Drought and hydrothermal humidity factor as one of the criteria to estimate its intensity degree (literature review)

The current paper has considered the following issues: determination of the drought phenomenon and its classification (atmospheric, soil and combined), drought harmfulness and spread in the Russian Federation. It has been established that regional droughts have specific features, namely soil or atmospheric, spring, summer or autumn. There has been given a classification by intensity and coverage of territories by droughts (very strong, strong, medium and weak). There has been shown a response of agricultural plants to various types of droughts. The northwestern and southeastern droughts (the second type) negatively affect the plants, as they combine low air humidity and soil with high temperature. There has been given a partial characteristic of the climate of the North Caucasus region (on the example of the Rostov region). The most used indicators of meteorological research are Selyaninov’s hydrothermal humidity factor (HHF) which is the ratio of the amount of precipitation for a period of at least a month to the sum of temperatures above 10 °C for the same period, reduced by 10 times. The classification of humidification zones according to the HHF is as follows: wet (1.6–1.3); slightly arid (1.3–1.0); arid (1.0–0.7); very arid (0.7–0.4); dry (<0.4). The data of the HHF are given on the example of meteorological conditions of the Zernograd district of the Rostov region (the years of 2001–2015). It has been found that in 2001–2015 the hydrothermal humidity factor over the autumn period was 0.13–0.17 (dry) on average, and the HHF of the summer period was 0.28 (dry). During the studied period, the hydrothermal factor during the growing season was 0.78 (dry) on average. Thus, for the period 2001–2015, the conditions for plants growth and development were unfavorable.

Non-stationary hydrological frequency analysis based on the reconstruction of extreme hydrological series

In this paper, a novel approach for non-stationary hydrological frequency analysis is proposed. The approach is due to the following consideration that, at present the data series used to detect mutation characteristic is very short, which may only reflect the partial characteristic of the population. That is to say, the mutation characteristic of short series may not fully represent the mutation characteristic of population, such as the difference of mutation degree between short sample and population. In this proposed method, an assumption is done that the variation hydrological series in a big time window owns an expected vibration center (EVC), which is a linear combination of the two mean values of the two subsample series obtained through separating the original hydrological series by a novel optimal segmentation technique (change rate of slope method). Then using the EVC to reconstruct non-stationary series to meet the requirement of stationary, and further ensure the conventional frequency analysis methods is valid.

A Novel Image Fusion Method Based on FRFT-NSCT

Nonsubsampled Contourlet transform (NSCT) has properties such as multiscale, localization, multidirection, and shift invariance, but only limits the signal analysis to the time frequency domain. Fractional Fourier transform (FRFT) develops the signal analysis to fractional domain, has many super performances, but is unable to attribute the signal partial characteristic. A novel image fusion algorithm based on FRFT and NSCT is proposed and demonstrated in this paper. Firstly, take FRFT on the two source images to obtain fractional domain matrices. Secondly, the NSCT is performed on the aforementioned matrices to acquire multiscale and multidirection images. Thirdly, take fusion rule for low-frequency subband coefficients and directional bandpass subband coefficients to get the fused coefficients. Finally, the fused image is obtained by performing the inverse NSCT and inverse FRFT on the combined coefficients. Three modes images and three fusion rules are demonstrated in the proposed algorithm test. The simulation results show that the proposed fusion approach is better than the methods based on NSCT at the same parameters.

The Trend Estimate of the Wind Turbine Based on the Wavelet Neural Network

In this paper，adopting wavelet neural network，fault forecast of characteristic parameters of Wind turbine are realized by forecasting time series of key characteristic parameters of Wind turbine that include vibration intensity. With more degree of freedom in relation to the general neural network, wavelet neural network is in possession of more vivid and more valid ability in function approximation. With the good partial characteristic and distinguish rate learning wavelet neural network realizes the signal with good matching, and then wavelet neural network had stronger self-adaptation ability, more sooner convergence rate and higher forecast accuracy. Emulation and experiment result show that the forecast accuracy of the wavelet neural network meets demand and is of far reaching importance to guarantee the steam turbine circulate efficiently safety .

On the Differentiation of Cognitive Reflection-Impulsivity

This investigation concerned the problems of confounding style and ability and generalizability in the case of indicators of cognitive reflection-impulsivity. On the basis of an interactional perspective, a number of simple assumptions about response latency and accuracy in cognitive tasks of reflection and impulsivity are developed and tasted in a sample of 46 male adolescents, aged 14 to 17 yr. The results show that the tempo variable and reasoning ability can account for a considerable portion of the inter-individual differences in accuracy. From the viewpoint of general psychology the response latency proves to be partially task-dependent, from the viewpoint of differential psychology it is a partial characteristic of persons and, probably, the real style indicator. The view that cognitive reflection represents a task-specific, problem-oriented adaptation of the conceptual tempo or intensity of alternatives-scanning is supported.