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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.


Papers
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Journal ArticleDOI
TL;DR: In this article, a quadratic finite element with generalized degrees of freedom (GDOF) and a finite strip with GDOF based on the principle that the local displacement fields of elements should be compatible with the global displacement field of the corresponding systems is presented.

3 citations

Journal ArticleDOI
TL;DR: In this article, a new exact approach for forced vibration analysis of single-degree-of-freedom (SDOF) systems with nonperiodically time-varying parameters (mass and stiffness) is presented.
Abstract: A new exact approach for forced vibration analysis of single-degree-of-freedom (SDOF) systems with nonperiodically time-varying parameters (mass and stiffness) is presented. In this paper, the variations of mass and stiffness, relative to time, are described by the selection of suitable expressions such as power functions and exponential functions. More general cases, such as the variation of mass is described by an arbitrary continuous real-valued function and the variation of stiffness is expressed as a functional relation with the variation of mass and vice versa, are also considered in this study. Using appropriate functional transformation, the governing differential equations for vibrations of SDOF systems with nonperiodically time-varying parameters are reduced to Bessel’s equations or other solvable equations for several important cases. Thus, classes of exact solutions for the free and forced vibrations of SDOF systems with arbitrarily time-varying parameters (mass and stiffness) are obtained. Nu...

3 citations

Journal ArticleDOI
TL;DR: In this article, the suboptimal control rule is introduced in structural control implementation as an alternative over the optimal control because the optimal Control may require large amount of processing time when applied to complex structural control problems.
Abstract: The suboptimal control rule is introduced in structural control implementation as an alternative over the optimal control because the optimal control may require large amount of processing time when applied to complex structural control problems. It is well known that any time delay in structural control implementation will cause un-synchronized application of the control forces, which not only reduce the effectiveness of an active control system, but also cause instability of the control system. The effect of time delay on the displacement and acceleration responses of building structures is studied when the suboptimal control rule is adopted. Two examples are given to show the effectiveness of the suboptimal control rule. It is shown through the examples that the present method is easy in implementation and high in efficiency and it can significantly reduce the time delay in structural control implementation without significant loss of performance.

3 citations

Journal Article
TL;DR: In this article, field measurements of wind effects on a low-rise building, during typhoon Hagupit, presented selected field measured data, the characteristics of wind speed,wind direction,gust factor, turbulence intensity,turbulence scale and spectra were discussed in detail.
Abstract: Based on field measurements of wind effects on a low-rise building,during typhoon Hagupit,the paper presented selected field measured data.The characteristics of wind speed,wind direction,gust factor,turbulence intensity,turbulence scale and spectra were discussed in detail.The measurement arrangements for the wind pressures on the low rise building were also introduced in the paper.The results show that,the instantaneous maximum wind speed was 56.7m/s,10-minitues mean wind speed 40.2m/s.The higher was the wind speed,the lower values were the turbulence intensity and the gust factor.Before Typhoon 'Hagupit' landfalling,the wind speed and wind direction were fluctuated remarkably.After 'Hagupit' landfalling,the turbulence intensity,the gust factor and the turbulence integral length scale became smaller obviously;and the measured wind speed spectra were in good agreement with von Karman spectrum.The outputs of this study are very useful for further understanding of the characteristics of wind field during severe typhoon,it is also expected that the results presented in this paper should be valuable for wind-resistant design of low-rise buildings.

3 citations

Journal ArticleDOI
TL;DR: In this article, NbC-SiC micro/nanowires (MNWs) were synthesized at 1600-1800°C via carbothermal reduction using silica sol, niobium pentoxide powder and carbon black starting materials.
Abstract: NbC–SiC micro/nanowires (MNWs) with NbC content varying from 5 to 20 mol.-% were synthesised at 1600–1800°C via carbothermal reduction utilising silica sol, niobium pentoxide powder and carbon black as starting materials. The synthesis process and growth mechanism of NbC–SiC system were investigated. Results show that the morphology of the synthesised products mainly appears as curve shaped microwires or nanowires. The crystalline consists of both SiC and NbC phases which doped with each other by substitution and interstitial reactions in solid solution. NbC–SiC MNWs were developed by vapour–liquid–solid mechanism according to the existence of liquid droplet phase in the tip at reaction temperature. β-SiC twin crystal growing along [112] direction was formed in the stem, and NbC polycrystal was dissociated from Nb–Si liquid phase. The varied concentration of Nb and Si in the Nb–Si liquid phase could be a significant reason for the curved growth of NbC–SiC MNWs.

3 citations


Cited by
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[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
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 …

33,785 citations

Book ChapterDOI
11 Dec 2012

1,704 citations

Journal ArticleDOI

1,604 citations

01 Mar 1995
TL;DR: This thesis applies neural network feature selection techniques to multivariate time series data to improve prediction of a target time series and results indicate that the Stochastics and RSI indicators result in better prediction results than the moving averages.
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)

1,545 citations