基于重力异常场特征的区域构造分析研究

重力异常场作为一种反映地下物质密度变化的物理场,可以在区域构造研究中发挥重要作用。本文首先对重力异常场的基本原理、测量方法、数据处理方法及特性进行了分析和总结。接着探讨了区域构造研究的特点与局限性,以及未来的发展方向。在此基础上,提出了基于重力异常场特征的区域构造研究方法,包括重力异常场的基本特征与信息提取方法,基于重力异常场特征的区域构造分析方法,以及区域构造分析方法的优化与改进。最后,通过介绍重力异常场在断裂带与隆起带研究、地下水资源与油气勘探中的应用,阐述了重力异常场在区域构造研究中的实际应用价值。

Study on Support Vector Machine Based on 1-Norm

The model of optimization problem for Support Vector Machine(SVM) is provided, which based on the definitions of the dual norm and the distance between a point and its projection onto a given plane. The model of improved Support Vector Machine based on 1-norm(1-SVM) is provided from the optimization problem, yet it is a discrete programming. With the smoothing technique and optimality knowledge, the discrete programming is changed into a continuous programming. Experimental results show that the algorithm is easy to implement and this method can select and suppress the problem features more efficiently. Illustrative examples show that the 1-SVM deal with the linear or nonlinear classification well.

HRM and Quantitatives： Decision Tree and Vector Analysis in HRM Theory

Research topic of this paper is to discuss theory of Human Resources Management （HRM） and to discuss using of quantitative methods in HRM. Firstly, five variables establish HRM theory. They are HRM practices, positive organizational behaviors, individual performance, performance of business departments, and firm performance. Transactions among those variables enable Human Resources （HR） practitioners to apply HRM theory in their organizations. Secondly, this paper discusses use of quantitative methods in HRM. They are vector analysis and decision tree analysis. Those analyses enable HR practitioners to make effective HR decisions. Decision tree sets HR alternatives to efficiently implement HRM practices in organizations. Research question is how HR practitioners apply quantitative methods in department of HRM in firms. Finally this research comes out a conclusion that quantitative methods may be used in HRM.

KERNEL NEIGHBORHOOD PRESERVING EMBEDDING FOR CLASSIFICATION

The Neighborhood Preserving Embedding(NPE) algorithm is recently proposed as a new dimensionality reduction method.However, it is confined to linear transforms in the data space.For this, based on the NPE algorithm, a new nonlinear dimensionality reduction method is proposed, which can preserve the local structures of the data in the feature space.First, combined with the Mercer kernel, the solution to the weight matrix in the feature space is gotten and then the corresponding eigenvalue problem of the Kernel NPE(KNPE) method is deduced.Finally, the KNPE algorithm is resolved through a transformed optimization problem and QR decomposition.The experimental results on three real-world data sets show that the new method is better than NPE, Kernel PCA(KPCA) and Kernel LDA(KLDA) in performance.

The modulation recognition based on decision-making mechanism and neural network integrated classifier

A neural network integrated classifier(NNIC) designed with a new modulation recognition algorithm based on the decision-making tree is proposed in this paper.Firstly,instantaneous parameters are extracted in the time domain by the coordinated rotation digital computer(CORDIC) algorithm based on the extended convergence domain and feature parameters of frequency spectrum and power spectrum are extracted by the time-frequency analysis method.All pattern identification parameters are calculated under the I/Q orthogonal two-channel structure,and constructed into the feature vector set.Next,the classifier is designed according to the modulation pattern and recognition performance of the feature parameter set,the optimum threshold is selected for each feature parameter based on the decision-making mechanism in a single classifier,multi-source information fusion and modulation recognition are realized based on feature parameter judge process in the NNIC.Simulation results show NNIC is competent for all modulation recognitions,8 kinds of digital modulated signals are effectively identified,which shows the recognition rate and anti-interference capability at low SNR are improved greatly,the overall recognition rate can reach 100%when SNR is12dB.

Optimum mining method selection using fuzzy analytical hierarchy process–Qapiliq salt mine,Iran

Mining method selection is the first and the most critical problem in mine design and depends on some parameters such as geotechnical and geological features and economic and geographic factors. In this paper, the factors affecting mining method selection are determined. These factors include shape, thick- ness, depth, slope, RMR and RSS of the orebody, RMR and RSS of the hanging wall and footwall. Then, the priorities of these factors are calculated. In order to calculate the priorities of factors and select the best mining method for Qapiliq salt mine, Iran, based on these priorities, fuzzy analytical hierarchy process （AHP） technique is used. For this purpose, a questionnaire was prepared and was given to the associated experts. Finally, after a comparison carried out based on the effective factors, between the four mining methods including area mining, room and pillar, cut and fill and stope and pillar methods, the stope and nillar mining method was selected as the most suitable method to this mine.

Application of Wavelet Packet Energy Spectrum to Extract the Feature of the Pulse Signal

The wavelet packet is presented as a new kind of multiscale analysis technique followed by Wavelet analysis. The fundamental and realization arithmetic of the wavelet packet analysis method are described in this paper. A new application approach of the wavelet packed method to extract the feature of the pulse signal from energy distributing angle is expatiated. It is convenient for the microchip to process and judge by using the wavelet packet analysis method to make the pulse signals quantized and analyzed. Kinds of experiments are simulated in the lab, and the experiments prove that it is a convenient and accurate method to extract the feature of the pulse signal based on wavelet packed-energy spectrumanalysis.

The Research of Fractal Characteristics of the Electrocardiogram in a Real Time Mode

The article presents the results of recent investigations into Holter monitoring of ECG, using non-linear analysis methods. This paper discusses one of the modern methods of time series analysis--a method of deterministic chaos theory. It involves the transition from study of the characteristics of the signal to the investigation of metric （and probabilistic） properties of the reconstructed attractor of the signal. It is shown that one of the most precise characteristics of the functional state of biological systems is the dynamical trend of correlation dimension and entropy of the reconstructed attractor. On the basis of this it is suggested that a complex programming apparatus be created for calculating these characteristics on line. A similar programming product is being created now with the support of RFBR. The first results of the working program, its adjustment, and further development, are also considered in the article.

Fault Feature Extraction of Rotating Machinery Based on Wavelet Transformation and Multi-resolution Analysis

This paper expounded in detail the principle of energy spectrum analysis based on discrete wavelet transformation and multiresolution analysis. In the aspect of feature extraction method study, with investigating the feature of impact factor in vibration signals and considering the non-placidity and non-linear of vibration diagnosis signals, the authors import wavelet analysis and fractal theory as the tools of faulty signal feature description. Experimental results proved the validity of this method. To some extent, this method provides a good approach of resolving the wholesome problem of fault feature symptom description.

A CHARACTERISTIC SET METHOD FOR SOLVING BOOLEAN EQUATIONS AND APPLICATIONS IN CRYPTANALYSIS OF STREAM CIPHERS

This paper presents a characteristic more efficient and has better properties than the set method for solving Boolean equations, which is general characteristic set method. In particular, the authors give a disjoint and monic zero decomposition algorithm for the zero set of a Boolean equation system and an explicit formula for the number of solutions of a Boolean equation system. The authors also prove that a characteristic set can be computed with a polynomial number of multiplications of Boolean polynomials in terms of the number of variables. As experiments, the proposed method is used to solve equations from cryptanalysis of a class of stream ciphers based on nonlinear filter generators. Extensive experiments show that the method is quite effective.

A POSTERIORI ERROR ANALYSIS OF NONCONFORMING METHODS FOR THE EIGENVALUE PROBLEM

This paper extends the unifying theory for a posteriori error analysis of the nonconformingfinite element methods to the second order elliptic eigenvalue problem.In particular,the authorproposes the a posteriori error estimator for nonconforming methods of the eigenvalue problems andprove its reliability and efficiency based on two assumptions concerning both the weak continuity andthe weak orthogonality of the nonconforming finite element spaces,respectively.In addition,the authorexamines these two assumptions for those nonconforming methods checked in literature for the Laplace,Stokes,and the linear elasticity problems.

Optimization of cross angle based on the pumping dynamics model

The single cylinder and multi-cylinder pumping dynamics model of a swash plate piston pump were improved.Particular attention has been paid to the design influences of key parts of the valve plate such as relief groove,pre-compression/ expansion and fluid inertia effect of the unsteady flow.Some important parameters,such as the discharge area,discharge coefficient,fluid bulk modulus,were especially analyzed using numerical methods or by experiment-based estimation.Consequently,the mathematical results of pressure pulsation and flow ripple agree well with experimental results from the test-rig of the flow ripple.Therefore,the cross angle and the pre-compression angle of the valve plate was optimized,based on the pumping dynamics model.Considering both the flow ripple and the cylinder pressure of the pump,the cross angle is set to be 2.2° to 2.7° with a pre-compression angle of 1.7° to 2.2°,so the pumping dynamics character can obtain the best result.

On the economic analysis paradigm of historical materialism

The economic analysis paradigm of historical materialism is marked by a basic framework that embodies the distinctive features of historical materialism. As a consciously applied scientific method of analysis it is a reflection in the mind of the objective dialectics of the economic realm, consisting of applying the analytical fimctions of Marxist economic categories and principles and grasping the dialectical elements in the analytical approach of historical materialism. Compared with the analytical method of Western economics, the economic analytical method of historical materialism is markedly more scientific and advantageous. It is innovative in theoretical terms due to the scientific nature of historical materialism.