Composite Strain Encoding (CSENC) is a new Magnetic Resonance Imaging (MRI) technique for simultaneously acquiring cardiac functional and viability images. It combines the use of Delayed Enhancement (DE) and the Strain Encoding (SENC) imaging techniques to identify the infracted (dead) tissue and to image the myocardial deformation inside the heart muscle. In this work, a new unsupervised

We introduce NileStore, a replica placement algorithm based on an economical model for use in Peer-assisted cloud storage. The algorithm uses storage and bandwidth resources of peers to offload the cloud provider's resources. We formulate the placement problem as a linear task assignment problem where the aim is to minimize time needed for file replicas to reach a certain desired threshold. Using

Purpose: This paper aims to present an integrated framework for hotel revenue room maximization. The revenue management (RM) model presented in this work treats the shortcomings in existing systems. In particular, it extends existing optimization techniques for hotel revenue management to address group reservations and uses "forecasted demand" arrivals generated from the real data. Design

Secure routing protocols presents one of the most important challenges of Mobile Ad hoc Networks (MANETs). This is due to their special characteristics such as shared wireless medium, stringent resource constraints and highly dynamic network topology. This paper presents a solution to the problem of routing information disclosure and traffic analysis in a new way that doesn't require exchanging a

Stimulated echo acquisition mode (STEAM) is a generic imaging technique that lies at the core of many magnetic resonance imaging (MRI) techniques such MRI tagging, displacement encoded MRI, black-blood cardiac imaging. Nevertheless, tissue deformation causes frequency shift of the MR signal and leads to severe signal attenuation. In this work, a maximum likelihood estimator for the signal

Multi-slice short-axis acquisitions of the left ventricle are fundamental for estimating the volume and mass of the left ventricle in cardiac MRI scans. Manual segmentation of the myocardium in all time frames per each cross-section is a cumbersome task. Therefore, automatic myocardium segmentation methods are essential for cardiac functional analysis. Region growing has been proposed to segment

Cardiac magnetic resonance (CMR) imaging is an important technique for cardiac diagnosis. Measuring the scar in myocardium is important to cardiologists to assess the viability of the heart. Delayed enhancement (DE) images are acquired after about 10 minutes following injecting the patient with contrast agent so the infracted region appears brighter than its surroundings. A common method to

Often in real world applications only a small number of labeled data is available while unlabeled data is abundant. Therefore, it is important to make use of unlabeled data. Co-training is a popular semi-supervised learning technique that uses a small set of labeled data and enough unlabeled data to create more accurate classification models. A key feature for successful co-training is to split

Wireless sensor networks open up a new realm of ubiquitous computing applications based on distributed large-scale data collection by embedded sensor nodes that are wirelessly connected and seamlessly integrated within the environment. 3D visualization of sensory data is a challenging issue, however, due to the large number of sensors used in typical deployments, continuous data streams, and

[No abstract available]