Detecting trending topics or events from Twitter is an active research area. The first step in detecting such topics focuses on efficiently capturing textual features that exhibit an unusual high rate of appearance during a specific timeframe. Previous work in this area has resulted in coining the term "detecting bursty features" to refer to this step. In this paper, TFIDF, entropy, and stream chunking are adapted to investigate a new technique for detecting bursty features from an Arabic Twitter stream. Experimental results comparing bursty features extracted from Twitter streams, to Twitter

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 the myocardium. Although the technique is simple and fast, non uniform intensity and low-contrast interfaces of the myocardium are major challenges of the technique that limit its use in myocardial

One of the key challenges in applying deep learning to solve real-life problems is the lack of large annotated datasets. Furthermore, for a deep learning model to perform well on the test set, all samples in the training and test sets should be independent and identically distributed (i.i.d.), which means that test samples should be similar to the samples that were used to train the model. In many cases, however, the underlying training and test set distributions are different. In such cases, it is common to adapt the test samples by transforming them to their equivalent counterparts in the

Energy efficient operation of cellular systems becomes a core design goal for economic and environment-friendly network operation. Several studies have shown that the energy consumed in base stations represents 60-80% of the energy consumption in cellular networks. In this paper, we develop an optimization framework that exploits several energy efficient techniques including switching power modes of base stations, Adaptive Modulation (AM), and the use of relays. Our main objective is to reduce both, transmitted and circuit power, subject to satisfying the quality of service constraints. To

Censoring has been proposed to be utilized in wireless distributed detection networks with a fusion center to enhance network performance in terms of error probability in addition to the well- established energy saving gains. In this paper, we further examine the employment of censoring in infrastructure-less cognitive radio networks, where nodes employ binary consensus algorithms to take global decisions regarding a binary hypothesis test without a fusion center to coordinate such a process. We show analytically - and verify by simulations - that censoring enhances the performance of such

This paper presents an energy efficient relay deployment algorithm that determines the optimal location and number of relays for future wireless networks, including Long Term Evolution (LTE)-Advanced heterogeneous networks. We formulate an energy minimization problem for macro-relay heterogeneous networks as a Mixed Integer Linear Programming (MILP) problem. The proposed algorithm not only optimally connects users to either relays or eNodeBs (eNBs), but also allows eNBs to switch into inactive mode. This is possible by enabling relay-to-relay communication which forms the basis for relays to

This study aims to enhance the performance of the flat sheet thin-film composite (TFC) polyamide-polysulfone reverse osmosis (RO) membranes. Composite RO membranes with high salt rejection were fabricated by treating a porous polysulfone (PS) support sequentially with a di-amine and then with a polyfunctional acid chloride, thereby forming a thin film of polyamide (PA) on the PS support. In order to establish conditions for the development of suitable thin-film composite (PS/TFC) membranes, various parametric studies were carried out which included varying the concentration of reactants

Pipelines conveying gas under pressure exhibit turbulence-induced vibrations. The current work is concerned with extracting useful power from pipelines operating well within their stability region. At such regions, the pipe vibrations exist in small magnitudes and are unlikely to cause structural failure, yet can be exploited to provide useful energy for low-power electronic devices. Accordingly, emphasis in the present work is placed on the development of an energy harvesting technique employing the omnipresent and inevitable flow-induced vibrations in gas pipelines. © 2010 SPIE.

Mn2+, Co2+, or Ni2+ monodoped CdS (or ZnS) and Mn2+-Co2+-Ni2+ tridoped CdS (or ZnS) have been successfully synthesized by novel one-step thermolysis method using thiourea as a sulphur source. The synthesized nanomaterials were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM), and scanning electron microscopy (SEM). It is found that the average diameter and morphology of the synthesized samples varied with the nature of dopant ion. The successful doping of Mn2+-Co2+-Ni2+ tridoped ions into the host CdS (or ZnS) was proved by the EDX spectra. The luminescence of

Abstract: Liquid crystal (LC) has long been a feature in Materials Science and Nanotechnology, have recently been extended into the appealing domain of complex hybrid materials. The crystalline structural effects of alkoxy chain lengths and the mesogen properties of hydrogen-bonded (n-OBASA) complexes (n = 5,6,7) have been investigated in recent studies. The LC-based hybrid nanocomposite materials–obtained by the homogeneous dispersion of zinc oxide nanowires (ZnO NWs) as a dopant into hydrogen-bonded liquid-crystalline compounds—seem to be particularly promising in this article. Optimizing