Ensemble Deep Random Vector Functional Link Neural Network for Regression حسب Minghui Hu (2457952)

"…<p dir="ltr">Inspired by the ensemble strategy of machine learning, deep random vector functional link (dRVFL), and ensemble dRVFL (edRVFL) has shown state-of-the-art results on different datasets. …"

Defining quantitative rules for identifying influential researchers: Insights from mathematics domain حسب Ghulam Mustafa (458105)

Real-Time Smart-Digital Stethoscope System for Heart Diseases Monitoring حسب Muhammad E.H. Chowdhury (17151154)

Diabetic Sensorimotor Polyneuropathy Severity Classification Using Adaptive Neuro Fuzzy Inference System حسب Fahmida Haque (16896489)

"…The model accuracy was validated with the results from different machine learning algorithms. The Accuracy, sensitivity, and specificity of the ANFIS model are 91.17±1.18%, 92±2.26%, 96.72±0.93%, respectively. …"

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network حسب Sakib Mahmud (15302404)

"…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …"

Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks حسب Mohamed Massaoudi (16888710)

A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation حسب Khaled Dhibi (16891524)

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... حسب 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 حسب Mohamed M.S., Nasser

"…In particular, we provide an algorithm for computing the conformal capacity of a condenser. …"
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Communications in electronic textile systems حسب Nakad, Z.

"…Abstract- Electronic textiles (e-textiles) are emerging as a novel method for constructing electronic systems in wearable and large area applications. …"
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Systematic reviews in sentiment analysis: a tertiary study حسب Alexander Ligthart (14150871)

"…In addition to the tertiary study, we also identified recent 112 deep learning-based sentiment analysis papers and categorized them based on the applied deep learning algorithms. …"

Computation of conformal invariants حسب Mohamed M.S. Nasser (16931772)

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

Multidimensional Gains for Stochastic Approximation حسب Saab, Samer S.

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A smart decentralized identifiable distributed ledger technology‐based blockchain (DIDLT‐BC) model for cloud‐IoT security حسب 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 حسب 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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Dynamic multiple node failure recovery in distributed storage systems حسب 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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Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks حسب Jafari, Reza

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Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network حسب Monzure-Khoda Kazi (17191207)

"…<p dir="ltr">This research aims to enhance the safety level and crash resiliency of targeted woven roving glass/epoxy composite material for various industry 4.0 applications. Advanced machine learning algorithms are used in this study to figure out the complicated relationship between the crashworthiness parameters of the hexagonal composite ring specimens under lateral compressive, energy absorption, and failure modes. …"

Building power consumption datasets: Survey, taxonomy and future directions حسب Yassine Himeur (14158821)

"…Accordingly, a novel visualization strategy based on using power consumption micro-moments has been presented along with an example of deploying machine learning algorithms to classify the micro-moment classes and identify anomalous power usage.…"

Predicting Android Malware Using Evolution Networks حسب Chahine, Joy

"…With this aim, we introduce evolutionary networks, and particularly the Susceptible-Infectious-Susceptible (SIS) model, as a way to address the limitations of previous studies which are typically based on traditional machine learning models. The SIS model is usually used to represent disease spread between individuals in a population with transition between susceptible and infected states. …"
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