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뉴스 빅 데이터를 활용한 농업용 드론 이용의 실태 분석 - 농협의 병충해 방제사업을 중심으로-
신인식 ( Shin¸ Insik ),최경식 ( Choi¸ Kyungsik ) 농협대학교 협동조합경영연구소 2020 협동조합경영연구 Vol.52 No.-
드론의 농업부문 이용실태와 빅 데이터 분석결과를 종합한 결과, 전남북·경남·충남이 타 지역보다 농업용 드론의 벼 병충해 방제사업 이용률이 높을 것으로 예측해 볼 수 있다. 뉴스 검색 키워드 농업용 드론의 검색건수와 장소 관계도 및 연관어 분석결과 2014~2015년도를 드론에 대한 인지단계로 도입기, 2016년 관심단계, 2017년 이후 관심이 증가하는 추세인데 이는 농협과 정부가 역할을 하였다고 볼 수 있다. 드론의 병충해 방제 도입 초기에는 기술센터가 시범사업추진 등으로 농업인이 인지하게 되었으며, 관심단계에서는 드론 이용확대를 위해 농협이 2015년 농기계은행 병충해 방제기에 드론을 포함하고 조합당 4천만원을 지원하는 등 적극적인 활동을 하고 있다. 농협의 드론 이용 병충해 방제사업 활성화를 위해서는 드론의 적재량을 늘리고 배터리 성능을 개선하고, 현재의 농기계이용 중심(필지 당 900평~1,200평)경지정리를 전남북 등 벼농사 중심지역을 중심으로 드론 등 4차 산업 수용이 가능한 대규모 경지정리(3만평~10만평)가 필요하다. 본 연구는 농업용 드론의 병충해 방제이용기간이 짧아 통계자료 및 기존 연구의 부족으로 심도 있는 분석이 아닌 실태분석에 그친 한계가 있다. As a result of synthesis, the status of using drones in the agricultural sector and big data analysis results show that it can be predicted that South Jeolla, North Gyeongsang, and South Chungcheong Province will have a higher utilization rate of agricultural drones' rice pest control projects than other regions. According to the analysis of the number of searches, location relations, and related terms of the news search keyword agricultural drones, 2014-2015 was the introduction of agricultural drones in the cognitive stage, 2016 was the phase of drone interest, and 2017 was when they were on the rise, which can be said to have been played by the government and agricultural cooperative. In the early days of the introduction of pest control for drones, the agricultural technology center became recognized by farmers due to the promotion of pilot projects, and in order to expand the use of drones, Nonghyup actively supports 40 million won per regional cooperative, including the drones of 2015 in the insect pest control machine at the Agricultural Machinery Bank. In order to revitalize Nonghyup’s project to control insect pests using drones, it is necessary to increase the load of drones and improve battery performance, and to provide large-scale readjustment of paddy fields (30,000 pyeong to 100,000 pyeong) that can accommodate the fourth industry, such as drones, in areas centered on rice farming, including North and South Jeolla Province. This study is limited to analyzing the actual conditions, not an in-depth analysis, due to the lack of statistical data and existing research in the short period of use of pest control for agricultural drones.
한국의료패널(KHP) 활용을 위한 Stata 패키지 개발
민인식 ( Min¸ Insik ) 경희대학교 경영연구원 2021 의료경영학연구 Vol.15 No.1
Korea Health Panel(KHP) provides detailed information on individual medical expenditure and diseases for establishing national medical policies. Since the survey conducted from 2008 to 2018 consists of more than 250 separate data files, KHP researchers spend a lot of time and effort in creating panel data for empirical analysis. In this study, we propose a Stata module with the name of “smart_khp_v3” to fill the gap between KHP raw data and the panel data for analysis. If we in advance set up a Stata command specifically working for KHP data files, we can save much time in constructing a panel data repetitively. This module has not only the advantage of a combined data set of household member + single episode, but also household member + multiple episodes panel data. We present the role of “smart_khp_v3” as an intermediate tool that can improve the quality of research by assigning more time and effort on research analysis itself rather than building panel data.
Particle identification of spectrograph focal-plane detectors using a simulation program
Insik Hahn 한국물리학회 2004 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.45 No.3
Many nuclear reactions that are currently under investigation for nuclear physics interests, as well as astrophysics reasons, usually have very small cross sections. Therefore, it is critical to optimize the detector setup due to the fact that identifying correct particles under large other background events is rather dicult. A detector simulation code DETECT was developed for focal-plane detectors for a magnetic spectrograph in order to understand the behaviors of particles produced in nuclear reactions. This program simulates a particular detector's response while varying the input parameters. The DETECT program was found to be useful in the 12C(12C,6He)18Ne and the 12C(14N,8Li)18Ne experiments and can be used for other nuclear reaction studies using focal plane detectors.