The use of multi-task learning in cybersecurity applications: a systematic literature review by Shimaa Ibrahim (22155739)

“…Cybersecurity has become vital in information technology, with data protection being a major priority. Despite government and corporate efforts, cybersecurity remains a significant concern. …”

Acoustic Based Localization of Partial Discharge Inside Oil-Filled Transformers by Hamidreza Besharatifard (16904823)

“…<p dir="ltr">This paper addresses the localization of Partial Discharge through a 3D Finite Element Method analysis of acoustic wave propagation inside a 3-phase 35kV transformer with the help of COMSOL Multiphysics software. …”

Correlation Clustering with Overlaps by Fakhereldine, Amin

“…We present a heuristic algorithm and a semi-exact algorithm for the Multi-Parameterized Cluster Editing with Vertex Splitting problem. …”
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Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation by Hariprasath Manoharan (14157966)

“…Additionally, a clustering algorithm with a fuzzy membership function is implemented, allowing the robots to advance in accordance with predefined clusters and arrive at their starting place within a predetermined amount of time. …”

Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”

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. Based on the FEM simulations, a new approximation method using separation of variables is proposed as a function of spiral coil's main parameters. …”

Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV by Zulkifli, Muhammad

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Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems by Ahmad K. Sleiti (14778229)

“…Data-driven algorithms with capabilities to predict the system’s dynamic behavior still need to be developed. …”

A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation by Kfouri, Ronald

“…Also, to evaluate the robustness of the algorithms, we test the neural network, without retraining it, on multiple scenarios with noisier data and bad data. …”
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An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study by Ayman Hassan (14426412)

“…The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model.…”

Competitive learning/reflected residual vector quantization for coding angiogram images by 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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Design and analysis of entropy-constrained reflected residual vector quantization by Mousa, W.A.H.

“…Residual vector quantization (RVQ) is a vector quantization (VQ) paradigm which imposes structural constraints on the encoder in order to reduce the encoding search burden and memory storage requirements of an unconstrained VQ. …”
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Communications in electronic textile systems by Nakad, Z.

“…A new algorithm based on token grid schemes is presented that takes advantage of the e-textile physical configuration.…”
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Regression testing C# programs. (c2007) by Staitieh, Wael

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An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System by Alkhatib, Osama

“…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. Experiment is performed using Azure Machine Learning (ML) platform to test and assess the most efficient model that would predict the failure of system elements and predict the abnormality of the operation. …”
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Plant disease detection using drones in precision agriculture by Ruben Chin (17725986)

“…Color-infrared (CIR) images are the most preferred data used and field images are the main focus. The machine learning algorithm applied most is convolutional neural network (CNN). …”

Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

“…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …”

Efficient Seismic Volume Compression using the Lifting Scheme by Khene, M. F.

“…In addition, the lifting scheme offers: 1) a dramatic reduction of the required auxiliary memory, 2) an efficient combination with parallel rendering algorithms to perform arbitrary surface and volume rendering for interactive visualization, and 3) an easy integration in the parallel I/O seismic data loading routines. …”
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An Evolutionary Meta-Heuristic for State Justification in Sequential Automatic Test Pattern Generation by El-Maleh, Aiman H.

“…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. New approaches are needed to enhance the existing techniques, both to reduce execution time and improve fault coverage. …”
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An evolutionary meta-heuristic for state justification insequential automatic test pattern generation by El-Maleh, A.H.

“…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. New approaches are needed to enhance the existing techniques, both the reduce execution time and improve fault coverage. …”
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