Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

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

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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Algorithm for the proposed work. by Shuvo Biswas (21728782)

“…To ensure model interpretability, an XAI-based algorithm named Local Interpretable Model-Agnostic Explanations (LIME) was used to explain the predictions of the proposed framework. …”

Binary form of Table 1. by Muhammad Waqar (500788)

“…The proposed work experiments eight state-of-the-art biclustering algorithms to identify the appropriate biclustering algorithm for the given recommendation task. …”

Results of VGG16 algorithm using FedProx-based FL approach on ISIB2017 dataset. (Top results are highlighted in bold.). by Shuvo Biswas (21728782)

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

“…<div><p>A fault diagnosis method for oil immersed transformers based on principal component analysis and SSA LightGBM is proposed to address the problem of low diagnostic accuracy caused by the complexity of current oil immersed transformer faults. Firstly, data on dissolved gases in oil is collected, and a 17 dimensional fault feature matrix is constructed using the uncoded ratio method. …”

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

The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Example measurement and analysis units for landscape elements. by Jaewon Han (8660295)

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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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