The phase-field function for three different network configurations considered in this work. by Martina Bukač (20161460)

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. …”

Functional Projection <i>K</i>-means by Roberto Rocci (16022201)

“…<p>A new technique for simultaneous clustering and dimensionality reduction of functional data is proposed. …”

Raw results. by Mahmood A. Jumaah (22272371)

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). …”

A typical BCI system depicting the flow and processing of EEG data. by Gursimran Singh (575288)

Subjects:

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. …”

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. …”

Decoding results. by Sam Hall-McMaster (10343795)