Initial Matrices Research Articles

Pixel Steganalysis - A Novel Approach in ImageSteganography Using F5 Algorithm

The Faugere F5 algorithm first calculates the Grobner basis of a pair of generator polynomials of the ideal. And it uses to reduce the sizes of initial matrices of created messages which had to be embedded in image steganography. The stenographical systems are weak against statistically and visually weak which offers only a relatively small capacity of stenographic message but the newly developed f5 algorithm help to embedded messages in images large capacity of steganography. It implement matrix encoding and permutation straddling to embedded message with large capacity and reduces the embedded-image.

Sorption and electrochemical properties of carbon–silica composites and carbons from 2,3-dihydroxynaphthalene

Carbon–silica composites were obtained by uniformly coating the entire pore surface of SBA-15 and KIT-6 with a thin carbon layer using a 2,3-dihydroxynaphthalene as a carbon source. Due to formation of uniform carbon coating obtained composites possesses electrical conductivity despite the insulative nature of the silicas and thus exhibit ohmic curves. The specific capacitance per surface area of carbon–silica composites is higher than those of conventional activated carbons due to carbon–silica composites exhibited capacitance from electric double-layer and a time-consuming process between carbon surface and H2SO4 electrolyte similar to pseudocapacitance. This allows considering such composites as electrode materials with uniform pores. The Hydrogen initial potential for adsorption |Δµ 0| and density of pore surface filling with hydrogen for the composite with higher carbon content (24.7 µg/m2) is more than 5 times higher than for the initial silica (4.6 µg/m2) and approximately 2 times higher than for the composite with lower carbon content (10.4 µg/m2). |Δµ 0| for the obtained porous carbons is higher (5.2 kJ/mol) than for the initial matrices (2.8 kJ/mol) and carbon–silica composites (3.7–5.1 kJ/mol).

Fabrication of SbSI Photonic Crystals

Photonic crystals (PCs) with periodically modulated dielectric constant have gathered great importance in recent years [1]. They posses a band gap for electromagnetic waves similar to that for valence electrons in crystalline semiconductors. Value of this gap strongly depends on geometrical parameters of the structure as well as on complex refractive indices of the applied materials. It is highly promising to use materials with refractive indices that can be tuned with external conditions, e.g. electric field or temperature. In this paper antimony sulfoiodide (SbSI) is using for the construction of photonic crystal. SbSI is a ferroelectric semiconductor with relatively high refractive index strongly dependent on temperature and external electric field, especially near its Curie point (TC = 293(1) K). Therefore, SbSI is potentially very useful in fabrication of photonic crystals. In this work we present threedimensional photonic crystals of air spheres in SbSI. The initial opal matrices with a closedpacked face centered cubic (fcc) lattice, were prepared from monodisperse silicon (SiO2) spheres by gravity sedimentation. Composite opal SbSI structures were obtained by infiltration the voids in opals with melted SbSI. To obtain the inverted SbSI opal consistent of air spheres in SbSI the original opal template was removed by etching in HF acid. Scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDX) and atomic force microscopy (AFM) confirm the quality of the samples.

“Light-Cone” Dynamics After Quantum Quenches in Spin Chains

Signal propagation in the nonequilibrium evolution after quantum quenches has recently attracted much experimental and theoretical interest. A key question arising in this context is what principles, and which of the properties of the quench, determine the characteristic propagation velocity. Here we investigate such issues for a class of quench protocols in one of the central paradigms of interacting many-particle quantum systems, the spin-1/2 Heisenberg XXZ chain. We consider quenches from a variety of initial thermal density matrices to the same final Hamiltonian using matrix product state methods. The spreading velocities are observed to vary substantially with the initial density matrix. However, we achieve a striking data collapse when the spreading velocity is considered to be a function of the excess energy. Using the fact that the XXZ chain is integrable, we present an explanation of the observed velocities in terms of "excitations" in an appropriately defined generalized Gibbs ensemble.

Nonlinear Seismic Analysis of Reinforced Concrete Bridges Using the Force Analogy Method

Abstract In this paper, a three-dimensional nonlinear dynamic analysis framework for RC bridges is established based on the force analogy method (FAM). Two biaxial local plastic mechanisms, rotation hinge (RH) and slide hinge (SH), are proposed based on the fundamental concept of FAM to simulate the nonlinear flexure-shear interactive behavior of RC piers, a critical consideration for seismic performance assessment of RC bridges. The RHs located at the ends of RC piers express the relationships of moment versus plastic rotation, whereas the SHs are assigned to simulate the shear versus plastic shear deformation behaviors of RC piers. Coupling the presented biaxial local plastic mechanisms with FAM, the nonlinear response of RC bridges under bidirectional earthquakes can be evaluated. Because only constant initial stiffness matrices are used throughout the whole analyzing process, the state space integration formulation can be used for solving the equations of motion, which makes the computational process ...

Nonlinear seismic analysis of reinforced concrete frames using the force analogy method

SUMMARYA method of nonlinear seismic analysis for RC framed structures considering full‐range factors, including stiffness and strength degradation, geometric nonlinearity, and structural member failure, is established based on the fundamental concept of the force analogy method. The strong material nonlinearity, large geometric deformation, and internal forces redistribution due to the member failure can be depicted by the proposed local plastic mechanisms, the rotation hinges at the member ends and the slide hinges assigned to the columns, of which the measurement relationships are moment versus plastic rotation and shear force versus shear plastic deformation, respectively. They are capable of evaluating the exact response of RC structures. Because only unchanging initial stiffness matrices are used through the whole computation process, the state‐space formulation was used for solving the equations of motion. The advantages of the force analogy method, such as high efficiency and stability, are still retained. The exactness of the proposed local plastic mechanisms is verified against a group of tests data, and the application of the proposed procedure is performed to an RC framed structure to simulate the full‐range nonlinear response by increasing the excitation step by step until failure of partial structural members appear. Copyright © 2014 John Wiley & Sons, Ltd.

Colossal magnetocapacitance effect at room temperature

First nano-hybridized clathrate/cavitant structure of hierarchical architecture was synthesized. The results of investigations of the properties of initial nanoporous silica matrices MCM-41, with encapsulated in its pores of β-cyclodextrin in cavitand and cavitat (with FeSO4) states and change at room temperature in a constant magnetic field intensity of 2.75 kOe, have been presented. Phenomenon of enormous magnetocapacitance and giant negative variable-current magnetoresistance has been discovered.

Decomposition and coupling of soil domain for modeling vertical ground heat exchangers using the state model size reduction technique

Numerical modeling of the ground heat exchangers requires important computational resources to accurately reproduce the short-time thermal responses over a long-time period. Considering geometries of the vertical ground heat exchanger, domain decomposition is proposed in the vertical and horizontal directions. As the principal direction of the heat transfer in such a system is horizontal and here the cumbersome finite element method in treating the domain decomposition is adopted, only the horizontal soil domain case is investigated in this work. A new type of boundaries to decomposed sub-zones is proposed, and then a restitution method is developed to keep all the matrix terms inherent in initial matrices ahead of decomposition. The state model size reduction technique is used for each sub-zone model to reduce the model size, and then the reduced models are regrouped into a single state model using the new proposed coupling method. Results show that the developed decomposition and coupling methods are pertinent with negligible errors (less than 0.005 °C for the maximum), and the final reduced model gives acceptable results for typical purposes of geothermal simulations. From some sensitivity tests, it is found that accuracy of the reduced model can be systematically improved by increasing the reduced order or the number of sub-zones. The proposed model is remarkably faster than the reference model (more than 300 times), implying that a detailed 3-D numerical model can be used for long-time simulations.

The precise consistency consensus matrix in a local AHP-group decision making context

A new decisional tool, the consensus consistency matrix (CCM) has recently been proposed for dealing with AHP-group decision making (AHP-GDM) in a local context (a single criterion). Each entry of this matrix, based on the property of consistency, corresponds to the range of values or interval in which all the decision makers are simultaneously consistent in their initial matrices. The main limitation of the CCM is that, on many occasions, it is not possible to obtain a matrix with the minimum $$n-1$$ judgments that are required to derive the priorities. In this local AHP context, using the row geometric mean as the prioritisation procedure, this paper presents an extension of the CCM, the precise consensus consistency matrix (PCCM), which significantly mitigates this problem. By identifying precise values in the common consistency intervals, the PCCM automatically allows the number of entries in the CCM to be increased. The PCCM provides more informed and participative GDM and offers more accurate estimations for the group’s priorities. It can also be used as a starting point for posterior negotiation processes between the actors and it can be employed in global AHP-GDM contexts (hierarchies). The new decisional tool has been applied to a real-life experience concerned with the analysis of the integral viability of public investment projects, more specifically, the economic valuation of social aspects.

The modified conjugate gradient methods for solving a class of generalized coupled Sylvester-transpose matrix equations

In this paper, we consider the iteration solutions of generalized coupled Sylvester-transpose matrix equations: A1XB1+C1YTD1=F1, A2YB2+C2XTD2=F2. When the coupled matrix equations are consistent, we propose a modified conjugate gradient method to solve the equations and prove that a solution (X∗,Y∗) can be obtained within finite iterative steps in the absence of roundoff-error for any initial value. Furthermore, we show that the minimum-norm solution can be got by choosing a special kind of initial matrices. When the coupled matrix equations are inconsistent, we present another modified conjugate gradient method to find the least-squares solution with the minimum-norm. Finally, some numerical examples are given to show the behavior of the considered algorithms.

Application of EMD-Based SVD and SVM to Coal-Gangue Interface Detection

Coal-gangue interface detection during top-coal caving mining is a challenging problem. This paper proposes a new vibration signal analysis approach to detecting the coal-gangue interface based on singular value decomposition (SVD) techniques and support vector machines (SVMs). Due to the nonstationary characteristics in vibration signals of the tail boom support of the longwall mining machine in this complicated environment, the empirical mode decomposition (EMD) is used to decompose the raw vibration signals into a number of intrinsic mode functions (IMFs) by which the initial feature vector matrices can be formed automatically. By applying the SVD algorithm to the initial feature vector matrices, the singular values of matrices can be obtained and used as the input feature vectors of SVMs classifier. The analysis results of vibration signals from the tail boom support of a longwall mining machine show that the method based on EMD, SVD, and SVM is effective for coal-gangue interface detection even when the number of samples is small.

Since the DNA Molecule Returns from the Transcriptional Process Exactly as it was before the Process, the DNA→Protein Production Can Be Seen as a Series of Eigenvalue Problems

Sequence of operators acts on the linear DNA-eigenfunction and gradually transforms it into the 3D protein-eigenvalue. The eigenvalue equation for the DNA→Protein production is Protein (DNA) = RxMxSxTxUtw (DNA).The operation of splicing of an exon (S) is studied in the presented work:mRNA = S (preRNA). Here preRNA = TxUtw (DNA).For illustration, the human beta globin gene cluster located on chromosome 11 is applied. The β- and δ-globin genes are expressed during adult life. The e- and γ-globins are expressed in early embryonic and fetal erythroid tissues. The relative positions of the nucleic acid content centers for each globin gene before and after the splicing determine the initial and final 4x4 matrices. The eigenvalue equation of the preRNA → mRNA transformation is:| g u a c|⋯⋯⋯|g c a u|| c g a u| = S x |g c u a|| c a g u|⋯⋯⋯|c g a u|| g a c u|⋯⋯⋯|c g u a|By solving this equation one finds the matrix operator of exon splicing, S =| u g c a|| a a u u|| g u a c|| c c g g|Is the process of exon splicing a simple removal of the mass? Is it rather a selective removal of specific nucleic acids? The latter changes the flexibility and the strength of the polypeptide chain, and is driven by electrostatic interactions. The former is an important component in defining the final structures and the spatial stability of the protein.

An iterative updating method for damped structural systems using symmetric eigenstructure assignment

An iterative method for updating finite element models with measured modal results using a symmetric eigenstructure assignment technique is developed. By the method, the updated symmetric damping and stiffness matrices can be obtained within finite iteration steps in the absence of roundoff errors by choosing a special kind of initial matrices and the measured data are embedded in the updated model. The numerical results show that the proposed method is reliable and attractive.

A finite iterative algorithm for the solution of Sylvester-conjugate matrix equations [formula omitted] and [formula omitted

In this paper, we consider two iterative algorithms for the Sylvester-conjugate matrix equation AV+BW=EV¯F+C and AV+BW¯=EV¯F+C. When these two matrix equations are consistent, for any initial matrices the solutions can be obtained within finite iterative steps in the absence of round off errors. Some lemmas and theorems are stated and proved where the iterative solutions are obtained. Two numerical examples are given to illustrate the effectiveness of the proposed method.

Subtractive clustering for seeding non-negative matrix factorizations

Non-negative matrix factorization is a multivariate analysis method which is proven to be useful in many areas such as bio-informatics, molecular pattern discovery, pattern recognition, document clustering and so on. It seeks a reduced representation of a multivariate data matrix into the product of basis and encoding matrices possessing only non-negative elements, in order to learn the so called part-based representations of data. All algorithms for computing non-negative matrix factorization are iterative, therefore particular emphasis must be placed on a proper initialization of NMF because of its local convergence. The problem of selecting appropriate starting matrices becomes more complex when data possess special meaning as in document clustering. In this paper, we propose the adoption of the subtractive clustering algorithm as a scheme to generate initial matrices for non-negative matrix factorization algorithms. Comparisons with other commonly adopted initializations of non-negative matrix factorization algorithms have been performed and the proposed scheme reveals to be a good trade-off between effectiveness and speed. Moreover, the effectiveness of the proposed initialization to suggest a number of basis for NMF, when data distances are estimated, is illustrated when NMF is used for solving clustering problems where the number of groups in which the data are grouped is not known a priori. The influence of a proper rank factor on the interpretability and the effectiveness of the results are also discussed.

Finite algorithms for solving the coupled Sylvester-conjugate matrix equations over reflexive and Hermitian reflexive matrices

It is known that solving coupled matrix equations with complex matrices can be very difficult and it is sufficiently complicated. In this work, we propose two iterative algorithms based on the Conjugate Gradient method (CG) for finding the reflexive and Hermitian reflexive solutions of the coupled Sylvester-conjugate matrix equations(including Sylvester and Lyapunov matrix equations as special cases). The iterative algorithms can automatically judge the solvability of the matrix equations over the reflexive and Hermitian reflexive matrices, respectively. When the matrix equations are consistent over reflexive and Hermitian reflexive matrices, for any initial reflexive and Hermitian reflexive matrices, the iterative algorithms can obtain reflexive and Hermitian reflexive solutions within a finite number of iterations in the absence of roundoff errors, respectively. Finally, two numerical examples are presented to illustrate the proposed algorithms.

Iterative algorithm for solving a class of general Sylvester-conjugate matrix equation $\sum_{i = 1}^{s} A_{i}V + \sum_{j = 1}^{t} B_{j}W = \sum_{l = 1}^{m} E_{l}\overline{V}F_{l} + C$

This paper is concerned with iterative solution to general Sylvester-conjugate matrix equation of the form \(\sum_{i = 1}^{s} A_{i}V + \sum_{j = 1}^{t} B_{j}W = \sum_{l = 1}^{m} E_{l}\overline{V}F_{l} + C\). An iterative algorithm is established to solve this matrix equation. When this matrix equation is consistent, for any initial matrices, the solutions can be obtained within finite iterative steps in the absence of round off errors. Some lemmas and theorems are stated and proved where the iterative solutions are obtained. Finally, a numerical example is given to verify the effectiveness of the proposed algorithm.

COMPARISON OF ACCURACY IN RANKING ALTERNATIVES PERFORMING GENERALIZED FUZZY AVERAGE FUNCTIONS

The paper defines the notions of point, interval and triangular intuitionistic fuzzy numbers expressing the degree of membership and non-membership in the fuzzy set. The generalized fuzzy weighted average function is introduced according to operation rules on intuitionistic fuzzy numbers. In special cases, the generalized weighted average coincides with an arithmetic average or a geometric average. The generalized fuzzy weighted average function could be applied for solving problems in multiple criteria decision making. Research on the stability of the generalized weighted averaging operator of ranking alternatives was performed applying the Monte Carlo method. The aim of the conducted research is to establish the types of intuitionistic fuzzy numbers and the exponent values of the generalized weighted averaging operator having the least error probabilities considering alternatives ranking. Computations were performed involving 3, 4 and 5 experts. In the case of 5 experts, initial decision matrices having high, middle and low separability alternatives were examined. Decision matrices created by the experts were modelled generating random intuitionistic fuzzy numbers according to uniform and normal distribution. The example of applying such methodology was shown to solve a real problem of ranking possible redevelopment alternatives for derelict rural buildings.

How To NOT Make the Extended Kalman Filter Fail

In an effort to assess the performance of newer estimation algorithms, many prior publications have presented comparative studies where the Extended Kalman Filter (EKF) failed. This is because the EKF’s design parameters were sometimes chosen arbitrarily and with little consideration of their role and impact on filter performance. This paper demonstrates in a tutorial way that EKF failure can often be avoided by a systematic design of its parameters, i.e. its covariance matrices. Particular focus is on the systematic selection of proper initial state and process noise covariance matrices. As in practice, model parameters are first identified from plant measurements. The covariance of these model parameters is subsequently required to calculate the proposed time-varying process noise covariance matrix for the EKF. Finally, the proposed EKF design is evaluated on a popular reactor example process from the literature and converges in all simulation runs. From this extensive set of simulations and by comparison with several out-of-the-box versions of the constrained Unscented Kalman Filter (UKF), we conclude that there exists a systematic way to design the EKF for a very satisfactory performance. Therefore, the EKF’s design parameters need not be tuned ad hoc by trial and error.

Finite Iterative Algorithm for Solving a Complex of Conjugate and Transpose Matrix Equation

We consider an iterative algorithm for solving a complex matrix equation with conjugate and transpose of two unknowns of the form: A1VB1+C1WD1+A2V¯B2+C2W¯D2+A3VHB3+C3WHD3+A4VTB4 + C4WTD4=E. With the iterative algorithm, the existence of a solution of this matrix equation can be determined automatically. When this matrix equation is consistent, for any initial matrices V1, W1 the solutions can be obtained by iterative algorithm within finite iterative steps in the absence of round-off errors. Some lemmas and theorems are stated and proved where the iterative solutions are obtained. A numerical example is given to illustrate the effectiveness of the proposed method and to support the theoretical results of this paper.