Qiusheng Li

Bio: Qiusheng Li is an academic researcher from City University of Hong Kong. The author has contributed to research in topics: Wind speed & Wind tunnel. The author has an hindex of 47, co-authored 429 publications receiving 8830 citations. Previous affiliations of Qiusheng Li include Chinese Ministry of Education & Guangzhou University.

Observational study of wind characteristics from 356-meter-high Shenzhen Meteorological Tower during a severe typhoon

Abstract: The characteristics of winds associated with tropical cyclones are of great significance in many engineering fields. This paper presents an investigation of wind characteristics over a coastal urban terrain based on field measurements collected from multiple cup anemometers and ultrasonic anemometers equipped at 13 height levels on a 356-m-high meteorological tower in Shenzhen during severe Typhoon Hato. Several wind quantities, including wind spectrum, gust factor, turbulence intensity and length scale as well as wind profile, are presented and discussed. Specifically, the probability distributions of fluctuating wind speeds are analyzed in connection with the normal distribution and the generalized extreme value distribution. The von Karman spectral model is found to be suitable to depict the energy distributions of three-dimensionally fluctuating winds. Gust factors, turbulence intensity and length scale are determined and discussed. Moreover, this paper presents the wind profiles measured during the typhoon, and a comparative study of the vertical distribution of wind speeds from the field measurements and existing empirical models is performed. The influences of the topography features and wind speeds on the wind profiles were investigated based on the field-measured wind records. In general, the empirical models can provide reasonable predictions for the measured wind speed profiles over a typical coastal urban area during a severe typhoon.

Terahertz vortex beam generator carrying orbital angular momentum in both transmission and reflection spaces.

Abstract: Vortex beam generators carrying orbital angular momentum (OAM) with both transmission and reflection modes has broad application prospects in full-space high data capacity communication and orbital angular momentum multiplexing systems. In this work, we proposed a vanadium dioxide (VO2) assisted metasurface to independently produce and manipulate focused vortex transmission-reflection modes with different number of beams and focal lengths under right-handed circular polarized (RCP) wave incidence. The proposed metasurface generates the diagonal vortex beams, four vortex beams, and focused vortex beam for transmission mode at 1.26THz and reflection mode at 1.06THz by changing phase state of the VO2. Our work may find many potential applications in future high data capacity information multiplexing communication systems.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Nonlinear Time Series Analysis.

Abstract: : This thesis applies neural network feature selection techniques to multivariate time series data to improve prediction of a target time series. Two approaches to feature selection are used. First, a subset enumeration method is used to determine which financial indicators are most useful for aiding in prediction of the S&P 500 futures daily price. The candidate indicators evaluated include RSI, Stochastics and several moving averages. Results indicate that the Stochastics and RSI indicators result in better prediction results than the moving averages. The second approach to feature selection is calculation of individual saliency metrics. A new decision boundary-based individual saliency metric, and a classifier independent saliency metric are developed and tested. Ruck's saliency metric, the decision boundary based saliency metric, and the classifier independent saliency metric are compared for a data set consisting of the RSI and Stochastics indicators as well as delayed closing price values. The decision based metric and the Ruck metric results are similar, but the classifier independent metric agrees with neither of the other metrics. The nine most salient features, determined by the decision boundary based metric, are used to train a neural network and the results are presented and compared to other published results. (AN)