Predicting the Impact of Data Poisoning Attacks in Blockchain-Enabled Supply Chain Networks حسب Javed Butt , Usman

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The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs حسب Muhammad Kashif (3923483)

"…<p dir="ltr">Recent advances in quantum computing and machine learning have brought about a promising intersection of these two fields, leading to the emergence of quantum machine learning (QML). …"

Semi-supervised Clustering of Facial Expressions حسب Jalal, Ahsan

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Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort حسب Sergio Márquez-Sánchez (19437985)

"…In response to these challenges, this article introduces a cutting-edge edge computing architecture grounded in virtual organizations, federated learning, and deep reinforcement learning algorithms, tailored to optimize energy consumption within buildings/homes and facilitate demand response. …"

MSD-NAS: multi-scale dense neural architecture search for real-time pedestrian lane detection حسب Sui Paul Ang (18460605)

"…This paper proposes a novel neural architecture search (NAS) algorithm, named MSD-NAS, to automate this laborious task. …"

Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV حسب Zulkifli, Muhammad

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Utilization of AI to Predict Shear Strength Parameters of Soil Based on Their Physical Properties حسب AbdulGhafour, Husaen

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L₂min^2/2s: Efficient Linear Reconstruction Filter for Incremental Delta-Sigma ADCs حسب Bo Wang (86769)

An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System حسب Alkhatib, Osama

"…Meaning no “perfect” machine learning algorithm that will produce good results at particular problem, in fact for each type of problem a specific algorithm is suited and might achieves good outcome, while another algorithm fails heavily. …"
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Blood-Based Proteomic Profiling Identifies Potential Biomarker Candidates and Pathogenic Pathways in Dementia حسب Hanan Ehtewish (17149825)

"…There was also the dysregulation of 153 plasma proteins in individuals with dementia compared with those with MCI, and machine learning algorithms identified 8 biomarkers that classified dementia from MCI with an AUC of 0.87 ± 0.07. …"

Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine حسب Naila, Rabbani

"…Development of diagnostic algorithms by artificial intelligence machine learning is enhancing the applications of glycation biomarkers. …"
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Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic حسب Hassan Farhat (9000509)

"…</p><h3>Methods</h3><p dir="ltr">Using Python® programming language, this study employed various supervised machine-learning algorithms, including parametric probabilistic models, such as logistic regression, and non-parametric models, including decision trees, random forest (RF), extra trees, AdaBoost, and k-nearest neighbours (KNN), using a dataset of non-transported patients (refused transport and did not receive treatment versus those who refused transport and received treatment) between 2018 and 2022. …"

An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control حسب Mahmoud Dahmani (18810247)

Harnessing Qatar Biobank to understand type 2 diabetes and obesity in adult Qataris from the First Qatar Biobank Project حسب Ehsan Ullah (2698921)

"…</p><h3>Methods</h3><p dir="ltr">In this study we apply a panorama of state-of-the-art statistical methods and machine learning algorithms to investigate associations and risk factors for diabetes and obesity on a sample of 1000 Qatari population.…"

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

"…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …"

Can AI Help in Screening Viral and COVID-19 Pneumonia? حسب Muhammad E. H. Chowdhury (14150526)

"…The aim of this paper is to propose a robust technique for automatic detection of COVID-19 pneumonia from digital chest X-ray images applying pre-trained deep-learning algorithms while maximizing the detection accuracy. …"

DRL-Based UAV Path Planning for Coverage Hole Avoidance: Energy Consumption and Outage Time Minimization Trade-Offs حسب Bahareh Jafari (22501715)

"…As such, in addition to avoiding coverage holes, we should also make the outage time as small as possible. By deploying a deep reinforcement learning algorithm, we find optimal UAV paths based on the two families of trajectories: spiral and oval curves, to tackle different design considerations and constraints, in terms of QoS, energy consumption and coverage hole avoidance. …"

Toward automatic motivator selection for autism behavior intervention therapy حسب Siyam, Nur

"…We use a Q-learning algorithm to solve the modeled problem. …"
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Artificial Intelligence–Driven Serious Games in Health Care: Scoping Review حسب Alaa Abd-alrazaq (17058018)

"…A narrative approach was used for data synthesis.</p><h3>Results</h3><p dir="ltr">The search process returned 1470 records. …"

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

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