Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm by Odat, Alhaj-Saleh A.

“…The model aims to compare the performance of classical perturb and observe (P&O) algorithm, particle swarm optimization (PSO) algorithm, flower pollination algorithm (FPA), and SMC-based tracking techniques. …”
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Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain by Jun Zhu (84054)

“…The “MODIS-like” VIIRS data (VIIRS_ML) are being produced experimentally at NASA, from a version of the “dark-target” algorithm that is applied to MODIS. In this study, the AOD and aerosol model types from these two VIIRS retrieval algorithms over the North China Plain (NCP) are evaluated using the ground-based CE318 Sunphotometer (CE318) measurements during 2 May 2012–31 March 2014 at three sites. …”

Online dynamic ensemble deep random vector functional link neural network for forecasting by Ruobin Gao (16003195)

“…<p>This paper proposes a three-stage online deep learning model for time series based on the ensemble deep random vector functional link (edRVFL). …”

Optimal Dispatch of Mobile Energy Storage Unit to Support EV Charging Stations by Elmeligy, Mohamed Mostafa Abdelazim

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Empowering IoT Resilience: Hybrid Deep Learning Techniques for Enhanced Security by Muhammad Maaz (5600600)

“…The time efficiency of both proposed algorithms renders them well-suited for deployment in IoT ecosystems. …”

Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis by Sami Elzeiny (16891521)

Design of adaptive arrays based on element position perturbations by Dawoud, M.M.

“…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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Identifying Regional Trends in Avatar Customization by Peter Mawhorter (18602944)

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Optimization of Piezoelectric Sensor-Actuator for Plate Vibration Control Using Evolutionary Computation: Modeling, Simulation and Experimentation by Asan G. A. Muthalif (16888818)

“…Both disturbance and control signal acting on the plate is created by using piezoelectric (PZT) patches. The analytical model is derived based on the Euler-Bernoulli model. …”

H.264/AVC to HEVC Video Transcoder Based on Dynamic Thresholding and Content Modeling by Peixoto, Eduardo

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A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis by Alaa Abd-Alrazaq (17430900)

“…Specifically, we used a clustering algorithm to group published articles based on the similarity of their abstracts to identify research hotspots and current research directions. …”

Reputation-based cooperative detection model of selfish nodes in cluster-based QoS-OLSR protocol. (c2014) by Moati, Nadia

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CFD Based Airfoil Shape Optimization for Aerodynamic Drag Reduction by Khot, Mohammed Taha Shafiq

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Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems by Majdi Mansouri (16869885)

“…The developed techniques are based on Support Vector Machine (SVM) model to improve the diagnosis of WEC systems. …”

Finetuning Analytics Information Systems for a Better Understanding of Users: Evidence of Personification Bias on Multiple Digital Channels by Bernard J. Jansen (7434779)

“…<p dir="ltr">Although the effect of hyperparameters on algorithmic outputs is well known in machine learning, the effects of hyperparameters on information systems that produce user or customer segments are relatively unexplored. …”

Learning-Based Spectrum Sensing and Access for Cognitive Radio Systems by Shehabeldin, Menatalla Diaaeldin

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The Use of Microwave Tomography in Bone Healing Monitoring by Alkhodari, Mohanad Ahmed

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Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

“…This computational framework can expedite and improve the process of finding desirable molecular structures of IL via accurate property predictions in a data-driven manner. Our proposed framework consists of two essential steps: establishing a correlation between IL viscosity and CO₂ solubility by merging two deep learning models (DNN-GC and ANN-GC) and utilizing this correlation to identify the optimal IL structure with maximal CO₂ absorption capacity. …”

Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends by Abdellatif M. Sadeq (16931841)

“…<p dir="ltr">Studying the spatial and temporal evolution in turbulent flames represents one of the most challenging problems in the combustion community. Based on previous 3D numerical analyses, this study aims to develop data-driven machine learning (ML) models for predicting the flame radius evolution and turbulent flame speeds for diesel, gas-to-liquids (GTL), and their 50/50 blend (by volumetric composition) under different thermodynamic and turbulence operating conditions. …”

Intelligent Bilateral Client Selection in Federated Learning Using Game Theory by Wehbi, Osama

“…Based on our simulation findings, our strategy surpasses the VanillaF selection approach in terms of maximizing both the revenues of the client devices and accuracy of the global federated learning model.…”
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