Information Centric Networks (ICNs) overcome the current IP-based networks weakness and aim to ensure efficient data distribution. The Main ICN features are location-independent naming, in-network caching, name-based routing, built-in security, and high mobility. ICN vehicular networks stratify the ICN architecture on the Vehicular Ad hoc Networks (VANETs) to reinforce a massive amount of data transmission and handle the critical time interests inside the vehicular networks while taking into consideration the vehicles’ high mobility. Original Equipment Manufacturers (OEMs) gather the real-time

The rise in Arabic usage within various socialmedia platforms, and notably in Twitter, has led to a growing interest in building ArabicNatural Language Processing (NLP) applications capable of dealing with informal colloquialArabic, as it is the most commonly used form of Arabic in social media. The uniquecharacteristics of the Arabic language make the extraction of Arabic named entities achallenging task, to which, the nature of tweets adds new dimensions. The majority ofprevious research done on Arabic NER focused on extracting entities from the formallanguage, namely Modern Standard Arabic

In this paper, we study a wireless powered cellular network (WPCN) supported with network coding capability. In particular, we consider a network consisting of k cellular users (CUs) served by a hybrid access point (HAP) that takes over energy transfer to the users on top of information transmission over both the uplink (UL) and downlink (DL). Each CU has k+1 states representing its communication behavior, and collectively are referred to as the user demand profile. Opportunistically, when the CUs have information to be exchanged through the HAP, it broadcasts this information in coded format

A novel algorithm for view-invariant human action recognition is presented. This approach is based on Two-Dimensional Principal Component Analysis (2DPCA) applied directly on the Motion Energy Image (MEI) or the Motion History Image (MHI) in both the spatial domain and the transform domain. This method reduces the computational complexity by a factor of at least 66, achieving the highest recognition accuracy per camera, while maintaining minimum storage requirements, compared with the most recent reports in the field. Experimental results performed on the Weizmann action and the INIRIA IXMAS

Objectives: The purpose of this study was to determine the prognostic value of strain-encoded magnetic resonance imaging (SENC) during high-dose dobutamine stress cardiac magnetic resonance imaging (DS-MRI) compared with conventional wall motion readings. Background: Detection of inducible ischemia by DS-MRI on the basis of assessing cine images is subjective and depends on the experience of the readers, which may influence not only the diagnostic classification but also the risk stratification of patients with ischemic heart disease. Methods: In all, 320 consecutive patients with suspected or

The aim of our study was to investigate the ability of Strain-Encoded magnetic resonance imaging (MRI) to detect cardiac allograft vasculopathy (CAV) in heart transplantation (HTx)-recipients. In consecutive subjects (n = 69), who underwent cardiac catheterization, MRI was performed for quantification of myocardial strain and perfusion reserve. Based on angiographic findings subjects were classified: group A including patients with normal vessels; group B, patients with stenosis

Time series classification is a supervised learning problem used in many vital applications. Classification of data varying with time is considered an important and challenging pattern recognition task. The temporal aspect and lack of features in time series data makes the learning process different from traditional classification problems. In this paper we propose a multiple classifier system approach for time series classification. The proposed approach adaptively integrates extracted local and global features together with distance similarity based methods. A feature extraction process is

In this paper, we report our experience in working with Network Address Translators (NATs). Traditionally, there were only 4 types of NATs. For each type, the (im)possibility of traversal is well-known. Recently, the NAT community has provided a deeper dissection of NAT behaviors resulting into at least 27 types and documented the (im)possibility of traversal for some types. There are, however, two fundamental issues that were not previously tackled by the community. First, given the more elaborate set of behaviors, it is incorrect to reason about traversing a single NAT, instead combinations

In this paper, we describe an application-level emulator for P2P systems with a special focus on high reproducibil-ity. We achieve reproduciblity by taking control over the scheduling ofconcurrent events from the operating system. We accomplish that for inter-and intra-peer concurrency. The development ofthe system was driven by the need to enhance the testing process ofan already-developed industrial product. Therefore, we were constrained by the architecture ofthe overlying application. However, we managed to provide highly transparent emulation by wrapping standard/widely-used networking

Objectives: This study sought to evaluate the diagnostic accuracy of strain-encoded cardiac magnetic resonance (SENC) for the detection of inducible ischemia during intermediate stress. Background: High-dose dobutamine stress cardiac magnetic resonance (DS-CMR) is a well-established modality for the noninvasive detection of coronary artery disease (CAD). However, the assessment of cine scans relies on the visual interpretation of wall motion, which is subjective, and modalities that can objectively and quantitatively assess the time course of myocardial strain response during stress are