• Herbal Formula Science
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• v.24 no.4
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• pp.335-351
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• 2016

Objective : This study was done to clarify ambiguous non-standard weight and measuring units in medical classics. Methods : Using medical classics and research dissertations, we studied the basic definitions of weight and measuring units and the types of non-standard weight and measuring units. We compared non-standard weight and measuring units in the reference literatures, to determine the dose of herbs in the prescriptions. Results : There are three types of units in non-standard weight and measuring units. These are 'Quantity measuring unit', 'Resembrance measuring unit', and 'Eye measuring unit'. And we found historical efforts and progresses for proper ways to convert non-standard weight and measuring units to standard weight and measuring units. Conclusions : This research will be the basic data for the standardization of prescriptions. Additional study was still required for precise weighing and measuring in Korean medicine and pharmacy.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.1-6
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• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.