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.

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.

Establishment of Constitutive Model of Silicone Rubber Foams Based on Statistical Theory of Rubber Elasticity

In this study, a constitutive model based on microscopic physical mechanism of silicone rubber foams was established. A theoretical statistical model of rubber elasticity considering the effect of dangling chains was modified to build this model. When a strain amplification factor （X） was introduced, the theoretical model could fit the tensile stress-strain data of mono- and bi-modal foam matrix well （Adj. R-Square = 0.9989, 0.9983）. Parameters related to the polymer network, namely, average molecular weight （Me） and volume fraction （Ф） of chain segments between adjacent cross-linking points （network strands）, were calculated by probabilistic method from the number-average molecular weight （Mn）, vinyl content （wvi） of the primary polysiloxanes and percent conversion （q） of vinyl groups. The primary and infinite strain amplification factors （X0, X∞） and decay exponent （z）, introduced by X and related to the nanoparticles, were obtained by fitting. Inspired by the fact that the actual strain of matrix was lower than that of the foams＇, we introduced another item, strain hysteresis item （H, related with the foam porosity and cell structure）, into the statistical model as well. With the same above values of Mc, Ф, X0 and X∞, the model could also fit the compressive stress-strain data of mono- and bi-modal foams well （Adj. R-Square = 0.9948, 0.9985）. Interestingly, the strain hysteresis items of the mono- and bi-modal foams almost completely coincided under all experimental strains, which may be attributed to the almost equal porosity and similar cell structure of the two foams. This constitutive model may connect the macroscopic stress-strain behaviour to the parameters of microscopic molecular structures, promisingly providing a basis for the performance improvement and optimization of silicone rubber foams.

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.

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.

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).

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.

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.

New Statistical Theory and a k-ε-PDF Model for Simulating Gas-particle Flows

A k ε PDF (probability density function) model based on a statistical theory for turbulent gas particle flows is proposed, and a numerical procedure combining the finite difference and finite fluctuating velocity group methods is used. The obtained statistically averaged equations have the same form as that of the equations obtained by the Reynolds averaging. Using the k ε PDF model (PDF particle turbulence model combined with k ε gas turbulence model), many terms, such as the diffusion term in particle Reynolds stress equations, can be exactly calculated for verifying the second order moment model. The k ε PDF model is used to simulate gas particle flows behind a backward facing step. Comparison of the predictions using both k ε PDF and the k ε k p models with experimental results shows that the k ε PDF model gives more reasonable nonisotropic features of particle turbulence.

Fatigue life of metal treated by magnetic field

This paper investigates theoretically the influence of magnetization on fatigue life by using non-equilibrium statistical theory of fatigue fracture for metals. The fatigue microcrack growth rate is obtained from the dynamic equation of microcrack growth, where the influence of magnetization is described by an additional term in the potential energy of microcrack. The statistical value of fatigue life of metal under magnetic field is derived, which is expressed in terms of magnetic field and macrophysical as well as microphysical quantities. The fatigue life of AISI 4140 steel in static magnetic field from this theory is basically consistent with the experimental data.

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.

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.

Quantifying Likelihood in Digital Forensic Investigations

While the conventional forensic scientists routinely validate and express the results of their investigations quantitatively using statistical measures from probability theory,digital forensics examiners rarely if ever do so.In this paper,we review some of the quantitative tools and techniques which are available for use in digital forensic investigations,including Bayesian networks,complexity theory,information theory and probability theory,and indicate how they may be used to obtain likelihood ratios or odds ratios for the relative plausibility of alternative explanations for the creation of the recovered digital evidence.The potential benefits of such quantitative measures for modern digital forensics are also outlined.

Estimating Military Aircraft Cost Using Least Squares Support Vector Machines

A multi-layer adaptive optimizing parameters algorithm is developed forimproving least squares support vector machines (LS-SVM) , and a military aircraft life-cycle-cost(LCC) intelligent estimation model is proposed based on the improved LS-SVM. The intelligent costestimation process is divided into three steps in the model. In the first step, a cost-drive-factorneeds to be selected, which is significant for cost estimation. In the second step, militaryaircraft training samples within costs and cost-drive-factor set are obtained by the LS-SVM. Thenthe model can be used for new type aircraft cost estimation. Chinese military aircraft costs areestimated in the paper. The results show that the estimated costs by the new model are closer to thetrue costs than that of the traditionally used methods.

Compression method based on training dataset of SVM

The method to compress the training dataset of Support Vector Machine （SVM） based on the character of the Support Vector Machine is proposed. First, the distance between the unit in two training datasets, and then the samples that keep away from hyper-plane are discarded in order to compress the training dataset. The time spent in training SVM with the training dataset compressed by the method is shortened obviously. The result of the experiment shows that the algorithm is effective.

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.

REVERSE MODELING FOR CONIC BLENDING FEATURE

A novel method to extract conic blending feature in reverse engineering is presented. Different from the methods to recover constant and variable radius blends from unorganized points, it contains not only novel segmentation and feature recognition techniques, but also bias corrected technique to capture more reliable distribution of feature parameters along the spine curve. The segmentation depending on point classification separates the points in the conic blend region from the input point cloud. The available feature parameters of the cross-sectional curves are extracted with the processes of slicing point clouds with planes, conic curve fitting, and parameters estimation and compensation, The extracted parameters and its distribution laws are refined according to statistic theory such as regression analysis and hypothesis test. The proposed method can accurately capture the original design intentions and conveniently guide the reverse modeling process. Application examples are presented to verify the high precision and stability of the proposed method.

Statistics of Evolving Populations and Their Relevance to Flood Risk

Statistical methods are commonly used to evaluate natural populations and environmental variables, yet these must recognize temporal trends in population character to be appropriate in an evolving world. New equations presented here define the statistical measures of aggregate historical populations affected by linear changes in population means and standard deviations. These can be used to extract the statistical character of present-day populations, needed to define modern variability and risk, from tables of historical data that are dominated by measurements made when conditions were different. As an example, many factors such as climate change and in-channel structures are causing flood levels to rise, so realistic estimation of future flood levels must take such secular changes into account. The new equations provide estimates of water levels for ＂100-year＂ floods in the USA Midwest that are 0.5 to 2 m higher than official calculations that routinely assume population stationarity. These equations also show that flood levels will continue to rise by several centimeters per year. This rate is nearly ten times faster than the rise of sea level, and thus represents one of the fastest and most damaging rates of change that is documented by robust data.