A reduced model for phase-change problems with radiation using simplified PN approximations by Belhamadia, Youssef

“…To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. A Newton-based algorithm is also adopted for solving the nonlinear systems resulting from the considered monolithic approach. …”
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Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

“…We build our model using machine learning techniques in particular rule-based models. …”
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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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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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Approximate XML structure validation based on document–grammar tree similarity by Tekli, Joe

“…Our approach exploits the concept of tree edit distance, introducing a novel edit distance recurrence and dedicated algorithms to effectively compare XML documents and grammar structures, modeled as ordered labeled trees. …”
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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. …”

Information warfare recovery-fighting back through the matrix. (c2012) by Zbib, Mirna

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

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

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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. …”

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. …”