The Influence of Cu and Cr on the Matrix Decomposition of Quenched AlZnMg Alloy

1991 ◽  
Vol 124 (1) ◽  
pp. K11-K14 ◽  
Author(s):  
C. Dos Santos Lourenço ◽  
M. Cilense ◽  
W. Garlipp
Keyword(s):  
Matrix Decomposition ◽  
Mg Alloy ◽  
The Matrix

Lattice imaging of precipitates in Al-Zn-Mg alloy

1986 ◽  
Vol 44 ◽  
pp. 412-413
Author(s):  
C. K. Wu
Keyword(s):  
Grain Boundaries ◽  
Homogeneous Nucleation ◽  
Alloy System ◽  
Mg Alloy ◽  
List Type ◽  
Lattice Structures ◽  
Type Number ◽  
Orientation Relationships ◽  
Lattice Imaging ◽  
The Matrix

The precipitation phenomenon in Al-Zn-Mg alloy is quite interesting and complicated and can be described in the following categories:(i) heterogeneous nucleation at grain boundaries;(ii) precipitate-free-zones (PFZ) adjacent to the grain boundaries;(iii) homogeneous nucleation of snherical G.P. zones, n' and n phases inside the grains. The spherical G.P. zones are coherent with the matrix, whereas the n' and n phases are incoherent. It is noticed that n' and n phases exhibit plate-like morpholoay with several orientation relationship with the matrix. The high resolution lattice imaging techninue of TEM is then applied to study precipitates in this alloy system. It reveals the characteristics of lattice structures of each phase and the orientation relationships with the matrix.

scholarly journals Effect of Vanadium Reinforcement on the Microstructure and Mechanical Properties of Magnesium Matrix Composites

Crystals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 806
Author(s):  
Liqing Sun ◽  
Shuai Sun ◽  
Haiping Zhou ◽  
Hongbin Zhang ◽  
Gang Wang ◽  
...  
Keyword(s):  
Grain Size ◽  
Grain Refinement ◽  
Milling Process ◽  
Mg Alloy ◽  
Matrix Composites ◽  
Magnesium Matrix Composites ◽  
Pinning Effect ◽  
Average Grain Size ◽  
The Matrix ◽  
Hot Press Sintering

In this work, vanadium particles (VP) were utilized as a novel reinforcement of AZ31 magnesium (Mg) alloy. The nanocrystalline (NC) AZ31–VP composites were prepared via mechanical milling (MM) and vacuum hot-press sintering. During the milling process, the presence of VP contributed to the cold welding and fracture mechanism, resulting in the acceleration of the milling process. Additionally, increasing the VP content accelerated the grain refinement of the matrix during the milling process. After milling for 90 h, the average grain size of AZ31-X wt % Vp (X = 5, 7.5, 10) was refined to only about 23 nm, 19 nm and 16 nm, respectively. In the meantime, VP was refined to sub-micron scale and distributed uniformly in the matrix, exhibiting excellent interfacial bonding with the matrix. After the sintering process, the average grain size of AZ31-X wt % VP (X = 5, 7.5, 10) composites still remained at the NC scale, which was mainly caused by the pinning effect of VP. Besides that, the porosity of the sintered composites was no more than 7.8%, indicating a good densification effect. As a result, there was little difference between the theoretical and real density. Compared to as-cast AZ31 Mg alloy, the microhardness of sintered AZ31-X wt % VP (X = 5, 7.5, 10) composites increased by 65%, 87% and 96%, respectively, owing to the strengthening mechanisms of grain refinement strengthening, Orowan strengthening and load-bearing effects.

Identifying graph clusters using variational inference and links to covariance parametrization

2009 ◽  
Vol 367 (1906) ◽  
pp. 4407-4426
Author(s):  
David Barber
Keyword(s):  
Mean Field ◽  
Matrix Decomposition ◽  
Difficult Problem ◽  
Positive Definite ◽  
Variational Inference ◽  
Field Theories ◽  
Variational Approximation ◽  
Positive Definite Matrices ◽  
The Matrix ◽  
Non Gaussian

Finding clusters of well-connected nodes in a graph is a problem common to many domains, including social networks, the Internet and bioinformatics. From a computational viewpoint, finding these clusters or graph communities is a difficult problem. We use a clique matrix decomposition based on a statistical description that encourages clusters to be well connected and few in number. The formal intractability of inferring the clusters is addressed using a variational approximation inspired by mean-field theories in statistical mechanics. Clique matrices also play a natural role in parametrizing positive definite matrices under zero constraints on elements of the matrix. We show that clique matrices can parametrize all positive definite matrices restricted according to a decomposable graph and form a structured factor analysis approximation in the non-decomposable case. Extensions to conjugate Bayesian covariance priors and more general non-Gaussian independence models are briefly discussed.

scholarly journals Linear Precoding Scheme Design for MIMO Two-Way Relay Systems with Imperfect Channel State Information

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xiao-min Chen ◽  
Jun-xu Su ◽  
Qiu-ming Zhu ◽  
Xu-jun Hu ◽  
Zhu Fang
Keyword(s):  
Iterative Scheme ◽  
Matrix Decomposition ◽  
Mean Square ◽  
Linear Precoding ◽  
Imperfect Channel State Information ◽  
Channel State ◽  
State Information ◽  
Scheme Design ◽  
Decomposition Scheme ◽  
The Matrix

The aim of this paper is to investigate a linear precoding scheme design for a multiple-input multiple-output two-way relay system with imperfect channel state information. The scheme design is simplified as an optimal problem with precoding matrix variables, which is deduced with the maximum power constraint at the relay station based on the minimum mean square error criterion. With channel feedback delay at both ends of the channel and the channel estimation errors being taken into account, we propose a matrix decomposition scheme and a joint iterative scheme to minimize the average sum mean square error. The matrix decomposition method is used to derive the closed form of the relay matrix, and the joint iterative algorithm is used to optimize the precoding matrix and the processing matrix. According to numerical simulation results, the matrix decomposition scheme reduces the system bit error rate (BER) effectively and the joint iterative scheme achieves the best performance of BER against existing methods.

Effect of Phase Fraction Ratio Between Al3Mg2 and Mg2Si on the Oxidation Behavior of Al–Mg–Si Alloys

2021 ◽  
Vol 16 (7) ◽  
pp. 1047-1051
Author(s):  
Seong-Ho Ha ◽  
Abdul Wahid Shah ◽  
Bong-Hwan Kim ◽  
Young-Ok Yoon ◽  
Hyun-Kyu Lim ◽  
...  
Keyword(s):  
Oxidation Resistance ◽  
High Temperatures ◽  
Cross Sections ◽  
Oxidation Behavior ◽  
Eutectic Phase ◽  
Mg Alloy ◽  
Phase Fraction ◽  
The Matrix ◽  
Si Content

The effect of the phase fraction ratio between Al3Mg2 and Mg2Si on the oxidation resistance of Al–Mg–Si alloys at high temperatures was investigated. With addition of 1 mass%Si in Al-6 mass%Mg alloy, the as-cast microstructures showed formation of Mg2Si phase by eutectic reactions. With increasing Si content more than 3 mass%, the Mg2Si and Si are formed as eutectic phases with no β-Al3Mg2 phase. In addition, with an increase in the Si content from 3 mass%, significantly refined as-cast microstructures and distribution of extended eutectic phase areas were observed. The oxidized cross-sections of Al-6 mass%Mg and Al-6 mass%Mg-1 mass%Si alloys showed coarse and dark areas, which are considered as oxide clusters, nonuniformly grown into the matrix. However, Al-6 mass%Mg-3 mass%Si and Al-6 mass%Mg-5 mass%Si alloys had no significantly grown oxide clusters on the surfaces. Based on the results, it was concluded that the reduction of the ratio between β-Al3Mg2 and Mg2Si phases can reduce the rapid oxidation of Mg.

scholarly journals Another look at matrix correlations

2019 ◽  
Vol 35 (22) ◽  
pp. 4748-4753 ◽  
Author(s):  
Ahmad Borzou ◽  
Razie Yousefi ◽  
Rovshan G Sadygov
Keyword(s):  
Matrix Decomposition ◽  
Data Matrix ◽  
Supplementary Information ◽  
Biological Processes ◽  
Single Experiment ◽  
Sample Number ◽  
The Matrix ◽  
Rv Coefficient ◽  
Systems View ◽  
Data Matrices

Abstract Motivation High throughput technologies are widely employed in modern biomedical research. They yield measurements of a large number of biomolecules in a single experiment. The number of experiments usually is much smaller than the number of measurements in each experiment. The simultaneous measurements of biomolecules provide a basis for a comprehensive, systems view for describing relevant biological processes. Often it is necessary to determine correlations between the data matrices under different conditions or pathways. However, the techniques for analyzing the data with a low number of samples for possible correlations within or between conditions are still in development. Earlier developed correlative measures, such as the RV coefficient, use the trace of the product of data matrices as the most relevant characteristic. However, a recent study has shown that the RV coefficient consistently overestimates the correlations in the case of low sample numbers. To correct for this bias, it was suggested to discard the diagonal elements of the outer products of each data matrix. In this work, a principled approach based on the matrix decomposition generates three trace-independent parts for every matrix. These components are unique, and they are used to determine different aspects of correlations between the original datasets. Results Simulations show that the decomposition results in the removal of high correlation bias and the dependence on the sample number intrinsic to the RV coefficient. We then use the correlations to analyze a real proteomics dataset. Availability and implementation The python code can be downloaded from http://dynamic-proteome.utmb.edu/MatrixCorrelations.aspx. Supplementary information Supplementary data are available at Bioinformatics online.

The Application of Matrix Compression Algorithm in Network Education Platform for the User Security Authentication

2014 ◽  
Vol 889-890 ◽  
pp. 1730-1736
Author(s):  
Nong Zheng
Keyword(s):  
Open Channel ◽  
Block Size ◽  
Matrix Decomposition ◽  
Compression Algorithm ◽  
Network Education ◽  
Cipher Text ◽  
Security Authentication ◽  
Matrix Compression ◽  
The Matrix ◽  
Education Platform

Using the matrix compression algorithm in the network education platform for the user information security certification is a good way. The sensitive user information is transfer in an open channel and it can be authentication for using the matrix compression/decompression, matrix decomposition/reduction algorithm. The client conduct random capture and compression by the user information been divided into a number of rectangular block size, corresponding to generate a key and cipher text. The server take out the corresponding data from the data queue of receiving and to extract In accordance with the key rules, then to reduce of information in corresponding positions. Thus the user identity information can be authenticity and integrity verification.

scholarly journals Split-and-Combine Singular Value Decomposition for Large-Scale Matrix

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Jengnan Tzeng
Keyword(s):  
Singular Value Decomposition ◽  
Large Scale ◽  
Semantic Analysis ◽  
Computational Cost ◽  
Matrix Decomposition ◽  
Singular Value ◽  
Fast Method ◽  
The Matrix ◽  
Scale Matrix ◽  
Value Decomposition

The singular value decomposition (SVD) is a fundamental matrix decomposition in linear algebra. It is widely applied in many modern techniques, for example, high- dimensional data visualization, dimension reduction, data mining, latent semantic analysis, and so forth. Although the SVD plays an essential role in these fields, its apparent weakness is the order three computational cost. This order three computational cost makes many modern applications infeasible, especially when the scale of the data is huge and growing. Therefore, it is imperative to develop a fast SVD method in modern era. If the rank of matrix is much smaller than the matrix size, there are already some fast SVD approaches. In this paper, we focus on this case but with the additional condition that the data is considerably huge to be stored as a matrix form. We will demonstrate that this fast SVD result is sufficiently accurate, and most importantly it can be derived immediately. Using this fast method, many infeasible modern techniques based on the SVD will become viable.

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