Suchergebnisse - (( (statny OR state) python code analysis ) OR ( (statenet OR stateeeei) 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

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

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

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

Serenity: Library Based Python Code Analysis for Code Completion and Automated Machine Learning

Autoren: Zhao, Wenting Abdelaziz, Ibrahim Dolby, Julian et al.

Index Begriffe: Computer Science - Programming Languages, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2301.05108

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

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

Hamzah Certainty Principle (HCP). Confirmation of Einstein's Statement 'God Does Not Play Dice' and the Refutation of Heisenberg's Uncertainty Principle (HUP): Contrasting the Planck Constant (ℏ/2) with the Hamzah Certainty Constant (ΩH∗). [ΔxΔp ≥ ℏ/2 Heisenberg] → [Hamzah Principle: ΔxΔp = ΩH∗]

Autoren: JALALI, SEYED RASOUL

Schlagwörter: quantum mechanics, Heisenberg uncertainty, Schrödinger equation, Hamzah equation, complex integral, fractal derivative, hidden variable, deterministic physics, classical model, electron hydrogen atom, Bohr radius, reduced Planck constant, electron mass, electron charge, vacuum permittivity, Δx, Δp, uncertainty principle, quantum simulation, numerical example, double-slit experiment, tunneling effect, quantum tunneling, probabilistic interpretation, deterministic interpretation, wavefunction, Born rule, Copenhagen interpretation, path integral, fractal physics, fractal uncertainty, hidden variable χ, atomic orbitals, hydrogen energy levels, quantum probabilities, quantum superposition, quantum states, electron trajectory, quantum dynamics, numerical modeling, graphical simulation, scientific validation, physics comparison, classical uncertainty, exponential decay, s-parameter, fractal dimension, knowledge level, visualisation, plotting, matplotlib, numpy, Python code, computational physics, advanced Python, simulation model, particle physics, quantum electrodynamics, atomic physics, subatomic particle, atomic structure, Bohr model, Planck constant, quantum computation, quantum information, QIS, uncertainty reduction, determinism, Heisenberg principle, Schrödinger model, quantum field theory, quantum system, fractal analysis, hidden dynamics, electron cloud, wave-particle duality, trajectory reconstruction, experimental validation, physics experiment, numerical test, s-values, quantum interference, light wavelength, slit separation, screen distance, intensity pattern, quantum fringes, deterministic fringes, tunneling probability, barrier height, barrier width, particle energy, exponential suppression, classical tunneling, Hamzah tunneling, quantum probability, fractal suppression, s-dependence, quantum-classical comparison, atomic simulation, electron localization, measurement effect, quantum determinism, philosophical implication, Einstein principle, God does not play dice, quantum philosophy, advanced modeling, scientific illustration, computational validation, physics education, research tool, atomic simulation, quantum mechanics validation, probability reduction, trajectory determinism, electron motion, hydrogen atom simulation, microscopic physics, electron dynamics, uncertainty minimization, quantum interpretation, experimental simulation, numerical plotting, double-slit pattern, deterministic pattern, interference fringes, Hamzah model comparison, classical vs Hamzah, scientific graphing, Δx·Δp curve, quantum-classical contrast, wavefunction collapse, electron uncertainty, quantum measurement, deterministic outcome, s-parameter scaling, fractal modeling, hidden variables theory, χ-variable, atomic orbital visualization, atomic physics computation, advanced physics code, Python simulation, electron path modeling, hydrogen energy computation, quantum-classical graph, uncertainty visualization, advanced plotting, fractal uncertainty curve, complex integral application, electron localization calculation, atomic electron dynamics, computational experiment, quantum behavior modeling, Heisenberg test, Schrödinger test, Hamzah simulation, numerical validation, physical constants, electron energy, atomic radius calculation, Bohr radius derivation, Planck constant application, mass-energy relation, electron interaction, fractal analysis physics, hidden variable application, complex trajectory, electron orbit prediction, deterministic physics modeling, advanced physics scenario, Hamzah model verification, quantum to classical transition, quantum determinism analysis, electron trajectory reconstruction, quantum uncertainty analysis, ΔxΔp comparison, electron position momentum, quantum state evolution, fractal dimension effect, knowledge-dependent uncertainty, deterministic path, quantum-classical integration, electron energy levels computation, atomic electron simulation, advanced numerical analysis, Python numerical modeling, matplotlib plotting physics, simulation of hydrogen atom, numerical physics experiments, quantum simulation techniques, Hamzah equation implementation, hidden variable physics, fractal derivative application, complex integral evaluation, atomic-scale modeling, electron dynamics visualization, numerical precision physics, quantum trajectory calculation, double-slit simulation, interference visualization, deterministic fringes visualization, Hamzah vs classical comparison, quantum tunneling simulation, tunneling coefficient calculation, exponential decay tunneling, classical tunneling probability, Hamzah tunneling probability, quantum-classical tunneling, s-dependent tunneling, electron barrier interaction, quantum barrier simulation, atomic physics numerical test, numerical modeling in physics, quantum-classical experiments, simulation of ΔxΔp, uncertainty reduction analysis, deterministic electron trajectory, fractal physics simulation, hidden variable validation, complex integral in physics, electron path visualisation, atomic electron path, Bohr orbit modeling, advanced simulation techniques, Python computational physics, numerical physics modeling, hydrogen atom analysis, ΔxΔp calculation, quantum uncertainty minimization, Hamzah model demonstration, electron probability cloud, electron localization analysis, s-parameter impact, fractal trajectory, deterministic quantum mechanics, quantum determinism illustration, advanced atomic physics, computational quantum mechanics, numerical physics research, physics education tool, scientific Python code, visualisation of uncertainty, electron behavior simulation, atomic-scale precision, quantum measurement modeling, deterministic simulation, quantum experimental validation, Hamzah numerical test, classical numerical test, Δx·Δp visualisation, electron orbit comparison, hydrogen atom simulation, fractal uncertainty modeling, hidden variable analysis, advanced physics plotting, Hamzah uncertainty calculation, classical uncertainty calculation, quantum vs Hamzah, electron trajectory analysis, numerical results comparison, graphical physics representation, electron dynamics charting, atomic physics visualization, advanced Python simulation, fractal dimension modeling, deterministic quantum simulation, classical vs deterministic comparison, quantum-classical overlay, simulation graph analysis, ΔxΔp trend, s-dependence visualization, knowledge-based uncertainty, atomic electron trajectory, quantum-to-deterministic mapping, electron momentum analysis, electron position analysis, trajectory vs uncertainty, deterministic physics visualization, Hamzah validation, classical validation, numerical physics experiments, simulation framework, advanced computational scenario, atomic orbitals visualization, atomic simulation Python, numerical modeling Python, computational modeling Python, quantum mechanics advanced, physics advanced modeling, simulation of electron, hydrogen electron visualization, electron orbital simulation, quantum wavefunction modeling, advanced physics computation, fractal physics implementation, hidden variable incorporation, complex integral computation, atomic structure simulation, electron position modeling, electron momentum modeling, trajectory reconstruction analysis, numerical verification, deterministic universe, quantum determinism confirmation, Einstein verification, probabilistic reduction, atomic-scale modeling, electron motion plotting, uncertainty decay, exponential uncertainty reduction, s-scaling impact, atomic precision simulation, electron localization precision, quantum-classical comparison graph, simulation of tunneling, classical vs Hamzah tunneling, electron barrier simulation, atomic physics numerical validation, quantum physics numerical modeling, physics Python simulation, numerical precision simulation, advanced simulation graphing, electron uncertainty evaluation, ΔxΔp comparison chart, simulation of electron path, atomic simulation numerical test, deterministic trajectory verification, complex integral application in atomic physics, fractal derivative impact, s-parameter effect, Hamzah scenario demonstration, quantum to deterministic transition, electron dynamics verification, classical physics vs Hamzah, atomic-scale electron modeling, advanced simulation framework, numerical visualization, simulation reproducibility, deterministic hydrogen atom model, computational physics validation, simulation scenario Python, electron path plotting, atomic physics computational code, hydrogen electron modeling Python, electron orbital path, deterministic quantum mechanics modeling, advanced atomic simulation, numerical precision Python, quantum-classical comparison demonstration, Hamzah numerical results, atomic physics scenario, simulation verification, numerical comparison, ΔxΔp calculation Python, advanced plotting Python, electron path reconstruction, quantum mechanics illustration, hydrogen atom numerical analysis, numerical physics demonstration, simulation code Python, deterministic electron simulation, fractal trajectory analysis, electron behavior visualization, numerical simulation framework, quantum determinism verification, s-dependent uncertainty modeling, Hamzah model graph, electron orbital visualisation, atomic precision modeling, advanced electron trajectory, electron motion charting, fractal physics Python, hidden variable χ application, complex integral simulation, atomic electron verification, deterministic trajectory illustration, quantum uncertainty comparison, classical ΔxΔp analysis, Hamzah ΔxΔp analysis, numerical experiment Python, advanced physics Python code, quantum-classical validation, electron orbit comparison chart, atomic physics numerical simulation, electron dynamics simulation, trajectory analysis Python, hydrogen atom experiment Python, electron localization demonstration, electron probability cloud visualization, atomic trajectory simulation, electron motion verification, advanced numerical physics, Hamzah equation simulation, simulation of Δx·Δp, graphical simulation Python, electron uncertainty Python, deterministic path verification, electron motion modeling, classical vs Hamzah numerical, atomic simulation scenario, numerical hydrogen atom simulation, simulation verification Python, atomic physics trajectory plotting, electron orbit simulation Python, advanced quantum physics modeling, deterministic trajectory Python, Hamzah validation scenario, classical validation scenario, advanced physics visualization, electron trajectory numerical, hydrogen atom visualization, atomic orbit numerical, electron motion experiment, quantum-classical overlay Python, deterministic hydrogen electron, ΔxΔp scenario Python, fractal derivative simulation, complex integral modeling, s-parameter visualization, Hamzah scenario graph, quantum-classical comparison Python, advanced simulation visualization, numerical simulation graph, electron behavior analysis Python, atomic orbit plotting, electron momentum visualization, Δx·Δp chart, deterministic quantum Python, electron trajectory demonstration, atomic electron motion Python, hydrogen electron path modeling, numerical scenario validation, quantum-classical scenario Python, atomic physics modeling Python, electron uncertainty visualization, Hamzah scenario validation, simulation of tunneling Python, classical vs Hamzah tunneling Python, deterministic electron behavior, advanced atomic visualization, numerical electron path, Δx·Δp comparison visualization, simulation code demonstration, electron orbital comparison, atomic physics simulation Python, advanced simulation techniques Python, quantum deterministic illustration, electron motion simulation Python, Hamzah numerical verification, classical numerical verification, simulation of electron motion, electron position trajectory, Δx·Δp trend visualization, hydrogen atom scenario modeling, electron trajectory analysis Python, Hamzah scenario demonstration Python, atomic-scale simulation Python, quantum-classical determinism, electron orbital trajectory, numerical physics demonstration Python, deterministic hydrogen electron path, advanced computational modeling, atomic physics simulation Python, Hamzah model numerical demonstration, simulation of electron trajectory, fractal trajectory Python, electron momentum trajectory, Δx·Δp visualization Python, simulation of hydrogen electron, numerical physics analysis Python, electron localization analysis Python, Hamzah equation Python, advanced scenario modeling Python, deterministic electron trajectory Python, atomic-scale modeling Python

Hamzah Certainty Principle. Confirmation of Einstein's Statement 'God Does Not Play Dice' and the Refutation of Heisenberg's Uncertainty Principle: Contrasting the Planck Constant (ℏ/2) with the Hamzah Certainty Constant (ΩH∗). [ΔxΔp ≥ ℏ/2 Heisenberg] → [Hamzah Principle: ΔxΔp = ΩH∗]

Autoren: JALALI, SEYED RASOUL

Schlagwörter: quantum mechanics, Heisenberg uncertainty, Schrödinger equation, Hamzah equation, complex integral, fractal derivative, hidden variable, deterministic physics, classical model, electron hydrogen atom, Bohr radius, reduced Planck constant, electron mass, electron charge, vacuum permittivity, Δx, Δp, uncertainty principle, quantum simulation, numerical example, double-slit experiment, tunneling effect, quantum tunneling, probabilistic interpretation, deterministic interpretation, wavefunction, Born rule, Copenhagen interpretation, path integral, fractal physics, fractal uncertainty, hidden variable χ, atomic orbitals, hydrogen energy levels, quantum probabilities, quantum superposition, quantum states, electron trajectory, quantum dynamics, numerical modeling, graphical simulation, scientific validation, physics comparison, classical uncertainty, exponential decay, s-parameter, fractal dimension, knowledge level, visualisation, plotting, matplotlib, numpy, Python code, computational physics, advanced Python, simulation model, particle physics, quantum electrodynamics, atomic physics, subatomic particle, atomic structure, Bohr model, Planck constant, quantum computation, quantum information, QIS, uncertainty reduction, determinism, Heisenberg principle, Schrödinger model, quantum field theory, quantum system, fractal analysis, hidden dynamics, electron cloud, wave-particle duality, trajectory reconstruction, experimental validation, physics experiment, numerical test, s-values, quantum interference, light wavelength, slit separation, screen distance, intensity pattern, quantum fringes, deterministic fringes, tunneling probability, barrier height, barrier width, particle energy, exponential suppression, classical tunneling, Hamzah tunneling, quantum probability, fractal suppression, s-dependence, quantum-classical comparison, atomic simulation, electron localization, measurement effect, quantum determinism, philosophical implication, Einstein principle, God does not play dice, quantum philosophy, advanced modeling, scientific illustration, computational validation, physics education, research tool, atomic simulation, quantum mechanics validation, probability reduction, trajectory determinism, electron motion, hydrogen atom simulation, microscopic physics, electron dynamics, uncertainty minimization, quantum interpretation, experimental simulation, numerical plotting, double-slit pattern, deterministic pattern, interference fringes, Hamzah model comparison, classical vs Hamzah, scientific graphing, Δx·Δp curve, quantum-classical contrast, wavefunction collapse, electron uncertainty, quantum measurement, deterministic outcome, s-parameter scaling, fractal modeling, hidden variables theory, χ-variable, atomic orbital visualization, atomic physics computation, advanced physics code, Python simulation, electron path modeling, hydrogen energy computation, quantum-classical graph, uncertainty visualization, advanced plotting, fractal uncertainty curve, complex integral application, electron localization calculation, atomic electron dynamics, computational experiment, quantum behavior modeling, Heisenberg test, Schrödinger test, Hamzah simulation, numerical validation, physical constants, electron energy, atomic radius calculation, Bohr radius derivation, Planck constant application, mass-energy relation, electron interaction, fractal analysis physics, hidden variable application, complex trajectory, electron orbit prediction, deterministic physics modeling, advanced physics scenario, Hamzah model verification, quantum to classical transition, quantum determinism analysis, electron trajectory reconstruction, quantum uncertainty analysis, ΔxΔp comparison, electron position momentum, quantum state evolution, fractal dimension effect, knowledge-dependent uncertainty, deterministic path, quantum-classical integration, electron energy levels computation, atomic electron simulation, advanced numerical analysis, Python numerical modeling, matplotlib plotting physics, simulation of hydrogen atom, numerical physics experiments, quantum simulation techniques, Hamzah equation implementation, hidden variable physics, fractal derivative application, complex integral evaluation, atomic-scale modeling, electron dynamics visualization, numerical precision physics, quantum trajectory calculation, double-slit simulation, interference visualization, deterministic fringes visualization, Hamzah vs classical comparison, quantum tunneling simulation, tunneling coefficient calculation, exponential decay tunneling, classical tunneling probability, Hamzah tunneling probability, quantum-classical tunneling, s-dependent tunneling, electron barrier interaction, quantum barrier simulation, atomic physics numerical test, numerical modeling in physics, quantum-classical experiments, simulation of ΔxΔp, uncertainty reduction analysis, deterministic electron trajectory, fractal physics simulation, hidden variable validation, complex integral in physics, electron path visualisation, atomic electron path, Bohr orbit modeling, advanced simulation techniques, Python computational physics, numerical physics modeling, hydrogen atom analysis, ΔxΔp calculation, quantum uncertainty minimization, Hamzah model demonstration, electron probability cloud, electron localization analysis, s-parameter impact, fractal trajectory, deterministic quantum mechanics, quantum determinism illustration, advanced atomic physics, computational quantum mechanics, numerical physics research, physics education tool, scientific Python code, visualisation of uncertainty, electron behavior simulation, atomic-scale precision, quantum measurement modeling, deterministic simulation, quantum experimental validation, Hamzah numerical test, classical numerical test, Δx·Δp visualisation, electron orbit comparison, hydrogen atom simulation, fractal uncertainty modeling, hidden variable analysis, advanced physics plotting, Hamzah uncertainty calculation, classical uncertainty calculation, quantum vs Hamzah, electron trajectory analysis, numerical results comparison, graphical physics representation, electron dynamics charting, atomic physics visualization, advanced Python simulation, fractal dimension modeling, deterministic quantum simulation, classical vs deterministic comparison, quantum-classical overlay, simulation graph analysis, ΔxΔp trend, s-dependence visualization, knowledge-based uncertainty, atomic electron trajectory, quantum-to-deterministic mapping, electron momentum analysis, electron position analysis, trajectory vs uncertainty, deterministic physics visualization, Hamzah validation, classical validation, numerical physics experiments, simulation framework, advanced computational scenario, atomic orbitals visualization, atomic simulation Python, numerical modeling Python, computational modeling Python, quantum mechanics advanced, physics advanced modeling, simulation of electron, hydrogen electron visualization, electron orbital simulation, quantum wavefunction modeling, advanced physics computation, fractal physics implementation, hidden variable incorporation, complex integral computation, atomic structure simulation, electron position modeling, electron momentum modeling, trajectory reconstruction analysis, numerical verification, deterministic universe, quantum determinism confirmation, Einstein verification, probabilistic reduction, atomic-scale modeling, electron motion plotting, uncertainty decay, exponential uncertainty reduction, s-scaling impact, atomic precision simulation, electron localization precision, quantum-classical comparison graph, simulation of tunneling, classical vs Hamzah tunneling, electron barrier simulation, atomic physics numerical validation, quantum physics numerical modeling, physics Python simulation, numerical precision simulation, advanced simulation graphing, electron uncertainty evaluation, ΔxΔp comparison chart, simulation of electron path, atomic simulation numerical test, deterministic trajectory verification, complex integral application in atomic physics, fractal derivative impact, s-parameter effect, Hamzah scenario demonstration, quantum to deterministic transition, electron dynamics verification, classical physics vs Hamzah, atomic-scale electron modeling, advanced simulation framework, numerical visualization, simulation reproducibility, deterministic hydrogen atom model, computational physics validation, simulation scenario Python, electron path plotting, atomic physics computational code, hydrogen electron modeling Python, electron orbital path, deterministic quantum mechanics modeling, advanced atomic simulation, numerical precision Python, quantum-classical comparison demonstration, Hamzah numerical results, atomic physics scenario, simulation verification, numerical comparison, ΔxΔp calculation Python, advanced plotting Python, electron path reconstruction, quantum mechanics illustration, hydrogen atom numerical analysis, numerical physics demonstration, simulation code Python, deterministic electron simulation, fractal trajectory analysis, electron behavior visualization, numerical simulation framework, quantum determinism verification, s-dependent uncertainty modeling, Hamzah model graph, electron orbital visualisation, atomic precision modeling, advanced electron trajectory, electron motion charting, fractal physics Python, hidden variable χ application, complex integral simulation, atomic electron verification, deterministic trajectory illustration, quantum uncertainty comparison, classical ΔxΔp analysis, Hamzah ΔxΔp analysis, numerical experiment Python, advanced physics Python code, quantum-classical validation, electron orbit comparison chart, atomic physics numerical simulation, electron dynamics simulation, trajectory analysis Python, hydrogen atom experiment Python, electron localization demonstration, electron probability cloud visualization, atomic trajectory simulation, electron motion verification, advanced numerical physics, Hamzah equation simulation, simulation of Δx·Δp, graphical simulation Python, electron uncertainty Python, deterministic path verification, electron motion modeling, classical vs Hamzah numerical, atomic simulation scenario, numerical hydrogen atom simulation, simulation verification Python, atomic physics trajectory plotting, electron orbit simulation Python, advanced quantum physics modeling, deterministic trajectory Python, Hamzah validation scenario, classical validation scenario, advanced physics visualization, electron trajectory numerical, hydrogen atom visualization, atomic orbit numerical, electron motion experiment, quantum-classical overlay Python, deterministic hydrogen electron, ΔxΔp scenario Python, fractal derivative simulation, complex integral modeling, s-parameter visualization, Hamzah scenario graph, quantum-classical comparison Python, advanced simulation visualization, numerical simulation graph, electron behavior analysis Python, atomic orbit plotting, electron momentum visualization, Δx·Δp chart, deterministic quantum Python, electron trajectory demonstration, atomic electron motion Python, hydrogen electron path modeling, numerical scenario validation, quantum-classical scenario Python, atomic physics modeling Python, electron uncertainty visualization, Hamzah scenario validation, simulation of tunneling Python, classical vs Hamzah tunneling Python, deterministic electron behavior, advanced atomic visualization, numerical electron path, Δx·Δp comparison visualization, simulation code demonstration, electron orbital comparison, atomic physics simulation Python, advanced simulation techniques Python, quantum deterministic illustration, electron motion simulation Python, Hamzah numerical verification, classical numerical verification, simulation of electron motion, electron position trajectory, Δx·Δp trend visualization, hydrogen atom scenario modeling, electron trajectory analysis Python, Hamzah scenario demonstration Python, atomic-scale simulation Python, quantum-classical determinism, electron orbital trajectory, numerical physics demonstration Python, deterministic hydrogen electron path, advanced computational modeling, atomic physics simulation Python, Hamzah model numerical demonstration, simulation of electron trajectory, fractal trajectory Python, electron momentum trajectory, Δx·Δp visualization Python, simulation of hydrogen electron, numerical physics analysis Python, electron localization analysis Python, Hamzah equation Python, advanced scenario modeling Python, deterministic electron trajectory Python, atomic-scale modeling Python

Hamzah Certainty Principle. Confirmation of Einstein's Statement 'God Does Not Play Dice' and the Refutation of Heisenberg's Uncertainty Principle

Autoren: JALALI, SEYED RASOUL

Schlagwörter: quantum mechanics, Heisenberg uncertainty, Schrödinger equation, Hamzah equation, complex integral, fractal derivative, hidden variable, deterministic physics, classical model, electron hydrogen atom, Bohr radius, reduced Planck constant, electron mass, electron charge, vacuum permittivity, Δx, Δp, uncertainty principle, quantum simulation, numerical example, double-slit experiment, tunneling effect, quantum tunneling, probabilistic interpretation, deterministic interpretation, wavefunction, Born rule, Copenhagen interpretation, path integral, fractal physics, fractal uncertainty, hidden variable χ, atomic orbitals, hydrogen energy levels, quantum probabilities, quantum superposition, quantum states, electron trajectory, quantum dynamics, numerical modeling, graphical simulation, scientific validation, physics comparison, classical uncertainty, exponential decay, s-parameter, fractal dimension, knowledge level, visualisation, plotting, matplotlib, numpy, Python code, computational physics, advanced Python, simulation model, particle physics, quantum electrodynamics, atomic physics, subatomic particle, atomic structure, Bohr model, Planck constant, quantum computation, quantum information, QIS, uncertainty reduction, determinism, Heisenberg principle, Schrödinger model, quantum field theory, quantum system, fractal analysis, hidden dynamics, electron cloud, wave-particle duality, trajectory reconstruction, experimental validation, physics experiment, numerical test, s-values, quantum interference, light wavelength, slit separation, screen distance, intensity pattern, quantum fringes, deterministic fringes, tunneling probability, barrier height, barrier width, particle energy, exponential suppression, classical tunneling, Hamzah tunneling, quantum probability, fractal suppression, s-dependence, quantum-classical comparison, atomic simulation, electron localization, measurement effect, quantum determinism, philosophical implication, Einstein principle, God does not play dice, quantum philosophy, advanced modeling, scientific illustration, computational validation, physics education, research tool, atomic simulation, quantum mechanics validation, probability reduction, trajectory determinism, electron motion, hydrogen atom simulation, microscopic physics, electron dynamics, uncertainty minimization, quantum interpretation, experimental simulation, numerical plotting, double-slit pattern, deterministic pattern, interference fringes, Hamzah model comparison, classical vs Hamzah, scientific graphing, Δx·Δp curve, quantum-classical contrast, wavefunction collapse, electron uncertainty, quantum measurement, deterministic outcome, s-parameter scaling, fractal modeling, hidden variables theory, χ-variable, atomic orbital visualization, atomic physics computation, advanced physics code, Python simulation, electron path modeling, hydrogen energy computation, quantum-classical graph, uncertainty visualization, advanced plotting, fractal uncertainty curve, complex integral application, electron localization calculation, atomic electron dynamics, computational experiment, quantum behavior modeling, Heisenberg test, Schrödinger test, Hamzah simulation, numerical validation, physical constants, electron energy, atomic radius calculation, Bohr radius derivation, Planck constant application, mass-energy relation, electron interaction, fractal analysis physics, hidden variable application, complex trajectory, electron orbit prediction, deterministic physics modeling, advanced physics scenario, Hamzah model verification, quantum to classical transition, quantum determinism analysis, electron trajectory reconstruction, quantum uncertainty analysis, ΔxΔp comparison, electron position momentum, quantum state evolution, fractal dimension effect, knowledge-dependent uncertainty, deterministic path, quantum-classical integration, electron energy levels computation, atomic electron simulation, advanced numerical analysis, Python numerical modeling, matplotlib plotting physics, simulation of hydrogen atom, numerical physics experiments, quantum simulation techniques, Hamzah equation implementation, hidden variable physics, fractal derivative application, complex integral evaluation, atomic-scale modeling, electron dynamics visualization, numerical precision physics, quantum trajectory calculation, double-slit simulation, interference visualization, deterministic fringes visualization, Hamzah vs classical comparison, quantum tunneling simulation, tunneling coefficient calculation, exponential decay tunneling, classical tunneling probability, Hamzah tunneling probability, quantum-classical tunneling, s-dependent tunneling, electron barrier interaction, quantum barrier simulation, atomic physics numerical test, numerical modeling in physics, quantum-classical experiments, simulation of ΔxΔp, uncertainty reduction analysis, deterministic electron trajectory, fractal physics simulation, hidden variable validation, complex integral in physics, electron path visualisation, atomic electron path, Bohr orbit modeling, advanced simulation techniques, Python computational physics, numerical physics modeling, hydrogen atom analysis, ΔxΔp calculation, quantum uncertainty minimization, Hamzah model demonstration, electron probability cloud, electron localization analysis, s-parameter impact, fractal trajectory, deterministic quantum mechanics, quantum determinism illustration, advanced atomic physics, computational quantum mechanics, numerical physics research, physics education tool, scientific Python code, visualisation of uncertainty, electron behavior simulation, atomic-scale precision, quantum measurement modeling, deterministic simulation, quantum experimental validation, Hamzah numerical test, classical numerical test, Δx·Δp visualisation, electron orbit comparison, hydrogen atom simulation, fractal uncertainty modeling, hidden variable analysis, advanced physics plotting, Hamzah uncertainty calculation, classical uncertainty calculation, quantum vs Hamzah, electron trajectory analysis, numerical results comparison, graphical physics representation, electron dynamics charting, atomic physics visualization, advanced Python simulation, fractal dimension modeling, deterministic quantum simulation, classical vs deterministic comparison, quantum-classical overlay, simulation graph analysis, ΔxΔp trend, s-dependence visualization, knowledge-based uncertainty, atomic electron trajectory, quantum-to-deterministic mapping, electron momentum analysis, electron position analysis, trajectory vs uncertainty, deterministic physics visualization, Hamzah validation, classical validation, numerical physics experiments, simulation framework, advanced computational scenario, atomic orbitals visualization, atomic simulation Python, numerical modeling Python, computational modeling Python, quantum mechanics advanced, physics advanced modeling, simulation of electron, hydrogen electron visualization, electron orbital simulation, quantum wavefunction modeling, advanced physics computation, fractal physics implementation, hidden variable incorporation, complex integral computation, atomic structure simulation, electron position modeling, electron momentum modeling, trajectory reconstruction analysis, numerical verification, deterministic universe, quantum determinism confirmation, Einstein verification, probabilistic reduction, atomic-scale modeling, electron motion plotting, uncertainty decay, exponential uncertainty reduction, s-scaling impact, atomic precision simulation, electron localization precision, quantum-classical comparison graph, simulation of tunneling, classical vs Hamzah tunneling, electron barrier simulation, atomic physics numerical validation, quantum physics numerical modeling, physics Python simulation, numerical precision simulation, advanced simulation graphing, electron uncertainty evaluation, ΔxΔp comparison chart, simulation of electron path, atomic simulation numerical test, deterministic trajectory verification, complex integral application in atomic physics, fractal derivative impact, s-parameter effect, Hamzah scenario demonstration, quantum to deterministic transition, electron dynamics verification, classical physics vs Hamzah, atomic-scale electron modeling, advanced simulation framework, numerical visualization, simulation reproducibility, deterministic hydrogen atom model, computational physics validation, simulation scenario Python, electron path plotting, atomic physics computational code, hydrogen electron modeling Python, electron orbital path, deterministic quantum mechanics modeling, advanced atomic simulation, numerical precision Python, quantum-classical comparison demonstration, Hamzah numerical results, atomic physics scenario, simulation verification, numerical comparison, ΔxΔp calculation Python, advanced plotting Python, electron path reconstruction, quantum mechanics illustration, 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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

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

How to select reference sites for long-term agricultural experiments: A data-driven approach

Autoren: Nishita Thakur Marco Donat Sonoko Bellingrath-Kimura et al.

Quelle: Smart Agricultural Technology, Vol 12, Iss , Pp 101357- (2025)

Schlagwörter: Experimental design, Land use change, Spatial data analysis, K-means clustering, Agriculture (General), S1-972, Agricultural industries, HD9000-9495

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S277237552500588X; https://doaj.org/toc/2772-3755

Zugangs-URL: https://doaj.org/article/4ab6baf947274359bdd6032f8ce9ff01

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)