Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

Subjects:

Mean and covariance estimation of functional data streams by Mingxue Quan (13282368)

The algorithm for the same-day surgery protocol. by Magnus Tveit (11442200)

Summary of results of naïve Bayes algorithms. by Christopher E. Niemczak (8586861)

“…Algorithms trained without auditory variables as features were statistically worse (p < .001) in both the primary measure of area under the curve (0.82/0.78) and the secondary measure of accuracy (72.3%/74.5%) for the Gaussian and kernel algorithms respectively.…”

(a) The volcano plot of GSE89408, where the red scatter represents the upregulated genes and the blue scatter represents the downregulated genes. (b) The heatmap of GSE89408. by Devi Soorya Narayana Sasikumar (22331743)

Experiment 2D and 5D: Progressive Sample Scaling Algorithm To Solve Many-Affine BBOB Functions. by Boris Almonacid (4110337)

“…</p><p dir="ltr">[2] GECCO 2024 Competition: Anytime Algorithms for Many-affine BBOB Functions <a href="https://markdownlivepreview.com/#cite_ref-2" target="_blank">https://gecco-2024.sigevo.org/Competitions#id_Anytime Algorithms for Many-affine BBOB Functions</a>.…”

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... by Hector Torres (11708207)

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

Subjects:

Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

Similarity between the hierarchical community structure of structural and functional brain graphs. by Arian Ashourvan (6685232)

If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

“…Both versions are evaluated on the same synthetic datasets with a 3-group ground truth. Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …”

Payoff spaces under <i>D</i>_<i>i</i> combinations where behavioral switching occurred and under all other <i>D</i>_<i>i</i> combinations of non-behavioral swit... by Hiroyuki Ichijo (13891153)

Fitness curves of the 6 test functions. by Peiwen Zhang (1863202)

Multi-scale detection of hierarchical community architecture in structural and functional brain networks by Arian Ashourvan (6685232)

“…Finally, we build an explicitly multimodal multiplex graph that combines both structural and functional connectivity in a single model, and we identify the topological scales where resting state functional connectivity and underlying structural connectivity show similar <i>versus</i> unique hierarchical community architecture. …”

Parameter selection for mixture of different cluster sizes. by Daniel F. Nino (9745709)

FOCAL3D performance for clusters of mean radius R_c = 80 nm, 60 nm and 40 nm at a noise level of <i>ζ</i> = 0.01. by Daniel F. Nino (9745709)

Computing the objective function. by Xiaochen He (455300)

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

“…<div><p>Chest X-ray image classification plays an important role in medical diagnostics. Machine learning algorithms enhanced the performance of these classification algorithms by introducing advance techniques. …”

Main parameters of braking system. by Honglei Pang (22693724)

Subjects:

Simulation Results Plot of the SBW System Response: (a) Step response curve of the SBW system; (b) Sine response curve of the SBW system; (c) Steady state error curve of the SBW sy... by Honglei Pang (22693724)

Subjects: