• Title/Summary/Keyword: 관계망분석

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Status and Implications of Hydrogeochemical Characterization of Deep Groundwater for Deep Geological Disposal of High-Level Radioactive Wastes in Developed Countries (고준위 방사성 폐기물 지질처분을 위한 해외 선진국의 심부 지하수 환경 연구동향 분석 및 시사점 도출)

  • Jaehoon Choi;Soonyoung Yu;SunJu Park;Junghoon Park;Seong-Taek Yun
    • Economic and Environmental Geology
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    • v.55 no.6
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    • pp.737-760
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    • 2022
  • For the geological disposal of high-level radioactive wastes (HLW), an understanding of deep subsurface environment is essential through geological, hydrogeological, geochemical, and geotechnical investigations. Although South Korea plans the geological disposal of HLW, only a few studies have been conducted for characterizing the geochemistry of deep subsurface environment. To guide the hydrogeochemical research for selecting suitable repository sites, this study overviewed the status and trends in hydrogeochemical characterization of deep groundwater for the deep geological disposal of HLW in developed countries. As a result of examining the selection process of geological disposal sites in 8 countries including USA, Canada, Finland, Sweden, France, Japan, Germany, and Switzerland, the following geochemical parameters were needed for the geochemical characterization of deep subsurface environment: major and minor elements and isotopes (e.g., 34S and 18O of SO42-, 13C and 14C of DIC, 2H and 18O of water) of both groundwater and pore water (in aquitard), fracture-filling minerals, organic materials, colloids, and oxidation-reduction indicators (e.g., Eh, Fe2+/Fe3+, H2S/SO42-, NH4+/NO3-). A suitable repository was selected based on the integrated interpretation of these geochemical data from deep subsurface. In South Korea, hydrochemical types and evolutionary patterns of deep groundwater were identified using artificial neural networks (e.g., Self-Organizing Map), and the impact of shallow groundwater mixing was evaluated based on multivariate statistics (e.g., M3 modeling). The relationship between fracture-filling minerals and groundwater chemistry also has been investigated through a reaction-path modeling. However, these previous studies in South Korea had been conducted without some important geochemical data including isotopes, oxidationreduction indicators and DOC, mainly due to the lack of available data. Therefore, a detailed geochemical investigation is required over the country to collect these hydrochemical data to select a geological disposal site based on scientific evidence.

Theoretical Study on Modeling Success Factors of Overseas Agricultural Startups (해외 농업스타트업 성공요인 모델링에 관한 이론적 고찰)

  • Jinhwan, Park;Sangsoon, Kim
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.1
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    • pp.85-106
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    • 2023
  • This study reviewed and derived the success factors of overseas agricultural startups and studied their integrated research model. Agricultural startups and general startups have in common that poor resources and infrastructure exist from a resource-based perspective after startup, but a differentiated approach from general startups is required due to the nature of the primary industry of agriculture. In this study, we approach the company internal factors (human resources/vision/distribution network capacity/capital capacity/cultivated crops/physical resources/farming technology, etc.) and external factors (agricultural infrastructure/laws/regulations/relationship with surrounding society, etc.) We tried to build a research model that can be integrated by focusing on various existing research models, success factors, and entrepreneurship. Through this, it is intended to present an integrated model that is practically helpful to business performance to entrepreneurs, business-related persons, and researchers who need an integrated understanding of agricultural startups at home and abroad. made for purpose In this paper, a standard model was established through three types (existing agricultural startup, small and medium-sized business startup, multinational company, and comprehensive approach) according to size and characteristics for modeling agricultural startup success factors. Through this, a total of 9 success factors (agricultural management, external environment, manager/founder characteristics, corporate identity, business management, organizational culture, infrastructure, commercialization capability, and sustainable growth) were derived. The implication of this study is that the success factors of agricultural startups were comprehensively presented based on 'entrepreneurship' for various domestic and foreign agricultural startup cases. By confirming the systematic categorization, a standard model for future agricultural startup success factors was presented, and as a result, a foundation was presented for systematic research and practical effectiveness of related research in the future.

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