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181
Cyberbullying Detection Model for Arabic Text Using Deep Learning
Published 2023“…As a result of the models’ evaluation, a hybrid DL model is proposed that combines the best characteristics of the baseline models CNN, BLSTM and GRU for identifying cyberbullying. …”
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182
Iterative Methods for the Solution of a Steady State Biofilter Model
Published 2017Get full text
doctoralThesis -
183
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184
Degree-Based Network Anonymization
Published 2020“…In this thesis, we study a new multi- objective parameterized anonymization approach that generalizes the known degree anonymization problem and attempts at improving it as a more realistic model for data security/privacy. Our model suggests a convenient privacy level for each net- work based on the standard deviation of its degrees. …”
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masterThesis -
185
A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm
Published 2023“…The t-test and the binary whale optimization algorithm (BWOA) were applied to choose the best features and train the support vector machine (SVM) model with validation and training data. …”
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186
Geographical Area Network—Structural Health Monitoring Utility Computing Model
Published 2019“…Every gateway is routing the data to SHM-UCM servers running a geo-spatial patch health assessment and prediction algorithm. …”
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187
A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
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masterThesis -
188
Modelling Exchange Rates during Currency Crisis using Neural Networks
Published 2006“…Exchange rate data from the Lebanese currency crisis period of 1985-1992 is used for training, testing and evaluation of the models. …”
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conferenceObject -
189
Modeling and Bias-Robust Estimation of the Acoustic Release of Chemotherapeutics from Liposomes
Published 2019“…The results suggest that the proposed algorithm, the optimal Kalman filter, performs well in modeling acoustically activated drug release from liposomes.…”
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190
Scatter search metaheuristic for homology based protein structure prediction. (c2015)
Published 2015“…We assess our algorithm on a total of 11 proteins whose structures are present in the Protein Data Bank (PDB) and which has been used in previous literature. …”
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masterThesis -
191
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192
Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
Published 2017Get full text
doctoralThesis -
193
A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation
Published 2021“…In the proposed FDD approach, named interval reduced kernel PCA (IRKPCA)-based Random Forest (IRKPCA-RF), the feature extraction and selection phase is performed using the IRKPCA models while the fault classification is ensured using the RF algorithm. …”
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194
Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques
Published 2022“…Nowadays, learning-based modeling methods are utilized to build a precise forecast model for renewable power sources. …”
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195
Identification of errors-in-variables model with observation outliers based on Minimum-Covariance-Determinant
Published 2007“…The proposed algorithm has been applied to a heat exchanger data.…”
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article -
196
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197
AI-based remaining useful life prediction and modelling of seawater desalination membranes
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doctoralThesis -
198
The use of multi-task learning in cybersecurity applications: a systematic literature review
Published 2024“…Cybersecurity has become vital in information technology, with data protection being a major priority. Despite government and corporate efforts, cybersecurity remains a significant concern. …”
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199
Developing a UAE-Based Disputes Prediction Model using Machine Learning
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doctoralThesis -
200
From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors
Published 2021“…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. …”