• Ocean and Polar Research
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• v.41 no.3
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• pp.121-133
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• 2019

Natural variability associated with a variety of large-scale climate modes causes regional differences in sea level rise (SLR), which is particularly remarkable in the Pacific Ocean. Because the superposition of the natural variability and the background anthropogenic trend in sea level can potentially threaten to inundate low-lying and heavily populated coastal regions, it is important to quantify sea level variability associated with internal climate variability and understand their interaction when projecting future SLR impacts. This study seeks to identify the dominant modes of sea level variability in the tropical Pacific and quantify how these modes contribute to regional sea level changes, particularly on the two strong El $Ni{\tilde{n}}o$ events that occurred in the winter of 1997/1998 and 2015/2016. To do so, an adaptive data analysis approach, Ensemble Empirical Mode Decomposition (EEMD), was undertaken with regard to two datasets of altimetry-based and in situ-based steric sea levels. Using this EEMD analysis, we identified distinct internal modes associated with El $Ni{\tilde{n}}o$-Southern Oscillation (ENSO) varying from 1.5 to 7 years and low-frequency variability with a period of ~12 years that were clearly distinct from the secular trend. The ENSO-scale frequencies strongly impact on an east-west dipole of sea levels across the tropical Pacific, while the low-frequency (i.e., decadal) mode is predominant in the North Pacific with a horseshoe shape connecting tropical and extratropical sea levels. Of particular interest is that the low-frequency mode resulted in different responses in regional SLR to ENSO events. The low-frequency mode contributed to a sharp increase (decrease) of sea level in the eastern (western) tropical Pacific in the 2015/2016 El $Ni{\tilde{n}}o$ but made a negative contribution to the sea level signals in the 1997/1998 El $Ni{\tilde{n}}o$. This indicates that the SLR signals of the ENSO can be amplified or depressed at times of transition in the low-frequency mode in the tropical Pacific.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.77-86
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• 2020

Power quality problems caused by feeder voltage drop and extension construction cost problems can occur with the increasing utilization rates of the existing fixed-type EV (electric vehicle) charger. Moreover, EV users might not be able to access the EV charger due to a lack of EV charging facilities. Therefore, this paper proposes an MPSD (movable power supply device) for EVs to overcome user inconvenience caused by the insufficient number of chargers and extension cost issues. The proposed MPSD was mainly composed of a PV (photovoltaic) system, ESS (energy storage system), EV charging system, and monitoring and control system. Furthermore, there are three operation modes available to enhance the flexibility of the MPSD application, depending on the situation. This paper also presents an economical evaluation modeling using the present worth method to consider the cost and benefit elements. The simulation results based on proposed modeling showed that MPSD is more economical than the existing EV charger. Moreover, its profit can be increased significantly depending on the distance to the installation point.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.8
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• pp.531-540
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• 2022

In this paper, we present an algorithm that identifies artillery type and rapidly predicts the impact point based on the IMM filter. The ballistic trajectory equation is used as a system model, and three models with different ballistic coefficient values are used. Acceleration was divided into three components of gravity, air resistance, and lift. And lift acceleration was added as a new state variable. The kinematic condition that the velocity vector and lift acceleration are perpendicular was used as a pseudo-measurement value. The impact point was predicted based on the state variable estimated through the IMM filter and the ballistic coefficient of the model with the highest mode probability. Instead of the commonly used Runge-Kutta numerical integration for impact point prediction, a semi-analytic method was used to predict impact point with a small amount of calculation. Finally, a state variable initialization method using the least-square method was proposed. An integrated algorithm including artillery type identification, impact point prediction and initialization was presented, and the validity of the proposed method was verified through simulation.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.5
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• pp.86-94
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• 2022

Replacement of FRP rod as steel reinforcement has been attracted significantly to prevent the degradation of the concrete structure due to corrosion. So, the technology development to extend the structure's service life by improving FRP properties has been proceeded worldwide. Accordingly, it is necessary to develop Korea's CFRP rod and CFRP grid, including the manufacturing techniques to improve the properties of high-strength and high-stiffness. Moreover, the research should be conducted to evaluate the structural behavior of the beams using the CFRP rod or grid. This study investigates the flexural and shear behavior of reinforced concrete beam using demonstrated CFRP rod as reinforcement according to the reinforcement ratio and shear span to depth ratio. From the results, when the reinforcement ratio is out of a specific range, it is seemed that the effect on performance improvement of the beam using CFRP rod is cancelled or not significant. Meanwhile, when the CFRP rod was used as reinforcement, the possibility of shear failure occurred, even steel stirrups were installed in the beam with CFRP rod as tensile reinforcement according to the Korean Design Standard. Therefore, when the CFRP rod is used as tensile reinforcement in a beam, it should be prepared that a specific limitation of reinforcement ratio and an investigation against shear failure. Also, the ductility of the beam using the CFRP rod is determined by the deformation energy evaluation method. So, the ductility should be investigated by applying the deformation energy evaluation method that reflects the structural behavior of the beam.

• The Journal of the Acoustical Society of Korea
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• v.40 no.6
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• pp.587-592
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• 2021

Change in the cortical thickness of long bones occurring with aging and osteoporosis is known to be a risk factor for fracture. The present study aims to investigate the dependencies of phase velocities of ultrasonic guided waves on the cortical thickness in 7 soft tissue-bone mimicking phantoms consisting of acrylic plates covered by a 2 mm-thick silicone rubber layer by using the axial transmission technique with a pair of transducers with a center frequency of 200 kHz and a diameter of 12.7 mm. Two distinct propagating waves with different velocities, the First Arriving Signal (FAS) and the Slow Guided Waved (SGW), were consistently observed for all the soft tissue-bone mimicking phantoms. The FAS velocity decreased slightly with increasing thickness, whereas the SGW velocity increased strongly with increasing thickness. The FAS and the SGW velocities were found to be closely consistent with the S0 and the A0 Lamb mode velocities for a free acrylic plate, respectively, suggesting that the presence of the soft tissue mimicking material (2 mm-thick silicone rubber layer) covering the acrylic plates does not influence significantly the velocity measurements.

• Advanced Industrial SCIence
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• v.1 no.1
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• pp.7-15
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• 2022

To adopt the development in the medical scenario IoT developed towards the advancement with the processing of a large amount of medical data defined as an Internet of Medical Things (IoMT). The vast range of collected medical data is stored in the cloud in the structured manner to process the collected healthcare data. However, it is difficult to handle the huge volume of the healthcare data so it is necessary to develop an appropriate scheme for the healthcare structured data. In this paper, a machine learning mode for processing the structured heath care data collected from the IoMT is suggested. To process the vast range of healthcare data, this paper proposed an MTGPLSTM model for the processing of the medical data. The proposed model integrates the linear regression model for the processing of healthcare information. With the developed model outlier model is implemented based on the FinTech model for the evaluation and prediction of the COVID-19 healthcare dataset collected from the IoMT. The proposed MTGPLSTM model comprises of the regression model to predict and evaluate the planning scheme for the prevention of the infection spreading. The developed model performance is evaluated based on the consideration of the different classifiers such as LR, SVR, RFR, LSTM and the proposed MTGPLSTM model and the different size of data as 1GB, 2GB and 3GB is mainly concerned. The comparative analysis expressed that the proposed MTGPLSTM model achieves ~4% reduced MAPE and RMSE value for the worldwide data; in case of china minimal MAPE value of 0.97 is achieved which is ~ 6% minimal than the existing classifier leads.

• Composites Research
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• v.20 no.5
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• pp.64-69
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• 2007

Matrix dominant properties of composites are largely degraded under harmful environments such as temperature and humidity. Therefore we should consider the harmful environmental factors in the design of an UAV integral fuel tank subjected to high temperature and high humidity. The harmful environment experiment was performed for carbon/epoxy composites made of a unidirectional prepreg USN175B, and a plain woven fabric prepreg WSN3. The immersion experiment was performed under $90^{\circ}C$. The specimens were tested when the weight gam of specimen was saturated. The specimens were tested under $74^{\circ}C$ to obtain tensile and inplane shear properties. The results showed that the matrix dominant properties were extremely degraded by hygrothermal environment. To consider the variability of load, the anti-optimization method was applied. By using this method, the worst load case was found by comparing the load convex model and stability boundary. The stability boundary was obtained by analysis of the integral wing fuel tank of UAV using degraded properties. To do this, it was known that the worst load case of the integral wing fuel tank was the hovering mode load case.

• Composites Research
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• v.20 no.3
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• pp.8-16
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• 2007

Bending collapse of light-weight square tubes used for vehicle structure components is a dominant failure mode in oblique collision and rollover of vehicles. In this paper bending performances of aluminum-GFRP hybrid tube beams were evaluated in relation with bending deformation behavior and energy absorption characteristics. Aluminum/GFRP hybrid tube beams fabricated by inserting adhesive film between prepreg and metal layer were used in the bending test. Failure mechanisms of hybrid tubes under a bending load were experimentally investigated to analyze the bending performance as a function of ply orientation and composite layer thickness. Ultimate bending moments and energy absorption capacity of hybrid tube beams were obtained from the measured load-displacement corves. It was found that aluminum/GFRP hybrid tubes could be converted to rather stable collapse mode showing excellent energy absorption capacity in comparison to the pure aluminum tube beams. In particular, the hybrid tube beam with $[0^{\circ}/90^{\circ}]s$ composite layer showed a large improvement by about 78% in energy absorption capacity and by 29% in specific energy absorption.

• Analytical Science and Technology
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• v.22 no.4
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• pp.326-335
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• 2009

A specific analytical method able to identify and quantify traces of six glucocorticoids residues in eggs were developed. The extraction and clean-up parameters for simultaneous analysis were evaluated and HPLC and spectrometric conditions were also established. For determination of glucocorticoids, 5 g of egg was transferred into a test tube, adjusted pH 5.2 with acetate buffer and was $\beta$-glucuronidase/arylsulfatase from Helix pomatia added. The mixture was centrifuged and supernatant was extracted twice with 20 mL n-hexane. The extraction was performed with HLB cartridge using methanol, followed by clean-up with silica cartridge using methanol/ethyl acetate (4/6, v/v). The analytes were determined by HPLC/ESI-MS/MS operating in the negative ion mode. Validation studies with fortified egg samples for established method were performed. The result of method validation gave good efficiency, linearity, accuracy and precision. The correlation coefficients ($r^2$) of the calibration curves appeared to be higher than 0.99 in egg, indicating excellent linearity. LOD was ranged 0.09 to $0.17{\mu}g/kg$, and recoveries for most compounds were in the range of 55.7-69.8%. This method can be used to determine ${\mu}g/kg$ levels of glucocorticoids in eggs.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.66-73
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• 2023

The construction industry suffers losses due to failures in demand forecasting due to price fluctuations in construction raw materials, increased user costs due to project cost changes, and lack of forecasting system. Accordingly, it is necessary to improve the accuracy of construction raw material price forecasting. This study aims to predict the price of construction raw materials and verify applicability through the improvement of the Data Refactor technique. In order to improve the accuracy of price prediction of construction raw materials, the existing data refactor classification of low and high frequency and ARIMAX utilization method was improved to frequency-oriented and ARIMA method utilization, so that short-term (3 months in the future) six items such as construction raw materials lumber and cement were improved. ), mid-term (6 months in the future), and long-term (12 months in the future) price forecasts. As a result of the analysis, the predicted value based on the improved Data Refactor technique reduced the error and expanded the variability. Therefore, it is expected that the budget can be managed effectively by predicting the price of construction raw materials more accurately through the Data Refactor technique proposed in this study.