On the P-type learning control by Saab, Samer S.

“…Sufficient conditions for the robustness and convergence of P-type learning control algorithms for a class of time-varying, nonlinear systems are presented. …”
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Theory of P-type learning control with implication for the robot manipulator by Saab, Samer S.

“…The robustness and convergence of P-type learning control algorithms for a class of time-varying, nonlinear systems with state disturbances, measurement noise at the output, and reinitialization errors at each iteration is studied. …”
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Experimental evaluation of multi-agent reinforcement learning in real-world scale-free networks by Al Hashimi, Rashid

“…However, the study and analysis of the state-of-the-art multi-agent reinforcement learning (MARL) algorithms have been limited to small problems involving few number of learning agents.The purpose of this project is to conduct an extensive evaluation and comparison of MARL algorithms when used in networks that exhibit the scale-free property. …”
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Robustness and Convergence of P-type Learning Control by Saab, Samer S.

“…The robustness and convergence of P-type learning control algorithms for a class of time-varying, nonlinear systems to state disturbances, measurement noise at the output, and reinitialization errors at each iteration is studied extensively. …”
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What are artificial intelligence literacy and competency? A comprehensive framework to support them by Thomas K.F., Chiu

“…Artificial intelligence (AI) education in K–12 schools is a global initiative, yet planning and executing AI education is challenging. …”
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A novel design technique for generating building form by KAYED, MAYS N. A.

“…The development of the technique is initiated by proposing an exploratory methodology where a procedural structure for the technique is formulated from four stages: “backward triangulation” stage, forward building formation stage, evaluation stage and selection stage. …”
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Predicting the Release of Chemotherapeutics From the Core of Polymeric Micelles Using Ultrasound by Abdel-Hafez, Mamoun

“…The release is measured as a decrease in fluorescence once ultrasound is applied. Initially, a Kalman filter is used to fuse the drug encapsulation (calculated as 100 %-release%) dynamics and measurements. …”
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Study of the Impact of Land Use and Land Cover (LULC) Changes on local climate in Six Mega Global Cities in the 21st Century by Sabobeh, Lara Ali

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Cardiovascular health research priorities in the United Arab Emirates by Ghader, Nariman

“…Participants were 37 experts from UAE hospitals, academic and research institutions, CVD associations, and paramedical organizations. Results: Initially, 138 research topics were suggested by participating experts. …”
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FarmTech: Regulating the use of digital technologies in the agricultural sector by Imad Antoine Ibrahim (14158998)

“…<p dir="ltr">Farming relies on the accurate collection and processing of data. Algorithms utilizing artificial intelligence can predict patterns and spot problems, helping farmers make more informed decisions. …”

LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

“…The main aim was to predict the initial leukemia disease. Machine learning algorithms such as decision tree (DT), naive bayes (NB), random forest (RF), gradient boosting machine (GBM), linear regression (LinR), support vector machine (SVM), and novel approach based on the combination of Logistic Regression (LR), DT and SVM named as ensemble LDSVM model. …”

Intelligent Bilateral Client Selection in Federated Learning Using Game Theory by Wehbi, Osama

“…Our solution involves designing (1) preference functions for the client IoT devices and federated servers to allow them to rank each other according to several factors such as accuracy and price, (2) intelligent matching algorithms that take into account the preferences of both parties in their design, and (3) bootstrapping technique that capitalizes on the collaboration of multiple federated servers in order to assign initial accuracy value for the new connected IoT devices. …”
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Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose by Atiq Ur Rehman (8843024)

“…These electronic instruments rely on Machine Learning (ML) algorithms for recognizing the sensed odors. The effect of long-term drift influences the performance of ML algorithms and the models those are trained on drift free data fail to perform on the drifted data. …”

Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review by Ruba, Sulaiman

“…Most of the included studies focused on mortality prediction, utilizing datasets of varying sizes and diverse ML algorithms. The most employed ML algorithms were random forest, logistics regression, and gradient boosting. …”
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Unlocking new frontiers in epilepsy through AI: From seizure prediction to personalized medicine by Majd A. AbuAlrob (22392505)

“…Ethical considerations, such as safeguarding patient privacy, ensuring data security, and mitigating algorithmic bias, underscore the importance of responsible AI integration. …”

Extracranial traumatic carotid artery dissections in children by Chamoun, Roukoz B.

“…Conclusions As a result of this review of the literature, the authors propose the algorithms for the evaluation and treatment of traumatic extracranial CADs in children. …”
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UML-based regression testing for OO software by Mansour, Nashat

“…Regression test selection determines a subset of test cases, from the initial test suite, which concentrates on the parts of the system affected by the modification. …”
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The automation of the development of classification models and improvement of model quality using feature engineering techniques by Sjoerd Boeschoten (17347045)

“…The proposed framework is extendable and configurable by adding algorithms supported by the CARET package implemented in the R programming language. …”

Predict Student Success and Performance factors by analyzing educational data using data mining techniques by ATIF, MUHAMMAD

“…The model is then applied to data collected from a reputable university that included 126,698 records with twenty-six (26) initial data attributes. The results show that the Random forest model performed better in terms of accuracy of 90.12% as compared to other models. …”
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE by Ben Romdhane, Haifa

“…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …”
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