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김기성,강통삼,민병용,임상동,박동준 한국낙농학회 1990 韓國酪農學會誌 Vol.12 No.3
계절의 변화 및 열처리방법의 차이에 따른 국산시유의 품질조사를 위해서 1989 년 1 월부터 12 월까지 매주 6가지 시유제품을 수거하여 분석한 결과는 다음과 같다. 1. 국산시유의 연평균 비중, pH 및 적정산도는 각각 1.0324, 6.66 및 0.167%였다. 2. 여름 제품의 pH가 다른 계절에 비하여 약간 높았으나 비중과 적정산도는 연중 큰 변화가 없었다. 3. 각 제품사이에 주목할 만한 차이는 나타나지 않았다. Studies were conducted to investigate the quality changes of market milk products by the season and the process of heat treatment. Market milks from 6 dairy processing companies were tested for their physicochemical properties every week from Jan. to Dec. in 1989. The results obtained were summarized as follows; 1. Average values of specific gravity, pH and titratable acidity of market milk products were 1.0324, 6.66 and 0.167%, respectively. 2. Specific gravity and titratable acidity of market milk products had little differences throughout the year, whereas pH of market milk products in summer showed a little higher value than that of other seasons. 3. Differences of physicochemical properties among 6 market milk products were not detected.
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생성집합을 이용한 다 기간 성과평가를 위한 DEA 모델 개발 및 공학교육혁신사업 사례적용
김기성,이태한 한국산업경영시스템학회 2022 한국산업경영시스템학회지 Vol.45 No.3
DEA(data envelopment analysis) is a technique for evaluation of relative efficiency of decision making units (DMUs) that have multiple input and output. A DEA model measures the efficiency of a DMU by the relative position of the DMU’s input and output in the production possibility set defined by the input and output of the DMUs being compared. In this paper, we proposed several DEA models measuring the multi-period efficiency of a DMU. First, we defined the input and output data that make a production possibility set as the spanning set. We proposed several spanning sets containing input and output of entire periods for measuring the multi-period efficiency of a DMU. We defined the production possibility sets with the proposed spanning sets and gave DEA models under the production possibility sets. Some models measure the efficiency score of each period of a DMU and others measure the integrated efficiency score of the DMU over the entire period. For the test, we applied the models to the sample data set from a long term university student training project. The results show that the suggested models may have the better discrimination power than CCR based results while the ranking of DMUs is not different.
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