Locomotives are complex electromechanical systems. Continuously monitoring the health state of locomotives is critical in modern cost-effective maintenance strategy. A typical locomotive is equipped with the capability to monitor their state and generate fault messages and a snapshot of sensed parametric readings in response to anomalous conditions. In our previous studies, we have developed an...

mobile ad-hoc networks (manets) by contrast of other networks have more vulnerability because of having nature properties such as dynamic topology and no infrastructure. therefore, a considerable challenge for these networks, is a method expansion that to be able to specify anomalies with high accuracy at network dynamic topology alternation. in this paper, two methods proposed for dynamic anom...

The use of hyperspectral imaging is a fast growing field with many applications in the civilian, commercial and military sectors. Hyperspectral images are typically composed of many spectral bands in the visible and infrared regions of the electromagnetic spectrum and have the potential to deliver a great deal of information about a remotely sensed scene. One area of interest regarding hyperspe...

With the rapidly increasing demands from surveillance and security industries, crowd behaviour analysis has become one of the hotly pursued video event detection frontiers within the computer vision arena in recent years. This research has investigated innovative crowd behaviour detection approaches based on statistical crowd features extracted from video footages. In this paper, a new crowd vi...

A major focus of the commercial aviation community is discovery of unknown safety events in flight operations data. Data-driven unsupervised anomaly detection methods are better at capturing unknown safety events compared to rule-based methods which only look for known violations. However, not all statistical anomalies that are discovered by these unsupervised anomaly detection methods are oper...

Network traffic anomaly detection has become a popular research tendency, as it can detect new type attacks in real time. However, the network traffic appears as a complex dynamic system, causing by the collaboration of many network factors. Although various methods have been proposed to detect anomalies, they are mostly based on the traditional statistical physics. In these methods, all factor...