• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.4
• /
• pp.621-628
• /
• 2021

This paper proposes a method to calibrate a thermal camera with three different perspectives. In particular, the intrinsic parameters of the camera and re-projection errors were provided to quantify the accuracy of the calibration result. Three lenses of the camera capture the same image, but they are not overlapped, and the image resolution is worse than the one captured by the RGB camera. In computer vision, camera calibration is one of the most important and fundamental tasks to calculate the distance between camera (s) and a target object or the three-dimensional (3D) coordinates of a point in a 3D object. Once calibration is complete, the intrinsic and the extrinsic parameters of the camera(s) are provided. The intrinsic parameters are composed of the focal length, skewness factor, and principal points, and the extrinsic parameters are composed of the relative rotation and translation of the camera(s). This study estimated the intrinsic parameters of thermal cameras that have three lenses of different perspectives. In particular, image enhancement based on a deep learning algorithm was carried out to improve the quality of the calibration results. Experimental results are provided to substantiate the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.3
• /
• pp.104-111
• /
• 2018

The sensorless control of high efficiency air compressors using a permanent magnet type synchronous motor as an oil-free air compressor is quite common. However, due to the nature of the air compressor, it is difficult to install a position sensor. In order to control the permanent magnet type synchronous motor at variable speed, the inclusion of a position sensor to grasp the position of the rotor is essential. Therefore, in order to achieve sensorless control, it is essential to use a permanent magnet type synchronous motor in the compressor. The position estimation method based on the back electromotive force, which is widely used as the sensorless control method, has a limitation in that position errors occur due either to the phase delay caused by the use of a stationary coordinate system or to the estimated back electromotive force in the transient state caused by the use of a synchronous coordinate system. Therefore, in this paper, we propose a method of estimating the position and velocity using a rotation angle tracking observer and reducing the speed ripple through a disturbance observer. An experimental apparatus was constructed using Freescale's MPU and the feasibility of the proposed algorithm was examined. It was confirmed that even if a position error occurs at a certain point in time, the position correction value converges to the actual vector position when the position error value is found.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.11
• /
• pp.527-536
• /
• 2017

With the recent development of smart grid industry, the necessity for efficient EMS(Energy Management System) has been increased. In particular, in order to reduce electric load and energy cost, sophisticated electric load forecasting and efficient smart grid operation strategy are required. In this paper, for more accurate electric load forecasting, we extend the data collected at demand time into high time resolution and construct an artificial neural network-based forecasting model appropriate for the high time resolution data. Furthermore, to improve the accuracy of electric load forecasting, time series data of sequence form are transformed into continuous data of two-dimensional space to solve that problem that machine learning methods cannot reflect the periodicity of time series data. In addition, to consider external factors such as temperature and humidity in accordance with the time resolution, we estimate their value at the time resolution using linear interpolation method. Finally, we apply the PCA(Principal Component Analysis) algorithm to the feature vector composed of external factors to remove data which have little correlation with the power data. Finally, we perform the evaluation of our model through 5-fold cross-validation. The results show that forecasting based on higher time resolution improve the accuracy and the best error rate of 3.71% was achieved at the 3-min resolution.

• International Area Studies Review
• /
• v.20 no.1
• /
• pp.23-51
• /
• 2016

This study analyzed the expected economic effects of the Korea-GCC FTA and sought strategies for industrial cooperation. To see the economic effects of Korea-GCC FTA, we analysed the effect of the oil tariff reduction of economy by Vector Autoregression(VAR) model. The estimation results shows that following the abolishment of the tariff on crude oil imports, GDP, GNI and consumption are expected to grow by 0.212%, 0.389% and 0.238%, respectively. Meanwhile, investment, export and import are estimated to drop by 0.462%, 0.413% and 0.342%, respectively. As for prices, producer prices are to rise by 6.356%p, whereas consumer prices fall by 2.996%p. In short, the Korea-GCC FTA and resultant abolishment of the tariff on crude oil imports followed by the decline in crude oil prices will result in declining prices whilst macroeconomic indices, such as GDP, GNI and consumption, will increase exerting positive effects on domestic economic growth. Also, it is necessary to proactively respond to GCC member states' industrial diversification policies for FTA-based industrial cooperation to diversify the sources of crude oil and natural gas imports for further resource risk management.

• Journal of Biomedical Engineering Research
• /
• v.24 no.2
• /
• pp.133-140
• /
• 2003

In this study, muscle activity was measured using surface EMG (sEMG) during a voluntary maneuver (ankle dorsiflexion) in the supine position was compared pre and post gait training. Nine patients with incomplete spinal cord injury participated in a supported treadmill ambulation training (STAT), twenty minutes a day, five days a week for three months. Two tests, a gait speed test and a voluntary maneuver test, were made the same day, or at least the same week, pre and post gait training. Ten healthy subjects' data recorded using the same voluntary maneuvers were used for the reference. sEMG measured from ten lower limb muscles was used to observe the two features of amplitude and motor control distribution pattern, named response vector. The result showed that the average gait speed of patients increased significantly (p〈0.1) from 0.47$\pm$0.35 m/s to 0.68$\pm$0.52 m/s. In sEMG analysis, six out of nine patients showed a tendency to increase the right tibialis anterior activity during right ankle dorsiflexion from 109.7$\pm$148.5 $mutextrm{V}$ to 145.9$\pm$180.7 $mutextrm{V}$ but it was not significant (p〈0.055). In addition, only two patients showed increase of correlation coefficient and total muscle activity in the left fide during left dorsiflexion. Patients' muscle activity changes after gait training varied individually and generally depended on their muscle control abilities of the pre-STAT status. Response vector being introduced for quantitative analysis showed good Possibility to anticipate. evaluate, and/or guide patients with SCI, before and after gait training.

• Journal of Korea Port Economic Association
• /
• v.37 no.4
• /
• pp.161-173
• /
• 2021

The shipping industry plummeted and was depressed due to the global economic crisis caused by the bankruptcy of Lehman Brothers in the US in 2008. In 2020, the shipping market also suffered from a collapse in the unstable global economic situation due to the COVID-19 pandemic, but unexpectedly, it changed to an upward trend from the end of 2020, and in 2021, it exceeded the market of the boom period of 2008. According to the Clarksons report published in May 2021, the decrease in cargo volume due to the COVID-19 pandemic in 2020 has returned to the pre-corona level by the end of 2020, and the tramper bulk carrier capacity of 103~104% of the Panamax has been in the ports due to congestion. Earnings across the bulker segments have risen to ten-year highs in recent months. In this study, as factors affecting BDI, the capacity and congestion ratio of Cape and Panamax ships on the supply side, iron ore and coal seaborne tonnge on the demand side and Granger causality test, IRF(Impulse Response Function) and FEVD(Forecast Error Variance Decomposition) were performed using VAR model to analyze the impact on BDI by congestion caused by strengthen quarantine at the port due to the COVID-19 pandemic and the loading and discharging operation delay due to the infection of the stevedore, etc and to predict the shipping market after the pandemic. As a result of the Granger causality test of variables and BDI using time series data from January 2016 to July 2021, causality was found in the Fleet and Congestion variables, and as a result of the Impulse Response Function, Congestion variable was found to have significant at both upper and lower limit of the confidence interval. As a result of the Forecast Error Variance Decomposition, Congestion variable showed an explanatory power upto 25% for the change in BDI. If the congestion in ports decreases after With Corona, it is expected that there is down-risk in the shipping market. The COVID-19 pandemic occurred not from economic factors but from an ecological factor by the pandemic is different from the past economic crisis. It is necessary to analyze from a different point of view than the past economic crisis. This study has meaningful to analyze the causality and explanatory power of Congestion factor by pandemic.