Boxplot analysis for ITAE objective function using en-CSA, CSA, RUN, PDO and RIME algorithms. by Sarah A. Alzakari (19704611)

The parameters of algorithms. by Le Huu Binh (18340233)

“…However, solving the RNP problem in WMN is difficult because it is NP-hard. As a result, this problem can only be solved using approximate optimization algorithms such as heuristics and meta-heuristics. …”

The algorithm for achieving the research objectives illustrating the process of developing a mathematical model of the braking moment as a function of tire deformation. by Bartosz Wieczorek (8098352)

“…<p>The algorithm for achieving the research objectives illustrating the process of developing a mathematical model of the braking moment as a function of tire deformation.…”

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

Subjects:

Multimodal test functions. by HaoCheng Wang (6089567)

Unimodal test functions. by HaoCheng Wang (6089567)

Parameters of trained algorithms. by Swathi Anil (17382903)

Heat maps of mean scores over 50 datasets of the algorithms as a function of relative noise and number of samples. by Yuanchen Zhao (12905580)

“…<p>Heat maps of mean scores over 50 datasets of the algorithms as a function of relative noise and number of samples.…”

Labyrinthine Microstructures with a High Dipole Moment Boron Complex for Molecular Physically Unclonable Functions by Tevhide Ayça Yıldız (22109101)

“…Here, we report the development of a new high dipole-moment small molecule, InIm-BF₂, a difluoroborate complex of an indolyl-imine ligand, and the fabrication of unique labyrinthine patterns through a facile two-step thin film process under ambient conditions. …”

Efficient Algorithms for GPU Accelerated Evaluation of the DFT Exchange-Correlation Functional by Ryan Stocks (16867476)

“…Kohn–Sham density functional theory (KS-DFT) has become a cornerstone for studying the electronic structure of molecules and materials. …”

Ms.FPOP: A Fast Exact Segmentation Algorithm with a Multiscale Penalty by Arnaud Liehrmann (10970682)

“…This penalty was proposed by Verzelen et al. and achieves optimal rates for changepoint detection and changepoint localization in a non-asymptotic scenario. Our proposed algorithm, Multiscale Functional Pruning Optimal Partitioning (Ms.FPOP), extends functional pruning ideas presented in Rigaill and Maidstone et al. to multiscale penalties. …”

ANOVA tests for Benchmark functions. by Yu Liu (6938)

“…<div><p>The competition of tribes and cooperation of members algorithm (CTCM) is a novel swarm intelligence algorithm, which increases the diversity of the population to a certain extent through tribal competition and member cooperation mechanisms. …”

The Wilcoxon results for Benchmark functions. by Yu Liu (6938)

“…<div><p>The competition of tribes and cooperation of members algorithm (CTCM) is a novel swarm intelligence algorithm, which increases the diversity of the population to a certain extent through tribal competition and member cooperation mechanisms. …”

Convergence graphs of Benchmark functions. by Yu Liu (6938)

“…<div><p>The competition of tribes and cooperation of members algorithm (CTCM) is a novel swarm intelligence algorithm, which increases the diversity of the population to a certain extent through tribal competition and member cooperation mechanisms. …”

Coarse-fine optimization algorithm. by Chao Ma (207385)

“…The improved gradient extraction method combines the Scale Invariant Feature Transformation (SIFT) algorithm to form a new multi-scale image sharpness evaluation function, SIFT Quad-Tenen. …”

Algorithm testing. by Ziad M. Ali (12516532)

“…The solutions are expressed in terms of the Lambert W function and solved using a special transcendental function approach called Special Trans Function Theory (STFT). …”

Algorithm operation steps. by Junyan Wang (4738518)

“…To address these issues, this paper proposes an improved object detection algorithm named SCI-YOLO11, which optimizes the YOLO11 framework from three aspects: feature extraction, attention mechanism, and loss function. …”

Example of a typical workflow to construct a network using NeKo. by Marco Ruscone (11747264)

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

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