Showing 141 - 160 results of 166 for search '(( python files implementation ) OR ( python code represents ))', query time: 0.36s Refine Results
  1. 141

    Bacterial persistence modulates the speed, magnitude and onset of antibiotic resistance evolution by Giorgio Boccarella (22810952)

    Published 2025
    “…This file can be used together with the analysis code (link to be added upon publication) to generate all figures.…”
  2. 142

    Probabilistic-QSR-GeoQA by Mohammad Kazemi (19442467)

    Published 2024
    “…Also we have written Python API for Probcog (ProbCog-API.py) and SparQ reasoners (SparQ-API.py).…”
  3. 143

    Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis by Alan Glanz (22109698)

    Published 2025
    “…</p><p dir="ltr">Genosophus addresses this gap by offering:</p><ul><li>A <b>quantitative diagnostic toolkit</b> for internal model health</li><li>A <b>framework for detecting emergent structure</b></li><li>A <b>method to measure phase transitions, collapse, or stabilization</b></li><li>A <b>model-agnostic system for embedding-space dynamics</b></li></ul><p dir="ltr">This tool is intended for use in interpretability research, safety evaluations, representation studies, and monitoring model behavior during training or fine-tuning.</p><h2><b>Included Files</b></h2><h3><b>1. </b><code><strong>GenosophusV2.py</strong></code></h3><p dir="ltr">Executable Python implementation of the Genosophus Engine.…”
  4. 144

    <b>Use case codes of the DDS3 and DDS4 datasets for bacillus segmentation and tuberculosis diagnosis, respectively</b> by Marly G F Costa (19812192)

    Published 2025
    “…The encoder was implemented with depth-wise separable convolution layers13.…”
  5. 145

    Data and code for: Automatic fish scale analysis by Christian Vogelmann (21646472)

    Published 2025
    “…</i></li></ul></li><li><b>README.txt</b> – detailed file explanations and usage instructions</li></ul><p dir="ltr">The full statistical analysis and visualization pipeline is implemented in R and hosted on GitHub:<br>https://github.com/Birdy332/Automatic-fish-scale-analysis-r-scripts</p><p dir="ltr"><br></p><p dir="ltr">All figures shown in the manuscript can be reproduced using these scripts and the datasets provided here.…”
  6. 146

    The artifacts and data for the paper "DD4AV: Detecting Atomicity Violations in Interrupt-Driven Programs with Guided Concolic Execution and Filtering" (OOPSLA 2025) by zixuan yuan (17602152)

    Published 2025
    “…</p><pre><pre>sudo apt-get install -y wget git build-essential python3 python python-pip python3-pip tmux cmake libtool libtool-bin automake autoconf autotools-dev m4 autopoint libboost-dev help2man gnulib bison flex texinfo zlib1g-dev libexpat1-dev libfreetype6 libfreetype6-dev libbz2-dev liblzo2-dev libtinfo-dev libssl-dev pkg-config libswscale-dev libarchive-dev liblzma-dev liblz4-dev doxygen libncurses5 vim intltool gcc-multilib sudo --fix-missing<br></pre></pre><pre><pre>pip install numpy && pip3 install numpy && pip3 install sysv_ipc<br></pre></pre><h4><b>Download the Code</b></h4><p dir="ltr">Download <b>DD4AV</b> from the Figshare website to your local machine and navigate to the project directory:</p><pre><pre>cd DD4AV<br></pre></pre><h4><b>Configure Environment and Install the Tool</b></h4><p dir="ltr">For convenience, we provide shell scripts to automate the installation process. …”
  7. 147

    <b>Code and derived data for</b><b>Training Sample Location Matters: Accuracy Impacts in LULC Classification</b> by Pajtim Zariqi (22155799)

    Published 2025
    “…<p dir="ltr">This repository contains the analysis code and derived outputs for the study <i>“Training Sample Location Matters: Accuracy Impacts in LULC Classification”</i>. The workflow was implemented in Google Earth Engine (JavaScript API) and replicated in Python notebooks (Jupyter/Kaggle) for reproducibility.…”
  8. 148

    Testing Code for JcvPCA and JsvCRP. by Océane Dubois (21989812)

    Published 2025
    “…<p>This file contains the code that implements both metrics in python and apply them on a simulated dataset.…”
  9. 149

    Electrical Tactile Dataset (Piezoelectric and Accelerometer) for textures by Dexter Shepherd (13238508)

    Published 2025
    “…</p><p dir="ltr">X shape: (Number, frame, sensor index)</p><p dir="ltr">y shape: (Number,)</p><p dir="ltr">All files are in compressed numpy format. Python users can load in the dataset using the code provided in the ReadMe.…”
  10. 150

    Phylogenomics of aquatic bacteria by Krzysztof Jurdzinski (12519700)

    Published 2025
    “…</p> <p><br></p> <p>all_MSG_ids.txt - a text file with names of all the representative MAGs within all the MSG pairs.</p> <p><br></p> <p>filter_MSGs.py - a Python script to extract the MAGs from within the MSGs (given all_MSG_ids.txt) from a folder containing a larger set of sequences.…”
  11. 151

    Optical Tactile (TacTip) Dataset for texture classification by Dexter Shepherd (13238508)

    Published 2025
    “…</p><p dir="ltr">X shape: (Number, frame, h, w)</p><p dir="ltr">y shape: (Number,)</p><p dir="ltr"><br></p><p dir="ltr">All files are in compressed numpy format. Python users can load in the dataset using the code provided in the ReadMe.…”
  12. 152
  13. 153

    Ambient Air Pollutant Dynamics (2010–2025) and the Exceptional Winter 2016–17 Pollution Episode: Implications for a Uranium/Arsenic Exposure Event by Thomas Clemens Carmine (19756929)

    Published 2025
    “…The full implementation is detailed in the accompanying Python script (Imputation_Air_Pollutants_NABEL.py). …”
  14. 154

    Improving the calibration of an integrated CA-What If? digital planning framework by CA What If? (21381170)

    Published 2025
    “…</p><p dir="ltr">This dataset includes (1) all required data for reproducing the materials within the manuscript, (2) detailed Python codes of the proposed CA-What If? model, and (3) a step-by-step instruction document.…”
  15. 155

    Hippocampal and cortical activity reflect early hyperexcitability in an Alzheimer's mouse model by Marina Diachenko (19739092)

    Published 2025
    “…</p><p dir="ltr">All data are available upon request. The standalone Python implementation of the fE/I algorithm is available under a CC-BY-NC-SA license at <a href="https://github.com/arthur-ervin/crosci" target="_blank">https://github.com/arthur-ervin/crosci</a>. …”
  16. 156

    Core data by Baoqiang Chen (21099509)

    Published 2025
    “…</p><p><br></p><p dir="ltr">For the 5′ UTR library, we developed a Python script to extract sequences and Unique Molecular Identifiers (UMIs) from the FASTQ files. …”
  17. 157

    Building footprtints from 1970s Hexagon spy satellite images for four global urban growth hotspots by Franz Schug (10165159)

    Published 2025
    “…</p> <p><strong>Processing environment</strong></p> <p>This research has been conducted using Python for ESRI ArcGIS Pro version 3.2.1 and the TensorFlow package. …”
  18. 158

    PepENS by Abel Chandra (16854753)

    Published 2025
    “…<br><br>Download and Use</p><p dir="ltr">The codes for Datasets 1 and 2 are found in the respective folders of this repository.…”
  19. 159

    Mean Annual Habitat Quality and Its Driving Variables in China (1990–2018) by ChenXi Zhu (21374876)

    Published 2025
    “…</p><p dir="ltr">(HQ: Habitat Quality; CZ: Climate Zone; FFI: Forest Fragmentation Index; GPP: Gross Primary Productivity; Light: Nighttime Lights; PRE: Mean Annual Precipitation Sum; ASP: Aspect; RAD: Solar Radiation; SLOPE: Slope; TEMP: Mean Annual Temperature; SM: Soil Moisture)</p><p dir="ltr"><br>A Python script used for modeling habitat quality, including mean encoding of the categorical variable climate zone (CZ), multicollinearity testing using Variance Inflation Factor (VIF), and implementation of four machine learning models to predict habitat quality.…”
  20. 160

    <b>Engineered Muscle-Derived Extracellular Vesicles Boost Insulin Sensitivity and Glucose Regulation</b> by Hagit Shoyhet (21090650)

    Published 2025
    “…</p><p dir="ltr"><b>miR_path_target_enrichment.csv</b></p><p dir="ltr"><b>Description:</b> KEGG pathway enrichment analysis results of shared mRNA targets of miRNAs miR-16-5p, miR-122-5p and miR-486-5p ranked by their interaction score defined in our paper. this includes the pathway name, the enrichment p-value, number of genes found in the term and number of miRNAs targeting these genes</p><p dir="ltr"><b>Code/software</b></p><p dir="ltr">Data were analyzed using R-V4.0.4, Python-V3.9.2 and GraphPad software. miRNA analyses were run in R-V4.0.4 Differential expression analysis was conducted using the “DEseq2” package and corrected for multiple hypotheses by FDR. …”