PyNoetic’s feature extraction module that supports time domain features, frequency domain features, time-frequency domain features, spatial features as well as Brain Connectivity m... by Gursimran Singh (575288)

Subjects:

Pseudo live-stream of EEG data is generated, and a simple pick-and-place flowchart is designed for channel selection and filtering. by Gursimran Singh (575288)

Subjects:

List of Abbreviations by Gursimran Singh (575288)

Subjects:

PyNoetic’s stimuli generation and recording module, which supports both ERP and SSVEP. by Gursimran Singh (575288)

Subjects:

PyNoetic’s channel selection module, which supports various channel selection criteria including CSP, correlation, Mutual Information, and Chi-squared. by Gursimran Singh (575288)

Subjects:

Tunable parameters in stimuli generation module. ^<i>a</i>The fixation cross is displayed once before an experiment starts to help subjects concentrate. <sup><i>b</i></su... by Gursimran Singh (575288)

Subjects:

The results of ICA performed using PyNoetic. by Gursimran Singh (575288)

Subjects:

PyNoetic’s pre-processing module, which supports filtering and artifact removal, including ICA. by Gursimran Singh (575288)

Subjects:

Performance of various deep learning models from PyNoetic’s classification module on the Motor Imagery decoding task. by Gursimran Singh (575288)

Subjects:

Illustration of recording paradigm with PyNoetic’s Stimuli generation and recording module. by Gursimran Singh (575288)

Subjects:

A typical BCI system depicting the flow and processing of EEG data. by Gursimran Singh (575288)

Subjects:

Contrast enhancement of digital images using dragonfly algorithm by Soumyajit Saha (19726163)

“…Comparisons with state-of-art methods ensure the superiority of the proposed algorithm. The Python implementation of the proposed approach is available in this <a href="https://github.com/somnath796/DA_contrast_enhancement" target="_blank">Github repository</a>.…”

Effects of Nash equilibrium attack and defense behaviors with the sensory–motor algorithm on encounters, agent numbers, and payoffs. by Hiroyuki Ichijo (13891153)

Attack and defense behaviors with the sensory–motor algorithm between a single predator and a single prey. by Hiroyuki Ichijo (13891153)

Variants of weighted methods. by Limin Ma (556873)

“…At this point, considering the weights as the probabilities of the contributions of different attributes to the model can enhance the interpretation ability of the algorithm. Specifically, we add an entropy regularization term to the objective function of the problem model and then use the Lagrange multiplier method to solve the weights. …”

Attack and defense behaviors between a single predator and a single prey using the sensory–motor algorithm. by Hiroyuki Ichijo (13891153)

GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios by Yang Lan (20927512)

“…Using occurrence data and environmental variable, we employ the Maximum Entropy (MaxEnt) algorithm within the species distribution modeling (SDM) framework to estimate occurrence probability at a spatial resolution of 1/12° (~10 km). …”

Accelerated MPC Algorithms and Augmented System Design for Legged Robots by John Ndegwa Nganga (21088838)

“…The approach is powered by a newly introduced algorithm, named the modified Recursive Newton Euler Algorithm~(mRNEA), which is inspired by classical RNEA, and computes the dynamics information pre-multiplied with a fixed vector. …”

Generated blended data using mouse brain cells and human embryonic heart cells, labeled as <i>Mix</i>[<i>a</i>,<i>b</i>,<i>c</i>], indicates the proportion of mouse brain cells fou... by Nuray Sogunmez Erdogan (21533872)

Example of a typical workflow to construct a network using NeKo. by Marco Ruscone (11747264)