Time-domain and frequency-domain waveform diagrams of AE signals collected from undamaged areas. by Li Jiaqing (21212614)

<b>Algorithm Pseudocode</b> by Yibin Zhao (22425801)

Degree 5 algorithm from Recovering the cluster picture of a polynomial over a discretely valued field by Lilybelle Cowland Kellock (20938306)

Risk Groups Immune Infiltration Analysis by ssGSEA Algorithm. by Yongling Wang (13261656)

R-squared comparison of test function. by Kejia Liu (5699651)

“…Its restrictions block GEP from successfully handling high-dimensional along with complex optimization problems. …”

Trainable parameters for different algorithms. by Anwar Hossain Efat (19942283)

Diagram of the proposed solution algorithm. by Vytautas Abromavičius (22008573)

Elementary effects (EE) results for the generation of villous vessels within a placentone employing the input parameter ranges from Table 1. by Diana C. de Oliveira (9220729)

Baseline data from participants referred to the gastroenterology service. by John N. Staffurth (20636565)

Comparative Analysis (Security Functionalities). by Naif Alzahrani (19992885)

Machine learning analysis of 10 hub genes related to SCI was performed using eight algorithms applied to the dataset. by Tianbao Feng (21722233)

A. Top – 14 days of continuous glucose monitor (CGM) data for a patient that spends all of their time within an optimal glucose range. by Jamison H. Burks (21029607)

Metapopulation model notation. by Jeffrey Keithley (14626551)

“…The submodularity ratio of a function is a measure of how distant <i>g</i> is from being submodular; here submodularity refers to the very useful “diminishing returns” property of set and lattice functions, i.e., the property that as the function inputs are increased the function value increases, but not by as much.…”

Estimates of for each problem instance. by Jeffrey Keithley (14626551)

“…The submodularity ratio of a function is a measure of how distant <i>g</i> is from being submodular; here submodularity refers to the very useful “diminishing returns” property of set and lattice functions, i.e., the property that as the function inputs are increased the function value increases, but not by as much.…”

Approximation factors for each problem instance. by Jeffrey Keithley (14626551)

“…The submodularity ratio of a function is a measure of how distant <i>g</i> is from being submodular; here submodularity refers to the very useful “diminishing returns” property of set and lattice functions, i.e., the property that as the function inputs are increased the function value increases, but not by as much.…”

MODeM 2023 TC NC-A by Anonymized (8222226)

Median fiber cleavage time (black) and the fraction of successful runs (red) for different parameter values. by Roukayatou R. Ouedraogo (20460980)

Attack and defense behaviors with the sensory–motor algorithm between multiple predators and prey. by Hiroyuki Ichijo (13891153)

The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…<div><p>In this paper, we study a class of non-parametric regression models for predicting graph signals as a function of explanatory variables . Recently, Kernel Graph Regression (KGR) and Gaussian Processes over Graph (GPoG) have emerged as promising techniques for this task. …”

Flowchart of simple ant colony algorithm. by Yang Yu (4292)

“…Simulation results from an actual power business communication network demonstrate that the algorithm outputs the main and alternate paths with the lowest risk costs. …”