• Clean Technology
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• v.27 no.1
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• pp.47-54
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• 2021

The adsorption of Acid Fuchsin (AF) on granular activated carbon (GAC) was investigated for isothermal adsorption and kinetics and thermodynamic parameters by experimenting with the initial concentration, contact time, temperature, and pH of the dye as adsorption parameters. In the pH effect experiment, the adsorption of AF on activated carbon showed a bathtub type with increased adsorption at pH 3 and 11. The adsorption equilibrium data of AF fit well with the Freundlich isotherm model, and the calculated separation factor (1/n) value was found in which activated carbon can effectively remove AF. The pseudo-second-order kinetic model fits well within 7.88% of the error percent in the adsorption process. According to Weber and Morris's model plot, it was divided into two straight lines. The intraparticle diffusion rate was slow because the stage 2 (intraparticle diffusion) slope was smaller than that of stage 1 (boundary layer diffusion). Therefore, it was confirmed that the intraparticle diffusion was a rate-controlling step. The activation energy of AF (13.00 kJ mol-1) corresponded to the physical adsorption process (5 - 40 kJ mol-1). The free energy change of the AF adsorption by activated carbon showed negative values at 298-318 K. As the spontaneity increased with increasing temperature. The adsorption of AF was an endothermic reaction (ΔH = 22.65 kJ mol-1).

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.892-903
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• 2020

The rapid and accurate prediction of storm-surge height during typhoon attacks is essential in responding to coastal disasters. Most methods used for predicting typhoon data are based on numerical modeling, but numerical modeling takes significant computing resources and time. Recently, various studies on the expeditious production of predictive data based on artificial intelligence have been conducted, and in this study, artificial intelligence-based storm-surge height prediction was performed. Several learning data were needed for artificial intelligence training. Because the number of previous typhoons was limited, many synthesized typhoons were created using the tropical cyclone risk model, and the storm-surge height was also generated using the storm surge model. The comparison of the storm-surge height predicted using artificial intelligence with the actual typhoon, showed that the root-mean-square error was 0.09 ~ 0.30 m, the correlation coefficient was 0.65 ~ 0.94, and the absolute relative error of the maximum height was 1.0 ~ 52.5%. Although errors appeared to be somewhat large at certain typhoons and points, future studies are expected to improve accuracy through learning-data optimization.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.547-554
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• 2021

In order to quickly and accurately diagnose pneumonia on a chest X-ray image, different batch sizes of 4, 8, 16, and 32 were applied to the same Xception deep learning model, and modeling was performed 3 times, respectively. As a result of the performance evaluation of deep learning modeling, in the case of modeling to which batch size 32 was applied, the results of accuracy, loss function value, mean square error, and learning time per epoch showed the best results. And in the accuracy evaluation of the Test Metric, the modeling applied with batch size 8 showed the best results, and the precision evaluation showed excellent results in all batch sizes. In the recall evaluation, modeling applied with batch size 16 showed the best results, and for F1-score, modeling applied with batch size 16 showed the best results. And the AUC score evaluation was the same for all batch sizes. Based on these results, deep learning modeling with batch size 32 showed high accuracy, stable artificial neural network learning, and excellent speed. It is thought that accurate and rapid lesion detection will be possible if a batch size of 32 is applied in an automatic diagnosis study for feature extraction and classification of pneumonia in chest X-ray images using deep learning in the future.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.125-131
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• 2022

Recently, the prevalence of remotely managed patient care systems in medical institutions is increasing due to COVID-19. In particular, in the case of fluid monitoring, hospitals are considering introducing it as a system that can reduce patient safety and nurses' work. There are two products under development: a load cell method that measures weight and a method that detects drops of sap by infrared sensing. Although each product has differences in operation principle, sensor type, size, usage, and price, medical institutions are highly interested in the accuracy of the data obtained.In this study, two prototypes with different sensor methods were manufactured and the total amount of infusion per hour was measured to test the accuracy, which is the core of the infusion monitoring device. In addition, when there was an external movement, the change in the measured value of the sap was tested to evaluate the accuracy according to the measurement method. As a result of the experiment, there was a difference of less than 5% in the measurement value error of the two devices, and the load cell method showed a difference in the low-capacity measurement value and the infrared method in the high-capacity measurement value. As a result of this experiment, there was little difference in accuracy according to the sensor method of the infusion monitoring device, and it is considered that there is no problem in accuracy when used in a medical institution.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.185-192
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• 2021

Various methods have been proposed to determine the defect detection of welding bead, and recently sensor data and image data inspection have been steadily announced. There are advantages that sensor data inspection is highly accurate, and two-dimensional-based image data inspection is able to determine the position of the welding bead. However, when analyzing only with sensor data, it is difficult to determine whether the welding has been performed at the correct position. On the other hand, the image data inspection does not have high accuracy due to noise and measurement errors. In this paper, we propose a method that can complement the shortcomings of each inspection method and increase its advantages to improve accuracy and speed up inspection by fusing sensor data inspection which are average current, average volt, and mixed gas data, and image data inspection methods and is implemented as software. In addition, it is intended to allow users to conveniently and intuitively analyze and grasp the results by performing analysis using a graphical user interface(GUI) and checking the data and inspection results used for the inspection. Sensor inspection is performed using the characteristics of each sensor data, and image data is inspected by applying a morphology geodesic active contour algorithm. The experimental results showed 98% accuracy, and when performing the inspection on the four image data, and sensor data the inspection time was about 1.9 seconds, indicating the performance of software that can be used as a real-time inspector in the welding process.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.289-296
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• 2022

The purpose of this study was to investigate the inter-correlation between crude oil prices and Dry Bulk Freight rates. Eco-friendly shipping fuels has being actively developed to reduce carbon emission. However, carbon neutrality will take longer than anticipated in terms of the present development process. Because of OVID-19 and the Russian invasion of Ukraine, crude oil price fluctuation has been exacerbated. So we must examine the impact on Dry Bulk Freight rates the oil prices have had, because oil prices play a major role in shipping fuels. By using the VAR (Vector Autoregressive) model with monthly data of crude oil prices (Brent, Dubai and WTI) and Dry Bulk Freight rates (BDI, BCI and (BP I) 2008.10~2022.02, the empirical analysis documents that the oil prices have an impact on Dry bulk Freight rates. From the analysis of the forecast error variance decomposition, WTI has the largest explanatory relationship with the BDI and Dubai ranks seoond, Brent ranks third. In conclusion, WTI and Dubai have the largest impact on the BDI, while there are some differences according to the ship-type.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.29-36
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• 2022

The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.169-175
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• 2022

Korea's construction industry has a shortage and aging of construction manpower, low productivity compared to other industries, and a high rate of industrial accidents. The Ministry of Land, Infrastructure and Transport is preparing for the 4th industrial revolution and is expanding investment in construction automation and innovative growth engines to improve productivity in the construction industry. In order for new technologies to be utilized in the road construction field, the accuracy of the technologies and the applicability of each type of work must be evaluated. In this study, the accuracy of the mobile mapping system was tried to verify based on the relevant work regulations, and to suggest the applicability of the mobile mapping system to high-speed driving tracks through data acquisition and analysis on road construction sites. The accuracy of the equipment used in the study was verified in accordance with the relevant work regulations, and the possibility of applying the mobile mapping system used for the study to road construction surveying was presented with a maximum error of less than 10cm in the horizontal and vertical directions. In addition, the possibility of utilizing the road construction survey using the mobile mapping system was presented through comparison with the existing method for data acquisition time for construction surveying, production of construction status survey results, and calculation of heatmap and earthworks. In the future, the use of construction status surveying of the mobile mapping system will greatly improve the efficiency of construction work.

• The Journal of Korean Academy of Prosthodontics
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• v.60 no.4
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• pp.313-319
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• 2022

Complete dentures are one of the most basic treatment methods for the treatment of edentulous patients. The manufacturing process of traditional complete dentures goes through the steps of taking primary impressions, secondary impressions, jaw relation record, trying in wax denture, and final denture insertion. Multiple visits and complex manufacturing procedures are required, and errors may occur in each step. With the development of digital technology, manufacturing steps have been reduced by introducing digital technology to the denture treatment process. In the process of manufacturing dentures by introducing a digital process, a more precise work is possible using Computer-Aided Design, and it is possible to shorten the period of labor and reduce the number of visits. In this case, the anterior teeth arrangement of the patient's existing dentures was transferred to the final dentures using a digital method. After taking impression, try-in dentures were digitally fabricated and tried in the oral cavity to evaluate their retention in the oral cavity. Final dentures were manufactured by milling process. The number of visits was reduced, satisfactory retention and stability of dentures were obtained, and aesthetic recovery was achieved.

• Journal of the Korea Institute of Building Construction
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• v.21 no.3
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• pp.203-211
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• 2021

Recently, the insulaton design standards for reducing the energy use of buildings have been strengthened. Althoug insulation work is the most cost-effective method for reducing the primary energy consumption per unit area of a building, there are no evaluation criteria for insulation performance at the time of construction and completion inspection. The purpose of this study is to provide objective data by establishing a standard for an analysis method and a method for easily experimenting with the exterior wall thermal transmittance of an apartment house using a thermal transmittance measuring device(TESTO 435). For the exterior wall of the test subject, the specific heat per unit area exceeded 20kJ/(m²·K), and the data at the end point suitable for ISO 9869-1 were analyzed by the average method. The measured values of the thermal transmittance for 3 consecutive days converged within +5% of the desing value, and the standard deviation of the thermal transmittance by day decreased in the order of 1-Day > 3-Day > 2-Day. The standard deviation of the thermal transmittance by time period decreased in the order of 00:00~24:00 < 19:00~07:00 < 00:00~07:00. The measured value of the thermal transmittance for the time perion of 00:00 to 07:00 per day almost coincided with an error of -3% to + 2% compare to the desing value.