Suchergebnisse - (( (stateeeeeeni OR state) python code analysis ) OR ( amastatin python code analysis ))*

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

TESTING THE DYNAMIC EXECUTION OF PYTHON PROGRAM CODE DURING THE CERTIFICATION TESTING (DEVELOPMENT) STAGE IN THE CERTIFICATION SYSTEM OF THE MINISTRY OF DEFENSE OF RUSSIA

Autoren: V.V. Samarov

Quelle: Надежность и качество сложных систем, Iss 2 (2023)

Schlagwörter: certification tests of software products, dynamic code analysis of python programs, control of completeness and lack of redundancy at the level of files and functional objects, code profiling for dynamic analysis, Motor vehicles. Aeronautics. Astronautics, TL1-4050

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2307-4205

Zugangs-URL: https://doaj.org/article/17c480a498a44ff5b1681dc8eb177136

Python API Misuse Mining and Classification Based on Hybrid Analysis and Attention Mechanism.

Autoren: He, Xincheng Liu, Xiaojin Xu, Lei

Quelle: International Journal of Software Engineering & Knowledge Engineering. Oct2023, Vol. 33 Issue 10, p1567-1597. 31p.

Schlagwörter: *COMPUTER software development, *APPLICATION program interfaces, PYTHONS, PYTHON programming language, CLASSIFICATION

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

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

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

Autoren: Tyler Parsotan Sibasish Laha David M. Palmer et al.

Quelle: The Astrophysical Journal. 953(2)

Schlagwörter: Space Radiation

Zugangs-URL: https://ntrs.nasa.gov/citations/20230009620

DeVAIC: A tool for security assessment of AI-generated code.

Autoren: Cotroneo, Domenico De Luca, Roberta Liguori, Pietro

Quelle: Information & Software Technology. Jan2025, Vol. 177, pN.PAG-N.PAG. 1p.

Schlagwörter: *COMPUTER software development, *ARTIFICIAL intelligence, *SECURITY management, CODE generators, SOURCE code

MLtool Python Code

Autoren: Nikolai A Zarkevich Nishan Senanayake Joshua Stuckner et al.

Schlagwörter: Computer Programming and Software

Relation: MLtool: Universal Supervised Machine Learning Tool to Model Tabulated Data

Zugangs-URL: https://ntrs.nasa.gov/citations/20230005458

Risk Model for Metastasis Detection of Neuroblastoma (NB)

Autoren: Shenzhen Children's Hospital The Children's Hospital of Zhejiang University School of Medicine Juan Ma, Associate Chief Physician of the Clinical Laboratory Department

Weitere Verfasser: Shenzhen Children's Hospital The Children's Hospital of Zhejiang University School of Medicine Juan Ma, Associate Chief Physician of the Clinical Laboratory Department

Quelle: Bone Marrow Cytology-based Artificial Intelligence Model for Detection and Prognosis of Neuroblastoma

PLangRec: Deep-learning model to predict the programming language from a single line of code.

Autoren: Rodriguez-Prieto, Oscar Pato, Alejandro Ortin, Francisco

Quelle: Future Generation Computer Systems. May2025, Vol. 166, pN.PAG-N.PAG. 1p.

Schlagwörter: *NATURAL language processing, *PROGRAMMING languages, DEEP learning, WEB-based user interfaces, SOURCE code

A Firm's Operational Risk: Data Set and Empirical Evidence.

Autoren: Astvansh, Vivek Simpson, Joseph J.

Quelle: Manufacturing & Service Operations Management (M&SOM). Jan/Feb2026, Vol. 28 Issue 1, p326-341. 16p.

Schlagwörter: *OPERATIONAL risk, *TRANSFORMER models, *STAKEHOLDER theory, *LEGAL liability, *FINANCIAL disclosure, *EMPIRICAL research, NUMERICAL analysis

Geografische Kategorien: UNITED States

Rapid Development of Interferometric Software Using MIRIAD and Python

Autoren: Williams, Peter K. G. Law, Casey J. Bower, Geoffrey C.

Quelle: Publications of the Astronomical Society of the Pacific, 2012 . 124(916), 624-636.

Zugangs-URL: https://www.jstor.org/stable/10.1086/666604

HGAN4VD: Leveraging Heterogeneous Graph Attention Networks for enhanced Vulnerability Detection.

Autoren: Zhang, Yucheng Ju, Xiaolin Chen, Xiang et al.

Quelle: Computers & Security. Oct2025, Vol. 157, pN.PAG-N.PAG. 1p.

Schlagwörter: DEEP learning, GRAPH neural networks, FEATURE extraction, PENETRATION testing (Computer security)

ChatGPT for Univariate Statistics: Validation of AI-Assisted Data Analysis in Healthcare Research.

Autoren: Ruta, Michael R Gaidici, Tony Irwin, Chase et al.

Quelle: Journal of Medical Internet Research. 2025, Vol. 27, p1-9. 9p.

Schlagwörter: *Data analysis, *Data management, ChatGPT, Inferential statistics, Medical care research, Statistical software, Univariate analysis, Descriptive statistics

Firma/Körperschaft: OpenAI Inc.

CLAVE: A deep learning model for source code authorship verification with contrastive learning and transformer encoders.

Autoren: Álvarez-Fidalgo, David Ortin, Francisco

Quelle: Information Processing & Management. May2025, Vol. 62 Issue 3, pN.PAG-N.PAG. 1p.

Schlagwörter: *Transformer models, Language models, Source code, Dispute resolution, Python programming language

Processing Government Data: ZIP Codes, Python, and OpenRefine.

Autoren: Donnelly, Frank¹ francis.donnelly@baruch.cuny.edu

Quelle: Code4Lib Journal. 7/21/2014, Issue 25, p10-10. 1p. 2 Color Photographs.

Schlagwörter: *Data analysis, *Librarians, Zip codes, Python programming language, Electronic spreadsheets

Effectiveness of Weight Loss Methods on Lifespan for Metabolic Syndrome

Autoren: Nazarbayev University School of Medicine Nazarbayev University Astana Medical University et al.

Weitere Verfasser: Nazarbayev University School of Medicine Nazarbayev University Astana Medical University et al.

Quelle: Effectiveness of Pharmacologic, Surgical, and Dietetic Weight Loss Methods on Lifespan in Patients With Metabolic Syndrome: a Comparative Clinical Trial

CDL Validation Study

Autoren: University Clinic for Ophthalmology and Optometry- Salzburg

Quelle: Safety and Feasibility of the Cornea DomeLens Ocular Surface Imaging System
Ang M, Cai Y, MacPhee B, Sim DA, Keane PA, Sng CC, Egan CA, Tufail A, Larkin DF, Wilkins MR. Optical coherence tomography angiography and indocyanine green angiography for corneal vascularisation. Br J Ophthalmol. 2016 Nov;100(11):1557-1563. doi: 10.1136/bjophthalmol-2015-307706. Epub 2016 Jan 28.
Steger B, Romano V, Kaye SB. Corneal Indocyanine Green Angiography to Guide Medical and Surgical Management of Corneal Neovascularization. Cornea. 2016 Jan;35(1):41-5. doi: 10.1097/ICO.0000000000000683.
McMonnies CW, Chapman-Davies A. Assessment of conjunctival hyperemia in contact lens wearers. Part I. Am J Optom Physiol Opt. 1987 Apr;64(4):246-50. doi: 10.1097/00006324-198704000-00003.
Bron AJ, Evans VE, Smith JA. Grading of corneal and conjunctival staining in the context of other dry eye tests. Cornea. 2003 Oct;22(7):640-50. doi: 10.1097/00003226-200310000-00008.
Guthoff RF, Baudouin C, Stave J. Atlas of Confocal Laser Scanning In-Vivo Microscopy in Ophthalmology. Springer; 2007
Krachmer JH, Mannis MJ, Holland EJ. Cornea. In: Vol I. 3rd Edition. Mosby Elsevier; 2011.
Steger B, Romano V, Jesacher A, et al. Ocular Surface Photography 2.0 -Curved Object Plane For Corneal Imaging. Appl Opt. in press 2017
Efron N. Grading scales for contact lens complications. Ophthalmic Physiol Opt. 1998 Mar;18(2):182-6. doi: 10.1016/s0275-5408(97)00066-5.

All of whom? Limitations encountered using All of Us Researcher Workbench in a Primary Care residents secondary data analysis research training block.

Autoren: LaPolla, Fred Willie Zametkin Grossi, Marco Barber Chen, Sharon et al.

Quelle: Journal of the American Medical Informatics Association. Dec2024, Vol. 31 Issue 12, p3008-3012. 5p.

Schlagwörter: Secondary analysis, Graduate medical education, Research personnel, Residents (Medicine), Research questions