MoveSchedule by Zouein, Pierette

“…The resource levels describe different methods or crew-sizes for performing the activity. …”
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Automated systems for diagnosis of dysgraphia in children: a survey and novel framework by Jayakanth Kunhoth (14158908)

“…This work discusses the data collection method, important handwriting features, and machine learning algorithms employed in the literature for the diagnosis of dysgraphia. …”

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…ConclusionWe present the effectiveness of DeepRaman, an innovative architecture inspired by the Progressive Fourier Transform and integrated with the scalogram transformation method, in classifying raw SERS Raman spectral data from biological specimens with unparalleled accuracy relative to conventional machine learning algorithms. …”
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Gene-specific machine learning model to predict the pathogenicity of BRCA2 variants by Mohannad N. Khandakji (13885434)

“…Local, gene-specific information have been shown to aid variant pathogenicity prediction; therefore, our aim was to develop a BRCA2-specific machine learning model to predict pathogenicity of all types of BRCA2 variants.</p><p><br></p><h3>Methods</h3><p dir="ltr">We developed an XGBoost-based machine learning model to predict pathogenicity of BRCA2 variants. …”

Designing Cellular Mobile Networks Using Non{Deterministic Iterative Heuristics by Sait, Sadiq M.

“…Hence, a randomized, heuristic algorithm, such as Simulated Evolution is used in this work to optimize the transmission costs in cellular networks. …”
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Systems biology analysis reveals NFAT5 as a novel biomarker and master regulator of inflammatory breast cancer by Andrea Remo (447375)

“…</p><h3>Methods</h3><p dir="ltr">In-silico modeling and Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) on IBC/non-IBC (nIBC) gene expression data (n = 197) was employed to identify novel master regulators connected to the IBC phenotype. …”

Decision-level Gait Fusion for Human Identification at a Distance by Al-Tayyan, Amer

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The political economy of AI: a content analysis of ChatGPT outputs and anti-Palestinian media bias by King, Gretchen

“…A theoretical framework for analysing digital Orientalism is advanced through a historicisation of media imperialism, the military–industrial–communications complex and the political economy of AI in occupied Palestine. Grounded in research-based teaching methods, and employing a mixed-method content and frequency analysis and comparison of ChatGPT outputs in English and Arabic, this article expands research on AI biases, algorithmic oppression and digital divides within the context of digital Orientalism and anti-Palestinianism. …”
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Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network by Monzure-Khoda Kazi (17191207)

“…These algorithms include random forest (RF) classification and artificial neural networks (ANN). …”

Comparative assessment of fracture risk among osteoporosis and osteopenia patients: a cross-sectional study by Snezana Tomasevic-Todorovic (5782682)

“…The assessment of the fracture risk was executed by applying the Fracture Assessment Risk (FRAX) index (an algorithm developed by the World Health Organization) based on clinical fracture risks or combination of clinical fracture risks and bone mineral density.…”

Current trends and future orientation in diagnosing lung pathologies: A systematic survey by Noorizadeh, Mohammad

“…These VOCs can aid in the diagnosis of lung pathologies such as pneumonia. The CV processing method involves the application of advanced imaging techniques and machine learning algorithms to scrutinize and diagnose lung pathologies and ventilator-associated pneumonia (VAP). …”
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Decision-level fusion for single-view gait recognition with various carrying and clothing conditions by Al-Tayyan, Amer

“…Gait samples are fed into the MPCA and MPCALDA algorithms using a novel tensor-based form of the gait images. …”
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Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach by Mohammad Taghi Dabiri (16904658)

“…Then, using geometrical analysis and deep reinforcement learning (RL) method, we propose several algorithms to find the optimal trajectory and select an optimal pattern during the trajectory. …”

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network by Sakib Mahmud (15302404)

“…Leave-one-out cross-validation method was used in this work. The performance of the deep learning models is measured using three well-known performance matrices viz. mean absolute error (MAE)-based construction error, the difference in the signal-to-noise ratio (ΔSNR), and percentage reduction in motion artifacts (<i>η</i>). …”

Face Flow: Constrained Optical Flow Framework for Faces by Alkaddour, Muhannad

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Modelling of pollutant transport in compound open channels by Chatila, Jean Georges

“…Different statistical methods were considered in evaluating the simulated results.…”
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Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters by Sakib Mahmud (15302404)

“…We combine features from all three modes of MMF-NIOM to achieve a state-of-the-art non-intrusive occupancy classification performance of 91.5 % accuracy and 91.5 % f1-score, approximately, by an ensemble of fine-tuned classifiers on the electricity consumption & occupancy (ECO) dataset. The proposed method is sustainable, robust, adaptable to various households, and can be mass-implemented within smart meters at a much lower cost and effort compared to the traditional internet of things (IoT)-based intrusive systems.…”

Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis by Hassan, Ali

“…We thus propose Con-Detect—a Contribution based Detection method—for detecting adversarial attacks against NLP classifiers. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

“…We thus propose Con-Detect—a Contribution based Detection method—for detecting adversarial attacks against NLP classifiers. …”

Deep and transfer learning for building occupancy detection: A review and comparative analysis by Aya Nabil Sayed (17317006)

“…Moreover, the paper conducted a comparative study of the readily available algorithms for occupancy detection to determine the optimal method in regards to training time and testing accuracy. …”