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

Statistical properties of high-flash-rate (≥500 lightning strokes) grid clusters identified in 2013 within the study region: (A) Spatial distribution of cluster centroids; (B, C) P... by Manxing Shi (22367181)

Image and optimization comparison diagram for the Hartmann 4-D function. by Kuiyuan Pan (21145338)

“…<p>(a) Hartmann 4-D three-dimensional function image. (b) Algorithm convergence curve comparison.…”

Image and optimization comparison diagram for the Schaffer F7 function. by Kuiyuan Pan (21145338)

“…<p>(a) Schaffer F7 three-dimensional function image. (b) Algorithm convergence curve comparison.…”

Reverse engineering information flow using stimulus-encoding and stimulus-transfer estimation algorithms. by Gabriel Matías Lorenz (21094672)

Comparison of optimization performance of six ABC algorithms. by Shuhui Yu (1535500)

Impact of different Copula functions and correlation strengths on optimal order quantities. by Minchao Zheng (20558832)

Analyses of Immune microenvironment and functions between gene clusters by Jiangli Zhao (2308330)

Reflection matrix microscopy data and CLASS algorithms by Sungsam Kang (18931031)

“…<h3><b>Reflection matrix microscopy data and CLASS algorithms</b></h3><p dir="ltr">This software package includes essential algorithms for reflection matrix microscope (RMM) and the CLASS algorithm. …”

Power comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset. by Liyan Sun (760586)

(a): These systems were simulated for (0,3] and (0,3] without the prior knowledge about different phases, and the probability density function of points in feature space illustrate... by Ali Talebi (7164203)

“…<p>The points stretch from the dense region corresponding to the spin glass phase (left top) to the dense region corresponding to the ferromagnetic phase (right bottom), representing the mixed phase region. (b): The dense areas are separated by removing the data less than threshold = 0.5 in the probability density function. …”

Accelerating Fock Build via Hybrid Analytical-Numerical Integration by Yong Zhang (5893)

“…A hybrid analytical-numerical integration scheme is introduced to accelerate the Fock build in self-consistent field (SCF) and time-dependent density functional theory (TDDFT) calculations. To evaluate the Coulomb matrix <b>J</b>[<b>D</b>], the density matrix <b>D</b> is first decomposed into two parts, the superposition of atomic density matrices <b>D</b>_⊕^<i>A</i> and the rest <b>D</b>^<i>R</i> = <b>D</b>–<b>D</b>_⊕^<i>A</i>. …”

Accelerating Fock Build via Hybrid Analytical-Numerical Integration by Yong Zhang (5893)

“…A hybrid analytical-numerical integration scheme is introduced to accelerate the Fock build in self-consistent field (SCF) and time-dependent density functional theory (TDDFT) calculations. To evaluate the Coulomb matrix <b>J</b>[<b>D</b>], the density matrix <b>D</b> is first decomposed into two parts, the superposition of atomic density matrices <b>D</b>_⊕^<i>A</i> and the rest <b>D</b>^<i>R</i> = <b>D</b>–<b>D</b>_⊕^<i>A</i>. …”

Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 by Robert Zomer (12796235)

Execution time comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset. by Liyan Sun (760586)

F-measure comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset. by Liyan Sun (760586)

F-measure comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset. by Liyan Sun (760586)

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

Code For Use in a Bookកូដសម្រាប់ប្រើប្រាស់ក្នុងសៀវភៅ by Sarun Horn (20899271)

Final path. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”