• 산업경영시스템학회지
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• 제21권45호
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• pp.201-213
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• 1998

We address the problem of choosing the most economic mean value for an automatic filling operation on a production line through the sampling inspection. If quality characteristic of a unit is less than inspection specification then the goods is not accepted. Otherwise, it is accepted. The lots that the numbers of non-conforming units in a sample are larger than the allowable number of non-conforming units are rejected. The non-conforming units in the rejected lots are separated by the screening inspection. The non-conforming units separated are sold in discount price. We assume that quality characteristic is larger-the-better characteristic, the distribution of quality characteristic is normal distribution, and the standard deviation of the distribution is known. This paper presents total expected profit function model considering sales revenue, inspection costs, and material costs. The manufacturing process mean value maximizing total expected profit is determined, and the results of the process target value and total expected profit is analyzed as coefficients change.

• 대한전자공학회논문지SP
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• 제48권4호
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• pp.21-29
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• 2011

사전에 정의된 피부 색상 정보를 이용한 기존 피부 검출 방법들은 배경과 피부 영역을 분할하는 단계에서 사용되는 임계값을 실험을 통하여 주관적 관점에서 결정하였다. 또한 기존 방법들은 배경 환경과 조명 환경에 따라 각각 다른 임계값을 설정하였다. 이러한 기존 방법들은 반복 실험을 통하여 추정된 임계값에 따라 성능이 좌우되는 단점이 제시되었다. 제시된 기존 방법들의 단점을 극복하기 위하여 본 논문은 mean shift 알고리즘 기반의 히스토그램 근사화를 이용한 피부 영역 검출 방법을 제안한다. 제안하는 방법은 CbCr 컬러공간에서의 표준 피부색상과 유사도를 비교하여 생성된 입력 영상의 피부맵(skin-map)의 히스토그램에서 mean shift 방법을 이용하여 각각 밝기 영역별로 수렴하는 극대점을 능동적으로 찾아서 배경 영역과 피부영역으로 분할한다. 히스토그램은 픽셀의 명도값에 따라 누적되는 불연속 함수의 형태를 가지므로 베이지 곡선(Bezier curve) 기법을 이용하여 연속 가우시안 함수로 근사화된다. 따라서 제안하는 방법은 기존 방법에서처럼 수동적으로 임계값을 설정하는 방법을 사용하지 않고 mean shift 기법을 이용하여 능동적으로 영역 분할점인 극대점을 찾아서 피부 영역을 검출한다. 제안된 방법은 실험을 통하여 강인하고 효율적으로 피부 영역을 검출하였다.

• 대한산업공학회지
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• 제29권2호
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• pp.126-134
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• 2003

Among a variety of models proposed by so far to calculate the real options value when the investment decision about the underlying project may be delayed, the Black-Scholes and the binomial lattice models have been widely used and discussed by academics and practitioners. However these two models do not provide us with intuition into how it is constructed and what it does really mean. In this paper, we will therefore explore its components and practically more intuitive meaning. With the components explored, we developed the mathematical model to calculate the real options value and thus strategic net present value, based on the opportunity cost concept, for which the investment decision about the underlying project is postponed by one year. We will finally present a short illustrative example for readers better understanding on the model proposed in the paper.

• 품질경영학회지
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• 제26권3호
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• pp.141-149
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• 1998

It is of great practical interest to decide when to stop testing a software system in the development phase and transfer it to the user. This decision problemcalled an optimal software release one is discussed to specify the a, pp.opriate release time. In almost all studies, the software reliability models used are nonphomogenous Poisson process(NHPP) model with bounded mean value function. HNPP models with unbounded mean value function are more suitable in practice because of the possibility of introducing new faults when correcting or modifying the software. We discuss optimal software release policies which minimize a total average software cost under the constraint of satisfying a software reliability requirement. A numerical example illustrates the results.

• 경영과학
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• 제15권1호
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• pp.33-47
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• 1998

The facility location problem considered here is to determine facility location sites under future's uncertain demand. The objective of this paper is to propose a solution method and algorithm for a two-stage stochastic facility location problem. utilizing the Benders decomposition method. As a two-stage stochastic facility location problem is a large-scale and complex to solve, it is usually attempted to use a mean value problem rather than using a stochastic problem. Thus, the other objective is to study the relative error of objective function values between a stochastic problem and a mean value problem. The simulation result shows that the relative error of objective function values between two problems is relatively small, when a feasibility constraint is added to a facility location model.

• 반도체디스플레이기술학회지
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• 제10권2호
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• pp.97-102
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• 2011

Lots of 2D vision algorithms have been applied for inspection. However, these 2D vision algorithms have limitation in inspection applications which require 3D information data such as the height of semiconductor chips. Stereo vision is a well known method to measure the distance from the camera to the object to be measured. But it is difficult to apply for inspection directly because of its measurement error. In this paper, we propose two adjustment methods to reduce the error of the measured height data for stereo vision. The weight value based model is used to minimize the mean squared error. The average value based model is used with simple concept to reduce the measured error. The effect of these algorithms has been proved through the experiments which measure the height of semiconductor chips.

• 한국자동차공학회논문집
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• 제24권1호
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• pp.74-81
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• 2016

The aim of this study was to find the initial design value of turbine blade for electrical type turbocompound system generating 10 kW. Turbocompound is one of the waste heat recovery system applying to internal combustion engine to recover exhaust gas energy that was about 30 % of total input energy. To design the turbine blade, 1-D mean line flow model was used. Exhaust gas temperature, pressure, flow rate and turbine rotating speed was fixed as primary boundary conditions. The velocity triangles was defined and used to determine the rotor inlet radius and width, the rotor outlet radius at shroud and radius at hub, the rotor flow angles and the number of blades.

• 수산해양기술연구
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• 제34권2호
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• pp.174-184
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• 1998

In order to accumulate fundamental. data for control of fishes’ behavior at the real fishing ground, the fitness of the numerical model for describing the behavior of fishes was examined by the marine fish. Mullet, Mugil cephalus were used as experimental fishes. The numerical model of fishes’ behavior presented in our earlier paper was modified on the vertical movement of fish school. For the comparision of parameters of the modified numerical model between mullet and rainbow trout, the estimated values of parameters were identified with dimension. The fitness of the modified numerical model was examined by the comparision between experiment and simulation on the several indexes represented by fishes’ swimming characteristics. The obtained result are summarized a follows : 1. The non-dimensional parameter a’ of propulsive force and kb’ of interactive force by the experiment without model net showed a similarity, but the non-dimensional parameter k sub(c’) of schooling force for rainbow trout was lager than one for mullet and the non-dimensional parameter k sub(w’) of repulsive force for mullet was lager than one for rainbow trout. 2. The non-dimensional parameter a’ and k sub(b’) for rainbow trout by the experiment with model net were a little lager than ones for mullet, but non-dimensional parameter k sub(c’) and k sub(w’) for mullet were lager than ones for rainbow trout. 3. The non-dimensional parameter k sub(c’) and k sub(b’) showed the largest and the smallest value among the non-dimensional parameters for rainbow trout and mullet, respectively. 4. The fitness of the modified numerical model was confirmed by means of the compulsion between experiment and simulation on the swimming trajectory of fishes, the mean distance of individual from wall, the mean swimming speed, the mean swimming depth and the mean distance between the nearest individuals. Especially, the similarity of mean swimming depth was improved by using the modified numerical model.

• 산업경영시스템학회지
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• 제39권1호
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• pp.64-72
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• 2016

In this paper, we utilize a Gaussian process to predict the power consumption in the air-conditioning system. As the power consumption in the air-conditioning system takes a form of a time-series and the prediction of the power consumption becomes very important from the perspective of the efficient energy management, it is worth to investigate the time-series model for the prediction of the power consumption. To this end, we apply the Gaussian process to predict the power consumption, in which the Gaussian process provides a prior probability to every possible function and higher probabilities are given to functions that are more likely consistent with the empirical data. We also discuss how to estimate the hyper-parameters, which are parameters in the covariance function of the Gaussian process model. We estimated the hyper-parameters with two different methods (marginal likelihood and leave-one-out cross validation) and obtained a model that pertinently describes the data and the results are more or less independent of the estimation method of hyper-parameters. We validated the prediction results by the error analysis of the mean relative error and the mean absolute error. The mean relative error analysis showed that about 3.4% of the predicted value came from the error, and the mean absolute error analysis confirmed that the error in within the standard deviation of the predicted value. We also adopt the non-parametric Wilcoxon's sign-rank test to assess the fitness of the proposed model and found that the null hypothesis of uniformity was accepted under the significance level of 5%. These results can be applied to a more elaborate control of the power consumption in the air-conditioning system.

• 재무관리연구
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• 제24권3호
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• pp.133-152
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• 2007

손실기피(limited down side risk) 선호를 가진 투자자의 경우 통상적으로 사용하는 위험도의 척도인 분산 혹은 표준편차 대신에 하방 위험성에 더 관심을 가지게 되는데, 이러한 경우 평균-VaR 모형이 평균-분산 모형보다 더 적합한 모형일 수 있다. 이 논문에서는 두 모형을 이용하여 최적자산배분 문제를 실증분석하고 그 결과의 차이를 비교하였다. 수익률의 분포에 정규분포 가정이 아닌 두터운 꼬리(fat tail) 분포 가정을 도입하여 극단적인 위험을 고려한 최적자산배분 문제를 분석을 하였다. 각 이론이나 가정들의 강건성(robustness)을 살펴보기 위하여 역사적 분포를 이용한 분석을 비교 기준으로 하였다. 경험적 혹은 역사적 분포를 이용한 분석을 통해서, 극단적인 위험을 고려하는 손실기피적인 선호체계에서의 최적화 행위는 정규분포의 가정이나 평균-분산 모형이 적절하지 않은 것으로 확인되었다. 일상적인 수준을 능가하는 극단적인 손실 위험성을 고려하기에 적합한 모형은 수익률의 두터운 꼬리를 반영하는 분포 가정에 기초한 평균-VaR 모형인 것으로 나타났다.