Abstract: Recently, it was shown that a dual- or triple-band patch antenna can be designed by cutting U-slots in the patch of a broadband antenna, and the method was applied to the L-probe fed patch, ...
Abstract: The surge in global population is compelling a shift toward smart agriculture practices. This coupled with the diminishing natural resources, limited availability of arable land, increase in ...
Abstract: In this paper, we present a patch-based land use and land cover classification approach using Sentinel-2 satellite images. The Sentinel-2 satellite images are openly and freely accessible, ...
Abstract: Infrared small target detection plays an important role in military and civilian fields while it is difficult to be solved by deep learning (DL) technologies due to scarcity of data and ...
Abstract: In this paper, a partial tracking error constrained fuzzy output-feedback dynamic surface control (DSC) scheme is proposed for a class of uncertain multi ...
Abstract: Instructions for conducting generally applicable and accepted tests to determine the performance characteristics of synchronous machines are contained in this guide. Although the tests ...
Abstract: When, in 1956, Artificial Intelligence (AI) was officially declared a research field, no one would have ever predicted the huge influence and impact its description, prediction, and ...
Abstract: The low-energy proton energy spectra of all shielded space environments have the same shape. This shape is easily reproduced in the laboratory by degrading a high-energy proton beam, ...
Abstract: The linearization of a power flow (PF) model is an important approach for simplifying and accelerating the calculation of a power system's control, operation, and optimization. Traditional ...
Abstract: Federated Learning (FL) is a collaborative machine learning (ML) framework that combines on-device training and server-based aggregation to train a common ML model among distributed agents.
Abstract: This paper considers cooperative kinematic control of multiple manipulators using distributed recurrent neural networks and provides a tractable way to extend existing results on individual ...
Abstract: The detection, diagnostic, and prognostic of bearing degradation play a key role in increasing the reliability and safety of electrical machines, especially in key industrial sectors. This ...