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files implementation » time implementation (Expand Search), pilot implementation (Expand Search), assess implementation (Expand Search)
python model » python tool (Expand Search), action model (Expand Search), motion model (Expand Search)
files implementation » time implementation (Expand Search), pilot implementation (Expand Search), assess implementation (Expand Search)
python model » python tool (Expand Search), action model (Expand Search), motion model (Expand Search)
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221
Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games"
Published 2024“…<br></pre></pre><h2>Structure and How to run</h2><p dir="ltr">There are four Python files in the repository.</p><pre><pre>(i) `StrategyIteration.py` is the backend code, containing the implementation of the RPPI algorithm described in the paper.…”
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222
<b>Anthropogenic nutrient inputs cause excessive algal growth for nearly half the world’s population</b>
Published 2025“…<p dir="ltr">Contains</p><p dir="ltr">Final Analysis Output.xlsx: Current and reference concentrations of DRP, TP, NO3-N and TN along with pivot table analysis</p><p dir="ltr">Code: Python code used to implement the model in ArcGIS Pro.…”
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223
Data from: Circadian activity predicts breeding phenology in the Asian burying beetle <i>Nicrophorus nepalensis</i>
Published 2025“…</p><p dir="ltr">The dataset includes:</p><ol><li>Raw locomotor activity measurements (.txt files) with 1-minute resolution</li><li>Breeding experiment data (Pair_breeding.csv) documenting nest IDs, population sources, photoperiod treatments, and breeding success</li><li>Activity measurement metadata (Loc_metadataset.csv) containing detailed experimental parameters and daily activity metrics extracted using tsfresh</li></ol><p dir="ltr">The repository also includes complete analysis pipelines implemented in both Python (3.8.8) and R (4.3.1), featuring:</p><ul><li>Data preprocessing and machine learning model development</li><li>Statistical analyses</li><li>Visualization scripts for generating Shapley plots, activity pattern plots, and other figures</li></ul><p></p>…”
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224
Table & Figure.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks
Published 2025“…Supplementary Materials</p> <p><br></p> <p>Experimental protocols and study design details</p> <p><br></p> <p>Questionnaires, surveys, or rubrics used in the study</p> <p><br></p> <p>Educational materials related to HOTS-based mathematics tasks</p> <p><br></p> <p><br></p> <p><br></p> <p>3. Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …”
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225
Raw Data EEG.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks
Published 2025“…Supplementary Materials</p> <p><br></p> <p>Experimental protocols and study design details</p> <p><br></p> <p>Questionnaires, surveys, or rubrics used in the study</p> <p><br></p> <p>Educational materials related to HOTS-based mathematics tasks</p> <p><br></p> <p><br></p> <p><br></p> <p>3. Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …”
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226
Keyhole Imagery Global Coverage Dataset (1960–1984)
Published 2025“…</li><li><b>Code</b>: Python scripts implementing the three-step workflow (imagery classification, global grid generation, and point-based property calculation).…”
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227
<b>Data Availability</b>
Published 2025“…</p><p dir="ltr">python scripts documenting the implementation of the Mixture Density Network (MDN) algorithm, including hyperparameter tuning and uncertainty quantification.…”
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228
<b>Data Availability</b>
Published 2025“…</p><p dir="ltr">python scripts documenting the implementation of the Mixture Density Network (MDN) algorithm, including hyperparameter tuning and uncertainty quantification.…”
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229
NanoDB: Research Activity Data Management System
Published 2024“…In a Python environment or as an executable. Ease of Implementation: Using the flexibility of the Python framework all the data setup and algorithm can me modified and new functions can be easily added. …”
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230
Demonstration of Isosteric Heat of Adsorption Calculation using AIFs and pyGAPs
Published 2025“…</p><p dir="ltr">The calculation is performed using the Clausius-Clapeyron method as implemented in the <code><strong>pyGAPS</strong></code> Python library for adsorption science. …”
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231
HCC Evaluation Dataset and Results
Published 2024“…</p><h3>Report Script</h3><p dir="ltr">On the top-level directory you find a <code>report.py</code> file, which is an executable Python script. …”
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232
Supervised Classification of Burned Areas Using Spectral Reflectance and Machine Learning
Published 2025“…Six Python scripts are provided, each implementing a distinct machine learning algorithm—Random Forest, k-Nearest Neighbors (k-NN), Multi-Layer Perceptron (MLP), Decision Tree, Naïve Bayes, and Logistic Regression. …”
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233
<b>Algorithm Pseudocode</b>
Published 2025“…The pseudo-code follows standard Python syntax specifications for functions and loops and is easy to understand and implement. …”
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234
A Hybrid Ensemble-Based Parallel Learning Framework for Multi-Omics Data Integration and Cancer Subtype Classification
Published 2025“…<p dir="ltr">The code supports replication of results on TCGA Pan-cancer and BRCA datasets and includes data preprocessing, model training, and evaluation scripts:<br>Python scripts for data preprocessing and integration</p><ul><li>Autoencoder implementation for multimodal feature learning</li><li>Hybrid ensemble training code (DL/ML models and meta-learner)</li><li>PSO and backpropagation hybrid optimization code</li><li>Parallel execution scripts</li><li>Instructions for replicating results on TCGA Pan-cancer and BRCA datasets</li></ul><p></p>…”
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235
The artifacts and data for the paper "DD4AV: Detecting Atomicity Violations in Interrupt-Driven Programs with Guided Concolic Execution and Filtering" (OOPSLA 2025)
Published 2025“…</li><li><ul><li><code><strong>DBDS</strong></code>: The code implements our proposed dynamic scheduling execution method, which systematically explores task interleaving for atomicity violation detection, enhanced by an effective prefix-directed strategy.…”
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236
Curvature-Adaptive Embedding of Geographic Knowledge Graphs in Hyperbolic Space
Published 2025“…</p><h3>Requirements</h3><ul><li>Python 3.7</li><li>PyTorch 1.10.0 & CUDA 11.8</li></ul><h3>Main Result Running commands:</h3><p dir="ltr">Execute <code>.sh: bash .…”
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237
Ambient Air Pollutant Dynamics (2010–2025) and the Exceptional Winter 2016–17 Pollution Episode: Implications for a Uranium/Arsenic Exposure Event
Published 2025“…Includes imputation statistics, data dictionary, and the Python imputation code (Imputation_Air_Pollutants_NABEL.py). …”
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238
Gene Editing using Transformer Architecture
Published 2025“…</p><p dir="ltr">Once TASAG detects a deviation from a reference sequence (e.g., the H-Bot sequence), it facilitates on-screen gene editing, enabling targeted mutations or the insertion of desired genes. Implementation requires Python and deep learning frameworks like TensorFlow or PyTorch, with optional use of Biopython for genetic sequence handling. …”
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239
IGD-cyberbullying-detection-AI
Published 2024“…</p><h2>Requirements</h2><p dir="ltr">To run this code, you'll need the following dependencies:</p><ul><li>Python 3.x</li><li>TensorFlow</li><li>scikit-learn</li><li>pandas</li><li>numpy</li><li>matplotlib</li><li>imbalanced-learn</li></ul><p dir="ltr">You can install the required dependencies using the provided <code>requirements.txt</code> file.…”
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240
World Heritage documents reveal persistent gaps between climate awareness and local action
Published 2025“…The analysis section includes a GLM model implemented in R, along with evaluation tools such as correlation heatmaps, ICC agreement analysis, and MCC-based binary classification assessment. …”