• Smart Media Journal
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• v.9 no.3
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• pp.52-58
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• 2020

The growing global energy demand has been the motivation for innovations for improved approaches on energy trade. The involvement of new energy market players known as prosumers have also enabled Peer-to-Peer (P2P) energy trade in microgrid communities. In this paper, a novel approach to energy trading based on Hive Strategy is proposed. The strategy aims to encourage prosumers to become workers that will meet the energy demands of consumers referred to as hives. The workers are selected based on their Prosumer Ratings (PR) and are ranked from the ones with the highest PR to the lowest. Using the PR, prosumers with the best energy consumption and generation behaviors are prioritized for energy trade. To test the proposed strategy, a simulation has conducted and the results show how the energy demand of the hive is met by the workers. Furthermore, an improvement in the pay-offs and PR of the workers are observed.

• Electronics and Telecommunications Trends
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• v.35 no.6
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• pp.97-106
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• 2020

This article explains domestic and overseas technology trends as well as an energy trading architecture model that can safely execute energy power trading through blockchain in the community. There is a way to trade energy between homes as well as between homes and the public in the community, but there are currently no institutions that make this possible. However, our aim is to approach these power trading methods collectively through global technology related to blockchain. We try to solve the problems of energy trading using the blockchain technique. We discuss domestic and overseas technology trends in power trading using blockchain and introduce the power trading architecture for the community proposed by ETRI. We propose a framework that supports reliability and interoperability based on blockchain and develop scalable technology capable of supporting not only small-scale electricity trading but also medium-scale power trading.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.904-913
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• 2020

As the data volumes and complexity rapidly increase, data-intensive science handling large-scale scientific data needs to investigate new techniques for intelligent storage and data distribution over networks. Recently, Named Data Networking (NDN) and data-intensive science communities have inspired innovative changes in distribution and management for large-scale experimental data. In this article, analysis on NDN testbeds for large-scale scientific data such as climate science data and High Energy Physics (HEP) data is presented. This article is the first attempt to analyze existing NDN testbeds for large-scale scientific data. NDN testbeds for large-scale scientific data are described and discussed in terms of status, NDN-based application, and features, which are NDN testbed instance for climate science, NDN testbed instance for both climate science and HEP, and the NDN testbed in SANDIE project. Finally various issues to prevent pitfalls in NDN testbed establishment for large-scale scientific data are analyzed and discussed, which are drawn from the descriptions of NDN testbeds and features on them.

• Tunnel and Underground Space
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• v.32 no.3
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• pp.173-193
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• 2022

In this study, international standardization trend of smart mining technology was analyzed focusing on the guidelines developed by GMG (Global Mining Guidelines Group). GMG is a non-profit organization that unites the global mining community. It was established to promote mining safety, innovation and sustainability. Currently, GMG's working group consists of artificial intelligence, asset management, autonomous mining, cybersecurity, data access and usage/interoperability, the electric mine, mineral processing, underground mining, and sustainability. Guideline development projects related to smart mining technology are being conducted in artificial intelligence, autonomous mining, cybersecurity, data access and usage/interoperability, and underground mining. As of April 2022, eight types of smart mining-related guidelines have been published through pre-launch, launch, guideline definition, contents generation, technical editing/layout/final review, and voting process. It is judged that the GMG guidelines can be an important reference for the development of domestic smart mining technology standards.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.79-96
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• 2021

Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.