Biosensors and Biomarkers for the Detection of Motion Sickness

Exploring Biomarkers and Biosensors for Motion Sickness: Innovative Approaches to Diagnostic Challenges Motion sickness (MS) is a common syndrome experienced by humans, triggered by unnatural motions such as those encountered during transportation or virtual reality (VR). It manifests through symptoms like headaches, nausea, vomiting, cold sweats, ...

Silver Lining in the Fake News Cloud: Can Large Language Models Help Detect Misinformation?

Can Large Language Models Tackle Misinformation? — In-Depth Research on LLMs In today’s digital era of rapid information dissemination, the spread of misinformation and fake news has become a significant societal challenge. The widespread use of the internet and social media has dramatically lowered the barriers to information sharing, enabling any...

Sector-Based Pairs Trading Strategy with Novel Pair Selection Technique

In-Depth Exploration of Sector-Based Pairs Trading Strategies and Innovative Pair Selection Techniques Background and Research Objectives Pairs Trading Strategy (PTS) is a widely used financial arbitrage strategy that leverages the relative performance of two highly correlated stocks to profit from temporary price deviations. The core concept of tr...

Migrant Resettlement by Evolutionary Multiobjective Optimization

A Research Report on a New Framework for Solving Migrant Resettlement Using Multiobjective Evolutionary Optimization Against the backdrop of accelerated globalization and evolving socio-economic conditions, migration has become an undeniable global trend. From the perspective of humanitarian relief or the sustainable development of a globalized eco...

Reinforcement Learned Multiagent Cooperative Navigation in Hybrid Environment with Relational Graph Learning

Multi-agent Cooperative Navigation in Hybrid Environments: A New Reinforcement Learning Approach Based on Relational Graph Learning Mobile robotics is witnessing a surge in applications, fueled by advancements in artificial intelligence, with navigation capabilities being one of the core focus areas of research. Traditional navigation methods often...

An Intrusion Detection Approach for Industrial Internet of Things Traffic Using Deep Recurrent Reinforcement Learning and Federated Learning

Intrusion Detection Approach for Industrial Internet of Things Traffic Using Deep Recurrent Reinforcement Learning and Federated Learning Academic Background The rapid development of the Industrial Internet of Things (IIoT) has profoundly transformed intelligent industrial systems, enabling data exchange, remote control, and smart decision-making b...