• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.9-17
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• 2021

Curved beams are increasingly used in buildings, vehicles, ships, and aircraft, which has resulted in considerable effort being directed toward developing an accurate method for analyzing the dynamic behavior of such structures. The stability behavior of elastic circular arches has been the subject of a large number of investigations. One of the efficient procedures for the solution of ordinary differential equations or partial differential equations is the differential quadrature method DQM. This method has been applied to a large number of cases to overcome the difficulties of the complex computer algorithms, as well as excessive use of storage due to conditions of non-linear geometries, loadings, or material properties. This study uses DQM to analyze the in-plane vibration of the circular arches considering the effects of midsurface extension and rotatory inertia. Fundamental frequency parameters are calculated for the member with various parameter ratios, boundary conditions, and opening angles. The solutions from DQM are compared with exact solutions or other numerical solutions for cases in which they are available and given to analyze the effects of midsurface extension and rotatory inertia on the frequency parameters of the circular arches.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.116-122
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• 2021

This study quantitatively evaluated the performance improvement of a circular reinforced concrete pier under dynamic load with strengthening using a steel plate. Various three-dimensional elements were applied using the finite element program ABAQUS. The analytical parameters included the ratios of the steel cover length to the pier's total height and the ratios of the steel cover thickness to the pier diameter for inelastic-nonlinear analysis. The lower part of the pier had fixed boundary conditions, and lateral repetitive loads were applied at the top of the pier. The pier was investigated to evaluate the dynamic performance based on the load-displacement curve, stress-strain curve, ductility, energy absorption capability, and energy ratio. The yield and ultimate loads of piers with steel covers increased by 3.76 times, and the energy absorption capability increased by 4 times due to the confinement effects caused by the steel plate. A plastic hinge part of the column with a steel plate improved the ductility, and the thicker the steel plate was, the greater the energy absorption capacity. This study shows that the reinforced pier should be improved in terms of the seismic performance.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.33-45
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• 2020

This paper aims to look at the perspective that the latest cutting-edge technologies are predicting individual diseases in the actual medical environment in a situation where various types of wearable devices are rapidly increasing and used in the healthcare domain. Through the process of collecting, processing, and transmitting data by merging clinical data, genetic data, and life log data through a user-participating wearable device, it presents the process of connecting the learning model and the feedback model in the environment of the Deep Neural Network. In the case of the actual field that has undergone clinical trial procedures of medical IT occurring in such a high-tech medical field, the effect of a specific gene caused by metabolic syndrome on the disease is measured, and clinical information and life log data are merged to process different heterogeneous data. That is, it proves the objective suitability and certainty of the deep neural network of heterogeneous data, and through this, the performance evaluation according to the noise in the actual deep learning environment is performed. In the case of the automatic encoder, we proved that the accuracy and predicted value varying per 1,000 EPOCH are linearly changed several times with the increasing value of the variable.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.92-111
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• 2021

As fine dust negatively affects disease, industry and economy, the people are sensitive to fine dust. Therefore, if the occurrence of fine dust can be predicted, countermeasures can be prepared in advance, which can be helpful for life and economy. Fine dust is affected by the weather and the degree of concentration of fine dust emission sources. The industrial sector has the largest amount of fine dust emissions, and in industrial complexes, factories emit a lot of fine dust as fine dust emission sources. This study targets regions with old industrial complexes in local cities. The purpose of this study is to explore the factors that cause fine dust and develop a predictive model that can predict the occurrence of fine dust. weather data and fine dust data were used, and variables that influence the generation of fine dust were extracted through multiple regression analysis. Based on the results of multiple regression analysis, a model with high predictive power was extracted by learning with a machine learning regression learner model. The performance of the model was confirmed using test data. As a result, the models with high predictive power were linear regression model, Gaussian process regression model, and support vector machine. The proportion of training data and predictive power were not proportional. In addition, the average value of the difference between the predicted value and the measured value was not large, but when the measured value was high, the predictive power was decreased. The results of this study can be developed as a more systematic and precise fine dust prediction service by combining meteorological data and urban big data through local government data hubs. Lastly, it will be an opportunity to promote the development of smart industrial complexes.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1435-1447
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• 2020

The seasonal variations in weather parameters can significantly affect the atmospheric transmission characteristics. Herein, we propose a novel augmented multiple regression algorithm for the accurate estimation of atmospheric transmittance and solar irradiance over highly localized areas. The algorithm employs 1) adaptive atmospheric model selection using measured meteorological data and 2) multiple linear regression computation augmented with the conventional application of MODerate resolution atmospheric TRANsmission (MODTRAN). In this study, the proposed algorithm was employed to estimate the solar irradiance over Taean coastal area using the 2018 clear days' meteorological data of the area, and the results were compared with the measurement data. The difference between the measured and computed solar irradiance significantly improved from 89.27 ± 48.08σ W/㎡ (with standard MODTRAN) to 21.35 ± 16.54σ W/㎡ (with augmented multiple regression algorithm). The novel method proposed herein can be a useful tool for the accurate estimation of solar irradiance and atmospheric transmission characteristics of highly localized areas with various weather conditions; it can also be used to correct remotely sensed atmospheric data of such areas.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.9-16
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• 2020

A CFRP sheet has been applied as a structural reinforcement in the field, and various studies are conducted to evaluate the effect of CFRP sheets on reinforced concrete. Although many experiments were performed from previous studies, there are still limitations to analyze structural behaviors with various parameters in experiments directly. This study shows the FEA on structural behaviors of RC beams reinforced with CFRP sheets using ABAQUS software. To simulate debonding failure of CFRP sheets which is a major failure mode of RC beam with CFRP sheets, a cohesive element was applied between the bottom surface of RC beam and CFRP sheets. Both quasi-static method and 2-D symmetric FE model technique were performed to solve nonlinear problems. Results obtained from the FE models show good agreements with experimental results. It was found that reinforcement level of CFRP sheets is closely related to structural behavior of reinforced concrete including maximum strength, initial stiffness and deflection at failure. Also, as over-reinforcement of CFRP sheets could give rise to the brittle failure of RCstructure using CFRP sheets, an appropriate measure should be required when installing CFRP sheets in the structure.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.325-331
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• 2022

One of the most important factors in predicting tomato growth and yield is the leaf area. Estimating leaf area accurately is the beginning of an effective tomato plant growth assessment model. To this end, this study was conducted to identify the most effective model for estimating plant leaf area through the measurement of tomato plant leaves. Leaf area (LA), leaf length (L), leaf width (W), and lamina length (La) were measured for all leaves of 5 plants at two-week intervals. The correlation between LA and tomato-leaf-independent variables showed a strong positive relationship with the formulas La × W, L × W, La + W, and L + W. For LA estimation, a linear model using the formula LA = a + b (La² + W²) gave the most accurate estimation (R² = 0.867, RMSE = 88.76). After examining the positions of upper, middle, and lower leaves from September to December, the coefficient of determination (R²) values for each model were 0.878, 0.726, and 0.794 respectively. The most accurate estimation came from the model that used the upper leaves of the plants. The high accuracy of the upper-leaf-based model is judged by the 50% defoliation performed by farmers after October.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.74-99
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• 2022

Surface ozone is produced by photochemical reactions of nitrogen oxides(NOx) and volatile organic compounds(VOCs) emitted from vehicles and industrial sites, adversely affecting vegetation and the human body. In South Korea, ozone is monitored in real-time at stations(i.e., point measurements), but it is difficult to monitor and analyze its continuous spatial distribution. In this study, surface ozone concentrations were interpolated to have a spatial resolution of 1.5km every hour using the stacking ensemble technique, followed by a 5-fold cross-validation. Base models for the stacking ensemble were cokriging, multi-linear regression(MLR), random forest(RF), and support vector regression(SVR), while MLR was used as the meta model, having all base model results as additional input variables. The results showed that the stacking ensemble model yielded the better performance than the individual base models, resulting in an averaged R of 0.76 and RMSE of 0.0065ppm during the study period of 2020. The surface ozone concentration distribution generated by the stacking ensemble model had a wider range with a spatial pattern similar with terrain and urbanization variables, compared to those by the base models. Not only should the proposed model be capable of producing the hourly spatial distribution of ozone, but it should also be highly applicable for calculating the daily maximum 8-hour ozone concentrations.

• Therapeutic Science for Rehabilitation
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• v.12 no.1
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• pp.51-63
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• 2023

Objective : This study aimed to analyze the association between lifestyle and medical expenses of older adults with mental illness using claims data. Methods : We conducted secondary data analysis using the older adult cohort database provided by the Korea National Health Insurance Service. The lifestyle and medical expense variables were extracted from the cohort database. We used a generalized linear model to examine the association between lifestyle and medical expenses. Results : In total, 32,853 records were extracted. The results showed that smokers had medical expenses (estimate = -218,255, p = .037). As the number of days of walking increased, medical expenses significantly decreased (estimate = -58,843, p < .0001). Furthermore, as the number of days of drinking decreased, medical expenses increased (estimate = 692,289, p < .0001). Conclusion : This study analyzed the estimates of medical expenses according to lifestyle among older adults with mental illness. Smoking and exercise were negatively associated with medical expenses. These results suggest the importance of a healthy lifestyle for older adults with mental illness. In addition, this study can be used as clinical evidence for lifestyle management programs to improve physical and mental health.

• Journal of Korea Water Resources Association
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• v.56 no.3
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• pp.211-224
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• 2023

In this study, a soil moisture estimation was performed using the Water Cloud Model (WCM), a backscatter model that considers vegetation based on SAR (Synthetic Aperture Radar). Sentinel-1 SAR and Sentinel-2 MSI (Multi-Spectral Instrument) images of a 40 × 50 km² area including the Yongdam Dam watershed of the Geum River were collected for this study. As vegetation descriptor of WCM, Sentinel-1 based vegetation index RVI (Radar Vegetation Index), depolarization ratio (DR), and Sentinel-2 based NDVI (Normalized Difference Vegetation Index) were used, respectively. Forward modeling of WCM was performed by 3 groups, which were divided by the characteristics between backscattering coefficient and soil moisture. The clearer the linear relationship between soil moisture and the backscattering coefficient, the higher the simulation performance. To estimate the soil moisture, the simulated backscattering coefficient was inverted. The simulation performance was proportional to the forward modeling result. The WCM simulation error showed an increasing pattern from about -12dB based on the observed backscattering coefficient.