Device parameter list. by Dawei Wang (471687)

“…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”

The process of IHWGWO. by Dawei Wang (471687)

“…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”

The computational results of the case. by Dawei Wang (471687)

“…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”

Working time of different processes (<i>h</i>). by Dawei Wang (471687)

“…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”

Effect of segmentation mask resolution on CUDA memory usage and performance metrics. (A) Memory usage as a function of queries when Cell-TRACTR produces a segmentation mask with th... by Owen M. O’Connor (11965460)

Fitness comparison on test function. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]. (b) An alternating active-phase... by Zhao Li (300229)

Enhanced USV path planning through integrated Bi-RRT and DWA algorithms considering environmental factors by Yanghua Zhou (20449441)

“…Furthermore, the evaluation function of the DWA algorithm undergoes enhancements, incorporating elements from heuristic functions within the A* algorithm and radar-based assessment of search range. …”

A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finit... by Hassan Mehboob (8960273)

R-squared comparison of test function. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Example of how the Resnet34UNet model functions. by Henrik Mustonen (20378529)

Scatter plots of PATH⁺ and our implementation of TNet-BP’s predictions on a held-out, test subset of PDBBind v2020 refined set for one run (90:10 train:test split ratio,... by Yuxi Long (11024307)

Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

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Multimodal reference functions. by Ruiyu Zhan (21602031)

“…-led initiative conducting in-depth molecular research to elucidate the causative mechanisms of cancer — this study focuses on three specific cancer types within the dataset: lung, breast, and esophageal cancers. …”

The 3Mont summary statistics for the top 10 most significant pro-groups that are identified for BRCA molecular subtypes (HR+ and HR-) dataset. These statistics include Frequency of... by Miray Unlu Yazici (14792680)

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Distribution of pro-group sizes before and after selecting the top 10 features. by Miray Unlu Yazici (14792680)

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Internal cross-validation step of S component in 3Mont. by Miray Unlu Yazici (14792680)

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Workflow of 3Mont. by Miray Unlu Yazici (14792680)

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Performance evaluation metrics of 3Mont across different cancer types. The total sample size column lists the numbers of the tumor and control samples, respectively. A 1:1 sampling... by Miray Unlu Yazici (14792680)

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Generated network illustrating the pro-groups and their associated features that are identified by 3Mont for differentiating among the BRCA molecular subtypes (HR by Miray Unlu Yazici (14792680)

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