A Comprehensive Review of Machine Learning Applications for Internet of Nano Things: Challenges and Future Directions

Academic Background In recent years, the rapid development of nanotechnology and the Internet of Things (IoT) has given rise to a revolutionary field—the Internet of Nano Things (IoNT). The IoNT connects nanoscale devices to the internet, enabling them to play significant roles in areas such as agriculture, military, multimedia, and healthcare. How...

Speech Emotion Recognition in Conversations Using Artificial Intelligence: A Systematic Review and Meta-Analysis

Academic Background Emotion Recognition is an important research direction in the fields of Artificial Intelligence (AI) and Affective Computing, with broad application prospects in areas such as healthcare, education, and Human-Computer Interaction (HCI). Speech, as a significant carrier of emotional expression, can convey rich emotional informati...

Challenges in Detecting Security Threats in WoT: A Systematic Literature Review

With the rapid development of the Internet of Things (IoT) and Web of Things (WoT), security issues have become increasingly prominent. In particular, the frequent occurrence of Denial of Service (DoS) attacks has made the security of WoT systems an urgent problem to be addressed. WoT achieves seamless connectivity between IoT devices and the inter...

Analyzing Content of Paris Climate Pledges with Computational Linguistics

The Paris Agreement is a crucial framework for global climate action, with countries outlining their climate goals and strategies through Nationally Determined Contributions (NDCs). While existing research has primarily focused on assessing the mitigation targets within NDCs, the broader textual content of these documents has received little system...

Online Signature Watermarking in the Transform Domain

Academic Background With the rapid growth of digital content, the importance of digital signatures in identity verification and content authentication has become increasingly prominent. However, the security and integrity of digital signatures face significant challenges. To protect the authenticity of signatures and prevent tampering, digital wate...

A Communication-Efficient Distributed Frank-Wolfe Online Algorithm with an Event-Triggered Mechanism

Academic Background In the era of big data, distributed learning has become an effective method for solving large-scale online machine learning problems. However, frequent communication and projection operations in distributed learning incur high communication and computational costs. Especially in high-dimensional constrained optimization problems...