确定裂陷盆地伸展量的分数维法

脆性断层群落的位移具有分数维特征，此特征可以用于建立一种裂陷盆地伸展量估算的新方法，即分数维法。这种方法可以用于确定在地震反射剖面上不可测定的小型断层之上滑移造成的伸展量大小，计算结果可以弥合不同计算方法之间的差异，阐明小型断层在区域裂陷作用变形过程中的重要意义。以二连断陷盆地群伸展量的确定为例，详细地介绍了这种方法的使用原理和步骤。

混凝土粘结面粗糙度测试方法研究

通过 30组混凝土立方体试块 ,分别对人工凿毛及劈拉试验试件的断开面两种类型分别采用自制量测仪法与灌砂法进行了粘结面粗糙度测试研究。给出了两种量测方法测试混凝土粘结面粗糙度回归公式且具有较好的相关性。该量测仪操作简单、使用方便、造价低 ,特别适合实际工程加固中混凝土粘结面粗糙度测量 ,为工程加固中提供了一种好的混凝土粘结面粗糙度测试方法。

Multi-Symplectic Splitting Method for Two-Dimensional Nonlinear Schrodinger Equation

Using the idea of splitting numerical methods and the multi-symplectic methods, we propose a multisymplectic splitting （MSS） method to solve the two-dimensional nonlinear Schrodinger equation （2D-NLSE） in this paper. It is further shown that the method constructed in this way preserve the global symplectieity exactly. Numerical experiments for the plane wave solution and singular solution of the 2D-NLSE show the accuracy and effectiveness of the proposed method.

Iterative Solution for Groundstate of H_2^+ Ion

To solve the wave functions and energies of the groundstate of H＋2 ion an iteration procedure for N- dimensional potentials is applied. The iterative solutions are convergent nicely, which are comparable to earlier results based on variational methods.

Chaos Existence in Surface Discharge of Tracking Test

Tracking tests for different polymer materials were carried out to investigate the chaotic behavior of surface discharge. The discharge sequences measured during the discharge process were analyzed for finding the evidence of chaos existence. Four kinds of nonlinear analysis methods were adopted： estimating the largest Lyapunov exponent, calculating the fractal dimension with increasing the embedding dimension, drawing the recurrence plots, and plotting the Poincare maps. It is found that the largest Lyapunov exponent of the discharge is positive, and the plot of fractal dimension, as a function of embedding dimension, will saturate at a value. The recur- rence plots show the chaotic frame-work patterns, and the Poincar6 maps also have the chaotic characteristics. The results indicate that the chaotic behavior does exist in the discharge currents of the tracking test.

Discriminant embedding by sparse representation and nonparametric discriminant analysis for face recognition

A novel supervised dimensionality reduction algorithm, named discriminant embedding by sparse representation and nonparametric discriminant analysis(DESN), was proposed for face recognition. Within the framework of DESN, the sparse local scatter and multi-class nonparametric between-class scatter were exploited for within-class compactness and between-class separability description, respectively. These descriptions, inspired by sparse representation theory and nonparametric technique, are more discriminative in dealing with complex-distributed data. Furthermore, DESN seeks for the optimal projection matrix by simultaneously maximizing the nonparametric between-class scatter and minimizing the sparse local scatter. The use of Fisher discriminant analysis further boosts the discriminating power of DESN. The proposed DESN was applied to data visualization and face recognition tasks, and was tested extensively on the Wine, ORL, Yale and Extended Yale B databases. Experimental results show that DESN is helpful to visualize the structure of high-dimensional data sets, and the average face recognition rate of DESN is about 9.4%, higher than that of other algorithms.

Iris Feature Extraction and Recognition Based on Fractal Dimension of Grayscale Extremums

This paper presented an individual recognition algorithm for human iris using fractal dimension of grayscale extremums for feature extraction.Firstly,iris region was localized from an eye image with modified circle detector stemmed from Daugman’s integro-differential operator.Then,segmentation was used to extract the iris and to exclude occlusion from eyelids and eyelashes.The extracted iris was normalized and mapped to polar coordinates for matching.In feature encoding,a new approach based on fractal dimension of grayscale extremums was designed to extract textural features of iris.Finally,a normalized correlation classifier was employed to determine the agreement of two iris feature templates,and the feature template was rotated left and right to avoid the interference from rotation of eyes and tilting of head.The experimental results show that fractal dimension of grayscale extremums can extract textural features from iris image effectively,and the proposed recognition algorithm is accurate and efficient.The proposed algorithm was tested on CASIA-IrisV3-Interval iris database and the performance was evaluated based on the analysis of both False Accept Rate(FAR)and False Reject Rate(FRR)curves.Experimental results show that the proposed iris recognition algorithm is effective and efficient.

3D Multiphase Piecewise Constant Level Set Method Based on Graph Cut Minimization

Segmentation of three-dimensional(3D) complicated structures is of great importance for many real applications.In this work we combine graph cut minimization method with a variant of the level set idea for 3D segmentation based on the Mumford-Shah model.Compared with the traditional approach for solving the Euler-Lagrange equation we do not need to solve any partial differential equations.Instead,the minimum cut on a special designed graph need to be computed.The method is tested on data with complicated structures.It is rather stable with respect to initial value and the algorithm is nearly parameter free.Experiments show that it can solve large problems much faster than traditional approaches.

Flow Label-Based TPv6 Packet Classification Algorithm with Dimension Reduction Capability

Traditional packet classification for IPv4 involves examining standard 5-tuple of a packet header, source address, destination address, source port, destination port and protocol. With introduction of IPv6 flow label field which entails labeling the packets belonging to the same flow, packet classification can be resolved based on 3 dimensions： flow label, source address and desti- nation address. In this paper, we propose a novel approach for the 3-tuple packet classification based on flow label. Besides, by introducing a conversion engine to covert the source-destination pairs to the compound address prefixes, we put forward an algorithm called Reducing Dimension （RD） with dimension reduction capability, which combines heuristic tree search with usage of buck- ets. And we also provide an improved version of RD, called Improved RD （IRD）, which uses two mechanisms： path compression and priority tag, to optimize the perforrmnce. To evaluate our algo- rithm, extensive experiraents have been conducted using a number of synthetically generated databas- es. For the memory consumption, the two pro- posed new algorithms only consumes around 3% of the existing algorithms when the number of ill- ters increases to 10 k. And for the average search time, the search time of the two proposed algo- rithms is more than four times faster than others when the number of filters is 10 k. The results show that the proposed algorithm works well and outperforms rmny typical existing algorithms with the dimension reduction capability.

3D stability analysis method of concave slope based on the Bishop method

In order to study the stability control mechanism of a concave slope with circular landslide, and remove the influence of differences in shape on slope stability, the limit analysis method of a simplified Bishop method was employed. The sliding body was divided into strips in a three-dimensional model, and the lateral earth pressure was put into mechanical analysis and the three-dimensional stability analysis methods applicable for circular sliding in concave slope were deduced. Based on geometric structure and the geological parameters of a concave slope, the influence rule of curvature radius and the top and bottom arch height on the concave slope stability were analyzed. The results show that the stability coefficient decreases after growth, first in the transition stage of slope shape from flat to concave, and it has been confirmed that there is a best size to make the slope stability factor reach a maximum. By contrast with average slope, the stability of a concave slope features a smaller range of ascension with slope height increase, which indicates that the enhancing effect of a concave slope is apparent only with lower slope heights.

Effect of Gravity on Collective Excitations of a Quasi Two-Dimensional Bose Einstein Condensate in an Anharmonic Trap

Abstract Using variational method, the wave function of a quasi two-dimensional Bose-Einstein Condensate in an anharmonic trap is analyzed and the influence of gravity on the eollective excitations is studied. It is found that the effect of gravity on the condensate has got crucial dependence on the anharmonieity of the trap.

Relationship between critical seismic acceleration coefficient and static factor of safety of 3D slopes

Many analytical methods have been adopted to estimate the slope stability by providing various stability numbers,e.g.static safety of factor(static FoS)or the critical seismic acceleration coefficient,while little attention has been given to the relationship between the slope stability numbers and the critical seismic acceleration coefficient.This study aims to investigate the relationship between the static FoS and the critical seismic acceleration coefficient of soil slopes in the framework of the upper-bound limit analysis.Based on the 3D rotational failure mechanism,the critical seismic acceleration coefficient using the pseudo-static method and the static FoS using the strength reduction technique are first determined.Then,the relationship between the static FoS and the critical seismic acceleration coefficient is presented under considering the slope angleβ,the frictional angleφ,and the dimensionless coefficients B/H and c/γH.Finally,a fitting formula between the static FoS and the critical seismic acceleration coefficient is proposed and validated by analytical and numerical results.

Analytical Investigation of Soliton Solutions to Three Quantum Zakharov-Kuznetsov Equations

In the present paper, the two-dimensional quantum Zakharov-Kuznetsov(QZK) equation, three-dimensional quantum Zakharov-Kuznetsov equation and the three-dimensional modified quantum Zakharov-Kuznetsov equation are analytically investigated for exact solutions using the modified extended tanh-expansion based method. A variety of new and important soliton solutions are obtained including the dark soliton solution, singular soliton solution, combined dark-singular soliton solution and many other trigonometric function solutions. The used method is implemented on the Mathematica software for the computations as well as the graphical illustrations.

CLASSIFICATION OF AF-ALGEBRAS AND THEIR DIMENSION GROUPS

This paper gives the intrinsic character of the classification for AF-algebras defined by J.Cuntz and G. K. Pedersen in terms of their dimension groups.

Influences of Fractal Substrate Structures on Dynamic Scaling Behaviors of Etching Model

The Etching model on various fractal substrates embedded in two dimensions was investigated by means of kinetic Mento Carlo method in order to determine the relationship between dynamic scaling exponents and fractal parameters. The fractal dimensions are from 1.465 to 1.893, and the random walk exponents are from 2.101 to 2.578.It is found that the dynamic behaviors on fractal lattices are more complex than those on integer dimensions. The roughness exponent increases with the increasing of the random walk exponent on the fractal substrates but shows a non-monotonic relation with respect to the fractal dimension. No monotonic change is observed in the growth exponent.

The four dimensional variational data assimilation with multiple regularization parameters as a weak constraint(Tikh-4D-Var) and its preliminary application on typhoon initialization

Traditional variational data assimilation （VDA） with only one regularization parameter constraint cannot produce optimal error tuning for all observations. In this paper, a new data assimilation method of ＂four dimensional variational data assimilation （4D-Var） with multiple regularization parameters as a weak constraint （Tikh-4D-Var）＂ is proposed by imposing different reg- ularization parameters for different observations. Meanwhile, a new multiple regularization parameters selection method, which is suitable for actual high-dimensional data assimilation system, is proposed based on the posterior information of 4D-Var system. Compared with the traditional single regularization parameter selection method, computation of the proposed multiple regularization parameters selection method is smaller. Based on WRF3.3.1 4D-Vat data assimilation system, initiali- zation and simulation of typhoon Chaba （2010） with the new Tikh-4D-Var method are compared with its counterpart 4D-Var to demonstrate the effectiveness of the new method. Results show that the new Tikh-4D-Var method can accelerate the con vergence with less iterations. Moreover, compared with 4D-Var method, the typhoon track, intensity （including center surface pressure and maximum wind speed） and structure prediction are obviously improved with Tikh-4D-Var method for 72-h pre- diction. In addition, the accuracy of the observation error variances can be reflected by the multiple regularization parameters.

Fractal characteristics of far-field diffraction patterns for two-dimensional Thue-Morse quasicrystals

We report a numerical method to analyze the fractal characteristics of far-field diffraction patterns for two-dimensional Thue-Morse (2-D TM) structures. The far-field diffraction patterns of the 2-D TM structures can be obtained by the numerical method, and they have a good agreement with the experimental ones. The analysis shows that the fractal characteristics of far-field diffraction patterns for the 2-D TM structures are determined by the inflation rule, which have potential applications in the design of optical diffraction devices.

Approximate Solutions of Nonlinear Fractional Kolmogorov-Petrovskii-Piskunov Equations Using an Enhanced Algorithm of the Generalized Two-Dimensional Differential Transform Method

By constructing the iterative formula with a so-called convergence-control parameter, the generalized two-dimensional differential transform method is improved. With the enhanced technique, the nonlinear fractional Kolmogorov-Petrovskii-Piskunov equations are dealt analytically and approximate solutions are derived. The results show that the employed approach is a promising tool for solving many nonlinear fractional partial differential equations. The algorithm described in this work is expected to be employed to solve more problems in fractional calculus.

Self-similar fractals: An algorithmic point of view

This paper studies the self-similar fractals with overlaps from an algorithmic point of view.A decidable problem is a question such that there is an algorithm to answer"yes"or"no"to the question for every possible input.For a classical class of self-similar sets{E b.d}b,d where E b.d=Sn i=1(E b,d/d+b i)with b=(b1,...,b n)∈Qn and d∈N∩[n,∞),we prove that the following problems on the class are decidable:To test if the Hausdorff dimension of a given self-similar set is equal to its similarity dimension,and to test if a given self-similar set satisfies the open set condition(or the strong separation condition).In fact,based on graph algorithm,there are polynomial time algorithms for the above decidable problem.