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

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Copy number variations in the genome of the Qatari population by Khalid A. Fakhro (3158862)

“…The four call-sets were integrated to identify high confidence CNV regions, which were subsequently annotated for putative functional effect and compared to public databases of CNVs in other populations. …”

A Robust Approach for Enhanced Autonomous Robot Navigation by Ismail, Sherif Khaled Mohamed Issa

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Tracking analysis of normalized adaptive algorithms by Moinuddin, M.

“…Close agreement between analytical analysis and simulation results is obtained for the case of the NLMS algorithm. The results show that, unlike the stationary case, the steady-state excess-mean-square error is not a monotonically increasing function of the step-size, while the ability of the adaptive algorithm to track the variations in the environment degrades by increasing the frequency offset.…”
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A fuzzy basis function network for generator excitation control by Abido, M.A.

“…A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper. …”
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Random vector functional link network: Recent developments, applications, and future directions by A.K. Malik (16003193)

“…We discuss the shallow RVFLs, ensemble RVFLs, deep RVFLs and ensemble deep RVFL models. The variations, improvements and applications of RVFL models are discussed in detail. …”

Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures by Leduc, Guillaume

“…We develop a semi-analytical method to determine the price of European options on these energy futures, involving the derivation of the characteristic function for the energy futures' dynamics. To determine the parameters of the regime switching model and identify when economic states change, we employ the EM algorithm, utilizing real gas futures price data. …”
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Tracking analysis of the NLMS algorithm in the presence of both random and cyclic nonstationarities by Moinuddin, M.

“…The results show that, unlike in the stationary case, the steady-state excess MSE is not a monotonically increasing function of the step size. Moreover, the ability of the adaptive algorithm to track the variations in the environment is shown to degrade with increasing frequency offset.…”
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Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm by Zerguine, A.

“…In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. …”
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Solution of Fractional Differential Equations: Transform and Iterative Methods Approach by Alchikh, Razan Abdul Satar

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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms by Md Ferdous Wahid (13485799)

“…This study aims to develop five robust machine learning (ML) algorithms and their fusions for a wide range of flow patterns (FP) regimes. …”

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

“…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. …”

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

“…The regulation speed in DTC is carried out by the classic Proportional Integrator Derivative (PID), which is known for its higher robustness in linear systems, except that in the case of non-linear systems, the PID controller gives poor reactions to variations in the system’s parameters. 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. …”

Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation by Raveendra Pilli (21633287)

“…<p dir="ltr">Accelerated brain aging and abnormalities are associated with variations in brain patterns. Effective and reliable assessment methods are required to accurately classify and estimate brain age. …”

A New Hamiltonian Semi-Analytical Approach to Vibration Analysis of Piezoelectric Multi-Layered Plates by Andrianarison, O.

“…By performing a Legendre Transform, the classical Lagrangian functional is recast into a Hamiltonian one, so that the resulting variational formulation can be expressed in terms of the displacements and electric potential and their transverse stresses and electric displacement dual variables. …”
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Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP by Abdelhafez, Nada

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Effective solutions for the capacitated vehicle routing problem and for the split delivery vehicle routing problem with time windows. (c2013) by Hilal, Nathalie

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DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications by Danya A. Saifaldeen (19498705)

“…To address this complexity optimally, we propose a deep reinforcement learning (DRL) approach based on the deep deterministic policy gradient (DDPG) technique. The DDPG algorithm can adapt to channel variations due to user movement and high-dimensional factors. …”

Phased Array Technique for Brain Source Localization by Zarghami, Tahereh

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Exploring the Dynamic Interplay of Deleterious Variants on the RAF1–RAP1A Binding in Cancer: Conformational Analysis, Binding Free Energy, and Essential Dynamics by Abbas Khan (5141000)

“…Integrated machine learning algorithms showed that among the 134 mutations reported for these 2 proteins, only 13 and 35 were classified as deleterious mutations in <i>RAF1</i> and <i>RAP1P</i>, respectively. …”