• Composites Research
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• v.34 no.5
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• pp.296-304
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• 2021

This study presented the evaluation of the stamp forming process for L-shape CF/PEKK thermoplastic composite using the finite element model. The formability of three different trimming allowances has been examined for representative product geometry. The results showed that those manufactured by high trimming allowance showed more excellent formability in those areas. Moreover, the effects of the trimming allowances on the stress, thickness, wrinkle distributions of thermoplastic composites fabricated with the stamp forming process were evaluated. The comparison of the simulation and experimental results for the thickness and wrinkle distributions proved the accuracy of the stamp forming model. The crystallinity of the composite was performed by differential scanning calorimetry (DSC). The void content of the composite was evaluated by matrix digestion. Then, the fabricated structure was characterized and achieved high quality in crystallinity and void content. Consequently, the presented FEM modeling shows excellent potential for application in the aircraft product design process. This pragmatic approach could efficiently offer a valuable solution for the thermoplastic composite manufacturing field.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.391-398
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• 2021

Since the leased line is a structure that exclusively uses two connected areas for data transmission, a stable quality level and security are ensured, and despite the rapid increase in the number of switched lines, it is a line method that is continuously used a lot in companies. However, because the cost is relatively high, one of the important roles of the network operator in the enterprise is to maintain the optimal state by properly arranging and utilizing the resources of the network leased line. In other words, in order to properly support business service requirements, it is essential to properly manage bandwidth resources of leased lines from the viewpoint of data transmission, and properly predicting and managing leased line usage becomes a key factor. Therefore, in this study, various prediction models were applied and performance was evaluated based on the actual usage rate data of leased lines used in corporate networks. In general, the performance of each prediction was measured and compared by applying the smoothing model and ARIMA model, which are widely used as statistical methods, and the representative models of deep learning based on artificial neural networks, which are being studied a lot these days. In addition, based on the experimental results, we proposed the items to be considered in order for each model to achieve good performance for prediction from the viewpoint of effective operation of leased line resources.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1149-1161
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• 2021

With a trend of the utilization of computer vision for satellite images, cloud detection using deep learning also attracts attention recently. In this study, we conducted a U-Net cloud detection modeling using SPARCS (Spatial Procedures for Automated Removal of Cloud and Shadow) Cloud Dataset with the image data augmentation and carried out 10-fold cross-validation for an objective assessment of the model. Asthe result of the blind test for 1800 datasets with 512 by 512 pixels, relatively high performance with the accuracy of 0.821, the precision of 0.847, the recall of 0.821, the F1-score of 0.831, and the IoU (Intersection over Union) of 0.723. Although 14.5% of actual cloud shadows were misclassified as land, and 19.7% of actual clouds were misidentified as land, this can be overcome by increasing the quality and quantity of label datasets. Moreover, a state-of-the-art DeepLab V3+ model and the NAS (Neural Architecture Search) optimization technique can help the cloud detection for CAS500 (Compact Advanced Satellite 500) in South Korea.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.5
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• pp.13-25
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• 2021

The particulate matters (PM₁₀ and PM_2.5) and ammonia emitted from livestock farms as dispersed to urban and residential areas can increase the public's concern over the health problem, social conflicts, and air quality. Understanding the atmospheric dispersion of such matters is important to prevent the problems for the regulatory purposes. In this study, AERMOD modeling was performed to predict the dispersion of livestock particulate matters and ammonia in Gwangju metropolitan city and five surrounding cities. The five cities were divided into 40 sub-zones to model the area-based emissions which varied with the number of livestock farms, species and growth stages of the animals. As a result, the concentrations of PM₁₀, PM_2.5 and ammonia resulted from livestock farms located in the surrounding cities were 2.00 ㎍ m^-3, 0.30 ㎍ m^-3 and 0.04 ppm in the southwestern part of Gwangju based on the average concentration of 1 hour. These values accounted for 0.7% of PM₁₀ concentration, 0.5% of PM_2.5 concentration, and 0.4% of the ammonia concentration in Gwangju, contributing to a small amount of air pollution compared to other sources. As preventive measures, the plantation was applied to high emission source areas to reduce particulate matters and ammonia emissions by 35% and 31%, respectively, and resulted in decrease of the area of influence by 57% for particulate matters and 59% for ammonia.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.9
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• pp.1381-1388
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• 2019

Objective: The aims of this study were to reveal the magnitude of the differences in protein structures at a cellular level as well as protein utilization and availability among soybean meal (SBM), canola meal (CM), and rapeseed meal (RSM) as feedstocks in China. Methods: Experiments were designed to compare the three different types of feedstocks in terms of: i) protein chemical profiles; ii) protein fractions partitioned according to Cornell Net Carbohydrate and Protein System; iii) protein molecular structures and protein second structures; iv) special protein compounds-amino acid (AA); v) total digestible protein and energy values; vi) in situ rumen protein degradability and intestinal digestibility. The protein second structures were measured using FT/IR molecular spectroscopy technique. A summary chemical approach in National Research Council (NRC) model was applied to analyze truly digestible protein. Results: The results showed significant differences in both protein nutritional profiles and protein structure parameters in terms of ${\alpha}-helix$, ${\beta}-sheet$ spectral intensity and their ratio, and amide I, amide II spectral intensity and their ratio among SBM, CM, and RSM. SBM had higher crude protein (CP) and AA content than CM and RSM. For dry matter (DM), SBM, and CM had a higher DM content compared with RSM (p<0.05), whereas no statistical significance was found between SBM and CM (p = 0.28). Effective degradability of CP and DM did not demonstrate significant differences among the three groups (p>0.05). Intestinal digestibility of rumen undegradable protein measured by three-step in vitro method showed that there was significant difference (p = 0.05) among SBM, CM, and RSM, which SBM was the highest and RSM was the lowest with CM in between. NRC modeling results showed that digestible CP content in SBM was significantly higher than that of CM and RSM (p<0.05). Conclusion: This study suggested that SBM and CM contained similar protein value and availability for dairy cattle, while RSM had the lowest protein quality and utilization.

• Journal of the Korean Applied Science and Technology
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• v.36 no.2
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• pp.581-591
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• 2019

The purpose of this study was to investigate the relationship among health belief, environmental concern and continue exercise for golf participants. To achieve the goal of this study, a total of 270 questionnaires were distributed and 270 copies were collected back. Out of those returned questionnaires, insincerely replied or double-replied questionnaires were excluded and finally 255 questionnaires were analyzed for this study. For analysis of the data, frequency analysis, exploratory factor analysis, reliability analysis, confirmatory factor analysis, correlation analysis, and structural equating modeling were conducted using SPSS 18.0 and AMOS 18.0. Main findings were as follows: First health belief had a positive effect on environmental concern. Second, environmental concern had a positive effect on continue exercise. Third, health belief had a positive effect on continue exercise. Fourth, environmental concern mediated the relationship between golf participant health belief and continue exercise. If golf participants improve their physical and psychological health effects through golf and environmental concern increase from gaining a sense of accomplishment such as acquiring or improving golf skills, they will be able to lead a better quality of life.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.297-305
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• 2019

The purpose of this study was to examine resilience and empathy on the relation between humanity and friendship of the early adolescents using structural equation modeling. The subjects were total 332 students of the 5th and 6th grade in elementary school and 1st and 2nd grade in junior school. The data were collected by means of the self-report questionnaire. The results of this study were as follows: Firstly, the direct effect of humanity on resilience, empathy, and friendship was found. Resilience also influence friendship directly, but empathy did not affect friendship. Secondly, humanity had influence on friendship partially mediated by resilience, but not mediated by empathy. This result shows that resilience was better mediated between humanity and friendship than empathy. Additionally, sex differences were found on empathy, but the differences were not found on resilience. The results revealed that the adolescents who scored high on humanity were better at friendship and when the higher humanity score was, the higher level of resilience was found, and this had an indirect effect on friendship quality.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1445-1456
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• 2018

The purpose of this study is to compare the quality and characteristics of matching DEMs by using KOMPSAT-3 stereo pair capture in in-track and cross-track. For this purpose, two stereo pairs of KOMPSAT-3 were collected that were taken in the same area. The two stereo pairs have similar stereo geometry elements such as B/H, convergence angle. Sensor modeling for DEM production was performed with RFM affine calibration using multiple GCPs. The GCPs used in the study were extracted from the 0.25 m ortho-image and 5 meter DEM provided by NGII. In addition, matching DEMs were produced at the same resolution as the reference DEMs for a comparison analysis. As a result of the experiment, the horizontal and vertical errors at the CPs indicated an accuracy of 1 to 3 pixels. In addition, the shapes and accuracy of two DEMs produced in areas where the effects of natural or artificial surface land were low were almost similar.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.397-404
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• 2019

When developing a weapon system, a T&E(Test and Evaluation) can be performed using M&S for the test items that cannot be evaluated in the real world. In this case, the VV&A activities are required to prove the credibility of M&S for the T&E. Recently, the use of M&S has been increasing as the R&D trends of weapon systems are becoming more advanced. Therefore, the VV&A activities are also increasing. The VV&A activities aim to verify, validate, and accredit that the simulation can represent a real system and ensure credibility regarding its purpose and intention of use. VV&A activities are divided into V&V and Accreditation. When performing VV&A in the ADD (Agency for Defense Development), the V&V activities are performed by a separate department of the ADD and the accreditation activities are performed in the DTAQ (Defense Agency for Technology and Quality). This paper proposes a V&V process for a T&E of M&S that has been performed in ADD. The process is used to verify and validate the documents and data generated during the development process according to the accreditation criteria, and provides objective data that can be used to judge whether the accreditation decision and acceptance criteria are met.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.435-447
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• 2019

In order to prevent unnecessary re-admission, it is necessary to intensively manage the groups with high probability of re-admission. For this, it is necessary to develop a re-admission prediction model. Two - year discharge summary data of one university hospital were collected from 2016 to 2017 to develop a predictive model of re-admission. In this case, the re-admitted patients were defined as those who were discharged more than once during the study period. We conducted descriptive statistics and crosstab analysis to identify the characteristics of rehospitalized patients. The re-admission prediction model was developed using logistic regression, neural network, and decision tree. AUC (Area Under Curve) was used for model evaluation. The logistic regression model was selected as the final re-admission predictive model because the AUC was the best at 0.81. The main variables affecting the selected rehospitalization in the logistic regression model were Residental regions, Age, CCS, Charlson Index Score, Discharge Dept., Via ER, LOS, Operation, Sex, Total payment, and Insurance. The model developed in this study was limited to generalization because it was two years data of one hospital. It is necessary to develop a model that can collect and generalize long-term data from various hospitals in the future. Furthermore, it is necessary to develop a model that can predict the re-admission that was not planned.