in order to obtain maximum information from magnetic and gravity anomaly maps, application of an edgedetection method is necessary. in this regard two commonly used methods are derivative filters and local phase filters. in this paper, a matlab code is expanded to combine an analytic signal filter and a tilt angle filter as a new edge detection filter called asta filter. this method was demonst...

We demonstrate an enterprise Dynamic Thresholding System for data-agnostic management of monitoring flows. The dynamic thresholding based on data historical behavior enables adaptive and more accurate control of business environments compared to static thresholding. We manifest the main blocks of a complex analytical engine that is implemented in VMware vCenter Operations Manager as a principal...

We consider the problem of anomaly detection in data streams, which is the problem of extracting subsequences that do not match an expected behaviour. The main challenge for detecting anomalous subsequences from data streams in the existing techniques is to determine the lengths of the normal and anomalous subsequences. Therefore, creating a robust model for detecting the anomalous subsequences...

We consider the problem of detecting past activities as well as anticipating which activity will happen in the future and how. We start by modeling the rich spatio-temporal relations between human poses and objects (called affordances) using a conditional random field (CRF). However, because of the ambiguity in the temporal segmentation of the sub-activities that constitute an activity, in the ...

This paper aims to address the problem of anomaly detection and discrimination in complex behaviours, where anomalies are subtle and difficult to detect owing to the complex temporal dynamics and correlations among multiple objects’ behaviours. Specifically, we decompose a complex behaviour pattern according to its temporal characteristics or spatial-temporal visual contexts. The decomposed beh...

Mobile Ad-hoc Networks (MANETs) in contrast to 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 can specify anomalies with high accuracy at network dynamic topology alternation. In this paper, two methods were proposed for dynamic anomaly ...

rise in temperature occurred after soil temperature was measured in different time series. in this article, ldf (logarithmic derivative filter) innovative method is applied to detect anomalies. this method tests soil temperature time series for 12 earthquakes in iran with magnitudes of either five or greater than five. results from this method were collected. based on the results of ldf method ...

This paper presents symbolic time series analysis of observable process variables for anomaly detection in thermal pulse combustors. The anomaly detection method has been tested on the time series data of pressure oscillations, generated from a non-linear dynamic model of a generic thermal pulse combustor. Results are presented to exemplify early detection of combustion instability due to reduc...

In this paper we propose an approach for anomaly detection and localization, in video surveillance applications, based on spatio-temporal features that capture scene dynamic statistics together with appearance. Real-time anomaly detection is performed with an unsupervised approach using a nonparametric modeling, evaluating directly multi-scale local descriptor statistics. A method to update sce...

Traditional anomaly detection on social media mostly focuses on individual point anomalies while anomalous phenomena usually occur in groups. Therefore it is valuable to study the collective behavior of individuals and detect group anomalies. Existing group anomaly detection approaches rely on the assumption that the groups are known, which can hardly be true in real world social media applicat...