Avec une population estimée à 17,07 millions d'habitants en 2021 et un taux d'électrification d'environ 45,5% 1, le déficit en desserte électrique de la Ville-Province de Kinshasa est estimé à 54,5 ...%. Renverser cette tendance fait partie des préoccupations du Gouvernement de la République. C'est dans ce cadre que plusieurs programmes de réhabilitation et d'extension sont en cours de réalisation. Ces projets sont financés par soit des bailleurs de fonds internationaux tels que le PMURR, le PMEDE, le PEPUR, l'EASE MALT, soit la SNEL SA elle-même sur fonds propres, soit sur intervention directe du gouvernement congolais. La stratégie de mise en oeuvre du projet EASE par la SNEL SA DKO fera l'objet de cette analyse. En considérant le volume des données qu'elle est sensé générer, une gestion informatique à base des données NoSQL est la mieux appropriée au point qu'elle est susceptible de la rendre performante.
Python for Natural Language Processing Goto, Isao
The Journal of The Institute of Image Information and Television Engineers,
2018, Volume:
72, Issue:
11
Journal Article
This is a comprehensive guide to Pyomo, an open source software package for formulating and solving large-scale optimization and operations research problems. Includes chapters on advanced modeling ...capabilities for nonlinear and stochastic optimization.
Motivation Biologists often wish to use their knowledge on a few experimental models of a given molecular system to identify homologs in genomic data. We developed a generic tool for this purpose. ...Results Macromolecular System Finder (MacSyFinder) provides a flexible framework to model the properties of molecular systems (cellular machinery or pathway) including their components, evolutionary associations with other systems and genetic architecture. Modelled features also include functional analogs, and the multiple uses of a same component by different systems. Models are used to search for molecular systems in complete genomes or in unstructured data like metagenomes. The components of the systems are searched by sequence similarity using Hidden Markov model (HMM) protein profiles. The assignment of hits to a given system is decided based on compliance with the content and organization of the system model. A graphical interface, MacSyView, facilitates the analysis of the results by showing overviews of component content and genomic context. To exemplify the use of MacSyFinder we built models to detect and class CRISPR-Cas systems following a previously established classification. We show that MacSyFinder allows to easily define an accurate "Cas-finder" using publicly available protein profiles. Availability and Implementation MacSyFinder is a standalone application implemented in Python. It requires Python 2.7, Hmmer and makeblastdb (version 2.2.28 or higher). It is freely available with its source code under a GPLv3 license at https://github.com/gem-pasteur/macsyfinder. It is compatible with all platforms supporting Python and Hmmer/makeblastdb. The "Cas-finder" (models and HMM profiles) is distributed as a compressed tarball archive as Supporting Information.
We present an algorithm implemented in the Astroalign Python module for image registration in astronomy. Our module does not rely on WCS information and instead matches three-point asterisms ...(triangles) on the images to find the most accurate linear transformation between them. It is especially useful in the context of aligning images prior to stacking or performing difference image analysis. Astroalign can match images of different point-spread functions, seeing, and atmospheric conditions.
Python for Scientists and Engineers Millman, K. Jarrod; Aivazis, Michael
Computing in science & engineering,
2011-March-April, 2011-03-00, 20110301, Volume:
13, Issue:
2
Journal Article
Peer reviewed
Open access
Python has arguably become the de facto standard for exploratory, interactive, and computation-driven scientific research. This issue discusses Python's advantages for scientific research and ...presents several of the core Python libraries and tools used in scientific research.
This book is intended for those who plan to become data scientists as well as anyone who needs to perform data cleaning tasks using Pandas and NumPy. --
Albany is a parallel C++ finite element library for solving forward and inverse problems involving partial differential equations (PDEs). In this paper we introduce PyAlbany, a newly developed Python ...interface to the Albany library. PyAlbany can be used to effectively drive Albany enabling fast and easy analysis and post-processing of applications based on PDEs that are pre-implemented in Albany. PyAlbany relies on the library PyBind11 to bind Python with C++ Albany code. Here we detail the implementation of PyAlbany and showcase its capabilities through a number of examples targeting a heat-diffusion problem. In particular we consider (1) the generation of samples for a Monte Carlo application, (2) a scalability study, (3) a study of parameters on the performance of a linear solver, and (4) a tool for performing eigenvalue decompositions of matrix-free operators for a Bayesian inference application.