• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1464-1471
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• 1999

A wide-band high power amplifier to use for radiated electromagnetic field immunity testing of EMS(Electromagnetic Susceptibility) standards has to meet IEC1000-4-3 specification in the frequency bandwidth of 80MHz to 1000MHz. The power amplifier to be described in this paper consists of driving and power stages with wide-band matched circuits by estimated impedances. The mismatching protection circuit is inserted in it to prevent from damage of power device when the output port of power amplifier is opened or shorted by user's mistake. The characteristics of the power amplifier are obtained output power over 100watts, gain over 40dB and flatness of $\pm$0.3dB in the frequency range of 80 ~300MHz. The harmonics suppression characteristics is measured over 20dBc. This wide-band high power amplifier can be useful fur radiated electromagnetic field immunity testing of IEC 1000-4-3 standard.

• Advances in materials Research
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• v.13 no.1
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• pp.63-86
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• 2024

Asphalt concrete (AC), is a mixture of bitumen and aggregates, which is very sensitive in the design of flexible pavement. In this study, the Marshall stability of the glass and carbon fiber bituminous concrete was predicted by using Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and M5P Tree machine learning algorithms. To predict the Marshall stability, nine inputs parameters i.e., Bitumen, Glass and Carbon fibers mixed in 100:0, 75:25, 50:50, 25:75, 0:100 percentage (designated as 100GF:0CF, 75GF:25CF, 50GF:50 CF, 25GF:75CF, 0GF:100CF), Bitumen grade (VG), Fiber length (FL), and Fiber diameter (FD) were utilized from the experimental and literary data. Seven statistical indices i.e., coefficient of correlation (CC), mean absolute error (MAE), root mean squared error (RMSE), relative absolute error (RAE), root relative squared error (RRSE), Scattering index (SI), and BIAS were applied to assess the effectiveness of the developed models. According to the performance evaluation results, Artificial neural network (ANN) was outperforming among other models with CC values as 0.9147 and 0.8648, MAE values as 1.3757 and 1.978, RMSE values as 1.843 and 2.6951, RAE values as 39.88 and 49.31, RRSE values as 40.62 and 50.50, SI values as 0.1379 and 0.2027 and BIAS value as -0.1 290 and -0.2357 in training and testing stage respectively. The Taylor diagram (testing stage) also confirmed that the ANN-based model outperforms the other models. Results of sensitivity analysis showed that the fiber length is the most influential in all nine input parameters whereas the fiber combination of 25GF:75CF was the most effective among all the fiber mixes in Marshall stability.

• KSTLE International Journal
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• v.3 no.1
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• pp.38-42
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• 2002

Diamond-like Carbon(DLC) films were deposited on Si wafers by an RF-plasma-assisted CVD using CH$_4$gas. Tribological tests were conducted with the use of a rotating type ball on a disk friction tester with dry air. This study made use of four kinds of mating balls that were made with stainless steel but subjected to different annealing conditions in order to achieve different levels of hardness. In all load conditions, testing results demonstrated that the harder the mating materials, the lower the friction coefficient was. The friction coefficients were fecund to be lower with austenite mating balls than with fully annealed martensite balls. Conversely, the high friction coefficient found in soft martensite balls appeared to be caused by the larger contact area between the DLC film and the ball. The wear tracks on DLC films and mating balls could prove that effect. Measuring the wear track of both DLC films and mating balls revealed a similar tendency compared to the results of friction coefficients. The wear rate of austenite balls was also less than that of fully annealed martensite balls. Friction eoefficients decrease when applied leads exceed critical amount. The wear track on mating balls showed that a certain amount of material transfer occurs from the DLC film to the mating ball during a high friction process. Raman Spectra analysis Showed that the transferred materials were a kind of graphite and that the contact surface of the DLC film seemed to undergo a phase transition from carbon to graphite during the high friction process.

• ETRI Journal
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• v.33 no.3
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• pp.335-343
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• 2011

The pad pitch of modern radio frequency integrated circuits is in the order of few tens of micrometers. Connecting a large number of high-speed I/Os to the outside world with good signal fidelity at low cost is an extremely challenging task. To cope with this requirement, we need reflection-free transmission lines from an on-chip pad to on-board SMA connectors. Such a transmission line is very hard to design due to the difference in on-chip and on-board feature size and the requirement for extremely large bandwidth. In this paper, we propose the use of narrow tracks close to chip and wide tracks away from the chip. This narrow-to-wide transition in width results in impedance discontinuity. A step change in substrate thickness is utilized to cancel the effect of the width discontinuity, thus achieving a reflection-free microstrip. To verify the concept, several microstrips were designed on multilayer FR4 PCB without any additional manufacturing steps. The TDR measurements reveal that the impedance variation is less than 3 ${\Omega}$ for a 50 ${\Omega}$ microstrip and S11 better than -9 dB for the frequency range 1 GHz to 6 GHz when the width changes from 165 ${\mu}m$ to 940 ${\mu}m$, and substrate thickness changes from 100 ${\mu}m$ to 500 ${\mu}m$.

• Journal of Applied Reliability
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• v.11 no.3
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• pp.251-265
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• 2011

Low-noise amplifier(LNA) is a component that amplifies the signal while lowering the noise figure of high-frequency signal. LNA holds a very important position in RF system so that it is widely used for telecommunication. Electro static discharge(ESD) is the most common cause of malfunction for low-powered components, such as Large Scale Integration and IC type LNA is weak in ESD. This thesis studies static effect of communication LNA. It analyzes ESD effect, which occurs within LNA circuit, and describes testing standard and methods. In order to find out LNA's susceptiblity to electro static, two well-recognized communication IC type LNA models were selected to be tested. Then static-induced malfunction was carefully analyzed and it suggests architectural problem and improvement from the LNA's ESD point of view.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.157-163
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• 2019

A small millimeter-wave tracking radar is a pulse radar that searches, detects, and tracks a target in real time through a TWS (Track While Scan) method on a sea-going traps target with a large RCS running at low speed. This paper describes the development of a simulated signal generator to verify the performance of a small millimeter wave tracking radar in laboratory anechoic chamber environment. We describe a GUI program for testing and performance analysis in conjunction with hardware configuration and tracking radar, and verified the simulated signal generator implemented through performance test.

• Advances in materials Research
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• v.11 no.1
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• pp.75-90
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• 2022

In this paper, functionality of soft computing algorithms such as Group method of data handling (GMDH), Random forest (RF), Random tree (RT), Linear regression (LR), M5P, and artificial neural network (ANN) have been looked out to predict the compressive strength of concrete mixed with marble powder. Assessment of result suggests that, the overall performance of ANN based model gives preferable results over the different applied algorithms for the estimate of compressive strength of concrete. The results of coefficient of correlation were maximum in ANN model (0.9139) accompanied through RT with coefficient of correlation (CC) value 0.8241 and minimum root mean square error (RMSE) value of ANN (4.5611) followed by RT with RMSE (5.4246). Similarly, other evaluating parameters like, Willmott's index and Nash-sutcliffe coefficient value of ANN was 0.9458 and 0.7502 followed by RT model (0.8763 and 0.6628). The end result showed that, for both subsets i.e., training and testing subset, ANN has the potential to estimate the compressive strength of concrete. Also, the results of sensitivity suggest that the water-cement ratio has a massive impact in estimating the compressive strength of concrete with marble powder with ANN based model in evaluation with the different parameters for this data set.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1708-1717
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• 2023

The grade analysis of lead-zinc ore is the basis for the optimal development and utilization of deposits. In this study, a method combining Prompt Gamma Neutron Activation Analysis (PGNAA) technology and machine learning is proposed for lead-zinc mine borehole logging, which can identify lead-zinc ores of different grades and gangue in the formation, providing real-time grade information qualitatively and semi-quantitatively. Firstly, Monte Carlo simulation is used to obtain a gamma-ray spectrum data set for training and testing machine learning classification algorithms. These spectra are broadened, normalized and separated into inelastic scattering and capture spectra, and then used to fit different classifier models. When the comprehensive grade boundary of high- and low-grade ores is set to 5%, the evaluation metrics calculated by the 5-fold cross-validation show that the SVM (Support Vector Machine), KNN (K-Nearest Neighbor), GNB (Gaussian Naive Bayes) and RF (Random Forest) models can effectively distinguish lead-zinc ore from gangue. At the same time, the GNB model has achieved the optimal accuracy of 91.45% when identifying high- and low-grade ores, and the F₁ score for both types of ores is greater than 0.9.

• Steel and Composite Structures
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• v.46 no.2
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• pp.153-173
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• 2023

Rectangular concrete-filled steel tubular (RCFST) column, a type of concrete-filled steel tubular (CFST), is widely used in compression members of structures because of its advantages. This paper proposes a robust machine learning-based framework for predicting the ultimate compressive strength of RCFST columns under both concentric and eccentric loading. The gradient boosting neural network (GBNN), an efficient and up-to-date ML algorithm, is utilized for developing a predictive model in the proposed framework. A total of 890 experimental data of RCFST columns, which is categorized into two datasets of concentric and eccentric compression, is carefully collected to serve as training and testing purposes. The accuracy of the proposed model is demonstrated by comparing its performance with seven state-of-the-art machine learning methods including decision tree (DT), random forest (RF), support vector machines (SVM), deep learning (DL), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and categorical gradient boosting (CatBoost). Four available design codes, including the European (EC4), American concrete institute (ACI), American institute of steel construction (AISC), and Australian/New Zealand (AS/NZS) are refereed in another comparison. The results demonstrate that the proposed GBNN method is a robust and powerful approach to obtain the ultimate strength of RCFST columns.

• Clinical and Experimental Pediatrics
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• v.46 no.9
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• pp.898-902
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• 2003

Purpose : To determine the clinical association of diagnostic criteria and the prevalence of autoantibodies in newly diagnosed children with juvenile dermatomyositis(JDM). Methods : Thirty-two children with JDM were identified at Seoul National University Children's Hospital from March 1985 to March 1999 by retrospective review. The diagnosis of JDM was based on the criteria proposed by Bohan and Peter. We investigated for the presence of several autoantibodies: antinuclear(ANA), double-stranded DNA, anti-Sm, anti-ribonucleoprotein(RNP), anti-SSA/ SSB, anti-Jo1, anti-Scl-70 antibodies and rheumatoid factor(RF). Results : Sex ratio and age at diagnosis were similar to data published in other studies. All the newly diagnosed children with JDM had a typical rash(100%) and proximal muscle weakness(100%); 17(53%) had muscle pain or tenderness; 10(31%) calcinosis; eight(25%) dysphagia; eight(25%) arthritis, and seven(22%) fever. Muscle enzymes were elevated in 90% of the patients. Of the 27 patients who had an electromyogram, 20(70%) had diagnostic results. Sixteen(70%) of biopsied patients had appropriated results for JDM. Patients were negative for all autoantibodies except ANA and RF. ANA and RF were detected in 47% and 7% of the patients respectively. Conclusion : Although the sensitivity of the criteria proposed by Bohan and Peter is superior, each of these criteria has possible confounding factors. Additional criteria may be needed for early diagnosis of JDM. Based on our findings of autoantibodies in JDM, we do not recommend routine testing for autoantibodies in children with typical JDM.