Suchergebnisse - (( (statu OR stat) python code analysis ) OR ( (statny OR stateen) python code analysis ))*

Recurrence Quantification Analysis Based Methodology in Automatic Aerobic Threshold Detection: Applicability and Accuracy across Age Groups, Exercise Protocols and Health Conditions

Autoren: Giovanna Zimatore Cassandra Serantoni Maria Chiara Gallotta et al.

Quelle: Applied Sciences, Vol 14, Iss 20, p 9216 (2024)

Schlagwörter: aerobic transition, heart rate variability, nonlinear time series analysis, python code, athletes, obesity, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2076-3417/14/20/9216; https://doaj.org/toc/2076-3417

Zugangs-URL: https://doaj.org/article/f7b3f6a6e6a84bba9ef80e21fe47cacc

Gistable: Evaluating the Executability of Python Code Snippets on GitHub

Autoren: Horton, Eric Parnin, Chris

Index Begriffe: Computer Science - Software Engineering, text

URL: http://arxiv.org/abs/1808.04919

Economic Impact of Abortions in Dairy Cow Herds.

Autoren: Palma, Osvaldo Plà-Aragonès, Lluís M. Mac Cawley, Alejandro et al.

Quelle: Veterinary Sciences; Jul2025, Vol. 12 Issue 7, p645, 14p

Schlagwörter: ECONOMIC impact, ABORTION, MARKOV processes, PROFITABILITY, MILK yield, DAIRY cattle, ANIMAL health

Reviewing seas of data: Integrating image‐based bio‐logging and artificial intelligence to enhance marine conservation

Autoren: Marianna Chimienti Akiko Kato Vahid Seydi et al.

Quelle: Methods in Ecology and Evolution, Vol 17, Iss 2, Pp 272-290 (2026)

Schlagwörter: artificial intelligence, bio‐logging, computer vision, conservation, marine ecosystems, underwater image, Ecology, QH540-549.5, Evolution, QH359-425

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2041-210X

Zugangs-URL: https://doaj.org/article/6beb54d71e9b454abe815c97a77269dd

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: LANGUAGE models, EXPERIMENTAL design, PYTHON programming language, GENERATIVE pre-trained transformers, QUANTITATIVE research, BENCHMARK problems (Computer science), CODE generators

CLM App: Interlamellar Distance of Pearlite via CLM Revisited and Automated.

Autoren: Zouhar, Martin Mikmeková, Šárka Hovjacký, Jan et al.

Quelle: Materials (1996-1944); Feb2026, Vol. 19 Issue 3, p635, 17p

Schlagwörter: AUTOMATION, IMAGE analysis, QUALITY control, MICROSTRUCTURE

A statistical approach to automated analysis of the low‐contrast object detectability test for the large ACR MRI phantom.

Autoren: Golestani, Ali M. Gee, Julia M.

Quelle: Journal of Applied Clinical Medical Physics; Jul2025, Vol. 26 Issue 7, p1-9, 9p

Schlagwörter: LINEAR statistical models, IMAGING phantoms, QUALITY control, PYTHON programming language, MAGNETIC resonance imaging

NJN: A Dataset for the Normal and Jaundiced Newborns

Autoren: Ahmad Yaseen Abdulrazzak Saleem Latif Mohammed Ali Al-Naji

Quelle: BioMedInformatics, Vol 3, Iss 3, Pp 543-552 (2023)

Schlagwörter: jaundice, hyperbilirubinemia, skin color analysis, NICU, artificial intelligence (AI) techniques, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Computer applications to medicine. Medical informatics, R858-859.7

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2673-7426/3/3/37; https://doaj.org/toc/2673-7426

Zugangs-URL: https://doaj.org/article/0c036b5f61e241169a397ae22ebb195f

CQLLM: A Framework for Generating CodeQL Security Vulnerability Detection Code Based on Large Language Model.

Autoren: Wang, Le Chen, Chan Zhu, Junyi et al.

Quelle: Applied Sciences (2076-3417); Jan2026, Vol. 16 Issue 1, p517, 17p

Schlagwörter: COMPUTER security vulnerabilities, LANGUAGE models, COMPUTER software correctness, SOFTWARE frameworks, PENETRATION testing (Computer security), CODE generators

Regularized Maximum Likelihood Estimation for the Random Coefficients Model in Python.

Autoren: Dunker, Fabian Mendoza, Emil Reale, Marco

Quelle: Mathematics (2227-7390); Dec2025, Vol. 13 Issue 23, p3764, 29p

Schlagwörter: PYTHON programming language, MAXIMUM likelihood statistics, CONSUMPTION (Economics), MATHEMATICAL programming, MULTILEVEL models, SCIENTIFIC computing

An Empirical Evaluation of Ensemble Models for Python Code Smell Detection.

Autoren: Rao, Rajwant Singh Dewangan, Seema Mishra, Alok

Quelle: Applied Sciences (2076-3417); Jul2025, Vol. 15 Issue 13, p7472, 27p

Schlagwörter: ENSEMBLE learning, FEATURE selection, BOOSTING algorithms, PYTHON programming language, COMPUTER software quality control, DESIGN failures, DATA augmentation

Testing an Educational Program to Improve Goals of Care Conversations Between Patients and Their Care Teams

Autoren: National Cancer Institute (NCI)

Quelle: A Randomized Controlled Trial of an Intervention Called "Algorithm-Enabled Patients Activated in Cancer Care Through Teams" (A-PACT) to Improve Goals of Care Communication for People With Cancer

A General Theorem and Proof for the Identification of Composed CFA Models

Autoren: Bee, R. Maximilian Koch, Tobias Eid, Michael

Schlagwörter: article, ScholarlyArticle, ddc:150, confirmatory factor analysis, identification, rank-deficient loading matrix, bifactor models, bifactor ( S - 1 ) \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(S-1)$$\end{document} model, CT-C ( M - 1 ) \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(M-1)$$\end{document} model

Dateibeschreibung: 20 Seiten

Relation: Psychometrika -- 0033-3123 -- 1860-0980

Verfügbarkeit: https://doi.org/10.1007/s11336-023-09933-6
https://nbn-resolving.org/urn:nbn:de:gbv:27-dbt-63137-2
https://www.db-thueringen.de/receive/dbt_mods_00063137
https://www.db-thueringen.de/servlets/MCRFileNodeServlet/dbt_derivate_00065357/s11336-023-09933-6.pdf

Insights and Analysis of Open-source License Violation Risks in LLMs Generated Code.

Autoren: Yibo Wang Ying Wang Yue Yu et al.

Quelle: International Journal of Software & Informatics; 2025, Vol. 15 Issue 2, p145-173, 29p

Schlagwörter: OPEN source software, COPYRIGHT infringement, LANGUAGE models, DATA analytics, CODE generators, INTELLECTUAL property infringement, DETECTION algorithms

Yusuf Suresinin Anlam İlişkileri ve Hikâye Birleşenlerinin Pyhton Kodlu Matematiksel Görselleştirmelerle Tahlili. (Turkish)

Alternate Title: Analysis of the Meaning Relations and Story Components of Surah Yusuf Via Python Coded Mathematical Visualizations. (English)

Autoren: Yücel, Doğan Er, Ülkü Aysel, Metin et al.

Quelle: International Journal of Social Sciences (IJSS) / Uluslararası Sosyal Bilimler Dergisi; 2025, Vol. 9 Issue 41, p1-42, 42p

Schlagwörter: TIME series analysis, THEMATIC maps, GRAPH theory, PYTHON programming language, QUR'ANIC criticism

JDroid: Android malware detection using hybrid opcode feature vector.

Autoren: Arslan, Recep Sinan

Quelle: PeerJ Computer Science; Jul2025, p1-30, 30p

Schlagwörter: MALWARE, MACHINE learning, DATA analytics, INFORMATION technology security, ENSEMBLE learning

Reviews & Products: ANDROID (Operating system)

BSN: Light Curve Modeling and Orbital Evolution of the Total-Eclipse Contact Binary EZ Oct

Autoren: Ababafi, Asma Poro, Atila Tanriver, Mehmet et al.

Schlagwörter: Solar and Stellar Astrophysics

Relation: http://arxiv.org/abs/2512.07372

Verfügbarkeit: http://arxiv.org/abs/2512.07372

Automating fuzz driver generation for deep learning libraries with large language models.

Autoren: Zheng, Tianming Meng, Fanchao Yi, Ping et al.

Quelle: Cybersecurity (2523-3246); 1/4/2026, Vol. 9 Issue 1, p1-21, 21p

Schlagwörter: LANGUAGE models, COMPUTER software testing, TEST systems, STATISTICAL reliability, MECHANIZATION

Mathematical Model of the Software Development Process with Hybrid Management Elements.

Autoren: Semenov, Serhii Tsukur, Volodymyr Molokanova, Valentina et al.

Quelle: Applied Sciences (2076-3417); Nov2025, Vol. 15 Issue 21, p11667, 44p

Schlagwörter: COMPUTER software development, AGILE software development, TELEMETRY, PREDICTION models, INTERDISCIPLINARY research, EPISTEMIC uncertainty, RISK assessment

GE-IA-NAM: gene–environment interaction analysis via imaging-assisted neural additive model.

Autoren: Li, Jingmao Xu, Yaqing Ma, Shuangge et al.

Quelle: Bioinformatics; Sep2025, Vol. 41 Issue 9, p1-9, 9p

Schlagwörter: CANCER research, GENOTYPE-environment interaction, DIAGNOSTIC imaging, DEEP learning, EMPIRICAL research, COMPUTER simulation