scispace - formally typeset
Search or ask a question
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
More filters
Journal IssueDOI
TL;DR: How three systems of types well known to systems engineers can be understood as complex systems are shown, based on a variety of sources, and the application of complex systems to one of the examples is shown.
Abstract: This paper shows how three systems of types well known to systems engineers can be understood as complex systems. This is important because research in complex systems sciences is vibrant and provides critical insight, but if systems engineers do not understand the complex aspects of the systems they work with daily, they may not be able to use these research results. To date, systems engineering has been looking only at exploiting the “order” side of the order-to-chaos spectrum, and it is time now to understand and begin to utilize principles from the middle and from the chaos side of the spectrum. Three complex systems examples are INCOSE, the systems engineering process (such as a company's standard process), and air traffic control. INCOSE represents most volunteer organizations and social groups. Most systems engineers do not realize that the systems engineering process for a company is a network that can be studied by complex systems methods. Air traffic control may come closest to many systems engineers' definition of a system. This paper provides principles of complex systems based on a variety of sources, and shows the application of complex systems to one of the examples. © 2008 Wiley Periodicals, Inc. Syst Eng

143 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examined the effects of peer feedback on subsequent behavior using a four-dimensional model of team behavior and found that participants rated themselves and each other using a 24-item behavioral observation scale after completing the first of two decision-making tasks.
Abstract: We examined the effects of peer feedback on subsequent behavior using a four-dimensional model of team behavior. Participants (N= 75) were randomly assigned to teams, and teams were randomly assigned to one of three experimental conditions: feedback, exposure, or control. In the feedback condition, participants rated themselves and each other using a 24-item behavioral observation scale after completing the first of two decison-making tasks. Before performing the second task, they received individualized feedback reports summarizing their self- and peer ratings. Those assigned to the exposure condition completed the behavioral observation scale after the first task but did not receive feedback. The second task was videotaped and rated by experts blind to experimental condition. Results showed significantly higher ratings for participants in the feedback and exposure conditions. The findings extend previous research on multisource feed-back by isolating exposure to key behaviors as an important variable in...

143 citations

Proceedings ArticleDOI
07 Aug 2006
TL;DR: It is argued that most of the proposed work is at an early stage and there is still a long way to go before a middleware that fully meets the wide variety of WSN requirements is achieved.
Abstract: Given the fast growing technological progress in microelectronics and wireless communication devices, in the near future, it is foreseeable that Wireless Sensor Networks (WSN) will offer and make possible a wide range of applications. However real world integration and application development on such networks composed of tiny, low power and limited resources devices are not easy. Therefore, middleware services are a novel approach offering many possibilities and drastically enhancing the application development on WSN. This survey shows the current state of research in this domain. It discusses middleware challenges in such networks and presents some representative middleware specifically designed for WSN. The selection of the studied methods tries to cover as many views of objectives and approaches as possible. We will focus on discovering similarities and differences by making classifications, comparisons and appropriateness studies. At the end we argue that most of the proposed work is at an early stage and there is still a long way to go before a middleware that fully meets the wide variety of WSN requirements is achieved.

143 citations

Journal ArticleDOI
TL;DR: Graphene-based conductive nanofibrous scaffolds are explored with the possibility of combining the conductive properties of graphene with electrospun nanofiber to create the electroactive biomimetic scaffolds for nerve tissue regeneration.

143 citations

Journal ArticleDOI
TL;DR: Incorporation of chitosan in PCL nanofibers not only improved the adhesion and proliferation of MC 3T3-E1 cells but also elevated calcium deposition, alkaline phosphatase (ALP) activity, and the expression of osteopontin (OPN) compared to PCL alone nan ofibers.

143 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
Network Information
Related Institutions (5)
Georgia Institute of Technology
119K papers, 4.6M citations

94% related

Nanyang Technological University
112.8K papers, 3.2M citations

92% related

Massachusetts Institute of Technology
268K papers, 18.2M citations

91% related

University of Maryland, College Park
155.9K papers, 7.2M citations

91% related

Purdue University
163.5K papers, 5.7M citations

91% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202342
2022139
2021765
2020820
2019799
2018563