2,346 research outputs found
Painlev\'e III and the Hankel Determinant Generated by a Singularly Perturbed Gaussian Weight
In this paper, we study the Hankel determinant generated by a singularly
perturbed Gaussian weight By using the ladder operator approach associated with the orthogonal
polynomials, we show that the logarithmic derivative of the Hankel determinant
satisfies both a non-linear second order difference equation and a non-linear
second order differential equation. The Hankel determinant also admits an
integral representation involving a Painlev\'e III. Furthermore, we consider
the asymptotics of the Hankel determinant under a double scaling, i.e.
and such that is fixed. The
asymptotic expansions of the scaled Hankel determinant for large and small
are established, from which Dyson's constant appears.Comment: 22 page
Efficiency of the spectral element method with very high polynomial degree to solve the elastic wave equation
International audienc
BITS-Net: Blind Image Transparency Separation Network
This research presents a new approach for blind single-image transparency separation, a significant challenge in image processing. The proposed framework divides the task into two parallel processes: feature separation and image reconstruction. The feature separation task leverages two deep image prior (DIP) networks to recover two distinct layers. An exclusion loss and deep feature separation loss are used to decompose features. For the image reconstruction task, we minimize the difference between the mixed image and the re-mixed image while also incorporating a regularizer to impose natural priors on each layer. Our results indicate that our method performs comparably or outperforms state-of-the-art approaches when tested on various image datasets
Attention-Enhancing Backdoor Attacks Against BERT-based Models
Recent studies have revealed that \textit{Backdoor Attacks} can threaten the
safety of natural language processing (NLP) models. Investigating the
strategies of backdoor attacks will help to understand the model's
vulnerability. Most existing textual backdoor attacks focus on generating
stealthy triggers or modifying model weights. In this paper, we directly target
the interior structure of neural networks and the backdoor mechanism. We
propose a novel Trojan Attention Loss (TAL), which enhances the Trojan behavior
by directly manipulating the attention patterns. Our loss can be applied to
different attacking methods to boost their attack efficacy in terms of attack
successful rates and poisoning rates. It applies to not only traditional
dirty-label attacks, but also the more challenging clean-label attacks. We
validate our method on different backbone models (BERT, RoBERTa, and
DistilBERT) and various tasks (Sentiment Analysis, Toxic Detection, and Topic
Classification).Comment: Findings of EMNLP 202
Robust Secure Transmission for Active RIS Enabled Symbiotic Radio Multicast Communications
In this paper, we propose a robust secure transmission scheme for an active
reconfigurable intelligent surface (RIS) enabled symbiotic radio (SR) system in
the presence of multiple eavesdroppers (Eves). In the considered system, the
active RIS is adopted to enable the secure transmission of primary signals from
the primary transmitter to multiple primary users in a multicasting manner, and
simultaneously achieve its own information delivery to the secondary user by
riding over the primary signals. Taking into account the imperfect channel
state information (CSI) related with Eves, we formulate the system power
consumption minimization problem by optimizing the transmit beamforming and
reflection beamforming for the bounded and statistical CSI error models, taking
the worst-case SNR constraints and the SNR outage probability constraints at
the Eves into considerations, respectively. Specifically, the S-Procedure and
the Bernstein-Type Inequality are implemented to approximately transform the
worst-case SNR and the SNR outage probability constraints into tractable forms,
respectively. After that, the formulated problems can be solved by the proposed
alternating optimization (AO) algorithm with the semi-definite relaxation and
sequential rank-one constraint relaxation techniques. Numerical results show
that the proposed active RIS scheme can reduce up to 27.0% system power
consumption compared to the passive RIS.Comment: 32 Pages, 12 figures, accepted to IEEE Transactions on Wireless
Communication
A Fast and Scalable Authentication Scheme in IoT for Smart Living
Numerous resource-limited smart objects (SOs) such as sensors and actuators
have been widely deployed in smart environments, opening new attack surfaces to
intruders. The severe security flaw discourages the adoption of the Internet of
things in smart living. In this paper, we leverage fog computing and
microservice to push certificate authority (CA) functions to the proximity of
data sources. Through which, we can minimize attack surfaces and authentication
latency, and result in a fast and scalable scheme in authenticating a large
volume of resource-limited devices. Then, we design lightweight protocols to
implement the scheme, where both a high level of security and low computation
workloads on SO (no bilinear pairing requirement on the client-side) is
accomplished. Evaluations demonstrate the efficiency and effectiveness of our
scheme in handling authentication and registration for a large number of nodes,
meanwhile protecting them against various threats to smart living. Finally, we
showcase the success of computing intelligence movement towards data sources in
handling complicated services.Comment: 15 pages, 7 figures, 3 tables, to appear in FGC
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