• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.229-250
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• 2022

Since the publication of Markowitz's (1952) mean-variance portfolio model, research on portfolio optimization has been conducted in many fields. The existing mean-variance portfolio model forms a nonlinear convex problem. Applying Dantzig's linear programming method, it was converted to a linear form, which can effectively reduce the algorithm computation time. In this paper, we proposed a Dantzig perturbation portfolio model that can reduce management costs and transaction costs by constructing a portfolio with stable and small (sparse) assets. The average return and risk were adjusted according to the purpose by applying a perturbation method in which a certain part is invested in the existing benchmark and the rest is invested in the assets proposed as a portfolio optimization model. For a covariance estimation, we proposed a Gaussian kernel weight covariance that considers time-dependent weights by reflecting time-series data characteristics. The performance of the proposed model was evaluated by comparing it with the benchmark portfolio with 5 real data sets. Empirical results show that the proposed portfolios provide higher expected returns or lower risks than the benchmark. Further, sparse and stable asset selection was obtained in the proposed portfolios.

• Journal of Hydrogen and New Energy
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• v.32 no.6
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• pp.442-454
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• 2021

The porous transport layer (PTL) is essential to effectively remove oxygen and hydrogen gas from the electrode surface at high current density operation conditions. In this study, the effect of PTL with different characteristics such as pore size, pore gradient, interfacial coating was investigated by multi-layered sintered mesh. A water electrolysis single cell of active area of the 34.56 cm² was constructed, and IV performance and impedance analysis were conducted in the range of 0 to 2.0 A/cm². It was confirmed that the multi-layered sintered mesh PTL, which have an average pore size of 25 to 57 ㎛ and a larger pore gradient, removed bubbles effectively and thus seemed to improve IV performance. Also, it was confirmed that the catalytic metals such as Ni, NiMo coating on the PTL reduced activation overpotential, but increased mass transport overpotential.

• Science of Emotion and Sensibility
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• v.24 no.4
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• pp.129-138
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• 2021

This study aimed to determine the effects of the shape and attachment position of stretchable textile sensors coated with carbon nanotube on their performance when used to measure children's joint movements. Moreover, the child-safe requirements for fabric motion sensors are established. The child participants were advised to wear integrated clothing equipped with the sensors of various shapes (rectangular and boat-shaped) and attachment positions (at the knee and elbow joints or 4 cm below the joints). The voltage change induced by the elongation and contraction of the fabric sensors was determined for arm and leg flexion-extension motions at 60 deg/s (three measurements of 10 repeats each for 60°and 90°angles, for a total of 60 repetitions). Their dependability was determined by comparing the fabric motion sensors to the associated acceleration sensors. The experimental results indicate that the rectangular-shaped sensor affixed 4 cm below the joint is the most effective fabric motion sensor for measuring children's arm and leg motions. In this study, we designed a textile sensor capable of tracking children's joint motion and analyzed the sensor shape and attachment position on motion sensing clothing. We demonstrated that flexible fabric sensors integrated into garments may be used to detect the joint motions of the human body.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.445-454
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• 2022

Ice accretion on the aircraft components, such as wings, fuselage, and empennage, can occur when the aircraft encounters a cloud zone with high humidity and low temperature. The prevention of ice accretion is important because it causes a decrease in the aerodynamic performance and flight stability, thus leading to fatal safety problems. In this study, a shape design optimization of a multi-element airfoil is performed to minimize the amount of ice accretion on the high-lift device including leading-edge slat, main element, and trailing-edge flap. The design optimization framework proposed in this paper consists of four major parts: air flow, droplet impingement and ice accretion simulations and gradient-free optimization algorithm. Reynolds-averaged Navier-Stokes (RANS) simulation is used to predict the aerodynamic performance and flow field around the multi-element airfoil at the angle of attack 8°. Droplet impingement and ice accretion simulations are conducted using the multi-physics computational analysis tool. The objective function is to minimize the total mass of ice accretion and the design variables are the deflection angle, gap, and overhang of the flap and slat. Kriging surrogate model is used to construct the response surface, providing rapid approximations of time-consuming function evaluation, and genetic algorithm is employed to find the optimal solution. As a result of optimization, the total mass of ice accretion on the optimized multielement airfoil is reduced by about 8% compared to the baseline configuration.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.67-78
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• 2022

Interest in bio-signal monitoring of wearable devices is increasing significantly as the next generation needs to develop new devices to dominate the global market of the information and communication technology industry. Accordingly, this research developed a resistive textile strain sensor through a wetting process in a single-wall carbon nanotube dispersion solution using an E-Band with low hysteresis. To measure the resistance signal in the E-Band to which electrical conductivity is applied, a universal material tester, an Arduino, and LCR meters that are microcontroller units were used to measure the resistance change according to the tensile change. To effectively handle various noises generated due to the characteristics of the fabric textile strain sensor, the filter performance of the sensor was evaluated using the moving average filter, Savitsky-Golay filter, and intermediate filters of signal processing. As a result, the reliability of the filtering result of the moving average filter was at least 89.82% with a maximum of 97.87%, and moving average filtering was suitable as the noise filtering method of the textile strain sensor.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.897-903
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• 2021

Purpose: Recently, ransomware damage that encrypts victim's data through hacking and demands money in exchange for releasing it is increasing domestically and internationally. Accordingly, research and development on various response technologies and solutions are in progress. Method: A secure storage area and a general storage area were created in the same virtual environment, and the sample data was saved by registering the access process. In order to check whether the stored sample data is infringed, the ransomware sample was executed and the hash function of the sample data was checked to see if it was infringed. The access control performance checked whether the sample data was accessed through the same name and storage location as the registered access process. Result: As a result of the experiment, the sample data in the secure storage area maintained data integrity from ransomware and unauthorized processes. Conclusion: Through this study, the creation of a secure storage area and the whitelist-based access control method are evaluated as suitable as a method to protect important data, and it is possible to provide a more secure computing environment through future technology scalability and convergence with existing solutions.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.118-129
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• 2022

The purpose of this report is to study a strategic model of promotion activities through various analysis and sales forecasting by selecting wearable products for domestic online companies and collecting sales data. For data analysis, various algorithms are used for analysis and the results are selected as the optimal model. The gradation boosting model, which is selected as the best result, will allow nine independent variables to be entered, including promotion type, price, amount, gender, model, company, grade, sales date, and region, when predicting dependent variables through supervised learning. In this study, the review values set as dependent variables for each type of sales promotion were studied in more detail through the ensemble analysis technique, and the main purpose is to analyze and predict them. The purpose of this study is to study the grades. As a result of the analysis, the evaluation result is 95% of AUC, and F1 is about 93%. In the end, it was confirmed that among the types of sales promotion activities, value-added benefits affected the number of reviews and review grades, and that major variables affected the review and review grades.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.3
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• pp.91-98
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• 2021

The installation and performance test of the ISOL (Isotope Separation On Line) system for the generation and separation of Rare Isotopes (RI) beams is in progress at the Rare Isotope Science Project (RISP), Institute for Basic Science (IBS). The various RI beams generated by the ISOL target/ion source go through the beam lines and separators, and only the RI beam desired by the user is selected and transmitted to the superconducting linear accelerator at the downstream of the ISOL. In the ISOL system, two separators are installed to separate a specific RI beam, and control is performed by the Experimental Physics and Industrial Control System (EPICS). In this study, an EPICS IOC (Input-Output Control) was developed to measure the magnetic field of a dipole magnet for mass separation of a multivalent (n+) RI beam in the A/Q separator, which is one of the ISOL RI beam separators. The operational stability of the A/Q separator was tested through a magnetic field measurement using a Hall probe.

• Journal of the Korean GEO-environmental Society
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• v.23 no.5
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• pp.33-39
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• 2022

For a slag-cement-bentonite (slag-CB) cut-off wall, GGBS replaces a part of the cement mixed to build a CB cut-off wall, which is used to block the flow and leakage of pollutants or groundwater; prevent seawater infiltration; and repair or reinforcement an aged embankments. Slag-CB cut-off walls are used in various applications in different fields where groundwater control is required due to its excellent characteristics. Such properties include high strength, low permeability, high durability and chemical resistance. However, despite these advantages, slag-CB cut-off walls are not extensively studied in Korea and thus are not applied in many cases. Particularly, GGBS, which replaces cement in a mixture, has different properties depending on its country of production. Consequently, it is necessary to perform various studies on slag-CB cut-off walls that use GGBS produced in Korea in order to increase its usability. This study has evaluated the bleeding rate, setting time, strength, and permeability in relation to the cement replacement rate of GGBS produced in Korea for slag-CB cut-off walls, with the aim to increase its usability. The evaluation found that slag-CB cut-off walls, made of a mixture containing GGBS produced in Korea, have a lower bleeding rate and permeability, and higher strengththan CB cut-off walls. It was also analyzed that such improved performance is more effective with a higher cement replacement rate of GGBS.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.237-250
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• 2022

In this study, we propose a method to estimate the biomass of invertebrate grazers from the videos with underwater drones by using a multi-object tracking model based on deep learning. In order to detect invertebrate grazers by classes, we used YOLOv5 (You Only Look Once version 5). For biomass estimation we used DeepSORT (Deep Simple Online and real-time tracking). The performance of each model was evaluated on a workstation with a GPU accelerator. YOLOv5 averaged 0.9 or more mean Average Precision (mAP), and we confirmed it shows about 59 fps at 4 k resolution when using YOLOv5s model and DeepSORT algorithm. Applying the proposed method in the field, there was a tendency to be overestimated by about 28%, but it was confirmed that the level of error was low compared to the biomass estimation using object detection model only. A follow-up study is needed to improve the accuracy for the cases where frame images go out of focus continuously or underwater drones turn rapidly. However,should these issues be improved, it can be utilized in the production of decision support data in the field of invertebrate grazers control and monitoring in the future.