A Cyber-Physical System and Graph-Based Approach for Transportation Management in Smart Cities حسب Muhammad Mazhar Rathore (17051745)

"…To efficiently process the incoming big data streams, the proposed architecture uses the Apache GraphX tool with several parallel processing nodes, along with Spark and Hadoop that ultimately provide better performance against various state-of-the-art solutions. …"

DoFP-ML: A Machine Learning Approach to Food Quality Monitoring Using a DoFP Polarization Image Sensor حسب Maen Takruri (10873368)

Extreme Early Image Recognition Using Event-Based Vision حسب Abubakar Abubakar (18278998)

"…<p dir="ltr">While deep learning algorithms have advanced to a great extent, they are all designed for frame-based imagers that capture images at a high frame rate, which leads to a high storage requirement, heavy computations, and very high power consumption. …"

Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective حسب Zhitao Xu (2426023)

"…It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …"

Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review حسب Rehaan Hussain (22302742)

"…In current literature, there are a number of papers that address all these faults using different methods, and this paper compiles the information from the written works for ease of access. Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …"

Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study حسب Alaa Abd-alrazaq (17058018)

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

Personalization in Real-Time Physical Activity Coaching Using Mobile Applications: A Scoping Review حسب Francisco Monteiro-Guerra (16864122)

A Multi-Channel Convolutional Neural Network approach to automate the citation screening process حسب Raymon van Dinter (10521952)

"…This study aims to automate the citation screening process using Deep Learning algorithms. With this, it is aimed to reduce the time and costs of the citation screening process and increase the precision and recall of the relevant primary studies. …"

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

"…For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. …"

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

"…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. …"

Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter حسب 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 multi-pretraining U-Net architecture for semantic segmentation حسب Cagla Copurkaya (22502042)

"…In this research, we propose and evaluate a modified version of a deep learning algorithm called U-Net architecture for partitioning histopathological images. …"

The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review حسب Uzair Shah (15740699)

"…We categorized the studies based on AI techniques, such as machine learning and deep learning. The most prominent ML algorithm was a support vector machine, and the DL algorithm was a convolutional neural network. …"

An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM حسب Al-Naffouri, T.Y.

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Leveraging UAVs for Coverage in Cell-Free Vehicular Networks حسب Samir, Moataz

"…To address these challenges, we formulate the trajectories decisions making as a Markov decision process where the system state space considers the vehicular network dynamics. Then, we leverage deep reinforcement learning to propose an approach for learning the optimal trajectories of the deployed UAVs to efficiently maximize the coverage, where we adopt Actor-Critic algorithm to learn the vehicular environment and its dynamics to handle the complex continuous action space. …"
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A forward-backward Kalman for the estimation of time-variant channels in OFDM حسب Al-Naffouri, T.Y.

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Communications in electronic textile systems حسب Nakad, Z.

"…Abstract- Electronic textiles (e-textiles) are emerging as a novel method for constructing electronic systems in wearable and large area applications. …"
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DASSI: differential architecture search for splice identification from DNA sequences حسب Shabir Moosa (14153316)

"…The demand for robust algorithms over the recent years has brought huge success in the field of Deep Learning (DL) in solving many difficult tasks in image, speech and natural language processing by automating the manual process of architecture design. …"

Competitive learning/reflected residual vector quantization for coding angiogram images حسب Mourn, W.A.H.

"…Medical images need to be compressed for the purpose of storage/transmission of a large volume of medical data. Reflected residual vector quantization (RRVQ) has emerged recently as one of the computationally cheap compression algorithms. …"
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