• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.41-50
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• 2022

In this paper, a method to directly calculate the major elements of skin color such as melanin and hemoglobin from the RGB signal of the camera is proposed. The main elements of skin color typically measure spectral reflectance using specific equipment, and reconfigure the values at some wavelengths of the measured light. The values calculated by this method include such things as melanin index and erythema index, and require special equipment such as a spectral reflectance measuring device or a multi-spectral camera. It is difficult to find a direct calculation method for such component elements from a general digital camera, and a method of indirectly calculating the concentration of melanin and hemoglobin using independent component analysis has been proposed. This method targets a region of a certain RGB image, extracts characteristic vectors of melanin and hemoglobin, and calculates the concentration in a manner similar to that of Principal Component Analysis. The disadvantage of this method is that it is difficult to directly calculate the pixel unit because a group of pixels in a certain area is used as an input, and since the extracted feature vector is implemented by an optimization method, it tends to be calculated with a different value each time it is executed. The final calculation is determined in the form of an image representing the components of melanin and hemoglobin by converting it back to the RGB coordinate system without using the feature vector itself. In order to improve the disadvantages of this method, the proposed method is to calculate the component values of melanin and hemoglobin in a feature space rather than an RGB coordinate system using a feature vector, and calculate the spectral reflectance corresponding to the skin color using a general digital camera. Methods and methods of calculating detailed components constituting skin pigments such as melanin, oxidized hemoglobin, deoxidized hemoglobin, and carotenoid using spectral reflectance. The proposed method does not require special equipment such as a spectral reflectance measuring device or a multi-spectral camera, and unlike the existing method, direct calculation of the pixel unit is possible, and the same characteristics can be obtained even in repeated execution. The standard diviation of density for melanin and hemoglobin of proposed method was 15% compared to conventional and therefore gives 6 times stable.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.127-135
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• 2021

To respond to the threat of global warming, countries around the world are promoting the spread of renewable energy and reduction of carbon emissions. In accordance with the United Nation's Sustainable Development Goal to combat climate change and its impacts, global automakers are pushing for a full transition to electric vehicles within the next 10 years. Electric vehicles can be a useful means for reducing carbon emissions, but in order to reduce carbon generated in the stage of producing electricity for charging, a power generation system using eco-friendly renewable energy is required. In this study, we propose a smart electric mobility operating system integrated with off-grid solar power plants established in Tanzania, Africa. By applying smart monitoring and communication functions based on Arduino-based computing devices, information such as remaining battery capacity, battery status, location, speed, altitude, and road conditions of an electric vehicle or electric motorcycle is monitored. In addition, we present a scenario that communicates with the surrounding independent solar power plant infrastructure to predict the drivable distance and optimize the charging schedule and route to the destination. The feasibility of the proposed system was verified through test runs of electric motorcycles. In considering local environmental characteristics in Tanzania for the operation of the electric mobility system, factors such as eco-friendliness, economic feasibility, ease of operation, and compatibility should be weighed. The smart electric mobility operating system proposed in this study can be an important basis for implementing the SDGs' climate change response.

• Clean Technology
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• v.28 no.4
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• pp.309-315
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• 2022

Research was conducted to derive the optimal operation conditions and the optimal cathode for using a DSA electrode as an anode to minimize electrode consumption during the removal of nitrogen from wastewater by the electro-chemical method. Of the various electrodes tested as cathodes, brass was determined to be the optimal electrode. It had the highest NO₃-N removal rate and the lowest concentration of residual NH₃-N, a by-product when Cl is present in the solution. Investigating the effect of current density found that when the initial concentration of NO₃-N was 50 mg L^-1, the optimal current density was 15 mA cm^-2. In addition, current densities above 15 mA cm^-2 did not significantly affect the NO₃-N removal rate. The effect of electrolytes on removing NO₃-N and minimizing NH₃-N was investigated by using Na₂SO₄ and NaCl as electrolytes and varying the reaction times. When Na₂SO₄ and NaCl are mixed at a ratio of 1.0 g L^-1 to 0.5 g L^-1 and reacted for 90 min at a current density of 15 mA cm^-2 and an initial NO₃-N concentration of 50 mg L^-1, the removal rate of NO₃-N was about 48% and there was no residual NH₃-N. On the other hand, when using only 1.5 g L^-1 of NaCl as an electrolyte, the removal rate of NO₃-N was the highest at about 55% and there was no residual NH₃-N.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.165-204
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• 2022

This study organized data from 2000 to 2014 for 20 grid-connected countries in Europe and analyzed the determinants of carbon emissions through the panel GLS method considering the problem of heteroscedasticity and autocorrelation. At the same time, the effect of introducing ETS was considered by dividing the sample period as of 2005 when the European emission trading system was introduced. Carbon emissions from individual countries were used as dependent variables, and proportion of generation by each source, power self-sufficiency ratio of neighboring countries, power production from resource-holding countries, concentration of power sources, total energy consumption per capita in the industrial sector, tax of electricity, net electricity export per capita, and size of national territory per capita. According to the estimation results, the proportion of nuclear power and renewable energy generation, concentration of power sources, and size of the national territory area per capita had a negative (-) effect on carbon emissions both before and after 2005. On the other hand, the proportion of coal power generation, the power supply and demand rate of neighboring countries, the power production of resource-holding countries, and the total energy consumption per capita in the industrial sector were found to have a positive (+) effect on carbon emissions. In addition, the proportion of gas generation had a negative (-) effect on carbon emissions, and tax of electricity were found to have a positive (+) effect. However, all of these were only significant before 2005. It was found that net electricity export per capita had a negative (-) effect on carbon emissions only after 2005. The results of this study suggest macroscopic strategies to reduce carbon emissions to green growth, suggesting mid- to long-term power mix optimization measures considering the electricity trade market and their role.

• Journal of the Korean Electrochemical Society
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• v.26 no.1
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• pp.1-10
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• 2023

The cathode, which is one of the four major components of a lithium secondary battery, is an important component responsible for the energy density of the battery. The mixing process of active material, conductive material, and polymer binder is very essential in the commonly used wet manufacturing process of the cathode. However, in the case of mixing conditions of the cathode, since there is no systematic method, in most cases, differences in performance occur depending on the manufacturer. Therefore, LiMn₂O₄ (LMO) cathodes were prepared using a commonly used THINKY mixer and homogenizer to optimize the mixing method in the cathode slurry preparation step, and their characteristics were compared. Each mixing condition was performed at 2000 RPM and 7 min, and to determine only the difference in the mixing method during the manufacture of the cathode other experiment conditions (mixing time, material input order, etc.) were kept constant. Among the manufactured THINKY mixer LMO (TLMO) and homogenizer LMO (HLMO), HLMO has more uniform particle dispersion than TLMO, and thus shows higher adhesive strength. Also, the result of the electrochemical evaluation reveals that HLMO cathode showed improved performance with a more stable life cycle compared to TLMO. The initial discharge capacity retention rate of HLMO at 69 cycles was 88%, which is about 4.4 times higher than that of TLMO, and in the case of rate capability, HLMO exhibited a better capacity retention even at high C-rates of 10, 15, and 20 C and the capacity recovery at 1 C was higher than that of TLMO. It's postulated that the use of a homogenizer improves the characteristics of the slurry containing the active material, the conductive material, and the polymer binder creating an electrically conductive network formed by uniformly dispersing the conductive material suppressing its strong electrostatic properties thus avoiding aggregation. As a result, surface contact between the active material and the conductive material increases, electrons move more smoothly, changes in lattice volume during charging and discharging are more reversible and contact resistance between the active material and the conductive material is suppressed.

• Fashion & Textile Research Journal
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• v.24 no.6
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• pp.667-685
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• 2022

This paper aims to investigate 4D printing materials for soft robots. 4D printing is a targeted evolution of the 3D printed structure in shape, property, and functionality. It is capable of self-assembly, multi-functionality, and self-repair. In addition, it is time-dependent, printer-independent, and predictable. The shape-shifting behaviors considered in 4D printing include folding, bending, twisting, linear or nonlinear expansion/contraction, surface curling, and generating surface topographical features. The shapes can shift from 1D to 1D, 1D to 2D, 2D to 2D, 1D to 3D, 2D to 3D, and 3D to 3D. In the 4D printing auxetic structure, the kinetiX is a cellular-based material design composed of rigid plates and elastic hinges. In pneumatic auxetics based on the kirigami structure, an inverse optimization method for designing and fabricating morphs three-dimensional shapes out of patterns laid out flat. When 4D printing material is molded into a deformable 3D structure, it can be applied to the exoskeleton material of soft robots such as upper and lower limbs, fingers, hands, toes, and feet. Research on 4D printing materials for soft robots is essential in developing smart clothing for healthcare in the textile and fashion industry.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.281-298
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• 2023

Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.49 no.3
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• pp.231-245
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• 2023

In the cosmetics industry, it is important to develop new materials for functional cosmetics such as whitening, wrinkles, anti-oxidation, and anti-aging, as well as technology to increase absorption when applied to the skin. Therefore, in this study, we tried to optimize the nanoemulsion formulation by utilizing response surface methodology (RSM), an experimental design method. A nanoemulsion was prepared by a high-pressure emulsification method using Glabridin as an active ingredient, and finally, the optimized skin absorption rate of the nanoemulsion was evaluated. Nanoemulsions were prepared by varying the surfactant content, cholesterol content, oil content, polyol content, high-pressure homogenization pressure, and cycling number of high-pressure homogenization as RSM factors. Among them, surfactant content, oil content, high-pressure homogenization pressure, and cycling number of high-pressure homogenization, which are factors that have the greatest influence on particle size, were used as independent variables, and particle size and skin absorption rate of nanoemulsion were used as response variables. A total of 29 experiments were conducted at random, including 5 repetitions of the center point, and the particle size and skin absorption of the prepared nanoemulsion were measured. Based on the results, the formulation with the minimum particle size and maximum skin absorption was optimized, and the surfactant content of 5.0 wt%, oil content of 2.0 wt%, high-pressure homogenization pressure of 1,000 bar, and the cycling number of high-pressure homogenization of 4 pass were derived as the optimal conditions. As the physical properties of the nanoemulsion prepared under optimal conditions, the particle size was 111.6 ± 0.2 nm, the PDI was 0.247 ± 0.014, and the zeta potential was -56.7 ± 1.2 mV. The skin absorption rate of the nanoemulsion was compared with emulsion as a control. As a result of the nanoemulsion and general emulsion skin absorption test, the cumulative absorption of the nanoemulsion was 79.53 ± 0.23%, and the cumulative absorption of the emulsion as a control was 66.54 ± 1.45% after 24 h, which was 13% higher than the emulsion.

• The Journal of Korean Society for Radiation Therapy
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• v.34
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• pp.51-60
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• 2022

Objectives: The purpose is to evaluate dosimetric performance and delivery efficiency of VMAT with Halcyon LINAC for double target spine SBRT Materials and Methods: 12 patients with spine oligometastases were retrospectively studied. Single-isocenter spine SBRT plans was established using Halcyon® with Dual Layer MLC and Truebeam® with High Definition MLC. All patients' plans were created in Eclipse TPS through the identical conditions and optimization. C.I, H.I, G.I (Gradient Index), maximal and volumetric doses to spinal cord and low dose area were evaluated for comparison of both plans. Also, total MU and BOT(Beam On Time) were evaluated. Results: Halcyon plans was no Statistical differences in C.I and H.I. However, the average of G.I was 4.64 for Halcyon, which decreased to 5.5% compared to Truebeam (P<0.001). Halcyon plans demonstrated statistically significant reduced G.I. The average of 50% and 25% isodose volume was 487.56 cc (-3.82%, P<0.001), 1859.45 cc (-4.75%, P<0.001) in Halcyon, respectively. Significantly reduced low dose spill were observed in Halcyon plans. In the evaluation of the spinal cord, the average of Dmean and V10 of Halcyon plans in the sample group with an overlap volume of less than 1 cc was 6.802 Gy (-3.504%, P=0.067), 5.766±1.683 cc (-8.199%, P=0.002), respectively. Halcyon plans demonstrated statistically significant reduced D_mean and V10. For delivery efficiency, MU and BOT(maximum dose rate for each machine), on average, increased in Halcyon plans. However, the average of BOT(800MU/min for each machine) was 648.33 sec for Halcyon (-1.74%, P<0.001). Conclusion: Halcyon plan for double-target spine SBRT demonstrated advantages in the low dose area with a steep dose gradient, while having dosimetrically equivalent target dose distribution and spinal cord protective effect. As a result, Halcyon LINAC produced a dosimetrically improved plan for double-target spine SBRT.