Trajectory comparison for system 1: (A) starting point within collection range; (B) starting point outside collection range. حسب Jingnan Yan (20727331)

Trajectory comparison for system 2: (A) starting point within collection range; (B) starting point outside collection range. حسب Jingnan Yan (20727331)

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 finite element analysis coupled with user’s subroutine for changes in bone density. حسب Hassan Mehboob (8960273)

"…<p>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 finite element analysis coupled with user’s subroutine for changes in bone density.…"

The convergence curves of the test functions. حسب Ruiyu Zhan (21602031)

"…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …"

Single-peaked reference functions. حسب Ruiyu Zhan (21602031)

"…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …"

Attack and defense behaviors with the sensory–motor algorithm between a single predator and a single prey. حسب Hiroyuki Ichijo (13891153)

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... حسب Hector Torres (11708207)

In this example the MPC algorithm perfectly tracks the noisy signal , which results in many false spikes. حسب Nicholas A. Rondoni (21573261)

Explained variance ration of the PCA algorithm. حسب Abeer Aljohani (18497914)

"…We developed a mechanism which converts a given medical image to a spectral space which have a base set composed of special functions. …"

Transmission modelling functional block diagram. حسب Alyssa N. Sbarra (18460545)

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

"…The study employed traditional benchmark functions and conducted evaluations versus baselines Standard GEP, NMO-SARA, and MS-GEP-A to assess fitness outcomes, R² values, population diversification, and the avoidance of local optima. …"

Identification and functional analysis of hub genes. حسب Wei Ya Lan (22403712)

"…(C, D) Top 10 hub genes identified using the Maximal Clique Centrality (MCC) algorithm; darker colors indicate higher centrality within the PPI network. …"

Test results of multimodal benchmark functions. حسب Ruiyu Zhan (21602031)

"…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …"

Fixed-dimensional multimodal reference functions. حسب Ruiyu Zhan (21602031)

"…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …"

Test results of multimodal benchmark functions. حسب Ruiyu Zhan (21602031)

"…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …"

Attack and defense behaviors between a single predator and a single prey using the sensory–motor algorithm. حسب Hiroyuki Ichijo (13891153)

Comparison the results with and without Fourier Loss Function for Rain100H. حسب Chaobing Zheng (20896579)

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

"…The study employed traditional benchmark functions and conducted evaluations versus baselines Standard GEP, NMO-SARA, and MS-GEP-A to assess fitness outcomes, R² values, population diversification, and the avoidance of local optima. …"

Comparison between the proposed framework with and without Fourier Loss Function for Rain100H. حسب Chaobing Zheng (20896579)

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