Motor imagery (MI) brain-computer interface (BCI) paradigms have been extensively used in neurological rehabilitation. However, due to the required long calibration time and non-stationary nature of electroencephalogram (EEG) signals, it is ...

Vehicular Crowdsensing System (VCS) has emerged as a promising paradigm for alleviating traffic congestion and improving driving safety due to its convenient collection and aggregation of various driving and traffic-related reports. However, the ...

Android mobile phones have the highest market share nowadays, bringing a boom of Android application programming as well as malicious software (malware) issues. Traditional machine learning and deep learning methods are widely used in Android ...

The internet, including social networking sites, has become a major source of health information for laypersons. Yet, the internet has also become a platform for spreading misinformation that challenges adults’ ability to critically evaluate the ...

• We explored how adults evaluated the credibility of health-related social media posts.
• Posts varied in terms of claim accuracy, evidence type, and source characteristics.
• Source expertise and prior belief consistency affected ...

This paper focuses on constructing a graph neural network deep learning model to analyse malicious Web requests and make timely warnings, in addition to generating adversarial samples for graph data structures through PGD topology attacks, conducting ...

People commonly turn to the Internet and social media for their information needs. Most popular social media platforms focus on short-form content that can be consumed rapidly. Given how fast such content spreads online, its trustworthiness and ...

Network anomaly traffic detection is an important technique for detecting intrusion activities and maintaining cyberspace security. Random forest is widely used in network anomalous traffic detection due to its good detection performance. However, ...

Social media is now an important source of everyday information. Given the plethora of scandals concerning the rapid spread of misinformation and disinformation on social media, the credibility of the content on these platforms is now a pivotal research ...

Developing efficient raw material ordering and transshipment strategies for companies with uncertain supply has attracted extensive interests from both academic and industrial researchers. Some methods have been proposed, such as obtaining a ...

Federated learning has become an emerging technology to protect data privacy in the distributed learning area, by keeping each client user’s data locally. However, recent work shows that client users’ data might still be stolen (or reconstructed) ...

• A new welding technology is proposed, which introduces the trailing ultrasonic vibration into the conventional laser welding process.

A trailing ultrasonic-assisted laser welding (T-ULW) technology is first proposed to weld SUS301 stainless steel sheet with a thickness of 0.6 mm. Secondly, welding experiments with conventional laser welding and ultrasonic-assisted ...

The identification of gene regulatory networks (GRN) from gene expression time series data is a challenge and open problem in system biology. This paper considers the structure inference of GRN from the incomplete and noisy gene expression data, which is ...

Nowadays corporate Intranet Security Monitoring generally relies on SIEM products or SOC platforms. The data comes from a large number of system logs, application running logs and business data, which are generated by network device, security ...

Re-configurable modular robot systems are advantageous for their scalability and versatility. However, creating kinematic models for every new assembly is a time-consuming and error-prone task. In this paper, a vision-based kinematic configuration ...

Usually long documents contain many sections and segments. In Wikipedia, one article can usually be divided into sections and one section can be divided into segments. But although one article is already divided into smaller segments, one segment ...

This paper proposes an effective spatiotemporal saliency model for unconstrained videos with complicated motion and complex scenes. First, superpixel-level motion and color histograms as well as global motion histogram are extracted as the features for ...

Graph partitioning is important in distributed graph processing. Classical method such as METIS works well on relatively small graphs, but hard to scale for huge, dynamic graphs. Streaming graph partitioning algorithms overcome this issue by processing ...