• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.8-15
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• 2019

The PM synchronous motor drives with vector control have been applied to wide fields of industry applications due to its high efficiency. The rotor position information for vector control of a PM synchronous motor is detected from the rotor position sensors or rotor position estimators. The sensorless control based on the mathematical model of PM synchronous motor is generally used and it can be classified into back EMF -based sensorless control and magnet flux-based sensorless control. The rotor position estimating performance of the back EMF-based sensorless control is deteriorated at low speeds since the magnitude of back EMF is proportional to the motor speed. The magnitude of the magnet flux for estimating rotor position in the flux-based sensorless control is independent on the motor speed so that the estimating performance is excellent for wide speed ranges. However, the estimation performance of the model-based sensorless control may be influenced by the motor parameter variation since the rotor position estimator uses the mathematical model of the PM synchronous motor. In this paper, the rotor position estimation performance for the back EMF based- and flux-based sensorless controls is analyzed theoretically and is compared through the simulation and experiment when the motor parameters including stator resistance and inductance are varied.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.61-68
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• 2018

In this paper, we propose a method of character detection by analyzing image enhancement and character type to detect characters in natural images that can be acquired in everyday life. The proposed method emphasizes the boundaries of the object part using the unsharp mask in order to improve the detection rate of the area to be recognized as a character in a natural image. By using the boundary of the enhanced object, the character candidate region of the image is detected using Maximal Stable Extermal Regions (MSER). In order to detect the region to be judged as a real character in the detected character candidate region, the shape of each region is analyzed and the non-character region other than the region having the character characteristic is removed to increase the detection rate of the actual character region. In order to compare the objective test of this paper, we compare the detection rate and the accuracy of the character region with the existing methods. Experimental results show that the proposed method improves the detection rate and accuracy of the character region over the existing character detection method.

• The Journal of the Korea Contents Association
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• v.19 no.8
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• pp.284-292
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• 2019

To evaluate the usefulness of pediatric chest CT scans by comparing the dose, examination time, and image quality by applying Helical mode, High-pitch mode, and Volume Axial mode to minimize the radiation exposure and obtain high diagnostic value. Revolution (GE Healthcare, Wisconsin USA) was used to divide PBU-70 phantom into Helical mode, High-pitch mode, and Volume Axial mode. After acquiring images, ROI is set for each image, heart, bone, lung, and back-ground air, and the average value is obtained by measuring CT number (HU) and noise (SD). SNR and CNR were measured and compared with DLP values provided directly by the equipment. Determining statistical significance Statistical analysis was performed using ONE-WAY-ANAOVA using SPSS 21.0. In this experiment, it was possible to inspect at a short time without deterioration of image quality with the lowest dose when using volume axial mode. Although the detector coverage of 16 cm is limited to all pediatric chest CT scans, it is recommended to be actively used in pediatric patients, and further study is needed to apply other test sites in volume axial mode.

• Clean Technology
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• v.25 no.2
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• pp.140-146
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• 2019

Flammable substances, such as organic solvents, are commonly used in laboratories and industrial processes. The flash point of flammable liquid mixtures is a very important parameter for characterizing the ignition and explosion hazards, and the flash points of mixtures of $C_2{\sim}C_3$ alcohols and 2,2,4-trimethylpentane were measured in the present study. The 2,2,4-trimethylpentane is an important component of gasoline and is frequently used in the petroleum industry as a solvent. Lower flash point data were measured for the binary systems {ethanol + 2,2,4-trimethylpentane}, {1-propanol + 2,2,4-trimethylpentane}, and {2-propanol + 2,2,4-trimethylpentane}. The flash point measurements were carried out according to the standard test method (ASTM D3278) using a Stanhope-Seta closed cup flash point tester. The measured flash points were compared with the predicted values calculated using Raoult's law and also following $G^E$ models: Wilson, Non-Random Two Liquid (NRTL) and UNIversal QUAsiChemical (UNIQUAC). These models were able to predict the experimental flash points for different compositions of {$C_2{\sim}C_3$ alcohols + 2,2,4-trimethylpentane} mixtures with minimal deviations. The average absolute deviation between the predicted and measured lower flash point was less than 1.28 K. A minimum flash point behaviour was observed in all of the systems as in the many observed cases for the hydrocarbon and alcohol mixtures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.598-603
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• 2019

Three-dimensional shape measurement technology is used in various industries. Among them, optical three-dimensional shape measurement techniques based on the optical trigonometry are mainly used in the field of semiconductor product inspection, where large quantities of three-dimensional shape measurements are made daily in factories and fine measurements are also required. The light source and the drive circuit, which are components of three-dimensional measurement equipment based on this optical trigonometry, produce heat generated by prolonged operation, and may be exposed to conditions where the ambient temperature is not constant, resulting in temperature-induced measurement errors. In this study, the compensation method of the Thermal Errors for Phase Measuring Profilometry is proposed. Three-Dimensional Shape Measurement Equipment based on Phase Measuring Profilometry is implemented to measure the height of an object and ambient temperature for 10 Hours, and a regression line was obtained line by making simple linear regression using measured temperature and height values. This regression line was used to correct the error of the height measurement according to the temperature, and thermal error was from 139.88 um(Micrometer) to 13.12 um.

• Tunnel and Underground Space
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• v.29 no.3
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• pp.184-196
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• 2019

This study aims to extract a 3D image of micro-cracks generated by hydraulic fracturing tests, using the deep learning method and X-ray computed tomography images. The pixel-level cracks are difficult to be detected via conventional image processing methods, such as global thresholding, canny edge detection, and the region growing method. Thus, the convolutional neural network-based encoder-decoder network is adapted to extract and analyze the micro-crack quantitatively. The number of training data can be acquired by dividing, rotating, and flipping images and the optimum combination for the image augmentation method is verified. Application of the optimal image augmentation method shows enhanced performance for not only the validation dataset but also the test dataset. In addition, the influence of the original number of training data to the performance of the deep learning-based neural network is confirmed, and it leads to succeed the pixel-level crack detection.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.104-111
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• 2019

The purpose of this study is to know the change of brain wave with stress by SUKI pressure alternative therapy. The experiment group was 12 students(male 6/female 6) with complained upper trapezius pain. Calculated the brain wave before and after stimulate the upper trapezius trigger point by SUKI and the stimulate time was 3min each persons(FP2, F3, F4, FP1, T3, T4, P3, P4). the experimet periods was 5times in a weeks with EEG(QEEG-S). The Date collecting used by Telescan(LXE5209). All the data was analyzed with SPSS 22.0 for window program. To compare the differences before and after the point pressure method, a corresponding sample of t-test was performed, and the statistical significance level was p<.05. The results was followed. The points of Fp2, F3, F4(*p<0.049, *p<0.042, *p<0.019) of EEG was showed a significant differences but Fp1, T3, T4, P3, P4 points did not showed. The SUKI alternative medicine techniques had a reduced effects for the some kind of brain stress. It is need to continuous research in the future.

• 재활복지
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• v.21 no.3
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• pp.129-146
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• 2017

In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.783-791
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• 2018

The biased estimation of low density rainfall network and radar rainfall has limited application to extreme rainfall in a small area. To improve this, more rainfall information needs to be produced. In this study, we analyzed the applicability of the vehicle rainfall sensor developed and used recently. The developed rainfall sensor was attached to the vehicle to observe the rainfall according to the movement of the vehicle. The analytical method used time series and average rainfall values for observations of rainfall sensors and nearby rainfall stations. The results show that the trend of observed values according to rainfall events shows a certain pattern. It is analyzed that it is caused by various causes such as the difference between the observation position of the rainfall sensor and the nearby rainfall station, the moving speed of the vehicle, and the rainfall observation method. This result shows the possibility of rainfall observation using a rainfall sensor for a vehicle, and it is possible to observe rainfall more precisely through experiments and improvement of rainfall sensors in various conditions in the future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.1
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• pp.37-44
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• 2019

A bond-based peridynamic model has been reported dynamic fracture characteristic of brittle materials through a simple constitutive model. In the model, each bond is assumed to be a simple spring operating independently. As a result, this simple bond interaction modeling restricts the material behavior having a fixed Poisson's ratio of 1/4 and not being capable of expressing shear deformation. We consider a state-based peridynamics as a generalized peridynamic model. Constitutive models in the state-based peridynamics are corresponding to those in continuum theory. In state-based peridynamics, thus, the response of a material particle depends collectively on deformation of all bonds connected to other particles. So, a state-based peridynamic theory can represent the volume and shear changes of the material. In this paper, the perfect plasticity is considered to express plastic deformation of material by the state-based peridynamic constitutive model with perfect plastic flow rule. The elastic-plastic behavior of the material is verified through the stress-strain curves of the flat plate example. Furthermore, we simulate the high-speed impact on 3D granite model with a nonlocal contact modeling. It is observed that the damage patterns obtained by peridynamics are similar to experimental observations.