Showing 201 - 220 results of 249 for search '(( algorithm hardening function ) OR ( algorithm python function ))', query time: 0.23s Refine Results
  1. 201

    Table 4_Kefir and healthy aging: revealing thematic gaps through AI-assisted screening and semantic evidence mapping.docx by Francesco Chiani (2661328)

    Published 2025
    “…To overcome this fragmentation, we applied an integrative approach that combines a cutting-edge AI-assisted algorithm for evidence screening with a Python-based semantic clustering pipeline. …”
  2. 202

    Seamless integration of legacy robotic systems into a self-driving laboratory via NIMO: a case study on liquid handler automation by Ryo Tamura (1957942)

    Published 2025
    “…We developed NIMO (formerly NIMS-OS, NIMS Orchestration System), an OS explicitly designed to integrate multiple artificial intelligence (AI) algorithms with diverse exploratory objectives. NIMO provides a framework for integrating AI into robotic experimental systems that are controlled by other OS platforms based on both Python and non-Python languages. …”
  3. 203

    Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

    Published 2025
    “…The analysis was conducted in a Jupyter Notebook environment, using Python and libraries such as Scikit-learn and Pandas. …”
  4. 204

    Least Bridges Graphs by Richard Frost (14064363)

    Published 2023
    “…This toolbox was originally created for analysis of values arising in genetic distance measures. The contained algorithms correct errors in commonly used nearest-neighbor and cluster software that are not designed with distances in mind (e.g. nearest-neighbor topology functions currently found in Python, SPSS, etc).…”
  5. 205

    Table1_Enhanced classification and severity prediction of major depressive disorder using acoustic features and machine learning.pdf by Lijuan Liang (4277053)

    Published 2024
    “…We used the Covarep open-source algorithm to extract a total of 1200 high-level statistical functions for each sample. …”
  6. 206

    Sudoku Dataset by David Towers (12857447)

    Published 2024
    “…</p> <p>NumPy (.npy) files can be opened through the NumPy Python library, using the `numpy.load()` function by inputting the path to the file into the function as a parameter. …”
  7. 207

    The software structure. by Moritz Hoffmann (6411821)

    Published 2019
    “…<p><b>(a)</b> Python user interface: Provides a Python binding to the “C++ user interface” with some additional convenience functionality. …”
  8. 208

    DataSheet1_Development of a Multilayer Deep Neural Network Model for Predicting Hourly River Water Temperature From Meteorological Data.docx by Reza Abdi (3636907)

    Published 2021
    “…We trained the LR and DNN algorithms on Google’s TensorFlow model using Keras artificial neural network library on Python. …”
  9. 209

    Datasheet1_A Workflow for Rapid Unbiased Quantification of Fibrillar Feature Alignment in Biological Images.zip by Stefania Marcotti (5896853)

    Published 2021
    “…<p>Measuring the organization of the cellular cytoskeleton and the surrounding extracellular matrix (ECM) is currently of wide interest as changes in both local and global alignment can highlight alterations in cellular functions and material properties of the extracellular environment. …”
  10. 210

    Known compounds and new lessons: structural and electronic basis of flavonoid-based bioactivities by Rohan J. Meshram (6563189)

    Published 2019
    “…Abbreviations2′HFN-2′</p><p>hydroxy flavonone</p>2D<p>2 dimension</p>3D<p>3 dimension</p>3H7MF<p>3-hydroxy-7-methoxy flavone</p>4′HFN-4′<p>hydroxy flavonone</p>4′MF- 4′<p>methoxy flavone</p>7HFN<p>7-hydroxy flavonone</p>CHARMM<p>Chemistry at Harvard Macromolecular Mechanics</p>COX<p>cyclooxygenase</p>COX-1<p>cyclooxygenase-1</p>COX-2<p>cyclooxygenase-2</p>DM<p>dipole moment</p>DPPH- 2, 2<p>diphenyl-1-picryl hydrazine</p>EA<p>electron affinities</p>EGFR<p>epidermal growth factor receptor</p>E-HOMO<p>Highest occupied molecular orbital energy</p>E-LUMO<p>Lowest unoccupied molecular orbital energy</p>EPA<p>eicosapentaenoic acid</p>FROG2<p>FRee Online druG conformation generation</p>GA<p>Genetic Algorithm</p>GROMACS<p>GROningen MAchine for Chemical Simulations</p>HOMO<p>Highest occupied molecular orbital</p>IP<p>Ionization potential</p>LOMO<p>Lowest unoccupied molecular orbital</p>MD<p>Molecular dynamics</p>MO<p>Molecular orbital</p>NAMD<p>Nanoscale Molecular Dynamics</p>NSAIDs<p>Non-Steroidal Anti Inflammatory Drugs</p>Ns<p>nanoseconds</p>NVE<p>Ensemble-constant-energy, constant-volume, Constant particle ensemble</p>PDB-ID<p>Protein Data Bank Identifier</p>PME<p>Particle Mesh Ewald</p>PyRX<p>Python Prescription</p>RMSD<p>Root-Mean-Square Deviation</p>RMSF<p>Root-Mean-Square Fluctuation</p>RLS<p>reactive lipid species</p>ROS<p>Reactive Oxygen Species</p>SASA<p>solvent accessible surface area</p>SMILES<p>simplified molecular-input line-entry system</p>SOR<p>superoxide anion radical</p>UFF<p>Universal force field</p>VEGF<p>vascular endothelial growth factor</p>VEGFR<p>vascular endothelial growth factor receptor</p>VMD<p>Visual molecular dynamics</p><p></p> <p>hydroxy flavonone</p> <p>2 dimension</p> <p>3 dimension</p> <p>3-hydroxy-7-methoxy flavone</p> <p>hydroxy flavonone</p> <p>methoxy flavone</p> <p>7-hydroxy flavonone</p> <p>Chemistry at Harvard Macromolecular Mechanics</p> <p>cyclooxygenase</p> <p>cyclooxygenase-1</p> <p>cyclooxygenase-2</p> <p>dipole moment</p> <p>diphenyl-1-picryl hydrazine</p> <p>electron affinities</p> <p>epidermal growth factor receptor</p> <p>Highest occupied molecular orbital energy</p> <p>Lowest unoccupied molecular orbital energy</p> <p>eicosapentaenoic acid</p> <p>FRee Online druG conformation generation</p> <p>Genetic Algorithm</p> <p>GROningen MAchine for Chemical Simulations</p> <p>Highest occupied molecular orbital</p> <p>Ionization potential</p> <p>Lowest unoccupied molecular orbital</p> <p>Molecular dynamics</p> <p>Molecular orbital</p> <p>Nanoscale Molecular Dynamics</p> <p>Non-Steroidal Anti Inflammatory Drugs</p> <p>nanoseconds</p> <p>Ensemble-constant-energy, constant-volume, Constant particle ensemble</p> <p>Protein Data Bank Identifier</p> <p>Particle Mesh Ewald</p> <p>Python Prescription</p> <p>Root-Mean-Square Deviation</p> <p>Root-Mean-Square Fluctuation</p> <p>reactive lipid species</p> <p>Reactive Oxygen Species</p> <p>solvent accessible surface area</p> <p>simplified molecular-input line-entry system</p> <p>superoxide anion radical</p> <p>Universal force field</p> <p>vascular endothelial growth factor</p> <p>vascular endothelial growth factor receptor</p> <p>Visual molecular dynamics</p> <p>Communicated by Ramaswamy H. …”
  11. 211

    PySilsub—a toolbox for silent substitution by Joel Martin (11864048)

    Published 2022
    “…Device settings that will produce lights to selectively stimulate the photoreceptor(s) of interest can be found using a variety of analytic and algorithmic approaches. Here we present <em>PySilSub</em>, a novel Python package for silent substitution featuring object-oriented support for individual colorimetric observer models, multi-primary stimulation devices, and solving silent substitution problems with linear algebra and constrained numerical optimisation. …”
  12. 212

    Table1_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

    Published 2024
    “…We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. …”
  13. 213

    Table8_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

    Published 2024
    “…We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. …”
  14. 214

    Table4_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

    Published 2024
    “…We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. …”
  15. 215

    Table3_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

    Published 2024
    “…We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. …”
  16. 216

    Table2_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

    Published 2024
    “…We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. …”
  17. 217

    Table7_Natural and artificial selection of multiple alleles revealed through genomic analyses.docx by Jana Biová (11287971)

    Published 2024
    “…We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. …”
  18. 218

    Table5_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

    Published 2024
    “…We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. …”
  19. 219

    DataSheet1_Natural and artificial selection of multiple alleles revealed through genomic analyses.docx by Jana Biová (11287971)

    Published 2024
    “…We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. …”
  20. 220

    Table6_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

    Published 2024
    “…We tested and validated the algorithm and presented the utilization of MADis in a pod pigmentation L1 gene case study with multiple CMs from natural or artificial selection. …”