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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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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Graphs of the regularization terms. by Tomokaze Shiratori (9635271)

“…Specifically, we convert the cardinality constraint into an equivalent constraint based on the largest-<i>K</i> norm, and reformulate the resultant constrained optimization problem into an unconstrained penalty form with a DC (difference of convex functions) representation. To solve this problem efficiently, we design a DC algorithm in which the graphical lasso algorithm is repeatedly executed to solve convex optimization subproblems. …”

Algorithm operation steps. by Junyan Wang (4738518)

“…To address these issues, this paper proposes an improved object detection algorithm named SCI-YOLO11, which optimizes the YOLO11 framework from three aspects: feature extraction, attention mechanism, and loss function. …”

Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]. (b) An alternating active-phase... by Zhao Li (300229)

Performance comparison of mainstream algorithms. by Junjie Lu (160350)

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Schematic diagram of the experimental algorithm. by Ronghua Meng (20978441)

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Overview of the wavess algorithm and R package. by Narmada Sambaturu (4989539)

Experimental results of cantilever beam design. by Qingwen Meng (156386)

“…This mechanism ensures that individuals that fail to update have a certain probability of being retained in the next generation population, while guaranteeing that the current global optimal solution remains unchanged, thereby accelerating the algorithm’s convergence. The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). …”

Details of the metaheuristic algorithms. by Yanzhao Gu (21192659)

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Synthetic Realness: Authenticity as Algorithm (Reality Drift Working Paper Series, 2025) by Reality Drift Working Papers Series 2020-2025 (22445446)

“…While deepfakes destabilized trust in representation, synthetic realness normalizes a world in which digital entities and curated personas are experienced as authentic by design.</p><p dir="ltr">The analysis situates this concept within the Reality Drift Working Papers (2020–2025), tracing how performative selfhood, emotional plausibility, and algorithmic curation reshape culture, identity, and trust. …”

Experimental results of three-bar truss design. by Qingwen Meng (156386)

“…This mechanism ensures that individuals that fail to update have a certain probability of being retained in the next generation population, while guaranteeing that the current global optimal solution remains unchanged, thereby accelerating the algorithm’s convergence. The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). …”

Experimental results of tension/compression spring design. by Qingwen Meng (156386)

Comparison of image clarity results of product appearance design using different methods. by Cheng-jie Chen (22272090)

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Analysis of ABIDE dataset: Conventional regression frameworks for optimized algorithmic value. by Alexandria M. Jensen (6494957)

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Standard benchmark functions. by Yanzhao Gu (21192659)

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Comparison of algorithms across metrics in test problems. by Jihui Hu (19812736)

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