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Greedy framework for optical flow tracking of myocardium contours

Optical flow (OF) tracking of the myocardium contours has a potential in segmenting the myocardium in time sequences of cardiac medical images. Nevertheless, to estimate the displacement field of the contour points, a number of assumptions are required to solve an under-determined set of optical flow equations. In this work, a new framework is proposed to solve the OF tracking problem using greedy

Artificial Intelligence
Healthcare

Classification of cardiac magnetic resonance image type and orientation

Cardiac magnetic resonance imaging provides a number of different imaging acquisition types and views of different body cross sections and orientations. A huge amount of images are produced which demand an automatic method for classification based on the visual contents to facilitate diagnosis and searching operations. In this work, we propose a fully automated classification method for

Artificial Intelligence
Healthcare

A time series classification approach for motion analysis using ensembles in Ubiquitous healthcare systems

Human motion analysis is a vital research area for healthcare systems. The increasing need for automated activity analysis inspired the design of low cost wireless sensors that can capture information under free living conditions. Body and Visual Sensor Networks can easily record human behavior within a home environment. In this paper we propose a multiple classifier system that uses time series

Artificial Intelligence
Healthcare

Parallelizing exact motif finding algorithms on multi-core

The motif finding problem is one of the important and challenging problems in bioinformatics. A variety of sequential algorithms have been proposed to find exact motifs, but the running time is still not suitable due to high computational complexity of finding motifs. In this paper we parallelize three efficient sequential algorithms which are HEPPMSprune, PMS5 and PMS6. We implement the

Healthcare

New insight into HCV E1/E2 region of genotype 4a

Introduction: Hepatitis C virus (HCV) genome contains two envelope proteins (E1 and E2) responsible for the virus entry into the cell. There is a substantial lack of sequences covering the full length of E1/E2 region for genotype 4. Our study aims at providing new sequences as well as characterizing the genetic divergence of the E1/E2 region of HCV 4a using our new sequences along with all

Healthcare

A fully automated approach for Arabic slang lexicon extraction from microblogs

With the rapid increase in the volume of Arabic opinionated posts on different social media forums, comes an increased demand for Arabic sentiment analysis tools and resources. Social media posts, especially those made by the younger generation, are usually written using colloquial Arabic and include a lot of slang, many of which evolves over time. While some work has been carried out to build

Artificial Intelligence
Software and Communications

Enhanced customer churn prediction using social network analysis

There were 6.8 billion estimates for mobile subscriptions worldwide by end of 2013 [11]. As the mobile market gets saturated, it becomes harder for telecom providers to acquire new customers, and makes it essential for them to retain their own. Due to the high competition between different telecom providers and the ability of customers to move from one provider to another, all telecom service

Artificial Intelligence

VAFLE: Visual analytics of firewall log events

In this work, we present VAFLE, an interactive network security visualization prototype for the analysis of firewall log events. Keeping it simple yet effective for analysts, we provide multiple coordinated interactive visualizations augmented with clustering capabilities customized to support anomaly detection and cyber situation awareness. We evaluate the usefulness of the prototype in a use

Artificial Intelligence

Accurate estimation of the myocardium global function from reduced magnetic resonance image acquisitions

Evaluating the heart global function from magnetic resonance images is based on estimating a number of functional parameters such as the left ventricular (LV) volume, LV mass, ejection fraction, and stroke volume. Estimating these parameters requires accurate calculation of the volumes enclosed by the inner and outer surfaces of the LV chamber at the max contraction and relaxation states of the

Artificial Intelligence

Using the sadakane compressed suffix tree to solve the all-pairs suffix-prefix problem

The all-pairs suffix-prefix matching problem is a basic problem in string processing. It has an application in the de novo genome assembly task, which is one of the major bioinformatics problems. Due to the large size of the input data, it is crucial to use fast and space efficient solutions. In this paper, we present a space-economical solution to this problem using the generalized Sadakane

Artificial Intelligence