Proposed Algorithm. حسب Hend Bayoumi (22693738)

Comparisons between ADAM and NADAM optimizers. حسب Hend Bayoumi (22693738)

Comparison between Bisection and Newton-Raphson in terms of (A) total time consumed, and (B) maximum computation rate. حسب Hend Bayoumi (22693738)

Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30. حسب Hend Bayoumi (22693738)

Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30. حسب Hend Bayoumi (22693738)

The data processing and analysis pipeline. حسب Xin Zhang (35492)

The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus re... حسب Aninda Astuti (21736334)

Performance Comparison of State-of-the-Art WPT-MEC Offloading Methods. حسب Hend Bayoumi (22693738)

CDF of task latency, approximated as the inverse of the achieved computation rate. حسب Hend Bayoumi (22693738)

The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames. حسب Hend Bayoumi (22693738)

An Example of a WPT-MEC Network. حسب Hend Bayoumi (22693738)

Related Work Summary. حسب Hend Bayoumi (22693738)

Simulation parameters. حسب Hend Bayoumi (22693738)

Training losses for N = 10. حسب Hend Bayoumi (22693738)

Normalized computation rate for N = 10. حسب Hend Bayoumi (22693738)

Summary of Notations Used in this paper. حسب Hend Bayoumi (22693738)

Dataset 1: Zip file containing the figures of the presented methods and results in jpeg files حسب Suchismita Behera (22027316)

tUbenet Foundation Model Weights حسب Natalie Holroyd (7099391)

An exemplar procedure for activity flow modeling based on the direct and shortest paths at a network density of 15%. حسب Zhengdong Wang (35299)

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles حسب Soham Savarkar (21811825)

"…</p><p dir="ltr">Encoding: Categorical variables such as surface coating and cell type were grouped into logical classes and label-encoded to enable model compatibility.</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…"