supported by the National Key Research and Development Program of China(Grant Nos.2024YFC2207500 and 2021YFC2203100);the CAS Young Interdisciplinary Innovation Team(Grant No.JCTD-2022-20);the Fundamental Research Funds for Central Universities;the National Natural Science Foundation of China(Grant Nos.92476203,12433002 and12261131497);the 111 Project(Grant No.B23042);the CSC Innovation Talent Funds;the USTC Fellowships for International Cooperation;the USTC Research Funds of the Double First-Class Initiative。
We investigate the sensitivity and performance of space-based optical lattice clocks(OLCs)in detecting gravitational waves,in particular the stochastic gravitational wave background(SGWB)at low frequencies(10~(-4),1)H...
supported by National Key Research and Development Plan of MOST of China(Grant No.2022YFB4500101);Natural Science Foundation of Hubei Province(Grant Nos.2024AFA043,2023AFB335);Fundamental Research Funds for the Central Universities(Grant No.HUST:5003190012)。
Ternary content addressable memory(TCAM)enables high-speed parallel in-situ pattern matching[1],serving as the key processing unit for an efficient in-memory search system,which is widely studied in areas such as rout...
Project supported by the National Natural Science Foundation of China (Grant Nos. 12174115,11834003,and 91836103)。
The recently demonstrated methods for cooling and trapping diatomic molecules offer new possibilities for precision searches in fundamental physical theories.Here,we propose to study the variations of the fine-structu...
supported by the Chinese Academy of Science"Light of West China"Program(2022-XBQNXZ-015);the National Natural Science Foundation of China(11903071);the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China and administered by the Chinese Academy of Sciences。
This paper addresses the performance degradation issue in a fast radio burst search pipeline based on deep learning.This issue is caused by the class imbalance of the radio frequency interference samples in the traini...
the support from the National Natural Science Foundation of China(Grant Nos.62131002,62305028,and 62071448);the Fundamental Research Funds for the Central Universities(BNU)。
The multi-class classification of images is a pivotal challenge within the realm of image processing.As the volume of visual data continues to expand,there is a burgeoning interest in harnessing the unique capabilitie...
A system based on a PV-Wind will ensure better efficiency and flexibility using lower energy production.Today,plenty of work is being focussed on Doubly Fed Induction Generators(DFIG)utilized in wind energy systems.DF...
support by the University of Arkansas Experimental Station and the University of Arkansas College of Engineering,USDA National Institute of Food and Agriculture (No:2023-70442-39232,2024-67022-42882).
Due to intensive genetic selection for rapid growth rates and high broiler yields in recent years,the global poultry industry has faced a challenging problem in the form of woody breast(WB)conditions.This condition ha...
supported by the teaching funding of TUM School of Engineering and Design.
Earthquake and other disasters nowadays still threat people's lives and property due to their de-structiveness and unpredictability.The past decades have seen the booming development of search and rescue robots due to...
Objective:Minimally invasive treatments for benign prostatic hyperplasia (BPH) have seen an increase in usage in recent years. We aimed to determine what types of events may influence patient search habits related to ...
supported by the Gravitational-Wave Open Science Center,a service of LIGO Laboratory,the LIGO Scientific Collaboration,and the Virgo Collaboration;supported by the National Key Research and Development Program of China (Grant No.2021YFC2203001);the National Natural Science Foundation of China (Grants Nos.11920101003,12021003,12364024,and 11864014);the Natural Science Foundation of Jiangxi (Grant Nos.20224BAB211012,and 20224BAB201023)。
In our previous work [Physical Review D,2024,109(4):043009],we introduced MSNRnet,a framework integrating deep learning and matched filtering methods for gravitational wave(GW) detection.Compared with end-to-end class...