Browsing Electrical Engineering by Subject "Learning systems"
Now showing items 1-15 of 15
-
A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications
( Academic Press , 2021 , Article Review)Monitoring structural damage is extremely important for sustaining and preserving the service life of civil structures. While successful monitoring provides resolute and staunch information on the health, serviceability, ... -
Advance Warning Methodologies for COVID-19 Using Chest X-Ray Images
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Coronavirus disease 2019 (COVID-19) has rapidly become a global health concern after its first known detection in December 2019. As a result, accurate and reliable advance warning system for the early diagnosis of COVID-19 ... -
An Agreement Based Dynamic Routing Method for Fault Diagnosis in Power Network with Enhanced Noise Immunity
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Conference Paper)The stable operation of a power system often depends on inscribing the faults that may arise when transmitting and distributing electrical power. Characterizing these faults is necessary to analyze the post-fault oscillography ... -
Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case study
( Elsevier B.V. , 2016 , Article)Time-frequency (TF) based machine learning methodologies can improve the design of classification systems for non-stationary signals. Using selected TF distributions (TFDs), TF feature extraction is performed on multi-channel ... -
Cybersecurity for industrial control systems: A survey
( Elsevier Ltd , 2020 , Article Review)Industrial Control System (ICS) is a general term that includes supervisory control & data acquisition (SCADA) systems, distributed control systems (DCS), and other control system configurations such as programmable logic ... -
Deep Learning for RF-Based Drone Detection and Identification: A Multi-Channel 1-D Convolutional Neural Networks Approach
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)Commercial unmanned aerial vehicles, or drones, are getting increasingly popular in the last few years. The fact that these drones are highly accessible to public may bring a range of security and technical issues to ... -
Efficiency validation of one dimensional convolutional neural networks for structural damage detection using a SHM benchmark data
( International Institute of Acoustics and Vibration, IIAV , 2018 , Conference Paper)In this paper, a novel one dimensional convolution neural network (1D-CNN) based structural damage assessment technique is validated with a benchmark study published by IASC-ASCE Structural Health Monitoring Task Group in ... -
Exploiting heterogeneity in operational neural networks by synaptic plasticity
( Springer Science and Business Media Deutschland GmbH , 2021 , Article)The recently proposed network model, Operational Neural Networks (ONNs), can generalize the conventional Convolutional Neural Networks (CNNs) that are homogenous only with a linear neuron model. As a heterogenous network ... -
Heterogeneous Multilayer Generalized Operational Perceptron
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)The traditional multilayer perceptron (MLP) using a McCulloch-Pitts neuron model is inherently limited to a set of neuronal activities, i.e., linear weighted sum followed by nonlinear thresholding step. Previously, generalized ... -
Human experts vs. machines in taxa recognition
( Elsevier B.V. , 2020 , Article)The step of expert taxa recognition currently slows down the response time of many bioassessments. Shifting to quicker and cheaper state-of-the-art machine learning approaches is still met with expert scepticism towards ... -
Information sharing in cooperative networks: A generic trustworthy issue
( Institute of Electrical and Electronics Engineers Inc. , 2016 , Conference Paper)In a cooperative network, users share information with each other to achieve a common target. Due to the concerns of privacy and cost, users may be reluctant to share genuine information with each other, which incurs the ... -
Long-term performance analysis and power prediction of PV technology in the State of Qatar
( Elsevier Ltd , 2017 , Article)?Solar photovoltaic (PV) energy in GCC?- the term seems convincing to many solar PV industries due to high solar exposure in GCC region. However, long-term effects such as dust accumulation and seasonal variation are major ... -
Machine learning-based management of electric vehicles charging: Towards highly-dispersed fast chargers
( MDPI AG , 2020 , Article)Coordinated charging of electric vehicles (EVs) improves the overall efficiency of the power grid as it avoids distribution system overloads, increases power quality, and decreases voltage fluctuations. Moreover, the ... -
Operational neural networks
( Springer , 2020 , Article)Feed-forward, fully connected artificial neural networks or the so-called multi-layer perceptrons are well-known universal approximators. However, their learning performance varies significantly depending on the function ... -
Real-time throughput prediction for cognitive Wi-Fi networks
( Academic Press , 2020 , Article)Wi-Fi as a wireless networking technology has become a widely acceptable commonplace. Over the course of time, the applications landscape of Wi-Fi networks is growing tremendously. The proliferation of new services is ...