Left Ventricular Wall Motion Estimation by Active Polynomials for Acute Myocardial Infarction Detection by Serkan Kiranyaz (3762058)

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

“…The developed model successfully identified stress instances using IBI-BVP spatial domain images with an average accuracy of 98.10% with a convolutional neural network (CNN) and 99.18% using the average pixel intensity of these images with the extra trees classifier. …”

Video Streaming over D2D Networks by Ahmed, Ibtihal Mohamed Taha

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Spatiotemporal Mapping and Monitoring of Mangrove Forests Changes From 1990 to 2019 in the Northern Emirates, UAE Using Random Forest, Kernel Logistic Regression and Naive Bayes Tr... by Elmahdy, Samy

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ThoraX-PriorNet: A Novel Attention-Based Architecture Using Anatomical Prior Probability Maps for Thoracic Disease Classification by Md. Iqbal Hossain (723299)

Impact Of Multidisciplinary Maternal Resuscitation Training Program on Improving the Front-Line Care Provider’s Readiness to Manage Maternal Cardiac Arrest: A Pre-test/Post-test St... by Mohamed Elsayed Saad Aboudonya (18466385)

“…The multidisciplinary resuscitation teams were observed during the cardiac arrest mock drills both before and after conducting the multidisciplinary resuscitation simulation-based training program and the introduction of the maternal resuscitation algorithm pathway against seven KPIs. Those KPIs were Time to Confirm Cardiac Arrest; Code Blue and /or Code White Activation Time; Time to attempt first chest compression; Defibrillator Arrival Time; Time to First Defibrillation shock; Code blue/code white arrival time and Time to perform Perimortem Caesarean Delivery.…”

Computation of conformal invariants by Mohamed M.S., Nasser

“…In particular, we provide an algorithm for computing the conformal capacity of a condenser. …”
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Computation of conformal invariants by Mohamed M.S. Nasser (16931772)

“…In particular, we provide an algorithm for computing the conformal capacity of a condenser. …”

Analysis of Using Machine Learning to Enhance the Efficiency of Facilities Management in the UAE by ULLAH, SAAD

“…This study addresses these issues by Implementing Machine Learning (ML) algorithms using data from Building Management Systems (BMS) and FM maintenance reports, focussing on predictive maintenance for Fresh Air Handling Units. …”
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Development of a cerebral aneurysm segmentation method to prevent sentinel hemorrhage by Yousra Regaya (17788964)

“…Here, we present a method combining a multiresolution and a statistical approach in two dimensional domain to segment cerebral aneurysm in which the Contourlet transform (CT) extracts the image features, while the Hidden Markov Random Field with Expectation Maximization (HMRF-EM) segments the image, based on the spatial contextual constraints. The proposed algorithm is tested on Three-Dimensional Rotational Angiography (3DRA) datasets; the average values of segmentation accuracy, DSC, FPR, FNR, specificity, and sensitivity, are found to be 99.72%, 93.52%, 0.07%, 5.23%, 94.77%, and 99.96%, respectively.…”

A smart decentralized identifiable distributed ledger technology‐based blockchain (DIDLT‐BC) model for cloud‐IoT security by Shitharth Selvarajan (14157976)

“…The novel contribution of this work is to incorporate the operations of Rabin digital data signature generation, DIDLT‐based blockchain construction, and BCA algorithms for ensuring overall data security in IoT networks. …”

Downlink channel estimation for IMT-DS by Faisal, S.

“…IMT-DS system is an approved terrestrial radio interface standard for 3G mobile communication based on direct sequence code division multiple access (DS-CDMA). It employs a RAKE receiver to exploit multipath diversity. …”
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Net energy–cost optimization of STPV–PDRC integrated greenhouses: Balancing energy production and cooling demand under crop-specific DLI constraints by Mohammadreza Gholami (17032317)

“…An improved equilibrium optimizer (IEO) algorithm was employed to solve the multi-objective problem. …”

Dynamic multiple node failure recovery in distributed storage systems by Itani, May

“…In this work, we address the problem of multiple failure recovery with dynamic scenarios using the fractional repetition code as a redundancy scheme. The fractional repetition (FR) code is a class of regenerating codes that concatenates a maximum distance separable code (MDS) with an inner fractional repetition code where data is split into several blocks then replicated and multiple replicas of each block are stored on various system nodes. …”
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Generic metadata representation framework for social-based event detection, description, and linkage by Abebe, Minale A.

“…SEDDaL consists of four main modules for: i) describing social media objects in a generic Metadata Representation Space Model (MRSM) consisting of three composite dimensions: temporal, spatial, and semantic, ii) evaluating the similarity between social media objects’ descriptions following MRSM, iii) detecting events from similar social media objects using an adapted unsupervised learning algorithm, where events are represented as clusters of objects in MRSM, and iv) identifying directional, metric, and topological relationships between events following MRSM’s dimensions. …”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

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Enhanced DC Microgrid Protection: a Neural Network and Wavelet Transform Approach by El Gohary, Youssef Hesham

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Could Petrol Stations Play a Key Role in Transportation Electrification? A GIS-Based Coverage Maximization of Fast EV Chargers in Urban Environment by Safak Bayram (16925975)

“…The spatial optimization problem is solved using a linear-programming relaxation based MCLP algorithm developed in Python. …”

Phased Array Technique for Brain Source Localization by Zarghami, Tahereh

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Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

“…The proposed approach of DDN is trained with proper data sequences used for communication and the training phase is conducted with the norms of numerous channel variants. …”