Neural network-based failure rate prediction for De Havilland Dash-8 tires by 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. …”
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An Adaptive Joint Sparsity Recovery for Compressive Sensing Based EEG System by Hamza Djelouat (14603379)

“…Furthermore, the paper proposes a modification to the SP algorithm based on an adaptive selection approach to further improve the performance in terms of reconstruction quality, execution time, and the robustness of the recovery process. …”

Optimizing Aircraft Pitch Control Systems: A Novel Approach Integrating Artificial Rabbits Optimizer with PID-F Controller by Abualigah, Laith

“…This combination aims to enhance the stability and performance of the aircraft pitch control system by effectively mitigating the kick effect through the incorporation of a filter coefficient in the derivative gain. The study employs a time-domain-based objective function to guide the optimization process. …”
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Computation of conformal invariants by Mohamed M.S. Nasser (16931772)

“…We compare the performance and accuracy to previous results in the cases when numerical data is available and also in the case of several model problems where exact results are available.…”

On sensor selection in mobile devices based on energy, application accuracy, and context metrics by Taleb, Sireen

“…We use this algorithm to build a sensor selection model to choose among location sensors. …”
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Failure-Rate Prediction for De Havilland Dash-8 Tires Employing Neural-Network Technique by 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. …”
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Soft Sensor for NOx Emission using Dynamical Neural Network by Shakil, M.

“…Neural network model is trained using real data logs of an industrial boiler. …”
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Artificial Intelligence–Driven Serious Games in Health Care: Scoping Review by Alaa Abd-alrazaq (17058018)

“…Accuracy was the most commonly used metric for evaluating the performance of AI models.</p><h3>Conclusions</h3><p dir="ltr">The last decade witnessed an increase in the development of AI-driven serious games for health care purposes, targeting various health conditions, and leveraging multiple AI algorithms; this rising trend is expected to continue for years to come. …”

Enhanced DC Microgrid Protection: a Neural Network and Wavelet Transform Approach by El Gohary, Youssef Hesham

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Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning by ALFALASI, FARIS Jr

“…The data needs to be initially prepared so that deep learning algorithms may be trained on it before cyberbullying analysis can be done. …”
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Topology and parameter estimation in power systems through inverter-based broadband stimulations by Margossian, Harag

“…This study describes a method for identifying parameters associated with the power system model. In particular, the proposed algorithm in this study addresses the line parameter and topology identification task in the scope of state estimation. …”
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Fragment based protein structure prediction. (c2013) by Terzian, Meghrig Ohanes

“…In recent years, the protein structure prediction problem has come under extensive investigation, and computational structure prediction methods are circumventing the time-consuming experimental methods by accelerating the prediction process. …”
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Recent advances on artificial intelligence and learning techniques in cognitive radio networks by Abbas, Nadine

“…For efficient real-time process, the cognitive radio is usually combined with artificial intelligence and machine-learning techniques so that an adaptive and intelligent allocation is achieved. …”
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Internal Model Control Structure Using Adaptive Inverse Control Strategy by Shafiq, M.Riyaz

“…The internal model of the plant is estimated by recursive least square algorithm and the inverse of the system by least mean square. …”
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Structural alignment. (c2006) by Kazma, Layal

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Combinatorial method for bandwidth selection in wind speed kernel density estimation by El Dakkak, Omar

“…This goal calls for devising probabilistic models with adaptive algorithms that accurately fit wind speed distributions. …”
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Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context by SALIM, MAHA JAWDAT

“…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …”
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Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier by Syed Ali Jafar Zaidi (19563178)

“…Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …”

A Machine Learning Approach to Predicting Diabetes Complications by Jian, Yazan Khaled

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A Closed Queueing Networks Approach for an Optimal Heterogeneous Fleet Size of an Inter-Facility Bulk Material Transfer System by Mohamed Amjath (17542512)

“…Methods: The material transfer process is modelled using a closed queueing network (CQN) that considers heterogeneous nodes and customised service times tailored to the unique characteristics of various truck types and their transported materials. …”