J. Qiu

activity

20102025

most citedDamage identification for bridges using machine learning: Development and application to KW51 bridge

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

hep-ex2025

First measurement of the cross sections for $e^{+} e^{-} \to K^{0} K^{-} π^{+} J / ψ + c . c .$ at $s$ from 4.396 to 4.951 GeV

BESIII Collaboration, M. Ablikim, M. N. Achasov +701

Using $e^{+} e^{-}$ collision data at 19 center-of-mass energies ranging from $4.396$ to $4.951 GeV$ corresponding to a total integrated luminosity of $8.86 fb^{- 1}$ coll…

eess.SP2024★ 1 cited

Damage identification for bridges using machine learning: Development and application to KW51 bridge

Yuqing Qiu, Bilal Ahmed, Diab W. Abueidda +6

The available tools for damage identification in civil engineering structures are known to be computationally expensive and data-demanding. This paper proposes a comprehensive mach…

physics.class-ph2010

A low-power circuit for piezoelectric vibration control by synchronized switching on voltage sources

Hui Shen, Jinhao Qiu, Hongli Ji +4

In the paper, a vibration damping system powered by harvested energy with implementation of the so-called SSDV (synchronized switch damping on voltage source) technique is designed…

First measurement of the cross sections for e+e−→K0K−π+J/ψ+c.c. at s​ from 4.396 to 4.951 GeV

Damage identification for bridges using machine learning: Development and application to KW51 bridge

A low-power circuit for piezoelectric vibration control by synchronized switching on voltage sources

First measurement of the cross sections for $e^{+} e^{-} \to K^{0} K^{-} π^{+} J / ψ + c . c .$ at $s$ from 4.396 to 4.951 GeV