Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)

“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”

Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems by Tarek Berghout (16905132)

Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes by Muhammad Mohsin Khan (22150360)

“…Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …”

The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review by Zainab Jan (17306614)

“…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …”

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

“…We aimed to develop an app using a comprehensive geomapping navigation and estimation system based on machine learning algorithms. This app uses key stroke-related timelines including the last time the patient was known to be well, patient location, treatment options, and imaging availability at different health care facilities.…”

Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas by Marwan Dhuheir (19170898)

“…<p dir="ltr">Over the past decade, Unmanned Aerial Vehicles (UAVs) have attracted significant attention due to their potential applications in emergency-response applications, including wireless power transfer (WPT) and data collection from Internet of Things (IoT) devices in disaster-affected areas. …”

Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter by Mena S. ElMenshawy (17983807)

“…A few research studies focused on developing data filtering algorithm for the load forecasting process using approaches such as Kalman filter, which has good tracking capability in the presence of noise in the data collection process. …”

A forward-backward Kalman for the estimation of time-variant channels in OFDM by Al-Naffouri, T.Y.

“…In this paper, we propose an expectation-maximization (EM) algorithm for joint channel and data recovery. The algorithm makes use of the rich structure of the underlying communication problem-a structure induced by the data and channel constraints. …”
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An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM by Al-Naffouri, T.Y.

“…In this paper, we propose an expectation-maximization algorithm for joint channel and data recovery in fast fading environments. …”
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An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System by Alkhatib, Osama

“…Therefore, for this paper multiple machine learning algorithms are investigated to predict system failure based on vehicle trips information as well as maintenance management historical data including preventive maintenance and corrective maintenance. …”
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Establishing Autonomous AUS-Quadrotor by Al Younes, Younes

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Corona power loss computation in bundled bipolar conductors by Al-Hamouz, Z.M.

“…In this paper, a finite element (FE) based algorithm devoted for the computation of the corona current and hence the corona power loss associated with bundled bipolar high voltage direct current (HVDC) conductors is presented. …”
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Newton-Raphson based adaptive inverse control scheme for tracking of nonlinear dynamic plants by Shafiq, M.

“…The U-model is utilized to design an adaptive inverse controller by using a simple root-solving algorithm of Newton-Raphson. The synergy of U-model with AIC structure has provided an effective and straight forward method for adaptive tracking of nonlinear plants. …”
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Simulations of the penetration of 6061-T6511 aluminum targets by spherical-nosed VAR 4340 steel projectiles by Warren, Thomas

“…In the context of an analysis code, this approximation eliminates the need for discretizing the target as well as the need for a contact algorithm. Thus, this method substantially reduces the computer time and memory requirements. …”
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RFID localization using single reader antenna. (c2014) by Msheik, Hamze

“…In today‟s modern world it is very important to wirelessly track assets whether small items such as bananas, patients in hospital, to massive mining machines. …”
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Vibration suppression in a cantilever beam using a string-type vibration absorber by Issa, Jimmy S.

“…The string is rigidly connected to the fixed end of the beam and through a spring and damper to a second point on the beam. The finite element method is used to model the system and a reduced order model is obtained through modal reduction performed on both the string and the beam. …”
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Online Control and Optimization of Directional Drilling by unknown

“…The objective function considered is to minimize the tracking error and drilling efforts. Detailed mathematical formulation and computer simulation were used for evaluation of the performance of the proposed techniques for both systems, based on real well data.…”
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A Deployment Optimization Model for Wimax Base-Stations by Aboualmal, Abdulhadi Mahmoud

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Portable Electromagnetic Surface Profiling System by Al Homssi, Bassel Mohamad

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Adaptive controlled superconducting magnetic energy storage devices for performance enhancement of wind energy systems by Rania A., Turky

“…The detailed modeling of the whole system is presented, including measured wind speed data, detailed switching techniques, a drive train model of the turbine, and real SMESD. …”
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