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. …”

Synthesis with VHDL. (c2001) by Halawi, Hatem

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From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors by Michael R. Giordano (9976173)

“…The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. Here we review the needs and challenges when trying to get high-quality data from low-cost sensors. …”

Framework for rapid design and optimisation of immersive battery cooling system by Ali Almshahy (23544823)

“…A conjugate heat transfer model for a 3S2P pouch cell module (20 Ah LiFePO₄) is developed and validated against experimental data (< 2% error). …”

Energy-aware adaptive compression for mobile devices. (c2009) by Maddah, Rakan

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Stacking-based ensemble learning for remaining useful life estimation by Begum Ay Ture (17773170)

A Novel Internal Model Control Scheme for Adaptive Tracking of Nonlinear Dynamic Plants by Khan, T.

“…The U-model utilizes only past data for plant modelling and standard root solving algorithm for control law formulation. …”
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Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS by Tekli, Joe

“…To do so, we design and construct a semantic-aware inverted index structure called SemIndex, extending the standard inverted index by constructing a tightly coupled inverted index graph that combines two main resources: a semantic network and a standard inverted index on a collection of textual data. We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. …”
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Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning by Zeinab, Samira Jihad

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Modeling of Chlorophyll-a and Eutrophication Indicators in the Dubai Creek Area using Remote Sensing by Bachir, Abdallah Raafat

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Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models by AL SHAMSI, ARWA AHMED

“…For the basic machine learning algorithms, LR, NB, SVM, RF, DT, MLP, AdaBoost, GBoost, and an ensemble model of machine learning classifiers were used. …”
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Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

“…In this thesis, we propose a novel heuristic based on Artificial Bee Colony (ABC) to optimize rule-based software quality prediction models. We validate our technique on data describing maintainability and reliability of classes in an Object-Oriented system. …”
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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)

“…The methodology involves data preparation with <u>imputation</u> and normalization, followed by training 9 supervised ML models. …”

DAP: A dataset-agnostic predictor of neural network performance by Sui Paul Ang (18460605)

C-3PA: Streaming Conformance, Confidence and Completeness in Prefix-Alignments by Raun, Kristo

“…The aim of streaming conformance checking is to find dis crepancies between process executions on streaming data and the refer ence process model. The state-of-the-art output from streaming confor mance checking is a prefix-alignment. …”
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Online dynamic ensemble deep random vector functional link neural network for forecasting by Ruobin Gao (16003195)

Single channel speech denoising by DDPG reinforcement learning agent by Sania Gul (18272227)

“…It achieves this performance by utilizing data that is 7 times smaller than that required by other models. …”

Generation and Detection of Sign Language Deepfakes - A Linguistic and Visual Analysis by Naeem, Shahzeb

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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System by Abougharib, Arwa

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Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper by Mutaz I. Othman (21186827)

“…<h3>Background</h3><p dir="ltr">Machine learning (ML) models can enhance patient–nurse assignments in healthcare organisations by learning from real data and identifying key capabilities. …”