Comparative assessment of fracture risk among osteoporosis and osteopenia patients: a cross-sectional study حسب 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 حسب 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 حسب 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 حسب 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 حسب 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 حسب Alkaddour, Muhannad

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Modelling of pollutant transport in compound open channels حسب 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 حسب 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 حسب 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 حسب 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 حسب 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. …"

ECG Signal Reconstruction on the IoT-Gateway and Efficacy of Compressive Sensing Under Real-Time Constraints حسب Mohammed Al Disi (16855407)

"…Compressive sensing (CS) has been explored as a method to extend the battery lifetime of medical wearable devices. …"

Resilience analytics: coverage and robustness in multi-modal transportation networks حسب Abdelkader Baggag (14153040)

"…However solutions are usually based on eigenvalue decomposition, known to be time consuming and hard to obtain in the case of large systems. In this work, we propose MUME, an efficient algorithm for Multi-modal Urban Mobility Estimation, that takes advantage of the special structure of the supra-Laplacian matrix of the transportation multiplex, to compute the coverage of the system. …"

Heuristics. (c2006) حسب Kallab, Chadi

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Artificial Intelligence for Skin Cancer Detection: Scoping Review حسب Abdulrahman Takiddin (14153181)

"…Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.…"

Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images حسب Rehan Raza (17019105)

"…Considering these shortcomings, computational methods especially machine learning and deep learning algorithms are leveraged as an alternative to accelerate the accurate detection of CT scans as cancerous, and non-cancerous. …"

Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review حسب Mohamed Massaoudi (16888710)

"…This review article taxonomically dives into the nitty-gritty of the mainstream DL-based PVPF methods while showcasing their strengths and weaknesses. …"

Crown Structures for Vertex Cover Kernelization حسب Abu-Khzam, Faisal N.

"…Crown structures in a graph are defined and shown to be useful in kernelization algorithms for the classic vertex cover problem. Two vertex cover kernelization methods are discussed. …"
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Identification of phantom movements with an ensemble learning approach حسب Akhan Akbulut (17380285)

"…The ensemble learning-based approaches outperformed the SVM, Decision tree, and kNN methods. …"

The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review حسب Zainab Jan (17306614)

"…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …"