• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.341-360
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• 2012

The network topology for a wide area sensor network has to support connectivity and a prolonged lifetime for the many applications used within it. The concepts of structure and group in sociology are similar to the concept of cluster in wireless sensor networks. The clustering method is one of the preferred ways to produce a topology for reduced electrical energy consumption. We herein propose a cluster topology method based on sociological structures and concepts. The proposed sociological clustering topology (SOCT) is a method that forms a network in two phases. The first phase, which from a sociological perspective is similar to forming a state within a nation, involves using nodes with large transmission capacity to set up the global area for the cluster. The second phase, which is similar to forming a city inside the state, involves using nodes with small transmission capacity to create regional clusters inside the global cluster to provide connectivity within the network. The experimental results show that the proposed method outperforms other methods in terms of energy efficiency and network lifetime.

• Journal of Hydrogen and New Energy
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• v.33 no.5
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• pp.591-597
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• 2022

Recently, technologies for efficient power grid operation have become important due to climate change. For this reason, predicting power demand using deep learning is being considered, and it is necessary to understand the influence of characteristics of each region, industrial structure, and climate. This study analyzed the power demand of New Jersey in US, with a high urbanization rate and a large service industry, and West Virginia in US, a low urbanization rate and a large coal, energy, and chemical industries. Using recurrent neural network algorithm, the power demand from January 2020 to August 2022 was learned, and the daily and weekly power demand was predicted. In addition, the power grid operation based on the power demand forecast was discussed. Unlike previous studies that have focused on the deep learning algorithm itself, this study analyzes the regional power demand characteristics and deep learning algorithm application, and power grid operation strategy.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.4
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• pp.200-207
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• 2018

In recent, KEPCO (Korea Electric Power Corporation) faced difficulties of the DCC (distribution control center) due to the increase of field equipment and operational cost, and aging of operating staffs. In response to these changes in the DCC, KEPCO is trying to change the organization and system of the DCC. In this paper, we present a new attempt to change organization and structure of distribution control center, which was implemented by KEPCO recently. This paper is divided into three major parts. First, to examine the adequacy of the divided basis of current DCCs based on the quantity of installed electrical equipment, we analyzed the correlation between the operational history of the DCCs and the number of equipment. Through the analysis, we confirmed that there is little relationship between the number of equipment and actual workload. Second, we conducted visits and questionnaire surveys of all the DCCs to identify factors affecting the actual workload of distribution operators and then summarized the results. Third, based on this survey, a general formula for analyzing the workload of a DCC was derived, and each DCC's average annual total workload, day/night workload, and required number of personnel were calculated. Through this study, we proposed a more realistic management method of DCCs that can overcome the division criteria based on equipment quantity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4389-4411
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• 2018

High dynamic range (HDR) images are becoming pervasive due to capturing or rendering of a wider range of luminance, but their special display equipment is difficult to be popularized because of high cost and technological problem. Thus, HDR images must be adapted to the conventional display devices by applying tone mapping (TM) operation, which puts forward higher requirements for intellectual property protection of HDR images. As the robustness presents regional diversity in the low dynamic range (LDR) watermarked image after TM, which is different from the traditional watermarking technologies, a concept of watermarking activity is defined and used to distinguish the essential distinction of watermarking between LDR image and HDR image in this paper. Then, a novel robust HDR image watermarking algorithm is proposed against TM operations. Firstly, based on the hybrid processing of redundant discrete wavelet transform and singular value decomposition, the watermark is embedded by modifying the structure information of the HDR image. Distinguished from LDR image watermarking, the high embedding strength can cause more obvious distortion in the high brightness regions of HDR image than the low brightness regions. Thus, a perceptual brightness mask with low complexity is designed to improve the imperceptibility further. Experimental results show that the proposed algorithm is robust to the existing TM operations, with taking into account the imperceptibility and embedded capacity, which is superior to the current state-of-art HDR image watermarking algorithms.

• Journal of Korean Society of Forest Science
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• v.96 no.3
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• pp.235-244
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• 2007

Potentials of AR CDM project in North Korea are assessed and feasible land area for AR CDM project is estimated. According to our estimation, There could be 515,000 hectares of forest lands deforested before 1990 in North Korea and 8,854 hectares at the regional level of Gae-sung City, which are eligible for AR CDM project, based on researches of satellite image analyses conducted from 1980's to 1990's. A baseline scenario assumed 44.73 tones of carbon stored in soil per hectare with no vegetation above ground remained during the project period following the default value of IPCC's Good Practice Guidance for LULUCF considering soil structure, climate and land use of the project area. The scenario also assumes that black rocust (Robinia pseudoacacia) is planted and the CDM project is implemented for 20 years. The costs for producing greenhouse gases CER (certified emission reduction) credits include costs of tree planting and forest management, and costs of project negotiation and transactions for issuing the credits. It is estimated that 376 tones of carbon dioxide per hectare can be accumulated and 503 temporary CER credits per hectare and 265 long-term CER credits per hectare could be produced during the project period. It is estimated to cost US$ 4.04 and US$ 7.67 to provide one unit of temporary credit and long-term credit, respectively. These values can be regarded as the cost of conferring emission commitment of a country or a private entity. However, it is not clear which option is better economically because the replacement periods are different in these two cases.