• 환경영향평가
• /
• 제6권2호
• /
• pp.165-180
• /
• 1997

Mitigation measures in EIS are the important factors in the effectiveness of EIS. This paper analyzed the content of mitigation measures described in the 30 EISs selected, using 7 analysis items in order to discover the degree of effectiveness of mitigation measures. 30 EISs used in this study were selected through variance maximization strategy, and the 7 analysis items were; 1) thoroughness of mitigation content, 2) quantification of mitigation content, 3) explicit description of mitigation effect, 4) likelihood of mitigation effect, 5) impacted area of mitigation effect, 6) time frame of mitigation effect, and 7) environmental impact of mitigation measures. The results showed that the effectiveness of mitigation measures in the analyzed EISs was relatively low both in the appropriateness and in the specificity. It was suggested that in order to improve the appropriateness of EIS as a decision making tool, the effect of mitigation measures, as well as the mitigation measures themselves, should be studied and described more thoroughly and specifically.

• 보존과학연구
• /
• 통권31호
• /
• pp.131-140
• /
• 2010

This study shows the comparison of chemical compositions of main component with other bronze bells after the research on the component analysis by non-destructive XRF analysis. There are shrinkage cavities caused by the shrinkage defect and pores with pollutants on Bronze Bell of Heungguksa Temple with gamma radiation images and 77.3% of copper, 8.4% of tin and 10.9% of lead were determined as the main components of it with XRF analysis The tin content of Brozen Bell of Heungguksa Temple is less than those (11~18%) of other bronze bells but the lead content of that is higher. The lead content of it shows 10.91% which is quite high while generally the lead contents of other bells were controlled lower than 2.1%. Buddhist bells have the different lead content according to the period. The lead content was low until Silla Dynasty and Unified Silla period but it has been getting higher since some point of Koryo Dynasty. It is assumed that expensive copper and tin were replaced with lead.

• Human Ecology Research
• /
• 제60권1호
• /
• pp.1-20
• /
• 2022

This paper presents a social network analysis of changes in Home Economics education content loaded on YouTube before and after the outbreak of COVID-19. From January 1, 2008 to June 30, 2021, a basic analysis was conducted of 761 Home Economics education videos loaded on YouTube, using NetMiner 4.3 to analyze important keywords and the centrality of video titles and full texts. Before COVID-19, there were 164 Home Economics education videos posted on YouTube, increasing significantly to 597 following the emergence of the pandemic. In both periods, there was more middle school content than high school content. The content in the child-family field was the most, and the main keywords were youth and family. Before COVID-19, a performance evaluation indicated that the proportion of student content was high, whereas after the outbreak of the disease, teacher content increased significantly due to the effect of distance learning. However, compared with video use, the self-expression and participation of users were lower in both periods. The centrality analysis indicated that in the title, 'family' exhibited a high degree of both centrality and eigenvector centrality over the entire period. Degree centrality of the video title was found to be high in the order of class, online, family, management, etc. after the outbreak of COVID-19, and the connection of keywords was strong overall. Eigenvector centrality indicated that career, search, life, and design were influential keywords before COVID-19, while class, youth, online, and development were influential keywords after COVID-19.

• 한국근적외분광분석학회:학술대회논문집
• /
• 한국근적외분광분석학회 2001년도 NIR-2001
• /
• pp.1528-1528
• /
• 2001

Ginseng cultivated in different country or growing condition has generally different components such as saponin and protein, and it relates to efficacy and action. Protein content assumes by nitrogen content in ginseng radix. Nitrogen content could be determined by chemical analysis such as kjeldahl or extraction methods. However, these methods require long analysis time and result environmental pollution and sample damage. In this work we investigated possibility of non-destructive determination of nitrogen content in ginseng radix using near-infrared spectroscopy. Ginseng radix, root of Panax ginseng C. A. Meyer, was studied. Total 120 samples were used in this study and it was consisted of 6 sample sets, 4, 5 and 6-year-old Korea ginseng and 7, 8 and 9-year-old China ginseng, respectively. Each sample set has 20 sample. Nigrogen content was measured by electronic analysis. NIR reflectance spectra were collected over the 1100 to 2500 nm spectral region with a InfraAlyzer 500C (Bran+Luebbe, Germany) equipped with a halogen lapmp and PbS detector and data were collected every 2 nm data point intervals. The calibration models were carried out by multiple linear regression (MLR) and partial least squares (PLS) analysis using IDAS and SESAME software. Result of electronic analysis, Korean ginseng were different mean value in nitrogen content of China ginseng. Ginseng tend to generally decrease the nitrogen content according as cultivation year is over 6 years. The MLR calibration model with 8 wavelengths using IDAS software accurately predicted nitrogen contents with correlation coefficient (R) and standard error of prediction of 0.985 and 0.855%, respectively. In case of SESAME software, the MLR calibration with 9 wavelength was selected the best calibration, R and SEP were 0.972 and 0.596%, respectively. The PLSR calibration model result in 0.969 of R and 0.630 of RMSEP. This study shows the NIR spectroscopy could be applied to determine the nitrogen content in ginseng radix with high accuracy.

• 정보관리학회지
• /
• 제31권4호
• /
• pp.49-68
• /
• 2014

본 연구의 목적은 국내 학술논문 데이터베이스에서 검색한 언어 네트워크 분석 관련 53편의 국내 학술논문들을 대상으로 하는 내용분석을 통해, 언어 네트워크 분석 방법의 기초적인 체계를 파악하기 위한 것이다. 내용분석의 범주는 분석대상의 언어 텍스트 유형, 키워드 선정 방법, 동시출현관계의 파악 방법, 네트워크의 구성 방법, 네트워크 분석도구와 분석지표의 유형이다. 분석결과로 나타난 주요 특성은 다음과 같다. 첫째, 학술논문과 인터뷰 자료를 분석대상의 언어 텍스트로 많이 사용하고 있다. 둘째, 키워드는 주로 텍스트의 본문에서 추출한 단어의 출현빈도를 사용하여 선정하고 있다. 셋째, 키워드 간 관계의 파악은 거의 동시출현빈도를 사용하고 있다. 넷째, 언어 네트워크는 단수의 네트워크보다 복수의 네트워크를 구성하고 있다. 다섯째, 네트워크 분석을 위해 NetMiner, UCINET/NetDraw, NodeXL, Pajek 등을 사용하고 있다. 여섯째, 밀도, 중심성, 하위 네트워크 등 다양한 분석지표들을 사용하고 있다. 이러한 특성들은 언어 네트워크 분석 방법의 기초적인 체계를 구성하는 데 활용할 수 있을 것이다.

• International Journal of Internet, Broadcasting and Communication
• /
• 제15권4호
• /
• pp.326-331
• /
• 2023

Korea's cultural content industry can develop into another unique tourism industry. However, since other prior studies focus on the Japanese content industry, this study identifies modern industrial trends by combining the unique characteristics of Korean content, that is, cultural content tourism, and the analysis ability of big data. The current status and direction of the cultural content tourism industry were studied by utilizing the extensive information collection and in-depth analysis capabilities of big data, and as a result, it was confirmed that the trend of the cultural content industry is related to the business aspect of cultural content, not the pure content interest of cultural content. This shows that Korean cultural contents have a strong business aspect. As a limitation, when research design was conducted using social media big data, the age, gender, etc. of the subject analyzed with unique anonymity could not be known. The Korean cultural content industry is expected to be successful in terms of business.

• 융합정보논문지
• /
• 제10권9호
• /
• pp.251-261
• /
• 2020

본 연구의 목적은 전 세계적인 한류의 열풍으로 K-beauty의 관심이 높아지고, 뷰티산업 종사자들도 유튜브 헤어미용 콘텐츠를 시청하며 최신 트랜드를 교류하고 있어 유튜브 콘텐츠의 이용동기와 신뢰도, 만족도, 지속이용의도의 관계를 살펴 보고, 향후 뷰티 종사자의 콘텐츠 소비 또는 제작 시 필요한 시사점을 제시하기 위함이다. 분석방법은 빈도분석, 요인분석, 신뢰도분석, 상관관계분석, 다중회귀분석 등을 하였고, 그 결과 콘텐츠 이용동기, 신뢰도, 만족도, 지속이용의도 간 상호 정(+)의 상관관계가 나타났고, 콘텐츠 이용동기가 유튜브 콘텐츠 만족도, 지속이용의도에 통계적 유의하게 정(+)의 영향이 나타났으며, 콘텐츠 신뢰도가 유튜브 콘텐츠 만족도와 지속이용의도에 통계적 유의하게 정(+)의 영향을 나타나는 것을 알 수 있었다. 따라서 콘텐츠에 대한 질적 향상을 통해 차별화 된 유튜브 콘텐츠 개발 및 제작으로 뷰티산업 발전에 기여할 수 있는 계기가 되길 바란다.

• 한국융합학회논문지
• /
• 제13권2호
• /
• pp.303-312
• /
• 2022

이 연구에서는 원격대학원생 콘텐츠 구성요소에 대한 중요도-수행도 분석(IPA)을 하였다. 이를 위해 J대학 원격대학원생 221명을 대상으로 온라인 설문조사를 한 결과 다음과 같은 결과를 얻었다. 첫째, 콘텐츠 구성요소의 영역별 중요도는 학습 내용, 상호작용, 교수-학습 전략, 평가의 순으로, 수행도는 교수-학습 전략, 상호작용, 평가, 학습내용의 순으로 나타났다. 둘째, 콘텐츠 구성요소 4가지 영역, 즉 학습내용, 교수-학습 전략, 상호작용, 평가 영역 모두 중요도와 수행도 간에 유의미한 차이가 있는 것으로 나타났다. 중요도-수행도 분석(IPA)은 영역별 및 항목별 두 차원에서 실시하였는데 그 결과는 다음과 같다. 학습내용은 유지관리 영역으로, 교수-학습 전략과 상호작용은 중점개선 영역으로, 평가 영역은 과잉투자 영역으로 밝혀졌다. 이 연구 결과는 원격대학원 콘텐츠의 현재를 진단하고 그에 기초하여 앞으로 개선해야 할 점이 무엇인가를 가늠하는 데 기초자료로 활용할 수 있을 것이다.

• Journal of Applied Biological Chemistry
• /
• 제66권
• /
• pp.305-310
• /
• 2023

Bandiburichodang (BDC) is a new variety of Zea mays L. Total polyphenol content (TPC) assay and quantitative analysis of ferulic acid (FA) were performed to determine the steaming, roasting conditions of BDC kernels that lead to the highest content. TPC levels increased after roasting under all conditions. TPC levels in samples steamed at 115 ℃ for 25 min were 3.157 mg/g before roasted, and increased to 3.825 and 4.739 mg/g after roasting at 160 and 200 ℃, respectively. Whether BDC kernels were roasted was relevant with TPC content. BDC kernels were extracted to perform quantitative analysis of FA. Roasting temperature affected FA content: the higher the temperature, the lower the content. BDC kernels that were steamed at 115 ℃ for 25 min had 0.178 mg/g of FA content before roasting, and levels decreased to 0.132 and 0.115 mg/g after roasting. Under different roasting conditions, FA content decreased 15 to 50%. We hypothesize that this phenomenon is due to a breakdown of phenolic compounds or cell wall disruption.

• 한국멀티미디어학회논문지
• /
• 제16권6호
• /
• pp.735-745
• /
• 2013

The emergence of Web 2.0 technologies, such as blogs and wiki, enable even naive users to easily create and share content on the Web using freely available content sharing tools. Wide availability of almost free data and promiscuous sharing of content through social networking platforms created a content borrowing phenomenon, where the same content appears (in many cases in the form of extensive quotations) in different outlets. An immediate side effect of this phenomenon is that identifying which content is re-used by whom is becoming a critical tool in social network analysis, including expert identification and analysis of information flow. Internet-scale reuse detection, however, poses extremely challenging scalability issues: considering the large size of user created data on the web, it is essential that the techniques developed for content-reuse detection should be fast and scalable. Thus, in this paper, we propose a $qSign_{lsh}$ algorithm, a mechanism for identifying multi-sentence content reuse among documents by efficiently combining sentence-level evidences. The experiment results show that $qSign_{lsh}$ significantly improves the reuse detection speed and provides high recall.