Line charts of the elbow method and the k-value selection algorithm: (A) elbow method; (B) k-value selection algorithm. by Jingnan Yan (20727331)

Autonomous Experiments in Scanning Probe Microscopy and Spectroscopy: Choosing Where to Explore Polarization Dynamics in Ferroelectrics by Rama K. Vasudevan (1612174)

Distribution of objective function values solved by three algorithms. by Meilin Zhu (688698)

Algorithm results based on FE simulated likelihood functions. by Nicolas Herzig (9230425)

“…<p>(A) Nodule depth estimation by the algorithm with the likelihood functions obtained by FEM simulation. …”

Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic by NELSON L. DIAS (8078003)

“…With these practical rules, simple summation algorithms provide sufficiently robust results for the calculation of the density function and its definite integrals. …”

Survival outcome missing at random (MAR) and predictors missing completely at random (MCAR): Imputation performance (sensitivity, specificity, percentage correctly classified [PCC]... by Alpha Forna (11436837)

Survival outcome missing not at random (MNAR) and predictors missing completely at random (MCAR): Imputation performance (sensitivity, specificity, percentage correctly classified... by Alpha Forna (11436837)

Flowchart of proposed algorithm. by Tibebu Legesse (21030014)

“…Moreover, the proposed algorithm significantly extends network lifetime, with a <b>3.5%</b> and <b>7.5%</b> improvement over EAPS-AODV and AODV. …”

(a-b) The LASSO algorithm was used for hyperparameter tuning and identification of the important predictive features. by Devi Soorya Narayana Sasikumar (22331743)

Flowchart of DAPF-RRT algorithm. 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. …”

Performance comparison of different algorithms. 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. …”

Schematic diagram of the TEAPS algorithm. by Yoshiaki Kariya (13767985)

Gene function enrichment analysis: GO function enrichment analysis (A) and KEGG pathway enrichment analysis (B). by Yaling Hu (11648397)

Flowchart of the phase optimization algorithm. by Maxim Terekhov (3429614)

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)

<b>The Application of the Optimized Genetic Algorithm in SerDes Circuit Design</b> by Xuan Wei (18564826)

The decomposition diagram of the large kernel convolution, where the blue grid represents the convolution kernel and the green grid represents the center point. by Xunqian Xu (21261899)

Autocorrelation functions <i>C</i>(<i>r</i>, <i>t</i>) as functions of the rescaled distance <i>r</i>/<i>R</i>(<i>t</i>) for several time points, where <i>R</i>(<i>t</i>) is determ... by Marc Durand (556746)

Fig 1 - Fusing multisensory signals across channels and time by Swathi Anil (17382903)

“…In classical multisensory algorithms the information from independent sensory channels (<i>Ch</i>₀, <i>Ch</i>₁) is combined via a linear sum (<b>C</b>) or nonlinear function (<b>D</b>) then summed over time. …”

Fig 2 - Fusing multisensory signals across channels and time by Swathi Anil (17382903)