• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.574-583
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• 2021

Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.100-112
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• 2021

With the advent of big data, traffic prediction has been developed based on historical data analysis methods, but this method deteriorates prediction performance when a traffic incident that has not been observed occurs. This study proposes a method that can compensate for the reduction in traffic prediction accuracy in traffic incidents situations by hybrid approach of machine learning and traffic simulation. The blind spots of the data-driven method are revealed when data patterns that have not been observed in the past are recognized. In this study, we tried to solve the problem by reinforcing historical data using traffic simulation. The proposed method performs machine learning-based traffic prediction and periodically compares the prediction result with real time traffic data to determine whether an incident occurs. When an incident is recognized, prediction is performed using the synthetic traffic data generated through simulation. The method proposed in this study was tested on an actual road section, and as a result of the experiment, it was confirmed that the error in predicting traffic state in incident situations was significantly reduced. The proposed traffic prediction method is expected to become a cornerstone for the advancement of traffic prediction.

• Applied Chemistry for Engineering
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• v.32 no.2
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• pp.168-173
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• 2021

In this study, we measured total flavonoids after extracting the total flavonoids from lemongrass which is known to have a high content of antioxidant ingredients when using microwave energy. Also, optimal extraction conditions of active ingredients using central composite design-response surface methodology (CCD-RSM) were presented. Both ultrapure water and alcohol were used as extraction solvents and the volume ratio of ethanol/ultrapure water, microwave irradiation time, and microwave irradiation power were set as independence variables. And the extraction yield and total flavonoids were measured. The optimal extraction conditions using CCD-RSM were the volume ratio of ethanol/ultrapure water = 56.3 vol.%, the microwave irradiation time = 6.1 min, and the microwave irradiation power = 574.6 W. We could also obtain expected results of yield = 17.2 wt.% and total flavonoids = 44.7 ㎍ QE/mL dw under the optimum conditions. The comprehensive satisfaction degree of this formula was 0.8562. The P-value was calculated for the yield of 0.037 and the total flavonoids content of 0.002. The average error from actual experiments established for the verification of conclusions was lower than 2.5%. Therefore, a high favorable level could be obtained when the CCD-RSM was applied to the optimization of extraction process.

• Journal of the Korean Society of Radiology
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• v.15 no.2
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• pp.239-246
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• 2021

Portal Dosimetry was verified using EPID to secure the clinical application and reliability of the existing research dose evaluation. The dose distribution of Geant4 was compared with the measured value by 360° rotational irradiation with a 2.5 cm cone for stereotactic brain surgery. To confirm the dose distribution of patients with brain metastasis, the dose distribution investigated by inserting a Gafchromic EBT film into the parietal phantom and the dose distribution obtained from the parietal phantom using VMAT are compared and applied to actual patients. As a result of the analysis, it was confirmed that the accuracy of the beam center and the center of the couch coincide accurately with an error within 1mm as a result of QA through a pin ball. In addition, it was confirmed that the EBT3 film has excellent linearity in the range of 0 to 10 Gy according to various dose irradiation. In the same setting as the two cervical phantoms, we confirm that the implementation and simulation results calculations of dose calculations based on Geant4 using photon beams match the experimental data within the treatment planning volume (PTV). Therefore, volume modulated arc treatment (VMAT) 360° rotational irradiation was performed, and the result of iso-dose distribution analysis by rotational irradiation confirmed that it is appropriate to include a virtual tumor.

• Applied Chemistry for Engineering
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• v.29 no.6
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• pp.663-669
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• 2018

The process of extracting active ingredients from wheat sprout using ultrasound assisted method was optimized with a central composite design model. The response value of the central composite design model established the extraction yield and the total flavonoids content, main effects and interactive effects were analyzed depending on independent variables such as the extraction time, volume ratio of ethanol to ultrapure water, and ultrasonic irradiation power. The volume ratio of ethanol to ultrapure water and ultrasonic irradiation power were relatively large for the extraction yield and the extraction time was most significantly affected the total flavonoids, Considering both the extraction yield and total flavonoids content, the optimal extraction conditions were as follows: the extraction time of 17.00 min, volume ratio of ethanol to ultrapure water of 50.25 vol%, ultrasonic irradiation power of 551.70 W. In this case, the extraction yield and total flavonoids content were 28.43 wt% and $29.99{\mu}g\;QE/mL\;dw$, respectively. The actual experimental extraction yield and total flavonoids content under this condition were 8.73 wt% and $29.65{\mu}g\;QE/mL\;dw$, respectively with respective error rates of 1.05 and 1.13%.

• Journal of Ecology and Environment
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• v.42 no.4
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• pp.272-277
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• 2018

Background: Studying the ecosystem carbon cycle requires analysis of interrelationships between soil respiration (Rs) and the environment to evaluate the balance. Various methods and instruments have been used to measure Rs. The closed chamber method, which is currently widely used to determine Rs, creates a closed space on the soil surface, measures $CO_2$ concentration in the inner space, and calculates Rs from the increase. Accordingly, the method is divided into automatic or manual chamber methods (ACM and MCM, respectively). However, errors of these methods and differences in instruments are unclear. Therefore, we evaluated the characteristics and difference of Rs values calculated using both methods with actual data. Results: Both methods determined seasonal variation patterns of Rs, reflecting overall changes in soil temperature (Ts). ACM clearly showed detailed changes in Rs, but MCM did not, because such small changes are unknown as Rs values are collected monthly. Additionally, Rs measured using MCM was higher than that using ACM and differed depending on measured plots, but showed similar tendencies with all measurement times and plots. Contrastingly, MCM Rs values in August for plot 4 were very high compared with ACM Rs values because of soil disturbances that easily occur during MCM measurements. Comparing Rs values calculated using monthly means with those calculated using MCM, the ACM calculated values for monthly averages were higher or lower than those of similar measurement times using the MCM. The difference between the ACM and MCM was attributed to greater or lesser differences. These Rs values estimated the carbon released into the atmosphere during measurement periods to be approximately 57% higher with MCM than with ACM, at 5.1 and $7.9C\;ton\;ha^{-1}$, respectively. Conclusion: ACM calculated average values based on various Rs values as high and low for measurement periods, but the MCM produced only specific values for measurement times as representative values. Therefore, MCM may exhibit large errors in selection differences during Rs measurements. Therefore, to reduce this error using MCM, the time and frequency of measurement should be set to obtain Rs under various environmental conditions. Contrastingly, the MCM measurement is obtained during $CO_2$ evaluation in the soil owing to soil disturbance caused by measuring equipment, so close attention should be paid to measurements. This is because the measurement process is disturbed by high $CO_2$ soil concentration, and even small soil disturbances could release high levels into the chamber, causing large Rs errors. Therefore, the MCM should be adequately mastered before using the device to measure Rs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.688-694
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• 2018

The mixture ratio of two-component liquid silicone is important for the inherent physical characteristics of the finished product. Therefore, it is necessary to uniformly control the ratio of the main material and the sub-material. In this paper, a mixing-ratio control system was designed, which consists of a digital flow meter and a flow control system to measure the flow rate of the raw materials and a pumping system to maintain constant pressure and transfer of the raw materials. In addition, a program was developed to control the organic interlocking and mixing ratio. For the verification of the developed system, we compared the actual weight of raw material with the value measured by the flow meter during pumping, and we measured the physical properties of the mixed material by making test samples with and without the application of the mixing-ratio improvement algorithm. The measured value was close to the reference value with a hardness range of 46-47 and tensile strength of 9.3-9.5 MPa. These results show that the mixing ratio of the liquid silicone is controlled within an error range of ${\pm}0.5%$.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.457-467
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• 2018

Currently, the regulation and rules for public surveying and the UCPs (Unified Control Points) adapts those of the triangulated traverse surveying. In addition, such regulations do not take account of the unique characteristics of GNSS (Global Navigation Satellite System) surveying, thus there are difficulties in field work and data processing afterwards. A detailed procesure of GNSS processing has not yet been described either, and the verification of accuracy does not follow the generic standards. In order to propose an appropriate procedure for field surveys, we processed a short session (30 minutes) based on the scenarios similar to actual situations. The reference network in Seoul was used to process the same data span for 3 days. The temporal variation during the day was evaluated as well. We analyzed the accuracy of the estimated coordinates depending on the parameterization of tropospheric delay, which was compared with the 24-hr static processing results. Estimating the tropospheric delay is advantageous for the accuracy and stability of the coordinates, resulting in about 5 mm and 10 mm of RMSE (Root Mean Squared Error) for horizontal and vertical components, respectively. Based on the test results, we propose a procedure to estimate the daily solution and then combine them to estimate the final solution by applying the minimum constraints (no-net-translation condition). It is necessary to develop a web-based processing system using a high-end softwares. Additionally, it is also required to standardize the ID of the public control points and the UCPs for the automatic GNSS processing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.310-316
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• 2019

In automotive application, customers are demanding high efficiency and various functions for convenience. The demand for these automotive applications is steadily increasing. In this study, it has been studied the analysis of heat flow to improve the PCB(printed circuit board) heating performance of WPC (wireless power charger) recently developed for convenience. The charging performance of the wireless charger has been reduced due to power dissipation and thermal resistance of PCB. Therefore, it has been proposed optimal PCB design, layout and position of electronic parts through the simulation of heat flow analysis and PCB design was analyzed and decided at each design stage. Then, the experimental test is performed to verify the consistency of the analysis results under actual environmental conditions. In this paper, The PCB modeling and heat flow simulation in transient response were performed using HyperLynx Thermal and FloTHERM. In addition, the measurement was performed using infrared thermal imaging camera and used to verify the analysis results. In the final comparison, the error between analysis and experiment was found to be less than 10 % and the heating performance of PCB was also improved.

• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.65-74
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• 2020

Continuous and accurate instrument of river water usage is needed for sustainable river water management. Although the instrument methods applicable to each point of use of river water are different, more precise direct instrument methods are required at the point of major open channel. Users of river water should select appropriate direct instrument methods to measure usage, but there is a lack of standards and verification research. In this study, the H-Q rating curve method, ultrasonic method, and microwave method were applied directly to the test basin in the upper basin of Mangyeong river, and the accuracy of measurement data was evaluated by comparing absolute error between discharge data calculated by instrument method. When comparing the calculated discharge of point units, the ultrasonic method showed the best results of the actual measurement. Through continuous instrument, the sum of the daily and monthly units was compared, and the ultrasonic and microwave methods were shown to be highly accurate. Based on the results of this study, it is hoped that the appropriate direct measurement method can be selected according to the importance of the river water use facility, considering that the ultrasonic method and the microwave method are relatively costly compared to the water level-flow relationship method.