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Institution

Stevens Institute of Technology

EducationHoboken, 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: Cognitive radio & Wireless network. The organization has 5440 authors who have published 12684 publications receiving 296875 citations. The organization is also known as: Stevens & Stevens Tech.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors explore under which circumstances an autonomous team is the best choice for new product development (NPD), based on contingency and information-processing theories, and the relative effectiveness of four types of team structures: autonomous, functional, lightweight, and heavyweight are compared.

82 citations

Journal ArticleDOI
TL;DR: The present review compares the similarities and differences in cellular response at the molecular level as tumor cells enter EMT or as keratinocytes begin the process of re-epithelialization of a wound.

82 citations

Journal ArticleDOI
TL;DR: This approach, involving ROS-responsive drug release, together with the identification of the target and mechanism of action of Rg3, provided an effective strategy for treating ischemic diseases and oxidative stress and could accelerate the implementation of hydrophobic natural products in clinical applications.

82 citations

Proceedings ArticleDOI
02 Jun 2014
TL;DR: This work investigates using smartphone WiFi signals to track human queues, which are common in many business areas such as retail stores, airports, and theme parks, and shows that in spite of noisy signal readings, the methods can measure service and waiting times to within a $10$ second resolution.
Abstract: We investigate using smartphone WiFi signals to track human queues, which are common in many business areas such as retail stores, airports, and theme parks. Real-time monitoring of such queues would enable a wealth of new applications, such as bottleneck analysis, shift assignments, and dynamic workflow scheduling. We take a minimum infrastructure approach and thus utilize a single monitor placed close to the service area along with transmitting phones. Our strategy extracts unique features embedded in signal traces to infer the critical time points when a person reaches the head of the queue and finishes service, and from these inferences we derive a person's waiting and service times. We develop two approaches in our system, one is directly feature-driven and the second uses a simple Bayesian network. Extensive experiments conducted both in the laboratory as well as in two public facilities demonstrate that our system is robust to real-world environments. We show that in spite of noisy signal readings, our methods can measure service and waiting times to within a $10$ second resolution.

82 citations

Journal ArticleDOI
TL;DR: In this paper, the secondary flow of an incompressible viscous fluid in a curved duct is studied by using a finite-volume method, and it is shown that as the Dean number is increased, secondary flow structure evolves into a double vortex pair for low-aspect-ratio ducts and roll cells for ducts of high aspect ratio.
Abstract: The occurrence of secondary flow in curved ducts due to the centrifugal forces can often significantly influence the flow rate. In the present work, the secondary flow of an incompressible viscous fluid in a curved duct is studied by using a finite-volume method. It is shown that as the Dean number is increased the secondary flow structure evolves into a double vortex pair for low-aspect-ratio ducts and roll cells for ducts of high aspect ratio. A stability diagram is obtained in the domain of curvature ratio and Reynolds number. It is found that for ducts of high curvature the onset of transition from single vortex pair to double vortex pair or roll cells depends on the Dean number and the curvature ratio, while for ducts of small curvature the onset can be characterized by the Dean number alone. A comparison with the available theoretical and experimental results indicates good agreement. A correlation for the friction factor as a function of the Dean number and aspect ratio is developed and is found to be in good agreement with the available experimental and computational results for a wide range of parameters.

82 citations


Authors

Showing all 5536 results

NameH-indexPapersCitations
Paul M. Thompson1832271146736
Roger Jones138998114061
Georgios B. Giannakis137132173517
Li-Jun Wan11363952128
Joel L. Lebowitz10175439713
David Smith10099442271
Derong Liu7760819399
Robert R. Clancy7729318882
Karl H. Schoenbach7549419923
Robert M. Gray7537139221
Jin Yu7448032123
Sheng Chen7168827847
Hui Wu7134719666
Amir H. Gandomi6737522192
Haibo He6648222370
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202342
2022139
2021765
2020820
2019799
2018563