• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5357-5381
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• 2018

Cloud computing offers a wide range of on-demand resources over the internet. Utility-based resource allocation in cloud data centers significantly increases the number of cloud users. Heavy usage of cloud data center encounters many problems such as sacrificing system performance, increasing operational cost and high-energy consumption. Therefore, the result of the system damages the environment extremely due to heavy carbon (CO2) emission. However, dynamic allocation of energy-efficient resources in cloud data centers overcomes these problems. In this paper, we have proposed Energy and Service Level Agreement (SLA) Aware Resource Allocation Heuristic Algorithms. These algorithms are essential for reducing power consumption and SLA violation without diminishing the performance and Quality-of-Service (QoS) in cloud data centers. Our proposed model is organized as follows: a) SLA violation detection model is used to prevent Virtual Machines (VMs) from overloaded and underloaded host usage; b) for reducing power consumption of VMs, we have introduced Enhanced minPower and maxUtilization (EMPMU) VM migration policy; and c) efficient utilization of cloud resources and VM placement are achieved using SLA-aware Modified Best Fit Decreasing (MBFD) algorithm. We have validated our test results using CloudSim toolkit 3.0.3. Finally, experimental results have shown better resource utilization, reduced energy consumption and SLA violation in heterogeneous dynamic cloud environment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.169-176
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• 2021

Maritime monitoring requirements have been beyond human operators capabilities due to the broadness of the coverage area and the variety of monitoring activities, e.g. illegal migration, or security threats by foreign warships. Abnormal vessel movement can be defined as an unreasonable movement deviation from the usual trajectory, speed, or other traffic parameters. Detection of the abnormal vessel movement requires the operators not only to pay short-term attention but also to have long-term trajectory trace ability. Recent advances in deep learning have shown the potential of deep learning techniques to discover hidden and more complex relations that often lie in low dimensional latent spaces. In this paper, we propose a deep autoencoder-based clustering model for automatic detection of vessel movement anomaly to assist monitoring operators to take actions on the vessel for more investigation. We first generate gridded trajectory images by mapping the raw vessel trajectories into two dimensional matrix. Based on the gridded image input, we test the proposed model along with the other deep autoencoder-based models for the abnormal trajectory data generated through rotation and speed variation from normal trajectories. We show that the proposed model improves detection accuracy for the generated abnormal trajectories compared to the other models.

• Computers and Concrete
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• v.29 no.6
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• pp.433-444
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• 2022

Concrete's compressive strength is widely studied in order to understand many qualities and the grade of the concrete mixture. Conventional civil engineering tests involve time and resources consuming laboratory operations which results in the deterioration of concrete samples. Proposing efficient non-destructive models for the prediction of concrete compressive strength will certainly yield advancements in concrete studies. In this study, the efficiency of using radial basis function neural network (RBFNN) which is not common in this field, is studied for the concrete compressive strength prediction. Complementary studies with back propagation neural network (BPNN), which is commonly used in this field, have also been carried out in order to verify the efficiency of RBFNN for compressive strength prediction. A total of 13 input parameters, including novel ones such as cement's and fly ash's compositional information, have been employed in the prediction models with RBFNN and BPNN since all these parameters are known to influence concrete strength. Three different train: test ratios were tested with both models, while different hidden neurons, epochs, and spread values were introduced to determine the optimum parameters for yielding the best prediction results. Prediction results obtained by RBFNN are observed to yield satisfactory high correlation coefficients and satisfactory low mean square error values when compared to the results in the previous studies, indicating the efficiency of the proposed model.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4474-4480
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• 2022

Deep geological disposal using a multibarrier system is a promising solution for treating high-level radioactive (HLRW) waste. The HLRW canister represents the first barrier for the migration of radionuclides into the biosphere, therefore, the corrosion behavior of canister materials is of significance. In this study, the electrochemical behaviors of SS316L, Ti-Gr.2, Alloy 22, and Cu in naturally aerated KAERI underground research tunnel (KURT) groundwater solutions were examined. The corrosion potential, current, and impedance spectra of the test materials were recorded using electrochemical methods. According to polarization and impedance measurements, Cu exhibits relatively higher corrosion rates and a lower corrosion resistance ability than those exhibited by the other materials in the given groundwater condition. In the anodic dissolution tests, SS316L exposed to the groundwater solution exhibited the most uniform corrosion, as indicated by its surface roughness. This phenomenon could be attributed to the extremely low concentration of chloride ions in KURT groundwater.

• Korea Trade Review
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• v.47 no.6
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• pp.71-96
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• 2022

This research will study the conversion intention of the users in China from fuel vehicle to new energy vehicles through the empirical methods. To this end, a questionnaire survey was conducted with car users as the object, combined with the theory of user migration and the PPM model to analyze the impact of fuel vehicle users' conversion intention to new-energy vehicles factor. The results showed that purchase experience contains the moderating effect, in which perceived risk and switching costs had a greater impact on the groups without purchase experience, whereas social identity, perceived value, personal attitude, and willingness to switch had a greater impact on groups with the purchase experience. Among all five factors, perceived risk had no discernible impact on the switching intention, but social identity, perceived value, attitude toward switching, and switching costs all had discernible impact on the switching intention. This study expects to come out with sustainable advises for the future growth of new energy vehicles from the study of car users' switching intention and the collective difference test of purchasing experience.

• Journal of Ginseng Research
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• v.47 no.5
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• pp.654-661
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• 2023

Background: Ginseng has been used as a traditional medicine and functional cosmetic ingredients for many years. Recent studies have focused on the potential biological effects of the ginseng berry and its ingredients. (+)-Syringaresinol (SYR) is enriched in ginseng berry and its beneficial effects on the skin have been recently reported. However, little is known about the its effects on the wound healing process of skin. Methods: Here, we evaluated the skin wound healing effect of (+)-SYR using the human fibroblast Hs68 cell and ex vivo pig and human skin tissue model. Scratch wound test and hydrogen peroxide (HPO) induce chemical wound model were employed. Results: (+)-SYR promoted the migration and proliferation of Hs68 cells without significant cytotoxicity at the tested concentrations. Especially, in ex vivo pig and human skin tissue, HPO-induced chemical wound was recovered almost completely by (+)-SYR. In line with the finding in Hs68, the protein expression levels of TGF-β and PCNA, a proliferation marker were increased, demonstrating the beneficial effects of (+)-SYR on skin wound repair. Conclusion: Collectively, we demonstrated that (+)-SYR from ginseng berry, can enhance the wound healing effect by accelerating cell proliferation and skin regeneration, suggesting the potential utility of (+)-SYR for skin wound repair.

• Journal of the Korean GEO-environmental Society
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• v.3 no.3
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• pp.15-25
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• 2002

The permeability coefficient is one of the fundamental engineering properties of soft clays. Consolidation process as well as migration of pollutants in soil are affected the permeability coefficient, which generally decreases with the reduction in void ratio during consolidation. After Kozeny(1927) and Carman(1956), many researchers have proposed the relationships between void ratio and permeability in such forms as; (1) log e - log k(1+e), (2) e - log k, or (3) log e - log k. Constant rate of strain (CRS) tests was performed with undisturbed samples obtained at Kunsan and Kimhae deposits, which are representative Korean marine clay. From the results of the tests, the relationships were found valid for Kunsan and Kimhae clays. The experimental correlation $C_k=0.5e_o$ was satisfied with Kimhae clay but not with Kunsan clay.

• Journal of Soil and Groundwater Environment
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• v.18 no.3
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• pp.109-118
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• 2013

Characteristics of the transport of zero-valent iron nanoparticles (nZVI) in an aquifer were investigated to evaluate an application of nZVI-based reactive zone technology. Main flow direction of groundwater was north. Preferential flow paths of the groundwater identified by natural gradient tracer test were shown northeast and northwest. The highest groundwater velocity was $4.86{\times}10^{-5}$ m/s toward northwest. When the breakthrough curves obtained from the gravity injection of nZVI were compared with the tracer curves, the transport of nZVI was retarded and retardation factors were 1.17 and 1.34 at monitoring wells located on the northeast and northwest, respectively. The ratios of the amount of nZVI delivered to the amount of tracer delivered at the two wells mentioned above were 24 and 28 times greater than that of the well on the main flow direction, respectively. Attachment efficiency based on a filtration theory was $4.08{\times}10^{-2}$ along the northwest direction that was the main migration route of nZVI. Our results, compared to attachment efficiencies obtained in other studies, demonstrate that the mobility of nZVI was higher than that of results reported in previous studies, regardless of large iron particle sizes of the current study. Based on distribution of nZVI estimated by the attachment efficiency, it was found that nZVI present within 1.05 m from injection well could remove 99% of TCE within 6 months.

• Geophysics and Geophysical Exploration
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• v.1 no.3
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• pp.161-169
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• 1998

The Kunsan basin is a pull-apart basin which was formed during Tertiary. The pre-Tertiary section consists of various rock types, such as meta-sediments, igneous rocks, carbonates, clastics, and volcanics. Tertiary sections are the main targets for the petroleum exploration. In order to determine the optimum processing parameters of the basin, about 12 kinds of test processings were performed. The first main steps for the quality control is to determine the noisy or bad traces by examining the near trace section and shot gathers. The true amplitude recovery was applied to account for the amplitude losses due to spherical divergence and inelastic attenuation. Source designature and predictive deconvolution test were conducted to determine the optimum wavelet parameters and to remove the multiples. Velocity analysis was performed at 1km intervals. The optimum mute function was picked by locating the range of offsets which gives the best stacking response for any particular reflections. Post-stack deconvolution was tested to see if the quality of stacked data improved. The stacked data was migrated using a finite difference algorithm. The migration velocity was obtained from the stacking velocities using the time varying percentages. The AGC sections were provided for the structural interpretation. The RAP sections were used for DHI analysis and for the detection of volcanics.

• Journal of the Korean Geotechnical Society
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• v.19 no.3
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• pp.83-91
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• 2003

The electrokinetic technique has been applied to remove mainly the heavy metal and the ultrasonic technique to remove mainly organic substance in contaminated soil. In this study, the combined electrokinetic and ultrasonic remediation technique was studied far the removal of heavy metal and organic substance in contaminated soils. This study emphasized the coupled effects of electrokinetic and ultrasonic techniques on migration as well as remediation of contaminants in soils. The laboratory soil flushing tests combining electrokinetic and ultrasonic technique were conducted using specially designed and fabricated devices to determine the effect of both of these techniques. A series of laboratory experiments involving the simple, electrokinetic, ultrasonic, and electrokinetic & ultrasonic flushing test were carried out. A soil admixed with sand and kaolin was used as a test specimen, and Pb and ethylene glycol were used as contaminants of heavy metal and organic substance. An increase in out flow, permeability and contaminant removal rate was observed in electrokinetic and ultrasonic flushing tests. Some practical implications of these results are discussed in terms of technical feasibility of in situ implementation of electrokinetic ultrasonic remediation technique.