Python code to find amino acid positions with matched anchor residue motifs and probable escape variants associated with HLA-Class-I binding. by Nobubelo K. Ngandu (12075108)

Python code to find amino acid positions with matched anchor residue motifs and probable escape variants associated with HLA-Class-II binding. by Nobubelo K. Ngandu (12075108)

FlakyFix: Using Large Language Models for Predicting Flaky Test Fix Categories and Test Code Repair by Sakina Fatima (15362704)

“…<p dir="ltr">This is the replication package associated with the paper: 'FlakyFix: Using Large Language Models for Predicting Flaky Test Fix Categories and Test for Code Repair'</p><p><br></p><p dir="ltr">### Requirements</p><p dir="ltr">This is a list of all required python packages:</p><p dir="ltr">-imbalanced_learn==0.8.1</p><p dir="ltr">-numpy==1.19.5</p><p dir="ltr">-pandas==1.3.3</p><p dir="ltr">-transformers==4.10.2</p><p dir="ltr">-torch==1.5.0</p><p dir="ltr">-scikit_learn==0.24.2</p><p dir="ltr">-openai==v0.28.1</p><p><br></p><p dir="ltr">#Automated tool for labelling dataset with flaky test fix categories</p><p><br></p><p dir="ltr">This is a step-by-step guideline for automatically labelling dataset with flaky test fix categories</p><p><br></p><p><br></p><p dir="ltr">### Input Files:</p><p dir="ltr">This is a an input file that is required to accomplish this step:</p><p dir="ltr">* Data/IdoFT_dataset_filtered.csv</p><p dir="ltr">https://figshare.com/s/47f0fb6207ac3f9e2351</p><p><br></p><p dir="ltr">### Output Files:</p><p dir="ltr">* Results/IdoFT_dataset_filtered.csv</p><p><br></p><p><br></p><p dir="ltr">### Replicating the experiment</p><p><br></p><p dir="ltr">This experiment can be executed using the following commands after navigating to the `Code\` folder:</p><p><br></p><p dir="ltr">```console</p><p dir="ltr">bash Automated_labelling_tool.sh</p><p>```</p><p><br></p><p dir="ltr">It will generate the dataset required to run our prediction models to predict the category of the fix, given a flaky test code</p><p><br></p><p>---</p><p><br></p><p dir="ltr"># Prediction models for fix categories using the test case code</p><p><br></p><p dir="ltr">This is the guideline for replicating the experiments we used to evaluate our prediction models i.e. …”

Python-Based Algorithm for Calculating Physical Properties of Aqueous Mixtures Composed of Substances Not Available in Databases by Jina Lee (3138492)

“…In this study, we developed a Python-based open-source algorithm compatible with the aqueous physical property models provided in the electrolyte templates of AspenTech software. …”

Python-Based Algorithm for Calculating Physical Properties of Aqueous Mixtures Composed of Substances Not Available in Databases by Jina Lee (3138492)

“…In this study, we developed a Python-based open-source algorithm compatible with the aqueous physical property models provided in the electrolyte templates of AspenTech software. …”

The ROC, calibration curve and DCA of the prediction model based on MRI. by Jiangfa Li (18345033)

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Supplementary data for PCI-based pavement modelling: code, presentation, and additional analysis by Azam Amir (21505033)

Code for the HIVE Appendicitis prediction modelRepository with LLM_data_extractor_optuna for automated feature extraction by Anoeska Schipper (18513465)

“…</p><p dir="ltr"><b>LLM Data Extractor optuna repo</b> is a Python framework for generating and evaluating clinical text predictions using large language models (LLMs) like <code>qwen2.5</code>. …”

The ROC, calibration curve and DCA of the predictive model based on enhanced CT. by Jiangfa Li (18345033)

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The ROC calibration curve and DCA of the combined prediction model based on CT and MRI. by Jiangfa Li (18345033)

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Settings for ABC-SMC code. by Román Zapién-Campos (9592478)

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

“…</p><p dir="ltr"><i>cd 1point2dem/CIPrediction</i></p><p dir="ltr"><i>python -u point_prediction.py --model [GCN|ChebNet|GATNet]</i></p><h3>step 4: Parallel computation</h3><p dir="ltr">This step uses the trained models to optimize parallel computation. …”

The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" by FirstName LastName (20554465)

“…</p><p dir="ltr"><i>cd 1point2dem/CIPrediction</i></p><p dir="ltr"><i>python -u point_prediction.py --model [GCN|ChebNet|GATNet]</i></p><h3>step 4: Parallel computation</h3><p dir="ltr">This step uses the trained models to optimize parallel computation. …”

Table 1_Entropy-adaptive differential privacy federated learning for student performance prediction and privacy protection: a case study in Python programming.docx by Shanwei Chen (12031760)

“…This study proposes an Entropy-Adaptive Differential Privacy Federated Learning method (EADP-FedAvg) to enhance the accuracy of student performance prediction while ensuring data privacy. Based on online test records from Python programming courses for Electronic Engineering students (grade 2021–2023) at the School of Physics and Optoelectronic Technology, Baoji University of Arts and Sciences, China, the study uses a Multilayer Perceptron (MLP) model and 10 distributed clients for training. …”

The ROC, calibration curve and DCA of the combined prediction model based on tumor diameter combined with the optimal radiomics features. by Jiangfa Li (18345033)

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ANFIS model for the four parameters. by Ahmed G. Ismail (21519374)

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LHS model for the four parameters. by Ahmed G. Ismail (21519374)

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Steering system model. by Honglei Pang (22693724)

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Braking system model. by Honglei Pang (22693724)

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Partial Rank Correlation Coefficient (PRCC) sensitivity analysis results, obtained using LHS with 1000 samples and run in Python version 3.11.0. by Tinashe Victor Mupedza (22022124)