Jun192021 by adminNo Comments
Article “Distributed Learning Applications in Power Systems: Methods, Gaps, and Challenges” has been published in MDPI Energies

Article “Distributed Learning Applications in Power Systems: Methods, Gaps, and Challenges” has been published in MDPI Energies

Articles
Article "Distributed Learning Applications in Power Systems: Methods, Gaps, and Challenges" has been published in MDPI Energies. Congratulations, Nastaran! Abstract: In recent years, machine learning methods have found numerous applications in power systems for load forecasting, voltage control, power quality monitoring, anomaly detection, etc. Distributed learning is a subfield of machine learning and a descendant of the multi-agent systems field. Distributed learning is a collaboratively decentralized machine learning algorithm designed to handle large data sizes, solve complex learning problems, and increase privacy. Moreover, it can reduce the risk of a single point of failure compared to fully centralized approaches and lower the bandwidth and central storage requirements. This paper introduces three existing distributed learning frameworks and reviews the applications that have been proposed for them in power systems so far.…
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May312021 by adminNo Comments

Article “Comparative Analysis of Machine Learning ‎Techniques for Temperature Compensation in ‎Microwave Sensors” was accepted for publication in IEEE Transactions on Microwave Theory and Techniques

Articles
Nazli's article "Comparative Analysis of Machine Learning ‎Techniques for Temperature Compensation in ‎Microwave Sensors" was accepted for publication in IEEE Transactions on Microwave Theory and Techniques. Congratulations! Abstract: The planar nature of microwave sensors leaves them vulnerable to ambient temperature changes with potential impact on the perception of the material under test. A temperature compensation technique is required to consider its direct effect on the dielectric property of materials. In this article, machine learning algorithms are employed in two configurations of classifier and regressor on frequency response of a split-ring resonator operating at 1.19 GHz. A wide range of dielectric constant is covered with concentrations of [0:20%:100%]-methanol/acetone in water with a temperature cycle of 25 °C-50 °C. This broad variety of cases captures the complicacy of entangled trends that are…
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Dec212020 by adminNo Comments
A Temperature-Compensated High-Resolution Microwave Sensor Using ANN

A Temperature-Compensated High-Resolution Microwave Sensor Using ANN

Articles
Nazli Kazemi, an ECE doctoral student, has published an article on her work titled 'A Temperature-Compensated High-Resolution Microwave Sensor Using Artificial Neural Network' with supervisor Petr Musilek in IEEE Microwave and Wireless Components Letters. In this study, they develop and train an artificial neural network (ANN) to model the behavior of the microwave sensor and to eliminate the uncertainty caused by uncontrolled temperature variations on the sensor response. You can access the article here: https://lnkd.in/ggBHG6w Nazli had originally started working on this project as an M.Sc. student under the guidance of Mojgan Daneshmand, before Mojgan's tragic and untimely passing in January this year. This article is dedicated to Mojgan's memory and her commitment to support and uplift women in STEM. An in memorium article about Mojgan and her family is available here: https://lnkd.in/gc83Kqi
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