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홍재영(Jaeyoung Hong),천동원(Dong Won Chun) 한국세라믹학회 2019 세라미스트 Vol.22 No.4
Even though, nanoscale materials of various shapes and compositions have been synthesized in the liquid, their underlying growth and transformation mechanisms are not well understood due to a lack of analytical methods. The advent of liquid cell for transmission electron microscope (TEM) enables the direct imaging of chemical reactions that occur in liquids with nanometer resolution of the electron microscope (EM). Here, the technical development of liquid cell TEM equipment and their applications to the study of nanomaterials analysis in liquid are discussed. Also new findings discovered through liquid cell TEM studies such as nucleation & growth, coalescence process and transformation are discussed.
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Fuzzy-DEA모형을 이용한 한우비육농가 경영효율성 분석
김윤호 ( Yun Ho Kim ),천동원 ( Dong Won Chun ),박승용 ( Sung Yong Park ),이준배 ( Jun Vae Lee ) 한국농업정책학회 2011 농업경영정책연구 Vol.38 No.4
DEA(Data Envelopment Analysis) model is a methodology for performance analysis. It is a set of LP technique used to construct empirical production frontiers and evaluates the relative efficiency of DMU(Decision Making Units) with multiple inputs and outputs by given input-output data. The DEA model is particularly very useful when a form of the production function of a DMU like an cattle farm is not known. It has also advantages that can evaluate the relative efficiency by using survey real data without trying to unify or modify units for measured data, and can provide the extend of inefficiency factors of DMUs, which is especially useful information required to improve efficiency. The assumptions underlying DEA are that all the data assume the form of specific numerical value and require a consistent and/or homogeneous operating environment. However, in real world problem as cattle farms system, the input-output data may be imprecise. Another problem in the classical DEA is its low discriminating power when evaluated DMUs are insufficient or inputs-outputs are too many relative to the number of DMUs. To resolve these problems, this study take to incorporate fuzzy set theory with classical DEA. The fuzzy set theory has been proposed as a way to quantify imprecise and vague data in DEA model. Fuzzy-DEA model enables the result to have a higher discrimination, a meaningful interpretation and comparison of the efficiency among DMUs. Simultaneously, the result of DEA offer decision makers bench-marking informations that can help to transform inefficient farms into efficient farms.
ScienceON
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