Yong Guan

ReVeal-MT: A Physics-Informed Neural Network for Multi-Transmitter Radio Environment Mapping

Mukaram Shahid, Kunal Das, Hadia Ushaq, Hongwei Zhang et autres

Accurately mapping the radio environment (e.g., identifying wireless signal strength at specific frequency bands and geographic locations) is crucial for efficient spectrum sharing, enabling Secondary Users~(SUs) to access underutilized spectrum bands while protecting Primary Users~(PUs). While existing models have made progress, they …

Tribological Properties of Aluminum–Silicon Alloy Cylinder Liners Paired with DLC and CKS Piston Rings

Yong Guan, Chengdi Li, Xiao Chen, Lian-Jie Dong et autres

With the increasing demand for energy conservation and emission reduction in the automotive industry, optimizing the performance of cylinder liner and piston ring pairs in engines has become crucial. Aluminum–silicon alloy cylinder liners, known for their lightweight and excellent thermal conductivity, have …

cn (code pays fourni par la source)

A Security Analysis of Anti-Audio Cloaking Schemes

Lucky Onyekwelu-Udoka, Yong Guan

Audio cloaking aims to protect audio artifacts from unauthorized cloning by speech synthesizers and to safeguard user identity by altering signals to make them unusable for voice synthesis and speaker identification. In this paper, we investigate the resilience of current audio cloaking …

Network-Centric Anomaly Filtering and Spoofer localization for 5G-NR Localization in LAWNs

Zexin Fang, Bin Han, Han Zhu, Yong Guan et autres

This paper investigates security vulnerabilities and countermeasures for the 3rd Generation Partnership Project (3GPP) Fifth Generation New Radio (5G-NR) Time Difference of Arrival (TDoA)-based unmanned aerial vehicle (UAV) localization in low-altitude urban environments. We first optimize node selection strategies under Air to …

Attentive TabNet Enabled Collision Prediction for V2X Network

Korukondabhattar Srivalli Anuradha, Low Xian Hao, Nguyen Thanh Hieu, Yong Guan et autres

Collision prediction is crucial for safety in Vehicle-to-Everything (V2X) networks, essential for smart cities and intelligent transportation. Traditional methods struggle with complexity, while learning-based approaches face challenges in feature extraction and prediction accuracy. To address this, we propose attentive TabNet for collision …

sg (code pays fourni par la source)

APEX: Automatic Event Sequence Generation for Android Applications

Wenhao Chen, Witawas Srisa‐an, Yong Guan

Due to the event driven nature and the versatility of GUI designs in Android programs, it is challenging to generate event sequences with adequate code coverage within a reasonable time. A common approach to handle this issue is to rely on GUI …

Clinical Validation of a Deep Learning-Based Auto-Segmentation Model for Organs at Risk in Patients with Thoracic and Breast Cancer: A Prospective, Multicenter, Randomized Clinical Trial in China

Gang Niu, Yong Guan, Yong Zhang, Jiayi Chen et autres

Author response for "A clickable spherical nucleic acid probe for fluorescence and synchrotron radiation X-ray dual-modality imaging"

Xiaobo Wang, Xin Yan, Feng Zhou, Qiaowei Tang et autres

Author response for "A clickable spherical nucleic acid probe for fluorescence and synchrotron radiation X-ray dual-modality imaging"

Xiaobo Wang, Xin Yan, Feng Zhou, Qiaowei Tang et autres

Author response for "A clickable spherical nucleic acid probe for fluorescence and synchrotron radiation X-ray dual-modality imaging"

Xiaobo Wang, Xin Yan, Feng Zhou, Qiaowei Tang et autres

A γ-ray responsive hydrogel “blasting fuse” for prevention of postoperative breast cancer recurrence and metastasis via radio-immunotherapy

Yi Xia, Dianyu Wang, Haixue Jia, Zhilong Wang et autres

Postoperative recurrence and metastasis of breast cancer is the leading cause of death. Radiotherapy is the standard procedure after breast cancer operation. The radiation-induced abscopal effect (RIAE) exhibited tremendous therapeutic efficacy for distant tumor metastasis, but the limited radiation dose and the …

cn (code pays fourni par la source)

ReVeal: A Physics-Informed Neural Network for High-Fidelity Radio Environment Mapping

Mukaram Shahid, Kunal Das, Hadia Ushaq, Hongwei Zhang et autres

Accurately mapping the radio environment (e.g., identifying wireless signal strength at specific frequency bands and geographic locations) is crucial for efficient spectrum sharing, enabling Secondary Users (SUs) to access underutilized spectrum bands while protecting Primary Users (PUs). However, existing models either lack …

us (code pays fourni par la source)