Suchergebnisse - (( (statnett OR stateeeed) python code analysis ) OR ( state python code analysis ))*

Quantifying cross-language code reuse via function-level clone detection

Autoren: Yi Rong Yan Zhou

Quelle: Journal of King Saud University: Computer and Information Sciences, Vol 37, Iss 10, Pp 1-20 (2025)

Schlagwörter: Natural language processing, Code reuse detection, Function-level clone analysis, Java and python source code, Academic plagiarism detection, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1319-1578; https://doaj.org/toc/2213-1248

Zugangs-URL: https://doaj.org/article/0e8d85656442482785bc981b326c25a4

A Study of Large Language Models in Detecting Python Code Violations

Autoren: Hekar A. Mohammed Salih Qusay I. Sarhan

Quelle: ARO-The Scientific Journal of Koya University, Vol 13, Iss 2 (2025)

Schlagwörter: Large language models, Software metrics, Software quality, Static code analysis, Technology, Science

Dateibeschreibung: electronic resource

Relation: https://aro.koyauniversity.org/index.php/aro/article/view/2395; https://doaj.org/toc/2410-9355; https://doaj.org/toc/2307-549X

Zugangs-URL: https://doaj.org/article/a66cf05353b54e19a03b46c0b089d1fc

GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Libraries.

Autoren: Fachada, Nuno Fernandes, Daniel Fernandes, Carlos M. et al.

Quelle: Future Internet. Sep2025, Vol. 17 Issue 9, p412. 28p.

Schlagwörter: *Experimental design, *Quantitative research, Language models, Python programming language, Generative pre-trained transformers, Benchmark problems (Computer science), Code generators

Analyzing LLM-Generated Code According to Four ISO/IEC 5055:2021 Categories

Autoren: Rasmus Krebs Somnath Mazumdar

Quelle: IEEE Access, Vol 13, Pp 202482-202499 (2025)

Schlagwörter: Analysis, ISO, LLMs, maintainability, performance, Python, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/11269792/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/3faae1da4e0b47beb1e1ac9da1ee6b78

Numerical Analyses of a SAW Gas Sensor in a Non-Steady State

Autoren: T. Hejczyk J. Wrotniak P. Powroźnik et al.

Quelle: International Journal of Electronics and Telecommunications, Vol vol. 71, Iss No 4 (2025)

Schlagwörter: gas sensors, numerical modeling, ingebrigtsen’s formula, dmmp, (rr)-p3ht, acoustoelectric analysis (naa), Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Telecommunication, TK5101-6720

Dateibeschreibung: electronic resource

Relation: https://journals.pan.pl/Content/136909/6-5168-Hejczyk_sk.pdf; https://doaj.org/toc/2081-8491; https://doaj.org/toc/2300-1933

Zugangs-URL: https://doaj.org/article/c9d170a1144c4d9f86026066ca8dbfea

GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Libraries

Autoren: Nuno Fachada Daniel Fernandes Carlos M. Fernandes et al.

Quelle: Future Internet, Vol 17, Iss 9, p 412 (2025)

Schlagwörter: large language models, code generation, Python libraries, Information technology, T58.5-58.64

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/1999-5903/17/9/412; https://doaj.org/toc/1999-5903

Zugangs-URL: https://doaj.org/article/0b7290b02eba46929e6de40288c33a7e

Programming models to support data science workflows

Autoren: Ramón-Cortés Vilarrodona, Cristián

Weitere Verfasser: University/Department: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors

Thesis Advisors: Badia Sala, Rosa M. (Rosa Maria), Ejarque Artigas, Jorge

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: Distributed computing, High-performance computing, Data science pipelines, Task-ba workflows, Dataflows, Containers (Computer sicience), COMPSs, PyCOMPSs, AutoParallel, Docker, Àrees temàtiques de la UPC::Informàtica

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/669728
https://dx.doi.org/10.5821/dissertation-2117-330142

Percolation Theory Using Python

Autoren: Malthe-Sørenssen, Anders

Schlagwörter: fractal models, critical phenomena in statistical physics, disordered systems, scaling theory, anomalous diffusion, random media textbook, Statistical physics, Condensed matter physics (liquid state and solid state physics), Cybernetics and systems theory, Engineering applications of electronic, magnetic, optical materials, Mathematical physics, Geophysics

Dateibeschreibung: application/pdf

Relation: Lecture Notes in Physics

Zugangs-URL: https://library.oapen.org/handle/20.500.12657/92326

MoveApps: a serverless no-code analysis platform for animal tracking data.

Autoren: Kölzsch, Andrea Davidson, Sarah C. Gauggel, Dominik et al.

Quelle: Movement Ecology. 7/18/2022, Vol. 10 Issue 1, p1-12. 12p.

Hands-on 3: Introduction to developing Python computational pipelines for predictive machine learning modelling of livestock data.

Autoren: Tulpan, Dan¹

Quelle: Journal of Animal Science. 2024 Supplement, Vol. 102, p68-68. 1/4p.

Schlagworte: Machine learning, Personal computers, Animal science, Data modeling, Python programming language

The state of the late Quaternary megafauna extinction debate: a systematic review and analysis.

Autoren: Stewart, Mathew Peters, Carli Ziegler, Michael J. et al.

Quelle: Frontiers in Mammal Science. 2025, p1-27. 27p.

Integrating multi-modal data fusion approaches for analysis of dairy cattle vocalizations.

Autoren: Jobarteh, Bubacarr Mincu-Iorga, Madalina Gavojdian, Dinu et al.

Quelle: Frontiers in Veterinary Science. 2025, p1-13. 13p.

Continuous automated analysis of facial dynamics of brachycephalic and normocephalic dogs in different contexts.

Autoren: Martvel, George Eretová, Petra Přibylová, Lucie et al.

Quelle: BMC Veterinary Research. 5/24/2025, Vol. 21 Issue 1, p1-13. 13p.

Schlagworte: Emotions in animals, Behavioral assessment, Dog behavior, Facial expression, Artificial intelligence, Dogs

Application of Artificial Intelligence Technologies in Livestock Management.

Alternate Title: Hayvancılıkta Yapay Zekâ Teknolojilerinin Uygulanması.

Autoren: DİLAVER, Hatice DİLAVER, Kamil Fatih

Quelle: Journal of Animal Science & Economics. Jul2025, Vol. 4 Issue 2, p64-74. 11p.

Schlagworte: Natural language processing, Artificial neural networks, Supervised learning, Artificial intelligence, Agriculture

Anna: an open-source platform for real-time integration of machine learning classifiers with veterinary electronic health records.

Autoren: Kong, Chun Yin Vasquez, Picasso Farhoodimoghadam, Makan et al.

Quelle: BMC Veterinary Research. 10/2/2025, Vol. 21 Issue 1, p1-12. 12p.

Schlagworte: Machine learning, Electronic health records, Open source software, Patient care, Veterinary medicine, Diagnosis, Classification algorithms, Synchronization

ORTEGA v1.0: an open-source Python package for context-aware interaction analysis using movement data.

Autoren: Su, Rongxiang Liu, Yifei Dodge, Somayeh

Quelle: Movement Ecology. 3/9/2024, Vol. 12 Issue 1, p1-14. 14p.

TLR2 c.374C>T variant linked to natural resistance against brucellosis in Italian Mediterranean river buffalo.

Autoren: Fulgione, Andrea Gentile, Antonio Iovane, Valentina et al.

Quelle: BMC Veterinary Research. 10/21/2025, Vol. 21 Issue 1, p1-16. 16p.

Schlagworte: Brucellosis, Toll-like receptors, Immune response, Water buffalo, Natural immunity, Case-control method, Single nucleotide polymorphisms, Genomics

Geografische Kategorien: Italy, Campania (Italy)

Analysis of dog movement using a single accelerometer in different body positions—a new approach.

Autoren: Reinstein, Rainer da Silva Pozzobon, Franciéli Mallmann Caye, Pâmela et al.

Quelle: Frontiers in Veterinary Science. 2025, p1-12. 12p.

Sportomics Analyses of the Exercise-Induced Impact on Amino Acid Metabolism and Acute-Phase Protein Kinetics in Female Olympic Athletes.

Autoren: Muniz-Santos, Renan Bassini, Adriana Falcão, Jefferson et al.

Quelle: Nutrients. Oct2024, Vol. 16 Issue 20, p3538. 21p.

ASAS-NANP symposium: mathematical modeling in animal nutrition—Making sense of big data and machine learning: how open-source code can advance training of animal scientists.

Autoren: Brennan, Jameson R. Menendez, III, Hector M. Ehlert, Krista et al.

Quelle: Journal of Animal Science. Jan2023, Vol. 101 Issue 1, p1-11. 11p. 4 Diagrams, 3 Graphs.