• Advances in nano research
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• v.16 no.3
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• pp.251-263
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• 2024

This article investigates the free vibration behavior of carbon nanotube reinforced composite (CNTRC) beams embedded using variational analytical methods and artificial neural networks (ANN). The material properties of layered functionally graded CNTRC (FG-CNTRC) beams are estimated using nonlocal parameters modified power-law with different types of CNT distributions through the thickness direction of the beam. Adopting Eringen's nonlocal elasticity theory to capture the small size effects, the nonlocal governing equations are derived and solved using the analytical method. And also, the problem was analyzed using the ANN method. The architecture of the proposed ANN model is 3-9-1. In the experiments, we used 112 different data to predict the natural frequency using ANN. Based on the nonlocal differential constitutive relations of Eringen, the equations of motion as well as the boundary conditions of the beam are derived using Hamilton's principle. The classical beam theory is used to formulate a governing equation for predicting the free vibration of laminated CNTRC beams. According to the experimental results, the prediction ability of the ANN model is very good and the natural frequency can be predicted in ANN without attempting any experiments.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4607-4616
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• 2023

We implement machine learning regression models to predict peak pressures of primary and secondary systems, a major safety concern in Loss Of Condenser Vacuum (LOCV) accident. We selected the Multi-dimensional Analysis of Reactor Safety-KINS standard (MARS-KS) code to analyze the LOCV accident, and the reference plant is the Korean Optimized Power Reactor 1000MWe (OPR1000). eXtreme Gradient Boosting (XGBoost) is selected as a machine learning tool. The MARS-KS code is used to generate LOCV accident data and the data is applied to train the machine learning model. Hyperparameter optimization is performed using a simulated annealing. The randomly generated combination of initial conditions within the operating range is put into the input of the XGBoost model to predict the peak pressure. These initial conditions that cause peak pressure with MARS-KS generate the results. After such a process, the error between the predicted value and the code output is calculated. Uncertainty about the machine learning model is also calculated to verify the model accuracy. The machine learning model presented in this paper successfully identifies a combination of initial conditions that produce a more conservative peak pressure than the values calculated with existing methodologies.

• Journal of muscle and joint health
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• v.31 no.2
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• pp.65-74
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• 2024

Purpose: This study was conducted to verify fall predictive power and reasonable fall risk assessment tool by a comparative analysis of the sensitivity, specificity, positive forecast and negative forecast of each tool by applying Morse Fall Scale (MFS), Johns Hopkins Fall Risk Assessment Tool (JHFRAT), and Fall Assessment Scale-Korean version (FAS-K) through electronic medical records to adult patients hospitalized in a general hospital in Korea. Methods: We performed a retrospective evaluation study from January to December 2018, 123 fall groups experiencing falls during hospitalization and 123 non-falls groups were selected. Data presented a reasonable assessment tool that predicts and distinguishes fall high-risk patients through area comparison based on the ROC curve for each tool. Results: In the ROC curve analysis by fall risk assessment group, the AUC of MFS is shown to be .706 (good), JHFRAT is shown to be .649 (sufficient) and FAS-K is shown to be .804 (very good). FAS-K at a cut-off score of 4, sensitivity, specificity, and positive and negative prediction values were 83.7%, 60.2%, 67.8%, and 78.7%, respectively. Conclusion: Based on the above findings, it is believed that the FAS-K was presented as a suitable and reasonable tool for predicting falls for adult patients in general hospitals.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.933-944
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• 2019

This study analyzes the tide deformation of land boundary regions on the east (Region A) and west (Region B) sides of the Ross Ice Shelf in Antarctica using Double-Differential Interferometric Synthetic Aperture Radar (DDInSAR). A total of seven Sentinel-1A SAR images acquired in 2015-2016 were used to estimate the accuracy of tide prediction model and Young's modulus of ice shelf. First, we compared the Ross Sea Height-based Tidal Inverse (Ross_Inv) model, which is a representative tide prediction model for the Antarctic Ross Sea, with the tide deformation of the ice shelf extracted from the DDInSAR image. The accuracy was analyzed as 3.86 cm in the east region of Ross Ice Shelf and it was confirmed that the inverse barometric pressure effect must be corrected in the tide model. However, in the east, it is confirmed that the tide model may be inaccurate because a large error occurs even after correction of the atmospheric effect. In addition, the Young's modulus of the ice was calculated on the basis of the one-dimensional elastic beam model showing the correlation between the width of the hinge zone where the tide strain occurs and the ice thickness. For this purpose, the grounding line is defined as the line where the displacement caused by the tide appears in the DDInSAR image, and the hinge line is defined as the line to have the local maximum/minimum deformation, and the hinge zone as the area between the two lines. According to the one-dimensional elastic beam model assuming a semi-infinite plane, the width of the hinge region is directly proportional to the 0.75 power of the ice thickness. The width of the hinge zone was measured in the area where the ground line and the hinge line were close to the straight line shown in DDInSAR. The linear regression analysis with the 0.75 power of BEDMAP2 ice thickness estimated the Young's modulus of 1.77±0.73 GPa in the east and west of the Ross Ice Shelf. In this way, more accurate Young's modulus can be estimated by accumulating Sentinel-1 images in the future.

• Journal of the Korean earth science society
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• v.43 no.2
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• pp.239-252
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• 2022

Quality control methods for the first G-band vapor radiometer (GVR) mounted on a weather aircraft in Korea were developed using the GVR Precipitable Water Vapor (PWV). The aircraft attitude information (degree of pitch and roll) was applied to quality control to select the shortest vertical path of the GVR beam. In addition, quality control was applied to remove a GVR PWV ≥20 mm. It was found that the difference between the warm load average power and sky load average power converged to near 0 when the GVR PWV increased to 20 mm or higher. This could be due to the high brightness temperature of the substratus and mesoclouds, which was confirmed by the Communication, Ocean and Meteorological Satellite (COMS) data (cloud type, cloud top height, and cloud amount), cloud combination probe (CCP), and precipitation imaging probe (PIP). The GVR PWV before and after the application of quality control on a cloudy day was quantitatively compared with that of a local data assimilation and prediction system (LDAPS). The Root Mean Square Difference (RMSD) decreased from 2.9 to 1.8 mm and the RMSD with Korea Local Analysis and Precipitation System (KLAPS) decreased from 5.4 to 4.3 mm, showing improved accuracy. In addition, the quality control effectiveness of GVR PWV suggested in this study was verified through comparison with the COMS PWV by using the GVR PWV applied with quality control and the dropsonde PWV.

• Korean Journal of Culture and Social Issue
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• v.15 no.1
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• pp.187-205
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• 2009

Based on the Motivational States Theory(MOST), the present research expanded and complemented Kim(2007)'s proposal to add the Life Satisfaction Expectancy Scale(LSES) to Diener et al's Satisfaction With Life Scale(SWLS) to measure subjective well-being(SWB). In the present study, the Life Satisfaction Motivation Scale(LSMS) was introduced to measure the strength of motivation for life satisfaction in general. Two hundred and eighty six college students participated in this study. Factor analyses revealed a two-factor structure, with the factors corresponding to life satisfaction and life satisfaction expectancy. Measures of internal and temporal reliability show the LSMS to be a good complement for the measure of SWB(The LSMS showed high internal and test-retest reliability). It was found that the addition of the LSES provided a significant increment in predictive power over the SWLS in the prediction of various factors related with well-being prediction. Exceptionally, in the prediction of anger the LSMS had the most predictive power. There were some differences between male and female students in the correlations among life satisfaction, life satisfaction expectancy and life satisfaction motivation and well-being-related factors. The merits of including LSES in the measurement of subjective well-being and the limitations of this study are discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.77-85
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• 2020

Currently, life-cycle cost analysis methods are introduced to maintain large infrastructure facilities in Korea. However, there are not many cases in which maintenance models are applied that reflect conditions such as the location of a facility and its surroundings. In order to establish an appropriate maintenance strategy, a cost prediction, deterioration model, and a decision model reflecting uncertainty should be established. In this study, an economic analysis model was developed for long-term cost planning and management based on user decisions based on maintenance methods and judgment criteria for painting specifications applied to power generation structures. The performance of the paintwork was assessed through the paint deterioration test for the application of the economic analysis model, and the results of the economic analysis according to the applied paint specifications (Urethan, polysiloxane, fluorine) were verified by applying the proposed economic analysis model. In this study, it is believed that the selection of the repair cycle and evaluation methods applied with the development model rather than the performance of the painting can be expected to be used as basic data for the maintenance cycle, even if it is not limited to the painting.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.11
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• pp.1465-1471
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• 2007

Response surface methodology (RSM) was employed to optimize extraction conditions in order to find the maximal functional properties of fluid Cheonggukjang. Based on central composite design, a study plan was established with variations of microwave power, ethanol concentration, and extraction time. Regression analysis was applied to obtain a mathematical model. The maximum inhibitory of tyrosinase activity was found as 26.75% at the conditions of 30.56W microwave power, 2.40 g/mL of ratio of solvent to sample content and 10.00 min extraction time, respectively. The maximum superoxide dismutase (SOD)-like activity was 53.23% under the extraction conditions of 108.42 W, 4.38 g/mL and 7.84 min. Based on superimposition of three dimensional RSM with respect to extraction yield, inhibitory of tyrosinase activity and SOD-like activity obtained under the various extraction conditions, the optimum ranges of extraction conditions were found to be microwave power of $55{\sim}75$ W, ratio of solvent to sample content of $2{\sim}5$ g/mL and extraction time of $3.5{\sim}15$ min, respectively.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.47-59
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• 2017

This study aims to assess offshore wind energy resources around Jeju Island using the InVEST Offshore Wind model. First the wind power density around the coast of Jeju was calculated using reanalysis data from the Korean Local Analysis and Prediction System (KLAPS). Next, the net present value (NPV) for the 168MW offshore wind farm scenario was evaluated taking into consideration factors like costs (turbine development, submarine cable installation, maintenance), turbine operation efficiency, and a 20year operation period. It was determined that there are high wind resources along both the western and eastern coasts of Jeju Island, with high wind power densities of $400W/m^2$ calculated. To visually evaluate the NPV around Jeju Island, a classification of five grades was employed, and results showed that the western sea area has a high NPV, with wind power resources over $400W/m^2$. The InVEST Offshore Wind model can quickly provide optimal spatial information for various wind farm scenarios. The InVEST model can be used in combination with results of marine ecosystem service evaluation to design an efficient marine spatial plan around Jeju Island.

• Journal of Distribution Science
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• v.12 no.6
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• pp.67-79
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• 2014

Purpose - This study aims to accomplish three major research goals. First, it strives to change consumers' focus from peripheral routes to a central route of public service advertising related to the good health policy, without problematic effects, by influencing consumers' knowledge or involvement. Second, this study examines the elaboration likelihood model (ELM) and construal level theory (CLT). Specifically, we consider that the central route of ELM might correspond with the focal goal of CLT. Third, this study analyzes ELM through CLT. That is, ELM predicted that low involvement would take the peripheral route, and high involvement would take the central route. Research design, data, and methodology - This study consisted of three experiments. The first experiment had a 2×2 between-subject design. The subjects were university students and the research period was approximately one year. The first independent variable was the involvement of the overweight issue; this variable was measured and split by the median. The second independent variable was the temporal distance (near vs. distant future); this variable was manipulated. The second experiment also had a 2×2 between-subject design. The first variable was the involvement of cervical adenocarcinoma prevention, and was considered already manipulated by sex. Specifically, males had a low involvement of the disease, but females had high involvement. The second independent variable was priming (power vs. submissive). Power priming would induce abstract thinking, but submissive priming would take concrete processing. The third experiment had a 2×2×2 between-subject design. The first variable was cognitive depletion, and was manipulated by memorizing 9-digit numbers. The second and third independent variables were involvement and abstract thinking induction, such as prior experiments. Data were collected through questionnaires, and were analyzed by an SPSS program. Major hypotheses were tested by examining the interaction effects through ANOVA. Results - Major findings are as follows. First, even for low-involved consumers in the overweight category, distant future manipulation induced them to focus not on the peripheral route but on the central route of the public service advertisement. This result does not correspond to the typical ELM prediction. Second, under power priming, low-involved males of the cervical adenocarcinoma category focused on the peripheral route because of the induction to abstract thinking. This result replicated the first experiment, and confirmed the theoretical robustness. Third, high-involved females focused not on the central but on the peripheral route under the mixed condition of cognitive depletion and near future manipulation. Depletion consumed cognitive resources, and the processing mode of consumers changed from systematic to heuristic. Conclusions - ELM needs to be complemented through CLT in context of public service good health advertising. Specifically, the involvement of ELM may impact consumers' thinking mode (abstract vs. concrete), and the interaction effects may influence consumers' focus on advertising (central vs. peripheral route). This study's limitations were bounded subjects, limited stimuli, and somewhat weak external validity.