Anomaly detection in big data is a key problem in the big data analytics domain. In this paper, the definitions of anomaly detection and big data were presented. Due to the sampling and storage burden and the inadequacy of privacy protection of anomaly detection based on uncompressed data, compressive sensing theory was introduced and used in the anomaly detection algorithm. The anomaly detecti...

Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection framework extends anomaly detection to the problem of identifying anomalous patterns on a subset of attributes in the data. The anomaly always depends (is conditioned) on the value of remaining attributes. The work presented in this paper focuses...

BACKGROUND Recurrence risks for familial congenital anomalies in successive pregnancies are known, but this information for major structural anomalies is lacking. We estimated the absolute and relative risks of recurrent congenital anomaly in the second pregnancy for women with a history of a congenital anomaly in the first pregnancy, for all major anomaly groups and subtypes. METHODS Populat...

Pelger-Huet (P-H) anomaly is a benign congenital anomaly of leukocytes, characterized by nuclear hyposegmentation of granulocytes. Patients with heterozygous form of P-H anomaly are not immunodeficient and not predisposed to infection. In this study, P-H anomaly has been detected during a routine blood examination conducted on a clinically normal five years old male Basenji dog. Nuclear hyposeg...

Due to the rapid growth of high speed network, the risk of credit-card attacks on the complex networks are also increases accordingly. Anomaly discovery from the database is a process of filtering uncertain features, so that it can be used wide variety of applications. Since the online distributed data is the communication between the remote client and the centralized server, it is difficult to...

Anomaly detection is an important problem that has been popularly researched within diverse research areas and application domains. One of the open problems in anomaly detection is the modeling and prediction of complex sequential data, which consist of a series of temporally related behavior patterns. In this paper, a novel sequential anomaly detection method based on temporal-difference (TD) ...

fMRI was used to examine the brain activity of 18 young adults while they read or heard matched sentences that were either well-formed or contained anomalies of syntactic form or pragmatic content. We examined specific regions of interest (ROI) based on activity patterns found in earlier research. We sought: a) brain regions that respond robustly to both speech and print; b) regions that are se...

Objectives: We analyzed and summarized the ultrasonic and anatomical features of fetal Ebstein anomaly to improve the ultrasonographic diagnostic rate. Methods: We analyzed the fetal echocardiographs and either the postnatal echocardiographs or anatomical specimens of 13 cases of fetal Ebstein anomaly. The cases were divided into typical and rare types according to the features of the Ebstein a...

In this paper, we suggest a multi-dimensional approach towards intrusion detection. Network and system usage parameters like source and destination IP addresses; source and destination ports; incoming and outgoing network traffic data rate and number of CPU cycles per request are divided into multiple dimensions. Rather than analyzing raw bytes of data corresponding to the values of the network...