The issue of signal outages in sub-THz frequency communication for future 6G networks is addressed by this research. A machine learning method is proposed, employing Random Forest and K-Means algorithms to predict the...
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Wind power generation is one of the most widely used distributed renewable energy sources. The diagnosis and monitoring of wind power system is one of the important means to ensure its power supply reliability. Since ...
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Feature selection is the most significant pre-processing activity, which intends to reduce the data dimensionality for enhancing the machine learning process. The evaluation of feature selection must consider classifi...
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In the Internet of Things (IoT) epoch, the seamless communication of smart devices through autonomous collaboration demands real-time IoT networks to possess a high level of intelligence. However, the resource-constra...
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A robust controller for an LCL-filtered grid-connected inverter (GCI) is presented in this article in the context of the system model uncertainties and nonideal grid environment. Under the occurrence of exogenous inpu...
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This paper introduces an innovative and efficient multi-scale Vision Transformer (ViT) for the task of image classification. The proposed model leverages the inherent power of transformer architecture and combines it ...
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A new, improved computer program made specifically for banking helps in solving problems like inadequate guidance and makes it convenient for people who cannot visit banks for some reason. This helps people answer que...
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The retail industry has undergone a rapid transformation in recent years, owing to technological advancements and the availability of massive amounts of data. In this context, predictive analytics is critical in assis...
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Line segment detection plays a cornerstone role in computer vision tasks. Among numerous detection methods that have been recently proposed, the ones based on edge drawing attract increasing attention owing to their e...
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This study aims at unlocking the integration of clinical and imaging data using the deep learning model for enhancing the diagnosis of oral cancer cases. Therefore, for image analysis, in this paper proposed to major ...
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