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 ...

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...

Abstract: With the rapid development of generative large-language models, the text they generate is becoming increasingly difficult to distinguish from human-written text, creating an urgent need for ...

The stroke deprives person's brain of oxygen and nutrients, which can cause brain cells to die. Numerous works have been carried out for predicting various diseases by comparing the performance of ...

Abstract: Quantum computing has the capability to efficiently solve complex problems that would require significantly longer processing times on classical computing systems. This study investigates ...

ABSTRACT: In the field of machine learning, support vector machine (SVM) is popular for its powerful performance in classification tasks. However, this method could be adversely affected by data ...

In the era of big data and artificial intelligence, machine learning is one of the hot issues in the field of credit rating. On the basis of combing the literature on credit rating methods at home and ...

Learn how to use vector databases for AI SEO and enhance your content strategy. Find the closest semantic similarity for your target query with efficient vector embeddings. A vector database is a ...

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...