• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.15 no.4 s.97
• /
• pp.404-411
• /
• 2005

To increase accurateness and reliability of the evaluation of power tool vibration transmitted to an operator, it is necessary to measure the grip and feed forces during the measurement of hand-transmitted vibration. In the study a system was invented to measure the vibration and the grip and/or feed force, which consists of a measurement handle and a PC with a data acquisition system and the corresponding software. Strain gauges and an accelerometer were mounted on the handle surface for the simultaneous measurement of the forces and the vibration. The program in the system makes it possible to monitor the grip and feed force during the tool operation so that the operator keeps the applying forces within the pre-determined range. Investigating the vibration total values, frequency-weighted root-mean-square accelerations at the handle, obtained in repetition for each power tool with control of the grip and feed force showed more consistency than those measured without force control. By using the system the experimenter can reduce random error of the measured vibration.

• Nuclear Engineering and Technology
• /
• v.33 no.1
• /
• pp.25-33
• /
• 2001

To determine the pin power distribution without disassembling, HANARO fuel assemblies are gamma-scanned and then the distribution is reconstructed tv using the tomography method. The iterative least squares method (ILSM and the wavelet singular value decomposition method (WSVD) are chosen to solve the problem. An optimal convergence criterion is used to stop the iteration algorithm to overcome the potential divergence in ILSM. WSVD gives better results than ILSM , and the average values from the two methods give the best results. The RMSE (root mean square errors) to the reference data are 5.1, 6.6, 5.0, 6.5, and 6.4% and the maximum relative errors are 10.2, 13.7, 12.2, 13.6, and 14.3%, respectively. It is found that the effect of random positions of the pins is important. Although the effect can be accommodated by the iterative calculations simulating the random positions, the use of experimental equipment with a slit covering the whole range of the assembly horizontally is recommended to obtain more accurate results. We made a new apparatus using the results of this study and are conducting an experiment in order to obtain more accurate results.

• Proceedings of the KIPE Conference
• /
• 2014.07a
• /
• pp.451-452
• /
• 2014

본 논문에서는 단상 계통연계형 컨버터의 전원 위상각을 추종함에 있어 필수적인 전압 센서의 옵셋 오차에 대한 영향을 분석하고 이를 검출 및 보상하기 위한 알고리즘을 제안하였다. 전원전압 측정에 따른 옵셋 오차는 전원 주파수의 1배 맥동을 야기하여 전원 위상각이 왜곡된다. 왜곡된 전원 위상각에 의한 좌표변환시 동기 좌표계 dq축 전류에 전원 주파수 1배의 맥동을 야기하며 이는 계통측 상전류에 직류성분과 전원 주파수 2배의 고조파 성분을 발생시키게 된다. 따라서, 본 논문에서는 전원측정시 야기되는 옵셋 오차의 영향을 분석하고 이의 검출신호로 전원 위상각 제어기의 적분출력을 선정하였다. 또한 RMS(Root Mean Square) 기법을 이용하여 옵셋 성분을 검출 및 보상하는 알고리즘을 제안하였다. 제안된 알고리즘의 성능은 시뮬레이션과 실험을 통하여 검증하였다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.8
• /
• pp.3925-3932
• /
• 2013

Emotion is closely related to the life of human, so has effect on many parts such as concentration, learning ability, etc. and makes to have different behavior patterns. The purpose of this paper is to extract important features based on physiological signals to recognize negative emotion. In this paper, after acquisition of electrocardiography(ECG), electroencephalography(EEG), skin temperature(SKT) and galvanic skin response(GSR) measurements based on physiological signals, we designed an accurate and fast algorithm using combination of linear discriminant analysis(LDA) and genetic algorithm(GA), then we selected important features. As a result, the accuracy of the algorithm is up to 96.4% and selected features are Mean, root mean square successive difference(RMSSD), NN intervals differing more than 50ms(NN50) of heart rate variability(HRV), ${\sigma}$ and ${\alpha}$ frequency power of EEG from frontal region, ${\alpha}$, ${\beta}$, and ${\gamma}$ frequency power of EEG from central region, and mean and standard deviation of SKT. Therefore, the features play an important role to recognize negative emotion.

• Journal of the Korean Solar Energy Society
• /
• v.39 no.2
• /
• pp.71-80
• /
• 2019

Daily ahead forecast is necessary for the electricity balance between load and supply due to the variability renewable energy. Numerical weather prediction is usually employed to produce the solar irradiance as well as electric power forecast for more than 12 hours forecast horizon. UM-LDAPS model is the numerical weather prediction operated by Korea Meteorological Administration and it generates the 36 hours forecast of hourly total irradiance 4 times a day. This study attempts to evaluate the model performance against the in situ measurements at 37 ground stations from January to May, 2013. Relative mean bias error, mean absolute error and root mean square error of hourly total irradiance are averaged over all ground stations as being 8.2%, 21.2% and 29.6%, respectively. The behavior of mean bias error appears to be different; positively largest in Chupoongnyeong station but negatively largest in Daegu station. The distinct contrast might be attributed to the limitation of microphysics parameterization for thick and thin clouds in the model.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_3
• /
• pp.953-966
• /
• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Smart Media Journal
• /
• v.7 no.1
• /
• pp.16-23
• /
• 2018

In this paper, we used the Deep Neural Network (DNN) to predict the number of daily spectators of Gwangju - KIA Champions Field in order to provide marketing data for the team and related businesses and for managing the inventories of the facilities in the stadium. In this study, the DNN model, which is based on an artificial neural network (ANN), was used, and four kinds of DNN model were designed along with dropout and batch normalization model to prevent overfitting. Each of four models consists of 10 DNNs, and we added extra models with ensemble model. Each model was evaluated by Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The learning data from the model randomly selected 80% of the collected data from 2008 to 2017, and the other 20% were used as test data. With the result of 100 data selection, model configuration, and learning and prediction, we concluded that the predictive power of the DNN model with ensemble model is the best, and RMSE and MAPE are 15.17% and 14.34% higher, correspondingly, than the prediction value of the multiple linear regression model.

• Journal of Korean Institute of Industrial Engineers
• /
• v.25 no.3
• /
• pp.330-335
• /
• 1999

The goal of the study is to determine the most sensitive parameter to represent the degree of muscle force and fatigue. Various numerical parameters such as the first coefficient of Autoregressive (AR) Model, Root Mean Square (RMS), Zero Crossing Rate (ZCR), Mean Power Frequency (MPF), Median Frequency (MF) were tested in this study. Ten healthy male subjects participated in the experiment. They were asked to extend their trunk by using the right and left erector spinae muscles during a sustained isometric contraction for twenty seconds. The force levels were 15%, 30%, 45%, 60%, and 75% of Maximal Voluntary Contraction (MVC), and the order of trials was randomized. The results showed that RMS was the best parameter to measure the force level of the muscle, and that the first coefficient of AR model was relatively sensitive parameter for the fatigue measurement at less than 60% MVC condition. At the 75% MVC, however, both MPF and the first coefficient of AR Model showed the best performance in quantification of muscle fatigue. Therefore, the sensitivity of measurement can be improved by properly selecting the parameter based upon the level of force during a sustained isometric condition.

• Journal of the Ergonomics Society of Korea
• /
• v.24 no.4
• /
• pp.55-62
• /
• 2005

This study examined the effect of ergonomic heel rest that was designed for drivers who have physical handicap in the low leg muscles or have to drive prolonged hours with frequent foot pedaling. An experiment was designed to test the ergonomic heel rest with traditional foot pedal. Forty subjects participated in the experiment. Electromyography(EMG) was used to monitor the muscle activity and fatigue of right leg, and Electro-goniometer was used to measure the ranges of motions of the knee and ankle. A simulator of driver's seat was built for the experiment and the heel rest was installed on it. In order to examine the low muscle activity and range of motion, subjects used the foot pedal for 15 minutes repetitively for each experimental condition. Another 15 minutes test without the heel rest was also performed for comparison. The Root Mean Square(RMS) and Mean Power Frequency(MPF) Shift were used to quantify the level of muscle activity and local muscle fatigue. In results, statistically significant decreases of muscle activity and fatigue were found in all the low leg muscles. The range of motion of the knee and ankle joint also decreased when the heel rest was used. The mechanism of the heel rest effect was discussed in this study. This type of heel rest can be applied to real driving situation after ensuring the safety, or overcoming the psychological discomfort possibly due to unfamiliarity.

• The Journal of the Acoustical Society of Korea
• /
• v.13 no.4
• /
• pp.20-31
• /
• 1994

The maximum likelihood(ML) estimation has excellent accuracy for frequency estimation of multiple sinusoids, but the maximum likelihood function requires much loss owing to the high nonlinearity. This paper presents a simplified maximum likelihood estimation, in order to improve the nonlinearity of the maximum likelihood estimation for frequencies of sinusoids in signals. This method is applied to the frequency estimation of sinusoidal signals corrupted by white or colored measurement noise. Monte-carlo simulations are conducted for the comparison of ML method with the best MFBLP method, in terms of sampled mean, root mean square and relative bias. The power spectral density and the position of frequency in unit circle are appeared in figures.