Institution
Stevens Institute of Technology
Education•Hoboken, New Jersey, United States•
About: Stevens Institute of Technology is a education organization based out in Hoboken, New Jersey, United States. It is known for research contribution in the topics: Computer science & Cognitive radio. The organization has 5440 authors who have published 12684 publications receiving 296875 citations. The organization is also known as: Stevens & Stevens Tech.
Topics: Computer science, Cognitive radio, Communication channel, Wireless network, Artificial neural network
Papers published on a yearly basis
Papers
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TL;DR: In this article, semi-dynamic leaching tests were conducted for artificial soils contaminated with lead oxide (PbO) in order to assess the long-term leaching behavior of lead, and the results indicated that S/S treatment was effective in immobilizing Pb and the treated soils can be considered acceptable for controlled utilization based on diffusion coefficients and leachability indices.
99 citations
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TL;DR: Evidence is provided that semantic priming probably occurred under conditions in which commensurate visual information was actually available and that McCauley et al.
Abstract: In a recent study, McCauley, Parmelee, Sperber, and Carr (1980) reported results indicating that semantic priming had been produced by visual stimuli that were backward masked at durations too brief for greater than chance report. The conclusions drawn from such an experiment are critically dependent upon whether or not the primes were actually masked below the thresh-old for identification during priming trials. The three experiments reported here provide evidence that this requirement was not met. Rather, McCauley et al.’s (1980) methodology allowed for an uncontrolled increase in light adaptation during the actual testing of prime efficacy in the priming session. This increase in light adaptation reduced the effectiveness of the backward mask and resulted in an increase in prime visibility during priming trials. Thus, semantic priming probably occurred under conditions in which commensurate visual information was actually available.
99 citations
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TL;DR: This work shows that many of the formulas for determiningt(G), the number of spanning trees of any graphG, in terms of a determinant, can be simply derived from known properties of Chebyshev polynomials.
Abstract: The Kirchhoff Matrix Tree Theorem provides an efficient algorithm for determiningt(G), the number of spanning trees of any graphG, in terms of a determinant. However for many special classes of graphs, one can avoid the evaluation of a determinant, as there are simple, explicit formulas that give the value oft(G). In this work we show that many of these formulas can be simply derived from known properties of Chebyshev polynomials. This is demonstrated for wheels, fans, ladders, Moebius ladders, and squares of cycles. The method is then used to derive a new spanning tree formula for the complete prismR
n
(m) =K
m
×C
n
. It is shown that
$$2^{\left( {\begin{array}{*{20}c} n \\ 2 \\ \end{array} } \right)\left( {1 - \frac{1}{{r - 1}} + o\left( 1 \right)} \right)} $$
whereT
n
(x) is then
th order Chebyshev polynomial of the first kind.
99 citations
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TL;DR: In this article, oil-impregnated nanoporous anodic aluminum oxide (AAO) layers are investigated to overcome the limitation of current passivation techniques for preventing corrosion, which is the lack of ability to withstand any external damages or local defects.
Abstract: The major drawback of current passivation techniques for preventing corrosion is the lack of ability to withstand any external damages or local defects. In this study, oil-impregnated nanoporous anodic aluminum oxide (AAO) layers are investigated to overcome such limitations and thus advance corrosion protection. By completely filling hydrophobized nanopores with oil via a solvent exchange method, a highly water-repellent surface that prevents the penetration of corrosive media into the AAO layer and hence the corrosion of aluminum is achieved. The impregnation of oil into the hydrophobic nanoporous AAO layer enhances the corrosion resistance of an AAO layer by two and four orders of magnitude compared to that of a hydrophobic (i.e., air-entrained) and a bare (hydrophilic) AAO, respectively. In the presence of local defects, the oil impregnated within the hydrophobic nanoporous AAO layer naturally permeates into the defects and ultimately inhibits the exposure of the aluminum surface to corrosive media. Whereas the corrosion current density of the air-entrained hydrophobic AAO layer increases by more than 30 times after cracks, that of the oil-impregnated AAO layer increases by no more than 4 times, showing superior anticorrosion property even after there are cracks, owing to the effective self-healing capability.
99 citations
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TL;DR: In this article, the stability of Poiseuille flow in a pipe of circular cross-section to azimuthally varying as well as axisymmetric disturbances has been studied.
Abstract: The stability of Poiseuille flow in a pipe of circular cross-section to azimuthally varying as well as axisymmetric disturbances has been studied. The perturbation velocity and pressure were expanded in a complete set of orthonormal functions which satisfy the boundary conditions. Truncating the expansion yielded a matrix differential equation for the time dependence of the expansion coefficients. The stability characteristics were determined from the eigenvalues of the matrix, which were calculated numerically. Calculations were carried out for the azimuthal wavenumbers n = 0,…, 5, axial wavenumbers α between 0·1 and 10·0 and αR [les ] 50000, R being the Reynolds number. Our results show that pipe flow is stable to infinitesimal disturbances for all values of α, R and n in these ranges.
99 citations
Authors
Showing all 5536 results
Name | H-index | Papers | Citations |
---|---|---|---|
Paul M. Thompson | 183 | 2271 | 146736 |
Roger Jones | 138 | 998 | 114061 |
Georgios B. Giannakis | 137 | 1321 | 73517 |
Li-Jun Wan | 113 | 639 | 52128 |
Joel L. Lebowitz | 101 | 754 | 39713 |
David Smith | 100 | 994 | 42271 |
Derong Liu | 77 | 608 | 19399 |
Robert R. Clancy | 77 | 293 | 18882 |
Karl H. Schoenbach | 75 | 494 | 19923 |
Robert M. Gray | 75 | 371 | 39221 |
Jin Yu | 74 | 480 | 32123 |
Sheng Chen | 71 | 688 | 27847 |
Hui Wu | 71 | 347 | 19666 |
Amir H. Gandomi | 67 | 375 | 22192 |
Haibo He | 66 | 482 | 22370 |