Abstract: Electric bicycles (e-bikes) are playing increasingly important roles in satisfying people's personal mobility and short trips in an eco-friendly (reducing carbon dioxide emission) and ...
Abstract: This article presents a novel wavelength modulation spectroscopy gas concentration detection approach based on linear convolution (LC-WMS). The linear convolution (LC) is first time utilized ...
Linear algebra is essential for understanding core data science concepts like machine learning, neural networks, and data transformations. Different books cater to various needs. Some focus on ...
Predicting the response of cell lines to characteristic drugs based on multi-omics gene information has become the core problem of precision oncology. At present, drug response prediction using ...
ABSTRACT: The development of new technologies in smart cities is often hailed as it becomes a necessity to solve many problems like energy consumption and transportation. Wireless networks are part of ...
We propose a direct domain adaptation (DDA) approach to enrich the training of supervised neural networks on synthetic data by features from real-world data. The process involves a series of linear ...
CoAtNets combines convolutional and attention models to enhance performance in deep learning tasks. This hybrid model has demonstrated state-of-the-art results in image classification, particularly on ...
Chromosomes are compactly folded in nuclei, and their specific 3D structures play a role in the regulation of gene expression. While cell type specificity of gene regulation has been revealed through ...
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