Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants حسب Hamad Al Shamsi, Jawaher

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LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications حسب Aldamani, Raghad

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Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers حسب Yousef, Hibba

"…In particular, Isolation Forest (iForest) was applied as an anomaly detection algorithm to address class imbalance. iForest was trained on the control group data to detect cases of high risk for T2DM development as outliers. …"
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Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting حسب Abdelkader Baggag (16864140)

"…The learned factors, with a graph-based temporal dependency, are then used in an autoregressive algorithm to predict the future state of the road network with a large horizon. …"

Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks حسب Sharma, Neetan

"…This paper aims to acknowledge the extended stellar forecasting algorithm using artificial neural network common sensical aspect. …"
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Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) حسب Fares Almomani (12585685)

"…The effect of surface area loading rate (SALR), organic matters (OMs), nutrients (N & P), feed flow rate (Q_feed), hydraulic retention time (HRT), and internal recycle flow (IRF) on the performance of the ENR-BP to fulfil rigorous discharge limitations were evaluated. Experimental data was used to develop the appropriate architecture for the AAN using iterative steps of training and testing. …"

Information warfare. (c2015) حسب Sai, Mohamed El

"…Numerous damage assessment and recovery algorithms have been proposed by researchers. In this work we present an efficient lightweight detection and recovery algorithm that is based on the matrix approach and that can be used to recover from malicious attacks. …"
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Identification of the Uncertainty Structure to Estimate the Acoustic Release of Chemotherapeutics From Polymeric Micelles حسب Wadi, Ali

"…The proposed algorithms are initially deployed in a simulation environment, and then the experimental data sets are fed into the algorithms to validate their performance. …"
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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization حسب Yassine Himeur (14158821)

"…While artificial intelligence (AI) smooths the path of computers to think like humans, machine learning (ML) and deep learning (DL) pave the way more, even by adding training and learning components. DL algorithms require data labeling and high-performance computers to effectively analyze and understand surveillance data recorded from fixed or mobile cameras installed in indoor or outdoor environments. …"

Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) حسب AL SHOUBAKI, HAMZA YOUNIS

"…We also explore a range of algorithms, including traditional classifiers and deep learning models, to determine and select the most suitable and accurate models of identifying poets' names from the verses. …"
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An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure حسب Fahmy, Ahmed

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A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network حسب KHAN, FIROZ

"…The data is finally classified as either ransomware or goodware using the learning methodologies. …"
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Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters حسب Sakib Mahmud (15302404)

"…In this study, we introduce the multimodal feature fusion for non-intrusive occupancy monitoring (MMF-NIOM) framework, which leverages both classical and deep machine learning algorithms to achieve state-of-the-art occupancy detection performance using smart meter data. …"

Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique حسب Iqbal Hassan (22155274)

"…In this study, we harnessed the capabilities of a four-channel, wearable EEG device that captured brain activity data during two distinct CL states: Baseline (representing a non-CL, resting state) and the Stroop Test (a CL-inducing state). …"

Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications حسب Abdallah Falah Mohammad Aldwekat (22457821)

"…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …"

EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach حسب Muhammad Adeel Asghar (6724982)

"…To reduce the feature dimensionality, spatial, and temporal based, bag of deep features (BoDF) model is proposed. A series of vocabularies consisting of 10 cluster centers of each class is calculated using the k-means cluster algorithm. …"

Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features حسب Mariam Bahameish (19255789)

"…However, limited datasets in affective computing and healthcare research can lead to inaccurate conclusions regarding the ML model performance. This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …"

Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test حسب Hasan T. Abbas (8115014)

"…Data generated from an oral glucose tolerance test (OGTT) was used to develop a predictive model based on the support vector machine (SVM). …"

Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information حسب M. Ghoniem, Rania

"…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …"
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Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images حسب Rehan Raza (17019105)

"…The class imbalance issue was handled through multiple data augmentation methods to overcome the biases. …"