Identification of errors-in-variables model with observation outliers based on Minimum-Covariance-Determinant by ALMutawa, J.

“…In this paper, we develop a subspace system identification algorithm for the errors-in-variables (EIV) model subject to observation noise with outliers. …”
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Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems by Tarek Berghout (16905132)

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. …”

A Biologicaly Inspired Decision Model for Multivariable Genetic- Fuzzy-AHP System by Kouatli, Issam

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AI-based remaining useful life prediction and modelling of seawater desalination membranes by Al Ali, Fajer

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Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models by EZZELDIN, KHALED MOHAMED KHALED

“…Additionally, the GRU-CNN hybrid model attained a notable accuracy of 90%. These findings establish the robustness and effectiveness of hybrid architectures in enhancing emotion recognition accuracy in Arabic speech data, presenting a novel approach for Arabic dialect sentiment analysis.…”
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Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar (16904526)

“…Several dataset analysis models are utilised to study the data diversity. Further, this study demonstrates the application of neural network-based models to effectively predict the permeability. …”

Developing a UAE-Based Disputes Prediction Model using Machine Learning by Abu Laila, Ibrahim Wasef Subhi

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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. …”

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. …”

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

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Practical Multiple Node Failure Recovery in Distributed Storage Systems by Itani, M.

“…The problem is solved using genetic algorithms that search within the feasible solution space. …”
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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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Modelling surface currents in the Eastern Levantine Mediterranean using surface drifters and satellite altimetry by Issa, Leila

“…We present a new and fast method that blends altimetric and drifter positions data in order to predict the surface velocity in the Eastern Levantine Mediterranean. …”
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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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DAP: A dataset-agnostic predictor of neural network performance by Sui Paul Ang (18460605)

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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