Ensemble Deep Random Vector Functional Link Neural Network for Regression حسب Minghui Hu (2457952)

"…<p dir="ltr">Inspired by the ensemble strategy of machine learning, deep random vector functional link (dRVFL), and ensemble dRVFL (edRVFL) has shown state-of-the-art results on different datasets. …"

An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization حسب Majdi Mansouri (16869885)

Artificial intelligence models for predicting the mode of delivery in maternal care حسب Rawan AlSaad (14159019)

"…</p><h3>Objectives</h3><p dir="ltr">This study aims to evaluate and compare the predictive accuracy of AI algorithms in predicting the mode of delivery (vaginal or cesarean) using routinely collected antepartum data from electronic health records (EHRs). …"

Framework for rapid design and optimisation of immersive battery cooling system حسب Ali Almshahy (23544823)

Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose حسب Atiq Ur Rehman (8843024)

"…These electronic instruments rely on Machine Learning (ML) algorithms for recognizing the sensed odors. …"

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. …"

Design and analysis of entropy-constrained reflected residual vector quantization حسب Mousa, W.A.H.

"…Residual vector quantization (RVQ) is a vector quantization (VQ) paradigm which imposes structural constraints on the encoder in order to reduce the encoding search burden and memory storage requirements of an unconstrained VQ. …"
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The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review حسب Uzair Shah (15740699)

"…We categorized the studies based on AI techniques, such as machine learning and deep learning. The most prominent ML algorithm was a support vector machine, and the DL algorithm was a convolutional neural network. …"

Neural network-based failure rate prediction for De Havilland Dash-8 tires حسب Al-Garni, Ahmed Z.

"…An artificial neural network (ANN) model for predicting the failure rate of De Havilland Dash-8 airplane tires utilizing the twolayered feed-forward back-propagation algorithm as a learning rule is developed. The inputs to the neural network are independent variables and the output is the failure rate of the tires. …"
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Failure-Rate Prediction for De Havilland Dash-8 Tires Employing Neural-Network Technique حسب Al-Garni, Ahmed Z.

"…An artificial neural-network model for predicting the failure rate of De Havilland Dash-8 airplane tires utilizing the two-layered feedforward back-propagation algorithm as a learning rule is developed. The inputs to the neural network are independent variables, and the output is the failure rate of the tires. …"
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Efficient Seismic Volume Compression using the Lifting Scheme حسب Khene, M. F.

"…In addition, the lifting scheme offers: 1) a dramatic reduction of the required auxiliary memory, 2) an efficient combination with parallel rendering algorithms to perform arbitrary surface and volume rendering for interactive visualization, and 3) an easy integration in the parallel I/O seismic data loading routines. …"
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Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials حسب Ghouti, Lahouari

"…The proposed techniques are: i) a batch-type deconvolution method using the complex bicepstrum algorithm, and ii) automatic ultrasonic defect classification system using a modular learning strategy. …"
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A multi-pretraining U-Net architecture for semantic segmentation حسب Cagla Copurkaya (22502042)

"…In this research, we propose and evaluate a modified version of a deep learning algorithm called U-Net architecture for partitioning histopathological images. …"

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

"…In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …"
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Estimating Bridge Deterioration Age Using Artificial Neural Networks حسب AL HUSSEIN, ASEEL

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Investigation of Forming a Framework to shortlist contractors in the tendering phase حسب DABASH, MOHANNAD SALAH

"…After obtaining the weights of the decision factors, a model using Machine Learning algorithm on Google Colab was written using the Python language. …"
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Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO حسب Majedeh Gheytanzadeh (17541927)

"…Accordingly, a dataset containg 258 data points was extracted from the DFT method to use in machine learning method. …"

Predicting COVID-19 cases using bidirectional LSTM on multivariate time series حسب Ahmed Ben Said (14158926)

"…Unlike other forecasting techniques, our proposed approach first groups the countries having similar demographic and socioeconomic aspects and health sector indicators using K-means clustering algorithm. The cumulative case data of the clustered countries enriched with data related to the lockdown measures are fed to the bidirectional LSTM to train the forecasting model. …"

Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier حسب Yassine Himeur (14158821)

"…Specifically, short local histograms are drawn to represent individual appliance consumption signatures and robustly extract appliance-level data from the aggregated power signal. Furthermore, an improved k-nearest neighbors (IKNN) algorithm is presented to reduce the learning computation time and improve the classification performance. …"

Generic metadata representation framework for social-based event detection, description, and linkage حسب Abebe, Minale A.

"…SEDDaL consists of four main modules for: i) describing social media objects in a generic Metadata Representation Space Model (MRSM) consisting of three composite dimensions: temporal, spatial, and semantic, ii) evaluating the similarity between social media objects’ descriptions following MRSM, iii) detecting events from similar social media objects using an adapted unsupervised learning algorithm, where events are represented as clusters of objects in MRSM, and iv) identifying directional, metric, and topological relationships between events following MRSM’s dimensions. …"
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