For contradiction and complexity of wind environment variables of coastal cities and difficulties in the quantitative research of urban spatial form, the multi-variable analysis technology is flexibly used to explore ...
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ISBN:
(纸本)9781510848061
For contradiction and complexity of wind environment variables of coastal cities and difficulties in the quantitative research of urban spatial form, the multi-variable analysis technology is flexibly used to explore the feasible technical approach and coupling mechanism for the integration of coastal urban spatial form and the mesoscale wind environment system. The mechanism of influence of changes of coastal urban spatial form on wind environment is summarized, and the energy balance mode based on mesoscale wind environment nested with the urban boundary layer combining with the underlying surface of cities is studied, so as to make strategies for the response by urban spatial form to urban wind environment, simulate and analyze the response characteristics of urban heat island, local wind and pollution diffusion under different scenarios, and determine the feasible scheme of urban spatial form combined with demands for the development of social economy. With the combination of satellite remote sensing and ground monitoring, related parameters are collected, and simulated and calculated with CFD. After a conclusion is drawn through the multi-variable analysis the large wind tunnel laboratory model is used for verification. Further R&D can optimize the spatial form guidance system software for wind environment of coastal cities. This study will help to actively adjust urban wind environment through space guidance;provide reference for air pollution prevention and control, typhoon prevention and mitigation, urban energy saving and emission reduction and other hot research issues caused by the high-speed development of coastal cities in China;and respond to the government's call for the construction of new smart cities.
In this work a design method for discrete-time current controllers in induction motor drives is addressed. The method of individual channel analysis and design is used in order to represent the IM model as two single-...
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ISBN:
(纸本)9781728114033
In this work a design method for discrete-time current controllers in induction motor drives is addressed. The method of individual channel analysis and design is used in order to represent the IM model as two single-input single-output (SISO) linear systems. Then, based on the obtained transfer functions, the controllers are designed in order to control the original multiple-input multiple-output system as if they were two SISO systems decoupled from each other. Therefore, the method allows to apply classical control techniques for the design of the controllers and simplify the analysis of the system. By following this approach, simple deadbeat controllers are proposed, analyzed and validated by simulation results.
ABSTRACTIn this study, we evaluate the performance of theN-dimensional multivariate Bias Correction (MBCn) statistical downscaling method over the Fraser River Basin in British Columbia, Canada. Modelling climatic and...
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ABSTRACTIn this study, we evaluate the performance of theN-dimensional multivariate Bias Correction (MBCn) statistical downscaling method over the Fraser River Basin in British Columbia, Canada. Modelling climatic and hydrologic processes in this key watershed in western Canada requires an expanded suite of variables beyond precipitation and temperature. Here, we assess how well MBCn downscaled simulations replicate univariate and multivariate properties of nine climatic variables in this basin, and whether MBCn provides added value over a univariate downscaling method (Quantile Delta Mapping; QDM) applied to the same variables. Data for the analysis include daily values from the Canadian Surface Reanalysis (CaSR) and two realizations of the Canadian Earth System Model Version 5 (CanESM5). multivariate downscaling to10×10km resolution is applied with MBCn using two approaches: first, using aggregated CaSR as input in a perfect model framework; second, using each CanESM5 realization subjected to two calibration strategies, yielding four distinct downscaled simulations that help reveal the role of internal variability. Results comparing each downscaling approach to CaSR during 1980–2018 indicate that MBCn reproduces the spatial and temporal properties of most univariate and multivariate indices considered, although there is greater disagreement between the MBCn-downscaled results and the target data in mountainous areas of the basin. Pairwise correlation analyses from the CanEM5 simulations reveal that MBCn is able to preserve the interdependencies among the nine climate variables in the target data that are not captured using the univariate QDM downscaling method. Similar added value is also found from MBCn in the representation of multivariate derived indices calculated from combinations of the nine climate variables in the basin. Overall, using MBCn to downscale interdependent variables in regions such as the Fraser River Basin offers potential improvements for app
This paper presents a method to classify chronic Low Back Pain subject by analyzing the muscular fatigue. A new signal characteristic is introduced: the spatial distribution of the Median Frequency slope. Because of t...
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ISBN:
(纸本)9781479961139
This paper presents a method to classify chronic Low Back Pain subject by analyzing the muscular fatigue. A new signal characteristic is introduced: the spatial distribution of the Median Frequency slope. Because of the high number of sensors relative to the number of subjects tested, the classification method used is the Naive Bayesian classifier. The low back muscular fatigue is measured by the use of a matrix of 60 surface electromyography sensors. A total of 65 subjects comprising 43 with chronic low back pain condition and 22 healthy have perform a Sorenson test to produce fatigue on lumbar erector spinae muscles. A success rate of almost 70% cross-validated by a leave-one-out method is reported. The statistical significance of this success rate is evaluated by a permutation method.
The objective is to analyse vocal dysperiodicities in connected speech produced by dysphonic speakers. The analysis involves a variogram-based method that enables tracking instantaneous vocal dysperiodicities. The dys...
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The objective is to analyse vocal dysperiodicities in connected speech produced by dysphonic speakers. The analysis involves a variogram-based method that enables tracking instantaneous vocal dysperiodicities. The dysperiodicity trace is summarized by means of the signal-to-dysperiodicity ratio, which has been shown to correlate strongly with the perceived degree of hoarseness of the speaker. Previously, this method has been evaluated on small corpora only. In this article, analyses have been carried out on two corpora comprising over 250 and 700 speakers. This has enabled carrying out multi-frequency band and multi-cue analyses without risking overfitting. The analysis results are compared to the cepstral peak prominence, which is a popular cue that indirectly summarizes vocal dysperiodicities frame-wise. A perceptual rating has been available for the first corpus whereas speakers in the second corpus have been categorized as normal or pathological only. For the first corpus, results show that the correlation with perceptual scores increases statistically significantly for multi-band analysis compared to conventional full-band analysis. Also, combining the cepstral peak prominence with the low-frequency band signal-to-dysperiodicity ratio statistically significantly increases their combined correlation with perceptual scores. The signal-to-dysperiodicity ratios of the two corpora have been separately submitted to principal component analysis. The results show that the first two principal components are interpretable in terms of the degree of dysphonia and the spectral slope, respectively. The clinical relevance of the principal components has been confirmed by linear discriminant analysis. (C) 2010 Elsevier B.V. All rights reserved.
FTA and ETA are popular method for analyzing the accidents of large scale process plants. While these are useful for the evaluation of rare but essential accidents of a specified plant, we can not use then effectively...
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FTA and ETA are popular method for analyzing the accidents of large scale process plants. While these are useful for the evaluation of rare but essential accidents of a specified plant, we can not use then effectively to such accidents that are caused by the combination of small and daily troubles. Most of them are based on human errors. In this paper, we introduce a new method which is effective for the analysis of this kind of troubles. We combine Fault Tree analysis with multi-variable analysis by considering sets of events. The grade of occurrence and the transition of of macro-events are fuzzified in the calculation of MFT. We can obtain common characteristics of accidents through this analysis and the general counterplans are easily deduced. We apply this method to the analysis on real data of the plant-accidents happened in Kawasaki industrial area in 12 years and comfirm its effectiveness.
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