메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
이철민 (서경대학교) 김재현 (서경대학교)
저널정보
한국냄새환경학회 실내환경 및 냄새 학회지 실내환경 및 냄새 학회지 제19권 제1호
발행연도
2020.1
수록면
94 - 100 (7page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
This study was conducted as a part of the research for the “Development of Big Data Analysis Techniques and AI-based Integrated Support System for Energy-Environment Management.” We collected research results on characterization of distribution of fine dust and re-analyzed using meta-analysis techniques to build “big data” with high potential for school environments. The results of prior studies on the characteristics of fine dust concentration distribution in a school environment conducted in Korea were collected and re-analyzed the results using the metaanalysis technique. In this manner, the variables that could be used to derive the independent variables needed to produce the e-coding book prior to the big data collection, were first derived. The possibility of using the data as independent variables was then evaluated. In this study, three variables: “elementary school vs. middle school vs. high school,” “general classroom vs. special classroom,” and “new classroom vs. old classroom” were evaluated for their application as major classification variables with priority. The necessity of being derived as a major classification variable was examined by testing the difference in fine dust concentration distribution in the school environment by each variable case. Results showed that “elementary school vs. middle school vs high school” and “general classroom vs. special classroom” could be used as independent variables, while “new classroom vs. old classroom” was less likely to be used as an independent variable.

목차

등록된 정보가 없습니다.

참고문헌 (22)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0