Deep learning models are pivotal in the advancements of Artificial Intelligence (AI) due to rapid learning and decision-making across various fields such as healthcare, finance, and technology. However, a harmful utilization of deep learning models poses a threat to public welfare, national security...

To meet latency constraints, fog computing takes computational assets to the network edge. Blockchain and reinforcement learning are increasingly being integrated into the Industrial Internet of Things (IIoT) to enhance security and efficiency. This study introduces a Reinforcement Learning-based Re...

This research proposes an advanced system for landmine detection combining the internet of things and reinforcement learning, which seeks to resolve issues in conventional methods that suffer from high false positive rates, slow reaction times, and poor adaptability across different environmental co...

To address the issues of low accuracy in manual observation and slow detection by radar in airport bird detection, this paper designs a lightweight bird detection network named MFE-YOLO. This network is based on the YOLOv8 framework, with the main body part featuring an MF module replacing the origi...

Electrochemistry plays a vital role in the sustainable development plans over the world due to its direct relation into many research and production directions such as energy, environment, and industry.

Traditional centralized machine learning approaches for IoT botnet detection pose significant privacy risks, as they require transmitting sensitive device data to a central server. This study presents a privacy-preserving Federated Learning (FL) approach that employs Federated Averaging (FedAvg) to...

As the Editor-in-Chief of this pioneering journal, it is with immense enthusiasm that a journey is embarked upon to explore the confluence of chemical engineering and renewable fuels. This journal aims to serve as a nexus for groundbreaking research, innovative methodologies, and transformative disc...

Abnormal fluctuations in financial markets may signal significant risks or market manipulation, so efficient time series anomaly detection methods are crucial for risk management. However, traditional statistical methods (e.g., ARIMA, GARCH) are difficult to adapt to the nonlinear and multi-scale ch...

In the field of natural language processing, Named entity recognition (NER) is a essential task. Mathematical formulas usually contain a large number of terminologies, units of measure and other proprietary knowledge, and the integration of this information into the knowledge graph can significantly...

Usage of nanomaterials in the wastewater treatment provides added value from the perspective of preparation and market perspectives, adding to the demand for sustainable and intelligent packaging solutions, resulting in a market interest in smart and active packaging based on the modification of na...