Compare NC versus the number of clients using WOA algorithm with different methods. by Le Huu Binh (18340233)

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Compare NC versus the number of clients using MVO algorithm with different methods. by Le Huu Binh (18340233)

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A Genetic Algorithm Approach for Compact Wave Function Representations in Spin-Adapted Bases by Maru Song (22593561)

“…The accurate treatment of many-unpaired-electron systems remains a central challenge in quantum chemistry, due to the exponential growth of the many-electron wave function with the number of correlated electrons. <i>Quantum Anamorphosis</i> addresses this challenge through physically motivated localization of molecular orbitals and site reordering, which yield unique block-diagonal Hamiltonian matrices and compact spin-adapted many-body wave functions. …”

Actual autocorrelation function <i>R</i>_<i>ϵϵ</i>(<i>n</i>, <i>k</i>) and sample autocorrelation function estimated online assuming λ = 0.9998 in the case of non-station... by Martin Dodek (20623832)

Results on solving TSS using different evolutionary and greedy algorithms. by Alexander Andreev (16822333)

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Proportion of simulated data with improved likelihood from using multiple restarts (Algorithm 1). by Jesse Wheeler (18462457)

Comparison of the set found when solving IM for <i>k</i> = 19 by the greedy algorithm (left) and the one found by (1 + 1)-WEA for a network with <i>n</i> = 50 vertices. by Alexander Andreev (16822333)

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Parameters of the genetic algorithm. by Jian Ma (170138)

Adding a new function module. by Yukako Yamane (9034133)

Performance comparison of mainstream algorithms. by Junjie Lu (160350)

“…Finally, the Inner-DIoU loss function is proposed to optimize bounding box regression. …”

CPU runtime of each algorithm: (a) Running Time Comparison of Different Algorithms on F1-F10 and (b) Running Time Comparison of Different Algorithms on F11-F20. by Ruyi Dong (9038174)

Multi-algorithm comparison figure. 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. …”

Longitudinal trajectories of functional network development across the birth transition. by Lanxin Ji (20290942)

“…<p><b> </b> (A) One-sample <i>t</i> test on RSFC across all subjects. …”

F1-Score of different algorithms for TMD on SHL dataset. by Rui Li (4631)

F1-Score of different algorithms for TMD on HTC dataset. by Rui Li (4631)

Data Sheet 1_A novel approach to monitoring rehabilitation progress in atrophic muscle using contactless measurement of free oscillations and advanced modal analysis.pdf by Agnieszka Tomaszewska (2022379)

STD and STD/mean as a function of <i>N</i>_<i>p</i> for distribution of points with added noise. by Luca Maria Del Bono (20479625)

“…<p>STD (a) and STD/mean (b) as a function of <i>N</i>_<i>p</i> for distribution of points with added noise, before and after GD. …”

Recombinant mapping narrows region of interest to identify a loss-of-function allele of <i>mttp.</i> by McKenna Feltes (11242085)

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Image 4_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…Key anoikis-DEGs in UC were identified using three machine learning algorithms, including least absolute shrinkage and selection operator (LASSO) Cox regression, random forest (RF), and support vector machine (SVM). …”

Image 5_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

“…Key anoikis-DEGs in UC were identified using three machine learning algorithms, including least absolute shrinkage and selection operator (LASSO) Cox regression, random forest (RF), and support vector machine (SVM). …”