The Application of Continuous Wavelet Transform Based Foreground Subtraction Method in 21 cm Sky Surveys

We propose a continuous wavelet transform based non-parametric foreground subtraction method for the detection of redshifted 21 cm signal from the epoch of reionization. This method works based on the assumption that the foreground spectra are smooth in frequency domain, while the 21 cm signal spectrum is full of saw-tooth-like structures, thus their characteristic scales are significantly different. We can distinguish them in the wavelet coefficient space easily and perform the foreground subtraction. Compared with the traditional spectral fitting based method, our method is more tolerant to complex foregrounds. Furthermore, we also find that when the instrument has uncorrected response error, our method can also work significantly better than the spectral fitting based method. Our method can obtain similar results with the Wp smoothing method, which is also a non-parametric method, but our method consumes much less computing time.Comment: Accepted by Ap

The strain softening model of rock damage under compression and tension

Deformation and failure of brittle material under compression are different from those under tension. The differences are characteristic for the brittle material such as rock, concrete and others. At present, few constitutive models for rock can reflect the differences. A damage-induced softening model for rock constitutive relations is presented based on statistical strength theory, continuum damage mechanics and elastic mechanics. The model can consider properties of rock mechanics such as strain softening, difference in strength between compression and tension, non-liner stress-strain relation, compressive hardening, brittleness and so on. The model is well-adapted, simple and practical as it is flexible and has only 7 parameters which can be easily obtained from uniaxial test under compression and tension. Under triaxial compression, uniaxial compression and uniaxial tension, the stress-strain relations obtained from the presented model are compared with those obtained from laboratory tests. The comparisons show that the differences between results obtained respectively from the presented model and laboratory tests are small. The presented model is rational

Dynamic Stochastic Multi-Criteria Decision Making Method Based on Prospect Theory and Conjoint Analysis

A method based on prospect theory and conjoint analysis is proposed for dynamic stochastic multi-criteria decision making problems, in which the information about criteria weight is unknown and criteria values follow some kinds of distributions. Decision-maker’s attitude towards risk is introduced into this paper. First, data is collected by investigation and criteria weights are derived by conjoint analysis. The prospect values of each alternative in different periods are calculated according to distribution function. Then, index distribution decides time sequence weight, and overall prospect values of each alternative are obtained and ranked by aggregating prospect values in different periods. Finally, an example of choosing the best product illustrates the feasibility and effectiveness of this method