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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∗]

Authors: JALALI, SEYED RASOUL

Subject Terms: 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 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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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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∗]

Authors: JALALI, SEYED RASOUL

Subject Terms: 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

What does this Python code do? An exploratory analysis of novice students’ code explanations: An exploratory analysis of novice students’ code explanations

Authors: Werf, V. van der. Aivaloglou, E. Hermans, F.F.J. et al.

Contributors: Werf, V. van der. Aivaloglou, E. Hermans, F.F.J. et al.

Source: The 10th Computer Science Education Research Conference. :94-107

Subject Terms: 4. Education, 05 social sciences, 10. No inequality, 0503 education, 3. Good health

File Description: application/pdf

Access URL: https://hdl.handle.net/1887/3655545

Code Redteaming: Probing Ethical Sensitivity of LLMs Through Natural Language Embedded in Code.

Authors: Park, Chanjun Yoon, Jeongho Lim, Heuiseok

Source: Mathematics (2227-7390). Jan2026, Vol. 14 Issue 1, p189. 18p.

Subject Terms: *LANGUAGE models, *ETHICS, *NATURAL language processing, *RISK assessment, *MORAL attitudes

Assessing code readability in Python programming courses using eye‐tracking

Authors: Milan Segedinac Goran Savić Ivana Zeljković et al.

Source: Computer Applications in Engineering Education. 32

Subject Terms: 05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, 0501 psychology and cognitive sciences, 02 engineering and technology

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

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

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

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

Revealing the Unseen: AI Chain on LLMs for Predicting Implicit Dataflows to Generate Dataflow Graphs in Dynamically Typed Code

Authors: Qing Huang Zhiwen Luo Zhenchang Xing et al.

Source: ACM Transactions on Software Engineering and Methodology. 33:1-29

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

A Systematic Survey on Large Language Models for Code Generation.

Authors: Jabrw, Sardar K. Sarhan, Qusay I.

Source: ARO: The Scientific Journal of Koya University; 2025, Vol. 13 Issue 2, p83-99, 17p

Subject Terms: LANGUAGE models, CODE generators, PROGRAMMING languages, EVALUATION research, COMPUTER software development, COMPUTER security vulnerabilities, NATURAL language processing

Anti-patterns in Students' Conditional Statements

Authors: Naude, Etienne Denny, Paul Luxton-Reilly, Andrew

Index Terms: Computer Science - Computers and Society, Computer Science - Software Engineering, text

URL: http://arxiv.org/abs/2410.18989

NAS Parallel Benchmarks with Python: a performance and programming effort analysis focusing on GPUs.

Authors: Di Domenico, Daniel Lima, João V. F. Cavalheiro, Gerson G. H.

Source: Journal of Supercomputing. May2023, Vol. 79 Issue 8, p8890-8911. 22p.

Subject Terms: *PYTHON programming language, *FORTRAN, *C++

Portable Electronic Olfactometer for Non-Invasive Screening of Canine Ehrlichiosis: A Proof-of-Concept Study Using Machine Learning.

Authors: Durán Cotrina, Silvana Valentina Acevedo, Cristhian Manuel Durán Carrillo Gómez, Jeniffer Katerine

Source: Veterinary Sciences. Jan2026, Vol. 13 Issue 1, p88. 20p.

Zinc as a Biomarker of Nutritional Status and Clinical Burden in Recessive Dystrophic Epidermolysis Bullosa: Implications for Preventive Monitoring.

Authors: Quintana-Castanedo, Lucía Maseda, Rocío Sánchez-Ramón, Silvia et al.

Source: Nutrients. Jan2026, Vol. 18 Issue 2, p232. 19p.

Enhanced cattle identification using Siamese network and MobileViT with EMA attention.

Authors: Han, Mingshuo Li, Baoshan Li, Qi et al.

Source: Frontiers in Veterinary Science. 2026, p1-15. 15p.

Primary data for BJC Carbonic anhydrase IX is a pH-stat that sets an acidic tumour extracellular pH in vivo

Authors: Griffiths, JR Lee, Shen-Han McIntyre, Dominick John et al.

Index Terms: Carbonic anhydrase IX, Extracellular pH, Intracellular pH, ISUCA, Magnetic Resonance Spectroscopy, MRS, pH-stat, Tumour pH, Dataset

URL: https://www.repository.cam.ac.uk/handle/1810/361916
https://doi.org/10.17863/CAM.26029
https://doi.org/10.1038/s41416-018-0216-5
https://www.repository.cam.ac.uk/handle/1810/287141
https://doi.org/10.1038/s41416-018-0216-5
https://www.repository.cam.ac.uk/handle/1810/287141

Debugging Python code using Spectra based fault localization and data flow analysis

Authors: Boussel, Juliette Åbo Akademi, Fakulteten för naturvetenskaper och teknik, Datavetenskap

Contributors: Boussel, Juliette Åbo Akademi, Fakulteten för naturvetenskaper och teknik, Datavetenskap

Subject Terms: Data Flow Analysis, Spectra-based fault localization, Software debugging, software development, Python (programming languages), data, programutveckling, Python, ohjelmistokehitys, 113 Data- och informationsvetenskap

File Description: true

Relation: https://www.doria.fi/handle/10024/192358

Availability: https://www.doria.fi/handle/10024/192358

應用Python程式碼的中小型會計師事務所財務報表編製解決方案 ; A Financial Statement Preparation Solution for Small and Medium-Sized Accounting Firms Using Python Code

Authors: 黃靖峰 Huang, Ching-Feng 周國華 et al.

Contributors: 黃靖峰 Huang, Ching-Feng 周國華 et al.

Subject Terms: 中小型會計師事務所, 自動化, 財務報表編製, Python, Automation, Financial statement preparation, Small and Medium-Sized Accounting Firms

File Description: 4644188 bytes; application/pdf

Relation: 中文文獻: [1]林東清，2023，資訊管理－智慧化企業的核心競爭能力，第八版，智勝文化事業有限公司。 [2]劉順仁、王俊凱、李季澄、黃宇翔，2020，機器學習與會計科目判斷—台灣半導體公司使用人工智慧提升行政效率個案對會計教育之啟示，中華會計學刊，第17卷第2期: 245–268。 [3]臺灣證券交易所股份有限公司，2024，臺灣證券交易所股份有限公司審閱上市公司財務報告作業程序。 英文文獻-網站: [1]Anghel, I., October 17, 2023, PwC Offers Advice from Bots in Deal with ChatGPT Firm OpenAI, Bloomberg Retrieved June 2 2024, from https://www.bloomberg.com/news/articles/2023-10-17/pwc-offers-advice-from-bots-in-deal-with-chatgpt-firm-openai?embedded-checkout=true [2]Faggella, D., 2020, AI in the Accounting Big Four – Comparing Deloitte, PwC, KPMG, and EY, Emerj Artificial Intelligence Research Retrieved June 2 2024, from https://emerj.com/ai-sector-overviews/ai-in-the-accounting-big-four-comparing-deloitte-pwc-kpmg-and-ey/ [3]Rozario, A. M., Zhang, A., & Vasarhelyi, M. A.,2019, Examining Automation in Audit, International Federation of Accountants, Retrieved from https://www.ifac.org/knowledge-gateway/preparing-future-ready-professionals/discussion/examining-automation-audit [4]Sanders, T., January 20, 2023, how to work with large language models, OpenAi Retrieved June 2 2024, from https://cookbook.openai.com/articles/how_to_work_with_large_language_models 英文文獻-學術期刊: [1]Baldwin, A. A., Brown, C. E., Trinkle, B. S. 2006. Opportunities for artificial intelligence development in the accounting domain: the case for auditing. Intelligent Systems in Accounting, Finance and Management 14(3): 77–86 [2]Chan, D. Y., Vasarhelyi, M. A. 2011. Innovation and practice of continuous auditing. International Journal of Accounting Information Systems 12 (2): 152–160 [3]Earley, C. E. 2015. Data analytics in auditing: Opportunities and challenges. Business Horizons, 58(3): 493–500 [4]Huang, F., Vasarhelyi, M. A.2019.Applying robotic process automation (RPA) in auditing: A framework. International Journal of Accounting Information Systems 35 [5]Jacobs, F. R., Weston, F. C., Jr. 2007. Enterprise resource planning (ERP)—A brief history. Journal of Operations Management 25: 357–363 [6]Kogan, A., Mayhew, B. W., Vasarhelyi, M. A.2019. Audit Data Analytics Research—An Application of Design Science Methodology. Accounting Horizons 33(3):69–73 [7]March, S. T., G. F. Smith. 1995. Design and natural science research information technology. Decision Support Systems 15 (4): 251–266 [8]Peffers, K., Tuunanen, T., Rothenberger, M. A., Chatterjee, S. 2007. A Design Science Research Methodology for Information Systems Research Journal of Management Information Systems 24(3): 45–77 [9]Xu, Y. 2024. A Study on the Application of Python in Corporate Financial Analysis. Frontiers in Business, Economics and Management 15(2):31–36 英文文獻-書籍: [1]Baan, J. 2005. The Way to Market Leadership. Vanenburg Group. [2]Simon, H. A. 1969. The Sciences of the Artificial. 3rd ed. The MIT Press.; G0111353107; https://nccur.lib.nccu.edu.tw//handle/140.119/152501; https://nccur.lib.nccu.edu.tw/bitstream/140.119/152501/1/310701.pdf

Availability: https://nccur.lib.nccu.edu.tw//handle/140.119/152501
https://nccur.lib.nccu.edu.tw/bitstream/140.119/152501/1/310701.pdf

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

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

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

Comprehensive Review of Nonstationary Seasonal Timeseries Models through Python Simulations

Authors: Venkata Krishna Rao Maddela

Data-Driven Early Warning Approach for Antimicrobial Resistance Prediction–Anomaly Detection Based on High-Level Indicators.

Authors: Csorba, Szilveszter Vribék, Krisztián Farkas, Máté et al.

Source: Veterinary Sciences. Oct2025, Vol. 12 Issue 10, p935. 17p.

Sex-Specific Dietary Predictors of Blood Glucose Identified Through Decision Tree Modeling in Adults.

Authors: Gautney, Joanna Aguilar, Christina Chan, Julian et al.

Source: Nutrients. Oct2025, Vol. 17 Issue 19, p3119. 12p.