Zobrazeno 1 - 10
of 138
pro vyhledávání: '"Cyr E"'
Publikováno v:
Journal of Public Health in Africa, Vol 3, Iss 1 (2012)
The growing rate of sexual risk-taking among young people contributes significantly to the spread of the HIV/AIDS epidemic in Nigeria. This study, explores the influence of socio-demographic, HIV/AIDS awareness and female empowerment on the sexual ri
Externí odkaz:
https://doaj.org/article/1736cdf7cd3e414f80ecb155d90623b2
Publikováno v:
Pharmacy Practice, Vol 13, Iss 4, p 634 (2015)
Objective: To assess if the pharmacy department should be more involved in the medication reconciliation process to assist in the reduction of medication errors that occur during transition of care points in the hospital setting. Methods: This was a
Externí odkaz:
https://doaj.org/article/d5f291c5c0fa45a79dc647178e714fee
The magnetohydrodynamics (MHD) equations model a wide range of plasma physics applications and are characterized by a nonlinear system of partial differential equations that strongly couples a charged fluid with the evolution of electromagnetic field
Externí odkaz:
http://arxiv.org/abs/2006.15700
In this paper we analyse full discretizations of an initial boundary value problem (IBVP) related to reaction-diffusion equations. To avoid possible order reduction, the IBVP is first transformed into an IBVP with homogeneous boundary conditions (IBV
Externí odkaz:
http://arxiv.org/abs/2006.02962
This paper provides a new approach to derive various arbitrary high order finite difference formulae for the numerical differentiation of analytic functions. In this approach, various first and second order formulae for the numerical approximation of
Externí odkaz:
http://arxiv.org/abs/2005.11754
This paper presents a sequence of deferred correction (DC) schemes built recursively from the implicit midpoint scheme for the numerical solution of general first order ordinary differential equations (ODEs). It is proven that each scheme is A-stable
Externí odkaz:
http://arxiv.org/abs/1903.02115
Residual neural networks (ResNets) are a promising class of deep neural networks that have shown excellent performance for a number of learning tasks, e.g., image classification and recognition. Mathematically, ResNet architectures can be interpreted
Externí odkaz:
http://arxiv.org/abs/1812.04352
Autor:
Ghoncheh, M.H., Sanjari, M., Zoeram, A. Shojaei, Cyr, E., Amirkhiz, B. Shalchi, Lloyd, A., Haghshenas, M., Mohammadi, M.
Publikováno v:
In Additive Manufacturing January 2021 37
Autor:
Ghoncheh, M.H., Sanjari, M., Cyr, E., Kelly, J., Pirgazi, H., Shakerin, S., Hadadzadeh, A., Amirkhiz, B. Shalchi, Kestens, L.A.I., Mohammadi, M.
Publikováno v:
In International Journal of Plasticity October 2020 133
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