• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.404-404
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• 1994

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.261-261
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• 1996

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.10a
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• pp.96-98
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• 1994

• Journal of Korean Society of Water and Wastewater
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• v.31 no.3
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• pp.237-248
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• 2017

The estimation method of economical leakage management target utilized upon planning business for improvement of revenue water ratio in South Korea is presented and applicability of methods developed in this study is assessed through application on site. With a consideration of revenue water ratio in application target area, estimation method of long-term economical leakage management target is applied. Three leakage reduction methods such as replacement of residual aged pipe, leakage investigation and restoration and water pressure management are applied with a consideration of characteristics of site. Due to difficulty of obtaining data, analysis of cost/benefit by leakage reduction methods is performed by applying method of leakages estimation equation among statistical methods. As a result of application, revenue water ratio corresponding to long-term economical leakage management target is 91.6 %.

• KIEE International Transactions on Power Engineering
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• v.11A no.4
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• pp.45-50
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• 2001

The impact evaluation of a DSM program is a very important issue since the results are used to determine the sustainability of a program. In general. to estimate the impacts of a DSM program it is required to measure the electricity usage changes before and after a program. Since the measurement-based approaches cost highly, most of the conventional evaluations are based on the average figures. However estimation of the average-based impacts can lead to both distorted results of over/under estimation of kW and kWh savings and non-optimal DSM planning. In this paper, we have developed a new multi-point measurement approach which can evaluate kW and kWh savings of a DSM program more exactly. To do this, the saving rate and operating rate are defined and set as the function of load factor of a customer, and these rates are incorporated with the conventional diffusion function of Bass to project the future impacts of a DSM program. The case study is performed on the inverter program of Korea by using the suggested approach.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.275-286
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• 2020

The study explores factors that affect the performance of responsibility accounting at public universities in Vietnam. The study conducted a survey of 130, out of 154 public universities in Vietnam and uses regression analysis methods. The results identify eight groups of factors affecting the performance of responsibility accounting at these establishments of higher education: Division of the organization into responsibility centers, Estimation and Reality, Cost and income allocation, University autonomy, Management decentralization, Estimation, Reward, and Report. Costs and income allocation for responsibility centers, university autonomy, and the division of universities into responsibility centers are shown to significantly affect the performance of public universities in Vietnam. The results show that the performance of responsibility accounting at public universities in Vietnam is influenced by decentralization of management, division of the organization into responsibility centers, reward, cost and income allocation, estimation, evaluation of the results achieved between the estimation compared with reality, release of reports and university autonomy. Among the factors, cost and income allocation, university autonomy, division of the organization into responsibility centers, reward and evaluation of results achieved between estimation and reality have strong impacts. The study findings also indicate that the school council does not affect responsibility accounting at these universities.

• Journal of Construction Engineering and Project Management
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• v.3 no.4
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• pp.1-4
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• 2013

Excavation is most commonly used activity in all construction projects. All contracting agencies prefer to use bigger and heavier excavators and dumpers on site to do excavations if quantity of excavation is huge. Estimation of required number of excavators and dumpers for completion of excavation could be rather a tedious process involving repetitive calculation on which professionals spend their valuable time. As the Information Technology is highly involved in construction section there os need to have IT model for estimation of number of excavators and dumpers. The developed model is useful to calculate required equipments within short period of time. The purpose of the developed IT model is to save the time and efforts of the construction professional. The paper discusses about model which can be used on site to estimate numbers of excavators and dumpers required for completion of certain quantity of excavation within the given time. The calculation considers various existing formulas and method to generate the output. This information could certainly be useful in planning equipments on construction project sites. The tool is user friendly where any non IT background person can use it on construction sites.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.2
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• pp.115-125
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• 2011

An accurate estimation of software development size is an important factor in calculating reasonable cost of project development and determining its success. In this study, we propose estimation models, using function point based on the functional correlation between software, with empirical data. Three models($FP_{est}(I)$, $FP_{est}(II)$, $FP_{est}(III)$) are developed with correlation and regression analysis. The validity of the models is evaluated by the significance test by comparing values of Mean Magnitude of Relative Error (MMRE) and predictions of each model at level n%. Model $FP_{est}(III)$ proved to be superior to other models such as IFPC(Indicative Function Point Count), EFPC(Estimated Function Point Count), EPFS(Early Prediction of Function Size), $FP_{est}(I)$, and $FP_{est}(II)$. As a result, the accuracy of the model appears to be very high to determine the usefulness of the model to finally overcome weakness of other estimation models. The model can be efficiently used to estimate project development size including software size or manpower allocation.

• Management & Information Systems Review
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• v.7
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• pp.427-450
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• 2001

This research suggests the estimation methodology of Logistics. This paper elucidates the main problems associated with estimation in the regression model. We review the methods for estimating the parameters in the model and introduce a modified procedure in which all models are fitted and combined to construct a combination of estimates. The resulting estimators are found to be as efficient as the maximum likelihood (ML) estimators in various cases. Our method requires more computations but has an advantage for large data sets. Also, it enables to detect particular features in the data structure. Examples of real data are used to illustrate the properties of the estimators. The backgrounds of estimation of logistic regression model is the increasing logistic environment importance today. In the first phase, we conduct an exploratory study to discuss 9 independent variables. In the second phase, we try to find the fittest logistic regression model. In the third phase, we calculate the logistic estimation using logistic regression model. The parameters of logistic regression model were estimated using ordinary least squares regression. The standard assumptions of OLS estimation were tested. The calculated value of the F-statistics for the logistic regression model is significant at the 5% level. The logistic regression model also explains a significant amount of variance in the dependent variable. The parameter estimates of the logistic regression model with t-statistics in parentheses are presented in Table. The object of this paper is to find the best logistic regression model to estimate the comparative accurate logistics.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.48-51
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• 2004

The estimation of NC machining time is of significance since it provides shop floor engineers with information for the determination of the productivity of the floor as well as process schedules. The NC machining time commonly depends on NC programs since they have various important information such as tool positions, feed rates, and other miscellaneous functions. Thus, nominal NC machining time can be easily acquired based on the programs. Actual machining time, however, cannot be simply obtained because of the dynamic characteristics of a NC machine controller such as acceleration and deceleration. Hence, this study presents a NC machine time estimation model for sculptured surfaces, considering the dynamic characteristics. The estimation model uses the distribution of NC blocks according to a factor influencing the machining time. Finally, machining time is estimated by a statistical machining time estimation model representing the relationship between the block distribution and the machining time. The parameters in the model are searched out by a genetic algorithm.