Search alternatives:
time implementation » _ implementation (Expand Search), policy implementation (Expand Search), effective implementation (Expand Search)
python based » method based (Expand Search), person based (Expand Search)
python time » python files (Expand Search)
time implementation » _ implementation (Expand Search), policy implementation (Expand Search), effective implementation (Expand Search)
python based » method based (Expand Search), person based (Expand Search)
python time » python files (Expand Search)
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Online Resource 3: Word Cloud Dataset and Code
Published 2025“…This set of files are part of Online Resource 3, which allows readers to implement a Jupyter Notebook Python program to create a word cloud based on survey responses. …”
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Five Operator Lattice Simulation
Published 2025“…</p><p dir="ltr">Running the included file <code>five_operator_lattice_sim.py</code> (Python 3.14 + NumPy 2.1) reproduces the dynamic interactions and figures reported in Appendix A of the paper, generating time-series data that demonstrate operator balance, instability, and renewal cycles.…”
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EthoPy: Reproducible Behavioral Neuroscience Made Simple
Published 2025“…To overcome these challenges, we developed EthoPy, an open-source, Python-based behavioral control framework that integrates stimulus presentation, hardware management, and data logging. …”
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Complex Eigenvalues, Orthogonality, and QR Factorization: Analytical Proofs and Numerical Verification
Published 2025“…Discrepancies between QR-based solutions and NumPy’s lstsq method are quantified to confirm high accuracy (~10⁻¹⁶), demonstrating numerical stability and machine-precision correctness.…”
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ZILLNB_Model
Published 2025“…<p dir="ltr">Acquire latent variables using deep-learning based model implemented in python</p>…”
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Graphical abstract of HCAP.
Published 2025“…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”
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Recall analysis.
Published 2025“…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”
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Convergence rate analysis.
Published 2025“…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”
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Computational efficiency.
Published 2025“…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”
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Analysis of IoMT data sources.
Published 2025“…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. The created system was implemented using Python, and various metrics, including false positive and false negative rates, accuracy, precision, recall, and computational efficiency, were used for evaluation. …”