Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning by Zeinab, Samira Jihad

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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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A combinatorial auction‐based approach for ridesharing in a student transportation system by Chefi Triki (14158860)

“…The concept of ridesharing is used and the mechanism of combinatorial auctions is incorporated within a routing-based model. The mathematical model is based on the vehicle routing problem along with appropriate constraints accommodating features that express the auction clearing phase. …”

On sensor selection in mobile devices based on energy, application accuracy, and context metrics by Taleb, Sireen

“…We use this algorithm to build a sensor selection model to choose among location sensors. …”
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Swarm intelligence-based hyper-heuristic for the vehicle routing problem with prioritized customers by Tarhini, Abbas

“…Various studies have been conducted regarding this topic; nevertheless, up to now, few studies used the Cuckoo Search-based hyper-heuristic. This paper modifies a classical mathematical model that represents the VRPC, implements and tests an evolutionary Cuckoo Search-based hyper-heuristic, and then compares the results with those of our proposed modified version of the Clarke Wright (CW) algorithm. …”
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Reconfigured Photovoltaic Model to Facilitate Maximum Power Point Tracking for Micro and Nano-Grid Systems by J. Prasanth Ram (19499062)

“…The I–V characteristics of conventional and reconfigured models are programmed into the simulator and the use of the hill climbing algorithm is validated. …”

Topology and parameter estimation in power systems through inverter-based broadband stimulations by Margossian, Harag

“…This study describes a method for identifying parameters associated with the power system model. In particular, the proposed algorithm in this study addresses the line parameter and topology identification task in the scope of state estimation. …”
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Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization by De Rochechouart, Maxence

“…This paper presents a reinforcement learning agent-based model that works by incorporating the MESA environment with the Stone Soup radar systems simulator. …”
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Generic metadata representation framework for social-based event detection, description, and linkage by Abebe, Minale A.

“…SEDDaL consists of four main modules for: i) describing social media objects in a generic Metadata Representation Space Model (MRSM) consisting of three composite dimensions: temporal, spatial, and semantic, ii) evaluating the similarity between social media objects’ descriptions following MRSM, iii) detecting events from similar social media objects using an adapted unsupervised learning algorithm, where events are represented as clusters of objects in MRSM, and iv) identifying directional, metric, and topological relationships between events following MRSM’s dimensions. …”
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An exact and general model order reduction technique for the finite element solution of elastohydrodynamic lubrication problems by Habchi, W.

“…The reduction technique is based on the static condensation principle. As such, it is exact and it preserves the generality of the solution scheme while reducing the size of its corresponding model and, consequently, the associated computational overhead. …”
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Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment by Farhat Mahmood (15468854)

“…The artificial neural network demonstrates a higher prediction accuracy and is used as the system model in the proposed control framework. A robust model predictive control strategy, based on the minimax objective function and particle swarm optimisation algorithm, is developed to handle the uncertainties in the system. …”

A pragmatic approach for testing robustness on real-time component based systems by Tarhini, Abbas

“…In this paper, we suggest a realistic methodology for testing robustness of real-time component-based systems (RTCBS). A RTCBS system is described as a collection of components where each component is specified by a nominal and a degraded specification, modeled as a timed input-output automaton (TIOA). …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti (21593819)

“…Three different publicly available datasets have been used based on the age group to create the best predicting model for each case. …”

MSLP: mRNA subcellular localization predictor based on machine learning techniques by Saleh Musleh (15279190)

“…</p><h3>Results</h3><p dir="ltr">Considering the combination of the above-mentioned features, ennsemble-based models achieved state-of-the-art results in mRNA subcellular localization prediction tasks for multiple benchmark datasets. …”

A heuristics for HTTP traffic identification in measuring user dissimilarity by Adeyemi R. Ikuesan (14157123)

“…The study utilizes HTTP request method of GET filtering, to develop a heuristic algorithm to identify user-initiated requests. The algorithm was experimentally tested on a group of users, to ascertain the certainty of identifying user-initiated requests. …”

Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

“…In this research, we present a novel data mining approach to predict retention among a homogeneous group of students, with similar social and cultural background, at an academic institution based in the UAE. Our model successfully identifes dropouts at an early stage. …”
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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. …”

Utilization of AI to Predict Shear Strength Parameters of Soil Based on Their Physical Properties by AbdulGhafour, Husaen

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Artificial intelligence-based methods for fusion of electronic health records and imaging data by Farida Mohsen (16994682)

Behavior-Based Machine Learning Approaches to Identify State-Sponsored Trolls on Twitter by Saleh Alhazbi (16869960)

“…We have proposed a set of behavioral features of users' activities on Twitter. Based on these features, we developed four classification models to identify political troll accounts, these models are based on decision tree, random forest, Adaboost, and gradient boost algorithms. …”