BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…We believe that BaNDyT is the first software package to include specialized and advanced features for analyzing MD simulation trajectories using a probabilistic graphical network model. We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”

MMRCC_original code by Rui Chen (21529631)

Python code for hierarchical cluster analysis of detected R-strategies from rule-based NLP on 500 circular economy definitions by Zahir Barahmand (18008947)

“…</p><p dir="ltr">This Python code was optimized and debugged using ChatGPT-4o to ensure implementation efficiency, accuracy, and clarity.…”

6. Motif Code Theory by William Terry (22279591)

“…<p dir="ltr">The Motif Code Theory (MCT) simulation code, mct_unified_code.py, is a Python 3.9 script that models the universe as a time-dependent directed multigraph G(t) = (V(t), E(t)) with N=10^7 vertices (representing quantum fields/particles) and edges (interactions). …”

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

“…</p><h3><b>Model training</b></h3><h4><code>python train_GTN.py</code></h4><p dir="ltr">This step trains the GTN model. …”

Numerical data and codes for "Noisy Probabilistic Error Cancellation and Generalized Physical Implementability" by Tian-Ren Jin (18781930)

“…<p dir="ltr">This data set contains the data and codes for "Noisy Probabilistic Error Cancellation and Generalized Physical Implementability". We numerically simulate the bias of noisy probabilistic error cancellation with noisy Pauli operations and the bias of error model violation.…”

BGC-Prophet by Haohong Zhang (17911673)

“…/output/ --name split --threads 10</code></pre><p dir="ltr"><b>4. Gene Prediction</b></p><p dir="ltr">Detect BGC genes using a trained model:</p><pre><code>bgc_prophet predict --datasetPath .…”

Probabilities of normal and various cyber attack types over time sequence. by Mohanad Faeq Ali (21354273)

Subjects:

Graphical abstract of HCAP. by Mohanad Faeq Ali (21354273)

Subjects:

Recall analysis. by Mohanad Faeq Ali (21354273)

Subjects:

FPR and FNR analysis based on varying cyber attack types. by Mohanad Faeq Ali (21354273)

Subjects:

Analysis of IoMT data sources. by Mohanad Faeq Ali (21354273)

Subjects:

Prediction accuracy on varying attack types. by Mohanad Faeq Ali (21354273)

Subjects:

<b> </b> Precision analysis. by Mohanad Faeq Ali (21354273)

Subjects:

Convergence rate analysis. by Mohanad Faeq Ali (21354273)

Subjects:

Computational efficiency. by Mohanad Faeq Ali (21354273)

Subjects:

FPR and FNR analysis based on different time steps. by Mohanad Faeq Ali (21354273)

Subjects:

Performance comparison of cyber security techniques in IoMT healthcare devices. by Mohanad Faeq Ali (21354273)

Subjects:

Prediction accuracy analysis over time steps. by Mohanad Faeq Ali (21354273)

Subjects:

Impact of cyberattack types on IoMT devices. by Mohanad Faeq Ali (21354273)

Subjects: