Diaz O.,University of New Mexico |
Xu F.,University of New Mexico |
Min-Allah N.,COMSATS Institute of Information Technology |
Khodeir M.,JUST |
And 3 more authors.
IEEE Communications Letters | Year: 2012
Network service recovery from multiple correlated failures is a major concern given the increased level of infrastructure vulnerability to natural disasters, massive power failures, and malicious attacks. To properly address this problem, a novel path protection solution is proposed to jointly incorporate traffic engineering and risk minimization objectives. The framework assumes probabilistic link failures and is evaluated against some existing multi-failure recovery schemes using network simulation. © 2012 IEEE.
Haddad B.,University of Jordan |
Journal of Circuits, Systems and Computers | Year: 2013
Recent demand for low power VLSI circuits has been pushing the development of innovative approaches to reduce power dissipation. Supply voltage (V CC) and switching activity factor (α) are main sources of dynamic power dissipation in CMOS technology. Furthermore, the power dissipation increases exponentially by the value of supply voltage. New approach based on switching activity analysis and multiple supply voltage is implemented successfully in logical circuits, taking in mind the critical path(s) of the design and switching activity factor of each element in the design. High supply voltage is applied on elements on the critical path(s). Elements off the critical path(s) are classified into categories according to their switching activity factors. The total power dissipation is reduced, while the propagation delay remains without any increase. The proposed approach combines the concepts of critical/non-critical paths and switching activity analysis to assign different VCCs to different elements. © 2013 World Scientific Publishing Company.
Hamdan M.A.,University of Jordan |
Al-Nimr M.A.,JUST |
Hammoudeh V.A.,University of Jordan
Journal of Fluids Engineering, Transactions of the ASME | Year: 2010
In this work, the effect of the second-order term to the velocityslip/temperature-jump boundary conditions on the solution of four cases in which the driving force is fluctuating harmonically was studied. The study aims to establish criteria that secure the use of the first order velocity-slip/temperature-jump model boundary conditions instead of the second-order ones. The four cases studied were the transient Couette flow, the pulsating Poiseuille flow, Stoke's second problem, and the transient natural convection flow. It was found that at any given Kn number, increasing the driving force frequency, increases the difference between the first and second-order models. Assuming that a difference between the two models of over 5% is significant enough to justify the use of the more complex second-order model, the critical frequencies for the four different cases were found. For the cases for which the flow is induced by the fluctuating wall as in cases 1 and 3, we found that critical frequency at Kn=0.1 to be ω=8. For the cases of flow driven by a fluctuating pressure gradient as in case 2, this frequency was found to be ω = 1, at the same Kn number. In case 4, for the temperature-jump model, the critical frequency was found to beω = 7 and for the velocity-slip model the critical frequency at the same Kn number was found to be ω = 1.35. Copyright © 2010 by ASME.
Alkhateeb A.,Jordan University of Science and Technology |
Karasneh J.,JUST |
Abbadi H.,Jordan University of Science and Technology |
Hassan A.,University of Baghdad |
Thornhill M.,University of Sheffield
Journal of Oral Pathology and Medicine | Year: 2013
Background: Recurrent aphthous stomatitis (RAS) is a common oral ulcerative condition. At ulcer sites vascular adhesion molecule-1 (VCAM-1), E-selectin and intercellular adhesion molecule-1 (ICAM-1) are strongly expressed on blood vessels, and ICAM-1 is expressed on keratinocytes. Expression of these molecules would promote leukocyte accumulation and invasion of the epithelium. Thus, polymorphisms in these candidate genes might contribute to RAS susceptibility. We investigated whether the inheritance of specific selectin, ICAM and VCAM gene polymorphisms is associated with RAS susceptibility. Methods: Ninety-six RAS cases and 153 controls were recruited from a Jordanian population. Blood was collected for hematological investigations and genotyping. Six SNPs were genotyped: E-selectin rs5361 and rs1805193, L-selectin, rs2205849, ICAM-1 rs5498, ICAM-5 rs885743 and VCAM-1 rs1800821. Association was determined using chi-square and binary logistic regression analysis after correcting for confounding factors. Linkage disequilibrium was determined using the EH program, and the Phase 2.1 program was used to construct and compare haplotypes between cases and controls. Results: There was a significant association of the A allele (Pcorr = 0.027), AA and AC genotypes (OR = 10.9 and 9.0, respectively) of the E-selectin rs5361 gene polymorphism and TAA haplotype (rs2205849, rs5361, and rs1805193, respectively; P = 0.03) with RAS. None of the other SNPs showed a significant association. Conclusions: This is the first report to link inheritance of the A allele, AA and AC genotypes of the E-selectin rs5361 polymorphism with increased risk of RAS. Further studies in different patient cohorts are needed to confirm the association, and functional analyses might clarify the biological significance of the association. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Harrag F.,Ferhat Abbas University Setif |
Hamdi-Cherif A.,Qassim University |
Neural Network World | Year: 2010
Text categorization is based on the idea of content-based texts clustering. An Artificial Neural Network (ANN) or simply Neural Network (NN) classifier for Arabic texts categorization is proposed. The Singular Value Decomposition (SVD) is used as preprocessor with the aim of further reducing data in terms of both size and dimensionality. Indeed, the use of SVD makes data more amenable to classification and the convergence training process faster. Specifically, the effectiveness of the Multilayer Perceptron (MLP) and the Radial Basis Function (RBF) classifiers are implemented. Experiments are conducted using an in-house corpus of Arabic texts. Precision, recall and F-measure are used to quantify categorization effectiveness. The results show that the proposed SVD-Supported MLP/RBF ANN classifier is able to achieve high effectiveness. Experimental results also show that the MLP classifier outperforms the RBF classifier and that the SVD-supported NN classifier is better than the basic NN, as far as Arabic text categorization is concerned. ©ICS AS CR 2010.