Learning control algorithms for tracking "slowly" varying trajectories by Saab, Samer S.

“…This is due to the requirement that all learning algorithms assume that a desired output is given a priori over the time duration t /spl isin/ ~0,T\. …”
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Adaptive Fault-Tolerant Communication Based-Control for Parallel Connected Rectifiers by Ali Sharida (17947847)

“…<p dir="ltr">This article proposes an adaptive and fault-tolerant communication method for controlling parallel-connected active front-end rectifiers (AFRs). …”

Learning-Based Space-Time Adaptive Processing by El Khatib, Alaa

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New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications by Mohieddine Benammar (18103039)

“…A new 2nd order rational approximation formula is introduced for the first time in this work and benchmarked against existing alternatives as it improves the new algorithm performance. …”

Digital-Twin-Based Diagnosis and Tolerant Control of T-Type Three-Level Rectifiers by Ali Sharida (17947847)

“…<p dir="ltr">This article proposes a digital twin (DT)-based diagnosis and fault-tolerant control for T-type three-level rectifiers. …”

Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing by Al Sadawi, Alia

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Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

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Linear-time algorithms for problems on planar graphs with fixed disk dimension by Abu-Khzam, Faisal N.

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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain by Al Sadawi, Alia

“…The objective is to minimize different cost types while satisfying constraints such as resources availability, customer service level, and tasks dependency relation. The algorithm proved its effectiveness by allocating tasks with higher priority and weight while taking into consideration customers’ Service Level Agreement, time, and different types of costs, which led to a lower total cost of the batching process. …”
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Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System by B. Rouabah (17947820)

“…In this study, a photovoltaic water pumping system with two power converters, the first is used to extract the maximum power using the maximum power point tracking (MPPT) algorithm, and the second is a three-cell multicellular power converter used to control the DC motor with a submerged pump. …”

A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net by Sania Gul (18272227)

“…It is found that the useful features hidden in the time domain are highlighted when the audio signal is converted to a spectrogram, which can be treated as an image. …”

Socially Motivated Approach to Simulate Negotiation Process by Hammadih, Mohammed Zaher

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Improved search-tree algorithms for the cluster edit problem. (c2011) by Ghrayeb, Ali Kassem

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Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”

A parallel search tree algorithm for vertex cover on graphical processing units. (c2013) by Kabbara, Rashad Karim

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Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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Image-CNN Based Process Control of Profile by Zeinab, Zeinab Jihad

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A decentralized load balancing strategy for parallel search-three optimization. (c2010) by Mouawad, Amer E.

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Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”

A discrete-time stochastic iterative learning control algorithm for a class of nonlinear systems by Saab, S. S.

“…This article presents a stochastic algorithm that computes the learning gain matrix of a “D-type iterative learning control (ILC) algorithm for a class of discrete-time varying nonlinear systems with linear input/output actions having relative degree one. …”
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