Integration of Ideological and Political Education into the Probability Theory and Mathematical Statistics Course:A Teaching Design Based on Estimation and Hypothesis Testing

With the rapid development of higher education in China,colleges and universities are facing new challenges and impacts in talent training.Probability Theory and Mathematical Statistics is one of the important courses in higher education for science and engineering majors and economics and management majors.Its critical role in cultivating students’thinking skills and improving their problem-solving skills is self-evident.Course ideological and political education construction is an important link in college talent training work.Combining ideological and political education with course teaching can help students establish correct value concepts and play a certain role in improving their comprehensive ability and quality.At present,the construction of ideological and political education in the Probability Theory and Mathematical Statistics course still faces some problems,mainly manifested in the lack of attention paid by teachers to course ideological and political education,insufficient exploitation of ideological and political elements,and the simplification of ideological and political education implementation methods.In order to comprehensively deepen the construction of course ideological and political education in line with the actual needs of Probability Theory and Mathematical Statistics course teaching,we should strengthen the construction of teacher teams,improve teachers’ability to carry out course ideological and political education,integrate educational resources,develop educational resources for ideological and political education,and innovate teaching methods to improve the overall effect of ideological and political education integration.

Theoretical analysis of the double-differential cross-sections of neutron,proton,deuteron,^(3)He,andαfor the p+^(6) Li reaction

Based on the unified Hauser–Feshbach and exciton model,which can describe the particle emission processes between discrete energy levels with energy,angular momentum,and parity conservations,a statistical theory of light nucleus reaction(STLN)is developed to calculate the double-differential cross-sections of the outgoing neutron and light charged particles for the proton-induced^(6) Li reaction.A significant difference is observed between the p+^(6) Li and p+^(7) Li reactions owing to the discrepancies in the energy-level structures of the targets.The reaction channels,including sequential and simultaneous emission processes,are analyzed in detail.Taking the double-differential cross-sections of the outgoing proton as an example,the influence of contaminations(such as^(1) H,^(7)Li,^(12)C,and^(16)O)on the target is identified in terms of the kinetic energy of the first emitted particles.The optical potential parameters of the proton are obtained by fitting the elastic scattering differential cross-sections.The calculated total double-differential cross-sections of the outgoing proton and deuteron at E_(p)=14 MeV agree well with the experimental data for different outgoing angles.Simultaneously,the mixed double differential cross-sections of^(3) He andαare in good agreement with the measurements.The agreement between the measured data and calculated results indicates that the two-body and three-body breakup reactions need to be considered,and the pre-equilibrium reaction mechanism dominates the reaction processes.Based on the STLN model,a PLUNF code for the p+^(6) Li reaction is developed to obtain an ENDF-6-formatted file of the double-differential cross-sections of the nucleon and light composite charged particles.

Nonequilibrium Statistical Theory of Fracture

Nonequilibrium statistical theory of fracture is a theory of fracture that macromechanical quantities can be derived from the microscopic atomic mechanism of microcrack(or microvoid)evolution kinetcs by means of nonequilibrium statistical physical concepts and methods. The microcrack evolution equation is the central equation in the theory.The coefficents of the equation, the microcrack growth rate and the microcrack nucleation rate,come from microscopic atomic mechanism.The solution of the equation connects with macromechanical quantities by the model of the weakest chain. All the other formulas and quantities, for instance, distribution function,fracture probability, reliability, failure rate and macromechanical quantities such as strength, toughness, life etc. and their statistical distribution function and statistical fluctuation are derived in a unified fashion and expressed by a few physical parameters. This theory can be widely applied to various kinds of fracture, such as the brittle, fatigue, delayed and environmental fracture of metals and structural ceramics. The theoretical framework of this theory is given in this paper.

Correlation of ^1H NMR Chemical Shift for Aqueous Solutions by Statistical Associating Fluid Theory Association Model

1H NMR chemical shifts of binary aqueous mixtures of acylamide, alcohol, dimethyl sulphoxide (DMSO), and acetone are correlated by statistical associating fluid theory (SAFT) association model. The comparison between SAPT association model and Wilson equation shows that the former is better for dealing with aqueous solutions. Finally, the specialties of both models are discussed.

Construction of a Comprehensive Soundscape Evaluation System in Forest Parks Based on Grey Statistical Theory

Based on collection and arrangement of evaluation indicators of soundscape in a forest park,24 primary evaluation indicators are chosen by grey statistical theory.The results show that there are 5 main factors influencing soundscape in a forest park,including water soundscape,wind soundscape,animal soundscape,recreation soundscape,and artificial soundscape,which contain 13 evaluation indicators.Among these factors,natural sound elements account for 84.6%.Thus a comprehensive evaluation indicator system of soundscape(including natural and unnatural soundscape) in a forest park is constructed by the selected evaluation indicators,and it is expected to provide a reference for scientific and systematic construction and development of forest parks in future.

SOME ISSUES OF TURBULENCE STATISTICS

The issue of dropping the random force f(i) and the arbitrariness of choosing the basic variable in the variational approach to turbulence closure problem, pointed out recently by the Russian scientists Bazdenkov and Kukharkin, are discussed. According to the mean-square estimation method, the random force f(i) should be dropped in the error expression of the LFP (Langevin-Fokker-Planck) model. However, f(i) is not neglected, its effect has been taken into account by the variational approach. In order to optimize the perturbation solution of the Liouville equation, the LFP model requires that the basic variable is as near to Gaussian as possible. Hence, the velocity, instead of the vorticity, should be chosen as the basic variable in the three-dimensional turbulence. Although the LFP model and the zero-order Gaussian term of PDF (probability density function) imply whiteness assumption (zero correlation time of f(i)), the higher-order non-Gaussian terms of PDF correspond to the nonwhiteness of turbulence dynamics, the variational approach does calculate the nonwhiteness effect properly.

Non-equilibrium statistical theory about microscopic fatigue cracks of metal in magnetic field

This paper develops the non-equilibrium statistical fatigue damage theory to study the statistical behaviour of micro-crack for metals in magnetic field. The one-dimensional homogeneous crack system is chosen for study. To investigate the effect caused by magnetic field on the statistical distribution of micro-crack in the system, the theoretical analysis on microcrack evolution equation, the average length of micro-crack, density distribution function of microcrack and fatigue fracture probability have been performed. The derived results relate the changes of some quantities, such as average length, density distribution function and fatigue fracture probability, to the applied magnetic field, the magnetic and mechanical properties of metals. It gives a theoretical explanation on the change of fatigue damage due to magnetic fields observed by experiments, and presents an analytic approach on studying the fatigue damage of metal in magnetic field.

Calculation of the Canonical Rate Constant for the Nonadiabatic Trapping Model Based on Unified Statistical Theory:A Test on The Exchange Reaction H_2+H

A new approach was employed to calculate the canonical (thermal) rate constant basedon unified statistical theory. All information for the calculation was obtained from ab initio meth-ods. The flux integral for any point of reaction coordinate was calculated by counting the numberof quantum states and applied to determine the dividing surfaces along the intrinsic reaction coor-dinate (IRC). The classical exchange reaction H2+H, as an example, was investigated. The IRC forthe reaction has been traced and detailed information of IRC was carried out at the QCISD/6-311 G** level .The calculated rate constants are well consistent with the experimental results.

Nonequilibrium Statistical Modeling of Fatigue Crack Growth Behaviour

In order to study the influence of microstructural texture on the growth of short fatigue cracks in metals, the nonequilibrium statistical theory of fatigue fracture correlating a microscopic mechanism with the macroscopic properties is modified to take into consideration the microstructural features of a material, thereby allowing a rationalisation of the experimental data of short fatigue crack growth and long fatigue crack growth. The nonequilibrium statistical theory thus developed relates the growth of cracks with a dislocation mechanism to simulate short fatigue crack growth with the long fatigue crack growth behaviour and predicts the fatigue crack growth rates throughout the fatigue lifetime. The results is finally compared with that of other fatigue theories.

Time series online prediction algorithm based on least squares support vector machine

Deficiencies of applying the traditional least squares support vector machine （LS-SVM） to time series online prediction were specified. According to the kernel function matrix＇s property and using the recursive calculation of block matrix, a new time series online prediction algorithm based on improved LS-SVM was proposed. The historical training results were fully utilized and the computing speed of LS-SVM was enhanced. Then, the improved algorithm was applied to timc series online prediction. Based on the operational data provided by the Northwest Power Grid of China, the method was used in the transient stability prediction of electric power system. The results show that, compared with the calculation time of the traditional LS-SVM（75 1 600 ms）, that of the proposed method in different time windows is 40-60 ms, proposed method is above 0.8. So the improved method is online prediction. and the prediction accuracy（normalized root mean squared error） of the better than the traditional LS-SVM and more suitable for time series online prediction.

A new decision tree learning algorithm

In order to improve the generalization ability of binary decision trees, a new learning algorithm, the MMDT algorithm, is presented. Based on statistical learning theory the generalization performance of binary decision trees is analyzed, and the assessment rule is proposed. Under the direction of the assessment rule, the MMDT algorithm is implemented. The algorithm maps training examples from an original space to a high dimension feature space, and constructs a decision tree in it. In the feature space, a new decision node splitting criterion, the max-min rule, is used, and the margin of each decision node is maximized using a support vector machine, to improve the generalization performance. Experimental results show that the new learning algorithm is much superior to others such as C4. 5 and OCI.

A Theoretical Study on Nonadiabatic Trapping Models of the Reaction NH+H←→N+H_2

The properties of nonadiabatic trapping models of the reaction NH+H -N+H, are investigated in a collinear model as \veil as a non-collinear thermal reaction on the basis of theintrinsic reaction coordinate (IRC) intbrmation obtained by ah initio calculations at QCISD/631 IG** ie\el. Using the unitied statistical theory fornonadiabatic trapping models. the thermal rateconstants over the temperature range of 2000-3000K are computed which are in excellent agreementwith the experiment results.

Estimating coal reserves using a support vector machine

The basic principles of the Support Vector Machine (SVM) are introduced in this paper. A specific process to establish an SVM prediction model is given. To improve the precision of coal reserve estimation, a support vector machine method, based on statistical learning theory, is put forward. The SVM model was trained and tested by using the existing exploration and exploitation data of Chencun mine of Yima bureau’s as the input data. Then coal reserves within a particular region were calculated. These calculated results and the actual results of the exploration block were compared. The maximum relative error was 10.85%, within the scope of acceptable error limits. The results show that the SVM coal reserve calculation method is reliable. This method is simple, practical and valuable.

A damage-based constitutive model for rock under impacting load

Using the Splitting Hopkinson Pressure Bar （SHPB） experimental system, investigations were made into the dynamic mechanical performances of underground soft rocks. The experiments proved that the measured stress-strain curves display the characteristics of plastic deformation. By making use of a revised overstress constitutive formula for the stress model and by taking into account that the strain rate and strain are a function of I - E（t）/Eo, a revised overstress constitutive formula for the stress model was simplified by applying dimensional analysis and consequently, a simplified overstress formula was obtained for the stress model. Then, by taking into consideration the effects of damage under a dynamic load on the dynamic loading strength of the rock, the continuous damage theory and the statistical strength theory were introduced into the development of the simplified overstress constitutive formula for the stress model. Hence, a damage-based constitutive formula for an overstress model, which can be appropriately applied to the analysis of full dynamic stress-strain curves, was developed. By using the simplified damage-based constitutive formula for an overstress model, the actually measured curves are fitted, indicating that the fitting curves and those actually measured are in good agreement.

SKEWNESS FACTOR OF TURBULENT VELOCITY DERIVATIVE

Using nonequilibrium statistical mechanics closure method, it is shown that the skewness factor of the velocity derivative of isotropic turbulence ap- proaches a constant -0.515 when the Reynolds number is very high, which is in agree- ment with the DNS (direct numerical simulation) result of Vincent and Meneguzzi (1991).

Support vector machine method for fore-casting future strong earthquakes in Chinese mainland

Statistical learning theory is for small-sample statistics. And support vector machine is a new machine learning method based on the statistical learning theory. The support vector machine not only has solved certain problems in many learning methods, such as small sample, over fitting, high dimension and local minimum, but also has a higher generalization （forecasting） ability than that of artificial neural networks. The strong earthquakes in Chinese mainland are related to a certain extent to the intensive seismicity along the main plate boundaries in the world, however, the relation is nonlinear. In the paper, we have studied this unclear relation by the support vector machine method for the purpose of forecasting strong earthquakes in Chinese mainland.

Support Vector Machine-Based Nonlinear System Modeling and Control

This paper provides an introduction to a support vector machine, a new kernel-based technique introduced in statistical learning theory and structural risk minimization, then presents a modeling-control framework based on SVM. At last a numerical experiment is taken to demonstrate the proposed approach's correctness and effectiveness.

Impact of the spatial coherence on self-interference digital holography

Owing to the unique feature that the signal and reference waves of self-interference digital holography(SIDH)contain the same spatial information from the same point of object,compared with conventional digital holography,the SIDH has the special spatial coherence properties.We present a statistical optics approach to analyzing the formation of cross-correlation image in SIDH.Our study reveals that the spatial coherence of illumination light can greatly influence the imaging characteristics of SIDH,and the impact extent of the spatial coherence depends substantially on the recording distance of hologram.The theoretical conclusions are supported well by numerical simulation and optical experiments.

Randomized Algorithms for Probabilistic Optimal Robust Performance Controller Design

Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach was given. The randomized algorithms here were based on a property from statistical learning theory known as (uniform) convergence of empirical means (UCEM). It is argued that in order to assess the performance of a controller as the plant varies over a pre-specified family, it is better to use the average performance of the controller as the objective function to be optimized, rather than its worst-case performance. The approach is illustrated to be efficient through an example.

Temperature and hydrogen-like impurity effects on the excited state of the strong coupling bound polaron in a CsI quantum pseudodot

With hydrogen-like impurity（HLI） located in the center of Cs I quantum pseudodot（QPD） and by using the variational method of Pekar type（VMPT）, we investigate the first-excited state energy（FESE）, excitation energy and transition frequency of the strongly-coupled bound polaron in the present paper. Temperature effects on bound polaron properties are calculated by employing the quantum statistical theory（QST）. According to the present work＇s numerical results, the FESE, excitation energy and transition frequency decay（amplify） with raising temperature in the regime of lower（higher）temperature. They are decreasing functions of Coulomb impurity potential strength.