Academic literature on the topic 'Langage Python'
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Journal articles on the topic "Langage Python"
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Laurent Bloch. "Un langage pour enseigner la programmation, Scheme ou Python ?" Bulletin 1024, no. 20 (November 2022): 85–95. http://dx.doi.org/10.48556/sif.1024.20.85.
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Philippot, Alexandre, Stéphane Lecasse, Bernard Riera, and François Gellot. "Développement d’un connecteur logiciel pour l’apprentissage de l’automatisme." J3eA 21 (2022): 2056. http://dx.doi.org/10.1051/j3ea/20222056.
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L’apprentissage de l’automatisme s’adresse aujourd’hui à un public d’étudiants ayant pour la plupart avant tout un background informatique. Ils/elles passent par des phases d’apprentissage de langages compilés et/ou interprétés. Il est compliqué alors pour eux de passer d’une réflexion informatique avec un langage venant du monde de l’IT (Information Technology) vers la programmation d’Automates Programmable Industriel (API), au comportement cyclique, synchrone et aux langages normalisés (IEC 61131-3) issu du monde de l’OT (Operational Technology). Ce papier présente une proposition de mise en place d’un connecteur logiciel entre ces deux mondes aux travers de l’utilisation d’un logiciel de simulation de Parties Opératives Factory I/O (realgames.co) et du langage Python.
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KENOUFI, Abdelouahab. "Probabilist Set Inversion using Pseudo-Intervals Arithmetic." TEMA (São Carlos) 15, no. 1 (2014): 097. http://dx.doi.org/10.5540/tema.2014.015.01.0097.
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<pre><!--StartFragment-->In this paper, we present how to use an interval arithmetic framework based on free algebra construction, in order to build better defined inclusion function for interval semi-group and for its associated vector space. One introduces the <span>psi</span>-algorithm, which performs set inversion of functions and exhibits some numerical examples developed with the python programming langage<!--EndFragment--></pre>.
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Jovanović, S., and S. Weber. "Modélisation et accélération de réseaux de neurones profonds (CNN) en Python/VHDL/C++ et leur vérification et test à l’aide de l’environnement Pynq sur les FPGA Xilinx." J3eA 21 (2022): 1028. http://dx.doi.org/10.1051/j3ea/20220028.
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Nous présentons un ensemble de travaux pratiques qui seront dispensés au sein du Master EEA - Électronique Embarquée à l’université de Lorraine dans le cadre des modules Modélisation SystemC et Conception VLSI. Ces TP sont destinés à initier les étudiants à la compréhension, modélisation et conception des réseaux de neurones convolutifs dans des langages de description de matériel au niveau RTL (VHDL, le module Conception VLSI) et dans un langage de haut niveau (C++/SystemC, le module Modélisation SystemC). Ils sont organisés autour d’un ensemble d’outils de modélisation et de synthèse de Mentor Graphics (Modelsim, Catapult HLS) et spécifiques aux plateformes FPGA Xilinx et à l’environnement Pynq pour la simulation, test et vérification.
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Graillet, Olivia, Frédéric Alicalapa, Pierre-Olivier Lucas de Peslouan, Denis Genon-Catalot, and Jean-Pierre Chabriat. "Approche pédagogique pour l’étude d’autoconsommation photovoltaïque au niveau Master avec utilisation de l’API de SolarIO en langage Python." J3eA 23 (2024): 0002. http://dx.doi.org/10.1051/j3ea/20240002.
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L’île de La Réunion, qui fait partie des Zones Non Interconnectées (ZNI), dépend actuellement à 62% des importations d’énergies fossiles pour la production d’électricité. Afin de contribuer à son autonomie énergétique, il est nécessaire de développer les sources d’énergies renouvelables locales. Dans ce contexte, l’unité de recherche ENERGY-Lab et la Faculté des Sciences et Technologies de l’Université de La Réunion proposent le cursus « Master Energie ». L’un des objectifs du Master est de permettre aux étudiants d’acquérir des compétences pouvant répondre aux problématiques énergétiques actuelles. A La Réunion, le secteur des installations photovoltaïques est particulièrement actif en raison d’un fort potentiel solaire, lié à son climat subtropical. La démarche pédagogique présentée dans ce document est ainsi composée d’activités en lien avec l’optimisation de l’autoconsommation d’une centrale photovoltaïque : établir un plan de sobriété énergétique, affiner la précision du dimensionnement de la centrale PV et simuler des flux de puissances. Les différents outils et technologies utilisés (tableurs, programmation Python et G LabVIEW, API, bases de données) ont été choisis pour s’adapter à la fois à un contexte scientifique et industriel.
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Akeel Hussein Alaasam, Hussein, Ahmed Ali Talib Al-Khazaali, Ali Hussein Aleiwi, and Doaa Wahhab Ibrahim. "Learn Land Features Using Python Language." BIO Web of Conferences 97 (2024): 00111. http://dx.doi.org/10.1051/bioconf/20249700111.
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Python has emerged as an essential programming language for research due to continuous technological advancements that emphasize its role in streamlining scientific workflows. This article elucidates Python's burgeoning impact on researchers across disciplines. Tracing Python's origins and applications within the earth sciences contextualizes its versatility. While acquiring proficiency in Python exceeds this article's scope, discussions detail its utilities for earth science data analysis, visualization, management, and rapid computations. With Python expertise, researchers can engineer customized software with domain-specific tools to advance all earth science spheres. Ultimately, this article underscores Python's position as a vital programming language for contemporary academic research through its flexibility and specialization for scientific use cases.
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Gujar, Advait. "C vs Python: A Cursory Look with Industry Opinion." International Journal for Research in Applied Science and Engineering Technology 11, no. 10 (2023): 55–64. http://dx.doi.org/10.22214/ijraset.2023.56446.
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In this paper, the author explores the characteristics and applications of C & Python programming languages across various industries, drawing insights from interviews with professionals. The study includes a comparative analysis of C and Python based on execution time, code readability, and length. C, favored for its speed and applicability in game development and embedded systems, has complexities such as large code size and lack of cross-platform support. In contrast, Python excels in artificial intelligence, machine learning, and web scraping due to its simplicity and extensive libraries. The article emphasizes the influence of programming communities on language popularity, noting Python's widespread adoption due to its concise syntax and strong community support. Industry experts concur on C's complexity and time-intensive nature but acknowledge its effectiveness. Python's ease of learning has made it the world's most widely used language, prompting non-coding sectors to encourage Python education.
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Peta, Saphalya. "Python- An Appetite for the Software Industry." International Journal of Programming Languages and Applications 12, no. 4 (2022): 1–14. http://dx.doi.org/10.5121/ijpla.2022.12401.
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Python is a scripting language that's high- positioned, interpreted, interactive, and object- oriented. Python is intended to be a veritably accessible programming language. It generally uses English terms rather than punctuation, and it has smaller syntactical structures than other languages. Python is a must-have skill for scholars and working professionals who want to become exceptional software masterminds, especially if they work in the web development field. It's a freshman-friendly scripting language. Some of the crucial features of Python programming language are- It supports OOP as well as functional and structured programming methodologies. It can be used as a scripting language or collected into bytecode for large-scale operations. It allows dynamic type verification and provides veritably high-position dynamic data types. It facilitates scrap collection by itself. Numerous different programming languages have been impacted by Python's design and gospel. Some of those languages are Boo, Cobra, CoffeeScript, Go, Swift, Ruby, etc. Some of the advantages of Python programming language are straightforward, free, simple to use, and largely compatible, object- acquainted, has multitudinous libraries, has erected in data structures, has a wide range of uses, boosts productivity and speed, and simple to understand. One of the most extensively used programming languages is Python. It's an open- source language. Python's demand is growing, and its operations are expanding in virtually every assiduity. It's abundant in every way. It has a wide range of capabilities. Python is a popular programming language. It's also developing a strong request in the IT sector. Python is in high demand across the globe. Python helps you negotiate more in lower time. Python has a large community that supports and meets the requirements of inventors. Python is therefore one of the most popular programming languages. It's a veritably reliable and effective programming language. Python programmers are in high demand because Python is being used in a variety of sectors. Python is an extensively used computer language that was created nearly 25 years ago. Python is useful in a variety of fields, including web development, desktop app development, machine literacy, big data, data analysis, and robotics. Clean syntax, extremely clear law, a wide range of uses, packages that help apply features, and a cool community that helps grow this excellent language are just a many of the reasons why people like this language and why it's well suited for different tasks. The Python programming language has a bright future. The advanced technologies like Artificial Intelligence, Machine Learning, Big Data, Cloud Computing, Data Science, etc and world-notorious companies similar as Amazon, Google, Apple, Deloitte, Microsoft, Netflix, and Accenture have the Python programming language as their backbone which states that Python is in demand and AN APPETITE FOR THE SOFTWARE INDUSTRY! A standard and scientific procedure of an Empirical Exploration Methodology (Survey) was conducted to check the statement stated by the author where 900 repliers from colourful corridors of the globe shared their thoughts. From the check, it was concluded that 99.8% of the respondents feel that Python is one of the in- demand programming languages for the digital assiduity in the present time.
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Patel, Aryan. "Mojo: A Python-based Language for High-Performance AI Models and Deployment." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 10 (2023): 1–11. http://dx.doi.org/10.55041/ijsrem26529.
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Python has become a popular language for AI model development due to its elegant and flexible programming capabilities, extensive tool ecosystem, and high-performance libraries like Numpy and PyTorch. However, Python's execution speed remains a challenge, especially for performance-critical inner loops. To address this, Python programmers often rely on wrappers for C, FORTRAN, or Rust code, leading to a "two-language" approach that introduces complexities in deployment and debugging. This research paper introduces Mojo, a promising solution to the Python performance issue, which is essentially Python++ and built on top of MLIR (Multi-Level Intermediate Representation). Mojo is a rigorously designed superset of Python that allows seamless integration of high-performance implementations by switching to a faster "mode." This paper discusses the key features of Mojo, its deployment advantages, and its comparison with other alternatives in the AI and ML development landscape.
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Lazebna, Nataliia. "ENGLISH-LANGUAGE BASIS OF PYTHON PROGRAMMING LANGUAGE." Research Bulletin Series Philological Sciences 1, no. 193 (2021): 371–76. http://dx.doi.org/10.36550/2522-4077-2021-1-193-371-376.
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The dynamic nature of the Python programming language, the accumulation of a certain linguosemiotic basis indicates the similarity of this language with the English language, which is the international one and mediates human communication in both real and virtual worlds. In this study, the English language is positioned as the linguistic basis of Python language of programming, which is widely used in industry, research, natural language processing, textual information retrieval, textual data processing, texts corpora, and more. English language, its lexical features, text representation and interaction with logical and functional basis in the context of Python programming language are considered further in this research. Thus, the unity of verbal units and symbols in the modern English-language digital discourse indicates both the order and variability of the constituents therein. The functionality of linguosemiotic elements produces a network of relationships, where each of these integrated elements can produce from a word or symbol a holistic set of units, which are extrapolated in the English-language digital discourse and mediates human communication with a machine. An overview of the basic properties of Python language, such as values, types, expressions, and operations are in focus of the study. Though users understand the responses of Python interpreter, there is a need to follow certain instructions and codes. To facilitate work with this programming language and prescribed English-language commands, it is necessary to involve linguists to cooperate with programmers to invent a certain logical and reasonable principle of Python commands operation.
Dissertations / Theses on the topic "Langage Python"
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Miled, Mahdi. "Ressources et parcours pour l'apprentissage du langage Python : aide à la navigation individualisée dans un hypermédia épistémique à partir de traces." Thesis, Cachan, Ecole normale supérieure, 2014. http://www.theses.fr/2014DENS0045/document.
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Les travaux de recherche de cette thèse concernent principalement l‘aide à la navigation individualisée dans un hypermédia épistémique. Nous disposons d‘un certain nombre de ressources qui peut se formaliser à l‘aide d‘un graphe acyclique orienté (DAG) : le graphe des épistèmes. Après avoir cerné les environnements de ressources et de parcours, les modalités de visualisation et de navigation, de traçage, d‘adaptation et de fouille de données, nous avons présenté une approche consistant à corréler les activités de conception ou d‘édition à celles dédiées à l‘utilisation et la navigation dans les ressources. Cette approche a pour objectif de fournir des mécanismes d‘individualisation de la navigation dans un environnement qui se veut évolutif. Nous avons alors construit des prototypes appropriés pour mettre à l‘épreuve le graphe des épistèmes. L‘un de ces prototypes a été intégré à une plateforme existante. Cet hypermédia épistémique baptisé HiPPY propose des ressources et des parcours portant sur l‘apprentissage du langage Python. Il s‘appuie sur un graphe des épistèmes, une navigation dynamique et un bilan de connaissances personnalisé. Ce prototype a fait l‘objet d‘une expérimentation qui nous a donné la possibilité d‘évaluer les principes introduits et d‘analyser certains usages<br>This research work mainly concerns means of assistance in individualized navigation through an epistemic hypermedia. We have a number of resources that can be formalized by a directed acyclic graph (DAG) called the graph of epistemes. After identifying resources and pathways environments, methods of visualization and navigation, tracking, adaptation and data mining, we presented an approach correlating activities of design or editing with those dedicated to resources‘ use and navigation. This provides ways of navigation‘s individualization in an environment which aims to be evolutive. Then, we built prototypes to test the graph of epistemes. One of these prototypes was integrated into an existing platform. This epistemic hypermedia called HiPPY provides resources and pathways on Python language. It is based on a graph of epistemes, a dynamic navigation and a personalized knowledge diagnosis. This prototype, which was experimented, gave us the opportunity to evaluate the introduced principles and analyze certain uses
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Tesser, Federico. "Solveur parallèle pour l’équation de Poisson sur mailles superposées et hiérarchiques, dans le cadre du langage Python." Thesis, Bordeaux, 2018. http://www.theses.fr/2018BORD0129/document.
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Les discrétisations adaptatives sont importantes dans les problèmes de fluxcompressible/incompressible puisqu'il est souvent nécessaire de résoudre desdétails sur plusieurs niveaux, en permettant de modéliser de grandes régionsd'espace en utilisant un nombre réduit de degrés de liberté (et en réduisant letemps de calcul).Il existe une grande variété de méthodes de discrétisation adaptative, maisles grilles cartésiennes sont les plus efficaces, grâce à leurs stencilsnumériques simples et précis et à leurs performances parallèles supérieures.Et telles performance et simplicité sont généralement obtenues en appliquant unschéma de différences finies pour la résolution des problèmes, mais cetteapproche de discrétisation ne présente pas, au contraire, un chemin faciled'adaptation.Dans un schéma de volumes finis, en revanche, nous pouvons incorporer différentstypes de maillages, plus appropriées aux raffinements adaptatifs, en augmentantla complexité sur les stencils et en obtenant une plus grande flexibilité.L'opérateur de Laplace est un élément essentiel des équations de Navier-Stokes,un modèle qui gouverne les écoulements de fluides, mais il se produit égalementdans des équations différentielles qui décrivent de nombreux autres phénomènesphysiques, tels que les potentiels électriques et gravitationnels. Il s'agitdonc d'un opérateur différentiel très important, et toutes les études qui ontété effectuées sur celui-ci, prouvent sa pertinence.Dans ce travail seront présentés des approches de différences finies et devolumes finis 2D pour résoudre l'opérateur laplacien, en appliquant des patchsde grilles superposées où un niveau plus fin est nécessaire, en laissant desmaillages plus grossiers dans le reste du domaine de calcul.Ces grilles superposées auront des formes quadrilatérales génériques.Plus précisément, les sujets abordés seront les suivants:1) introduction à la méthode des différences finies, méthode des volumes finis,partitionnement des domaines, approximation de la solution;2) récapitulatif des différents types de maillages pour représenter de façondiscrète la géométrie impliquée dans un problème, avec un focussur la structure de données octree, présentant PABLO et PABLitO. Le premier estune bibliothèque externe utilisée pour gérer la création de chaque grille,l'équilibrage de charge et les communications internes, tandis que la secondeest l'API Python de cette bibliothèque, écrite ad hoc pour le projet en cours;3) la présentation de l'algorithme utilisé pour communiquer les données entreles maillages (en ignorant chacune l'existence de l'autre) en utilisant lesintercommunicateurs MPI et la clarification de l'approche monolithique appliquéeà la construction finale de la matrice pour résoudre le système, en tenantcompte des blocs diagonaux, de restriction et de prolongement;4) la présentation de certains résultats; conclusions, références.Il est important de souligner que tout est fait sous Python comme framework deprogrammation, en utilisant Cython pour l'écriture de PABLitO, MPI4Py pour lescommunications entre grilles, PETSc4py pour les parties assemblage et résolutiondu système d'inconnues, NumPy pour les objets à mémoire continue.Le choix de ce langage de programmation a été fait car Python, facile àapprendre et à comprendre, est aujourd'hui un concurrent significatif pourl'informatique numérique et l'écosystème HPC, grâce à son style épuré, sespackages, ses compilateurs et pourquoi pas ses versions optimisées pour desarchitectures spécifiques<br>Adaptive discretizations are important in compressible/incompressible flow problems since it is often necessary to resolve details on multiple levels,allowing large regions of space to be modeled using a reduced number of degrees of freedom (reducing the computational time).There are a wide variety of methods for adaptively discretizing space, but Cartesian grids have often outperformed them even at high resolutions due totheir simple and accurate numerical stencils and their superior parallel performances.Such performance and simplicity are in general obtained applying afinite-difference scheme for the resolution of the problems involved, but this discretization approach does not present, by contrast, an easy adapting path.In a finite-volume scheme, instead, we can incorporate different types of grids,more suitable for adaptive refinements, increasing the complexity on thestencils and getting a greater flexibility.The Laplace operator is an essential building block of the Navier-Stokes equations, a model that governs fluid flows, but it occurs also in differential equations that describe many other physical phenomena, such as electric and gravitational potentials, and quantum mechanics. So, it is a very importantdifferential operator, and all the studies carried out on it, prove itsrelevance.In this work will be presented 2D finite-difference and finite-volume approaches to solve the Laplacian operator, applying patches of overlapping grids where amore fined level is needed, leaving coarser meshes in the rest of the computational domain.These overlapping grids will have generic quadrilateral shapes.Specifically, the topics covered will be:1) introduction to the finite difference method, finite volume method, domainpartitioning, solution approximation;2) overview of different types of meshes to represent in a discrete way thegeometry involved in a problem, with a focuson the octree data structure, presenting PABLO and PABLitO. The first one is anexternal library used to manage each single grid’s creation, load balancing and internal communications, while the second one is the Python API ofthat library written ad hoc for the current project;3) presentation of the algorithm used to communicate data between meshes (beingall of them unaware of each other’s existence) using MPI inter-communicators and clarification of the monolithic approach applied building the finalmatrix for the system to solve, taking into account diagonal, restriction and prolongation blocks;4) presentation of some results; conclusions, references.It is important to underline that everything is done under Python as programmingframework, using Cython for the writing of PABLitO, MPI4Py for the communications between grids, PETSc4py for the assembling and resolution partsof the system of unknowns, NumPy for contiguous memory buffer objects.The choice of this programming language has been made because Python, easy to learn and understand, is today a significant contender for the numerical computing and HPC ecosystem, thanks to its clean style, its packages, its compilers and, why not, its specific architecture optimized versions
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Monat, Raphaël. "Static type and value analysis by abstract interpretation of Python programs with native C libraries." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS263.
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Dans cette thèse, nous avons pour objectif de concevoir, à la fois théoriquement et expérimentalement, des méthodes pour la détection automatique de bogues potentiels dans les logiciels – ou la preuve de leur absence. Ces méthodes sont statiques : elles analysent le code source des programmes sans les exécuter. Nos travaux s’inscrivent dans le cadre de l’interprétation abstraite pour dériver une sémantique sûre et décidable. Le principal objet de ce travail est l’analyse des langages de programmation dynamiques. En particulier, ce travail se concentre sur les programmes écrits en Python, qui peuvent appeler des bibliothèques écrites en C<br>In this thesis, we aim at designing both theoretically and experimentally methods for the automatic detection of potential bugs in software – or the proof of the absence thereof. This detection is done statically by analyzing programs’ source code without running them. We rely on the abstract interpretation framework to derive sound, computable semantics. In particular, we focus on analyzing dynamic programming languages. The target of this work is the analysis of Python programs combined with native C libraries
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Huth, Jacob. "Modelling Aging in the Visual System & The Convis Python Toolbox." Electronic Thesis or Diss., Sorbonne université, 2018. http://www.theses.fr/2018SORUS140.
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Dans cette thèse, nous étudions les processus de vieillissement dans le système visuel à partir d’une perspective de modélisation computationnelle. Nous passons en revue les phénomènes de vieillissement neuronal, les changements fondamentaux du vieillissement et les mécanismes possibles qui peuvent relier les causes et les effets. Les hypothèses que nous formulons à partir de cette revue sont : l’hypothèse de bruit d’entrée, l’hypothèse de plasticité, l’hypothèse de matière blanche et l’hypothèse d’inhibition. Puisque l’hypothèse de bruit d’entrée a la possibilité d’expliquer un certain nombre de phénomènes de vieillissement à partir d’une prémisse très simple, nous nous concentrons principalement sur cette théorie. Puisque la taille et l’organisation des champs récepteurs est importante pour la perception et change à un âge élevé, nous avons développé une théorie sur l’interaction entre le bruit et la structure des champs récepteurs. Nous proposons ensuite la STDP comme mécanisme possible qui pourrait changer la taille du champ récepteur en réponse au bruit d’entrée. Dans deux chapitres distincts, nous examinons les approches pour modéliser les données neurales et les données psychophysiques respectivement. Dans ce processus, nous examinons respectivement un mécanisme de contrôle du gain de contraste et un modèle cortical simplifié. Enfin, nous présentons convis, une boîte à outils Python pour la création de modèles de vision convolutionnelle, qui a été développée lors de cette thèse. convis peut mettre en œuvre les modèles les plus importants utilisés actuellement pour modéliser les réponses des cellules ganglionnaires rétiniennes et des cellules des corticales inférieures (V1/V2)<br>In this thesis we investigate aging processes in the visual system from a computational modelling perspective. We give a review about neural aging phenomena, basic aging changes and possible mechanisms that can connect causes and effects. The hypotheses we formulate from this review are: the input noise hypothesis, the plasticity hypothesis, the white matter hypothesis and the inhibition hypothesis. Since the input noise hypothesis has the possibility to explain a number of aging phenomena from a very simple premise, we focus mainly on this theory. Since the size and organization of receptive fields is important for perception and is changing in high age, we developed a theory about the interaction of noise and receptive field structure. We then propose spike-time dependent plasticity (STDP) as a possible mechanism that could change receptive field size in response to input noise. In two separate chapters we investigate the approaches to model neural data and psychophysical data respectively. In this process we examine a contrast gain control mechanism and a simplified cortical model respectively. Finally, we present convis, a Python toolbox for creating convolutional vision models,which was developed during the studies for this thesis. convis can implement the most important models used currently to model responses of retinal ganglion cells and cells in the lower visual cortices (V1 and V2)
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Bleuzé, Alexandre. "Transfert d'apprentissage intra et inter sujets en interfaces cerveau-machine non-invasives." Electronic Thesis or Diss., Université Grenoble Alpes, 2023. http://www.theses.fr/2023GRALS057.
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Une interface cerveau-ordinateur (ICO) désigne un système de liaison directe entre un cerveau et un ordinateur, permettant à un individu d’effectuer des tâches sans passer par l’action des nerfs périphériques et des muscles. Ces dernières années les ICO sont devenues de plus en plus intéressantes, surtout dans le secteur de la santé en raison de leur potentiel d'aide aux patients. Elles ont été utilisées pour aider certaines personnes à récupérer leurs fonctions motrices après un accident vasculaire cérébral ou une lésion de la moelle épinière ou encore pour aider les personnes atteintes de maladies dégénératives telles que la sclérose latérale amyotrophique, et qui perdent peu à peu la capacité de contrôler leurs membres puis de communiquer. Un autre facteur qui ajoute à l'attrait des ICO est leur potentiel d'augmentation des capacités des personnes en bonne santé dans des domaines tels que le jeux vidéo. Aujourd’hui grâce aux avancées technologiques dans le domaine de la santé, les outils nécessaires à la mise en place d’ICO tels que les électroencéphalogrammes deviennent plus abordables et permettent la multiplication d’expérimentations et de test cliniques donnant alors accès à une grande quantité de données, parfois en accès libre sur internet. Ces données pourraient rendre possible la création de modèles ayant été entraînés à partir des données de nombreuses personnes, permettant à la fois d'augmenter les performances des futurs systèmes tout en réduisant leur temps de calibration. Cela aurait également pour conséquence de permettre l'utilisation de matériel moins couteux pour des performances équivalentes, rendant les ICO plus abordables. Le problème principal aujourd'hui est que les données disponibles en accès libre sont très hétérogènes, que ce soit en termes de qualité, de paradigme ou même simplement de matériel. Pour ces raisons, il est très difficile d’exploiter toutes ces données pour en retirer des caractéristiques communes. Cette thèse a pour objectif de trouver des méthodes permettant d'adapter et d'utiliser les données disponibles en accès libre afin de créer des modèles d'apprentissage automatique très robustes car entraînés sur les données de nombreux sujets. Pour ce faire, on s'intéresse à la géométrie Riemannienne dont l'utilisation dans le cadre des interfaces cerveau-ordinateur a récemment démontré une grande efficacité. Ce travail original porte plus précisément sur le développement de méthodes d’apprentissage par transfert dans l’espace tangent à la variété Riemannienne. Les méthodes proposées ont été évaluées sur un grand nombre de bases de données regroupant plusieurs paradigmes : l’imagerie motrice, les potentiels évoqués de type P300 et les potentiels évoqués visuels stables. Les travaux de cette thèse ont permis de développer une méthode nommée Tangent Space Alignment (TSA) avec laquelle une amélioration globale de la précision de 2,7 % est obtenue par rapport à une méthode riemannienne publiée précédemment, l'analyse de Procrustes Riemannienne (RPA). Une amélioration d’autant plus importante dans le cadre des ICO en P300. Un autre apport de cette thèse à la communauté scientifique est la recherche autour de l’utilisation de sources arbitraires mathématiques dans le cadre d’apprentissage par transfert en ICO. Les travaux poursuivis au cours de cette thèse montrent que peu d'informations sont perdues lors de l'alignement vers cette source arbitraire et étudient l'impact sur la précision entre les sujets, permettant alors d’explorer de nouvelles possibilités d’alignement et de chercher des sources d’alignement normées et mathématiques plutôt que des données de sujet existant qui ne possèdent pas forcément les bonnes propriétés mathématiques pour servir de source de qualité<br>A brain-computer interface (BCI) is a direct link between a brain and a computer, enabling an individual to perform tasks without the need for peripheral nerves or muscles. In recent years, BCIs have become increasingly interesting, especially in the healthcare sector, because of their potential to help patients. They have been used to help some people recover their motor functions after a stroke or spinal cord injury, or to help people with degenerative diseases such as amyotrophic lateral sclerosis, who gradually lose the ability to control their limbs and then communicate. Another factor adding to the appeal of BCIs is their potential to enhance the capabilities of healthy people in areas such as video games. Today, thanks to technological advances in the healthcare field, the tools needed to set up BCIs, such as electroencephalograms, are becoming more affordable, enabling the multiplication of experiments and clinical tests, giving access to a vast amount of data, sometimes freely available on the Internet. This data could make it possible to create models that have been trained from the data of many people, thereby increasing the performance of future systems while reducing their calibration time. This would also enable the use of less expensive hardware for equivalent performance, making BCIs more affordable. The main problem today is that the data available in open access is very heterogeneous, whether in terms of quality, paradigm or even simply hardware. For these reasons, it is very difficult to exploit all this data to extract common features. The aim of this thesis is to find methods for adapting and using open-access data to create machine learning models that are highly robust because they are trained on data from a wide range of subjects. To this end, we are focusing on Riemannian geometry, the use of which in brain-computer interfaces has recently shown to be highly effective. More specifically, this original work focuses on the development of transfer learning methods in the tangent space of the Riemannian variety. The proposed methods have been evaluated on a large number of databases covering several paradigms: motor imagery, P300 evoked potentials and steady-state visual evoked potentials. The work carried out in this thesis has led to the development of a method called Tangent Space Alignment (TSA), which achieves an overall improvement in accuracy of 2.7% over a previously published Riemannian method, Riemannian Procrustes Analysis (RPA). Another contribution of this thesis to the scientific community is research into the use of mathematical arbitrary sources in BCI transfer learning. The work carried out in this thesis shows that little information is lost when aligning to this arbitrary source, and studies the impact on accuracy between subjects, enabling new alignment possibilities to be explored and mathematically normalized alignment sources to be sought, rather than existing subject data which may not possess the right mathematical properties to serve as a quality source
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Larouche, Tremblay François. "Analyse détaillée du fonctionnement interne du schéma de surface CLASS." Master's thesis, Université Laval, 2014. http://hdl.handle.net/20.500.11794/25359.
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Le fonctionnement du schéma de surface canadien CLASS a été analysé en détail, basé sur une démarche de rétroconception. L’impact des multiples variables d’états du modèle sur les termes des bilans énergétique et hydrique a été expliqué. La valeur des albédos et des transmissivités de la canopée augmente en fin de saison lorsque la canopée devient moins dense. Donc, le rayonnement au sol augmente alors que celui à la canopée diminue. La résistance de couche limite de la feuille ralentit les transferts de chaleur sensible et latente à la canopée durant le jour, mais n’a aucune influence la nuit. La résistance aérodynamique au transfert de chaleur est plus élevée le jour que la nuit. Elle influe sur les flux de chaleur sensible et latente à la canopée. La résistance de surface au transfert de chaleur est très élevée le jour et peu élevée la nuit. Elle influe sur les flux de chaleur sensible et latente au sol. La résistance stomatale est très grande la nuit. Elle freine le transfert de chaleur latente durant le jour et n’a aucune influence sur les flux de chaleur sensible. Finalement, on a observé de grandes fluctuations de température et de teneur en eau dans les deux premières couches de sol. Tandis que la troisième couche de sol a montré une réaction très lente aux précipitations et aux variations de température à la surface du sol. Les résultats sont supportés d’explications théoriques très détaillées dans la section théorie.<br>Canadian Land Surface Scheme
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Silva, Bruno Hartmann da. "Nano-κ : a Python code for the multiscale modelling of the thermal conductivity". Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0212.
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Les appareils électroniques sont présents dans presque tous les aspects de la société moderne et leur optimisation et leur contrôle sont d'une importance capitale pour le développement de nouvelles technologies. En outre, les préoccupations environnementales relatives à leur efficacité énergétique et à leur durée de vie nécessitent de tester des alternatives qui minimisent l'impact de l'homme sur la nature. Les semi-conducteurs, tels que le silicium (Si) et le germanium (Ge), sont l'un des matériaux les plus couramment utilisés dans les nanodispositifs électroniques. Dans ce contexte, l'étude des phonons, quanta de vibration du réseau cristallin, qui sont les principaux vecteurs de l'énergie thermique dans les semi-conducteurs, suscite une forte motivation. À l'échelle macroscopique, les propriétés des matériaux telles que la conductivité thermique sont généralement considérées comme indépendantes des conditions de bord. Ce n'est pas le cas à l'échelle nanométrique, où chaque mode de vibration du matériau peut se comporter différemment en raison de la configuration géométrique. Cela nécessite un calcul plus détaillé pour comprendre comment les paramètres géométriques affectent la capacité du nanodispositif à conduire la chaleur. Il est important de comprendre la conduction de la chaleur à l'échelle nanométrique pour éviter la surchauffe du système et pour comprendre comment la température affecte ses performances électriques. Les outils informatiques pourraient fournir des informations précieuses pour comprendre ces effets. En fait, plusieurs travaux ont déjà utilisé des calculs numériques pour comprendre le comportement thermique des nanodispositifs, mais généralement avec des codes internes qui ne sont pas ouverts à la communauté. Dans ce contexte, cette thèse présente Nano-κ, un code Python pour résoudre l'équation de transport de Boltzmann (BTE) dans les nanodispositifs en utilisant la méthode Monte Carlo avec des données ab initio en entrée. Tout d'abord, la théorie du transport des phonons et sa mise en œuvre dans Nano-κ sont discutées. Ensuite, une analyse de sensibilité est réalisée pour vérifier l'effet des principaux paramètres de simulation sur la conductivité thermique estimée. La conductivité thermique calculée par Nano-κ est ensuite comparée aux résultats de la littérature dans plusieurs contextes de couches minces et de nanofils, qui montrent en général une bonne concordance. En outre, une géométrie arbitraire est simulée dans deux cas différents, démontrant la flexibilité et la cohérence d'Nano-κ pour fournir de bonnes estimations du transfert de chaleur dans les nanodispositifs. La thèse conclut en suggérant des pistes d'amélioration possibles pour les travaux futurs<br>Electronic devices are present in almost every aspect of modern society and their optimisation and control is of paramount importance in the development of new technologies. In addition, environmental concerns about their energy efficiency and lifetime require the testing of alternatives that minimise human impact on nature. One of the most common materials used in electronic nanodevices is semiconductors, such as silicon (Si) and germanium (Ge). In this context, there is a strong motivation to study phonons, quanta of crystal lattice vibration, which are the main carriers of thermal energy in semiconductors. At the macroscale, material properties such as thermal conductivity are usually considered to be independent of boundary conditions. This is not the case at the nanoscale, where each vibrational mode of the material can behave differently due to the geometric configuration. This requires a more detailed calculation to understand how geometric parameters affect the ability of the nanodevice to conduct heat. Understanding heat conduction at the nanoscale is important to avoid overheating the system and to understand how temperature affects its electrical performance. Computational tools could efficiently provide great insights to understand these effects. In fact, several works have already used numerical calculations to understand the thermal behaviour of nanodevices, but usually with in-house codes that are not open to the community. In this context, this thesis presents Nano-κ, a Python code to solve the Boltzmann transport equation (BTE) in nanodevices using the Monte Carlo method with ab initio data as input. First, the theory behind phonon transport and its computational implementation in Nano-κ is discussed. Then, a sensitivity analysis is performed to verify the effect of the main simulation parameters on the estimated thermal conductivity. The thermal conductivity calculated by Nano-κ is then compared with results from the literature in several thin film and nanowire settings, which in general show good agreement. In addition, an arbitrary geometry is simulated in two different cases, demonstrating Nano-κ's flexibility and consistency in providing good estimates of heat transfer in nanodevices. The thesis concludes by suggesting possible avenues for improvement in future work
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Hold-Geoffroy, Yannick. "SCOOP : cadriciel de calcul distribué générique." Master's thesis, Université Laval, 2015. http://hdl.handle.net/20.500.11794/25711.
Full textAbstract:
Ce document présente SCOOP, un nouveau cadriciel Python pour la distribution automatique de hiérarchies de tâches dynamiques axé sur la simplicité. Une hiérarchie de tâches réfère à des tâches qui peuvent récursivement générer un nombre arbitraire de sous-tâches. L’infrastructure de calcul sous-jacente consiste en une simple liste de ressources de calcul. Le cas d’utilisation typique est l’exécution d’un programme principal sous la tutelle du module SCOOP, qui devient alors la tâche racine pouvant générer des sous-tâches au travers de l’interface standard des « futures » de Python. Ces sous-tâches peuvent elles-mêmes générer d’autres sous-sous-tâches, etc. La hiérarchie de tâches complète est dynamique dans le sens où elle n’est potentiellement pas entièrement connue jusqu’à la fin de l’exécution de la dernière tâche. SCOOP distribue automatiquement les tâches parmi les ressources de calcul disponibles en utilisant un algorithme de répartition de charge dynamique. Une tâche n’est rien de plus qu’un objet Python pouvant être appelé en conjonction avec ses arguments. L’utilisateur n’a pas à s’inquiéter de l’implantation du passage de message ; toutes les communications sont implicites.<br>This paper presents SCOOP, a new Python framework for automatically distributing dynamic task hierarchies focused on simplicity. A task hierarchy refers to tasks that can recursively spawn an arbitrary number of subtasks. The underlying computing infrastructure consists of a simple list of resources. The typical use case is to run the user’s main program under the umbrella of the SCOOP module, where it becomes a root task that can spawn any number of subtasks through the standard “futures” API of Python, and where these subtasks may themselves spawn other subsubtasks, etc. The full task hierarchy is dynamic in the sense that it is unknown until the end of the last running task. SCOOP automatically distributes tasks amongst available resources using dynamic load balancing. A task is nothing more than a Python callable object in conjunction with its arguments. The user need not worry about message passing implementation details; all communications are implicit.
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Combrisson, Etienne. "Décodage des intentions et des exécutions motrices : étude du rôle des oscillations cérébrales via l’apprentissage machine et développement d’outils open-source." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE1327/document.
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L'exécution d'un simple mouvement est associée à des modulations complexes de l'activité oscillatoire du cerveau. Toutefois, notre compréhension du rôle spécifique des composantes de phase, d'amplitude ou de couplage phase-amplitude (PAC) durant la préparation et l'exécution motrice est encore partielle. La première partie de cette thèse traite de cette question en analysant des données d'EEG intracrânien obtenues chez des sujets épileptiques effectuant une tâche center out différée. Les outils d'apprentissage machine ont permis d'identifier des marqueurs neuronaux propres aux états moteur ou aux directions de mouvement. En plus du rôle déjà bien connu de la puissance spectrale, cette approche dictée par les données (data-driven) a identifié une implication importante de la composante de phase basse fréquence ainsi que du PAC dans les processus neuronaux de la préparation et de l'exécution motrice. En plus de cet apport empirique, une importante partie de ce travail de thèse a consisté à implémenter des outils d'analyse et de visualisation de données électrophysiologiques. Plusieurs utilitaires ont été conçus spécifiquement : une toolbox dédiée à l'extraction et à la classification de marqueurs neuronaux (Brainpipe), des outils de calcul de PAC modulaire basé sur des tenseurs (Tensorpac) ainsi qu'un ensemble d'interfaces graphiques dédiées à la visualisation de données cérébrales (Visbrain). Ces recherches auront permis de mieux comprendre le rôle des oscillations neuronales lors de comportements dirigés et met également à disposition un ensemble d'outils efficaces et libres permettant à la communauté scientifique de répliquer et d'étendre ces recherches<br>The execution of a motor task is associated with complex patterns of oscillatory modulations in the brain. However, the specific role of oscillatory phase, amplitude and phase-amplitude coupling (PAC) across the planning and execution stages of goal-directed motor behavior is still not yet fully understood. The aim of the first part of this PhD thesis was to address this question by analyzing intracranial EEG data recorded in epilepsy patients during the performance of a delayed center-out task. Using machine learning, we identified functionally relevant oscillatory features via their accuracy in predicting motor states and movement directions. In addition to the established role of oscillatory power, our data-driven approach revealed the prominent role of low-frequency phase as well as significant involvement of PAC in the neuronal underpinnings of motor planning and execution. In parallel to this empirical research, an important portion of this PhD work was dedicated to the development of efficient tools to analyze and visualize electrophysiological brain data. These packages include a feature extraction and classification toolbox (Brainpipe), modular and tensor-based PAC computation tools (Tensorpac) and a versatile brain data visualization GUI (Visbrain). Taken together, this body of research advances our understanding of the role of brain oscillations in goal-directed behavior, and provides efficient open-source packages for the scientific community to replicate and extend this research
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Häggholm, Petter. "PyRemote : object mobility in the Python programming language." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/31573.
Full textAbstract:
The current trend in computation is one of concurrency and multiprocessors. Large
supercomputers have long been eclipsed in popularity by cheaper clusters of small
computers. In recent years, desktop processors with multiple cores have become commonplace. A plethora of languages, tools, and techniques for dealing with concurrency already exist. Where concurrency and multiprocessors meet modern,
highly dynamic languages, however, is uncharted territory.
Traditional distributed systems, however complex, tend to be simplified by assumptions of type consistency. Even in systems where types and not merely instances and primitive objects can be serialised and distributed, it is usually the case that such types are assumed to be static. The Python programming language, as an example of a modern language with highly dynamic types, presents novel challenges, in that classes may be altered at runtime, both through the addition, removal, or modification of attributes such as member variables and methods, and through modifications to the type's inheritance hierarchy.
This thesis presents a system called PyRemote which aims to explore some of the issues surrounding type semantics in this environment.<br>Science, Faculty of<br>Computer Science, Department of<br>Graduate
Books on the topic "Langage Python"
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Lutz, Mark. Python: Pocket Reference. 3rd ed. Edited by Jonathan Gennick. O’Reilly Media, 2005.
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Ziadé, Tarek. Programmation Python: Conception et optimisation. 2nd ed. Eyrolles, 2009.
Find full textBook chapters on the topic "Langage Python"
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Browning, J. Burton, and Marty Alchin. "Python Language Moratorium." In Pro Python. Apress, 2014. http://dx.doi.org/10.1007/978-1-4842-0334-7_18.
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Cannon, Brett, Jesse Noller, and Guido van Rossum. "Python Language Moratorium." In Pro Python. Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-2758-8_18.
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Gupta, Pramod, and Anupam Bagchi. "Python Language Basics." In Essentials of Python for Artificial Intelligence and Machine Learning. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-43725-0_3.
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Nakao, Masahiro. "Mixed-Language Programming with XcalableMP." In XcalableMP PGAS Programming Language. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7683-6_5.
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AbstractThis chapter presents the mixed-language programming with XcalableMP and other programming languages. It is supported by the linkage functions between XcalableMP and MPI library. We also demonstrate how to call XcalableMP program from Python program (M. Nakao et al., Linkage of XcalableMP and Python languages for high productivity on HPC cluster system, Proceedings of Workshops of HPC Asia, No .9, pp.39–47, 2018).
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Köhl, Maximilian A., Michaela Klauck, and Holger Hermanns. "Momba: JANI Meets Python." In Tools and Algorithms for the Construction and Analysis of Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72013-1_23.
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AbstractJANI-model [6] is a model interchange format for networks of interacting automata. It is well-entrenched in the quantitative model checking community and allows modeling a variety of systems involving concurrency, probabilistic and real-time aspects, as well as continuous dynamics. Python is a general purpose programming language preferred by many for its ease of use and vast ecosystem. In this paper, we present Momba, a flexible Python framework for dealing with formal models centered around the JANI-model format and formalism. Momba strives to deliver an integrated and intuitive experience for experimenting with formal models making them accessible to a broader audience. To this end, it provides a pythonic interface for model construction, validation, and analysis. Here, we demonstrate these capabilities.
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Dhaliwal, C. K., Poonam Rana, and T. P. S. Brar. "Introduction to Python Language." In Python Programming. CRC Press, 2024. http://dx.doi.org/10.1201/9781032691053-1.
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Mehare, Hussam Bin, Jishnu Pillai Anilkumar, and Naushad Ahmad Usmani. "The Python Programming Language." In A Guide to Applied Machine Learning for Biologists. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-22206-1_2.
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Kumar, Sunil. "Introduction to Python Language." In Python for Accounting and Finance. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-54680-8_2.
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Schäfer, Christoph. "Overview of the Programming Language Python." In Quickstart Python. Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-33552-6_1.
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Danial, Albert. "Language Basics." In Python for MATLAB Development. Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-7223-7_3.
Full textConference papers on the topic "Langage Python"
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Carter, H., Jason Rupert, Alexander Chan, and Chris Vinegar. "Concerns with using Python in Machine Learning Flight Critical Applications." In Vertical Flight Society 79th Annual Forum & Technology Display. The Vertical Flight Society, 2023. http://dx.doi.org/10.4050/f-0079-2023-18015.
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Python is a programming language that is proving irresistible to the Machine Learning development community. The characteristics that make it irresistible may not be well suited for flight critical applications, e.g., Python is an interpreted programming language reliant upon a virtual machine to execute bytecode. Programming languages used in flight critical applications have higher assurance expectations than non-flight critical applications. For aviation applications, Python may be appropriate for the development of Machine Learning models, but Python does not appear to be appropriate for the implementation of those Machine Learning models for deployment on flight critical applications. This paper explores concerns for using Python in those applications and offers potential courses of action to alleviate these concerns: (1) certify/qualify/mature Python, (2) transition from development in Python to implementation in a certified/qualified/maturity programming language, or (3) development and implementation in an environment with certification/qualification/maturity pedigree.
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Reiss, Frederick, Bryan Cutler, and Zachary Eichenberger. "Natural Language Processing with Pandas DataFrames." In Python in Science Conference. SciPy, 2021. http://dx.doi.org/10.25080/majora-1b6fd038-006.
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Singh, Jyotika. "Social Media Analysis using Natural Language Processing Techniques." In Python in Science Conference. SciPy, 2021. http://dx.doi.org/10.25080/majora-1b6fd038-009.
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Chapman, Brian, and Jeannie Irwin. "Python as a First Programming Language for Biomedical Scientists." In Python in Science Conference. SciPy, 2015. http://dx.doi.org/10.25080/majora-7b98e3ed-002.
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Красноусов, Виктор Михайлович, Леонид Вячеславович Букреев, Георигий Андреевивич Шпаковский, Евгений Романович Калюжный, and Наталья Вячеславовна Зариковская. "MOBILE APPLICATIONS FOR THE ANDROID OPERATING SYSTEM: DEVELOPMENT TECHNOLOGIES." In Сборник избранных статей по материалам научных конференций ГНИИ "Нацразвитие" (Санкт-Петербург, Август 2021). Crossref, 2021. http://dx.doi.org/10.37539/aug298.2021.28.84.027.
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В статье рассмотрены технологии, используемые для реализации мобильных приложений для платформы Android, на языке программирования Kotlin и архитектуры MVVM, а также реализации их серверной части на языке программирования Python. The article discusses technologies for implementing an application for the Android platform in the Kotlin and MVVM programming languages, as well as the implementation of the server side in the Python programming language.
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Jin, Eric, and Yu Sun. "An Algorithm-Adaptive Source Code Converter to Automate the Translation from Python to Java." In 5th International Conference on Computer Science and Information Technology (COMIT 2021). Academy and Industry Research Collaboration Center (AIRCC), 2021. http://dx.doi.org/10.5121/csit.2021.111719.
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In the fields of computer science, there exist hundreds of different programming languages. They often have different usage and strength but also have a huge number of overlapping abilities [1]. Especially the kind of general-purpose coding language that is widely used by people, for example Java, Python and C++ [2]. However, there is a lack of comprehensive methods for the conversion for codes from one language to another [3], making the task of converting a program in between multiple coding languages hard and inconvenient. This paper thoroughly explained how my team designs a tool that converts Python source code into Java which has the exact same function and features. We applied this converter, or transpiler, to many Python codes, and successfully turned them into Java codes. Two qualitative experiments were conducted to test the effectiveness of the converter. 1. Converting Python solutions of 5 United States Computer Science Olympic (USACO) problems into Java solutions and conducting a qualitative evaluation of the correctness of the produced solution; 2. converting codes of various lengths from 10 different users to test the adaptability of this converter with randomized input. The results show that this converter is capable of an error rate less than 10% out of the entire code, and the translated code can perform the exact same function as the original code.
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Qi, Peng, Yuhao Zhang, Yuhui Zhang, Jason Bolton, and Christopher D. Manning. "Stanza: A Python Natural Language Processing Toolkit for Many Human Languages." In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations. Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.acl-demos.14.
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Singh, Gurpartap, Anup Lal Yadav, and Satbir S Sehgal. "Sign language recognition Using Python." In 2022 International Conference on Cyber Resilience (ICCR). IEEE, 2022. http://dx.doi.org/10.1109/iccr56254.2022.9996001.
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Dobesova, Zdena. "Programming language Python for data processing." In 2011 International Conference on Electrical and Control Engineering (ICECE). IEEE, 2011. http://dx.doi.org/10.1109/iceceng.2011.6057428.
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Drozd, Aleksandr, Anna Gladkova, and Satoshi Matsuoka. "Python, performance, and natural language processing." In the 5th Workshop. ACM Press, 2015. http://dx.doi.org/10.1145/2835857.2835858.
Full textReports on the topic "Langage Python"
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Zhu, Minjie, and Michael Scott. Fluid-Structure Interaction and Python-Scripting Capabilities in OpenSees. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, 2019. http://dx.doi.org/10.55461/vdix3057.
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Building upon recent advances in OpenSees, the goals of this project are to expand the framework’s Python scripting capabilities and to further develop its fluid–structure interaction (FSI) simulation capabilities, which are based on the particle finite-element method (PFEM). At its inception, the FSI modules in OpenSees were based on Python scripting. To accomplish FSI simulations in OpenSees, Python commands have been added for a limited number of pre-existing element and material commands, e.g., linear-elastic triangle elements and beam–column elements with Concrete01/Steel01 fiber sections. Incorporation of hundreds of constitutive models and element formulations under the Python umbrella for FSI and general OpenSees use remain to be done. Although the original scripting language, Tcl, in OpenSees is string based, powerful, and easy to learn, it is not suitable for mathematical computations. Recent trends in scripting languages for engineering applications have embraced more general, scientific languages such as Python, which has evolved to a large community with numerous libraries for numerical computing, data analysis, scientific visualization, and web development. These libraries can be utilized with the FSI simulation for tsunami analysis. Extending OpenSees to Python will help OpenSees keep pace with new scripting developments from the scientific computing community and make the framework more accessible to graduate students, who likely have learned Python as undergraduates.
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Prasad, Jayanti. Large Language Models: AI Foundations and Applications in Python. Instats Inc., 2023. http://dx.doi.org/10.61700/85rfezw01y0q9521.
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This 5-day workshop provides a comprehensive understanding of large language models, their AI foundations, and applications in Python. Designed for PhD students, professors, and professional researchers, the seminar offers hands-on coding sessions, case studies, and discussions on the future of large language models in academic research.
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Kohler, Karsten. Teaching macroeconomics with an open-source online model simulation in R and Python. The Economics Network, 2024. http://dx.doi.org/10.53593/n3917a.
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Saltus, Christina, Todd Swannack, and S. McKay. Geospatial Suitability Indices Toolbox (GSI Toolbox). Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41881.
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Habitat suitability models are widely adopted in ecosystem management and restoration, where these index models are used to assess environmental impacts and benefits based on the quantity and quality of a given habitat. Many spatially distributed ecological processes require application of suitability models within a geographic information system (GIS). Here, we present a geospatial toolbox for assessing habitat suitability. The Geospatial Suitability Indices (GSI) toolbox was developed in ArcGIS Pro 2.7 using the Python® 3.7 programming language and is available for use on the local desktop in the Windows 10 environment. Two main tools comprise the GSI toolbox. First, the Suitability Index Calculator tool uses thematic or continuous geospatial raster layers to calculate parameter suitability indices based on user-specified habitat relationships. Second, the Overall Suitability Index Calculator combines multiple parameter suitability indices into one overarching index using one or more options, including: arithmetic mean, weighted arithmetic mean, geometric mean, and minimum limiting factor. The resultant output is a raster layer representing habitat suitability values from 0.0 to 1.0, where zero is unsuitable habitat and one is ideal suitability. This report documents the model purpose and development as well as provides a user’s guide for the GSI toolbox.
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Liu, X., Z. Chen, and S. E. Grasby. Using shallow temperature measurements to evaluate thermal flux anomalies in the southern Mount Meager volcanic area, British Columbia, Canada. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/330009.
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Geothermal is a clean and renewable energy resource. However, locating where elevated thermal gradient anomalies exist is a significant challenge when trying to assess potential resource volumes during early exploration of a prospective geothermal area. In this study, we deployed 22 temperature probes in the shallow subsurface along the south flank of the Mount Meager volcanic complex, to measure the transient temperature variation from September 2020 to August 2021. In our data analysis, a novel approach was developed to estimate the near-surface thermal distribution, and a workflow and code with python language have been completed for the thermal data pre-processing and analysis. The long-term temperature variation at different depths can be estimated by modelling, so that the relative difference of deducing deeper geothermal gradient anomalies can be assessed. Our proposed inversion and simulation methods were applied to calculating the temperature variation at 2.0 meters depth. The results identified a preferred high thermal flux anomalous zone in the south Mount Meager area. By combining with previous studies, the direct analysis and estimation of anomalous thermal fields based on the collected temperature data can provide a significant reference for interpretation of the regional thermal gradient variation.
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Saltus, Christina, S. McKay, and Todd Swannack. Geospatial suitability indices (GSI) toolbox : user's guide. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45128.
Full textAbstract:
Habitat suitability models have been widely adopted in ecosystem management and restoration to assess environmental impacts and benefits according to the quantity and quality of a given habitat. Many spatially distributed ecological processes require application of suitability models within a geographic information system (GIS). This technical report presents a geospatial toolbox for assessing habitat suitability. The geospatial suitability indices (GSI) toolbox was developed in ArcGIS Pro 2.7 using the Python 3.7 programming language and is available for use on the local desktop in the Windows 10 environment. Two main tools comprise the GSI toolbox. First, the suitability index (SIC) calculator tool uses thematic or continuous geospatial raster layers to calculate parameter suitability indices using user-specified habitat relationships. Second, the overall suitability index calculator (OSIC) combines multiple parameter suitability indices into one overarching index using one or more options, including arithmetic mean, weighted arithmetic mean, geometric mean, and minimum limiting factor. The result is a raster layer representing habitat suitability values from 0.0–1.0, where zero (0) is unsuitable habitat and one (1) is ideal suitability. This report documents the model purpose and development and provides a user’s guide for the GSI toolbox.
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Тарасова, Олена Юріївна, and Ірина Сергіївна Мінтій. Web application for facial wrinkle recognition. Кривий Ріг, КДПУ, 2022. http://dx.doi.org/10.31812/123456789/7012.
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Facial recognition technology is named one of the main trends of recent years. It’s wide range of applications, such as access control, biometrics, video surveillance and many other interactive humanmachine systems. Facial landmarks can be described as key characteristics of the human face. Commonly found landmarks are, for example, eyes, nose or mouth corners. Analyzing these key points is useful for a variety of computer vision use cases, including biometrics, face tracking, or emotion detection. Different methods produce different facial landmarks. Some methods use only basic facial landmarks, while others bring out more detail. We use 68 facial markup, which is a common format for many datasets. Cloud computing creates all the necessary conditions for the successful implementation of even the most complex tasks. We created a web application using the Django framework, Python language, OpenCv and Dlib libraries to recognize faces in the image. The purpose of our work is to create a software system for face recognition in the photo and identify wrinkles on the face. The algorithm for determining the presence and location of various types of wrinkles and determining their geometric determination on the face is programmed.
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Sladen, W. E., R. J. H. Parker, P. D. Morse, S V Kokelj, and S. L. Smith. Geomorphic feature inventory along the Dempster and Inuvik to Tuktoyaktuk highway corridor, Yukon and Northwest Territories. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329969.
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Thaw of permafrost and associated ground ice melt can reduce ground stability, modify terrain, and reconfigure drainage patterns affecting terrestrial and aquatic ecosystems and presenting challenges to northern infrastructure and societies. The integrity of ground-based transportation infrastructure is critical to northern communities. Geomorphic features can indicate ground ice presence and thaw susceptibility. This Geological Survey of Canada Open File presents the digital georeferenced database of landforms identified in continuous permafrost terrain using high-resolution satellite imagery. The database is for a 10 km-wide corridor centered on the Dempster and Inuvik-Tuktoyaktuk highways. This 875 km-long transect traverses a variety of geological and physiographic terrain types, including glaciated and non-glaciated terrain, in the northcentral Yukon and northwestern Northwest Territories, where variation in climate, relief, ecology, and disturbance have produced a variety of periglacial conditions. We identified geomorphic features in high-resolution (0.6 m) satellite imagery visualized in 3D, and digitized them in ArcGIS. We used custom Python scripts to populate the attributes for each geomorphic feature. A total of 8746 features were mapped by type and categorized within three main classes: hydrological (n = 1188), mass movement (n = 2435), and periglacial (n = 5123). Features were identified at 1:10 000 and mapped at 1:5000. This report presents the geospatial database in ESRI shapefile, Keyhole Markup Language (KML), and comma-delineated formats.
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Mbani, Benson, Timm Schoening, and Jens Greinert. Automated and Integrated Seafloor Classification Workflow (AI-SCW). GEOMAR, 2023. http://dx.doi.org/10.3289/sw_2_2023.
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The Automated and Integrated Seafloor Classification Workflow (AI-SCW) is a semi-automated underwater image processing pipeline that has been customized for use in classifying the seafloor into semantic habitat categories. The current implementation has been tested against a sequence of underwater images collected by the Ocean Floor Observation System (OFOS), in the Clarion-Clipperton Zone of the Pacific Ocean. Despite this, the workflow could also be applied to images acquired by other platforms such as an Autonomous Underwater Vehicle (AUV), or Remotely Operated Vehicle (ROV). The modules in AI-SCW have been implemented using the python programming language, specifically using libraries such as scikit-image for image processing, scikit-learn for machine learning and dimensionality reduction, keras for computer vision with deep learning, and matplotlib for generating visualizations. Therefore, AI-SCW modularized implementation allows users to accomplish a variety of underwater computer vision tasks, which include: detecting laser points from the underwater images for use in scale determination; performing contrast enhancement and color normalization to improve the visual quality of the images; semi-automated generation of annotations to be used downstream during supervised classification; training a convolutional neural network (Inception v3) using the generated annotations to semantically classify each image into one of pre-defined seafloor habitat categories; evaluating sampling strategies for generation of balanced training images to be used for fitting an unsupervised k-means classifier; and visualization of classification results in both feature space view and in map view geospatial co-ordinates. Thus, the workflow is useful for a quick but objective generation of image-based seafloor habitat maps to support monitoring of remote benthic ecosystems.
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Le Béchec, Mariannig, Aline Bouchard, Philippe Charrier, Claire Denecker, Gabriel Gallezot, and Stéphanie Rennes. State of open science practices in france (SOSP-FR). Ministère de l'enseignement supérieur et de la recherche, 2022. http://dx.doi.org/10.52949/5.
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L’enquête State of Open Science Practices in France (SOSP-FR) a été conduite entre juin 2020 et septembre 2020. Elle a pour but d’interroger les pratiques des outils numé- riques et autour des données de la recherche dans les communautés scientifiques françaises. Le questionnaire se compose de 38 questions réparties en 9 thématiques. Les questions portent sur des pratiques déjà établies et des pratiques ou usages émer- gents comme l’open peer review ou les articles de données dits data paper. Le nombre de répondants est de 1089, permettant d’interroger une répartition disciplinaire, genrée et statutaire assez représentative de l’état de l’emploi dans l’enseignement supérieur et de recherche en France. Dans l’enquête, le focus sur le contexte de travail des répondants, qualifié de solitaire ou collectif, met en exergue des différences dans les pratiques, notamment d’archivage des données de recherche et dans les usages, particulièrement d’accès à l’information, aux infrastructures de recherche ou aux outils numériques institutionnels. Les réseaux sociaux des chercheurs semblent influencer les pratiques et les usages liés à la science ouverte en France. En distinguant les usages et les pratiques selon deux perspectives, l’une où la science ouverte est associée à une dimension humaine incluant une ouverture au plus grand nombre des résultats de recherche et l’autre où la dimension technique, incluant l’usage d’un environnement numérique libre et gratuit, est celle qui prévaut, les résultats aboutissent à des distinctions disciplinaires mais également statuaires, générationnelles et au niveau du contexte de travail. Les résultats sont équivalents quant à l’arrivée de nouveaux logiciels et langages de programmation, comme nous avons pu le constater avec R, Excel et Python. L’acculturation aux enjeux de la science ouverte passe par des collectifs, plus accessibles dans des environnements de recherche que dans le couple recherche-enseignement.