Jordan University of Science and Technology

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.

Hypertension Prevalence, Awareness, Treatment and Control, and Associated Factors: Results from a National Survey, Jordan

Abstract: The study examined prevalence, awareness, treatment and control of hypertension (HTN), and associated factors and to evaluate the trend in hypertension between 2009 (period 2) and 1994–1998 (period 1). A national sample of 4117 adults aged 25 years and older was selected. Prevalence rate of HTN (SBP ≥ 140 or DBP ≥ 90 or on antihypertensive therapy) was 32.3% and was higher than the 29.4% prevalence rate reported in period 1. Prevalence rate was significantly higher among males, older age groups, least educated, obese, and diabetics than their counterparts. The rate of awareness among hypertensives was 56.1% and was higher than the 38.8% rate reported form period 1 data. Awareness was positively associated with age, smoking, and diabetes for both men and women, and with level of education and body mass index for men. Rate of treatment for HTN among aware patients was 63.3% and was significantly higher than the 52.8% rate reported in period1. Control rate of HTN among treated hypertensives was 39.6%; significantly higher than the 27.9% control rate in period 1. Control of HTN was positively associated with age but only for women. In conclusion, HTN is still on the rise in Jordan, and levels of awareness and control are below the optimal levels.

Semi‐active neuro‐control for base‐isolation system using magnetorheological (MR) dampers

Abstract: Vibration mitigation using smart, reliable and cost-effective mechanisms that requires small activation power is the primary objective of this paper. A semi-active controller-based neural network for base-isolation structure equipped with a magnetorheological (MR) damper is presented and evaluated. An inverse neural network model (INV-MR) is constructed to replicate the inverse dynamics of the MR damper. Next, linear quadratic Gaussian (LQG) controller is designed to produce the optimal control force. Thereafter, the LQG controller and the INV-MR models are linked to control the structure. The coupled LQG and INV-MR system was used to train a semi-active neuro-controller, designated as SA-NC, which produces the necessary control voltage that actuates the MR damper. To evaluate the proposed method, the SA-NC is compared to passive lead–rubber bearing isolation systems (LRBs). Results revealed that the SA-NC was quite effective in seismic response reduction for wide range of motions from moderate to severe seismic events compared to the passive systems. In addition, the semi-active MR damper enjoys many desirable features, such as its inherent stability, practicality and small power requirements. The effectiveness of the SA-NC is illustrated and verified using simulated response of a six-degree-of-freedom model of a base-isolated building excited by several historical earthquake records. Copyright © 2006 John Wiley & Sons, Ltd.