• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.705-712
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• 2002

Geotextile tube is environmentally sustainable technology and has been applied in hydraulic and coastal engineering applications. Geotextile tube is composed in permeable fabrics and Inside dredged materials, and hydraulically or mechanically filled with dredged materials. These tube are generally about 1.0m to 2.0m in diameter, through they can be sized for any application. The tubes can be used solely, or stacked to add greater height and usability. Stacked geotextile tubes will create by adding the height necessary for some breakwaters and embankment, therefore increasing the usability of geotextile tubes. This paper presents the hydrodynamic behavior of stacked geotextile tube by hydraulic model tests. The hydraulic model test conducted by structural condition and wave conditions. Structural condition is installation direction to the wave(perpendicular band 45$^{\circ}$), and wave condition is varied with the significant wave height ranging from 3.0m to 6.0m. Based on the test results, the hydrodynamic behaviors such as structural stability, wave control capacity, and strain are interpreted.

• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
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• 2003.10a
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• pp.250-253
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• 2003

In general, AC transport current loss of vertically stacked HTS tapes is larger than simple multiplication of single tape by stacked number. In this study we investigated the transport current and current distribution in face-to-face stacked conductor Numerical method has been developed for loss estimation and compared to the experimental works. Two results showed goof agreement each other The stacked conductor behaved like a single watching current distribution, From this point of view it is possible to suggest the other analogy to predict the transport current loss. All results were presented and checked the validities of the loss estimation.

• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
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• 2003.10a
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• pp.14-17
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• 2003

In general, AC transport current loss of vertically stacked HTS tapes is larger than simple multiplication of single tape by stacked number. In this study we investigated the transport current and current distribution in face-to-face stacked conductor Numerical method has been developed for loss estimation and compared to the experimental works. Two results showed goof agreement each other. The stacked conductor behaved like a single watching current distribution, From this point of view, it is possible to suggest the other analogy to predict the transport current loss. All results were presented and checked the validities of the loss estimation.

• ETRI Journal
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• v.26 no.1
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• pp.61-64
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• 2004

We have explored the fabrication of an InP/InGaAs single heterojunction bipolar transistor (HBT) and a wave guide p-i-n photodiode (PD) on two kinds of double stacked layers for the implementation of an optoelectronic millimeter-wave monolithic integrated circuit (OEMMIC). We applied a photosensitive polyimide for passivation and integration to overcome the large difference between the HBT and PD layers of around $3{\mu}m$. Our experiment showed that the RF characteristics of the HBT were dependent on the location of the PD layer, while the dc performances of the HBTs and PDs were independent of the type of stacked layer used. The $F_t$ and $F_{max}$ of the HBTs on the HBT/PD stacked layer were 10% lower than those of the HBTs on the PD/HBT stacked layer.

• Proceedings of the KIEE Conference
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• summer
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• pp.776-778
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• 2004

In this paper, we present effect of the stacked HTS tapes. AC losses of HTS pancake windings with stacked tapes are shown. Magnetic flux density in the HTS winding under operating conditions was calculated by FEM. AC loss of the pancake winding were measured and compared with the calculated loss by using AC losses of the stacked samples. Test results show that measured results generally agreed well with the calculated value by using AC loss of 4-stacked sample data.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1020-1025
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• 2021

Facial alignment is very important task for human life. And facial landmark detection is one of the instrumental methods in face alignment. We introduce the stacked hourglass networks with transposed convolutional layers for facial landmark detection. our method substitutes nearest neighbor upsampling for transposed convolutional layer. Our method returns better accuracy in facial landmark detection compared to stacked hourglass networks with nearest neighbor upsampling.

• Progress in Superconductivity
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• v.5 no.2
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• pp.89-93
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• 2004

We have studied alternating transport current losses in the vertically stacked high temperature superconducting tapes(HTS) using numerical techniques. In the case of stacked conductors, HTS tapes are exposed to self-field generated by transport current itself and also experienced external magnetic field around adjacent tapes. It is well known that magnetic interactions between neighbored tapes have significant effect on their properties of superconducting tapes such as current distribution, AC loss, and critical current. In this paper, we investigated the transport current losses in stacked conductors consisting of a few of the HTS tapes using numerical analysis. Current distributions are calculated in HTS tape cross-section taking account of magnetic field dependencies, which are represented superconducting nonlinear properties. Dissipated losses in tape and stacked conductors were integrated with current distribution and electric field intensity in the whole conductor region. Finally estimated results were discussed and verified through the analytical theory.

• Journal of the Microelectronics and Packaging Society
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• v.21 no.3
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• pp.63-66
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• 2014

In this study, we investigated the effects of Cu TSV on the thermal management of 3D stacked IC. Combination of backside point-heating and IR microscopic measurement of the front-side temperature showed evolution of hot spots in thin Si wafers, implying 3D stacked IC is vulnerable to thermal interference between stacked layers. Cu TSV was found to be an effective heat path, resulting in larger high temperature area in TSV wafer than bare Si wafer, and could be used as an efficient thermal via in the thermal management of 3D stacked IC.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.5
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• pp.58-64
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• 2008

A 6Gbps 1:2 demultiplexer(DEMUX) IC using $0.18{\mu}m$ CMOS was designed and fabricated. For high speed performance current mode logic(CML) flipflop was used and inductive peaking technology was used so as to obtain higher speed than conventional Current mode logic flipflop. On-chip spiral inductor was designed to maximize the inductive peaking effect using stack structure. Total twelve inductors of $100{\mu}m^2$ area increase was used. The measurement was processed on wafer and 1:2 demultiplexer with and without micro stacked spiral inductors were compared. For 6Gbps data rate measurement, eye width was improved 7.27% and Jitter was improved 43% respectively. Power consumption was 76.8mW and eye height was 180mV at 6 Gbps

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.54.2-54.2
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• 2019

Removing noise which occurs inevitably when taking image data has been a big concern. There is a way to raise signal-to-noise ratio and it is regarded as the only way, image stacking. Image stacking is averaging or just adding all pixel values of multiple pictures taken of a specific area. Its performance and reliability are unquestioned, but its weaknesses are also evident. Object with fast proper motion can be vanished, and most of all, it takes too long time. So if we can handle single shot image well and achieve similar performance, we can overcome those weaknesses. Recent developments in deep learning have enabled things that were not possible with former algorithm-based programming. One of the things is generating data with more information from data with less information. As a part of that, we reproduced stacked image from single shot image using a kind of deep learning, conditional generative adversarial network (cGAN). r-band camcol2 south data were used from SDSS Stripe 82 data. From all fields, image data which is stacked with only 22 individual images and, as a pair of stacked image, single pass data which were included in all stacked image were used. All used fields are cut in $128{\times}128$ pixel size, so total number of image is 17930. 14234 pairs of all images were used for training cGAN and 3696 pairs were used for verify the result. As a result, RMS error of pixel values between generated data from the best condition and target data were $7.67{\times}10^{-4}$ compared to original input data, $1.24{\times}10^{-3}$. We also applied to a few test galaxy images and generated images were similar to stacked images qualitatively compared to other de-noising methods. In addition, with photometry, The number count of stacked-cGAN matched sources is larger than that of single pass-stacked one, especially for fainter objects. Also, magnitude completeness became better in fainter objects. With this work, it is possible to observe reliably 1 magnitude fainter object.