A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks by Umesh Kumar Lilhore (17727684)

“…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …”

Cortical EEG Source Localization of Focal Epilepsy by Siyam, Wisal Elfatih Mohamed

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Automatic Video Summarization Using HEVC and CNN Features by Issa, Obada

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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”

Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link by Bayan Hussein (16904856)

Predict Student Success and Performance factors by analyzing educational data using data mining techniques by ATIF, MUHAMMAD

“…The model is then applied to data collected from a reputable university that included 126,698 records with twenty-six (26) initial data attributes. …”
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Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey by Faria Nawshin (21841598)

Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

“…For such high-dimension data our approach outperforms the Synthetic Minority Oversampling Technique for Regression (SMOTER) algorithm for the IMDB-WIKI and AgeDB image datasets. …”

Label dependency modeling in Multi-Label Naïve Bayes through input space expansion by PKA Chitra (21749216)

“…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. We subject our enhanced iMLNB model to a rigorous empirical evaluation, utilizing six benchmark datasets. …”

Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic by Hassan Farhat (9000509)

Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation by Fawaz Kserawi (16904859)

“…We describe our differentially-private model with flexible constraints and a dynamic window algorithm to maintain the privacy-budget loss in infinitely generated time-series data. …”

Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review by Mohamed Massaoudi (16888710)

“…With the massive smart meter integration, DL takes advantage of the large-scale and multi-source data representations to achieve a spectacular performance and high PV forecastability potential compared to classical models. …”

A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models by Osama Bassam J. Rabie (21323741)

“…Moreover, the DBRF classification model is deployed to categorize the normal and attacking data flows using optimized features. …”

Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE by SHWEDEH, FATEN

“…We examined different feature selection methods and classification algorithms to find the best prediction model with the highest accuracy. …”
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On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network by Nasru Minallah (9427338)

Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment by Zakaria Tolba (16904718)

“…This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …”

The Effects of Data Mining on Small Businesses in Dubai by AlMutawa, Rasha

“…While there are numerous studies on the best data mining models and their uses, even on certain industries, this study focuses on the applications more than the algorithms and models and their usefulness for small businesses specifically. …”
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Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

“…LR with the reduced feature set using the intersection between CS and RFE proved to be the best model among the tested algorithms. This model can be used in a clinical setting as a decision support system or for public health awareness as an informal risk prediction system. …”
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Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV by Zulkifli, Muhammad

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