Suchergebnisse - (( (staten OR state) python code analysis ) OR ( stateline 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

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

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

Smart Compiler Assistant: An AST based Python Code Analysis

Autoren: Aneesh, Ch Saumik, Gembali Varun, Kvv et al.

Quelle: 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) ; page 1-6

Verfügbarkeit: https://doi.org/10.1109/icccnt61001.2024.10724220
http://xplorestaging.ieee.org/ielx8/10723818/10723316/10724220.pdf?arnumber=10724220

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

Travel times and distances to health services in Australia

Autoren: Michaela Filipcikova Louisa Jorm Sebastiano Barbieri

Quelle: Scientific Data, Vol 13, Iss 1, Pp 1-6 (2025)

Schlagwörter: Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2052-4463

Zugangs-URL: https://doaj.org/article/3f04c331bd41458c8c42e566f2961448

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

Otimização do processo de fabrico e controlo de qualidade na maquinação

Autoren: Oliveira, Tiago Viegas

Schlagwörter: Digitalização, Indústria 4.0, Gestão de processos, Controlo produtivo, Metrologia

Dateibeschreibung: application/pdf

Verfügbarkeit: http://hdl.handle.net/10773/45577

Exploring Methods for Quantifying Expressibility and Entangling Capability of Parameterized Quantum Circuits

Autoren: Mjaaseth, Jørgen

Verfügbarkeit: https://hdl.handle.net/11250/3145867

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

A parametric analysis of CLT wall and outrigger structural system in tall timber buildings

Autoren: Blom, Herman Mørkved Hellem, Sverre Grøttebø Stamatopoulos, Haris et al.

Weitere Verfasser: Blom, Herman Mørkved Hellem, Sverre Grøttebø Stamatopoulos, Haris et al.

Verfügbarkeit: https://hdl.handle.net/11250/3024629

Utilizing Deep Learning and Object-Based Image Analysis to Search for Low-Head Dams in Indiana, USA.

Autoren: Crookston, Brian M. Arnold, Caitlin R.

Quelle: Water (20734441); Mar2025, Vol. 17 Issue 6, p876, 24p

Schlagwörter: IMAGE analysis, WATER supply, DAMS, MODEL validation, LEARNING ability

The AI revolution : demystifying machine learning and neural networks v.3.14

Autoren: Bengtsson, Magnus, Docent

Schlagwörter: Resource Recovery, Resursåtervinning

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-34324

BiGSM: Bayesian inference of gene regulatory network via sparse modelling

Autoren: Qin, Hang Garbulowski, Mateusz Sonnhammer, Erik L. L. et al.

Quelle: Bioinformatics. 41(6)

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-367876
https://doi.org/10.1093/bioinformatics/btaf318

Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images

Autoren: Marini, Niccolo Otalora, Sebastian Podareanu, Damian et al.

Quelle: Frontiers in Computer Science. 3

Schlagwörter: multi-scale approaches, computational pathology, scale detection, classification, segmentation, deep learning

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-209564
https://liu.diva-portal.org/smash/get/diva2:1913229/FULLTEXT01.pdf

Cell-ACDC: a user-friendly toolset embedding state-of-the-art neural networks for segmentation, tracking and cell cycle annotations of live-cell imaging data

Autoren: Padovani, F Mairhörmann, B Falter-Braun, P et al.

Quelle: bioRxiv.

Zugangs-URL: http://kipublications.ki.se/Default.aspx?queryparsed=id:

Modelling the positive and negative interaction between mood and thermal sensation in the built environment using a combined Markov Chain Monte Carlo algorithm and Morris method.

Autoren: Özbey, Mehmet Furkan Turhan, Cihan

Quelle: Building Services Engineering Research & Technology. Nov2025, Vol. 46 Issue 6, p737-752. 16p.

Schlagwörter: *MARKOV chain Monte Carlo, MOOD (Psychology), THERMAL comfort, SENSITIVITY analysis, PSYCHOLOGICAL factors, ENVIRONMENTAL psychology

Measurement and Development for Automated Secure Coding Solutions

Autoren: Frantz, Miles Eugene

Thesis Advisors: Computer Science and#38; Applications, Yao, Danfeng, Rajagopalan, Raj, Meng, Na, Chung, Taejoong Tijay, Brown, Dwayne Christian

Schlagwörter: Large Language Models, Machine Learning, Static Code Analysis, Python, Java, Benchmark

Dateibeschreibung: ETD; application/pdf

Verfügbarkeit: https://hdl.handle.net/10919/121100

Embracing Computer Vision for Diagnostic Maxillofacial Imaging -- An Artificial Intelligence Machine Learning (AIML)Pilot Project.

Autoren: Akadiri, Oladimeji Adeniyi Yarhere, Kesiena Seun

Quelle: Nigerian Medical Journal; 2025, Vol. 66 Issue 3, p973-982, 10p

Schlagwörter: ARTIFICIAL intelligence, MACHINE learning, CLINICAL decision making, DIAGNOSIS, COMPUTER vision, JAWS, DIGITAL health, COMPUTER-assisted image analysis (Medicine)

The Computational Content Analyst : Using Machine Learning to Classify Media Messages

Autoren: Chris J. Vargo

Resource Type: eBook.

Schlagworte: Machine learning

Categories: LANGUAGE ARTS & DISCIPLINES / Communication Studies, SOCIAL SCIENCE / Methodology, SOCIAL SCIENCE / Media Studies