Qiang Wang

Multi point monitoring method of prestressed tendon based on distributed sensors

2021 · Journal of Physics Conference Series

Abstract This paper presents a multi-point strain monitoring method based on distributed sensors, which can monitor the multi-point stress of prestressed tendons in concrete. Firstly, the special sensor protection device is installed in the designated …

On stable polynomials of degrees $2,3,4$

2023 · arXiv (Cornell University)

Let $q$ be a prime power. We construct stable polynomials of the form $b^{m-1}(x+a)^m+c(x+a)+d$ over a finite field $\mathbb{F}_{q}$ for $m=2,3,4$ by Capelli's lemma. When $m=3$ and $q$ is even, we confirm the conjecture of …

PATVD:Vulnerability Detection Based on Pre-training Techniques and Adversarial Training

2022

Software vulnerability detection has attracted more and more attention. Traditional vulnerability detection methods require a lot of expertise to define the vulnerability features, whereas the deep learning based methods can perform the feature extraction automatically. …

An Efficient Client Selection for Wireless Federated Learning

2023

As a promising distributed learning technology, federated learning (FL) is used in wireless communication to efficiently utilize distributed data. However, statistical heterogeneity is often ignored as a crucial factor affecting wireless federated learning (WFL) performance. …

Permutation polynomials, projective polynomials, and bijections between $μ_{\frac{q^n-1}{q-1}}$ and $PG(n-1,q)$

2025 · arXiv (Cornell University)

Using arbitrary bases for the finite field $\mathbb{F}_{q^n}$ over $\mathbb{F}_{q}$, we obtain the generalized Möbius transformations (GMTs), which are a class of bijections between the projective geometry $PG(n-1,q)$ and the set of roots of unity …

Multi-layer Representation Fusion for Neural Machine Translation

2020 · arXiv (Cornell University)

Neural machine translation systems require a number of stacked layers for deep models. But the prediction depends on the sentence representation of the top-most layer with no access to low-level representations. This makes it more …

Learning Deep Transformer Models for Machine Translation

2019

Transformer is the state-of-the-art model in recent machine translation evaluations. Two strands of research are promising to improve models of this kind: the first uses wide networks (a.k.a. Transformer-Big) and has been the de facto …