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Xiang Zhang

Researcher at Baylor College of Medicine

Publications -  3483
Citations -  144843

Xiang Zhang is an academic researcher from Baylor College of Medicine. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 154, co-authored 1733 publications receiving 117576 citations. Previous affiliations of Xiang Zhang include University of California, Berkeley & University of Texas MD Anderson Cancer Center.

Papers
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Study of cosmic ray events with high muon multiplicity using the ALICE detector at the CERN Large Hadron Collider

Jaroslav Adam, +1028 more
TL;DR: In this article, the multiplicity distribution of these atmospheric muons and its comparison with Monte Carlo simulations are presented, and a special emphasis is given to the study of high multiplicity events containing more than 100 reconstructed Muons and corresponding to a muon areal density ≥ 5.9~$m$−2.
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Nonresonant Metasurface for Fast Decoding in Acoustic Communications

TL;DR: In this paper, a parabolic-phased metasurface is proposed to convert the spiral-phase patterns of vortex beams carrying various angular momenta into plane waves with different in-plane linear momenta.
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Quantification of Extensional Uncertainty of Segmented Image Objects by Random Sets

TL;DR: It is shown that several characteristics of extensional uncertainty of segmented objects can be quantified numerically and spatially by random sets.
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Resonance amplification of left-handed transmission at optical frequencies by stimulated emission of radiation in active metamaterials

TL;DR: It is demonstrated that left-handed resonance transmission from metallic metamaterial, composed of periodically arranged double rings, can be extended to visible spectrum by introducing an active medium layer as the substrate.
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Mining Dual Networks: Models, Algorithms, and Applications

TL;DR: This article proposes the novel dual-network model and investigates the problem of finding the densest connected subgraph (DCS), which has the largest density in the conceptual network and is also connected in the physical network, and develops a two-step approach to solve the DCS.