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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Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter by Syed Rahman (569240)

“…Since, PWAM control algorithm is more complex than PSCPWM, FPGA based implementation for PWAM control is discussed. …”

Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

“…The effect of surface area loading rate (SALR), organic matters (OMs), nutrients (N & P), feed flow rate (Q_feed), hydraulic retention time (HRT), and internal recycle flow (IRF) on the performance of the ENR-BP to fulfil rigorous discharge limitations were evaluated. Experimental data was used to develop the appropriate architecture for the AAN using iterative steps of training and testing. …”

Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives by Yassine Himeur (14158821)

“…In this regard, this paper is an in-depth review of existing anomaly detection frameworks for building energy consumption based on artificial intelligence. Specifically, an extensive survey is presented, in which a comprehensive taxonomy is introduced to classify existing algorithms based on different modules and parameters adopted, such as machine learning algorithms, feature extraction approaches, anomaly detection levels, computing platforms and application scenarios. …”

Information warfare. (c2015) by Sai, Mohamed El

“…Numerous damage assessment and recovery algorithms have been proposed by researchers. In this work we present an efficient lightweight detection and recovery algorithm that is based on the matrix approach and that can be used to recover from malicious attacks. …”
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A Comprehensive Review on Conventional and Machine Learning-Assisted Design of 5G Microstrip Patch Antenna by Nupur Chhaule (21224987)

Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…So far none addresses the use of Threat Intelligence (IT) data in Ensemble Learning algorithms to improve the detection process, nor does it work as a function of time, that is, taking into account what happens on the network in a limited time interval. …”
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A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network by KHAN, FIROZ

“…The data is finally classified as either ransomware or goodware using the learning methodologies. …”
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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization by Yassine Himeur (14158821)

Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters by Sakib Mahmud (15302404)

“…In this study, we introduce the multimodal feature fusion for non-intrusive occupancy monitoring (MMF-NIOM) framework, which leverages both classical and deep machine learning algorithms to achieve state-of-the-art occupancy detection performance using smart meter data. …”

Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala (22330876)

“…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …”

DRL-Based UAV Path Planning for Coverage Hole Avoidance: Energy Consumption and Outage Time Minimization Trade-Offs by Bahareh Jafari (22501715)

“…As such, in addition to avoiding coverage holes, we should also make the outage time as small as possible. By deploying a deep reinforcement learning algorithm, we find optimal UAV paths based on the two families of trajectories: spiral and oval curves, to tackle different design considerations and constraints, in terms of QoS, energy consumption and coverage hole avoidance. …”

Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) by AL SHOUBAKI, HAMZA YOUNIS

“…In our research, we introduce a comprehensive approach to Arabic poetry text classification using deep learning techniques. We have used an almost one-million record dataset of Arabic poetry verses extracted from a poetry encyclopedia. …”
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Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique by Iqbal Hassan (22155274)

“…In this study, we harnessed the capabilities of a four-channel, wearable EEG device that captured brain activity data during two distinct CL states: Baseline (representing a non-CL, resting state) and the Stroop Test (a CL-inducing state). …”

An Auction-Based Scheduling Approach for Minimizing Latency in Fog Computing Using 5G Infrastructure by Fahmy, Ahmed

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Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images by Rehan Raza (17019105)

“…Moreover, it is faster and requires fewer parameters to train than other CNN based models, making it a good choice for large-scale deployment in clinical settings and a promising tool for automated lung cancer diagnosis from CT scan images.…”

Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks by Sharma, Neetan

“…The proposed ANN based algorithm has been used for unswerving petite term forecasting. …”
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HVAC system attack detection dataset by Mariam Elnour (14147790)

“…It aims to promote and support the research in the field of cybersecurity of HVAC systems in smart buildings by facilitating the validation of attack detection and mitigation strategies, benchmarking the performance of different data-driven algorithms, and studying the impact of attacks on the HVAC system.…”

Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur (712349)

“…The most widely used algorithms incorporate Support Vector Machine (SVM), Random Forest (RF), Convolutional Neural Network (CNN), and MobileNet with accuracy rates between 64.3 and 100%. …”