• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.119-130
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• 1997

In this paper, we analyze quality loss function(QLF) of Taguchi. Taguchi method of QLF gives more advanced measure process capability than classic capacity(i.e. Cp). We first discuss of QLF and Cp and give one good example of QLF. Because of simplicity of QLF, it is not good fit to a, pp.y in the real field. We suggest interval quantity-loss cost function and total loss cost(TLC) which modify QLF. Also we give one example which can be obtained in the real field.

• Journal of Korean Society for Quality Management
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• v.21 no.1
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• pp.199-213
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• 1993

The function-cost matrix table is not constant, but can be changed by many factors including equipment capacity, level of production technique, fluctuation of production volume, and the continuous development of products. Such changes would give the VE analysists additional work burden. By using computer. in this study, much of the time and effort of the function evaluation could be saved, and the efficiency of the analysis could also be enhanced. The application of the function evaluation data of R Company, as a case analysis, to the function evaluation computer program developed in this study resulted in the faster management of function-cost matrix table and function evaluation.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.59-64
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• 2022

Existing edge discovery techniques only found edges of defined shapes based on precise definitions of edges. Therefore, there are many limitations in finding edges for images of complex and diverse shapes that exist in the real world. A method for solving these problems and discovering various types of edges is a cost minimization method. In this method, the cost function and cost factor are defined and used. This cost function calculates the cost of the candidate edge model generated according to the candidate edge generation strategy. If a satisfactory result is obtained, the corresponding candidate edge model becomes the edge for the image. In this study, a new candidate edge generation strategy was proposed to discover edges for images of more diverse shapes in order to improve the disadvantage of only finding edges of a defined shape, which is a problem of the cost minimization method. In addition, the contents of improvement were confirmed through a simple simulation that reflected these points.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.62-70
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• 2020

As an effective means of price discrimination, some suppliers offer trade credit to the distributors in order to stimulate the demand for the product they produce. The availability of the delay in payments from the supplier enables discount of the distributor's selling price from a wider range of the price option in anticipation of increased customer's demand. Since the distributor's lot-size is affected by the demand for the customer, the distributor's lot-size and the selling price determination problem is interdependent and must be solved at the same time. Also, in many common business transactions, the distributor pays the shipping cost for the order and hence, the distributor's ordering cost consists of a fixed ordering cost and the shipping cost that depend on the order quantity. In this regard, we deal with the joint lot-size and price determination problem when the supplier allows delay in payments for an order of a product. The positive effects of credit transactions can be integrated into the EOQ (economic order quantity) model through the consideration of retailing situations, where the customer's demand is a function of the distributor's selling price. It is also assumed that the distributor's order cost consists of a fixed ordering cost and the variable shipping cost. We formulate the distributor's mathematical model from which the solution algorithm is derived based on properties of an optimal solution. A numerical example is presented to illustrate the algorithm developed.

• Journal of the Korean housing association
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• v.13 no.5
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• pp.89-99
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• 2002

The multifamily housing has various advantages in construction cost, land-use intensity. KRIHS(1997) recommended the proper scale of th multifamily housing as 800 households in constructability, 1,000 households in facility compactability, 500 households in social aspect. At the early planning stage of project, the size of the multiftmily housing has, until now, been maximizingly considered under the regulation on which has been emphasized at the building volume ratio, land area, etc., except for the expenditure during the maintenance stage. This paper aimed at providing the proper size of multifamily housing in aspect of area and household number with maintenance cost at the early stage of project. For these, it took 곧 average cost function which is made from the 3-rd quardratic form and analyzes the unit increasing rate of the average cost. It surveyed in nationwide focused on the central heating system using diesel and kerosene. The number of samples is 88 and items of management cost is 11. The results are as follows ; first, 3rd-order quadratic function is proper at explaining the cost variation, considering the multicollinearity and statistics. Second, the proper size of multifamily housing is recommended with 83,000 $m^2$ on management area, 820 or over the 2,630 household number in aspect of total management cost.

• IE interfaces
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• v.17 no.spc
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• pp.122-130
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• 2004

Since the cost of software maintenance occupies about 50~75% in a general successful organization, the software maintenance plays an important role in software life cycle. In particular, if the managed system needs to be operated in a long term or the system is very large and complex, then the maintenance is especially more important. Software maintenance is defined as software modification activities after customer delivery, such as improvement of performance or functionality, error correction, adaptation to environmental changes, etc. In this paper, software cost estimation models are proposed, that is based on productivity of manpower in maintenance projects. In order to do this, the activities of maintenance are classified into function change, non-function change, user support and application operation. The proposed models are constructed and verified based on the real size and cost information of projects in the real world. The approach in this paper is to discriminate the heterogeneous activities in maintenance projects, and then to calculate the respective cost of each discriminated activity. By using the proposed models, the total cost of maintenance project is summed from the costs of four activities. In addition the number of conflicts between owner and order receiver about the amount of cost will be reduced and the reasonable cost estimation system will be established.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.253-263
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• 2021

Machine learning is the process of constructing a cost function using learning data used for learning and an artificial neural network to predict the data, and finding parameters that minimize the cost function. Parameters are changed by using the gradient-based method of the cost function. The more complex the digital signal and the more complex the problem to be learned, the more complex and deeper the structure of the artificial neural network. Such a complex and deep neural network structure can cause over-fitting problems. In order to avoid over-fitting, a weight decay regularization method of parameters is used. We additionally use the value of the cost function in this method. In this way, the accuracy of machine learning is improved, and the superiority is confirmed through numerical experiments. These results derive accurate values for a wide range of artificial intelligence data through machine learning.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.2
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• pp.205-210
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• 2014

The micro grid considered in this paper consists of a diesel generator, a photovoltaic array, a wind turbine, a fuel cell, and a energy storage system. This paper explains and simulates the micro grid components in terms of accuracy and efficiency of having a system model based on the costs of fuel as well as operation and maintenance. For operational efficiency, the objective function in a diesel generator consists of the fuel cost function similar to the cost functions used for the conventional fossil-fuel generating plants. The wind turbine generator is modeled by the characteristics of variable output. The optimization is aimed at minimizing the cost function of the system while constraining it to meet the customer demand and safety of micro grid. The operating cost in fuel-cell system includes the fuel costs and the efficiency for fuel to generate electric power. To develop the overall system model gives a possibility to minimize of the total cost of micro grid. The application of optimal operation can save the interruption costs as well as the operating costs, and improve reliability index in micro grid.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.41-48
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• 2004

We may consider the inducement of demand to public transportation as a solution to relieve traffic congestion and pollution. Subway has merits as moving on schedule, transporting more people than bus. But subway is required a vast investment in the early stage of construction has a huge debt. So it runs into red figures, and on this account, services of subway are falling more and more. Development of subway's operation cost function is useful to understand structure of subway's operation and catch the relations of operation cost and actual results. In addition, we can present the policy that is a helpful to the operation as development of operation cost function. But there are short of studies about operation cost deal with a subway comparison with local train. Because local train has many lines and data, on the other hand, subway has one to four lines and less data. Most of previous studies sought the operation cost function of Seoul. So this study aimed to develop and apply the operation cost function of Seoul, Incheon, Busan and Daegu area using full allocation method. In this study, we considered the number of passengers, track-km, train-km, revenue as actual results. By appling the operation cost function, we compared the average cost of each city and confirmed the existence of economies of scale about the number of passengers, train-km.

• Environmental and Resource Economics Review
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• v.23 no.3
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• pp.453-472
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• 2014

Analyzing the effects of carbon emissions trading, which is scheduled to be introduced in Korea in 2015, requires an accurate assessment of $CO_2$ abatement costs by both industries and firms. Firms faced with regulatory constraints are unlikely to minimize their production costs due to rising production costs caused by allocative inefficiency of inputs. The use of a distance function would results in underestimation of $CO_2$ abatement costs, because it fails to capture the allocative distortion costs. Recognizing the disadvantage of the previous approach, first, this paper tests for allocative efficiency of input for the Korean steel industry over the period 1990-2010, then derives the marginal $CO_2$ abatement costs by applying a cost function approach. The hypothesis of allocative efficiency in inputs is rejected and the steel industry pays an annual average cost of 92,000 won in removing an additional ton of $CO_2$ over the sample period.