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

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

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A combined algorithm based on finite elements and a modified methodof characteristics for the analysis of the corona in wire-ductelectrostatic precipitators حسب Al-Hamouz, Z.M.

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Nonlinear analysis of shell structures using image processing and machine learning حسب 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 discrete-time stochastic iterative learning control algorithm for a class of nonlinear systems حسب 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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EEG Signal Processing for Medical Diagnosis, Healthcare, and Monitoring: A Comprehensive Review حسب Nisreen Said Amer (17984077)

"…The development of novel sensors for EEG recording, digital signal processing algorithms, feature engineering, and detection algorithms increases the need for efficient diagnostic systems. …"

A reduced model for phase-change problems with radiation using simplified PN approximations حسب Belhamadia, Youssef

"…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …"
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Parallel processing حسب Mansour, Nashat

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Decision-level Gait Fusion for Human Identification at a Distance حسب Al-Tayyan, Amer

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A fast exact sequential algorithm for the partial digest problem حسب Mostafa M. Abbas (17058093)

"…Determining the exact locations of restriction sites following a partial digestion is challenging due to the computational time required even with the best known practical algorithm.…"

Brain Source Localization in the Presence of Leadfield Perturbations حسب Momin, Rabiya Nakhat

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FPGA-based Parallel Hardware Architecture for Real-time Object Classification حسب Qasaimeh, Murad Mohammad

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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques حسب Fares, Samar

"…The first method uses an offline technique based on a global optimizer called the CMA-ES algorithm and the second one uses LSTM in its different forms to learn the online adjustment of the fusion weights between the two tracks. …"
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MSD-NAS: multi-scale dense neural architecture search for real-time pedestrian lane detection حسب Sui Paul Ang (18460605)

Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study حسب Alkhodari, Mohanad Ahmed

"…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …"
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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms حسب Arafat Rahman (8065562)

A Survey of Data Clustering Techniques حسب Sobeh, Salma

"…The situation can become problematic as these vast amounts of data require significant storage capacity, which leads to challenges in executing tasks such as analytical operations, processing operations, and retrieval operations that are time-consuming and arduous. …"
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Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning حسب Zeinab, Samira Jihad

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

الموضوعات:

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children حسب Jayakanth, Kunhoth

"…The feature fusion approach substantially improved the classification accuracy, with the SVM trained on fused features from the task specific-data achieving an accuracy of 97.3%. …"
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