• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.45 no.6
• /
• pp.22-27
• /
• 2008

Analytical models for breakdown voltage and specific on-resistance of 4H-silicon carbide Schottky diodes have been derived successfully by extracting an effective ionization coefficient $\gamma$ from ionization coefficients $\alpha$ and $\beta$ for electron and hole in 4H-SiC. The breakdown voltages extracted from our analytical model are compared with experimental results. The specific on-resistance as a function of doping concentration is also compared with the ones reported previously. Good fits with the experimental results are found for the breakdown voltage within 10% in error for the doping concentration in the range of about $10^{15}{\sim}10^{18}\;cm^{-3}$. The analytical results show good agreement with the experimental data for the specific on-resistance in the range of $3{\times}10^{15}{\sim}2{\times}10^{16}\;cm^{-3}$.

• Journal of Korean Association for Spatial Structures
• /
• v.7 no.6
• /
• pp.61-68
• /
• 2007

The hole for the insertion of the pin in the shank is exist at ball joint connection of the space frame. It brings about the brittle fracture caused by stress concentration. Consequently it cannot expect the deformation performance or energy absorption performance from ball joint connection. In this study we developed a new connection details which will increase the plastic deformation performance at ball joint connection and can absorb the error in construction, which expect the plastic deformation performance at the reduced shank without brittle fracture at the screw of bolt and pin. Also it's capacity is verified by the performance in numerical analysis and test. We confirmed bolt's plastic deformantion performance through controled shank and pin's area.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.26 no.5
• /
• pp.315-320
• /
• 2006

This paper describes stress analysis and fatigue limit evaluation of plate with V-notch and hole-notch by lock-in infrared thermography. Temperature variation of a specimen under cyclic loading is negatively proportional to the sum of principle stress change and the surface temperature measured by infrared camera is calculated to the stress of notch specimens, based on thermoelastic equation. And also, fatigue limitation can be evaluated by the change of intrinsic energy dissipation. Fatigue limitation of two notch specimens is evaluated as 164 MPa and 185 MPa, respectively and the stress measured by Lock-in infrared Thermography show good agreement within 10% error.

• Journal of Korean Society of Water and Wastewater
• /
• v.32 no.5
• /
• pp.461-470
• /
• 2018

In this study, the leak signal was measured by using an accelerometer to analyze the basic data and methodology for the development of the leak point estimation method in the water supply pipe. The measured results were analyzed by frequency analysis and cross-correlation analysis for leakage signals, and the error range was compared and analyzed with the actual leak point distance. As a result, it was confirmed that the vibration intensity due to leakage from the water leakage point was attenuated according to the distance. In the case of the ductile iron casting used in the experiment, the intensity of the signal at the 945 Hz, 1,500 Hz, 2,300 Hz band was increased with the change of the pressure in the pipe at 4mm of leakage hole. Also, it was confirmed that as the water pressure increases, the intensity of the leak signal increases but the similarity of the signal decreases. The results of this study confirm that the accelerometer sensor can be used efficiently for leak detection and it can be used as a basic data for the analysis for the development of leak point estimation method in the future.

• Smart Media Journal
• /
• v.1 no.3
• /
• pp.29-35
• /
• 2012

A depth image-based rendering (DIBR) technique is one of the rendering processes of virtual views with a color image and the corresponding depth map. The most important issue of DIBR is that the virtual view has no information at newly exposed areas, so called dis-occlusion. In this paper, we propose an intermediate view generation algorithm using the Kinect depth camera that utilizes the infrared structured light. After we capture a color image and its corresponding depth map, we pre-process the depth map. The pre-processed depth map is warped to the virtual viewpoint and filtered by median filtering to reduce the truncation error. Then, the color image is back-projected to the virtual viewpoint using the warped depth map. In order to fill out the remaining holes caused by dis-occlusion, we perform a background-based image in-painting operation. Finally, we obtain the synthesized image without any dis-occlusion. From experimental results, we have shown that the proposed algorithm generated very natural images in real-time.

• Smart Media Journal
• /
• v.2 no.4
• /
• pp.27-33
• /
• 2013

Multi-view video system provides both realistic 3D feelings and free-view navigation. But it is hard to transmit too huge data, so we send only two or three view images and generate intermediate view image using depth information. In this paper, we propose high quality multi-view image generation method from stereoscopic images. Since the stereo matching method does not provide accurate disparity values for all the pixels, especially at the occlusion area, we propose an occlusion handling method using the background pixels at first. We also apply a joint bilateral filtering to enhance the disparity map at the object boundary since it can affect the quality of synthesized images significantly. Finally, we can generate virtual view images at intermediate view positions using confidence map to reduce bad pixel and hole's error. Experimental results show the proposed method performs better than the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.1A
• /
• pp.65-75
• /
• 2009

In Wireless Sensor Network, the sensor node localization is important issue for information tracking, event detection, routing. Generally, in wireless sensor network localization, the absolute positions of certain anchor nodes are required based on the use of global positioning system, then all the other nodes are approximately localized using various algorithms based on a coordinate system of anchor DV-Hop is a localized, distributed, hop by hop positioning algorithm in wireless sensor network where only a limited fraction of nodes have self positioning capability. However, instead of uniformly distributed network, in anisotropic network with possible holes, DV-Hop's performance is very low. To address this issue, we propose Group based DV-Hop (GDV-Hop) algorithm. Best contribution of GDV-Hop is that it performs localization with reduced error compared with DV-Hop in anisotropic network.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.12
• /
• pp.152-158
• /
• 2001

In this paper, we have developed an electro discharge machine for micro drilling driven by a voice coil actuator. Because the voltage signal of the electro-discharging circuit shows a lot of peaks and valleys, the active type low-pass filtering technique is adopted to get the average of the signal. Since the motion of the voice coil is precisely controlled by the error value between the object voltage value and the measured one, it is possible to prevent the mechanical contact between the rotating electrode and the workpiece and to maintain the appropriate machining conditions during the process. The electro-chemical machining technology was also adopted to make small diameter electrodes. Pure water is used as a dielectric. The machining procedure is performed to verify the feasibility of the developed system. It takes about 10 seconds to drill the ${\phi}m$100${\mu}m$ hole to the 100${\mu}m$ thickness stainless steel plate. The machining time depends on the values of the resister and the capacitor. There may exist the optimal values of time constant and the tendency is displayed In the appendix.

• Safety and Health at Work
• /
• v.6 no.4
• /
• pp.268-278
• /
• 2015

Background: This study aimed to assess the whole-body vibration (WBV) exposure among large blast hole drill machine operators with regard to the International Organization for Standardization (ISO) recommended threshold values and its association with machine- and rock-related factors and workers' individual characteristics. Methods: The study population included 28 drill machine operators who had worked in four opencast iron ore mines in eastern India. The study protocol comprised the following: measurements of WBV exposure [frequency weighted root mean square (RMS) acceleration ($m/s^2$)], machine-related data (manufacturer of machine, age of machine, seat height, thickness, and rest height) collected from mine management offices, measurements of rock hardness, uniaxial compressive strength and density, and workers' characteristics via face-to-face interviews. Results: More than 90% of the operators were exposed to a higher level WBV than the ISO upper limit and only 3.6% between the lower and upper limits, mainly in the vertical axis. Bivariate correlations revealed that potential predictors of total WBV exposure were: machine manufacturer (r = 0.453, p = 0.015), age of drill (r = 0.533, p = 0.003), and hardness of rock (r = 0.561, p = 0.002). The stepwise multiple regression model revealed that the potential predictors are age of operator (regression coefficient ${\beta}=-0.052$, standard error SE = 0.023), manufacturer (${\beta}=1.093$, SE = 0.227), rock hardness (${\beta}=0.045$, SE = 0.018), uniaxial compressive strength (${\beta}=0.027$, SE = 0.009), and density (${\beta}=-1.135$, SE = 0.235). Conclusion: Prevention should include using appropriate machines to handle rock hardness, rock uniaxial compressive strength and density, and seat improvement using ergonomic approaches such as including a suspension system.

• Journal of ILASS-Korea
• /
• v.27 no.2
• /
• pp.57-65
• /
• 2022

The purpose of this study is to use machine learning to build a model capable of predicting the flash boiling spray characteristics. In this study, the flash boiling spray was visualized using Shadowgraph visualization technology, and then the spray image was processed with MATLAB to obtain quantitative data of spray characteristics. The experimental conditions were used as input, and the spray characteristics were used as output to train the machine learning model. For the machine learning model, the XGB (extreme gradient boosting) algorithm was used. Finally, the performance of machine learning model was evaluated using R² and RMSE (root mean square error). In order to have enough data to train the machine learning model, this study used 12 injectors with different design parameters, and set various fuel temperatures and ambient pressures, resulting in about 12,000 data. By comparing the performance of the model with different amounts of training data, it was found that the number of training data must reach at least 7,000 before the model can show optimal performance. The model showed different prediction performances for different spray characteristics. Compared with the upstream spray angle and the downstream spray angle, the model had the best prediction performance for the spray tip penetration. In addition, the prediction performance of the model showed a relatively poor trend in the initial stage of injection and the final stage of injection. The model performance is expired to be further enhanced by optimizing the hyper-parameters input into the model.