Institution
Jordan University of Science and Technology
Education•Irbid, 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.
Topics: Population, Health care, Heat transfer, Cloud computing, Adsorption
Papers published on a yearly basis
Papers
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TL;DR: In this article, the authors presented the first few months of operation of a large seawater desalination system at the Marine Science Station (MSS) of Aqaba, Jordan.
177 citations
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TL;DR: Evaluation in two testbeds on Android phones shows that the SemanticSLAM system can achieve 0.53 meters human median localization errors, which is 62 percent better than a system that does not use SLAM, and has a 33 percent lower convergence time.
Abstract: Indoor localization using mobile sensors has gained momentum lately. Most of the current systems rely on an extensive calibration step to achieve high accuracy. We propose SemanticSLAM , a novel unsupervised indoor localization scheme that bypasses the need for war-driving. SemanticSLAM leverages the idea that certain locations in an indoor environment have a unique signature on one or more phone sensors. Climbing stairs, for example, has a distinct pattern on the phone's accelerometer; a specific spot may experience an unusual magnetic interference while another may have a unique set of Wi-Fi access points covering it. SemanticSLAM uses these unique points in the environment as landmarks and combines them with dead-reckoning in a new Simultaneous Localization And Mapping (SLAM) framework to reduce both the localization error and convergence time. In particular, the phone inertial sensors are used to keep track of the user's path, while the observed landmarks are used to compensate for the accumulation of error in a unified probabilistic framework. Evaluation in two testbeds on Android phones shows that the system can achieve $0.53$ meters human median localization errors. In addition, the system can detect the location of landmarks with 0.83 meters median error. This is 62 percent better than a system that does not use SLAM. Moreover, SemanticSLAM has a 33 percent lower convergence time compared to the same systems. This highlights the promise of SemanticSLAM as an unconventional approach for indoor localization.
176 citations
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TL;DR: The findings of the study indicated a direct and a buffering effect of recognition of nurses' performance on job stress and the level of intention to stay at work.
Abstract: Purpose To investigate: (1) relationships between job stress, recognition of nurses’ performance, job performance and intention to stay among hospital nurses; and (2) the buffering effect of recognition of staff performance on the ‘stress–intention to stay at work’ relationship.
Background Workplace stress tremendously affects today’s workforce. Recognition of nurses’ performance needs further investigation to determine if it enhances the level of intention to stay at work and if it can buffer the negative effects of stress on nurses’ intention to stay at work.
Design and methods The sample of the present study was a convenience one. It consisted of 206 Jordanian staff nurses who completed a structured questionnaire.
Results The findings of the study indicated a direct and a buffering effect of recognition of nurses’ performance on job stress and the level of intention to stay at work.
Conclusion The results of the study indicated the importance of recognition for outstanding performance as well as achievements.
Implications for nursing management The results of this study support the need to focus on the implementation of recognition strategies in the workplace to reduce job stress and enhance retention.
176 citations
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TL;DR: A novel approach has been proposed to diagnose PD using the gait analysis, that consists of the gact cycle, which can be broken down into various phases and periods to determine normative and abnormal gait.
176 citations
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TL;DR: This study examined three releases of the Eclipse project and found that although some metrics can still predict class error proneness in three error-severity categories, the accuracy of the prediction decreased from release to release and the prediction cannot be used to build a metrics model to identify error-prone classes with acceptable accuracy.
175 citations
Authors
Showing all 7666 results
Name | H-index | Papers | Citations |
---|---|---|---|
Andrew McCallum | 113 | 472 | 78240 |
Yousef Khader | 94 | 586 | 111094 |
Michael P. Jones | 90 | 707 | 29327 |
David S Sanders | 75 | 639 | 23712 |
Nidal Hilal | 72 | 395 | 21524 |
Nagendra P. Shah | 71 | 334 | 19939 |
Jeffrey R. Idle | 70 | 261 | 16237 |
Rahul Sukthankar | 70 | 240 | 28630 |
Matthias Kern | 66 | 332 | 14871 |
David De Cremer | 65 | 297 | 13788 |
Moustafa Youssef | 61 | 299 | 15541 |
Mohammed Farid | 61 | 299 | 15820 |
Rudolf Holze | 58 | 388 | 13761 |
Rich Caruana | 57 | 145 | 26451 |
Eberhardt Herdtweck | 56 | 332 | 10785 |