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Name: Western OC2 Lab

Type: Organization

Bio: The Optimized Computing and Communications (OC2) Laboratory within the Department of Electrical and Computer Engineering at Western University, London, Canada.

Location: Canada

Blog: https://www.eng.uwo.ca/oc2/

Western OC2 Lab's Projects

corrfl icon corrfl

This repository includes the code used in the paper titled "CorrFL: Correlation-based Neural Network Architecture for Unavailability Concerns in a Heterogeneous IoT Environment"

fl-iov-its icon fl-iov-its

Code for the case study presented in "Making a Case for Federated Learning in the Internet of Vehicles and Intelligent Transportation Systems" accepted for publication in the IEEE Network Magazine May 2021 Special Issue on AI-empowered Mobile Edge Computing in the Internet of Vehicles.

hierarchical-co2 icon hierarchical-co2

This is a repository that includes the code used in the paper titled "Hierarchical Modelling for CO2 Variation Prediction for HVAC System Operation"

intelligentaqm icon intelligentaqm

Intelligent method to be used with AQM schemes such as CoDel and FQ-CoDel

msana-online-data-stream-analytics-and-concept-drift-adaptation icon msana-online-data-stream-analytics-and-concept-drift-adaptation

Data stream analytics: Implement online learning methods to address concept drift and model drift in dynamic data streams. Code for the paper entitled "A Multi-Stage Automated Online Network Data Stream Analytics Framework for IIoT Systems" published in IEEE Transactions on Industrial Informatics.

oasw-concept-drift-detection-and-adaptation icon oasw-concept-drift-detection-and-adaptation

An online learning method used to address concept drift and model drift. Code for the paper entitled "A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streams" published in IEEE Internet of Things Magazine.

pwpae-concept-drift-detection-and-adaptation icon pwpae-concept-drift-detection-and-adaptation

Data stream analytics: Implement online learning methods to address concept drift and model drift in data streams using the River library. Code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streams" published in IEEE GlobeCom 2021.

signal-processing-for-machine-learning icon signal-processing-for-machine-learning

This repository serves as a platform for posting a diverse collection of Python codes for signal processing, facilitating various operations within a typical signal processing pipeline (pre-processing, processing, and application).

similarity-based-predictive-maintenance-framework-for-rotating-machinery icon similarity-based-predictive-maintenance-framework-for-rotating-machinery

Python code “Jupyter notebooks” for the paper entitled " Similarity-Based Predictive Maintenance Framework for Rotating Machinery" has been presented in the Fifth International Conference on Communications, Signal Processing, and their Applications (ICCSPA’22), Cairo, Egypt, 27-29 December 2022. Techniques used: statistical analysis, FFT, and STFT.

tinyml_evci icon tinyml_evci

This repository contains code for comparing traditional Machine Learning (ML) and Tiny Machine Learning (TinyML) in terms of time, memory usage, and performance, specifically in the context of electric vehicle charging infrastructure. It also offers practical insights by implementing TinyML on the ESP32 microcontroller.

vibration-based-fault-diagnosis-with-low-delay icon vibration-based-fault-diagnosis-with-low-delay

Python codes “Jupyter notebooks” for the paper entitled "A Hybrid Method for Condition Monitoring and Fault Diagnosis of Rolling Bearings With Low System Delay, IEEE Trans. on Instrumentation and Measurement, Aug. 2022. Techniques used: Wavelet Packet Transform (WPT) & Fast Fourier Transform (FFT). Application: vibration-based fault diagnosis.

zero-touch-network-and-automl-case-study icon zero-touch-network-and-automl-case-study

This repository includes code for the AutoML-based case study for zero-touch networks presented in the paper "Zero-touch networks: Towards next-generation network automation" published in Computer Networks (IF:5.6).

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