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Application of data-driven attack detection framework for secure operation in smart buildings
(
Elsevier Ltd
, 2021 , Article)
With the rapid advancement in the industrial control technologies and the increased deployment of the industrial Internet of Things (IoT) in the buildings sector, this work presents an analysis of the security of the ...
Novel Actuator Fault Diagnosis Framework for Multizone HVAC Systems Using 2-D Convolutional Neural Networks
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Heating, ventilation, and air conditioning (HVAC) systems are used to condition the indoor environment in buildings. They can be subjected to malfunctioning since they are the most extensively operated buildings' components ...
Actuator Fault Diagnosis in Multi-Zone HVAC Systems using 2D Convolutional Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
This paper presents a novel supervised on-line fault diagnosis strategy in Heating, Ventilation, and Air conditioning (HVAC) systems for actuator faults using 2D Convolutional Neural Networks. It is based on an efficient ...
Hybrid attack detection framework for industrial control systems using 1D-convolutional neural network and isolation forest
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Industrial control systems (ICSs) are used in various infrastructures and industrial plants for realizing their control operation and ensuring their safety. Concerns about the cybersecurity of industrial control systems ...
Deep Learning for RF-Based Drone Detection and Identification: A Multi-Channel 1-D Convolutional Neural Networks Approach
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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 ...
A Deep Learning Model for LoRa Signals Classification Using Cyclostationay Features
(
IEEE Computer Society
, 2021 , Conference Paper)
With the witnessed exponential growth of Internet of Things (IoT) nodes deployment following the emerging applications, multiple variants of technologies have been proposed to handle the IoT requirements. Among the proposed ...
Early Bearing Fault Diagnosis of Rotating Machinery by 1D Self-Organized Operational Neural Networks
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Preventive maintenance of modern electric rotating machinery (RM) is critical for ensuring reliable operation, preventing unpredicted breakdowns and avoiding costly repairs. Recently many studies investigated machine ...
Self-organized Operational Neural Networks with Generative Neurons
(
Elsevier Ltd
, 2021 , Article)
Operational Neural Networks (ONNs) have recently been proposed to address the well-known limitations and drawbacks of conventional Convolutional Neural Networks (CNNs) such as network homogeneity with the sole linear neuron ...
Real-time phonocardiogram anomaly detection by adaptive 1D Convolutional Neural Networks
(
Elsevier B.V.
, 2020 , Article)
The heart sound signals (Phonocardiogram ? PCG) enable the earliest monitoring to detect a potential cardiovascular pathology and have recently become a crucial tool as a diagnostic test in outpatient monitoring to assess ...
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 ...