생산투자수익률 계산방법에 대한 연구 (A Study on the Calculation of Productive Rate of Return)
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- 산업경영시스템학회지
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- 제38권3호
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- pp.95-99
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- 2015
The IRR(internal rate of return) is often used by investors for the evaluation of engineering projects. Unfortunately, it has serial flaws: (1) multiple real-valued IRRs may arise; (2) complex-valued IRRs may arise; (3) the IRR is, in special cases, incompatible with the net present value (NPV) in accept/reject decisions. The efforts of management scientists and economists in providing a reliable project rate of return have generated over the decades an immense amount of contributions aiming to solve these shortcomings. Especially, multiple internal rate of returns (IRRs) have a fatal flaw when we decide to accep it or not. To solve it, some researchers came up with external rate of returns (ERRs) such as ARR (Average Rate of Return) or MIRR (MIRR, Modified Internal Rate of Return). ARR or MIRR. will also always yield the same decision for a engineering project consistent with the NPV criterion. The ERRs are to modify the procedure for computing the rate of return by making explicit and consistent assumptions about the interest rate at which intermediate receipts from projects may be invested. This reinvestment could be either in other projects or in the outside market. However, when we use traditional ERRs, a volume of capital investment is still unclear. Alternatively, the productive rate of return (PRR) can settle these problems. Generally, a rate of return is a profit on an investment over a period of time, expressed as a proportion of the original investment. The time period is typically the life of a project. The PRR is based on the full life of the engineering project. but has been annualised to project one year. And the PRR uses the effective investment instead of the original investment. This method requires that the cash flow of an engineering project must be separated into 'investment' and 'loss' to calculate the PRR value. In this paper, we proposed a tabulated form for easy calculation of the PRR by modifing the profit and loss statement, and the cash flow statement.
Supplementation of maturation medium with additional granulosa cells has beneficial effect on in vitro maturation of bovine follicular oocytes and their subsequent cleavage and development in vitro. However, maturation system using granulosa cells have some disadvantages that collection of granulosa cells is cumbersome and metabolic activity of the cells is variable according to ovarian cycle or follicular size. We hypothesized that bovine immsture oocytes matured without granulosa cell coculture can fertilize and develop normally if the medium volume per oocyte is reduced during in vitro maturation. Immature oocytes were matured for 24 hours in a TCM199 containing 10% fetal calf serum, anterior pitultary hormone (0.02 AU /ml Antrinⓡ) and estradiol with or without granulosa cells in vitro. In Group 1, 35 to 40 oocytes were matured in a well of 4-well plastic dish containing 500
본 연구에서는 시뮬레이션을 이용하여 동맥압 파형 형태에 대한 오실로메트릭 방법을 분석하고 수축기압과 이완기압을 검출할 수 있는 새로운 알고리즘을 제시하였다. 동맥압 파형 형태에 대한 오실로메트릭 방법을 분석하고 수축기압과 이완기압을 검출할 수 있는 새로운 알고리즘을 제시하였다. 동맥압 파형 형태에 대한 오실로메트릭 방법을 분석하기 위해 동맥압 파형 형태를 쉽게 가변할 수 있는 동맥압 모델을 만들었으며, 기존의 정적인 동맥 압력-용적 지수함수 모델을 이용하여 오실로메트릭 모델의 구현 및 컴퓨터 시뮬레이션을 수행하였다. 동맥압 파형 형태와 보편화된 혈압 검출 기준인 특성비율과의 상관관계 분석을 통하여 동맥압 파형 형태와 맥압의 영향 때문에 특성비율이 수축기압과 이완기압을 결정하는 유일한 기준이 될 수 없음을 밝혔으며, 동맥압 파형 형태와 오실레이션 파형 형태의 상관관계 분석을 통하여 오실레이션 파형으로부터 동맥압 파형 형태를 추정할 수 있는 방법을 제시하였다. 최대 크기 오실레이션 파형과 동맥압 파형의 관계로부터 맥압을 구할 수 있는 맥압 표를 구성하여 수축기압과 이완기압을 검출할 수 있는 혈압 검출 알고리즘을 제시하였으며 그 결과 수축압, 이완압, 평균압의 절대편차 평균값은 각각 1.62%, 2.40%, 2.20%를 얻었다. 결론적으로 제안된 알고리즘은 정확한 혈압검출을 위한 유용 가능성을 보였다.
Purpose - Despite the importance of price, many companies do not implement pricing policies smoothly, because typical price management strategies insufficiently consider logistics efficiency and an increase in logistics costs due to logistics waste. This study attempts to examine the effect of product line pricing, which corresponds to product mix pricing, on logistics efficiency in the case of manufacturer A, and analyzes how logistics performance changes in response to these variables. Research design, data, and methodology - This study, based on the case of manufacturer A, involved research through understanding the current status, analyses, and then proposing improvement measures. Among all the products of manufacturer A, product group B was selected as the research object, and its distribution channel and line pricing were examined. As a result of simulation, for products with low loading efficiency, improvement measures such as changing the number of bags in the box were suggested, and a quantitative analysis was conducted on how these measures influence logistics costs. The TOPS program was used for the Pallet loading efficiency simulation tool in this study. To prevent products from protruding out of the pallet, the maximum measurement was set as 0.0mm, and loading efficiency was based on the pallet area, and not volume. In other words, its size (length x width) was focused upon, following the purpose of this study and, then, the results were obtained. Results - As a result of the loading efficiency simulation, when the number of bags in the box was changed for 36 products with low average loading efficiency of 73.7%, as shown in