• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.144-145
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• 2006

ZnO is a promising material to make high efficiency violet or blue light emitting diodes (LEDs) for its large binding energy (60meV) and big bandgap. But the high quality p-type conduction of ZnO is a dilemma to achieve LEDs with it. In present study, we presented a reliable method to prepare ZnO thin films on (100)silicon substrates by RF magnetron sputtering in the mixture ambient of $N_2$ and $O_2$, accompanying with low pressure annealing in the sputtering chamber in $O_2$ at $600^{\circ}C$ and $800^{\circ}C$ respectively. X-ray diffraction and Hail effect with Van der Paul method were performed to test ZnO films. Seeback effect was also carried out to identify carrier types in ZnO films and showed the N-doped ZnO film annealed at $800^{\circ}C$ had achieved p-type conduction.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.9
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• pp.121-126
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• 2009

Stainless steel 316L (STS 316L) is widely used as a material of biopsy needle. However it has a side effect that tissue can be damaged by electrochemical operation between tissue and STS 316L. Many studies have been made on the ceramic coating of biopsy needle to reduce the side effect. In this study, STS 316L was coated with three bioceramics, $Al_2O_3$, $SiO_2$ and $ZrO_2$ using a RF magnetron sputtering method. The effects of ceramic coating on the electrical conductivity and coating strength of ceramic-coated STS 316L were investigated. The results showed that the electrical conductivity of ceramic-coated STS 316L was much lower than that of uncoated STS 316L. The coating strength of $ZrO_2$-coated STS 316L was 30% and 70% higher, respectively than those of $Al_2O_3$-coated STS 316L and $SiO_2_3$-coated STS 316L.

• Geomechanics and Engineering
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• v.32 no.3
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• pp.271-291
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• 2023

Settlement estimation in cohesion materials is a crucial topic to tackle because of the complexity of the cohesion soil texture, which could be solved roughly by substituted solutions. The goal of this research was to implement recently developed machine learning features as effective methods to predict settlement (S_m) of shallow foundations over cohesion soil properties. These models include hybridized support vector regression (SVR), random forests (RF), and coot optimization algorithm (COM), and black widow optimization algorithm (BWOA). The results indicate that all created systems accurately simulated the S_m, with an R² of better than 0.979 and 0.9765 for the train and test data phases, respectively. This indicates extraordinary efficiency and a good correlation between the experimental and simulated S_m. The model's results outperformed those of ANFIS - PSO, and COM - RF findings were much outstanding to those of the literature. By analyzing established designs utilizing different analysis aspects, such as various error criteria, Taylor diagrams, uncertainty analyses, and error distribution, it was feasible to arrive at the final result that the recommended COM - RF was the outperformed approach in the forecasting process of S_m of shallow foundation, while other techniques were also reliable.

• Journal of the Korean Institute of Gas
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• v.2 no.4
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• pp.34-41
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• 1998

To oxide film, $A1_2O_3,\;Ta_2O_5$ and $ZrO_2$, coated on stainless steel (SUS410, SUS304) and pure Fe using RF magnetron sputtering method, the corrosion resistance on oxide coatings was studied using electrochemical measurement. Also, the adherence between film and substarte was studied. The adherence index ( $\chi$ ) was determined by the measure of micro hardness test. In this paper, we know that oxide film coated on SUS304 have better corrosion resistance than that coated on SUS410. In oxide film, the difference of corrosion resistance due to crystal structure have not been showed. In evaluating defect area rate of ceramic coated materials, CPCD method can be used effectively. In the micro-hardness test, with $1{\mu}m$ thickness film, it has only one the value of $\chi$. Above $2{\mu}m$ thickness film, however, get another value of $\chi$ as the cracks in film. The oxide film adhere well on the mild materials such as pure steel than high intensity materials like stainless.

• Water for future
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• v.28 no.6
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• pp.183-191
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• 1995

Applying microwave, a velocity measurement system has been developed in order to measure the velocity of stream water surface. It's main purpose is the measurement for high velocity of flood water. It is under the developing stage of experimental measurement system. The microwave surface velocity meter uses Doppler effects of microwave. It consists of a radio frequency(RF) part and that of signal processing. Thr RF part has the function of microwave oscillation, reception of reflected wave, and determination of Doppler frequency, etc. Signal processing designates amplification, fast Fourier transform, etx. Various measuring experiments were performed at bridges and a spillway of Taechong re-regulation dam with the microwave velocity meter. Verification test was also made through water tank of ship model test at Research Institute of Ships and Ocean Engineering. It shows 4% error inherent in A/D converter and additional several percentage errors from measurement circumstance. The measuring ranges are from 0.5 to 3.5 m/s. The result shows good linear relationship between carriage velocity and measured velocity, thus proves usefulness as a measuring instrument for flood water velocity. The instrument requires overall re-engineering procedure and number of data should be accumulated and analyzed to treat wind effects and random fluctuations of water surface.

• Korean Journal of Applied Biomechanics
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• v.34 no.1
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• pp.25-33
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• 2024

Objective: The purpose of this study was to compare the lower extremity muscle activity and knee joint load according to movement speed conditions during the barbell back squat. Method: Nine males with resistance training experience participated in this study. Participants performed the barbell back squat in three conditions (Standard, Fast, and Slow) differing movement speed. During the barbell back squat, muscle activity of the rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM), biceps femoris long head (BFL), semitendinosus (ST), gluteus maximus (GM), gastrocnemius (GCN), and tibialis anterior (TA) was collected using an 8 channel wireless EMG system. The peak flexion angle of the lower extremity joints and the peak resultant joint force in each direction of the knee joint were calculated using eight motion capture cameras and ground reaction force plates. This study was to used the Friedman test and the Wilcoxon signed rank test, to compare lower extremity muscle activity and peak resultant joint force at knee joint according to movement speed conditions during the barbell back squat, and the statistical significance level was set at .01. Results: In the downward phase of the barbell back squat, the RF and TA showed the higher muscle activity in the fast condition, and in the upward phase, RF, VL, VM, BFL, ST, GM, and TA showed the higher muscle activity in the fast condition. As a results, analyzing of the load on the knee joint, in the downward phase, and in the upward phase, the higher peak compressive force of the knee joint was showed in the fast condition. Conclusion: The barbell back squat with fast movement speed was more effective due to increased muscle activity of lower extremity, but one must be careful of knee joint injuries because the load on the knee joint may increase during the barbell back squat with fast movement speed.

• 전자공학회논문지 IE
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• v.45 no.1
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• pp.31-37
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• 2008

A Wibro RF down converter of 2.3GHz band is designed and implemented in this paper. The problems that can occur in the receiver LNA(Low Noise Amplifier) to minimize additional purposes. In addition, 2.3GHz band from the 75 MHz downward to minimize the losses in the process, transform and improve efficiency, and achieve stable characteristics can be used to make high frequency characteristics of the device. Wibro repeater uses a TDMA(Time Division Multiplexing Access) method is needed because the RF switch. Production criterion specification, the input voltage from +8 V 1.2A of current consumption, 60dB gain and the noise figure of less than 2.5dB, VSWR(Voltage Standing Wave Ratio) less than 1.5, more than IMD(Inter Modulation Distortion) 60dB satisfied. Environmental conditions ($-20^{\circ}C$ to $70^{\circ}C$) to pass the test of reliability in a long time, that seemed crafted Wibro down converter be applied to the Wibro repeater.

• Journal of radiological science and technology
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• v.38 no.2
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• pp.155-161
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• 2015

This study confirmed the correlation between the change of the cooling water in internal cooling system and the size of the ablation site of bovine liver in RF heat treatment equipment. The bovine liver was resection with $4{\times}4{\times}4cm^3$ in 2cm cool-tip and with $6{\times}6{\times}6cm^3$ in 3cm cool-tip for the experiments. Area and perimeter of the ablation site for bovine liver were measured by Freehand techniques of MRI. It showed area and perimeter decreased during cool-tip temperature rises 6 and 12 minutes ablation using a 2cm and 3cm cool-tip. The correlation of cool-tip temperature and area and perimeter was statistically significant the result are shown(p=.000). The measurements of area and perimeter were more accurate with MRI in actual measurements and MRI for ablation range. The statistical results using Paired sample T-test was also significant(p=.038). The ablation range of bovine liver decreased according as cooling water temperature increases in RF heat treatment equipment for reason of carbonization occurred due to does not accurately pass the RF energy. Therefore, it is considered the effect of RF heat treatment would be increased if the temperature of the cooling water consistently maintain the low temperature in order to reduce the generation of carbide at RF heat treatment and RF energy is delivered accurately.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.351-361
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• 2021

The seriousness of fire is rising because fire causes enormous damage to property and human life. Therefore, this study aims to predict various risk factors affecting fire by fire type. The predictive analysis of fire factors was carried out targeting Gyeonggi-do, which has the highest number of fires in the country. For the analysis, using machine learning methods SVM (Support Vector Machine), RF (Random Forest), GBRT (Gradient Boosted Regression Tree) the accuracy of each model was presented with a high fit model through MAE (Mean Absolute Error) and RMSE (Root Mean Squared Error), and based on this, predictive analysis of fire factors in Gyeonggi-do was conducted. In addition, using machine learning methods such as SVM (Support Vector Machine), RF (Random Forest), and GBRT (Gradient Boosted Regression Tree), the accuracy of each model was presented with a high-fit model through MAE and RMSE. Predictive analysis of occurrence factors was achieved. Based on this, as a result of comparative analysis of three machine learning methods, the RF method showed a MAE = 1.765 and RMSE = 1.876, as well as the MAE and RMSE verification and test data were very similar with a difference between MAE = 0.046 and RMSE = 0.04 showing the best predictive results. The results of this study are expected to be used as useful data for fire safety management allowing decision makers to identify the sequence of dangers related to the factors affecting the occurrence of fire.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.2
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• pp.217-230
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• 2022

The adequate control of TBM face pressure is of vital importance to maintain face stability by preventing face collapse and surface settlement. An EPB shield TBM excavates the ground by applying face pressure with the excavated soil in the pressure chamber. One of the challenges during the EPB shield TBM operation is the control of face pressure due to difficulty in managing the excavated soil. In this study, the face pressure of an EPB shield TBM was predicted using the geological and operational data acquired from a domestic TBM tunnel site. Four machine learning algorithms: KNN (K-Nearest Neighbors), SVM (Support Vector Machine), RF (Random Forest), and XGB (eXtreme Gradient Boosting) were applied to predict the face pressure. The model comparison results showed that the RF model yielded the lowest RMSE (Root Mean Square Error) value of 7.35 kPa. Therefore, the RF model was selected as the optimal machine learning algorithm. In addition, the feature importance of the RF model was analyzed to evaluate appropriately the influence of each feature on the face pressure. The water pressure indicated the highest influence, and the importance of the geological conditions was higher in general than that of the operation features in the considered site.