Showing 221 - 232 results of 232 for search '(( algorithm python function ) OR ( algorithms waning function ))', query time: 0.20s Refine Results
  1. 221

    VinaLigGen: a method to generate LigPlots and retrieval of hydrogen and hydrophobic interactions from protein-ligand complexes by Raghvendra Agrawal (17135479)

    Published 2023
    “…This paper describes an implementation of an automation technique on the executable programs like ligplot.exe, hbplus.exe and hbadd.exe to obtain the 2D interaction map (LigPlots) of the protein and ligand complex (*.ps) and hydrogen bonds and hydrophobic interactions in *.csv format for molecules to be considered for virtual screening by using some sorting & searching algorithms and python’s file handling functions, and it also mentions the program’s limitations and availability of the program. …”
  2. 222

    Data_Sheet_1_MCIC: Automated Identification of Cellulases From Metagenomic Data and Characterization Based on Temperature and pH Dependence.docx by Mehdi Foroozandeh Shahraki (9555317)

    Published 2020
    “…MCIC is freely available as a python package and standalone toolkit for Windows and Linux-based operating systems with several functions to facilitate the screening and thermal and pH dependence prediction of cellulases.…”
  3. 223

    Presentation_1_NeuroEditor: a tool to edit and visualize neuronal morphologies.pdf by Ivan Velasco (9463019)

    Published 2024
    “…Moreover, NeuroEditor can be easily extended by users, who can program their own algorithms in Python and run them within the tool. Last, this paper includes an example showing how users can easily define a customized workflow by applying a sequence of editing operations. …”
  4. 224

    Decoding fairness motivations - repository by Sebastian Speer (6489207)

    Published 2020
    “…</div><div> In the non-social control condition (24 trials), participants played against a computer algorithm, allegedly programmed to mimic human behaviour. …”
  5. 225

    Barro Colorado Island 50-ha plot aerial photogrammetry orthomosaics and digital surface models for 2018-2023: Globally and locally aligned time series. by Vicente Vasquez (13550731)

    Published 2023
    “…Agisoft LLC. https://www.agisoft.com/pdf/metashape_python_api_2_0_4.pdf.</p><p dir="ltr">Vicente Vasquez. (2023). …”
  6. 226

    datasheet1_ThermoScan: Semi-automatic Identification of Protein Stability Data From PubMed.xlsx by Paola Turina (10431428)

    Published 2021
    “…The results show that ThermoScan returns accurate predictions and outperforms recently developed text-mining algorithms based on the analysis of publication abstracts.…”
  7. 227

    presentation1_ThermoScan: Semi-automatic Identification of Protein Stability Data From PubMed.pdf by Paola Turina (10431428)

    Published 2021
    “…The results show that ThermoScan returns accurate predictions and outperforms recently developed text-mining algorithms based on the analysis of publication abstracts.…”
  8. 228

    PresQT - Services to Improve Re-use and FAIRness of Research Data and Software by Sandra Gesing (4501198)

    Published 2021
    “…PresQT services are easily integratable and target systems can be added via extending JSON files and Python functions. Data is packaged as BagITs for uploads, downloads and transfers. …”
  9. 229

    Skeletal_ Muscle_MRI_Registration by Lucia Fontana (9435020)

    Published 2020
    “…</p> <p>wxPython library was employed to develop the GUI, which is composed by two main windows – initial window and registration window – and 5 secondary frames for support functionalities. 3D images are presented with three views – axial, coronal and sagittal – with three sliders to adjust maximum value, minimum value, and gamma correction.…”
  10. 230

    A paired dataset of multi-modal MRI at 3 Tesla and 7 Tesla with manual hippocampal subfield segmentations on 7T T2-weighted images by Shuyu Li (18401358)

    Published 2024
    “…</p><p dir="ltr">The dataset is freely accessible on IEEE DataPort, a data repository created by IEEE and can be found at the following URL: <a href="https://ieeexplore.ieee.org/document/10218394/algorithms?tabFilter=dataset" target="_blank">https://ieeexplore.ieee.org/document/10218394/algorithms?…”
  11. 231

    Expression vs genomics for predicting dependencies by Broad DepMap (5514062)

    Published 2024
    “…If you are interested in trying machine learning, the files Features.hdf5 and Target.hdf5 contain the data munged in a convenient form for standard supervised machine learning algorithms.</p><p dir="ltr"><br></p><p dir="ltr">Some large files are in the binary format hdf5 for efficiency in space and read-in. …”
  12. 232

    An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows by Pierre-Alexis DELAROCHE (22092572)

    Published 2025
    “…Performance Profiling Algorithms Energy Measurement Methodology # Pseudo-algorithmic representation of measurement protocol def capture_energy_metrics(workflow_type: WorkflowEnum, asset_vector: List[PhotoAsset]) -> EnergyProfile: baseline_power = sample_idle_power_draw(duration=30) with PowerMonitoringContext() as pmc: start_timestamp = rdtsc() # Read time-stamp counter if workflow_type == WorkflowEnum.LOCAL: result = execute_local_pipeline(asset_vector) elif workflow_type == WorkflowEnum.CLOUD: result = execute_cloud_pipeline(asset_vector) end_timestamp = rdtsc() energy_profile = EnergyProfile( duration=cycles_to_seconds(end_timestamp - start_timestamp), peak_power=pmc.get_peak_consumption(), average_power=pmc.get_mean_consumption(), total_energy=integrate_power_curve(pmc.get_power_trace()) ) return energy_profile Statistical Analysis Framework Our analytical pipeline employs advanced statistical methodologies including: Variance Decomposition: ANOVA with nested factors for hardware configuration effects Regression Analysis: Generalized Linear Models (GLM) with log-link functions for energy modeling Temporal Analysis: Fourier transform-based frequency domain analysis of power consumption patterns Cluster Analysis: K-means clustering with Euclidean distance metrics for workflow classification Data Validation and Quality Assurance Measurement Uncertainty Quantification All energy measurements incorporate systematic and random error propagation analysis: Instrument Precision: ±0.1W for CPU power, ±0.5W for GPU power Temporal Resolution: 1ms sampling with Nyquist frequency considerations Calibration Protocol: NIST-traceable power standards with periodic recalibration Environmental Controls: Temperature-compensated measurements in climate-controlled facility Outlier Detection Algorithms Statistical outliers are identified using the Interquartile Range (IQR) method with Tukey's fence criteria (Q₁ - 1.5×IQR, Q₃ + 1.5×IQR). …”