Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting
Accurate and real-time traffic passenger flows forecasting at transportation hubs, such as
subway/bus stations, is a practical application and of great significance for urban traffic …
subway/bus stations, is a practical application and of great significance for urban traffic …
Exploiting blockchain data to detect smart ponzi schemes on ethereum
Blockchain technology becomes increasingly popular. It also attracts scams, for example, a
Ponzi scheme, a classic fraud, has been found making a notable amount of money on …
Ponzi scheme, a classic fraud, has been found making a notable amount of money on …
Spatio-temporal analysis of passenger travel patterns in massive smart card data
Metro systems have become one of the most important public transit services in cities. It is
important to understand individual metro passengers' spatio-temporal travel patterns. More …
important to understand individual metro passengers' spatio-temporal travel patterns. More …
Surveillance and intervention of infrastructure-free mobile communications: A new wireless security paradigm
Conventional wireless security assumes wireless communications are legitimate, and aims
to protect them against malicious eavesdrop** and jamming attacks. However, emerging …
to protect them against malicious eavesdrop** and jamming attacks. However, emerging …
Urban human mobility: Data-driven modeling and prediction
Human mobility is a multidisciplinary field of physics and computer science and has drawn a
lot of attentions in recent years. Some representative models and prediction approaches …
lot of attentions in recent years. Some representative models and prediction approaches …
Video-based fall detection using human pose and constrained generative adversarial network
Falls are a major health threat for older people. A timely assistance can reduce the extent of
physical injury caused by the falls. Currently, low-cost and convenient video surveillance …
physical injury caused by the falls. Currently, low-cost and convenient video surveillance …
Federated anomaly analytics for local model poisoning attack
The local model poisoning attack is an attack to manipulate the shared local models during
the process of distributed learning. Existing defense methods are passive in the sense that …
the process of distributed learning. Existing defense methods are passive in the sense that …
[PDF][PDF] Neural Network based Continuous Conditional Random Field for Fine-grained Crime Prediction.
Crime prediction has always been a crucial issue for public safety, and recent works have
shown the effectiveness of taking spatial correlation, such as region similarity or interaction …
shown the effectiveness of taking spatial correlation, such as region similarity or interaction …
Big data and emergency management: concepts, methodologies, and applications
Recent decades have seen a significant increase in the frequency, intensity, and impact of
natural disasters and other emergencies, forcing the governments around the world to make …
natural disasters and other emergencies, forcing the governments around the world to make …
Online deep ensemble learning for predicting citywide human mobility
Predicting citywide human mobility is critical to an effective management and regulation of
city governance, especially during a rare event (eg large event such as New Year's …
city governance, especially during a rare event (eg large event such as New Year's …