Features of microstructure and fracture in the transient liquid phase bonded aluminium-based metal matrix composite joints

Transient liquid phase (TLP) bonded aluminium based metal matrix composite (MMC) joints can be classified into three distinct regions, i.e. the particulate segregation region, the denuded particulate region and the base material region. The microstructure of the particulate segregation region consists of alumina particulate and Al alloy matrix with the Al 2Cu and MgAl 2O 4. It contains more and smaller alumina particulates compared with the base material region. The TLP bonded joints have the tensile strength of 150 MPa ～200 MPa and the shear strength of 70 MPa ～100 MPa . With increasing tensile stress, cracks initiate in the particulate segregation region, especially in the particulate/particulate interface and the particulate/matrix interface, and propagate along particulate/matrix interface, througth thin matrix metal and by linking up the close cracks. The particulate segregation region is the weakest during tensile testing and shear testing due to obviously increased proportion of weak bonds (particulate particulate bond and particulate matrix bond).

Extracellular matrix based biomaterials for central nervous system tissue repair: the benefits and drawbacks

Functional repair of injured tissue in the adult central nervous system （CNS） still remains a big challenge for current biomed- ical research and its upcoming clinical translation. The axonal regeneration of the adult CNS is generally low, and it is addi- tionally restricted after injury by the presence of inhibitory mol- ecules, generated by the glial scar.

Spectral clustering based on matrix perturbation theory

This paper exposes some intrlnsic chsracterlstlca of the spectral clustering method by using the tools from the mstrlx perturbation theory. We construct s welght mstrix of s graph and study Its elgenvalues and elgenvectors. It shows that the number of clusters Is equal to the number of elgenvslues that are larger than 1, and the number of polnts In each of the clusters can be spproxlmsted by the associated elgenvslue. It also shows that the elgenvector of the weight rnatrlx can be used dlrectly to perform clusterlng; that Is, the dlrectlonsl angle between the two-row vectors of the mstrlx derlved from the elgenvectors Is s sultable distance measure for clustsrlng. As s result, an unsupervised spectral clusterlng slgorlthm based on welght mstrlx （USCAWM） Is developed. The experlmental results on s number of srtlficisl and real-world data sets show the correctness of the theoretical analysis.

Image registration based on matrix perturbation analysis using spectral graph

We present a novel perspective on characterizing the spectral correspondence between nodes of the weighted graph with application to image registration. It is based on matrix perturbation analysis on the spectral graph. The contribution may be divided into three parts. Firstly, the perturbation matrix is obtained by perturbing the matrix of graph model. Secondly, an orthogonal matrix is obtained based on an optimal parameter, which can better capture correspondence features. Thirdly, the optimal matching matrix is proposed by adjusting signs of orthogonal matrix for image registration. Experiments on both synthetic images and real-world images demonstrate the effectiveness and accuracy of the proposed method.

Towed line array sonar platform noise suppression based on spatial matrix filtering technology

The spatial matrix filter was designed and used for solving the problem to detect a weak target who was influenced by the strong nearby platform noise interference of the towed line array sonar. The MFP technology and the DOA estimation technology were combined together by using the sound propagation characteristics of both target and interference. The spatial matrix filter with platform noise zero response constraint was designed by the near-field platform noise normal modes copy vectors and the far-field plane wave bearing vectors together. The optimal solution of the optimization problem for designing the spatial matrix filter was deduced directly, and it was simplified by the generalized singular value decomposition. The total response error to the plane wave bearing vectors and the total response to the platform noise copy vectors were given. The phenomena that strong interferences existed in the bearing course and blind areas existed after filtering were analyzed by the correlation between the plat- form noise copy vectors and the plane wave bearing vectors. It could be found from simulations that it has less blind area and higher detection ability by using the spatial matrix filtering technology.

Frequency-invariant robust adaptive beamforming based on interference covariance matrix reconstruction

Consider the problems of frequency-invariant beampattern optimization and robustness in broadband beamforming.Firstly,a global optimization algorithm,which is based on phase compensation of the array manifolds,is used to construct the frequency-invariant beampattern.Compared with some methods presented recently,the proposed algorithm is not only available to get the global optimal solution,but also simple for physical realization.Meanwhile,a robust adaptive broadband beamforming algorithm is also derived by reconstructing the covariance matrix.The essence of the proposed algorithm is to estimate the space-frequency spectrum using Capon estimator firstly,then integrate over a region separated from the desired signal direction to reconstruct the interference-plus-noise covariance matrix,and finally caleulate the adaptive beamformer weights with the reconstructed matrix.The design of beamformer is formulated as a convex optimization problem to be solved.Simulation results show that the performance of the proposed algorithm is almost always close to the optimal value across a wide range of signal to noise ratios.

Round-trip imaging through scattering media based on optical transmission matrix

Traditional one-way imaging methods become invalid when a target object is completely hidden behind scattering media. In this case, it has been much more challenging, since the light wave is distorted twice.To solve this problem, we propose an imaging method, so-called round-trip imaging, based on the optical transmission matrix of the scattering medium. We show that the object can be recovered directly from the distorted output wave, where no scanning is required during the imaging process. We predict that this method might improve the imaging speed and have potential application for real-time imaging.

An all-optical matrix multiplication scheme with non-linear material based switching system

Optics is a potential candidate in information, data, and image processing. In all-optical data and information processing, optics has been used as information carrying signal because of its inherent advantages of parallelism. Several optical methods are proposed in support of the above processing. In many algebraic, arithmetic, and image processing schemes fundamental logic and memory operations are conducted exploring all-optical devices. In this communication we report an all-optical matrix multiplication operation with non-linear material based switching circuit.

Structural Damage Detection in Framed Structures Under Foundation Settlement/Rotation of Bases

This paper describes the damage detection in framed structures due to thevertical support settlement and rotation of footing bases. The damage detection procedureproposed by Nobahari et al. [Nobahari and Seyedpoor (2013)] is used to detect thedamage in the members of the frame. In the present study, instead of using the flexibilitymatrix (referred here as original flexibility matrix) method, the generalized flexibilitymatrix is used in the same algorithm and the results are compared. The algorithm usesflexibility matrix and strain energy concept to detect the damage in the members. Thebehaviour of the frame is discussed through changes observed in flexibility in theassociated degree of freedom. Finally, the results indicate that, the damage indexdetermined by generalized flexibility matrix method is more reliable than using theoriginal flexibility matrix based method for the problem of settlement and rotation offooting base.

An algorithm to solve autocorrelation matrix singular value based on SNR estimation

SNR estimation of communication signals is important to improve demodulation performance and channel quality of communication system,thus it is an important research issue of communication field.According to the core problem of autocorrelation matrix singular value in SNR estimation process,through making use of householder transforming autocorrelation matrix into tridiagonal matrix,and by using the relation of corresponding characteristic equation coefficients and singular value,a numerical algorithm is given to obtain autocorrelation matrix singular value,and the algorithm is used for SNR solving process.Theoretical analysis shows that the algorithm can satisfy the requirements in the aspect of constringency speed and stability.