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{\bf Abstract  } 1 \vv  Verde-Star, Luis \vw   
\section{Matrix functions}By {\sl Luis Verde-Star}.\\ \begin{abstract}We study a family of  groups of infinite matrices that includes groups of generalized \\ Pascal and Stirling matrices. To each matrix $[a_{n,k}]$ we associate a\\ generating-function $G(u,z)=\sum \sum a_{n,k} u^n z^k$ considered as  formal Laurent \\ series in $z$ with coefficients that are formal Laurent series in $u$.\\Matrix multiplication corresponds to certain convolution product of the generating-functions.\\ We show that certain families of generating-functions, related to structured matrices, are groups under convolution.  In such cases, the computation of the  convolution \\ is quite simple. For example, it may be substitution of a series into another one. \\ \\We obtain one-parameter groups of generalized Stirling matrices from some of the \\ binomial formulas obtained in [L.Verde-Star and  H. M. Srivastava, Some binomial formulas of the generalized Appell form, J. Math. Anal. Appl. 274 (2002) 755--771].\\ We extend results from [L. Verde-Star, Groups of generalized Pascal matrices, Linear Algebra Appl. 382 (2004) 179--194]. \end{abstract}   
Keywords: certain families, Matrix , groups \vw  
AMS classification: 15A16, 15A33 \vw  

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{\bf Abstract  } 2 \vv  Arroyo, María José \vw   
\section{Eigenvalues}  By {\sl Maria Jose Arroyo}.    

\medskip\noindent  In this talk ... \vw  
Keywords: eigenvalues \vw  
AMS classification: 15A18,  \vw  

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{\bf Abstract  } 4 \vv  Shahryari, Mohammad \vw   
\section{$\Z_2$-graded symmetry classes of tensors}  By {\sl M. Shahryari}.    

\medskip\noindent    In this paper, we define a natural $\Z_2$-gradation on the symmetry class of tensors $V_{\chi}(G)$. We give the dimensions of {\em even}  and {\em odd} parts of this gradation. Also we prove that the even part ( the odd part) of this gradation is zero, if and only if the whole symmetry class is zero. \vw  
Keywords: Gradation, Symmetry classes of tensors, Characters of finite groups \vw  
AMS classification: 15A69, 20C15 \vw  

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{\bf Abstract  } 5 \vv  Al Zhour, Dr. Zeyad \vw   
\section{Matrix Results on Weighted Drazin Inverse and Some Applications}  By {\sl Zeyad Al Zhour and Adem Kilicman}.    

\medskip\noindent  In this paper, we present two general representations of the weighted Drazin inverse $A_{d,W}$ of an arbitrary rectangular matrix $A_{m,n}$ related to Moore-Penrose Inverse (MPI) and Kronecker product of matrices. These generalizations extend earlier results on the Drazin inverse $A_{d}$, group inverse $A_{g}$ and usual inverse $A^{-1}$. Furthermore, some necessary and sufficient conditions for Drazin and weighted Drazin inverses are given for the reverse order law $(AB)_{d}=B_{d}A_{d}$  and $(AB)_{d,Z}=B_{d,R}A_{d,W}$  to hold. Finally, we present the solution of the restricted singular matrix equations using our new approaches. \vw  
Keywords: Kronecker Product, Weighted Drazin Inverses, General algebraic structures, Index. Nilpotent matrix. \vw  
AMS classification: 15A69, 15A09 \vw  

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{\bf Abstract  } 6 \vv  Bardsley, John \vw   
\section{Stopping rules for a nonnegatively constrained iterative method for ill-posed Poisson imaging problems}  By {\sl Johnathan?? M. Bardsley}.    

\medskip\noindent  Image data is often collected by a charge coupled device (CCD) camera. CCD camera noise is known to be well-modeled by a Poisson distribution. If this is taken into account, the negative-log of the Poisson likelihood is the resulting data-fidelity function. We derive, via a Taylor series argument, a weighted least squares approximation of the negative-log of the Poisson likelihood function. The image deblurring algorithm of interest is then applied to the problem of minimizing this weighted least squares function subject to a nonnegativity constraint. Our objective in this paper is the development of stopping rules for this algorithm. We present three stopping rules and then test them on data generated using two different true images and an accurate CCD camera noise model. The results indicate that each of the three stopping rules is effective. \vw  
Keywords: iterative methods, image reconstruction, regularization, statistical methods \vw  
AMS classification: 65F20, 65F30 \vw  

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{\bf Abstract  } 7 \vv  Rakotondrajao, Fanja \vw   
\section{Euler's difference table and maximum permanents of $(0,1)$-matrices}  By {\sl Fanja Rakotondrajao}.    

\medskip\noindent  First, we will enumerate the injections from $[m]$ to $[n]$ without $k$-fixed-points, that is, injection $f$ without $i$ such that $f(i) = i+k$. We will deduce the exact values of maximum permanent of $(0,1)- m \times n $ matrices having $m-k$ numbers of zero entries for any non negative integers $0\leq k \leq m \leq n$. Unexpectedly these values are related to the numbers $d^k_n$ of $k$-fixed-points-permutations over $[n]$. The numbers $d^k_n$ are the derivate of Euler's difference table. \vw  
Keywords: $k$-fixed-points, $(0,1)$-matrices, permanent, injections, $k$-fixed-points-permutations. \vw  
AMS classification: 05A19, 05B20 \vw  

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{\bf Abstract  } 8 \vv  Verde-Star, Luis \vw   
\section{Your title here}  By {\sl names of all authors here}.    

\medskip\noindent  Insert your abstract here      abstract test \vw  
Keywords: matrix, exponential, inverse \vw  
AMS classification: 15A25, 15A30 \vw  
Remarks: This is a test \vw  

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