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Institution

University of Jordan

EducationAmman, Jordan
About: University of Jordan is a education organization based out in Amman, Jordan. It is known for research contribution in the topics: Population & Health care. The organization has 7796 authors who have published 13764 publications receiving 213526 citations.


Papers
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Journal ArticleDOI
TL;DR: Two experiments were completed to examine effects of inclusion of a yeast culture (YC) to a diet based on barley grain and wheat straw on digestibility, growth and meat traits of Awassi lambs and Shami goat kids.

76 citations

Journal ArticleDOI
TL;DR: A new model that uses Competitive Swarm Optimizer (CSO) to optimize the values of the input weights and hidden neurons of ELM to increase the generalization performance, stabilize the classifier, and to produce more compact networks by reducing the number of neurons in the hidden layer is proposed.
Abstract: Extreme Learning Machine (ELM) is swiftly gaining popularity as a way to train Single hidden Layer Feedforward Networks (SLFN) for its attractive properties. ELM is a fast learning network with remarkable generalization performance. Although ELM generally can outperform traditional gradient descent-based algorithms such as Backpropagation, its performance can be highly affected by the random selection of the input weights and hidden biases of SLFN. Moreover, ELM networks tend to have more hidden neurons due to this random selection. In this paper, we propose a new model that uses Competitive Swarm Optimizer (CSO) to optimize the values of the input weights and hidden neurons of ELM. Two versions of ELM are considered: the classical ELM and the regularized version. The goal of the model is to increase the generalization performance, stabilize the classifier, and to produce more compact networks by reducing the number of neurons in the hidden layer. The proposed model is experimented based on 15 medical classification problems. Experimental results demonstrate that the proposed model can achieve better generalization performance with smaller number of hidden neurons and with higher stability. In addition, it requires much less training time compared to other metaheuristic based ELMs.

76 citations

Journal ArticleDOI
TL;DR: In this paper, the removal of Pb(II) from aqueous solution by adsorption onto insolubilized humic acid (IHA) in single component system at different temperatures and different pH, and at constant ionic strength has been investigated.

76 citations

Journal ArticleDOI
TL;DR: The potential of endophytic Beauveria bassiana to provide protection against Zucchini yellow mosaic virus (ZYMV), one of the most economically important viral diseases in cucurbits, is investigated.
Abstract: We investigated the potential of endophytic Beauveria bassiana to provide protection against Zucchini yellow mosaic virus (ZYMV), one of the most economically important viral diseases in cucurbits. Four selected B. bassiana strains were able to successfully colonise squash plants following foliar inoculation with the conidial suspension of each respective strain. However, no significant difference in percentage colonisation was observed among the tested B. bassiana strains. Disease incidence (percentage of plants showing ZYMV symptoms) and severity (rating based on a 5-point scale), sampled weekly for four weeks following the challenge inoculation of plants with ZYMV, were significantly lower in B. bassiana-inoculated plants as compared to control plants, regardless of the inoculated strain. This is, to our knowledge, the first report on the potential of endophytic B. bassiana to confer protection against plant viruses. Further studies should be conducted to determine whether such endophytic B. bassiana-m...

76 citations

Proceedings ArticleDOI
11 Jul 2018
TL;DR: This study has implemented the AT&T scheme for managing the access control mechanism of patients data using the XACML access model, that provides hierarchically satisfied access to various data resources.
Abstract: Mobile medicine and health care have been adopted on a very large scale with support from the influx of medical devices and increased usability of remote health services. These are combined with an approachable interest of the patients and a readily approachable conscience about their healthcare. This leads to a huge set of medical data. These data sets require secure transfer, archival and access. In this study, we have proposed an efficient approach to preserve the identity and also protect the privacy of clinical data using highly effective encryption scheme. Moreover, we have also discussed an authorization framework using access of varying degrees. Medical records are often accessed by various entities with varying degrees of authorization. In this study, we have implemented the AT&T scheme for managing the access control mechanism of patients data. Further, encryption is undertaken using ARCANA, that provides hierarchically satisfied access to various data resources. It utilizes the XACML access model to formulate the access control framework. The primary reason for using this model is the regulation to access the data through AT&T based on XACML policies. In addition to this, the encrypting of medical data using various authorization techniques have been required for the proper data access regulation. Which may impact trust of the users in the e-health paradigm and in turn increase the large-scale usability.

76 citations


Authors

Showing all 7905 results

NameH-indexPapersCitations
Yousef Khader94586111094
Crispian Scully8691733404
Debra K. Moser8555827188
Pierre Thibault7733217741
Ali H. Nayfeh7161831111
Harold S. Margolis7119926719
Gerrit Hoogenboom6956024151
Shaher Momani6430113680
Robert McDonald6257717531
Kaarle Hämeri5817510969
James E. Maynard561419158
E. Richard Moxon5417610395
Liam G Heaney532348556
Stephen C. Hadler5214811458
Nicholas H. Oberlies522629683
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202334
2022163
20211,459
20201,313
20191,166
2018932