Management
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• v.49 no.2
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• pp.201-211
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• 2021

Purpose: This paper proposes a density adaptive grid algorithm for the k-NN regression model to reduce the computation time for large datasets without significant prediction accuracy loss. Methods: The proposed method utilizes the concept of the grid with centroid to reduce the number of reference data points so that the required computation time is much reduced. Since the grid generation process in this paper is based on quantiles of original variables, the proposed method can fully reflect the density information of the original reference data set. Results: Using five real-life datasets, the proposed k-NN regression model is compared with the original k-NN regression model. The results show that the proposed density adaptive grid-based k-NN regression model is superior to the original k-NN regression in terms of data reduction ratio and time efficiency ratio, and provides a similar prediction error if the appropriate number of grids is selected. Conclusion: The proposed density adaptive grid algorithm for the k-NN regression model is a simple and effective model which can help avoid a large loss of prediction accuracy with faster execution speed and fewer memory requirements during the testing phase.