Qingdao Innovation

2 months ago | onlinelibrary.wiley.com | Fanzhou Lv |Qingdao Innovation |Yan Zheng |Yi Wang

Conflict of Interest The authors declare no conflict of interest. Supporting Information Filename Description smll202412315-sup-0001-SuppMat.docx877.8 KB Supporting Information References 1, , Nat. Photonics 2013, 7, 674. 2, , , , , , , , Nat. Photonics 2014, 8, 835. 3, , , J. Phys. Chem. B 2003, 107, 7343. 4, , J. Chem. Phys. 2004, 121, 12606. 5, , , , , , , , , Nano Lett. 2005, 5, 1065. 6, , , , , , , , , , Nature 2009, 460, 1110. 7, , , , , , , , Nat. Nanotechnol.

Dec 4, 2024 | pubs.aip.org | Harbin Engineering |Qingdao Innovation |Crystal Owens |Zengshun Chen

The water entry cavity and load characteristics obtained through scaled-down tests are correlated with the atmospheric pressure and density at the free surface. The evaluation of the influence of the cavitation number and atmospheric density coefficient is highly essential for scale tests to improve the prototype prediction accuracy.

Sep 5, 2024 | onlinelibrary.wiley.com | Shibo Wei |Qingdao Innovation |Jingcong Hu |Engineering Beijing

Chenghao Bi Qingdao Innovation and Development Base, Harbin Engineering University, Qingdao, 266000 China College of Physics and Optoelectronic Engineering, Harbin Engineering University, Harbin, 150001 China Yantai Research Institute, Harbin Engineering University, Yantai, 264000 ChinaSearch for more papers by this author

Jun 13, 2024 | pubs.aip.org | Harbin Engineering |Qingdao Innovation |Calbert Graham

Topics Underwater acoustics, Hydrophone, Speed of sound, Spectrograms, Acoustic signal processing, Data processing, Signal-to-noise ratio, Fourier analysis, Calculus of variations, Covariance and correlation Underwater passive detection of target-of-interest (TOI) in the presence of multiple strong interferences becomes a significant challenge.

May 23, 2024 | link.springer.com | Harbin Engineering |Qingdao Innovation

AbstractThe estimation of sparse underwater acoustic (UWA) channels can be regarded as an inference problem involving hidden variables within the Bayesian framework. While the classical sparse Bayesian learning (SBL), derived through the expectation maximization (EM) algorithm, has been widely employed for UWA channel estimation, it still differs from the real posterior expectation of channels.