• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.730-738
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• 1994

The major advantage of the short-term load forecasting technique using general exponential smoothing is high accuracy and operational simplicity, but it makes large forecasting error when the load changes repidly. The paper has presented new technique to improve those shortcomings, and according to forecasted the technique proved to be valid for two years. The structure of load model is time function which consists of daily-and temperature-deviation component. The average of standard percentage erro in daily forecasting for two years was 2.02%, and this forecasting technique has improved standard erro by 0.46%. As relative coefficient for daily and seasonal forecasting is 0.95 or more, this technique proved to be valid.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.6
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• pp.170-176
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• 2018

Recently, weapon system requires personal protection products due to the explosion of rapid-fire explosion, which is considered to be multi threat in modernization, complication and war against terrorism. However, the conventional Korean military bullet protection helmets are not suitable for wearing convenience and combatant interoperability in terms of ergonomic. In this paper, we propose a suitable 3D Scanning method for the head, and compare the measured 3D dimension with the existing 2D measurement value to identity the reliability. Reverse engineered soldier head using the quick surface method was realized with a perfect free-form surface and satisfactory tolerance range (${\pm}0.2mm$). Through the comparison of 3D and 2D measured head dimensions, the absolute error value was 0.73 mm on average and relative error was 0.35 %, confirming the high accuracy of the 3D scan modeling. Also, quick surface method using 3D scanner is suggested a fast and accurate skill for ergonomics in obtaining the head modeling needed for military's personal bullet protection helmet design.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2000.05a
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• pp.135-143
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• 2000

The COCOMO Ⅱ model is well-suited for the new software development life cycle such as non-sequential and rapid-development processes. The traditional regression approach based on the least square criterion is the most commonly used technique for empirical calibration in the COCOMO Ⅱ model. But it has a few assumptions frequently violated by software engineering data sets. It is true that the source data is also generally imprecise in reporting size, effort, and cost-driver ratings, particularly across different organizations. And that the outlier for the source data is a peculiarity and indicates a data pint To cope with difficulties, in this paper, we propose a new regression method for calibrating COCOMO Ⅱ post-architecture model based on the minimum relative erro(MRE) criterion. The characteristic of the proposed method is insensitive to the extreme values of the data in the empirical calibration. As the experimental results, It is evident that our proposed calibration method MRE was shown to be superior to the traditional regression approach for model calibration, as illustrated by the values obtained for standard deviation(^σ), and prediction at level L PRED(L) measures.