• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.209-218
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• 2021

First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.489-495
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• 2020

The amount of data is increasing through various IT devices in a hyper-connected society where the 4th revolution is progressing, and new value can be created by analyzing that data. This paper was collected total 1,526 articles from 2017 to 2019 in central magazines, economic magazines, regional associations, and major broadcasting companies with the keyword "(East Coast Tourism or East Coast Travel) and Gangwon-do" through Bigkinds. It was performed the topic modeling using LDA algorithm implemented in the R language to analyze the collected 1,526 articles. It was extracted keywords for each year from 2017 to 2019, and classified and compared keywords with high frequency for each year. It was setted the optimal number of topics to 8 using Log Likelihood and Perplexity, and then inferred 8 topics using the Gibbs Sampling method. The inferred topics were Gangneung and Beach, Goseong and Mt.Geumgang, KTX and Donghae-Bukbu line, weekend sea tour, Sokcho and Unification Observatory, Yangyang and Surfing, experience tour, and transportation network infra. The changes of articles on East coast tourism was was analyzed using the proportion of the inferred eight topics. As the result, the proportion of Unification Observatory and Mt. Geumgang showed no significant change, the proportion of KTX and experience tour increased, and the proportion of other topics decreased in 2018 compared to 2017. In 2019, the proportion of KTX and experience tour decreased, but the proportion of other topics showed no significant change.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.697-705
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• 2020

This paper deals with an analysis of crustal movement for the sourthern part of Korean peninsula using GNSS (Global Navigation Satellite System) data. An earthquake of more than 5.0 occurred in the southeastern region of the Korean Peninsula, and it is necessary to evaluate the risk of earthquakes in various ways.In order to reveal long-term tectonic movement patten in Pohang and Gyeongju provinces, we derived crustal movement parameters related with elastic theory. We used GAMIT/GLOBK for analyzing seven-year interval GNSS data of CORS (Continuously Operating Reference Stations). The azimuth of velocity vectors trended generally about 110° with an mean magnitude of 31mm/yr.The main characteristics of the strain change for seven-year in Korea obtaind from our study. Direction of the principal axis of the maximum compression is ENE-WSW as a whole, through there are some exceptions. The mean rate of the maximum shear strain change is (0.11±0.07)μ/yr, that is approximately one third that of Chubu district, Central Japan. Taking into account our results, the mean rate of maximum shear in southern part of Korean peninsula is considered as reasonable. The mean azimuth of principal strain is about (85.4°±26.8°). There are some exceptions of azimuth because the average azimuth differ from the left and right side in Yangsan fault which are about (73.2°±21.5°) and (105.2°±17.0°) respectively, It is noteworthy that the high seismicity areas in the southern part of Korea peninsula almost coincides with the area of large strain rate. As a conclusion, it could be stated that the our study represents the characteristics of crustal deformation in the southern part of peninsula, and contributes to the researches on earthquake disaster management.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.303-311
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• 2022

Recently the telemedicine platform firms which have been temporarily permitted since COVID-19 outbreak have increasingly provided online prescription drugs delivery, causing concerns among incumbent providers of medicine, some of whom began to take aggressive actions again them. In this study, using game theoretic market entry - deterrence model, we show that although the incumbent medicine provider can effectively deter entry by the telemedicine platform firms by its preemptive action, accommodation could be a optimal action when telemedicine platform firms already have penetrated the market with their being permitted to do business due to the COVID-19. However, for the incumbent to cooperate for the successful change in the retail market for medicines, policies like placing a ceiling on the maximum number of taking prescriptions by the pharmacists a day in the telemedince platform network, providing favorable exposure of community pharmacists on the telemedicine platform user interface, and allowing community pharmacies to participate as shareholders of the telemedicine platform firms in its initial public opening of capital, are suggested.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.793-810
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• 2022

Synthetic Aperture Radar (SAR) is considered to be suitable for near real-time inundation monitoring. The distinctly different intensity between water and land makes it adequate for waterbody detection, but the intrinsic speckle noise and variable intensity of SAR images decrease the accuracy of waterbody detection. In this study, we suggest two modules, named 'morphology module' and 'edge-enhanced module', which are the combinations of pooling layers and convolutional layers, improving the accuracy of waterbody detection. The morphology module is composed of min-pooling layers and max-pooling layers, which shows the effect of morphological transformation. The edge-enhanced module is composed of convolution layers, which has the fixed weights of the traditional edge detection algorithm. After comparing the accuracy of various versions of each module for U-Net, we found that the optimal combination is the case that the morphology module of min-pooling and successive layers of min-pooling and max-pooling, and the edge-enhanced module of Scharr filter were the inputs of conv9. This morphologic and edge-enhanced U-Net improved the F1-score by 9.81% than the original U-Net. Qualitative inspection showed that our model has capability of detecting small-sized waterbody and detailed edge of water, which are the distinct advancement of the model presented in this research, compared to the original U-Net.

• Clean Technology
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• v.28 no.4
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• pp.278-284
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• 2022

This study presents an excellent planar heater based on low-dimensional composites. By optimizing the ratio of 1D carbon nanotubes (CNT) and 2D MXene (Ti₃C₂T_X), it is possible to create a planar heater that has superior electrical conductivity and high heat generation characteristics. Low-dimensional composites were prepared by mixing CNT paste and MXene solution with eco-friendly waterborne polyurethane (WPU). In order to find the optimal mixing ratio for the MXene-CNT-WPU composites, samples with MXene to CNT weight ratios of 3:1, 1:1, 1:3, 1:7, and 1:14 were investigated. In addition to these different weight ratios, 5 wt% WPU was equally applied to each sample. It was confirmed that the higher the weight ratio of CNT, the lower the sheet resistance and the higher the heating temperature. In particular, when the MXene-CNT-WPU planar heater was fabricated by mixing MXene and CNT at a weight ratio of 1:7 and 1:14, the heating temperature was higher than the heating temperature of a CNT-WPU planar heater. These characteristics are due to the optimized mixture of the 1D materials (CNT) and the 2D materials (MXene) causing the formation of a flat surface and a dense network structure. The low-dimensional composites manufactured with the optimized mixing ratios found in this study are expected to be applied in flexible electronic devices.

• Korean Journal of Clinical Pharmacy
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• v.32 no.3
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• pp.215-225
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• 2022

Background: Patients with hematologic cancers have a risk of drug-related problems (DRPs) from medications associated with chemotherapy and supportive care. Although the role of oncology pharmacists has been widely documented in the literature, few studies have reported its impact on cost reduction. This study aimed to describe the activities of oncology pharmacists with respect to hematologic diseases and evaluate the associated cost avoidance. Methods: From January to July 2021, patients admitted to the department of hemato-oncology at Seoul National University, Bundang Hospital were studied. The activities of oncology pharmacists were reported by DRP type following the Pharmaceutical Care Network version 9.1 guidelines, and the acceptance rate was calculated. The avoided cost was estimated based on the cost of the pharmacy intervention, pharmacist manpower, and prescriptions associated with the intervention. Results: Pharmacists intervened in 584 prescriptions from 208 patients during the study period. The most prevalent DRP was "adverse drug event (possibly) occurring" (32.4%), followed by "effect of drug treatment not optimal" (28.6%). "Drug selection" (42.5%) and "dose selection" (30.3%) were the most common causes of DRPs. The acceptance rate of the interventions was 97.1%. The total avoidance cost was KRW 149,468,321; the net profit of the avoidance cost, excluding labor costs, was KRW 121,051,690; and the estimated cost saving was KRW 37,223,748. Conclusion: Oncology pharmacists identified and resolved various types of DRPs from prescriptions for patients with hematologic disease, by reviewing the prescriptions. Their clinical service contributed to enhanced patient safety and the avoidance of associated costs.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.367-374
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• 2022

This papter presents the use of the automatic differential method based on the backpropagation method to obtain the design sensitivity and its application to topology optimization considering the stress constraints. Solving topology optimization problems with stress constraints is difficult owing to singularities, the local nature of stress constraints, and nonlinearity with respect to design variables. To solve the singularity problem, the stress relaxation technique is used, and p-norm for stress constraints is applied instead of local stresses for global stress measures. To overcome the nonlinearity of the design variables in stress constraint problems, it is important to analytically obtain the exact design sensitivity. In conventional topology optimization, design sensitivity is obtained efficiently and accurately using the adjoint variable method; however, obtaining the design sensitivity analytically and additionally solving the adjoint equation is difficult. To address this problem, the design sensitivity is obtained using a backpropagation technique that is used to determine optimal weights and biases in the artificial neural network, and it is applied to the topology optimization with the stress constraints. The backpropagation technique is used in automatic differentiation and can simplify the calculation of the design sensitivity for the objectives or constraint functions without complicated analytical derivations. In addition, the backpropagation process is more computationally efficient than solving adjoint equations in sensitivity calculations.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.269-282
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• 2023

The purpose of this study was to construct land cover maps using a deep learning model and to select the optimal deep learning model for land cover classification by adjusting the dataset such as input image size and Stride application. Two types of deep learning models, the U-net model and the DeeplabV3+ model with an Encoder-Decoder network, were utilized. Also, the combination of the two deep learning models, which is an Ensemble model, was used in this study. The dataset utilized RapidEye satellite images as input images and the label images used Raster images based on the six categories of the land use of Intergovernmental Panel on Climate Change as true value. This study focused on the problem of the quality improvement of the dataset to enhance the accuracy of deep learning model and constructed twelve land cover maps using the combination of three deep learning models (U-net, DeeplabV3+, and Ensemble), two input image sizes (64 × 64 pixel and 256 × 256 pixel), and two Stride application rates (50% and 100%). The evaluation of the accuracy of the label images and the deep learning-based land cover maps showed that the U-net and DeeplabV3+ models had high accuracy, with overall accuracy values of approximately 87.9% and 89.8%, and kappa coefficients of over 72%. In addition, applying the Ensemble and Stride to the deep learning models resulted in a maximum increase of approximately 3% in accuracy and an improvement in the issue of boundary inconsistency, which is a problem associated with Semantic Segmentation based deep learning models.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.91-101
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• 2023

In this study, we estimated the concentration of chlorophyll-a (Chl-a) using hyperspectral water surface reflectance in an inland weir (Baekjae weir) and estuarine reservoir (Namyang Reservoir) for monitoring the occurrence of algae in freshwater in South Korea. The hyperspectral reflectance was measured by aircraft in Baekjae Weir (BJW) from 2016 to 2017, and a drone in Namyang Reservoir (NYR) from 2020 to 2021. The 30 reflectance bands (BJW: 400-530, 620-680, 710-730, 760-790 nm, NYR: 400-430, 655-680, 740-800 nm) that were highly related to Chl-a concentration were selected using permutation importance. Artificial neural network based Chl-a estimation model was developed using the selected reflectance in both water bodies. And the performance of the model was evaluated with the coefficient of determination (R²), the root mean square error (RMSE), and the mean absolute error (MAE). The performance evaluation results of the Chl-a estimation model for each watershed was R²: 0.63, 0.82, RMSE: 9.67, 6.99, and MAE: 11.25, 8.48, respectively. The developed Chl-a model of this study may be used as foundation tool for the optimal management of freshwater algal blooms in the future.