An efficient failure-resilient mutual exclusion algorithm for distributed systems leveraging a novel zero-message overlay structure by Mouna Rabhi (17086969)

“…The overlay structure – a unique logical tree – used to control access to the critical section maintains its consistency even when nodes fail. An extensive simulation study demonstrates the viability and efficiency of the proposed algorithm under various node failure models, and relevant metrics (e.g., node queue dimension, number of exchanged messages, and number of disconnected nodes) indicate a graceful degradation in performance with decreasing number of functioning nodes. …”

Motion Artifacts Correction From EEG and fNIRS Signals Using Novel Multiresolution Analysis by Md. Shafayet Hossain (16888833)

STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization by Muhammad Salman Khan (7202543)

ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation by Said Mahfoud (17150968)

“…The best solutions adopted in this situation are often based on optimization algorithms that generate the controller’s gains in each period where there is an internal or external perturbation, adapting the behaviors of the PID against the system’s nonlinearity. …”

Fragment-based computational protein structure prediction by Mansour, Nashat

“…The method is based on a two-phase Scatter Search algorithm that minimizes the energy function. Backbone fragments are extracted from the Robetta server and side chains are, extracted from the Dunbrack Library. …”
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Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids by Khayata, Mohammad Tarek

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Single channel speech denoising by DDPG reinforcement learning agent by Sania Gul (18272227)

“…<p dir="ltr">Speech denoising (SD) covers the algorithms that suppress the background noise from the contaminated speech and improve its clarity. …”

Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm by Noor Habib Khan (22224775)

“…To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. For validation of ILCA, the non‐parametric and the statistical analysis are performed using benchmark standard functions. …”

Development of an Optimization Scheme for A Fixed-Wing UAV Long Endurance with PEMFC and Battery by Al Rayes, Zaid

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Second-order conic programming for data envelopment analysis models by Mourad, Nahia

“…Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. …”
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Fragment based protein structure prediction. (c2013) by Terzian, Meghrig Ohanes

“…The method is based on a two-phase Scatter Search metaheuristic that minimizes the energy function. Backbone fragments selections extracted from the Robetta server are followed by side chain selections, extracted from the Dunbrack Library. …”
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Attacking ElGamal based cryptographic algorithms using Pollard's rho algorithm by El-Kassar, A. N.

“…In this work we implement the classical and modified ElGamal cryptosystem to compare and to test their functionality, reliability and security. To test the security of the algorithms we use a famous attack algorithm called Pollard's rho algorithm that works in the domain of natural integers. …”
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Cross entropy error function in neural networks by Nasr, G.E.

“…The ANN is implemented using the cross entropy error function in the training stage. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …”
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An Introduction to the Special Issue “Protein Glycation in Food, Nutrition, Health and Disease” by Naila Rabbani (291722)

“…The keynote speaker was Lasker Laureate Professor Kazutoshi Mori, speaking on the unfolded protein response, and there were sessions on: glycation in obesity, diabetes, and diabetic complications; glycation in food; glycation through the life course—from maternal bonding to aging; glycation in plants—physiology, function, and food security; glycation in the COVID-19 response; glycation analytics and chemistry; glycation in kidney disease, cancer, and mental health; glycation-related imaging, diagnostic algorithms, and therapeutics; and methods and models in glycation research. …”

Evolution Of Activation Functions for Neural Architecture Search by Nader, Andrew

“…However, to the best of our knowledge, the design of new activation functions has mostly been done by hand. In this work, we propose the use of a self-adaptive evolutionary algorithm that searches for new activation functions using a genetic programming approach, and we compare the performance of the obtained activation functions to ReLU. …”
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Scatter search metaheuristic for homology based protein structure prediction. (c2015) by Stamboulian, Mouses Hrag

“…Determining a protein’s structure is a challenging goal in structural bioinformatics, offering important insight towards understanding the function of a protein. …”
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Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact las... by Masurkar, Faeez

“…The functioning of the algorithm was successfully tested by carrying out extensive experiments on a real rail track in the presence of different types of surface and sub-surface defects on its head and web. …”
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Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning by Sait, Sadiq M.

“…The problem of partitioning appears in several areas ranging from VLSI, parallel programming, to molecular biology. …”
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Particle swarm optimization approach for protein structure prediction in the 3D HP model by Mansour, Nashat

“…Starting from a small set of candidate solutions, our algorithm efficiently explores the search space and returns 3D protein structures with minimal energy. …”
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AGEomics Biomarkers and Machine Learning—Realizing the Potential of Protein Glycation in Clinical Diagnostics by Naila Rabbani (291722)

“…The term AGEomics is defined as multiplexed quantitation of spontaneous modification of proteins damage and other usually low-level modifications associated with a change of structure and function—for example, citrullination and transglutamination. …”