a) Representation of the deployed porous media submitted to an incident isotropic distribution function <i>f</i>_<i>i</i> with gaussian spatial profile at the inlet face. by Loris Ibarrart (15195203)

A Wavelet Lifting Approach for Representing and Denoising Functions on Network Edges by Dingjia Cao (22411671)

Frequency response of a hypothetical indicator. by Nicholas A. Rondoni (21573261)

ddPCR mtDNA amplicon concentration as a function of distance. by Patrick Kurtz (21772385)

Convergence curves on the functions C19F2, C19F3, C19F5, C19F6, C19F10, C21F2, C21F3, C21F9, and C21F10. by Mahmood A. Jumaah (22272371)

Convergence curves on the functions C17F5, C17F7, C17F8, C17F9, C17F11, C17F19, C17F20, C17F22, and C17F27. by Mahmood A. Jumaah (22272371)

The structure of a pressure vessel. by Yanzhao Gu (21192659)

“…The experimental results showed that GWOA achieved better convergence speed and solution accuracy than other algorithms in most test functions, especially in multimodal and compositional optimization problems, with an Overall Efficiency (OE) value of 74.46%. …”

The structure of a speed reducer. by Yanzhao Gu (21192659)

“…The experimental results showed that GWOA achieved better convergence speed and solution accuracy than other algorithms in most test functions, especially in multimodal and compositional optimization problems, with an Overall Efficiency (OE) value of 74.46%. …”

The structure of a piston lever. by Yanzhao Gu (21192659)

“…The experimental results showed that GWOA achieved better convergence speed and solution accuracy than other algorithms in most test functions, especially in multimodal and compositional optimization problems, with an Overall Efficiency (OE) value of 74.46%. …”

Different mathematical formalization of model fairness. TPR: True Positive Rate; FPR: False Positive Rate; FNR: False Negative Rate; TNR: True Negative Rate; PPV: Positive Predicti... by Marine Hoche (20896647)

The parameters of simulation scenarios. 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. …”

S1 Dataset - 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. …”

Validation of IDRAS on a model of bacterial growth and division. by Ron Teichner (21492434)

Distribution of dominant plant functional types (PFTs): CARAIB LIG (A), CARAIB 8700–8200 BP (B); REVEALS mesocratic I (C), REVEALS 8700–8200 BP. by Anastasia Nikulina (22477710)

Bootstrap results (N = 368). by Linsha Liu (20378293)

“…Since the inherent flaws of virtual social networking cannot be eliminated solely through algorithm matching, a potential solution is to introduce more offline to online social functions for strangers. …”

Analysis of confirmatory factors (N = 368). by Linsha Liu (20378293)

“…Since the inherent flaws of virtual social networking cannot be eliminated solely through algorithm matching, a potential solution is to introduce more offline to online social functions for strangers. …”

The relevant data file for this article. by Linsha Liu (20378293)

“…Since the inherent flaws of virtual social networking cannot be eliminated solely through algorithm matching, a potential solution is to introduce more offline to online social functions for strangers. …”

Results of common fit indexes for SEM (N = 368). by Linsha Liu (20378293)

“…Since the inherent flaws of virtual social networking cannot be eliminated solely through algorithm matching, a potential solution is to introduce more offline to online social functions for strangers. …”

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. …”

Expansion procedure. 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. …”