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 …

I and i

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

System Identification I

Dynamics of structures

: 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)

/pdf/nonlinear-time-series-analysis-1j3a35n4y3.pdf

Nonlinear Time Series Analysis.

Experimental study on wind load characteristics of high‐rise buildings with opening

Summary
Tropical cyclone-induced disasters cause significant economic losses and heavy causalities every year. Most of the casualties were caused by low-rise buildings collapsing. This study aims to investigate the characteristics of tropical cyclone-generated winds and evaluate the wind effects on a typical low-rise building under tropical cyclone conditions through field measurements. In-situ monitoring was conducted on a full-scale low-rise building during the landfall of severe tropical storm Rumbia in 2013. Both the wind velocity field around and the surface pressures on the building were recorded during the storm. Characteristics of wind velocity field near ground during the windstorm were analyzed and compared with the specifications in the load code of China. Furthermore, when the wind approached in oblique directions, the windward roof corner suffered from the worst suctions under conical vortex. It was found that the maximum shape factors under the oblique winds were significantly larger than those specified in the load code. Moreover, probability density distributions of surface pressures induced by conical vortex were found to deviate from the Gaussian distribution. The outcomes of this study are expected to be of practical and imperative use to the wind-resistant design of low-rise buildings in tropical cyclone-prone regions. Copyright © 2016 John Wiley & Sons, Ltd.

Monitoring of wind effects on an instrumented low‐rise building during the landfall of a severe tropical storm

Time-dependent reliability analysis of glass cladding under wind action

The stochastic subspace algorithm is one of the most widely used structural identification techniques, which is generally involved with the stabilization diagram for estimating modal parameters. However, the conventional stabilization diagram has an inherent problem: some spurious modes may be identified as stable results, resulting in adverse effects on structural modal identification. To address this critical issue, this paper proposes an improved stochastic subspace algorithm involving a Monte Carlo–based stabilization diagram. Through a numerical simulation study, the good performance of the Monte Carlo–based stabilization diagram for discriminating the poles denoting the physical modes from those representing spurious modes is demonstrated. The numerical simulation results show that the proposed method can estimate structural modal parameters with high accuracy and robustness. Moreover, the proposed method is applied to field measurements on a 600-m-high skyscraper during Super Typhoon Mangkhut, and the results verify the applicability and effectiveness of the proposed method to field measurements. This paper aims to provide an effective tool for accurate estimation of modal parameters of civil structures. 

Qiusheng Li

Papers

Experimental study on wind load characteristics of high‐rise buildings with opening

Monitoring of wind effects on an instrumented low‐rise building during the landfall of a severe tropical storm

Time-dependent reliability analysis of glass cladding under wind action

Modal Identification of Civil Structures via Stochastic Subspace Algorithm with Monte Carlo–Based Stabilization Diagram

Large eddy simulation of wind-driven rain effects on a large span retractable roof stadium