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Institution

Applied Science Private University

EducationAmman, Jordan
About: Applied Science Private University is a education organization based out in Amman, Jordan. It is known for research contribution in the topics: Population & Catalysis. The organization has 4124 authors who have published 5299 publications receiving 116167 citations.


Papers
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Journal ArticleDOI
TL;DR: The dynamical steady-state probability density is found in an extended phase space with variables x, p/sub x/, V, epsilon-dot, and zeta, where the x are reduced distances and the two variables epsilus-dot andZeta act as thermodynamic friction coefficients.
Abstract: Nos\'e has modified Newtonian dynamics so as to reproduce both the canonical and the isothermal-isobaric probability densities in the phase space of an N-body system. He did this by scaling time (with s) and distance (with ${V}^{1/D}$ in D dimensions) through Lagrangian equations of motion. The dynamical equations describe the evolution of these two scaling variables and their two conjugate momenta ${p}_{s}$ and ${p}_{v}$. Here we develop a slightly different set of equations, free of time scaling. We find the dynamical steady-state probability density in an extended phase space with variables x, ${p}_{x}$, V, \ensuremath{\epsilon}\ifmmode \dot{}\else \.{}\fi{}, and \ensuremath{\zeta}, where the x are reduced distances and the two variables \ensuremath{\epsilon}\ifmmode \dot{}\else \.{}\fi{} and \ensuremath{\zeta} act as thermodynamic friction coefficients. We find that these friction coefficients have Gaussian distributions. From the distributions the extent of small-system non-Newtonian behavior can be estimated. We illustrate the dynamical equations by considering their application to the simplest possible case, a one-dimensional classical harmonic oscillator.

17,939 citations

Journal ArticleDOI
TL;DR: Efficiency figures show that the proposed technique for motion detection outperforms recent and proven state-of-the-art methods in terms of both computation speed and detection rate.
Abstract: This paper presents a technique for motion detection that incorporates several innovative mechanisms. For example, our proposed technique stores, for each pixel, a set of values taken in the past at the same location or in the neighborhood. It then compares this set to the current pixel value in order to determine whether that pixel belongs to the background, and adapts the model by choosing randomly which values to substitute from the background model. This approach differs from those based upon the classical belief that the oldest values should be replaced first. Finally, when the pixel is found to be part of the background, its value is propagated into the background model of a neighboring pixel. We describe our method in full details (including pseudo-code and the parameter values used) and compare it to other background subtraction techniques. Efficiency figures show that our method outperforms recent and proven state-of-the-art methods in terms of both computation speed and detection rate. We also analyze the performance of a downscaled version of our algorithm to the absolute minimum of one comparison and one byte of memory per pixel. It appears that even such a simplified version of our algorithm performs better than mainstream techniques.

1,777 citations

Journal ArticleDOI
TL;DR: In this article, the thermal properties, crystallinity index, reactivity, and surface morphology of untreated and chemically modified fibers have been studied using differential scanning calorimetry (DSC), X-ray diffraction (WAXRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM), respectively.
Abstract: Plant fibers are rich in cellulose and they are a cheap, easily renewable source of fibers with the potential for polymer reinforcement. The presence of surface impurities and the large amount of hydroxyl groups make plant fibers less attractive for reinforcement of polymeric materials. Hemp, sisal, jute, and kapok fibers were subjected to alkalization by using sodium hydroxide. The thermal characteristics, crystallinity index, reactivity, and surface morphology of untreated and chemically modified fibers have been studied using differential scanning calorimetry (DSC), X-ray diffraction (WAXRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM), respectively. Following alkalization the DSC showed a rapid degradation of the cellulose between 0.8 and 8% NaOH, beyond which degradation was found to be marginal. There was a marginal drop in the crystallinity index of hemp fiber while sisal, jute, and kapok fibers showed a slight increase in crystallinity at caustic soda concentration of 0.8–30%. FTIR showed that kapok fiber was found to be the most reactive followed by jute, sisal, and then hemp fiber. SEM showed a relatively smooth surface for all the untreated fibers; however, after alkalization, all the fibers showed uneven surfaces. These results show that alkalization modifies plant fibers promoting the development of fiber–resin adhesion, which then will result in increased interfacial energy and, hence, improvement in the mechanical and thermal stability of the composites. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 84: 2222–2234, 2002

1,396 citations

Journal ArticleDOI
TL;DR: In this article, the authors present the main research challenges and the existing solutions in the field of IoT security, identifying open issues and suggesting some hints for future research, and suggest some hints to future research.

1,258 citations

Journal ArticleDOI
TL;DR: The advances made toward understanding the basis of cancer immune evasion are discussed, the efficacy of various therapeutic measures and targets that have been developed or are being investigated to enhance tumor rejection are summarized and some natural agents and phytochemicals merit further study.

1,064 citations


Authors

Showing all 4150 results

NameH-indexPapersCitations
Richard Martin5433911465
Eiji Nishibori5426611089
Masayuki Takeuchi542409729
Hiroshi Ikeda5334110947
Jeff Sakamoto532049660
Akira Sekiguchi524019929
John D. Mackenzie522799987
William G. Hoover5224427658
Sean R. Agnew5218814260
Gary J. Shiflet512559497
Qi Chen5117823090
Michelle Y. Simmons5145811835
Vijay K. Vasudevan5122143241
Laurent Pilon512167922
Seungkwan Hong5119811380
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20239
202255
2021599
2020473
2019404
2018355