Superconvergence of Direct Discontinuous Galerkin Methods:Eigen-structure Analysis Based on Fourier Approach

This paper investigates superconvergence properties of the direct discontinuous Galerkin(DDG)method with interface corrections and the symmetric DDG method for diffusion equations.We apply the Fourier analysis technique to symbolically compute eigenvalues and eigenvectors of the amplification matrices for both DDG methods with different coefficient settings in the numerical fluxes.Based on the eigen-structure analysis,we carry out error estimates of the DDG solutions,which can be decomposed into three parts:(i)dissipation errors of the physically relevant eigenvalue,which grow linearly with the time and are of order 2k for P^(k)(k=2,3)approximations;(ii)projection error from a special projection of the exact solution,which is decreasing over the time and is related to the eigenvector corresponding to the physically relevant eigenvalue;(iii)dissipative errors of non-physically relevant eigenvalues,which decay exponentially with respect to the spatial mesh sizeΔx.We observe that the errors are sensitive to the choice of the numerical flux coefficient for even degree P^(2)approximations,but are not for odd degree P^(3)approximations.Numerical experiments are provided to verify the theoretical results.

A Novel CCA-NMF Whitening Method for Practical Machine Learning Based Underwater Direction of Arrival Estimation

Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based DOA estimation methods trained on simulated Gaussian noised array data cannot be directly applied to actual underwater DOA estimation tasks.In order to deal with this problem,environmental data with no target echoes can be employed to analyze the non-Gaussian components.Then,the obtained information about non-Gaussian components can be used to whiten the array data.Based on these considerations,a novel practical sonar array whitening method was proposed.Specifically,based on a weak assumption that the non-Gaussian components in adjacent patches with and without target echoes are almost the same,canonical cor-relation analysis(CCA)and non-negative matrix factorization(NMF)techniques are employed for whitening the array data.With the whitened array data,machine learning based DOA estimation models trained on simulated Gaussian noised datasets can be used to perform underwater DOA estimation tasks.Experimental results illustrated that,using actual underwater datasets for testing with known machine learning based DOA estimation models,accurate and robust DOA estimation performance can be achieved by using the proposed whitening method in different underwater con-ditions.

Energy Theft Detection in Smart Grids:Taxonomy,Comparative Analysis,Challenges,and Future Research Directions

Electricity theft is one of the major issues in developing countries which is affecting their economy badly.Especially with the introduction of emerging technologies,this issue became more complicated.Though many new energy theft detection(ETD)techniques have been proposed by utilising different data mining(DM)techniques,state&network(S&N)based techniques,and game theory(GT)techniques.Here,a detailed survey is presented where many state-of-the-art ETD techniques are studied and analysed for their strengths and limitations.Three levels of taxonomy are presented to classify state-of-the-art ETD techniques.Different types and ways of energy theft and their consequences are studied and summarised and different parameters to benchmark the performance of proposed techniques are extracted from literature.The challenges of different ETD techniques and their mitigation are suggested for future work.It is observed that the literature on ETD lacks knowledge management techniques that can be more effective,not only for ETD but also for theft tracking.This can help in the prevention of energy theft,in the future,as well as for ETD.

Direction navigability analysis of geomagnetic field based on Gabor filter

Direction navigability analysis is a supplement to the navigability analysis theory, in which extraction of the direction suitable-matching features(DSMFs) determines the evaluation performance. A method based on the Gabor filter is proposed to estimate the direction navigability of the geomagnetic field. First,the DSMFs are extracted based on the Gabor filter’s responses.Second, in the view of pattern recognition, the classification accuracy in fault diagnosis is introduced as the objective function of the hybrid particle swarm optimization(HPSO) algorithm to optimize the Gabor filter’s parameters. With its guidance, the DSMFs are extracted. Finally, a direction navigability analysis model is established with the support vector machine(SVM), and the performances of the models under different objective functions are discussed. Simulation results show the parameters of the Gabor filter have a significant influence on the DSMFs, which, in turn, affects the analysis results of direction navigability. Moreover, the risk of misclassification can be effectively reduced by using the analysis model with optimal Gabor filter parameters. The proposed method is not restricted in geomagnetic navigation, and it also can be used in other fields such as terrain matching and gravity navigation.

Fast Tensor Principal Component Analysis via Proximal Alternating Direction Method with Vectorized Technique

This paper studies the problem of tensor principal component analysis (PCA). Usually the tensor PCA is viewed as a low-rank matrix completion problem via matrix factorization technique, and nuclear norm is used as a convex approximation of the rank operator under mild condition. However, most nuclear norm minimization approaches are based on SVD operations. Given a matrix , the time complexity of SVD operation is O(mn2), which brings prohibitive computational complexity in large-scale problems. In this paper, an efficient and scalable algorithm for tensor principal component analysis is proposed which is called Linearized Alternating Direction Method with Vectorized technique for Tensor Principal Component Analysis (LADMVTPCA). Different from traditional matrix factorization methods, LADMVTPCA utilizes the vectorized technique to formulate the tensor as an outer product of vectors, which greatly improves the computational efficacy compared to matrix factorization method. In the experiment part, synthetic tensor data with different orders are used to empirically evaluate the proposed algorithm LADMVTPCA. Results have shown that LADMVTPCA outperforms matrix factorization based method.

Stress Analysis of Buried Pipeline Installed by Horizontal Directional Drilling Using ANSYS Finite Element Software

In designing a horizontal directional drilling (HDD) pipeline project, designers face the challenge of determining the regions of maximum and minimum stresses on pipelines, ensuring the stability of the bore-hole from collapse and minimizing the stresses induced on the pipeline due to the bore-profile. This study analyses the stress induced on an HDD pipeline system using the ANSYS Version 18, mechanical APDL finite element (FE) software. The pipeline used as the case study was a gas transmission pipeline installed in south-west Nigeria. A macro-file for ANSYS Version 18, mechanical APDL used to model the pipeline was developed. The results showed that the maximum and minimum stresses induced on the HDD pipeline were at the top and bottom of the pipe, respectively;while the stresses on the sides were uniform (≈888 kg/cm2) all through the pipeline, irrespective of element number. The maximum stress occurred at the curvature point with the highest entry angle (10°), resulting in a maximum deflection at this point. The model stress validation performed by comparing results with theoretical solutions, both with respect to radius of curvature and internal pressure, showed percentage difference (errors) less than 10%. The cross sectional area validation showed a percentage difference of 0.059%.

Research on the Drawing-up of the Pole Figure for Orientation Analysis of Directional Si Steel Sheet

The magnetic property of soft magnetic metals and alloys depends strongly on the crystallo-graphic orientation. In automated equipment for orientation research, the intensity for drawing up the pole figure is measured in detail. The present research shows that the accurate pole figure can be drawn up without measuring concretely the intensity. For directional Si steel sheet the measuring step may be 4～5 degrees. In this paper the experimental equation for defo-cusing correction was derived from the experimental data in different specimens with random orientation.

Directional Analysis of the Chaotic Superlattice around the Equilibrium Point in the Phase Space

The recently proposed method of our research group named as directional Lyapunov exponents（DLEs） is presented. Then, DLEs are used to analyze the eigenstructure of the output phase space around the equilibrium points. Finally, the impacts of the superlattice parameter changes on the characteristics of the output chaotic signal are analyzed. The experimental results show that parameter changes of the superlattice will affect the eigenstructure around the equilibrium points in the output phase space, and DLEs are sensitive to these changes.

MoM Analysis and Design of a Compact Coaxial-to-Microstrip Directional Coupler

In order to overcome the main drawbacks of coaxial, waveguide, and stripline couplers, the analysis and the design of a compact coaxial-to-microstrip directional coupler convenient for power and antenna control application, are presented using the method of moments (MoM) in two dimensions. This technique is adapted to study the complex configuration of the line’s system, which does not have a simple analytical solution. The modeling of this structure consists in analyzing the primary inductive and capacitive matrices ([L] and [C]). When these matrices are determined, it is possible to calculate the inductive and capacitive coupling coefficients (kL and kC) and estimate the resulting scattering parameters of the coupler using an adapted numerical model. The coupler can be integrated into a printed circuit board (PCB) and operates over 17 to 35 dB coupling coefficients and is always compensated. The compensation is achieved by the proper displacement of a tuning ground plane with respect to the edge of the PCB from 0.1 to 3.3 mm. As an application, we present the design of a compact coupler with 7.5 × 4.8 × 25.8 mm of size and having approximately 20 dB of coupling coefficient at 2 GHz and a minimum directivity of 23.3 dB in the frequency range [0.1 - 4] GHz. In order to check our numerical calculations by the MoM we made simulations in 3D by using CST MICROWAVE STUDIO software for the same geometrical and physical parameters of our designed coupler. The results obtained by the two numerical models (MoM and CST) show a good agreement of the frequency responses of the coaxial-to-microstrip directional coupler. The studied structure represents a great improvement for high power measurement systems, since it has broad-band, good directivity, and can be easily designed and fabricated.

Shear wave splitting analysis of local earthquakes from dense arrays in Shimian,Sichuan

The Shimian area of Sichuan sits at the junction of the Bayan Har block.Sichuan-Yunnan rhombic block,and Yangtze block,where several faults intersect.This region features intense tectonic activity and frequent earthquakes.In this study,we used local seismic waveform data recorded using dense arrays deployed in the Shimian area to obtain the shear wave splitting parameters at 55 seismic stations and thereby determine the crustal anisotropic characteristics of the region.We then analyzed the crustal stress pattern and tectonic setting and explored their relationship in the study area.Although some stations returned a polarization direction of NNW-SSE.a dominant polarization direction of NW-SE was obtained for the fast shear wave at most seismic stations in the study area.The polarization directions of the fast shear wave were highly consistent throughout the study-area.This orientation was in accordance with the direction of the regional principal compressive stress and parallel to the trend of the Xianshuihe and Daliangshan faults.The distribution of crustal anisotropy in this area was affected by the regional tectonic stress field and the fault structures.The mean delay time between fast and slow shear waves was 3.83 ms/km.slightly greater than the values obtained in other regions of Sichuan.This indicates that the crustal media in our study area had a high anisotropic strength and also reveals the influence of tectonic complexity resulting from the intersection of multiple faults on the strength of seismic anisotropy.

Signed Directed Graph and Qualitative Trend Analysis Based Fault Diagnosis in Chemical Industry

In the past 30 years,signed directed graph(SDG) ,one of the qualitative simulation technologies,has been widely applied for chemical fault diagnosis.However,SDG based fault diagnosis,as any other qualitative method,has poor diagnostic resolution.In this paper,a new method that combines SDG with qualitative trend analysis(QTA) is presented to improve the resolution.In the method,a bidirectional inference algorithm based on assumption and verification is used to find all the possible fault causes and their corresponding consistent paths in the SDG model.Then an improved QTA algorithm is used to extract and analyze the trends of nodes on the consis-tent paths found in the previous step.New consistency rules based on qualitative trends are used to find the real causes from the candidate causes.The resolution can be improved.This method combines the completeness feature of SDG with the good diagnostic resolution feature of QTA.The implementation of SDG-QTA based fault diagno-sis is done using the integrated SDG modeling,inference and post-processing software platform.Its application is illustrated on an atmospheric distillation tower unit of a simulation platform.The result shows its good applicability and efficiency.

Wave load computation in direct strength analysis of semi-submersible platform structures

A wave load computation approach in direct strength analysis of semi-submersible platform structures was presented in this paper. Considering the differences in shape of pontoon, column and beam, the combination of accumulative chord length cubic parameter spline theory and analytic method was adopted for generating the wet surface mesh of platform. The hydrodynamic coefficients of platform were calculated by the three-dimensional potential flow theory of the linear hydrodynamic problem for platform with low forward speed. The equation of platform motions was established and solved in frequency domain, and the responses of wave-induced loads on the platform can be obtained. With the interpolation method being utilized, the pressure loads on shell elements for finite element analysis (FEA) were converted from those on the hydrodynamic computation mesh, which pave the basis for FEA with commercial software.A computer program based on this method has been developed, and a calculation example of semi-submersible platform was illustrated.Analysis results show that this method is a satisfying approach of wave loads computation for this kind of platform.

Direct linear discriminant analysis based on column pivoting QR decomposition and economic SVD

A direct linear discriminant analysis algorithm based on economic singular value decomposition （DLDA/ESVD） is proposed to address the computationally complex problem of the conventional DLDA algorithm, which directly uses ESVD to reduce dimension and extract eigenvectors corresponding to nonzero eigenvalues. Then a DLDA algorithm based on column pivoting orthogonal triangular （QR） decomposition and ESVD （DLDA/QR-ESVD） is proposed to improve the performance of the DLDA/ESVD algorithm by processing a high-dimensional low rank matrix, which uses column pivoting QR decomposition to reduce dimension and ESVD to extract eigenvectors corresponding to nonzero eigenvalues. The experimental results on ORL, FERET and YALE face databases show that the proposed two algorithms can achieve almost the same performance and outperform the conventional DLDA algorithm in terms of computational complexity and training time. In addition, the experimental results on random data matrices show that the DLDA/QR-ESVD algorithm achieves better performance than the DLDA/ESVD algorithm by processing high-dimensional low rank matrices.

Empirical Analysis of China's Direct Food Subsidy Policy Based on DEA Model: A Case Study of Direct Food Subsidy Policy in Shandong Province

The direct food subsidy is an important agricultural subsidy policy under current conditions,more efficient than grain price protection policy and other policies,and it is of great importance to the agricultural development,but this policy will not meet the interests of society in the long run. In this paper,we make an empirical study with the direct food subsidy policy in Shandong Province as an example,focusing on the analysis of the efficiency of policy implementation in different regions. Study suggests that direct food subsidy has made some achievements,but there are some problems in practice,such as low standard for direct food subsidy policy,less subsidy varieties,generally low efficiency of direct food subsidy policy,lack of unified policy implementation,serious waste of money and inefficient supervision during the subsidy policy implementation process. In order to improve the efficiency of direct food subsidy,it is necessary to raise standard for subsidy,and expand the scope of subsidy varieties; unify the policy,and make the policy suit local circumstances; improve the subsidy mechanism,regulate government behavior,and strengthen supervision.

Decomposition Analysis on Direct Material Input and Dematerialization of Mining Cities in Northeast China

Material dematerialization is a basic approach to reduce the pressure on the resources and environment and to realize the sustainable development. The material flow analysis and decomposition method are used to calculate the direct material input (DMI) of 14 typical mining cities in Northeast China in 1995–2004 and to analyze the demateri- alization and its driving factors in the different types of mining cities oriented by coal, petroleum, metallurgy and multi-resources. The results are as follows: 1) from 1995 to 2006, the increase rates of the DMI and the material input intensity of mining cities declined following the order of multi-resources, metallurgy, coal, and petroleum cities, and the material utilizing efficiency did following the order of petroleum, coal, metallurgy, and multi-resources cities; 2) during the research period, all the kinds of mining cities were in the situation of weak sustainable development in most years; 3) the pressure on resources and environment in the multi-resources cities was the most serious; 4) the petro- leum cities showed the strong trend of sustainable development; and 5) in recent years, the driving function of eco- nomic development for material consuming has continuously strengthened and the controlling function of material utilizing efficiency for it has weakened. The key approaches to promote the development of circular economy of min- ing cities in Northeast China are put forward in the following aspects: 1) to strengthen the research and development of the technique of resources’ cycling utilization, 2) to improve the utilizing efficiency of resources, and 3) to carry out the auditing system of resources utilization.

Kernel Model Applied in Kernel Direct Discriminant Analysis for the Recognition of Face with Nonlinear Variations

A kernel-based discriminant analysis method called kernel direct discriminant analysis is employed, which combines the merit of direct linear discriminant analysis with that of kernel trick. In order to demonstrate its better robustness to the complex and nonlinear variations of real face images, such as illumination, facial expression, scale and pose variations, experiments are carried out on the Olivetti Research Laboratory, Yale and self-built face databases. The results indicate that in contrast to kernel principal component analysis and kernel linear discriminant analysis, the method can achieve lower （7%） error rate using only a very small set of features. Furthermore, a new corrected kernel model is proposed to improve the recognition performance. Experimental results confirm its superiority （1% in terms of recognition rate） to other polynomial kernel models.

The Security Analysis of Two-Step Quantum Direct Communication Protocol in Collective-Rotation Noise Channel

To analyze the security of two-step quantum direct communication protocol （QDCP） by using Einstein-Podolsky Rosen pair proposed by Deng et al. [Phys. Rev. A 68 （2003）042317] in collective-rotation noise channel, an excellent model of noise analysis is proposed. In the security analysis, the method of the entropy theory is introduced, and is compared with QDCP, an error rate point Qo（M ： （Q0, 1.0）） is given. In different noise levels, if Eve wants to obtain the same amount of information, the error rate Q is distinguishable. The larger the noise level ~ is, the larger the error rate Q is. When the noise level ~ is lower than 11%, the high error rate is 0.153 without eavesdropping. Lastly, the security of the proposed protocol is discussed. It turns out that the quantum channel will be safe when Q 〈 0.153. Similarly, if error rate Q〉 0.153 = Q0, eavesdropping information I 〉 1, which means that there exist eavesdroppers in the quantum channel, and the quantum channel will not be safe anymore.

Importance Analysis of a Multi-state System Based on Direct Partial Logic Derivatives and Multi-valued Decision Diagrams

Importance analysis quantifies the critical degree of individual component. Compared with the traditional binary state system,importance analysis of the multi-state system is more aligned with the practice. Because the multi-valued decision diagram( MDD) can reflect the relationship between the components and the system state bilaterally, it was introduced into the reliability calculation of the multi-state system( MSS). The building method,simplified criteria,and path search and probability algorithm of MSS structure function MDD were given,and the reliability of the system was calculated. The computing methods of importance based on MDD and direct partial logic derivatives( DPLD) were presented. The diesel engine fuel supply system was taken as an example to illustrate the proposed method. The results show that not only the probability of the system in each state can be easily obtained,but also the influence degree of each component and its state on the system reliability can be obtained,which is conducive to the condition monitoring and structure optimization of the system.

Reliability Analysis Based on a Direct Ship Hull Strength Assessment

A method of reliability analysis based on a direct strength calculation employing the von Mises stress failure criterion is presented here. The short term strain distributions of ship hull structural components are identified through the statistical analysis of the wave-induced strain history and the long term distributions by the weighted summation of the short term strain distributions. The wave-induced long term strain distribution is combined with the still water strain. The extreme strain distribution of the response strain is obtained by statistical analysis of the combined strains. The limit state function of the reliability analysis is based on the von Mises stress failure criterion, including the related uncertainties due to the quality of the material and model uncertainty. The reliability index is calculated using FORM and sensitivity analysis of each variable that has effects on the reliability is also discussed.

Middle or low water pressure direct spiral double helix converging nozzle structure optimization and flow field analysis

In order to solve the problem of using new nozzle is proposed in fire rescue robot. middle or low water pressure to form fine water mist, a Existing water mist nozzles are basically used for high pressure and in large size, complex structure and poor low pressure atomization effect in comparison with requirement of snake-like fire rescue robots. On the basis of comprehensive typical spray noz- zles, a direct spiral double helix converging nozzle （DSDHCN） is proposed, which has the advanta- ges of small volume, light weight, simple structure, and convenient installation. To make the spray nozzle have good performance, and meet the requirements of more efficient fire extinguishing, a nu- merical study is carried out to analyze the internal and external full flow field of nozzle. A gas-liquid two-phase flow is applied to simulate the external full flow field of nozzle with VOF model in fluent software. The simulation results show the real situation of water flow out of the atomization nozzle and the water jet trajectory. Some simulations about middle or low water pressure direct spiral double he- lix converging optimized nozzle have been done in 30bar pressure. The simulation results show that the optimized nozzle structure not only makes the spray droplets have a good cone angle, but also have a sufficient axial velocity,which proves the structure rationality of the proposed optimized nozzle.