• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.5
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• pp.505-512
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• 2021

A 3D model was developed to calculate the UV intensity of a submerged-type UV disinfection reactor. Numerical experiments were conducted by inputting the design factors of an open channel-type disinfection reactor and a pipe-type disinfection reactor that were installed in an actual sewage treatment plant. The following data were obtained: The average UV intensity of the installed open channel-type reactor and pipe-type reactor was 7.87 mW/cm² and 13.09 mW/cm², respectively; the UV dose reflecting the UV irradiation time and taking into account attenuation effects such as mixing imbalance, lamp aging, temperature, and fouling, was expected to be 21.1 mJ/cm² and 24.8 mJ/cm², respectively, and these values are 5 % and 24 % higher than the target UV dose of 20 mJ/cm², respectively. By using the UV3D model, the optimal lamp position, which maximizes the average UV intensity without changing the size of the disinfection reactor or lamp output power, can be found. In this case, by only adjusting the lamp position, the average UV intensity can be increased by 0.9 % for the open channel-type and 0.5 % for the pipe-type, respectively. A better average UV intensity can be obtained by model simulation. By adjusting the horizontal and vertical ratio of the open channel-type reactor and by moving the lamp position, the average UV intensity can be increased by 7.4 % more than the present case.

• Journal of Mushroom
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• v.19 no.3
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• pp.216-224
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• 2021

This study analyzed food component characteristics and antioxidant activities in five kinds of domestic commercial shiitake mushrooms (Lentinula edodes). Moisture content (79.17-82.90 g/100 g) showed little difference, but there was a significant difference in crude protein content. Total mineral content showed a significant difference, and potassium (K) content was the highest. Total and essential amino acid contents were higher in mushroom A than in the other samples. Nonetheless, the ratios of essential amino acids, aspartic acid, and glutamic acid to total amino acids were similar in all samples. 𝛽-Glucan content was in the range of 10.28-5.68 g/100 g, exhibiting a significant difference. The color intensity and overall texture of the mushrooms showed no remarkable difference. Total phenol and flavonoid contents were in the range of 19.92-30.77 mg/100 g and 6.95-10.39 mg/100 g, respectively; the ratio of flavonoids to total phenols ranged from 31.53% to 38.21%. DPPH and ABTS radical scavenging activities were 74.92-79.04% and 80.47-84.97%, respectively, and showed little difference. However, the reducing power varied between 195.23 𝜇M and 317.85 𝜇M, displaying a significant difference in all samples. Therefore, this study observed similar trends in the food component characteristics and antioxidant activities of domestic commercial shiitake mushrooms.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.5
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• pp.263-270
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• 2021

In this study, a reliability-based design optimization of a 130-m class fixed-type offshore platform, to be installed in the North Sea, was carried out, while considering environmental, material, and manufacturing uncertainties to enhance its structural safety and economic aspects. For the reliability analysis, and reliability-based design optimization of the structural integrity, unity check values (defined as the ratio between working and allowable stress, for axial, bending, and shear stresses), of the members of the offshore platform were considered as constraints. Weight of the supporting jacket structure was minimized to reduce the manufacturing cost of the offshore platform. Statistical characteristics of uncertainties were defined based on observed and measured data references. Reliability analysis and reliability-based design optimization of a jacket-type offshore structure were computationally burdensome due to the large number of members; therefore, we suggested a method for variable screening, based on the importance of their output responses, to reduce the dimension of the problem. Furthermore, a deterministic design optimization was carried out prior to the reliability-based design optimization, to improve overall computational efficiency. Finally, the optimal design obtained was compared with the conventional rule-based offshore platform design in terms of safety and cost.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.3
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• pp.253-259
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• 2021

Plastic wastes generated from household waste are separated by mixed discharge with foreign substances, and recycling is relatively low. In this study, the effect of the ratio and content of mixed plastic waste coarse aggregate(MPWCA)s and mixed plastic waste fine aggregate(MPWFA)s filled with blast furnace slag fine powder on the slump and compressive strength of concrete was evaluated experimentally. The MPWCAs were found to have a similar fineness modulus, but have a single particle size distribution with a smaller particle size compared to coarse aggregates. However, the MPWFAs were found to have a single particle size distribution with a larger fineness modulus and particle size compared to fine aggregates. Meanwhile, the effect of improving the density and filling pores by the blast furnace slag fine power was found to be greater in the MPWFA compared to the MPWCA. As the amount of the mixed plastic waste aggregate(MPWA)s increased, the slump and compressive strength of concrete decreased. In particular, the lower the slump and compressive strength of concrete was found to decrease the greater the amount of MPWFA than MPWCA when the amount of MPWA was the same. This is because of the entrapped air and voids formed under the angular- and ROD-shaped aggregates among the MPWFAs. On the other hand, the addition of the admixture and the increase in the unit amount of cement were found to be effective in improving the compressive strength of the concrete with MPWAs.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.125-131
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• 2021

In recent years, Convolutional Neural Networks (CNNs) have achieved outstanding performance in the fields of computer vision such as image classification, object detection, visual quality enhancement, etc. However, as huge amount of computation and memory are required in CNN models, there is a limitation in the application of CNN to low-power environments such as mobile or IoT devices. Therefore, the need for neural network compression to reduce the model size while keeping the task performance as much as possible has been emerging. In this paper, we propose a method to compress CNN models by combining matrix decomposition methods of LR (Low-Rank) approximation and CP (Canonical Polyadic) decomposition. Unlike conventional methods that apply one matrix decomposition method to CNN models, we selectively apply two decomposition methods depending on the layer types of CNN to enhance the compression performance. To evaluate the performance of the proposed method, we use the models for image classification such as VGG-16, RestNet50 and MobileNetV2 models. The experimental results show that the proposed method gives improved classification performance at the same range of 1.5 to 12.1 times compression ratio than the existing method that applies only the LR approximation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.232-241
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• 2019

This study examines one of the conventional and controversial issues in modern finance. Specifically, this study identifies financial determinants of corporate R&D intensity for firms belonging to Korean Chaebols. Empirical estimation procedures are applied to derive more robust results of each hypothesis test. Static panel data, Tobit regression and stepwise regression models are employed to obtain significant financial factors of R&D expenditures, while logit, probit and complementary log-log regression models are used to detect financial differences between Chaebol firms and their counterparts not classified as Chaebols. Study results found the level of R&D intensity in the prior fiscal year, market-value based leverage ratio and firm size empirically showed their significance to account for corporate R&D intensity in the first hypothesis test, whereas the majority of explanatory variables had important power on a relative basis. Assuming that the current circumstances in the domestic capital market may necessitate gradual changes of Korean Chaebols in terms of their socio-economic function, the results of this study are expected to contribute to identifying financial antecedents that can be beneficial to attain optimal level of corporate R&D expenditures for Chaebol firms on a virtuous cycle.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.45-50
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• 2019

With the gradual advancement of IT, passive work processes are automated and the overall quality of life has greatly improved. This is made possible by the formation of an organic topology between a wide variety of real-life smart devices. To serve these diverse smart devices, businesses or users are using the cloud. The services in the cloud are divided into Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). SaaS runs on PaaS, and PaaS runs on IaaS. Since IaaS is the basis of all services, an algorithm is required to operate virtualization resources efficiently. Among them, desktop resource virtualization is used for resource high availability of unused state time of existing desktop PC. Clustering of hierarchical structures is important for high availability of these resources. In addition, it is very important to select a suitable algorithm because many clustering algorithms are mainly used depending on the distribution ratio and environment of the desktop PC. If various attempts are made to find an algorithm suitable for desktop resource virtualization in an operating environment, a great deal of power, time, and manpower will be incurred. Therefore, this paper proposes a resource clustering simulator for cluster selection of desktop virtualization. This provides a clustering simulation to properly select clustering algorithms and apply elements in different environments of desktop PCs.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.153-161
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• 2018

This paper describes the performance improvement of Software (SW) digital filter using GPU (Graphical Processing Unit). The previous developed SW digital filter has a problem that it operates on a CPU (Central Processing Unit) basis and has a slow speed. The GPU was introduced to filter the data of the EAVN (East Asian VLBI Network) observation to improve the operation speed and to process data with other stations through filtering, respectively. In order to enhance the computational speed of the SW digital filter, NVIDIA Titan V GPU board with built-in Tensor Core is used. The processing speed of about 0.78 (1Gbps, 16MHz BW, 16-IF) and 1.1 (2Gbps, 32MHz BW, 16-IF) times for the observing time was achieved by filtering the 95 second observation data of 2 Gbps (512 MHz BW, 1-IF), respectively. In addition, 2Gbps data is digitally filtered for the 1 and 2Gbps simultaneously observed with KVN (Korean VLBI Network), and compared with the 1Gbps, we obtained similar values such as cross power spectrum, phase, and SNR (Signal to Noise Ratio). As a result, the effectiveness of developed SW digital filter using GPU in this research was confirmed for utilizing the data processing and analysis. In the future, it is expected that the observation data will be able to be filtered in real time when the distributed processing optimization of source code for using multiple GPU boards.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.127-132
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• 2019

This study examined the change in the attention of University students after being given Transcranial Direct Current Stimulation (tDCS). The participants were divided randomly into two group (tDCS vs. Control). tDCS was applied to 37 university students ($23.08{\pm}3.33years$). The tDCS group was applied 2 mA, for 13 minutes twice over a 26 minute period ($n_1=19$). The control ($n_2=18$) was not applied after padding and was applied twice for 13 minutes over a 26 minute period. This study was conducted from September 3 to 28, 2018 and three times a week for a total of four weeks. The electroencephalogram was confirmed to affect attention. tDCS showed significant improvement in the results in the sensory motor rhythm wave (p<0.01, 95% CI: -1.955, -0.459), middle beta wave (p<0.05; 95% CI: 0.027, 0.943), and power ratio (p<0.01, 95% CI: -1.764, -0.315). The results showed that tDCS application increased the attention ability significantly. These results can be applied to attention deficit disorder (ADHD) patients and college students.

• Journal of Life Science
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• v.29 no.1
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• pp.52-59
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• 2019

The leave of Polygonum tinctorium (LPT) have been used for centuries as a traditional medicine and as a food ingredient and natural dye. The aim of the current study was to develop high-value added products using LPT. Hot water extract (HWE) and ethanol extract (EE) of LPT were prepared, respectively, and their bioactivity was evaluated. The extraction ratio for the HWE was 27.6%, which was two-fold higher than that of the EE. The contents of total polyphenol in the HWE and total sugar in the EE were 51.2 mg/g and 297.8 mg/g, respectively. The total flavonoid and reducing sugar contents were similar in the extracts, irrespective of the extraction solvent. The HWE did not show antimicrobial activity in a disc-diffusion assay, but the EE showed strong growth inhibition against gram-positive bacteria. The EE exhibited stronger DPPH and ABTS radical scavenging activities and reducing power than those of the HWE. The HWE was particularly effective as a scavenger of nitrite ($RC_{50}$ of $6.0{\mu}g/ml$). In an antithrombosis activity assay, the EE showed significant anticoagulation activity as determined by an extended blood coagulation time (thrombin time, prothrombin time, and activated partial thromboplastin time), in addition to platelet aggregation activity. The HWE also showed platelet aggregation inhibitory activity. This report provides the first evidence of antithrombosis activities of LPT. Our results suggest that LPT has potential as a new antioxidant and antithrombosis agent.