On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

“…Next, due to the NP-hardness of the problem, an enhanced Genetic Algorithm (GA)-based metaheuristic with efficient problem-specific improvement rules as local search and effective crossover and mutation operators is proposed. …”

A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

“…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”

AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients by Azar, Danielle

“…However, keeping track of the data for this purpose is overwhelming. …”
Get full text
Get full text

Assessing Factors Influencing Customers’ Adoption of AI-Based Voice Assistants by Surbhi Choudhary (21633701)

“…It also provides implications for tech-managers and algorithm designers to build effective voice technology for superior user experience.…”

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

“…The analytical model is derived based on the Euler-Bernoulli model. The Optimal location of the collocated sensor-actuator, as well as PID controller gains, are determined using Ant Colony Optimization (ACO) technique, then compared with the Genetic Algorithm (GA) and enumerative method (EM). …”

Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Alg... by Ali S. Alghamdi (12722891)

“…In this paper, the scheduling and management framework of an energy hub (EH) is presented with the aim of energy profit maximization in partnership with electricity, natural gas, and district heating networks (EGHNs) considering the coordinated multi-energy management based on the day-ahead market. The optimum capacity of EH equipment, including photovoltaic and wind renewable energy sources, a combined heat and power system (CHP), a boiler, energy storage, and electric vehicles is determined in the day-ahead market using the improved Fick’s law algorithm (IFLA), considering the energy profit maximization and also satisfying the linear network and hub constraints. …”

Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

Get full text
Get full text

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

Get full text

A heuristics for HTTP traffic identification in measuring user dissimilarity by Adeyemi R. Ikuesan (14157123)

“…The study utilizes HTTP request method of GET filtering, to develop a heuristic algorithm to identify user-initiated requests. The algorithm was experimentally tested on a group of users, to ascertain the certainty of identifying user-initiated requests. …”

A 3-D vision-based man-machine interface for hand-controlled telerobot by Al-Mouhamed, M.A.

“…To determine the three-dimensional (3-D) position a tracking algorithm based on uncalibrated cameras with weak perspective projection model is used. …”
Get full text
Get full text

Secrecy Performance of Decode-and-Forward Based Hybrid RF/VLC Relaying Systems by Jaber Al-Khori (16855470)

“…We develop physical layer security algorithms that mitigate eavesdropping on both RF and VLC networks based on zero-forcing beamforming techniques. …”

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

Get full text

A simulated annealing-based optimal controller for a three phase induction motor by Mantawy, A.H.

“…This paper presents a new approach for optimal controller design of a three-phase induction motor (IM), based on using the simulated annealing (SA) method to find the optimal controller gains that satisfy a specific performance criterion. …”
Get full text
Get full text

Proactive machine learning-based solution for advanced manageability of multi-persona mobile computing by Tout, Hanine

Get full text
Get full text
Get full text
Get full text

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. …”

Tensile Test Optimization Using the Design of Experiment and Soft Computing by Mehdi Moayyedian (14880358)

“…This study employs a hybrid soft computing approach, integrating an adaptive network-based fuzzy inference system (ANFIS), genetic algorithm (GA) optimization, and design of experiments (DOE). …”

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

“…ML based informal diagnostic and decision support systems can provide a first line of detection to alert patients about potential disease risk. …”
Get full text

Nonlinear Control of Brushless Dual-Fed Induction Generator With a Flywheel Energy Storage System for Improved System Performance by Mohammed Hamidat (3722086)

“…In the first stage, a robust Sliding Mode Control (SMC)-based nonlinear decoupled control algorithm is designed to efficiently regulate BDFIG operation. …”

Correlation Clustering with Overlaps by Fakhereldine, Amin

“…In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …”
Get full text
Get full text
Get full text

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

“…<p dir="ltr">In this article, we present a novel deep learning-based group contribution framework for the targeted design of ionic liquids (ILs). …”