Literatura científica selecionada sobre o tema "Langage Python"

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Artigos de revistas sobre o assunto "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
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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 Ment
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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 actu
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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 custo
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Tom, Tiji. "Python Language Libraries." International Journal of Science and Research (IJSR) 10, no. 2 (2021): 1225–27. https://doi.org/10.21275/sr21220134218.

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Zhang, Zejun, Zhenchang Xing, Xiaoxue Ren, Qinghua Lu, and Xiwei Xu. "Refactoring to Pythonic Idioms: A Hybrid Knowledge-Driven Approach Leveraging Large Language Models." Proceedings of the ACM on Software Engineering 1, FSE (2024): 1107–28. http://dx.doi.org/10.1145/3643776.

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Pythonic idioms are highly valued and widely used in the Python programming community. However, many Python users find it challenging to use Pythonic idioms. Adopting rule-based approach or LLM-only approach is not sufficient to overcome three persistent challenges of code idiomatization including code miss, wrong detection and wrong refactoring. Motivated by the determinism of rules and adaptability of LLMs, we propose a hybrid approach consisting of three modules. We not only write prompts to instruct LLMs to complete tasks, but we also invoke Analytic Rule Interfaces (ARIs) to accomplish ta
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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 librari
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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 we
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Teses / dissertações sobre o assunto "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 le
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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
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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 p
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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
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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 ma
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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
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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
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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.

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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-tâ
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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
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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.

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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
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Livros sobre o assunto "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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Lutz, Mark. Learning Python. 2nd ed. O'Reilly, 2003.

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Lutz, Mark. Learning Python. 2nd ed. O'Reilly, 2004.

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Martelli, Alex. Python in a nutshell. O'Reilly, 2003.

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Martelli, Alex. Python in a nutshell. O'Reilly, 2002.

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Ziadé, Tarek. Programmation Python: Conception et optimisation. 2nd ed. Eyrolles, 2009.

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Swinnen, Gérard. Apprendre à programmer avec Python. Éditions O'Reilly, 2004.

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Swinnen, Gérard. Apprendre à programmer avec Python. 2nd ed. O'Reilly, 2005.

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David, Ascher, ed. Learning Python. O'Reilly, 1999.

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Ferguson, Paula, and Laura Lewin, eds. Python In a Nutshell: A Desktop Quick Reference. O'Reilly, 2003.

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Capítulos de livros sobre o assunto "Langage Python"

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Toal, Ray, Sage Strieker, and Marco Berardini. "Python." In Programming Language Explorations, 2nd ed. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003222354-5.

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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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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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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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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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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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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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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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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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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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Trabalhos de conferências sobre o assunto "Langage Python"

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Raj, Mayank, Ashish Devang, Satya Chanchal, and Kavita Saini. "Language Translator Using Python." In 2024 1st International Conference on Advances in Computing, Communication and Networking (ICAC2N). IEEE, 2024. https://doi.org/10.1109/icac2n63387.2024.10894993.

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Kulkarni, Abhishek v., Addanki Ranga Ravindra, Maheswarla Sai Sangeethi, G. Tejdeep Reddy, and Meena Belwal. "Cross Language Compiler Construction From Matlab To Python." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10726222.

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Jiri, Medlen, Bari Emese, and Patrick Medlen. "Leveraging Large Language Models for Python Unit Test." In 2024 IEEE International Conference on Artificial Intelligence Testing (AITest). IEEE, 2024. http://dx.doi.org/10.1109/aitest62860.2024.00020.

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Singh, Gurpartap, Anup Lal Yadav, and Satbir S Sehgal. "Expression of Concern for: Sign language recognition Using Python." In 2022 International Conference on Cyber Resilience (ICCR). IEEE, 2022. http://dx.doi.org/10.1109/iccr56254.2022.10703518.

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Farsi, Farhan, Parnian Fazel, Sepand Haghighi, et al. "ParsiPy: NLP Toolkit for Historical Persian Texts in Python." In Proceedings of the Second Workshop on Ancient Language Processing. Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.alp-1.17.

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Someki, Masao, Kwanghee Choi, Siddhant Arora, et al. "ESPnet-EZ: Python-Only ESPnet For Easy Fine-Tuning And Integration." In 2024 IEEE Spoken Language Technology Workshop (SLT). IEEE, 2024. https://doi.org/10.1109/slt61566.2024.10832148.

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Pandey, Mayank, Naga Sai Shreya Kunda, Kc Pranave, and Meena Belwal. "Transcribing Natural Language to Python Code: A Compiler Based Approach." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10725235.

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Kumar, Raj, Angad Anand, Suryansh Chaudhary, Vikas Phluriya, Shaurya Pathania, and Devanshu Garg. "Integrating Deep Learning and Python for Effective Sign Language Recognition." In 2024 International Conference on Progressive Innovations in Intelligent Systems and Data Science (ICPIDS). IEEE, 2024. https://doi.org/10.1109/icpids65698.2024.00082.

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Zhao, Kunpeng, Shuya Duan, Ge Qiu, Jinyuan Zhai, Mingze Li, and Long Liu. "Python Source Code Vulnerability Detection Based on CodeBERT Language Model." In 2024 7th International Conference on Algorithms, Computing and Artificial Intelligence (ACAI). IEEE, 2024. https://doi.org/10.1109/acai63924.2024.10899694.

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McCormick, Matthew, and Paul Elliott. "ITK-Wasm." In Python in Science Conference. SciPy, 2024. http://dx.doi.org/10.25080/tcfj5130.

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In recent years, WebAssembly (Wasm) has emerged as a widely-supported technology that offers high performance, compact binary size, support for multiple languages, hardware independence, security, and universal platform support, enabling developers to bring near-native speeds and portability to applications for the web and beyond. ITK-Wasm brings WebAssembly’s capabilities to scientific computing by combining the Insight Toolkit (ITK) and WebAssembly to enable high-performance spatial analysis across programming languages and hardware architectures.In the scientific Python ecosystem, ITK-Wasm
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Relatórios de organizações sobre o assunto "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
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May, Trent, Thomas Clement, John Miller, Charles Carleton, Aaron Webber, and Samuel Williams. From research to production : lessons learned and best practices. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49197.

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This paper provides an overview of best practices to assist individuals and teams in transitioning software from a research product into a production environment. The information contained in this paper consists of best practices and lessons learned from an assignment consisting of transitioning a science-based research suite of programs into a more modern software format with appropriate preparations and considerations to be deployed in a production environment. The original software suite was written using both MATLAB and Python programming languages, and the new production version was writt
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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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Zinilli, Antonio. Text Mining in Action: Tools and Techniques using Python. Instats Inc., 2024. http://dx.doi.org/10.61700/k4powzm518m5z1739.

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This seminar provides a comprehensive exploration of text mining techniques using Python, tailored for academic researchers seeking to analyze large textual datasets effectively. Participants will gain hands-on experience with Python libraries and methodologies for natural language processing, sentiment analysis, topic modeling, text classification, and more, enhancing their data analysis capabilities across various disciplines.
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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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Nova Martínez, Manuel Arturo, Carlos Ignacio Torres Londoño, and Yerson Ferney Porras García. Exploring relationships between statistical variables with implementation in Python and R: A practical guide for basic statistics courses. Ediciones Universidad Cooperativa de Colombia, 2024. https://doi.org/10.16925/gcgp.135.

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This document presents the elementary theory for conducting an initial exploratory analysis of a data set using descriptive measures and statistical diagrams, focusing on demonstrating how valuable information about the phenomenon of interest can be extracted through these tools. It includes a comparative analysis of the behavior of certain socioeconomic variables among a sample of professional individuals from the Meta department in Colombia, with implementations in both the R software and the Python language. Based on these concepts and methods, a guided project is developed.
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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 i
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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
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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.

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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 Window
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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 landmar
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