162,151 research outputs found

    La mort, filosòficament parlant

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    En el número 60 de la revista L'Espill trobaràs un dossier monogràfic sobre "L’apoteosi del kitsch", amb contribucions d'Antoni Martí Monterde, Anacleto Ferrer, Josep Maria Ruiz Simon i Hermann Broch. A més, articles de Marta Marín-Dòmine, Enzo Traverso, Antoni Defez, Josep J. Conill, Francisco Fuster, Manuel Guerrero i Jordi Nieva, així com La mirada de Mar Arza i fulls de dietari de Maria Folch i Ignasi Mora

    Els humans, animals que juguen i es busquen lingüísticament

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    En el número 56 de la revista L'Espill trobaràs un dossier monogràfic sobre "Nació i narració", amb contribucions de Joan Ramon Resina, Simona Škrabec, Jernej Habjan, Ferran Garcia-Oliver, Àlex Martín Escribà i Jaume Subirana. A més, articles d'Herman Daly, Remo Bodei, Maria Xosé Agra, Blanca Llum Vidal, Gustau Muñoz, Josep J. Conill, Antoni Defez, Victoria Saenz i Sebastià Alzamora, així com documents de Ievgueni Zamiatin i un full de dietari de Francesc Parcerisas

    [Report to Chief J. E. Curry, by an unknown author #1]

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    Report to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney

    [Report to Chief J. E. Curry, by an unknown author #2]

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    Report to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney

    Computing Matrix Trigonometric Functions with GPUs through Matlab

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    [EN] This paper presents an implementation of one of the most up-to-day algorithms proposed to compute the matrix trigonometric functions sine and cosine. The method used is based on Taylor series approximations which intensively uses matrix multiplications. To accelerate matrix products, our application can use from one to four NVIDIA GPUs by using the NVIDIA cublas and cublasXt libraries. The application, implemented in C++, can be used from the Matlab command line thanks to the mex files provided. We experimentally assess our implementation in modern and very high-performance NVIDIA GPUs.This work has been supported by Spanish Ministerio de Economia y Competitividad and the European Regional Development Fund (ERDF) Grants TIN2014-59294-P and TEC2015-67387-C4-1-RAlonso-Jordá, P.; Peinado Pinilla, J.; Ibáñez González, JJ.; Sastre, J.; Defez Candel, E. (2019). Computing Matrix Trigonometric Functions with GPUs through Matlab. The Journal of Supercomputing. 75(3):1227-1240. https://doi.org/10.1007/s11227-018-2354-1S12271240753Serbin SM (1979) Rational approximations of trigonometric matrices with application to second-order systems of differential equations. Appl Math Comput 5(1):75–92Serbin Steven M, Blalock Sybil A (1980) An algorithm for computing the matrix cosine. SIAM J Sci Stat Comput 1(2):198–204Hargreaves GI, Higham NJ (2005) Efficient algorithms for the matrix cosine and sine. Numer Algorithms 40:383–400Al-Mohy Awad H, Higham Nicholas J (2009) A new scaling and squaring algorithm for the matrix exponential. SIAM J Matrix Anal Appl 31(3):970–989Defez E, Sastre J, Ibáñez Javier J, Ruiz Pedro A (2011) Computing matrix functions arising in engineering models with orthogonal matrix polynomials. Math Comput Model 57:1738–1743Sastre J, Ibáñez J, Ruiz P, Defez E (2013) Efficient computation of the matrix cosine. Appl Math Comput 219:7575–7585Al-Mohy Awad H, Higham Nicholas J, Relton Samuel D (2015) New algorithms for computing the matrix sine and cosine separately or simultaneously. SIAM J Sci Comput 37(1):A456–A487Alonso P, Ibáñez J, Sastre J, Peinado J, Defez E (2017) Efficient and accurate algorithms for computing matrix trigonometric functions. J Comput Appl Math 309(1):325–332CUBLAS library (2017) http://docs.nvidia.com/cuda/cublas/index.html . Accessed May 2017Alonso Jordá P, Boratto M, Peinado Pinilla J, Ibáñez González JJ, Sastre Martínez J (2014) On the evaluation of matrix polynomials using several GPGPUs. Universitat Politècnica de València, 2014. http://hdl.handle.net/10251/39615 . Accessed Sept 2017Boratto Murilo, Alonso Pedro, Giménez Domingo, Lastovetsky Alexey L (2017) Automatic tuning to performance modelling of matrix polynomials on multicore and multi-gpu systems. J Supercomput 73(1):227–239Alonso P, Peinado J, Ibáñez J, Sastre J, Defez E (2017) A fast implementation of matrix trigonometric functions sine and cosine. In: Proceedings of the 17th International Conference on Computational and Mathematical Methods in Science and Engineering (CMMSE 2017), pp 51–55, Costa Ballena, Rota, Cadiz (Spain), July 4th–8thSastre Jorge, Ibáñez Javier, Alonso Pedro, Peinado Jesús, Defez Emilio (2017) Two algorithms for computing the matrix cosine function. Appl Math Comput 312:66–77Paterson Michael S, Stockmeyer Larry J (1973) On the number of nonscalar multiplications necessary to evaluate polynomials. SIAM J Comput 2(1):60–66Higham Nicholas J (2008) Functions of matrices: theory and computation. SIAM, PhiladelphiaSastre J, Ibáñez Javier J, Defez E, Ruiz Pedro A (2011) Efficient orthogonal matrix polynomial based method for computing matrix exponential. Appl Math Comput 217:6451–6463Sastre J, Ibáñez Javier J, Defez E, Ruiz Pedro A (2015) Efficient scaling-squaring Taylor method for computing matrix exponential. SIAM J Sci Comput 37(1):A439–455Higham NJ, Tisseur F (2000) A block algorithm for matrix 1-norm estimation, with an application to 1-norm pseudospectra. SIAM J Matrix Anal Appl 21:1185–1201Demmel JW (1987) A counterexample for two conjectures about stability. IEEE Trans Autom Control 32:340–343Wright Thomas G (2002) EigTool library. http://www.comlab.ox.ac.uk/pseudospectra/eigtool/ . Accessed May 201

    Murder on the mountain: author talk with Peter J. Wosh

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    Author talk by Peter J. Wosh on May 5th, 2022, on his book, "Murder on the Mountain: crime, passion, and punishment in gilded age New Jersey.

    Simulation of harmonic oscillators on the lattice

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    [EN] This work deals with the simulation of a two¿dimensional ideal lattice having simple tetragonal geometry. The harmonic character of the oscillators give rise to a system of second¿order linear differential equations, which can be recast into matrix form. The explicit solutions which govern the dynamics of this system can be expressed in terms of matrix trigonometric functions. For the derivation we employ the Lagrangian formalism to determine the correct solutions, which extremize the underlying action of the system. In the numerical evaluation we develop diverse state¿of¿the¿art algorithms which efficiently tackle equations with matrix sine and cosine functions. For this purpose, we introduce two special series related to trigonometric functions. They provide approximate solutions of the system through a suitable combination. For the final computation an algorithm based on Taylor expansion with forward and backward error analysis for computing those series had to be devised. We also implement several MATLAB programs which simulate and visualize the two¿dimensional lattice and check its energy conservation.This work has been supported by the Spanish Ministerio de Economia y Competitividad, the European Regional Development Fund (ERDF) under grant TIN2017-89314-P, and the Programa de Apoyo a la Investigacion y Desarrollo 2018 (PAID-06-18) of the Universitat Politecnica de Valencia under grant SP20180016.Tung, MM.; Ibáñez González, JJ.; Defez Candel, E.; Sastre, J. (2020). Simulation of Harmonic Oscillators on the Lattice. Mathematical Methods in the Applied Sciences. 43(14):8237-8252. https://doi.org/10.1002/mma.6510S823782524314Dehghan, M., & Hajarian, M. (2009). Determination of a matrix function using the divided difference method of Newton and the interpolation technique of Hermite. Journal of Computational and Applied Mathematics, 231(1), 67-81. doi:10.1016/j.cam.2009.01.021Dehghan, M., & Hajarian, M. (2010). Computing matrix functions using mixed interpolation methods. Mathematical and Computer Modelling, 52(5-6), 826-836. doi:10.1016/j.mcm.2010.05.013Kazem, S., & Dehghan, M. (2017). Application of finite difference method of lines on the heat equation. Numerical Methods for Partial Differential Equations, 34(2), 626-660. doi:10.1002/num.22218Kazem, S., & Dehghan, M. (2018). Semi-analytical solution for time-fractional diffusion equation based on finite difference method of lines (MOL). Engineering with Computers, 35(1), 229-241. doi:10.1007/s00366-018-0595-5Paterson, M. S., & Stockmeyer, L. J. (1973). On the Number of Nonscalar Multiplications Necessary to Evaluate Polynomials. SIAM Journal on Computing, 2(1), 60-66. doi:10.1137/0202007Sastre, J., Ibáñez, J., Defez, E., & Ruiz, P. (2011). Efficient orthogonal matrix polynomial based method for computing matrix exponential. Applied Mathematics and Computation, 217(14), 6451-6463. doi:10.1016/j.amc.2011.01.004Higham, N. J. (2008). Functions of Matrices. doi:10.1137/1.9780898717778Sastre, J., Ibáñez, J., Defez, E., & Ruiz, P. (2011). Accurate matrix exponential computation to solve coupled differential models in engineering. Mathematical and Computer Modelling, 54(7-8), 1835-1840. doi:10.1016/j.mcm.2010.12.049Serbin, S. M., & Blalock, S. A. (1980). An Algorithm for Computing the Matrix Cosine. SIAM Journal on Scientific and Statistical Computing, 1(2), 198-204. doi:10.1137/0901013Ruiz, P., Sastre, J., Ibáñez, J., & Defez, E. (2016). High performance computing of the matrix exponential. Journal of Computational and Applied Mathematics, 291, 370-379. doi:10.1016/j.cam.2015.04.001Higham, N. J. (1988). FORTRAN codes for estimating the one-norm of a real or complex matrix, with applications to condition estimation. ACM Transactions on Mathematical Software, 14(4), 381-396. doi:10.1145/50063.21438

    Mr. Melvin J. Collier, RWWL AUC, June 2011

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    This video is a conversation with Mr. Melvin J. Collier. Mr. Collier talks about his book, "From Mississippi to Africa: A Journey of Discovery". Daniel Le, AUC Woodruff Library, is the interviewer

    New matrix series expansions for the matrix cosine approximation

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    This work has been partially supported by Spanish Ministerio de Economia y Competitividad and European Regional Development Fund (ERDF) grants TIN2017-89314-P and by the Programa de Apoyo a la Investigacion y Desarrollo 2018 of the Universitat Politecnica de Valencia (PAID-06-18) grants SP20180016.Defez Candel, E.; Ibáñez González, JJ.; Alonso Abalos, JM.; Peinado Pinilla, J.; Alonso-Jordá, P. (2019). New matrix series expansions for the matrix cosine approximation. R. Company, J. C. Cortés, L. Jódar and E. López-Navarro. 64-69. https://riunet.upv.es/handle/10251/180537S646

    A Tripartite Post-Recession Rebalancing

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    In this latest Advance & Rutgers Report, entitled “A Tripartite Post-Recession Rebalancing,” Dean James W. Hughes and Professor Joseph J. Seneca deliver an incisive assessment of the current market conditions and obstacles in the path of our economic recovery. They offer a statistical cautionary tale that the private and public sector need to hear and acknowledge in order for the economy to make continued progress.This report was published as Issue Paper Number 7, November 2011, in Advance & Rutgers Report
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