Illustration of PyNoetic’s 2D and 3D simulation module with visual feedback. by Gursimran Singh (575288)

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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)

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

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List of Abbreviations by Gursimran Singh (575288)

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PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

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

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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)

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

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

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

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

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

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

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Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

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Factors influencing the discovery of new genetic signatures. by Wei Liu (20030)

The phylogenetic dendrogram of selected sequences of ToLCNDV, TA (A) and TB (B), based on their respective full-length sequences. by Zafar Iqbal (284405)

The relevant code used in this study. by Jiaxin Jiang (10656134)

Comparison between pyAKI’s generated labels and the labels generated by the MIMIC-code implementation of the KDIGO criteria. by Christian Porschen (12967868)

Feature intersection and sequence patterns for <i>S</i>. <i>cerevisiae</i> S site of five fungal species. by Chao Wang (146527)

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Accuracy values of the model constructed with embedded features with different k-mer length and window size. by Chao Wang (146527)

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