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.

Synthesis of β-Ga2O3 Nanowires by Laser Ablation

Abstract: A simple laser ablation method has been employed for the synthesis of β-Ga2O3 nanowires. The as-synthesized products were characterized by X-ray powder diffraction (XRD), transmission electron microscopy (TEM), and room-temperature photoluminescence. The synthesized β-Ga2O3 nanowires have diameters of 15−50 nm and lengths up to several micrometers, and a few of the nanowires appear to have ring-shaped structures. Photoluminescence of the bulk β-Ga2O3 nanowires shows a stable and broad green emission band centered at 497 nm, which has a blueshift of 30 nm from β-Ga2O3 powder. Possible growth mechanisms of the β-Ga2O3 nanowires are briefly discussed.

Structural performance of multi-outrigger-braced tall buildings

Abstract: The optimum designs of multi-outriggers in tall building structures are presented and discussed in this paper, through the analysis of structural performance of outrigger-braced frame-core structures. The influences of the locations of outriggers and the variations of structural element stiffness on the base moment in core, top drift and fundamental vibration period of such tall building structures are analysed in detail. A non-linear optimum design procedure for reducing the base moment in the core is presented based on the penalty function method. The computer programs are developed on the basis of the proposed methods for analysing the behaviour and optimum design of multi-outrigger structures. A series of figures presented in this paper can be used for the design purposes of outrigger-braced tall building structures. Copyright © 2003 John Wiley & Sons, Ltd.

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)