• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1510-1532
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• 2017

In smart grid, privacy implications to individuals and their families are an important issue because of the fine-grained usage data collection. Wireless communications are utilized by many utility companies to obtain information. Network coding is exploited in smart grids, to enhance network performance in terms of throughput, delay, robustness, and energy consumption. However, random linear network coding introduces a new challenge for privacy preserving due to the encoding of data and updating of coefficients in forwarder nodes. We propose a distributed privacy preserving scheme for random linear network coding in smart grid that considers the converged flows character of the smart grid and exploits a homomorphic encryption function to decrease the complexities in the forwarder node. It offers a data confidentiality privacy preserving feature, which can efficiently thwart traffic analysis. The data of the packet is encrypted and the tag of the packet is encrypted by a homomorphic encryption function. The forwarder node random linearly codes the encrypted data and directly processes the cryptotext tags based on the homomorphism feature. Extensive security analysis and performance evaluations demonstrate the validity and efficiency of the proposed scheme.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.64-73
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• 2015

Recent emergence of spatial big data attracts the attention of various research groups. This paper analyzes the research trend on spatial big data by text mining the related Scopus DB. We apply topic model and network analysis to the extracted abstracts of articles related to spatial big data. It was observed that optics, astronomy, and computer science are the major areas of spatial big data analysis. The major topics discovered from the articles are related to mobile/cloud/smart service of spatial big data in urban setting. Trends of discovered topics are provided over periods along with the results of topic network. We expect that uncovered areas of spatial big data research can be further explored.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.162-168
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• 2023

As the old saying goes "a picture is worth a thousand words" data visualization is essential in almost every industry. Companies make Data-driven decisions and gain insights from visual data. However, there is a need to investigate the role of data visualization in human resource management. This review aims to highlight the power of data visualization in the field of human resources. In addition, visualize the latest trends in the research area of human resource and data visualization by conducting a bibliometric analysis. The study adopted a literature review on recent publications from 2017 to 2022 to address research questions.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.11 no.3
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• pp.281-291
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• 1999

A computer code based on a node equation method has been developed for the analysis of pipe network. Both data structure and object-oriented programming technique are used for pipe and node modelling, in which simplification process is applied to complicated and large pipe network. The semi-direct solver, ILU-CGS, improves greatly both the accuracy and the rate of convergence. The computational result of high-pressure pipe network of city gas in Taegu shows the good agreement with the real data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1842-1848
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• 2009

This paper summarizes a data modeling for developing the baseline network analysis software of the Korean energy management system (EMS). The study is concentrated on the following aspects. First, the data for operating the each application software are extracted. Some of the EMS network application softwares are selected for basis model. Those are based on the logical functions of each software and are not considered the other softwares. Second, the common data are extracted for equipment model and topological structure of power system in Korea. We propose the application common model(ACM) that can be applied whole EMS network application softwares. The ACM model includes the hierarchy and non-hierarchy power system structure, and is connected each other using the direct and indirect link. Proposed database model is tested using the Korea Electric Power Corporation(KEPCO) system. The real time SCADA data are provided for the test. Through the test, we verified that the proposed database structure can be effectively used to accomplish the Korean EMS system.

• Journal of Korea Technology Innovation Society
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• v.3 no.3
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• pp.36-52
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• 2000

This study takes an issue of efficiency analysis in the presence of network effect utilizing the DEA (Data Envelopment Analysis) framework. Network effect has important policy implication for the regulation of local monopolies which undertake their business through physical network, such as electricity, natural gas, local telephony, etc. If the difference in spatial condition between companies is not controlled properly, the performance comparison and associated incentive regulation bear significant bias. In this study, we propose a methodology to measure the true managerial or technical efficiency apart from efficiency difference accruing from the difference in spatial condition. A series of modified DEA efficiency models are combined to investigate the extent of exogenous and endogenous efficiency component in the Korean natural gas distribution companies. Empirical results show that the network effect plays significant role in determining superficial performance difference.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.443-451
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• 2024

The purpose of this study is to comprehend the knowledge structure of data scholarship within data journals and repositories. The study explored various aspects, including types of peer review, co-occurrence analysis through author keywords, and network analysis via article titles. The majority of data repositories in the DCI are maintained by countries in North America and the European Union. In Korea, data repositories are predominantly managed by research institutions. This study contributes to enhancing our understanding of the practices in data scholarship.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.525-544
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• 2017

With the advent of the big data era, the interest in the development of land using traffic data has increased significantly. However, the current research on traffic big data lingers around organizing or calibrating the data only. In this research, a novel method for discovering the hidden values within the traffic data through data mining is proposed. Considering the fact that traffic data and network structures have similarities, network analysis algorithms are used to find valuable information in the actual traffic volume data. The PageRank and HITS algorithms are then employed to find the centralities. While conventional methods present centralities based on uncomplicated traffic volume data, the proposed method provides more reasonable centrality locations through network analysis. Since the centrality locations that we have found carry detailed spatiotemporal characteristics, such information can be used as an objective basis for making policy decisions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.91-97
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• 2019

In automatic map generalization, the formalization of cartographic principles is important. This study proposes and evaluates the selection method for road network generalization that analyzes existing maps using reverse engineering and formalizes the selection rules for the road network. Existing maps with a 1:5,000 scale and a 1:25,000 scale are compared, and the criteria for selection of the road network data and the relative importance of each network object are determined and analyzed using $T{\ddot{o}}pfer^{\prime}s$ Radical Law as well as the logistic regression model. The selection model derived from the analysis result is applied to the test data, and road network data for the 1:25,000 scale map are generated from the digital topographic map on a 1:5,000 scale. The selected road network is compared with the existing road network data on the 1:25,000 scale for a qualitative and quantitative evaluation. The result indicates that more than 80% of road objects are matched to existing data.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.643-647
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• 2021

The use of data analysis on large volumes of data constitutes a challenge for deducting knowledge and new information. Data can be heterogeneous and complex: Semi-structured data (Example: XML), Data from social networks (Example: Tweets) and Factual data (Example: Spreading of Covid-19). In this paper, we propose a generic multidimensional model in order to analyze complex data, according to several dimensions.