Classification performances of Ensemble (Subspace KNN), SVM, and KNN algorithms when trained with time domain HbO features. by Ayşenur Eser (21713911)

Labyrinthine Microstructures with a High Dipole Moment Boron Complex for Molecular Physically Unclonable Functions by Tevhide Ayça Yıldız (22109101)

“…The design and development of novel <i>molecular</i>-physically unclonable functions (PUFs) with advanced encoding characteristics and ease of fabrication have recently attracted attention in cryptography, secure authentication, and anticounterfeiting. …”

Flowchart of improved FOX optimization algorithm. by Mahmood A. Jumaah (22272371)

“…Additionally, it achieved 880 wins, 228 ties, and 348 losses against 16 optimization algorithms across all involved functions and problems. …”

Results of power spectral density simulated by the Gillespie algorithm compared to that predicted by the Markov model for [Ru(bpy)₃]Br₂ fluorophores (N = 100)... by Nicholas H. Vitale (20469289)

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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. …”

Impact of POMCP parameters on the estimated value function. by Benoîte de Saporta (20454662)

Data Sheet 1_Simplified two-compartment neuron with calcium dynamics capturing brain-state specific apical-amplification, -isolation and -drive.pdf by Elena Pastorelli (7024235)

“…This work provides the computational community with a two-compartment spiking neuron model that supports the proposed forms of brain-state-specific activity. A machine learning evolutionary algorithm, guided by a set of fitness functions, selected parameters defining neurons that express the desired apical dendritic mechanisms. …”

Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. by Borjan Milinkovic (21349908)

Python code for a rule-based NLP model for mapping circular economy indicators to SDGs by Zahir Barahmand (18008947)

“…The package includes:</p><ul><li>The complete Python codebase implementing the classification algorithm</li><li>A detailed manual outlining model features, requirements, and usage instructions</li><li>Sample input CSV files and corresponding processed output files to demonstrate functionality</li><li>Keyword dictionaries for all 17 SDGs, distinguishing strong and weak matches</li></ul><p dir="ltr">These materials enable full reproducibility of the study, facilitate adaptation for related research, and offer transparency in the methodological framework.…”

Multimodal reference functions. by Ruiyu Zhan (21602031)

“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”

Flawless analysis framework overview, with application to EEG power spectral densities as functional data observed over time. by Owen Forbes (4530652)

Test function description table. by Zhihao Li (359073)

Boxplot of en-CSA compared to CSA, CGO, HHO, SSA, GTO, WOA, PSO, and TSA using benchmark functions. by Sarah A. Alzakari (19704611)

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Convergence of en-CSA compared to CSA, CGO, HHO, SSA, GTO, WOA, PSO, and TSA using benchmark functions. by Sarah A. Alzakari (19704611)

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Predicted SNR normalized to the acquisition time of 1s versus input excitation power for CW and TG systems. by Nicholas H. Vitale (20469289)

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Closed-form formulations for signal-to-noise ratios. by Nicholas H. Vitale (20469289)

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Simulation specifications for figure. by Nicholas H. Vitale (20469289)

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Expected behavior system of ODEs. by Nicholas H. Vitale (20469289)

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The impact of extrinsic noise sources on the measured SNR is plotted for both CW and TG against varying optical filter magnitudes. by Nicholas H. Vitale (20469289)

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Plot of the predicted power spectral density of fluorescence for an arbitrary fluorophore. by Nicholas H. Vitale (20469289)

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