Advances in Study on Water Resources Carrying Capacity in China

AbstractThe article systematically reviews the history of water resource carrying capacity and shows that water resource carrying capacity through three exhibition stages: initial, prosperity and development. The initial stage of the study is concentrated on environmental vulnerability arid area of northwest, and put forward the concept of water resource carrying capacity. it focus on the research of the theory, quantitative research is only initial. In this phase, the writer mainly uses two methods, which are trend in conventional and fuzzy comprehensive evaluation, to study. The prosperous phase of the study extends to urban areas, drainage basin, etc. In this stage, the research mainly probes into water resource carrying capacity from characteristic, connotation and the index system, which are using a variety of new mathematical models, in order to let the study gradually transmute into quantitative-rization. The expansion phase of the study refers to groundwater resources carrying capacity, the areas of Karst and irrigation .In this stage, theory study has been especially mature, there are the artificial neural network mode and projection trace appraises model besides the first two stages methods in quantitative-rization evaluation. In the future, the study of water resources bearing capacity will be combined with water resource optional distribution and ecological water requirement enhance study representative area, simultaneously, paying more attention to the issue of recycling Reclaimed Water; During the study, quantitative analysis should be combined with advanced means such as remote sensing, etc. which can realize the development of study from static to dynamics

A comparison of cosmological models with high-redshift quasars

The non-linear relationship between the monochromatic X-ray and UV luminosities in quasars offers the possibility of using high-z quasars as standard candles for cosmological testing. In this paper, we use a high-quality catalog of 1598 quasars extending to redshift 6, to compare the flat and uniformly expanding cosmological model, $R_h$ = ct and $\Lambda$CDM cosmological models which are the most debated. The quasar samples are mainly from the XMM-Newton and the Sloan Digital Sky Survey (SDSS). The final result is that the Akaike Information Criterion favors $\Lambda$CDM over $R_h$=ct with a relative probability of 86.30% versus 13.70%.Comment: 10 pages, 5 figures, Accepted for publication in APS

Vibration model of a multi-supported guide bar and analysis on the effect of supports location

Two methods (equivalent force method and segmental mode assuming method) of calculating the natural frequencies and mode shapes of a free-free-multi-supported beam subjected to an axial load is found, considering the structure characteristic of the guide bar, which has long length but small section, and supported by many bearings. The calculation shows that these two methods are convenient for computer programing and have the same results in obtaining the natural frequencies and mode shapes of a free-free-multi-supported beam subjected to an axial load, solving the problem that the vibration function of this kind of beam is hard to deal with because it cannot be simplified with the boundary condition of two ends. Then the segmental mode assuming method is used to analyze the impact of the support location on the natural frequencies and mode shapes of the guide bar. The relation graphs of the natural frequencies with support location, as well as the support locations where the natural frequencies reached the maximum and the minimum are found, providing a reference for the support location selection for the guide bar. The changing curves of the mode shapes with support location are plotted, which show that the bending deformation is homogeneous when the length of each segment is approximately equal, avoiding the phenomenon that bending stresses concentrates at the large-amplitude segments and cause breakage while less stress exists in small-amplitude segments and hinder the exploiting of their performance, providing a reference for the structure design of the guide bar

Solution Path Algorithm for Twin Multi-class Support Vector Machine

The twin support vector machine and its extensions have made great achievements in dealing with binary classification problems, however, which is faced with some difficulties such as model selection and solving multi-classification problems quickly. This paper is devoted to the fast regularization parameter tuning algorithm for the twin multi-class support vector machine. A new sample dataset division method is adopted and the Lagrangian multipliers are proved to be piecewise linear with respect to the regularization parameters by combining the linear equations and block matrix theory. Eight kinds of events are defined to seek for the starting event and then the solution path algorithm is designed, which greatly reduces the computational cost. In addition, only few points are combined to complete the initialization and Lagrangian multipliers are proved to be 1 as the regularization parameter tends to infinity. Simulation results based on UCI datasets show that the proposed method can achieve good classification performance with reducing the computational cost of grid search method from exponential level to the constant level

Longitudinal compression of macro relativistic electron beam

We presented a novel concept of longitudinal bunch train compression capable of manipulating relativistic electron beam in range of hundreds of meters. This concept has the potential to compress the electron beam with a high ratio and raise its power to an ultrahigh level. The method utilizes the spiral motion of electrons in a uniform magnetic field to fold hundreds-of-meters-long trajectories into a compact set-up. The interval between bunches can be adjusted by modulating their sprial movement. The method is explored both analytically and numerically. Compared to set-up of similar size, such as chicane, this method can compress bunches at distinct larger scales and higher intensities, opening up new possibilities for generating beam with ultra-large energy storage.Comment: 6 pages, 6 figure

Uncertainty management in assessment of FMEA expert based on negation information and belief entropy

The failure mode and effects analysis (FMEA) is a commonly adopted approach in engineering failure analysis, wherein the risk priority number (RPN) is utilized to rank failure modes. However, assessments made by FMEA experts are full of uncertainty. To deal with this issue, we propose a new uncertainty management approach for the assessments given by experts based on negation information and belief entropy in the Dempster–Shafer evidence theory framework. First, the assessments of FMEA experts are modeled as basic probability assignments (BPA) in evidence theory. Next, the negation of BPA is calculated to extract more valuable information from a new perspective of uncertain information. Then, by utilizing the belief entropy, the degree of uncertainty of the negation information is measured to represent the uncertainty of different risk factors in the RPN. Finally, the new RPN value of each failure mode is calculated for the ranking of each FMEA item in risk analysis. The rationality and effectiveness of the proposed method is verified through its application in a risk analysis conducted for an aircraft turbine rotor blade

Multinomial Regression with Elastic Net Penalty and Its Grouping Effect in Gene Selection

For the multiclass classification problem of microarray data, a new optimization model named multinomial regression with the elastic net penalty was proposed in this paper. By combining the multinomial likeliyhood loss and the multiclass elastic net penalty, the optimization model was constructed, which was proved to encourage a grouping effect in gene selection for multiclass classification