• Journal of Biosystems Engineering
• /
• v.21 no.4
• /
• pp.449-455
• /
• 1996

The temperature distributions at various soil depths were predicted by heat transfer model during and after infrared irradiation on sand loam or loam soil. At each soil depth, predicted and measured temperature distributions were compared with using the mean relative percentage deviation and standard error. The mean relative percentage deviation was less than 10% between predicted and measured temperature distributions at each soil depth. Thus, it was concluded that the temperature distribution at each soil depth could be predicted satisfactorily by heat transfer model. Also, it is expected that these predicted temperature distributions can be used as basic information for determining the working speed of weeder and the size when the real weeder is constructed.

• Proceedings of the KSME Conference
• /
• 2007.05a
• /
• pp.620-625
• /
• 2007

Autofrettage process is used for internal forming and sizing of cylinder designed to withstand high internal pressures. Once the tube is autofrettaged, it needs to be machined to its final dimensions both at the bore and its outer surface. This paper presents an analytical analysis and numerical analysis of machined compound cylinder using finite element code, ANSYS10.0. An analytical model for predicting the level of autofrettage following either inner, outer, or combined machining of the compound cylinder is developed for the autofrettage residual stress field is simulated by an autofrettaged pressure. The autofrettaged pressures are obtained by using trying-error method. As autofrettage percentage is 20 %, the numerical results are found to be in almost agreement with the analytical ones. However, as autofrettage percentage is 60 %, the numerical results have a little difference with the analytical ones.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.45 no.4
• /
• pp.511-516
• /
• 1996

In this paper, weekly maximum power demand forecasting method in consideration of temperature estimation using a time series model was presented. The method removing weekly, seasonal variations on the load and irregularities variation due to unknown factor was presented. The forecasting model that represent the relations between load and temperature which get a numeral expected temperature based on the past 30 years(1961~1990) temperature was constructed. Effect of holiday was removed by using a weekday change ratio, and irregularities variation was removed by using an autoregressive model. The results of load forecasting show the ability of the method in forecasting with good accuracy without suffering from the effect of seasons and holidays. Percentage error load forecasting of all seasons except summer was obtained below 2 percentage. (author). refs., figs., tabs.

• Journal of the Korean Society of Mechanical Technology
• /
• v.20 no.6
• /
• pp.872-878
• /
• 2018

Steam tables including superheated, saturated and compressed region were simultaneously modeled using the neural networks. Pressure and temperature were used as two inputs for superheated and compressed region. On the other hand Pressure and dryness fraction were two inputs for saturated region. The outputs were specific volume, specific enthalpy and specific entropy. The neural network model were compared with the linear interpolation model in terms of the percentage relative errors. The criterion of judgement was selected with the percentage relative error of 1%. In conclusion the neural networks showed better results than the interpolation method for all data of superheated and compressed region and specific volume of saturated region, but similar for specific enthalpy and entropy of saturated region.

• Journal of the Korean Society of Radiology
• /
• v.12 no.5
• /
• pp.651-658
• /
• 2018

A foot pedal switch in the diagnosis x-ray radiography system has been researched to improve radiologic technologist works and patient satisfaction. The switch has been installed in the diagnosis x-ray radiography system used in domestic clinics. Quantitative evaluation has been conducted by measuring the exposure dose reproducibility test, tube voltage, mAs, and percentage average error. Qualitative evaluation has been conducted by analysis of the radiologic technologists questionnaire. In the quantitative evaluation for the use of the foot pedal switch, the coefficient of variation was less than 0.05 in the exposure dose reproducibility test. In the mAs test, percentage average error of ${\pm}20%$ was measured. There was no problem raised since it meets the all inspection standards of the diagnosis x-ray generator. In the qualitative evaluation, most of the opinions are that it has a clinical value for the foot pedal switch in the diagnosis x-ray radiography system. Therefore, developing the foot pedal switch for the diagnosis x-ray radiography system can improve effectively the rapidity and accuracy of the radiologic technologist work. In addition, it is effective in decreasing the x-ray exposure of patients and increasing satisfaction for the medical service due to reduction of retaking x-ray.

• Journal of the Korean Society of Radiology
• /
• v.14 no.2
• /
• pp.139-148
• /
• 2020

The purpose of this study is to propose a method to optimize the performance of Digital Radiography (DR) by analyzing the effect of exposure time change on the stability of radiation output and image quality. The experimental method was used to change the exposure time to 50 msec, 100 msec, 200 msec, and 400 msec so that the Percentage Average Error (PAE), Time-to-Radiation Dose Curve, Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR) and theses analysis were performed to evaluate the normal operation of parameters, radiation output and image quality. As a result, all the parameters used in the experiment showed the Percentage Average Error in the normal range, and the shorter the exposure time, the stability of radiation output and image quality decrease. In conclusion, it was found that the performance of Digital Radiography can be optimized when stable radiation output and image quality are applied by applying 100 msec ~ 200 msec exposure time.

• Journal of the Korean Society of Radiology
• /
• v.14 no.4
• /
• pp.375-383
• /
• 2020

This study aimed to propose a methodology for quantitatively analyzing problems resulting from the performance and combination of the ionization chamber when using an automatic exposure control (AEC) and to optimize the performance of the digital radiography (DR). In the experimental method, the X-ray quality of the parameters used for the examination of the abdomen and pelvis was evaluated by percentage average error (PAE) and half value layer (HVL). Then, the stability of the radiation output and the image quality were analyzed by calculating the entrance surface dose (ESD) and entropy when the three ionization chambers were combined. As a result, all of the X-ray quality of the digital radiography used in the experiment showed a percentage average error and a half value layer in the normal range. The entrance surface dose increased in proportion to the combination of chambers, and entropy increased in proportion to the combination of ionization chambers except when three chambers were combined. In conclusion, analysis using entrance surface dose and entropy was found to be a useful method for evaluating the performance and combination problems of the ionization chamber, and the optimal performance of the digital radiography can be maintained when two or less ionization chambers are combined.

• Communications for Statistical Applications and Methods
• /
• v.19 no.6
• /
• pp.869-876
• /
• 2012

In this paper, we applied seasonal time series models such as ARIMA, FARIMA, AR-GARCH and Holt-Winters in consideration of seasonality to forecast short-term electricity demand data. The results for performance evaluation on the time series models show that seasonal FARIMA and seasonal Holt-Winters models perform adequately under the criterion of Mean Absolute Percentage Error(MAPE).

• Proceedings of the Korea Water Resources Association Conference
• /
• 2016.05a
• /
• pp.222-222
• /
• 2016

기후변화에 의한 자연재해의 규모와 빈도가 증가함에 따라 수자원 영향 평가 및 대응전략 수립을 위한 연구가 활발히 이루어지고 있다. 본 연구에서는 물리기반의 분포형 수문기상모형인 DHSVM을 이용하여 2012년-2014년 동안의 한반도 유역의 기상인자 자료를 수집하여 증발산, 토양수분, 현열, 잠열, 지열, 순복사량 등의 수문기상인자를 산정하였다(Fig. 1). 모형의 적합성 평가를 위해서 안동댐 유역에 대하여 검정통계량으로 NSE(Nash-Sutucliffe model efficiency coefficient), RMSE, $R^2$, MAPE(mean absolute percentage error example)위한 계산하였다.

• Journal of Korean Society of Forest Science
• /
• v.97 no.2
• /
• pp.140-143
• /
• 2008

This study compared the plywood demand prediction accuracy of econometric and vector autoregressive models using Korean data. The econometric model of plywood demand was specified with three explanatory variables; own price, construction permit area, dummy. The vector autoregressive model was specified with lagged endogenous variable, own price, construction permit area and dummy. The dummy variable reflected the abrupt decrease in plywood consumption in the late 1990's. The prediction accuracy was estimated on the basis of Residual Mean Squared Error, Mean Absolute Percentage Error and Theil's Inequality Coefficient. The results showed that the plywood demand prediction can be performed more accurately by econometric model than by vector autoregressive model.