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Institution

Jordan University of Science and Technology

EducationIrbid, Irbid, Jordan
About: Jordan University of Science and Technology is a education organization based out in Irbid, Irbid, Jordan. It is known for research contribution in the topics: Population & Health care. The organization has 7582 authors who have published 13166 publications receiving 298158 citations. The organization is also known as: JUST.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors evaluated and optimized the conversion of waste animal fat (WAF) into ethyl and methyl esters called biodiesel, and found that the physical and chemical characteristics of these esters were much closer to those of Diesel fuel than those of fresh vegetable oil or fat.

175 citations

Journal ArticleDOI
TL;DR: In this article, a series of treatment steps composed of settling, centrifugation, and filtration was consecutively used to condition Olive Mill effluent (OME) wastewater, and the filtrate was then subjected to a post-treatment process, namely adsorption on activated clay.

174 citations

Journal ArticleDOI
TL;DR: The results clearly demonstrate the adverse effects of cypermethrin pesticide on fertility and reproduction in male rats.
Abstract: Adult male Sprague-Dawley rats were exposed to tap water containing 0, 8,571, 17,143, or 34,286 ppm cypermethrin for 12 weeks. Based on water consumption per animal per day the rats received 13.15, 18.93, and 39.66 mg cypermethrin, respectively. Fertility was significantly reduced in male rats ingesting cypermethrin at a concentration of 13.15 and 18.93 mg in that the number of females impregnated by them was significantly reduced. The number of implantation sites was significantly reduced in females mated with males that had ingested cypermethrin at a concentration of 39.66 mg. A significant reduction in the number of viable fetuses was observed in females impregnated by the exposed males at all three doses of cypermethrin.

173 citations

Journal ArticleDOI
23 Jun 2015
TL;DR: A comprehensiveSoftware defined based framework model is proposed to simplify the IoT management process and provide a vital solution for the challenges in the traditional IoT architecture to forward, store, and secure the produced data from the IoT objects by integrating the software defined network, software defined storage, and software defined security into one software defined based control model.
Abstract: The internet of things (IoT) represent the current and future state of the Internet. The large number of things (objects), which are connected to the Internet, produce a huge amount of data that needs a lot of effort and processing operations to transfer it to useful information. Moreover, the organization and control of this large volume of data requires novel ideas in the design and management of the IoT network to accelerate and enhance its performance. The software defined systems is a new paradigm that appeared recently to hide all complexity in traditional system architecture by abstracting all the controls and management operations from the underling devices (things in the IoT) and setting them inside a middleware layer, a software layer. In this work, a comprehensive software defined based framework model is proposed to simplify the IoT management process and provide a vital solution for the challenges in the traditional IoT architecture to forward, store, and secure the produced data from the IoT objects by integrating the software defined network, software defined storage, and software defined security into one software defined based control model.

172 citations

Journal ArticleDOI
TL;DR: This paper proposes a state-of-the-art research for aspect-based sentiment analysis of Arabic Hotels’ reviews using two implementations of long short-term memory (LSTM) neural networks and shows that the approaches outperform baseline research on both tasks.
Abstract: This paper proposes a state-of-the-art research for aspect-based sentiment analysis of Arabic Hotels’ reviews using two implementations of long short-term memory (LSTM) neural networks. The first one is (a) a character-level bidirectional LSTM along with conditional random field classifier (Bi-LSTM-CRF) for aspect opinion target expressions (OTEs) extraction, and the second one is (b) an aspect-based LSTM for aspect sentiment polarity classification in which the aspect-OTEs are considered as attention expressions to support the sentiment polarity identification. Proposed approaches are evaluated using a reference dataset of Arabic Hotels’ reviews. Results show that our approaches outperform baseline research on both tasks with an enhancement of 39% for the task of aspect-OTEs extraction and 6% for the aspect sentiment polarity classification task.

172 citations


Authors

Showing all 7666 results

NameH-indexPapersCitations
Andrew McCallum11347278240
Yousef Khader94586111094
Michael P. Jones9070729327
David S Sanders7563923712
Nidal Hilal7239521524
Nagendra P. Shah7133419939
Jeffrey R. Idle7026116237
Rahul Sukthankar7024028630
Matthias Kern6633214871
David De Cremer6529713788
Moustafa Youssef6129915541
Mohammed Farid6129915820
Rudolf Holze5838813761
Rich Caruana5714526451
Eberhardt Herdtweck5633210785
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202331
2022104
20211,371
20201,304
2019994
2018862