Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials by Ghouti, Lahouari

“…The proposed techniques are: i) a batch-type deconvolution method using the complex bicepstrum algorithm, and ii) automatic ultrasonic defect classification system using a modular learning strategy. …”
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Design Optimization of Inductive Power Transfer Systems Considering Bifurcation and Equivalent AC Resistance for Spiral Coils by Alireza Namadmalan (16864236)

“…Equivalent AC resistance of spiral coils is modeled based on eddy currents simulations using Finite Element Method (FEM) and Maxwell simulator. …”

A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis by Alaa Abd-Alrazaq (17430900)

“…We used a machine learning–based method to analyze the most relevant COVID-19–related articles and extracted the most prominent topics. …”

Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark by Ameema Zainab (16864263)

“…<p>Machine learning algorithms have been intensively applied to perform load forecasting to obtain better accuracies as compared to traditional statistical methods. …”

"Particle swarm based design of variable structure stabilizer for a nonlinear model of SMIB system" by Al-Duwaish, H.

“…Unlike the methods reported in the literature which involve either linearizing the model of synchronous machine around a suitable operation point or applying nonlinear transformation techniques before linear control theory is used in designing a fixed parameter PSS, the present method formulates the design of VSC as an optimization problem and utilized the PSO algorithm to provide a simple and systematic way of arriving at the optimal feedback gains and switching vector values of the stabilizer. …”
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"Particle Swarm Based Design of Variable Structure Stabilizer for a Nonlinear Model of SMIB System" by Al-Hamouz, Z.

“…Unlike the methods reported in the literature which involve either linearizing the model of synchronous machine around a suitable operation point or applying nonlinear transformation techniques before linear control theory is used in designing a fixed parameter PSS, the present method formulates the design of VSC as an optimization problem and utilized the PSO algorithm to provide a simple and systematic way of arriving at the optimal feedback gains and switching vector values of the stabilizer. …”
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A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks by Umesh Kumar Lilhore (17727684)

“…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. …”

An automated temporal partitioning and loop fission approach for FPGA based reconfigurable synthesis of DSP applications by Ouaiss, I.

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Machine Learning-based X-Ray Projection Interpolation for Improved 4D-CBCT Reconstruction by Ramesh, Jayroop

“…Respiration-correlated cone-beam computed tomography (4D-CBCT) is an X-ray-based imaging modality that uses reconstruction algorithms to produce time-varying volumetric images of moving anatomy over a cycle of respiratory motion. …”
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An Enhanced MPPT Approach Based on CUSA for Grid-Integrated Hybrid Electric Vehicle Charging Station by Debabrata Mazumdar (18560506)

Mixed precision iterative refinement with adaptive precision sparse approximate inverse preconditioning by Noaman Khan (19810050)

“…In this work, we develop an adaptive precision sparse approximate inverse preconditioner and demonstrate its use within a five-precision GMRES-based iterative refinement method. We call this algorithm variant BSPAI-GMRES-IR. …”

On Equivalent Circuit Model-Based State-of-Charge Estimation for Lithium-Ion Batteries in Electric Vehicles by Fatma Ahmed (11084787)

“…Two real-time model-based estimation algorithms, Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF), are compared for SoC estimation. …”

Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018) by Tay, Bilal M.

“…Moreover, we propose in this thesis a Deep Learning Based Approach to Predict Non-Performing Loans. Compared to the literature, the proposed model embeds a new feature selection method and offers higher detection accuracy, which helps lenders and financial institutions to better manage their lending activities and loan monitoring processes.…”
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Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)

“…Therefore, this paper proposes an extensive review on deep learning based FDD methods for PV systems. After a brief description of the DL-based strategies, techniques for diagnosing PV systems proposed in recent literature are overviewed and analyzed to point out their differences, advantages and limits. …”

Robust Kalman filter and smoother for errors-in-variables model with observation outliers based on Least-Trimmed-Squares by ALMutawa, Jaafar

“…Keywords: Errors-in-variables model, Least-Trimmed- Squares, Kalman filter and smoother, outliers, random search algorithm, subsampling method.…”
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Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators by Abu Zitar, Raed

“…Moreover, the results of MGWO are compared with seven state-of-art gene selection methods using the same datasets based on classification accuracy and the number of selected genes. …”
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A degree-based heuristic for strongly connected dominating-absorbent sets in wireless ad-hoc networks by Abu-Khzam, Faisal N.

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A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata by Siddiqui, Ansah Juned

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Cuckoo search for portfolio optimization. (c2014) by Medawar, Mohammad Kamal El

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Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition by Abboud, Ralph

“…However, few methods have targeted sentiment-based music composition: generating music that expresses human emotions. …”
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