Expanding Access to Advanced Scientific Workflows: The NSF Unidata Science Gateway Leverages Innovative Capabilities of the NSF Jetstream2 Cloud for Atmospheric Science Education حسب Julien Chastang (640650)

"…</p><p><br></p><p dir="ltr">This presentation will highlight two case studies that demonstrate the practical applications of our advanced computational tools. The first case study involves our support of a Master’s thesis project focused on the predictive capabilities of AI/ML in atmospheric science, specifically using convolutional neural networks (CNNs) to simulate and predict storm patterns. …"

DeepB3Pred_source_code حسب Muhammad Arif (17012472)

Computing speed and memory usage. حسب David Berling (22170661)

"…<b>(b)</b> Physical memory consumption depending on simulated plane in radial and depth direction. Color coding same as in (a). Memory consumption was recorded as the maximum resident size during simulation monitored with the Python built-in module resource. …"

The codes and data for "Lane Extraction from Trajectories at Road Intersections Based on Graph Transformer Network" حسب Chongshan Wan (19247614)

"…The lane extraction result is saved in `result/predicted_lane.csv`.</p><p dir="ltr"></p><h2>Requirements</h2><p dir="ltr">The codes use the following dependencies with Python 3.11</p><ul><li>networkx==3.2.1</li><li>pytorch==2.0.1</li><li>torch-geometric==2.5.3</li><li>geopandas==1.0.1</li></ul><p dir="ltr"><br></p>…"

Extending the pyAFQ software. حسب John Kruper (18809386)

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

"…<p dir="ltr"><b>Use case codes of the DDS3 and DDS4 datasets for bacillus segmentation and tuberculosis diagnosis, respectively</b></p><p dir="ltr">The code was developed in the Google Collaboratory environment, using Python version 3.7.13, with TensorFlow 2.8.2. …"

Relationship between sunlight measures and daily activity. حسب Oleg Kovtun (1618660)

Data and some code used in the paper:<b>Expansion quantization network: A micro-emotion detection and annotation framework</b> حسب Zhou (20184816)

"…Attached is the micro-emotion annotation code based on pytorch, which can be used to annotate the Goemotions dataset by yourself, or predict the emotion classification based on the annotation results. …"

Heat Map Correlation. حسب Majed Alzara (20700224)

"…The study shows that deep learning models can accurately predict economic indicators. This gives Egypt’s construction industry a useful, data-driven tool for estimating costs ahead of time. …"

Research Methodology. حسب Majed Alzara (20700224)

"…The study shows that deep learning models can accurately predict economic indicators. This gives Egypt’s construction industry a useful, data-driven tool for estimating costs ahead of time. …"

Spearman’s Rank Correlation. حسب Majed Alzara (20700224)

"…The study shows that deep learning models can accurately predict economic indicators. This gives Egypt’s construction industry a useful, data-driven tool for estimating costs ahead of time. …"

Result of Stepwise Regression. حسب Majed Alzara (20700224)

"…The study shows that deep learning models can accurately predict economic indicators. This gives Egypt’s construction industry a useful, data-driven tool for estimating costs ahead of time. …"

Variance Inflation Factor. حسب Majed Alzara (20700224)

"…The study shows that deep learning models can accurately predict economic indicators. This gives Egypt’s construction industry a useful, data-driven tool for estimating costs ahead of time. …"

Pearson Correlation Matrix. حسب Majed Alzara (20700224)

"…The study shows that deep learning models can accurately predict economic indicators. This gives Egypt’s construction industry a useful, data-driven tool for estimating costs ahead of time. …"

Evaluation Metrics for LSTM Model and GRU Model. حسب Majed Alzara (20700224)

"…The study shows that deep learning models can accurately predict economic indicators. This gives Egypt’s construction industry a useful, data-driven tool for estimating costs ahead of time. …"

A model of neural population dynamics for flexible sensorimotor control حسب Hari Kalidindi (17123467)

The Twin Prime Conjecture: Collapse-Band Parity Cancellation and Operator Proof حسب Jennifer Bulyaki (22283308)

Table 1_Magnetic resonance imaging-based deep learning for predicting subtypes of glioma.docx حسب Zhen Yang (107412)

"…The receiver operating characteristic curve (ROC), area under the curve (AUC) of the ROC were generated in the jupyter notebook tool using python language to evaluate the accuracy of the models in classification and comparing the predictive value of different MRI sequences.…"

Data and Code for 'A Comparative Study of Physics-Informed and Data-Driven Neural Networks for Compound Flood Simulation at River-Ocean Interfaces: A Case Study of Hurricane Irene' حسب Dongyu Feng (21196556)

"…<br><br>conda create --name tf2 --file requirement_tf2.txt<br>conda activate tf2<br><br><br>### Before training<br>Before running the code, need to create folders to save the model output<br><br>For CNN, create /files/CNN<br><br>For PINNs, create /saved_model<br><br>For saving figures from visualization, create /figures<br><br></p><p dir="ltr">Training and Results</p><p dir="ltr"><br>PINNs<br>Training: To train the model, run:</p><p dir="ltr">python PINN_test_bnd_uh_Telemac.py</p><p dir="ltr">python PINN_test_bnd_uh_Telemac_FDM.py<br></p><p dir="ltr">Result Plotting and Comparison: For plotting and comparing results, use:</p><p dir="ltr">python PINN_plot_comparison.py<br><br><br>Data-driven Model<br>CNN Training: To train the CNN model, execute:</p><p dir="ltr">python train_CNN.py<br><br>Result Visualization: To visualize the results of the CNN model, run:</p><p dir="ltr">python predict_CNN.py<br><br>To reproduce all results and figures in the manuscript, please refer to the scripts in analysis/</p>…"

Data from: Circadian activity predicts breeding phenology in the Asian burying beetle <i>Nicrophorus nepalensis</i> حسب Hao Chen (20313552)

"…The repository contains all necessary data and code for reproducing the analyses of beetle breeding phenology predictions using circadian activity patterns.…"