• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.80-84
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• 2014

The discharge characteristics of Surface Dielectric Barrier Discharge (SDBD) reactor are investigated to find optimal driving condition with adjusting various parameter. When the high voltage with sine wave form is applied to SDBD source, successive pulsed current waveforms are observed owing to multiple ignitions through the long discharge channel and wall charge accumulation on the dielectric surface. The discharge voltage, total charge between dielectrics, mean energy and power are calculated from measured current and voltage according to electrode gap and dielectric thickness. Discharge mode transition from filamentary to diffusive glow is observed for narrow gap and high applied voltage case. However, when the diffusive discharge is occurred with high applied voltage, the actual firing voltage is always lower than that with low driving voltage. The $Si_3N_4$, $MgF_2$, $Al_2O_3$ and $TiO_2$ are considered for dielectric protection and high secondary electron emission coefficient. SDBD with $MgF_2$ shows the lowest breakdown voltage. $MgF_2$ thin film is proposed as a protection layer for low voltage atmospheric dielectric barrier discharge devices.

• Proceedings of the KSR Conference
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• 2009.05b
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• pp.379-384
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• 2009

It is of great importance to assure the running safety and ride comfort in designing the floating slab track for the mitigation of train-induced vibration. In this paper, for this, analyzed are the system requirements for the running safety and ride comfort, and then, the behavior of train and track at the transition zone between the floating slab track and the conventional concrete slab track according to several main design variables such as spring constant, damping coefficient, spacing and arrangement of isolators and slab length, using the dynamic analysis technique considering the train-track interaction. The results of numerical analysis demonstrate that the discontinuity of the support stiffness at the transition results in a drastic increase of the vertical vibration acceleration of the train body, wheel-rail interaction force, rail bending stress and uplift force. The increase becomes higher with the decrease of the spring constant of isolators and the increase of the isolator spacing, but the damping ratio does not significantly affect the behavior of train and track at the transition. Therefore, to assure the running safety and ride comfort, simultaneously increasing the effectiveness of vibration isolation, it is effective to minimize the relative vertical offset between the floating slab and the conventional track slab by adjusting the spring constant and spacing of isolators at the transition.

• Journal of the Optical Society of Korea
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• v.15 no.1
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• pp.38-43
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• 2011

We have developed a simple model of a bright-room contrast ratio (BRCR) measurement system for plasma display panels (PDPs) adopting a contrast enhancement film (CEF) by using an illumination design tool. Only four model parameters were used, namely, total ambient illumination power delivered by fluorescent lamps, a panel scattering rate, illuminance of PDP white patterns, and the absorption coefficient of a color adjusting film. These parameters were determined by simple optical measurements and matching simulations. The proposed model was employed to predict the BRCR values of four different CEF samples, and the simulated ones were found to be in agreement with measured ones within about 10% relative-error.

• Structural Engineering and Mechanics
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• v.25 no.6
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• pp.717-732
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• 2007

A formula to approximate the fundamental period of a fixed-free mass-spring system with varying mass and varying stiffness is formulated. The formula is derived mainly by taking the dominant parts from the general form of the characteristic polynomial, and adjusting the initial approximation by a coefficient derived from the exact solution of a uniform case. The formula is tested for a large number of randomly generated structures, and the results show that the approximated fundamental periods are within the error range of 4% with 90% of confidence. Also, the error is shown to be normally distributed with zero mean, and the width of the distribution (as measured by the standard deviation) tends to decrease as the total number of discretized elements in the system increases. Other possible extensions of the formula are discussed, including an extension to a continuous cantilever structure with distributed mass and stiffness. The suggested formula provides an efficient way to estimate the fundamental period of building structures and other systems that can be modeled as mass-spring systems.

• Korean Journal of Materials Research
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• v.33 no.4
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• pp.164-174
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• 2023

The bandgap characteristics of semiconductor materials are an important factor when utilizing semiconductor materials for various applications. In this study, based on data provided by AFLOW (Automatic-FLOW for Materials Discovery), the bandgap of a semiconductor material was predicted using only the material's compositional features. The compositional features were generated using the python module of 'Pymatgen' and 'Matminer'. Pearson's correlation coefficients (PCC) between the compositional features were calculated and those with a correlation coefficient value larger than 0.95 were removed in order to avoid overfitting. The bandgap prediction performance was compared using the metrics of R² score and root-mean-squared error. By predicting the bandgap with randomforest and xgboost as representatives of the ensemble algorithm, it was found that xgboost gave better results after cross-validation and hyper-parameter tuning. To investigate the effect of compositional feature selection on the bandgap prediction of the machine learning model, the prediction performance was studied according to the number of features based on feature importance methods. It was found that there were no significant changes in prediction performance beyond the appropriate feature. Furthermore, artificial neural networks were employed to compare the prediction performance by adjusting the number of features guided by the PCC values, resulting in the best R² score of 0.811. By comparing and analyzing the bandgap distribution and prediction performance according to the material group containing specific elements (F, N, Yb, Eu, Zn, B, Si, Ge, Fe Al), various information for material design was obtained.

• Analytical Science and Technology
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• v.20 no.1
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• pp.55-60
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• 2007

A sensitive technique for the determination of trace Cu(II) in various samples after the column preconcentration by adsorbing its N-benzoylphenylhydroxylamine (BPHA) onto benzophenone was developed. Several experimental conditions such as the pH of the sample solution, the amount of chelating agent, the amount of benzophenone, and the flowrate of sample solution and so forth were optimized. The interfering effects of diverse concomitant ions were investigated. Fe(III) and $CN^-$ interfered with more seriously than any other ions. However, the interference by these ions could be overcome sufficiently by adjusting the added volume of 0.01M BPHA to 10 mL. The dynamic range, the correlation coefficient ($r^2$) and the detection limit obtained by this proposed technique were 5.0~120 ng/mL, 0.9974, and 2.1 ng/mL, respectively. For validating this proposed technique, the aqueous samples (stream water, reservoir water, and wastewater), the plastic sample and the diluted brass sample were used. Recovery yields of 93~102% were obtained. These measured data were not different from ICP-MS data at 95% confidence level. This method was also validated by the rice flour CRM (normal, fortified) samples. Based on the results from the experiment, it was found that this proposed technique could be applied to the determination of Cu(II) in various real samples.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.142-142
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• 2022

Adjusting weather radar data is a prerequisite for its use in various hydrological studies. Effect of spatial variables are considered to adjust weather radar data in many of these researches. The existence of diverse topography in South Korea has increased the importance of analyzing these variables. In this study, some spatial variable like slope, elevation, aspect, distance from the sea, plan and profile curvature was considered. To investigate different topographic conditions, tried to use three radar station of Gwanaksan, Gwangdeoksan and Gudeoksan which are located in northwest, north and southeast of South Korea, respectively. To form the suitable fuzzy model and create the best membership functions of variables, ANFIS-PSO model was applied. After optimizing the model, the correlation coefficient and sensitivity of adjusted Quantitative Precipitation Estimation (QPE) based on spatial variables was calculated to find how variables work in adjusted QPE process. The results showed that the variable of elevation causes the most change in rainfall and consequently in the adjustment of radar data in model. Accordingly, the sensitivity ratio calculated for variables shows that with increasing rainfall duration, the effects of these variables on rainfall adjustment increase. The approach of this study, due to the simplicity and accuracy of this method, can be used to adjust the weather radar data and other required models.

• Safety and Health at Work
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• v.15 no.2
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• pp.147-150
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• 2024

Background: We examined the association between supervisor consultation, as an actual practice representing supervisor support, and work engagement. Methods: This was a prospective cohort study in Japan, involving 14,026 participants who met the requirement for a one-year follow-up. Supervisor consultation was measured using a single question, and work engagement was defined using the Japanese version of the nine-item Utrecht Work Engagement Scale (UWES-9). Associations were examined using linear regression analysis. Results: Supervisor consultation was positively associated with work engagement after adjusting for gender, age, education, income, and industry (𝛽 = 3.474; p < 0.001). The relationship remained significant after adjustment for perceived supervisor support, although the coefficient decreased (𝛽 = 1.315; p < 0.001). Conclusion: Supervisor consultation probably acted on work engagement in different ways than perceived supervisor support.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.71-81
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• 2008

Our objective was to evaluate the image of spatial domain filtering as an alternative to additional image reconstruction using different kernels in MDCT. Derived from thin collimated source images were generated using water phantom and abdomen B10(very smooth), B20(smooth), B30(medium smooth), B40 (medium), B50(medium sharp), B60(sharp), B70(very sharp) and B80(ultra sharp) kernels. MTF and spatial resolution measured with various convolution kernels. Quantitative CT attenuation coefficient and noise measurements provided comparable HU(Hounsfield) units in this respect. CT attenuation coefficient(mean HU) values in the water were values in the water were $1.1{\sim}1.8\;HU$, air($-998{\sim}-1000\;HU$) and noise in the water($5.4{\sim}44.8\;HU$), air($3.6{\sim}31.4\;HU$). In the abdominal fat a CT attenuation coefficient($-2.2{\sim}0.8\;HU$) and noise($10.1{\sim}82.4\;HU$) was measured. In the abdominal was CT attenuation coefficient($53.3{\sim}54.3\;HU$) and noise($10.4{\sim}70.7\;HU$) in the muscle and in the liver parenchyma of CT attenuation coefficient($60.4{\sim}62.2\;HU$) and noise ($7.6{\sim}63.8\;HU$) in the liver parenchyma. Image reconstructed with a convolution kernel led to an increase in noise, whereas the results for CT attenuation coefficient were comparable. Image scanned with a high convolution kernel(B80) led to an increase in noise, whereas the results for CT attenuation coefficient were comparable. Image medications of image sharpness and noise eliminate the need for reconstruction using different kernels in the future. Adjusting CT various kernels, which should be adjusted to take into account the kernels of the CT undergoing the examination, may control CT images increase the diagnostic accuracy.

• Smart Media Journal
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• v.11 no.2
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• pp.77-83
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• 2022

The neuromorphic architecture uses a spiking neural network (SNN) model to derive more accurate results as more spike values are accumulated through inference experiments. When the inference result converges to a specific value, even if the inference experiment is further performed, the change in the result is smaller and power consumption may increase. In particular, in an AI-based IoT environment, power consumption can be a big problem. Therefore, in this paper, we propose a technique to reduce the power consumption of AI-based IoT by reducing the inference time by adjusting the inference image exposure time in the neuromorphic architecture environment. The proposed technique calculates the next inferred image exposure time by reflecting the change in inference accuracy. In addition, the rate of reflection of the change in inference accuracy can be adjusted with a coefficient value, and an optimal coefficient value is found through a comparison experiment of various coefficient values. In the proposed technique, the inference image exposure time corresponding to the target accuracy is greater than that of the linear technique, but the overall power consumption is less than that of the linear technique. As a result of measuring and evaluating the performance of the proposed method, it is confirmed that the inference experiment applying the proposed method can reduce the final exposure time by about 90% compared to the inference experiment applying the linear method.