Sensitivity analysis of the TV-BayesOpt algorithm with a forgetting (orange line) or a forgetting-periodic (blue line) covariance function for a range of ε values. by John E. Fleming (8533956)

“…<p>Incorporation of prior knowledge of the temporal variation in the objective function optimum value (blue line) resulted in improved TV-BayesOpt algorithm performance than implementing a forgetting covariance function (orange line) alone. …”

Table_2_Optimizing functional near-infrared spectroscopy (fNIRS) channels for schizophrenic identification during a verbal fluency task using metaheuristic algorithms.XLSX by Dong Xia (54339)

“…Three features frequently used in the analysis of fNIRS signals, namely time average, functional connectivity, and wavelet, were extracted and optimized using various metaheuristic operators, i.e., genetic algorithm (GA), particle swarm optimization (PSO), and their parallel and serial hybrid algorithms. …”

Table_1_Optimizing functional near-infrared spectroscopy (fNIRS) channels for schizophrenic identification during a verbal fluency task using metaheuristic algorithms.XLSX by Dong Xia (54339)

“…Three features frequently used in the analysis of fNIRS signals, namely time average, functional connectivity, and wavelet, were extracted and optimized using various metaheuristic operators, i.e., genetic algorithm (GA), particle swarm optimization (PSO), and their parallel and serial hybrid algorithms. …”

Data_Sheet_1_Classifying 3-D Models of Coral Reefs Using Structure-From-Motion and Multi-View Semantic Segmentation.docx by Jordan Pierce (11622679)

“…<p>Benthic quadrat surveys using 2-D images are one of the most common methods of quantifying the composition of coral reef communities, but they and other methods fail to assess changes in species composition as a 3-dimensional system, arguably one of the most important attributes in foundational systems. Structure-from-motion (SfM) algorithms that utilize images collected from various viewpoints to form an accurate 3-D model have become more common among ecologists in recent years. …”

List of Arabidopsis thaliana, Fagopyrum esculentum and Zea mays RNA-seq samples from transcriptome maps. by Artem S. Kasianov (8783363)

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

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

DataSheet1_Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images.PDF by Niccolò Marini (11247936)

“…<p>Algorithms proposed in computational pathology can allow to automatically analyze digitized tissue samples of histopathological images to help diagnosing diseases. …”

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.…”

Spatial properties of RFs generated by thresholding algorithms and in macaques’ V1 and V2. by Ilias Rentzeperis (10215602)

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

Highest 18 BacSD rankings as a function of detection probability using simulated data with a clutter mean of 8. by Tom Northardt (17817484)

GLAST-Cre⁺ cells from the GER mitotically regenerate IPhCs. by Tomokatsu Udagawa (11675636)

Sparkler plot representation of functional impact of ARAF variants. by Alexis M. Thornton (11068403)

Application of the algorithm to unseen data. Presynaptic neurons labelled by rabies viral injection into layer 2/3 primary visual cortex in Penk-Cre mice. by Adam L. Tyson (10892822)

Modelling the impact of agrometeorological variables on regional tea yield variability in South Indian tea-growing regions: 1981-2015 by Esack Edwin Raj (6517805)

DataSheet_1_Alteration and clinical potential in gut microbiota in patients with cerebral small vessel disease.docx by Yachen Shi (6835871)

“…Additionally, a composite biomarker depending on six gut microbiota at the genus level displayed an area under the curve of 0.834 to distinguish CSVD patients from HCs using the least absolute shrinkage and selection operator (LASSO) algorithm.…”

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

Post-stroke change in modularity for different clustering algorithms, numbers of clusters and edge density threshold ranges. by Francisco Páscoa dos Santos (16510676)