• 월간 기계설비
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• s.180
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• pp.40-49
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• 2005

• Korean Journal of Construction Engineering and Management
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• v.7 no.2 s.30
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• pp.138-147
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• 2006

The objective of this research is to explore a more precise forecasting method by applying Case-based Reasoning (CBR). The newly suggested method in this study enables project managers to forecast monthly expenditures with less time and effort by retrieving and referring only projects of a similar nature, while filtering out irrelevant cases included in database. For the purpose of accurate forecasting, 1) the choice of the numbers of referring projects and 2) the better selection among three levels ? which include a 20-work package level, a 7-major work package level, and a total sum level analysis, were investigated in detail. It is concluded that selecting similar projects at $12{\sim}19%$ out of the whole database will produce a more precise forecasting. The new forecasting model, which suggests the predicted values based on previous projects, is more than just a forecasting methodology; it provides a bridge that enables current data collection techniques to be used within the context of the accumulated information. This will eventually help all the participants in the construction industry to build up the knowledge derived from invaluable experience.

• Journal of Biosystems Engineering
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• v.16 no.4
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• pp.384-398
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• 1991

A computer program was developed to select the optimum size of farm machine and analyze its operation costs according to various farming conditions. It was written in FORTRAN 77 and BASIC languages and can be run on any personal computer having Korean Standard Complete Type and Korean Language Code. The program was developed as a user-friendly type so that users can carry out easily the costs analysis for the whole farm work or respective operation in rice production, and for plowing, rotarying and pest controlling in upland. The program can analyze simultaneously three different machines in plowing & rotarying and two machines in transplanting, pest controlling and harvesting operations. The input data are the sizes of arable lands, possible working days and number of laborers during the opimum working period, and custom rates varying depending on regions and individual farming conditions. We can find out the results such as the selected optimum combination farm machines, the overs and shorts of working days relative to the planned working period, capacities of the machines, break-even points by custom rate, fixed costs for a month, and utilization costs in a hectare.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3390-3398
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• 2009

The knowledge management starts from the enhancement of learning capability in the members of the organization. The strategic change into the learning organization should be aligned with the change of organizational strategy, structure and processes. The study employed action learning methodology to transform the traditional organization into the learning one. The learning organization project has been successful thanks to the members' zeal and consensus to change the processes. However, not every learning team has been so successful. Some cases complained time consuming where others expect to be helpful for their incentives. The researchers concluded that the most important point for success of the learning organization project should be the support of top management.

• Information Systems Review
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• v.7 no.1
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• pp.275-295
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• 2005

Changes in business environment caused by globalization of the world economy and the beginning of the knowledge society forced hospitals to equip with tools for the enhanced competitiveness. In other words, hospitals must aim three targets such as acquisition of advanced medical skills and equipments, improvement of service level for patients, and achievement of superior managerial performance simultaneously. This study has been done to suggest a way to reduce the possibility of hospital bill claim reduction as an alternative for the achievement of superior managerial performance. If the reduction rate of hospital bill claim is high, it will put negative impact on the hospital's revenue stream and hospital's reliability. Thus, if they want to stay competitive, hospitals need to device ways to cut the reduction rate as much as possible. In this study, a prototype system has been developed and implemented to check the possibility to cut the reduction rate through deep analysis of causes of reduction. The prototype first developed utilizing data mining techniques and the relation rules algorithm. Then the prototype was tested its performance using the D hospital's live data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.518-525
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• 2018

In the 21st century, human beings are becoming increasingly concerned about greenhouse gas emissions as the environment changes due to climate change become serious. The temperature of Korea has risen by approximately $1.5^{\circ}C$ from 1904 to 2000, and the climate is changing gradually to a subtropical climate. As a result, the frequency of floods and droughts increases, so that the water available to humans is decreasing every year, and the cost of using city water is rising every year. The reuse of wastewater that is normally abandoned is inevitable. This study examined the monthly data for 6 months of operation by installing a reuse system of concentrated wastewater (Re R/O System) that is generated during the process of manufacturing de-ionized water (DI-Water System) used in semiconductor processing. As a result of the survey, the city water supply saved approximately $2,767m^3$ per month. The average annual greenhouse gas emissions was $1,329.07kg-CO_2$ per month due to the electricity consumption of the water reuse system. On the other hand, because of the reduction in city water supply, the average monthly average of $918.64kg-CO_2$ was reduced, and the greenhouse gas emissions were increased to $410.43kg-CO_2$ per month. If it improves some processes in the water reuse system, the amount of greenhouse gas emissions can be reduced by an average of $254.41kg-CO_2$ per month.