• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.374-377
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• 2005

Hyundai motor company has designed a above 50kW-class PEMFC stack for Fuelcell vehicle based on SUV. Hyundai increased the power density of the stack through the optimized flowfield of bipolar plate, manifold structure, and improvement of sealing, etc. Also, Gas to Gas humidifier was adopted in fuelcell system to reduce the system humidification load, it had been proven by short stack test. Components of stack, bilpolar plate, manifold, were analyzed through the computer simulation, so temperature and pressure distribution in the components and system were improved. This stack tested in Bread Board which was organized similar to real vehicle system.

• Cartoon and Animation Studies
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• s.46
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• pp.151-179
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• 2017

The purpose of this study is to analyse the characteristics of the 1920s and 1930s to analyze the emotions of laughter in the popular culture, This period, such as the style of comic books, tools, and textures, has been influenced by the influence of the eodi, and it is in its way to establish the aesthetic aesthetics of the colonial Joseon Dynasty. In the pop culture of the 1920-30s, laughter was a new feeling in the gloomy atmosphere of colonial rule. It was the comic media that showed the sensation to the public, owned it, and injured it. Also, the comic book was an important period in which comic books were produced to produce quantitative and qualitative growth. The study explored how the comics interacted with other media in the 1920s and 30s. And the study analyzed what was selected in there. This can quickly explain how the comics gained, or how they obtained them. This shows how the comics gained, in a way, how they obtained laughter.

• Korean Journal of Radiology
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• v.24 no.8
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• pp.807-820
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• 2023

Objective: To assess whether computed tomography (CT) conversion across different scan parameters and manufacturers using a routable generative adversarial network (RouteGAN) can improve the accuracy and variability in quantifying interstitial lung disease (ILD) using a deep learning-based automated software. Materials and Methods: This study included patients with ILD who underwent thin-section CT. Unmatched CT images obtained using scanners from four manufacturers (vendors A-D), standard- or low-radiation doses, and sharp or medium kernels were classified into groups 1-7 according to acquisition conditions. CT images in groups 2-7 were converted into the target CT style (Group 1: vendor A, standard dose, and sharp kernel) using a RouteGAN. ILD was quantified on original and converted CT images using a deep learning-based software (Aview, Coreline Soft). The accuracy of quantification was analyzed using the dice similarity coefficient (DSC) and pixel-wise overlap accuracy metrics against manual quantification by a radiologist. Five radiologists evaluated quantification accuracy using a 10-point visual scoring system. Results: Three hundred and fifty CT slices from 150 patients (mean age: 67.6 ± 10.7 years; 56 females) were included. The overlap accuracies for quantifying total abnormalities in groups 2-7 improved after CT conversion (original vs. converted: 0.63 vs. 0.68 for DSC, 0.66 vs. 0.70 for pixel-wise recall, and 0.68 vs. 0.73 for pixel-wise precision; P < 0.002 for all). The DSCs of fibrosis score, honeycombing, and reticulation significantly increased after CT conversion (0.32 vs. 0.64, 0.19 vs. 0.47, and 0.23 vs. 0.54, P < 0.002 for all), whereas those of ground-glass opacity, consolidation, and emphysema did not change significantly or decreased slightly. The radiologists' scores were significantly higher (P < 0.001) and less variable on converted CT. Conclusion: CT conversion using a RouteGAN can improve the accuracy and variability of CT images obtained using different scan parameters and manufacturers in deep learning-based quantification of ILD.