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

Convergence curve of the DBO algorithm. by Ma Haohao (22177538)

“…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …”

Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). by Johannes Weyer (13392175)

Comparison of results based on CycleGAN method. by Xiaojun Wang (50332)

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Scatter diagram of different principal elements. by Jizhong Wang (7441697)

“…Finally, a transformer diagnostic model based on SSA-LightGBM was constructed, and the ten fold cross validation method was used to verify the classification ability of the model. …”

Numbers of iterations (#Ite) and eigenvalue calculations (#Eig) in the DC algorithm on the random and chain graph datasets. by Tomokaze Shiratori (9635271)

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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)

Element model generation method with geometric distribution errors by Yiqi Liu (21357815)

“…The product surface geometric distribution error is directly attached to the element nodes of the product ideal element model using the error surface reconstruction method and the replacement algorithm of the element node vector height based on the product’s point cloud data. …”

Model-Based Clustering of Categorical Data Based on the Hamming Distance by Raffaele Argiento (647076)

“…<p>A model-based approach is developed for clustering categorical data with no natural ordering. …”

The method for determining the chemical constituents of unknown materials in the algorithm. by Dong Hyeok Choi (12562048)

Computation time as a function of the sample size on the chain graph dataset. by Tomokaze Shiratori (9635271)

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Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

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Computation time as a function of the sample size on the random graph dataset. by Tomokaze Shiratori (9635271)

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F1 score of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

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Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

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Examples of ground-truth graph structures with (<i>p</i>, <i>n</i>_≠0) = (10, 10). by Tomokaze Shiratori (9635271)

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Number of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

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Number of edges selected through cross-validation on the random graph dataset. by Tomokaze Shiratori (9635271)

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Graphs of the regularization terms. by Tomokaze Shiratori (9635271)

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F1 score of a given number of selected edges on the chain graph dataset. by Tomokaze Shiratori (9635271)

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