165 research outputs found
K-pop Lyric Translation: Dataset, Analysis, and Neural-Modelling
Lyric translation, a field studied for over a century, is now attracting
computational linguistics researchers. We identified two limitations in
previous studies. Firstly, lyric translation studies have predominantly focused
on Western genres and languages, with no previous study centering on K-pop
despite its popularity. Second, the field of lyric translation suffers from a
lack of publicly available datasets; to the best of our knowledge, no such
dataset exists. To broaden the scope of genres and languages in lyric
translation studies, we introduce a novel singable lyric translation dataset,
approximately 89\% of which consists of K-pop song lyrics. This dataset aligns
Korean and English lyrics line-by-line and section-by-section. We leveraged
this dataset to unveil unique characteristics of K-pop lyric translation,
distinguishing it from other extensively studied genres, and to construct a
neural lyric translation model, thereby underscoring the importance of a
dedicated dataset for singable lyric translations
CiFHER: A Chiplet-Based FHE Accelerator with a Resizable Structure
Fully homomorphic encryption (FHE) is in the spotlight as a definitive
solution for privacy, but the high computational overhead of FHE poses a
challenge to its practical adoption. Although prior studies have attempted to
design ASIC accelerators to mitigate the overhead, their designs require
excessive amounts of chip resources (e.g., areas) to contain and process
massive data for FHE operations.
We propose CiFHER, a chiplet-based FHE accelerator with a resizable
structure, to tackle the challenge with a cost-effective multi-chip module
(MCM) design. First, we devise a flexible architecture of a chiplet core whose
configuration can be adjusted to conform to the global organization of chiplets
and design constraints. The distinctive feature of our core is a recomposable
functional unit providing varying computational throughput for number-theoretic
transform (NTT), the most dominant function in FHE. Then, we establish
generalized data mapping methodologies to minimize the network overhead when
organizing the chips into the MCM package in a tiled manner, which becomes a
significant bottleneck due to the technology constraints of MCMs. Also, we
analyze the effectiveness of various algorithms, including a novel limb
duplication algorithm, on the MCM architecture. A detailed evaluation shows
that a CiFHER package composed of 4 to 64 compact chiplets provides performance
comparable to state-of-the-art monolithic ASIC FHE accelerators with
significantly lower package-wide power consumption while reducing the area of a
single core to as small as 4.28mm.Comment: 15 pages, 9 figure
Toward Practical Privacy-Preserving Convolutional Neural Networks Exploiting Fully Homomorphic Encryption
Incorporating fully homomorphic encryption (FHE) into the inference process
of a convolutional neural network (CNN) draws enormous attention as a viable
approach for achieving private inference (PI). FHE allows delegating the entire
computation process to the server while ensuring the confidentiality of
sensitive client-side data. However, practical FHE implementation of a CNN
faces significant hurdles, primarily due to FHE's substantial computational and
memory overhead. To address these challenges, we propose a set of
optimizations, which includes GPU/ASIC acceleration, an efficient activation
function, and an optimized packing scheme. We evaluate our method using the
ResNet models on the CIFAR-10 and ImageNet datasets, achieving several orders
of magnitude improvement compared to prior work and reducing the latency of the
encrypted CNN inference to 1.4 seconds on an NVIDIA A100 GPU. We also show that
the latency drops to a mere 0.03 seconds with a custom hardware design.Comment: 3 pages, 1 figure, appears at DISCC 2023 (2nd Workshop on Data
Integrity and Secure Cloud Computing, in conjunction with the 56th
International Symposium on Microarchitecture (MICRO 2023)
Reflective Filters Design for Self-Filtering Narrowband Ultraviolet Imaging Experiment Wide-Field Surveys (NUVIEWS) Project
We report the design of multilayer reflective filters for the self-filtering cameras of the NUVIEWS project. Wide angle self-filtering cameras were designed to image the C IV (154.9 nm) line emission, and H2 Lyman band fluorescence (centered at 161 nm) over a 20 deg x 30 deg field of view. A key element of the filter design includes the development of pi-multilayers optimized to provide maximum reflectance at 154.9 nm and 161 nm for the respective cameras without significant spectral sensitivity to the large cone angle of the incident radiation. We applied self-filtering concepts to design NUVIEWS telescope filters that are composed of three reflective mirrors and one folding mirror. The filters with narrowband widths of 6 and 8 rim at 154.9 and 161 nm, respectively, have net throughputs of more than 50 % with average blocking of out-of-band wavelengths better than 3 x 10(exp -4)%
The impact of geopolitical risk on stock returns: Evidence from inter-Korea geopolitics
We investigate how corporate stock returns respond to geopolitical risk in the case of South Korea, which has experienced large and unpredictable geopolitical swings that originate from North Korea. To do so, a monthly index of geopolitical risk from North Korea (the GPRNK index) is constructed using automated keyword searches in South Korean media. The GPRNK index, designed to capture both upside and downside risk, corroborates that geopolitical risk sharply increases with the occurrence of nuclear tests, missile launches, or military confrontations, and decreases significantly around the times of summit meetings or multilateral talks. Using firm-level data, we find that heightened geopolitical risk reduces stock returns, and that the reductions in stock returns are greater especially for large firms, firms with a higher share of domestic investors, and for firms with a higher ratio of fixed assets to total assets. These results suggest that international portfolio diversification and investment irreversibility are important channels through which geopolitical risk affects stock returns
Multilayer Thin Film Polarizer Design for Far Ultraviolet using Induced Transmission and Absorption Technique
Good theoretical designs of far ultraviolet polarizers have been reported using a MgF2/Al/MgF2 three layer structure on a thick Al layer as a substrate. The thicknesses were determined to induce transmission and absorption of p-polarized light. In these designs Al optical constants were used from films produced in ultrahigh vacuum (UHV: 10(exp -10) torr). Reflectance values for polarizers fabricated in a conventional high vacuum (p approx. 10(exp -6 torr)) using the UHV design parameters differed dramatically from the design predictions. Al is a highly reactive material and is oxidized even in a high vacuum chamber. In order to solve the problem other metals have been studied. It is found that a larger reflectance difference is closely related to higher amplitude and larger phase difference of Fresnel reflection coefficients between two polarizations at the boundary of MgF2/metal. It is also found that for one material a larger angle of incidence from the surface normal brings larger amplitude and phase difference. Be and Mo are found good materials to replace Al. Polarizers designed for 121.6 nm with Be at 60 deg and with Mo at 70 deg are shown as examples
Household Borrowing Constraints and Residential Investment Dynamics
Why does residential investment lead output in the US and Canada but it is coincident in other industrialized countries? In this paper we explore the role of home-equity loans used to boost consumption as a channel that affects residential investment. Towards this end, we consider a multi
Spin-driven stationary turbulence in spinor Bose-Einstein condensates
We report the observation of stationary turbulence in antiferromagnetic
spin-1 Bose-Einstein condensates driven by a radio-frequency magnetic field.
The magnetic driving injects energy into the system by spin rotation and the
energy is dissipated via dynamic instability, resulting in the emergence of an
irregular spin texture in the condensate. Under continuous driving, the spinor
condensate evolves into a nonequilibrium steady state with characteristic spin
turbulence, while the low energy scale of spin excitations ensures that the
sample's lifetime is minimally affected. When the driving strength is on par
with the system's spin interaction energy and the quadratic Zeeman energy,
remarkably, the stationary turbulent state exhibits spin-isotropic features in
spin composition and spatial spin texture. We numerically show that ambient
field fluctuations play a crucial role in sustaining the turbulent state within
the system. These results open up new avenues for exploring quantum turbulence
in spinor superfluid systems.Comment: 9 pages, 9 figure
Transparent conductive coatings in the far ultraviolet
In certain cases a space-borne optical instrument with a dielectric window requires a transparent conductive coating deposited on the window to remove the electrostatic charge collected due to the bombardment of ionized particles. Semiconductor and metal films are studied for use as transparent conductive coatings for the front window of far ultraviolet camera. Cr is found to be the best coating material. The theoretical search for the semiconductor and metal coating materials and experimental results for ITO and Cr films are reported
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