detecting anomalies is an important challenge for intrusion detection and fault diagnosis in wireless sensor networks (wsns). to address the problem of outlier detection in wireless sensor networks, in this paper we present a pca-based centralized approach and a dpca-based distributed energy-efficient approach for detecting outliers in sensed data in a wsn. the outliers in sensed data can be ca...

Multi-view outlier detection is a challenging problem due to the inconsistent behaviors and complicated distributions of samples across different views. The existing approaches are designed to identify the outlier exhibiting inconsistent characteristics across different views. However, due to the inevitable system errors caused by data-captured sensors or others, there always exists another typ...

Outlier detection shows its increasingly high practical value in many application areas such as intrusion detection, fraud detection, discovery of criminal activities in electronic commerce and so on. Many techniques have been developed for outlier detection, including distribution-based outlier detection algorithm, depth-based outlier detection algorithm, distance-based outlier detection algor...

Outlier detection has been a long-debated subject among researchers due to its effect on model fitting. Spatial outlier received considerable attention in the recent past. On other hand, accommodation, particularly spatial applications, retains vital information about model. It is pertinent develop method that capable of accommodating detected outliers fashion models. In this paper, we formulat...

BACKGROUND Potential severe liver injury is identified in clinical trials by ALT >3 × upper limits of normal (ULN) and total bilirubin >2 × ULN, and termed 'Hy's Law' by the US FDA. However, there is limited evidence or validation of these thresholds in clinical trial populations. Using liver chemistry data from clinical trials, decision boundaries were built empirically with truncated robust m...

In this paper the use of outlier detection methods is discussed. This analysis is an introduction to the use of various methods of outlier detection in medical diagnoses (screening). The authors investigated the usefulness of selected outlier detection methods in the context of detection sensitivity, speed performance analysis and the difficulty of automating the performance analysis by using t...

Article history: Received 19 April 2010 Received in revised form 1 September 2011 Accepted 1 August 2012 Available online 30 September 2012 Most multi-generation models investigate the monotonously incremental market potential of later generation by expanding applications for the product, besides, neither corporate marketing variables nor the competitive environment is considered. However, a ne...