1,721 research outputs found
Japan’s Security Contribution to South Korea, 1950 to 2023
政策研究大学院大学 / National Graduate Institute for Policy Studies博士(国際関係論) / Ph.D. in International Relations論文審査委員: 道下 徳成(主査), 岩間 陽子, 竹中 治堅, CHOI Kyungwon(常葉大学), 隅藏 康一application/PDF安全保障・国際問題プログラム / Security and International Studies Programdoctoral thesi
NeuJeans: Private Neural Network Inference with Joint Optimization of Convolution and Bootstrapping
Fully homomorphic encryption (FHE) is a promising cryptographic primitive for
realizing private neural network inference (PI) services by allowing a client
to fully offload the inference task to a cloud server while keeping the client
data oblivious to the server. This work proposes NeuJeans, an FHE-based
solution for the PI of deep convolutional neural networks (CNNs). NeuJeans
tackles the critical problem of the enormous computational cost for the FHE
evaluation of convolutional layers (conv2d), mainly due to the high cost of
data reordering and bootstrapping. We first propose an encoding method
introducing nested structures inside encoded vectors for FHE, which enables us
to develop efficient conv2d algorithms with reduced data reordering costs.
However, the new encoding method also introduces additional computations for
conversion between encoding methods, which could negate its advantages. We
discover that fusing conv2d with bootstrapping eliminates such computations
while reducing the cost of bootstrapping. Then, we devise optimized execution
flows for various types of conv2d and apply them to end-to-end implementation
of CNNs. NeuJeans accelerates the performance of conv2d by up to 5.68 times
compared to state-of-the-art FHE-based PI work and performs the PI of a CNN at
the scale of ImageNet (ResNet18) within a mere few secondsComment: 16 pages, 9 figure
A Study on the Lateral Load Capacity of a Novel Hybrid Monopile via a Centrifuge Model Test
publishedVersio
Selection of Elevation Models for Flood Inundation Map Generation in Small Urban Stream: Case Study of Anyang Stream
To reduce flood damages, the Ministry of Environment in Korea has provided a flood inundation map so that people can expediently identify flood-prone areas. However, the current flood inundation maps have been produced based on the DEM which makes it difficult to represent realistic situations due to the lack of reproduction of land surface conditions. This study aims to provide more accurate and detailed flood inundation maps for flooding events due to river overflow in small urban areas. In this study, flood inundation analysis is performed using the river analysis system, HEC-RAS 2D, with the DSM and the DEM of urban areas in the Anyang Stream Basin, Korea to examine the differences in terms of terrain data and flooded area. Finally, for urban areas with dense buildings and congested road networks, the flood inundation analysis based on DSM can represent a more realistic flood situation and create an appropriate flood inundation map
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