Exploration of the Impact Mechanism of Government Credibility Based on Variable Screening Method

Government credibility is an important asset of contemporary national governance, an important criterion for evaluating government legitimacy, and a key factor in measuring the effectiveness of government governance. In recent years, researchers’ research on government credibility has mostly focused on exploring theories and mechanisms, with little empirical research on this topic. This article intends to apply variable selection models in the field of social statistics to the issue of government credibility, in order to achieve empirical research on government credibility and explore its core influencing factors from a statistical perspective. Specifically, this article intends to use four regression-analysis-based methods and three random-forest-based methods to study the influencing factors of government credibility in various provinces in China, and compare the performance of these seven variable selection methods in different dimensions. The research results show that there are certain differences in simplicity, accuracy, and variable importance ranking among different variable selection methods, which present different importance in the study of government credibility issues. This study provides a methodological reference for variable selection models in the field of social science research, and also offers a multidimensional comparative perspective for analyzing the influencing factors of government credibility.

Base force element method of complementary energy principle for large rotation problems

Using the concept of the base forces, a new finite element method （base force element method, BFEM） based on the complementary energy principle is presented for accurate modeling of structures with large displacements and large rotations. First, the complementary energy of an element is described by taking the base forces as state variables, and is then separated into deformation and rotation parts for the case of large deformation. Second, the control equations of the BFEM based on the complementary energy principle are derived using the Lagrange multiplier method. Nonlinear procedure of the BFEM is then developed. Finally, several examples are analyzed to illustrate the reliability and accuracy of the BFEM.

A New Multidimensional Time Series Forecasting Method Based on the EOF Iteration Scheme

In this paper a new .mnultidimensional time series forecasting scheme based on the empirical orthogonal function (EOF) stepwise iteration process is introduced. The scheme is tested in a series of forecast experiments of Nino3 SST anomalies and Tahiti-Darwin SO index. The results show that the scheme is feasible and ENSO predictable.

Distance-Coefficient-Based Imaging Accuracy Improving Method Based on the Lamb Wave

An imaging accuracy improving method is established, within which a distance coefficient including location information between sparse array configuration and the location of defect is proposed to select higher signal- to-noise ratio data from all experimental data and then to use these selected data for elliptical imaging. Tile relationships among imaging accuracy, distance coefficient and residual direct wave are investigated, and then the residual direct wave is introduced to make the engineering application more convenient. The effectiveness of the proposed method is evaluated experimentally by sparse transducer array of a rectangle, and the results reveal that selecting experimental data of smaller distance coefficient can effectively improve imaging accuracy. Moreover, the direct wave difference increases with the decrease of the distance coefficient, which implies that the imaging accuracy can be effectively improved by using the experimental data of the larger direct wave difference.

A LEAST SQUARE BASED WEAK GALERKIN FINITE ELEMENT METHOD FOR SECOND ORDER ELLIPTIC EQUATIONS IN NON-DIVERGENCE FORM

This article is devoted to establishing a least square based weak Galerkin method for second order elliptic equations in non-divergence form using a discrete weak Hessian operator.Naturally,the resulting linear system is symmetric and positive definite,and thus the algorithm is easy to implement and analyze.Convergence analysis in the H2 equivalent norm is established on an arbitrary shape regular polygonal mesh.A superconvergence result is proved when the coefficient matrix is constant or piecewise constant.Numerical examples are performed which not only verify the theoretical results but also reveal some unexpected superconvergence phenomena.

A New Diagnostic Method Applied to Gearbox Missing Gear Faults——LOD-ICA

With the increasingly stringent requirements for carbon emissions,countries have increased the scale of clean energy use in recent years.As an important new clean energy source,the ratio of wind power in energy utilization has been increasing.The horizontal axis wind turbine is the main form of wind power generation,which is subject to random wind loads during operation and is prone to various failures after a long period of operation,resulting in reduced power generation efficiency or even shutdown.In order to ensure stable external power transmission,it is necessary to perform fault diagnosis for wind turbines.However,the traditional time-frequency analysis method is defective.This paper proposes a new LOD-ICA method to realize the resolution of the vibration signals mode mixing problem incorporated the merits of both methods.The LOD-ICA method and the LOD method based on noise-assisted analysis decompose the same signal to produce different signal components.The feasibility of the LOD-ICA method was verified by comparing the correlation coefficients between each of the signal components generated by the two methods and the original signal.In the field of wind turbine fault diagnosis,the LOD-ICA method is employed to the fault characteristics of gearboxes to extract the fault signs of vibration signals,further demonstrated the superiority of the LOD-ICA method in processing vibration signals of rotating machinery.

Variable-Coefficient Mapping Method Based on Elliptical Equation and Exact Solutions to Nonlinear SchrSdinger Equations with Variable Coefficient

In this paper, by means of the variable-coefficient mapping method based on elliptical equation, we obtain explicit solutions of nonlinear Schrodinger equation with variable-coefficient. These solutions include Jacobian elliptic function solutions, solitary wave solutions, soliton-like solutions, and trigonometric function solutions, among which some are found for the first time. Six figures are given to illustrate some features of these solutions. The method can be applied to other nonlinear evolution equations in mathematical physics.

Prediction of Superconductivity for Oxides Based on Structural Parameters and Artificial Neural Network Method

Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distributed ranges of the superconductive transition temperature (Tc) for complex oxides, and Tc values for cuprate superconductors. The calculated results indicated that the adjusted ANN can be used to predict superconductive properties for unknown oxides.

QUANTITATIVE ANALYSIS OF VERY WEAK ACID AND BASE BY pH-FIXED TITRATION METHOD

pH-fixed titration method for the determination of weak acids and bases has been studied in this paper.It is not necessary to know the ionization constant of weak acid or base and the concentration of titrant. This method had been applied to determine phenol,4-aminoantipyrine and glycine,whose ionization constants range from 10^(-10)to 10^(-12).The results were satisfactory.

Visual Passive Ranging Method Based on Re-entrant Coaxial Optical Path and Experimental Verification

To overcome the shortcomings of the traditional passive ranging technology based on image, such as poor ranging accuracy, low reliability and complex system, a new visual passive ranging method based on re-entrant coaxial optical path is presented. The target image is obtained using double cameras with coaxial optical path. Since there is imaging optical path difference between the cameras, the images are different. In comparison of the image differences, the target range could be reversed. The principle of the ranging method and the ranging model are described. The relationship among parameters in the ranging process is analyzed quantitatively. Meanwhile,the system composition and technical realization scheme are also presented. Also, the principle of the method is verified by the equivalent experiment. The experimental results show that the design scheme is correct and feasible with good robustness. Generally, the ranging error is less than 10% with good convergence. The optical path is designed in a re-entrant mode to reduce the volume and weight of the system. Through the coaxial design,the visual passive range of the targets with any posture can be obtained in real time. The system can be widely used in electro-optical countermeasure and concealed photoelectric detection.

Man-Computer Interactive Method on Cloud Classification Based on Bispectral Satellite Imagery

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Artificial Neural Network Method Based on Expert Knowledge and Its Application to Quantitative Identification of Potential Seismic Sources

In this paper,an approach is developed to optimize the quality of the training samples in the conventional Artificial Neural Network(ANN)by incorporating expert knowledge in the means of constructing expert-rule samples from rules in an expert system,and through training by using these samples,an ANN based on expert-knowledge is further developed.The method is introduced into the field of quantitative identification of potential seismic sources on the basis of the rules in an expert system.Then it is applied to the quantitative identification of the potential seismic sources in Beijing and its adjacent area.The result indicates that the expert rule based on ANN method can well incorporate and represent the expert knowledge in the rules in an expert system,and the quality of the samples and the efficiency of training and the accuracy of the result are optimized.

THE ANALYTICAL SOLUTIONS BASED ON THE CONCEPT OF FINITE ELEMENT METHODS

On the basis of the concept of finite element methods, the rigorous analytical solutions of structural response in terms of the design variables are researched in this paper. The spatial trusses are taken as an example for the solution of the analytical expressions of the explicit displacements which are proved mathematically; then some conclusions are reached that are useful to structural sensitivity analysis and optimization. In the third part of the paper, a generalized geometric programming method is sugguested for the optimal model with the explicit displacement. Finally, the analytical solutions of the displacements of three trusses are given as examples.

Isolating cDNA clones from rice induced by Magnaporthe grisea using PCR based differential screening method

The differential hybridization technique hasbeen widely used to identify genes that are dif-ferentially expressed.However,this approachhas several drawbacks.First,the screeningprocedures are rather labor-intensive and time-consuming.Second,the amount of phageDNAs transferred onto the two filters may notbe equivalent,which leads to an inaccurate se-lection of a positive clone.Third,isolation ofphage DNA is slow and cumbersome.Here,aPCR based differential screening method that

A Method for Preparation of Ordered Porous Silicon Based on a 2D SiO_2 Template

A new method for fabricating ordered porous silicon is reported. A two-dimensional silica nanosphere array is used as a template with a hydrofluoric acid-hydrogen peroxide solution for etching the nanospheres. The initial diameter and distribution of the holes in the resulting porous silicon layer are determined by the size and distribution of the silica nanospheres. The corrosion time can be used to control the depths of the holes. It is found that the presence of a SiO2 layer, formed by the oxidation of the rough internal surface of the hole, is the primary reason allowing the corrosion to proceed. Ultraviolet reflection and thermal conductivity measurements show that the diameter and distribution of the holes have a great influence on properties of the porous silicon.

Residue Based Open-Loop Modal Analysis Method for Detecting LFMR of PMSG-WFs Penetrated Power Systems

This paper proposes a residue based open-loop modal analysis method to detect low frequency modal resonance(LFMR),including asymmetric low frequency modal attraction(ALFMA)and asymmetric low frequency modal repulsion(ALFMR),of permanent magnetic synchronous generator based wind farms(PMSG-WFs)penetrated power systems.The formation of ALFMA and ALFMR caused by two open-loop low frequency oscillation(LFO)modes moving close and apart is analyzed in detail.Via predicting the trajectories of closed-loop LFO modes based on calculation of residue of open-loop LFO modes,both ALFMA and ALFMR can be detected.The proposed method can select LFO modes which move to the right half complex plane as control parameters vary.Simulation studies are carried out on a three-machine power system and a four-machine 11-bus power system to verify the properties of the proposed method.

WAVELET-BASED FAIRING OF B-SPLINE SURFACES

A method of fairing B spline surfaces by wavelet decomposition is investigated. The wavelet decomposition and reconstruction of quasi uniform bicubic B spline surfaces are described in detail. A method is introduced to approximate a B spline surface by a quasi uniform one. An error control approach for wavelet based fairing is suggested. Samples are given to show the feasibility of the algorithms presented in this paper. The practice showed that the wavelet based fairing is better than energy based one in case where the number of vertices of the B spline surface is greater than 1000. The quantitative variance of the approximation error in accordance with the change of decomposition levels needs to be further explored.

Evolutionary Computation for Realizing Distillation Separation Sequence Optimization Synthesis

Evolutionary algorithm is applied for distillation separation sequence optimization synthesis problems with combination explosion. The binary tree data structure is used to describe the distillation separation sequence, and it is directly applied as the coding method. Genetic operators, which ensure to prohibit illegal filial generations completely, are designed by using the method of graph theory. The crossover operator based on a single parent or two parents is designed successfully. The example shows that the average ratio of search space from evolutionary algorithm with two-parent genetic operation is lower, whereas the rate of successful minimizations from evolutionary algorithm with single parent genetic operation is higher.

Experimental Analysis of Dynamic Stiffness Coefficient of the New Mn-Cu Alloy Annular Parts

Based on excitation-resonance mass testing principle, a proper experiment testing system is designed for annular parts. The dynamics characters of the axis sleeve, which is made of a new Mn-Cu alloy and used as a vibration reductor in high acceleration rotary testing machine for fusee, is investigated. The relationship between stiffness coefficient and utilizing frequency is obtained, and the simplified dynamics model of crystal is established From the viewpoint of crystal microstructure of the Mn-Cu alloy, the experiment result is analyzed by the viscoelastic theory, and the characters of stress and strain in the condition of high frequency are discussed. The results indicate that the Mn-Cu alloy annular parts are fit to be used on the high accleration rotary testing machine for fusee.

Recognizing Expression Variant and Occluded Face Images Based on Nested HMM and Fuzzy Rule Based Approach

The face recognition with expression and occlusion variation becomes the greatest challenge in biometric applications to recognize people. The proposed work concentrates on recognizing occlusion and seven kinds of expression variations such as neutral, surprise, happy, sad, fear, disgust and angry. During enrollment process, principle component analysis (PCA) detects facial regions on the input image. The detected facial region is converted into fuzzy domain data to make decision during recognition process. The Haar wavelet transform extracts features from the detected facial regions. The Nested Hidden markov model is employed to train these features and each feature of face image is considered as states in a Markov chain to perform learning among the features. The maximum likelihood for the input image was estimated by using Baum Welch algorithm and these features were kept on database. During recognition process, the expression and occlusion varied face image is taken as the test image and maximum likelihood for test image is found by following same procedure done in enrollment process. The matching score between maximum likelihood of input image and test image is computed and it is utilized by fuzzy rule based method to decide whether the test image belongs to authorized or unauthorized. The proposed work was tested among several expression varied and occluded face images of JAFFE and AR datasets respectively.