Neural networks : the official journal of the International Neural Network Society
Feb 15, 2025
This paper proposes an explainable abstraction-based verification method that prioritizes user interaction and enhances interpretability. By partitioning the system's state space using a data-driven process, we can abstract the dynamics into words co...
Scientific reports
Jan 2, 2025
Smart wearable devices detection and recording of people's everyday activities is critical for health monitoring, helping persons with disabilities, and providing care for the elderly. Most of the research that is being conducted uses a machine learn...
Neural networks : the official journal of the International Neural Network Society
Nov 29, 2024
Social media platforms, rich in user-generated content, offer a unique perspective on public opinion, making stance detection an essential task in opinion mining. However, traditional deep neural networks for stance detection often suffer from limita...
Gastroenterologia y hepatologia
Jun 7, 2024
The development of machine learning (ML) tools in many different medical settings is largely increasing. However, the use of the resulting algorithms in daily medical practice is still an unsolved challenge. We propose an epistemological approach (i....
Food chemistry
May 30, 2024
The overuse and misuse of tetracycline (TCs) antibiotics, including tetracycline (TTC), oxytetracycline (OTC), doxycycline (DC), and chlortetracycline (CTC), pose a serious threat to human health. However, current rapid sensing platforms for tetracyc...
PloS one
Mar 27, 2024
The modeling of uncertain information is an open problem in ontology research and is a theoretical obstacle to creating a truly semantic web. Currently, ontologies often do not model uncertainty, so stochastic subject matter must either be normalized...
Proceedings of the National Academy of Sciences of the United States of America
Oct 5, 2023
Machine learning methods, particularly neural networks trained on large datasets, are transforming how scientists approach scientific discovery and experimental design. However, current state-of-the-art neural networks are limited by their uninterpre...
Neural networks : the official journal of the International Neural Network Society
Jul 3, 2023
Under the framework of a hybrid-index model, this paper investigates safe control problems of state-dependent random impulsive logical control networks (RILCNs) on both finite and infinite horizons, respectively. By using the ΞΎ-domain method and the ...
Brain structure & function
Jun 23, 2023
Foundational models such as ChatGPT critically depend on vast data scales the internet uniquely enables. This implies exposure to material varying widely in logical sense, factual fidelity, moral value, and even legal status. Whereas data scaling is ...
Neural networks : the official journal of the International Neural Network Society
Apr 26, 2023
Event temporal relation extraction is an important task for information extraction. The existing methods usually rely on feature engineering and require post-process to achieve optimization, though inconsistent optimization may occur in the post-proc...