• Transactions on Electrical and Electronic Materials
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• v.13 no.6
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• pp.273-277
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• 2012

The vacuum drying process for drying of paper in current transformers was modeled with an aim to develop an understanding of the drying mechanism involved and also to predict the water collection rates. A molecular as well as macroscopic approach was adopted for the prediction of drying rate. Ficks law of diffusion was adopted for the prediction of drying rates at macroscopic levels. A steady state and dynamic mass transfer simulation was performed. The bulk diffusion coefficient was calculated using weight loss experiments. The accuracy of the solution was a strong function of the relation developed to determine the equilibrium moisture content. The actually observed diffusion constant was also important to predict the plant water removal rate. Thermo gravimetric studies helped in calculating the diffusion constant. In addition, simulation studies revealed the formation of perpetual moisture traps (loops) inside the CT. These loops can only be broken by changing the temperature or pressure of the system. The change in temperature or pressure changes the kinetic or potential energy of the effusing vapor resulting in breaking of the loop. The cycle was developed based on this mechanism. Additionally, simulation studies also revealed that the actual mechanism of moisture diffusion in CT's is by surface jumps initiated by surface diffusion balanced against the surrounding pressure. Every subsequent step in the cycle was to break such loops. The effect of change in drying time on the electrical properties of the insulation was also assessed. The measurement of capacitance at the rated voltage and one third of the rated voltage demonstrated that the capacitance change is within the acceptance limit. Hence, the new cycle does not affect the electrical performance of the CT.

• Journal of the Korean Society of Visualization
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• v.12 no.1
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• pp.49-53
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• 2014

In this study, a novel FDR-SPC is first synthesized in this study. The drag reducing functional radical such as PEGMA (Poly(ethylene) glycol methacrylate) has been utilized to participate in the synthesis process of the SPC. The types of the baseline SPC monomers, the molecular weight and the mole fraction of PEGMA were varied in the synthesis process. The resulting SPCs were coated to the substrate plates for the subsequent hydrodynamic test for skin friction measurement. In a low-Reynolds number flow measurement using PIV (Particle Image Velocimeter), a significant reduction in Reynolds stress was observed in a range of specimen, with the maximum drag reduction being 15.9% relative to the smooth surface.

• Korean Journal of Pharmacognosy
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• v.47 no.2
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• pp.172-178
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• 2016

Using high-fat diet-induced obese (DIO) mice, the mechanism of anti-adiposity and anti-obesity actions produced by Inonotus obliquus water extract (IOE) was investigated. Significant reduction in body weight in DIO mice orally administrated with IOE for 8 weeks compared to IOE-non-treated control mice was observed, which was attributed to the reduction of epididymal and mesenteric adipose tissue, but not the liver and skeletal muscle. Adiponectin synthesis in epididymal adipose tissue (EAT) and AMPK phosphorylation in the liver were significantly increased in IOE-treated DIO mice. Gene expression analysis showed that IOE-treated DIO mice had higher expression levels of lipogenic genes in EAT and fatty-acid oxidative genes in the liver, but lower expression levels of hepatic pro-inflammatory cytokines compared to IOE-non-treated controls. Our findings confirm a therapeutic potential of Inonotus obliquus for reducing adiposity and ameliorating hyperlipidemia to treat metabolic disorders.

• Journal of Navigation and Port Research
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• v.34 no.3
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• pp.189-194
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• 2010

As the seriousness of the global environment is gaining our attention recently, studies on application of LCA(Life Cycle Assessment) to ship are being carried out dynamically in various industrial fields. This study was carried out to examine the application of LCA to ships and was focused on the inventory analysis on global warming gas from merchant cargo ships. Two merchant cargo ships were adopted as ship models. Actual voyage data of at last several years was used to analysis the ship's exhaust gas inventory. The analysis shows how many weight of global warming gas being exhausted to transport 1 ton of each cargo per 1 nautical mile.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4326-4344
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• 2021

The SinGAN is one of generative adversarial networks that can be trained on a single nature image. It has poor ability to learn more global features from nature image, and losses much local detail information when it generates arbitrary size image sample. To solve the problem, a non-linear function is firstly proposed to control downsampling ratio that is ratio between the size of current image and the size of next downsampled image, to increase the ratio with increase of the number of downsampling. This makes the low-resolution images obtained by downsampling have higher proportion in all downsampled images. The low-resolution images usually contain much global information. Therefore, it can help the model to learn more global feature information from downsampled images. Secondly, the attention mechanism is introduced to the generative network to increase the weight of effective image information. This can make the network learn more local details. Besides, in order to make the output image more natural, the TVLoss function is introduced to the loss function of SinGAN, to reduce the difference between adjacent pixels and smear phenomenon for the output image. A large number of experimental results show that our proposed model has better performance than other methods in generating random samples with fixed size and arbitrary size, image harmonization and editing.

• Structural Engineering and Mechanics
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• v.66 no.4
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• pp.543-555
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• 2018

Fiber Reinforced Polymer (FRP), which has a high strength to weight ratio, are now regularly used for strengthening of deficient reinforced concrete (RC) structures. While various researches have been conducted on FRP strengthening, an area that still requires attention is predicting the debonding failure load of prestressed FRP strengthened RC beams. Application of prestressing increases the capacity and reduces the premature failure of the beams largely, though not entirely. Few analytical methods are available to predict the failure loads under flexure failure. With this paucity, this research proposes a method for predicting debonding failure induced by intermediate crack (IC) for prestressed FRP-strengthened beams. The method consists of a numerical study on beams retrofitted with prestressed FRP in the tension side of the beam. The method applies modified Branson moment-curvature analysis together with the global energy balance approach in combination with fracture mechanics criteria to predict failure load for complicated IC-induced failure. The numerically simulated results were compared with published experimental data and the average of theoretical to experimental debonding failure load is found to be 0.93 with a standard deviation of 0.09.

• Computers and Concrete
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• v.26 no.5
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• pp.411-420
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• 2020

Deep Convolution neural network (DCNN) has been widely used in the healthy maintenance of civil infrastructure. Using DCNN to improve crack detection performance has attracted many researchers' attention. In this paper, a light-weight spatial attention network module is proposed to strengthen the representation capability of ResNet and improve the crack detection performance. It utilizes attention mechanism to strengthen the interested objects in global receptive field of ResNet convolution layers. Global average spatial information over all channels are used to construct an attention scalar. The scalar is combined with adaptive weighted sigmoid function to activate the output of each channel's feature maps. Salient objects in feature maps are refined by the attention scalar. The proposed spatial attention module is stacked in ResNet50 to detect crack. Experiments results show that the proposed module can got significant performance improvement in crack detection.

• Toxicological Research
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• v.22 no.4
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• pp.323-328
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• 2006

Global gene expression profile was analyzed by microarray analysis of rat liver RNA after acute acetaminophen (APAP) administration. A single dose of 1g/kg body weight of APAP was given orally, and the liver samples were obtained after 24, 48 h, and 2 weeks. Histopathologic and biochemical studies enabled the classification of the APAP effect into injury (24 and 48 h) and regeneration (2 weeks) stages. The expression levels of 4900 clones on a custom rat gene microarray were analyzed and 484 clones were differentially expressed with more than a 1.625-fold difference(which equals 0.7 in log2 scale) at one or more time points. Two hundred ninety seven clones were classified as injury-specific clones, while 149 clones as regeneration-specific ones. Characteristic gene expression profiles could be associated with APAP-induced gene expression changes in lipid metabolism, stress response, and protein metabolism. We established a global gene expression profile utilizing microarray analysis in rat liver upon acute APAP administration with a full chronological profile that not only covers injury stage but also later point of regeneration stage.

• Structural Engineering and Mechanics
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• v.75 no.6
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• pp.723-736
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• 2020

In this paper, acoustic emission (AE) and pattern recognition are utilized to identify the AE signal signatures caused by propagation of stress corrosion cracking (SCC) in a 304 stainless steel plate. The surface of the plate is under almost uniform tensile stress at a notch. A corrosive environment is provided by exposing the notch to a solution of 1% Potassium Tetrathionate by weight. The Global b-value indicated an occurrence of the first visible crack and damage stages during the SCC. Furthermore, a method based on linear regression has been developed for damage identification using AE data.

• Journal of the Korean Society for Railway
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• v.8 no.6 s.31
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• pp.581-585
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• 2005

In this study, the environmental impacts of a bogie in the electric motor unit(EMU) were evaluated quantitatively using simplified life cycle assessment(S_LCA). Target was the bogie and life cycle inventory(LCI) database for the bogie was established. The software used for simplified LCA was PASS. Environmental impacts with the parts of the bogie were dependent on their weight significantly. Among impact categories, abiotic resource depletion(ARD) and global warming(GW) were shown dominantly. Global warming was occurred mainly due to the emission of CO₂released from energy consumption and abiotic resource depletion was caused mostly by the consumption of iron ore for the manufacturing of steel. Therefore, the environmental impacts of the bogie could be reduced by the light-weighting of EMU and the improvement of energy efficiency.