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The optical properties of two-dimensional (2D) Janus MoSTe photodetectors under irradiation of polarized light have attracted tremendous attention recently due to their potential applications in low power consumption nanoelectronics and ...${}_{\mathrm{}}^{\mathrm{}}$${}_{\mathrm{}}^{\mathrm{}}$${}_{\mathrm{}}^{\mathrm{}}$

• We reported an experimental method to simulate arteries aging, developed a fluid-structure interaction model with the effect of AAPSR changes.
• Decreased AAPSR leads to declined arterial elasticity, decreased of arterial elastic strain ...

It is an indisputable physiological phenomenon that the arterial axial pre-stretch ratio (AAPSR) decreases with age, but little attention has been paid to the effect of this reduction on chronic diseases during aging.

With the advancement of AI-powered personal voice assistants, speaker authentication via earbuds has become increasingly vital, serving as a critical interface between users and mobile devices. However, existing audio-based speaker authentication methods ...

Deep neural networks (DNNs) are frequently employed in a variety of computer vision applications. Nowadays, an emerging trend in the current video distribution system is to take advantage of DNN’s overfitting properties to perform video resolution ...$$$$

In educational settings, a challenge is the lack of linked and labeled data, hindering effective analysis. The integration of ontology facilitates the formulation of educational knowledge concepts, student behaviors, and their relations. ...

Learning analytics, blending education theory, psychology, statistics, and computer science, utilizes data about learners and their environments to enhance education. Artificial Intelligence advances this field by personalizing learning and ...

The challenge caused by redundant feature interference in high-dimensional fault feature data of analog circuits, will undermines the efficacy of conventional analog circuit fault diagnosis techniques, Thus, a novel approach termed Heterogeneous ...

Large Language Models (LLMs), renowned for their remarkable performance across diverse domains, present a challenge when it comes to practical deployment due to their colossal model size. In response to this challenge, efforts have been directed toward ...

Score-based diffusion models, while achieving remarkable empirical performance, often suffer from low sampling speed, due to extensive function evaluations needed during the sampling phase. Despite a flurry of recent activities towards speeding up ...

Dynamic Sparse Training (DST) has been effectively addressing the substantial training resource requirements of increasingly large Deep Neural Networks (DNNs). Characterized by its dynamic "train-prune-grow" schedule during training, DST implicitly ...

Deformation detection of building structures is a key technology to ensure building safety. It can identify problems that may cause structural disasters early, so as to take preventive measures to reduce or avoid potential disaster risks, avoid accidents,...

This paper is concerned with the problem of policy evaluation with linear function approximation in discounted infinite horizon Markov decision processes. We investigate the sample complexities required to guarantee a predefined estimation error of the ...

This paper makes progress toward learning Nash equilibria in two-player, zero-sum Markov games from offline data. Despite a large number of prior works tackling this problem, the state-of-the-art results suffer from the curse of multiple agents in the ...

This paper makes progress toward learning Nash equilibria in two-player, zero-sum Markov games from offline data. Specifically, consider a γ-discounted, infinite-horizon Markov game with S states, in which the max-player has A actions and the min-player ...

Visible watermarks, while instrumental in protecting image copyrights, frequently distort the underlying content, complicating tasks like scene interpretation and image editing. Visible watermark removal aims to eliminate the interference of watermarks ...

In particle method, the number of particles is an important factor affecting the computational efficiency. For the free-surface flow, gas particles are usually necessary for surface tension calculation, but they have little impact to the liquid ...

We present PyroSense, the first-of-its-kind system that enables fine-grained 3D posture reconstruction using ubiquitous COTS passive infrared sensor (PIR sensor). PyroSense senses heat signals generated by the human body and airflow due to body movement ...

As extreme weather becomes more prevalent, it has serious implications for the insurance industry, real estate owners, and historic buildings. First of all, for the extreme weather, we summarize extreme weather into three parts: extreme ...

A crucial problem in reinforcement learning is learning the optimal policy. We study this in tabular infinite-horizon discounted Markov decision processes under the online setting. The existing algorithms either fail to achieve regret optimality or have ...

This paper investigates model robustness in reinforcement learning (RL) via the framework of distributionally robust Markov decision processes (RMDPs). Despite recent efforts, the sample complexity of RMDPs is much less understood regardless of the ...

Sparse training has received an upsurging interest in machine learning due to its tantalizing saving potential for the entire training process as well as inference. Dynamic sparse training (DST), as a leading sparse training approach, can train deep ...