A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

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CNN and HEVC Video Coding Features for Static Video Summarization by Issa, Obada

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Novel algorithms for accurate DNA base-calling by Mohammed, Omniyah Gul

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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

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

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A reduced model for phase-change problems with radiation using simplified PN approximations by 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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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices by Khawam, Yahya Bader

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

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

“…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …”
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Evacuation of a highly congested urban city by El Khoury, John

“…The algorithm uses Dijkstras algorithm to find the shortest path(s) and a modified greedy algorithm to assign maximum flows to selected paths given a specific schedule per time interval. …”
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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid (22047578)

Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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Study of the Impact of Land Use and Land Cover (LULC) Changes on local climate in Six Mega Global Cities in the 21st Century by Sabobeh, Lara Ali

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The Use of Microwave Tomography in Bone Healing Monitoring by Alkhodari, Mohanad Ahmed

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

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Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices by Aya Hasan Alkhereibi (17151070)

“…Drawing on data from the Smart Cities Index (SCI) and other economic and sustainability competitiveness metrics, the study uses various <u>ML algorithms</u> to categorize cities into <u>performance classes</u>, ranging from high-achieving Class 1 to emerging Class 3 cities. …”

Design of adaptive arrays based on element position perturbations by Dawoud, M.M.

“…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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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. …”

Next-generation energy systems for sustainable smart cities: Roles of transfer learning by Yassine Himeur (14158821)

“…This is possible by adopting next-generation energy systems, which leverage artificial intelligence, the Internet of things (IoT), and communication technologies to collect and analyze big data in real-time and effectively run city services. However, training machine learning algorithms to perform various energy-related tasks in sustainable smart cities is a challenging data science task. …”