ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

BIC-SAC findings. by Nayeem Ahmad Khan (11727377)

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BIC Non-linearity findings. by Nayeem Ahmad Khan (11727377)

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SAC’s findings for suggested S-Box. by Nayeem Ahmad Khan (11727377)

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Non-linearities’ findings against the proposed S-Box. by Nayeem Ahmad Khan (11727377)

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Federated averaging algorithm pseudocode. by Hadi Mohammadian KhalafAnsar (22783784)

Performance of machine learning algorithms. by Wenxue Liu (6877754)

The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…We find evidence that the generalised GLS-KGR algorithm is well-suited to such time-series applications, outperforming several standard techniques on this dataset.…”

Feature selection using Boruta algorithm. by Shayla Naznin (13014015)

“…</p><p>Methods</p><p>Multiple machine learning (ML) algorithms were applied to data from the 2022 Bangladesh Demographic Health Survey, including Random Forest, Decision Tree, K-Nearest Neighbors, Logistic Regression, Support Vector Machine, XGBoost, LightGBM and Neural Networks. …”

Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. by Abdullah Asım Yılmaz (20715311)

Local Means Thresholding Algorithm shows high robustness. by Araven Tiroumalechetty (17827252)

A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

Technological Fitness and Coherence explanation. Schematic representation of the workings of the Fitness and Complexity algorithm and Coherence diversification. by Matteo Straccamore (15083799)

Data Sheet 1_i-DENV: development of QSAR based regression models for predicting inhibitors targeting non-structural (NS) proteins of dengue virus.docx by Sakshi Gautam (10305897)

Training and Testing Set for HRDsig Algorithm Development. by Wenshu Li (762627)

Data underlying the findings. by Carol Kotliar (22351525)

The robustness test results of the model. by Xini Fang (20861990)

Data Sheet 1_A method for finding epistatic effects of maternal and fetal variants.docx by Michael Nodzenski (3714730)

“…Though the epistasis-mining algorithms MDR-PDT, TrioFS, and EPISFA-LD were originally designed to find epistatic offspring variants, we generalize them to include maternal SNPs and search more broadly. …”

Data. by Zhipeng Wei (1418458)

“…Utilizing non-parametric estimation techniques in machine learning, particularly the Random Forest and XGBoost algorithms, this study develops predictive models to analyze the impact of 27 influencing factors on behavioral responses following risk perception. …”