A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral analysis and SVM classification, the approach improves ...

Introduction: The rapid and accurate identification of natural and non-natural seismic events is crucial for compiling comprehensive earthquake catalogs and assessing regional seismic risk. Methods: ...

Traditional machine learning algorithms for classification tasks operate under the assumption of balanced class distributions. However, this assumption only holds in some practical scenarios. In most ...

Microsoft has added official Python support to Aspire 13, expanding the platform beyond .NET and JavaScript for building and running distributed apps. Documented today in a Microsoft DevBlogs post, ...

Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

Abstract: Support Vector Machine (SVM), a robust machine learning algorithm, exhibits exceptional efficacy in addressing image multi-classification challenges. This paper aims to discuss the image ...

ABSTRACT: Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral ...

1 College of Rural Revitalization, Jiangsu Open University, Nanjing, China 2 Institute of Agricultural Resources and Environment, Jiangsu Academy of Agricultural Sciences, Nanjing, China Accurate ...