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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: Theoretical analysis proves that REA can provide less erroneous prediction results than a comparative algorithm and empirical study on both synthetic benchmarks and real-world data set is applied to validate effectiveness of REA as compared with other algorithms in terms of evaluation metrics.
Abstract: Difficulties of learning from nonstationary data stream are generally twofold. First, dynamically structured learning framework is required to catch up with the evolution of unstable class concepts, i.e., concept drifts. Second, imbalanced class distribution over data stream demands a mechanism to intensify the underrepresented class concepts for improved overall performance. To alleviate the challenges brought by these issues, we propose the recursive ensemble approach (REA) in this paper. To battle against the imbalanced learning problem in training data chunk received at any timestamp t, i.e., $${{\mathcal{S}}_t,}$$ REA adaptively pushes into $${{\mathcal{S}}_t}$$ part of minority class examples received within [0, t − 1] to balance its skewed class distribution. Hypotheses are then progressively developed over time for all balanced training data chunks and combined together as an ensemble classifier in a dynamically weighted manner, which therefore addresses the concept drifts issue in time. Theoretical analysis proves that REA can provide less erroneous prediction results than a comparative algorithm. Besides that, empirical study on both synthetic benchmarks and real-world data set is also applied to validate effectiveness of REA as compared with other algorithms in terms of evaluation metrics consisting of overall prediction accuracy and ROC curve.

126 citations

Journal ArticleDOI
TL;DR: The authors explored the antecedent factors that impact new product development team stability as well as its consequences and found that the most direct antecedents of team stability are goal stability and goal support.
Abstract: Group member change or team stability is a popular and important topic in the group and organizational behavior literature. Team member stability is viewed as a critical factor for an effectively functioning and performing group. Even though there is a plethora of studies on group member change and stability, research on member stability in cross-functional new product development teams is still lacking. This study explores the antecedent factors that impact new product development team stability as well as its consequences. By studying 211 new product teams, we found: (1) the most direct antecedents of team stability are goal stability and goal support; and (2) team stability has a significantly positive effect on outcome variables including team learning and cycle time. This study also shows that team stability may not be universally good; under some circumstances, such as when there is a high degree of market and technical turbulence, team instability can be advantageous.

126 citations

Journal ArticleDOI
TL;DR: The numerical results strongly support the conclusion that maximal ratio combining of channel diversity can enhance the security of the wireless communication system in normal operating scenarios.
Abstract: In this paper, we present a method of utilizing channel diversity to increase secrecy capacity in wireless communication. With the presence of channel diversity, an intended receiver can achieve a relatively high secrecy capacity even at low SNRs. We present a theoretical analysis on the outage probability at a normalized target secrecy capacity in Rayleigh fading environment. Our numerical results strongly support our conclusion that maximal ratio combining of channel diversity can enhance the security of the wireless communication system in normal operating scenarios.

126 citations

Posted Content
TL;DR: A significant shift in IT priorities first captured in 2009 continues: IT organizations are working aggressively and closely with their business partners to identify opportunities to reduce costs and improve productivity across the company through IT initiatives.
Abstract: While the recession has officially been declared as ending during the past summer, the prolonged economic conundrum continues to pose new challenges to organizations around the world. The past year has shown some increase in IT investments, yet IT executives continue to proceed cautiously and predict incremental improvements in 2011; there is no anticipated dramatic return to the growth levels that preceded the recession.However, a significant shift in IT priorities first captured in 2009 continues: IT organizations are working aggressively and closely with their business partners to identify opportunities to reduce costs and improve productivity across the company through IT initiatives. This phenomenon is very different from previous recessions where IT budgets were typically the first to be cut.Since its inception in 1980, the Society for Information Management (SIM) survey has helped IT leaders around the globe understand important issues and trends. This article presents the major findings based on survey responses from 172 U.S. organizations in mid-2010. The top five management concerns were: 1. Business productivity and cost reduction; 2. Business agility and speed to market; 3. IT and business alignment; 4. IT reliability and efficiency; 5. Business process re-engineering.This is the fifth in a series of MISQE-published reports based on a SIM membership survey facilitated by the lead author. As in previous reports, this article also presents findings on key application and technology developments, and various aspects of the IT organization. In addition, similarities and differences between the U.S. results and those from similar samples of European and Asian/Australian organizations provide a more global perspective.

125 citations

Journal ArticleDOI
TL;DR: In this paper, a two-stage compressed sensing method for mmWave channel estimation is proposed, where the sparse and low-rank properties are respectively utilized in two consecutive stages, namely, a matrix completion stage and a sparse recovery stage.
Abstract: We consider the problem of channel estimation for millimeter wave (mmWave) systems, where, to minimize the hardware complexity and power consumption, an analog transmit beamforming and receive combining structure with only one radio frequency chain at the base station and mobile station is employed. Most existing works for mmWave channel estimation exploit sparse scattering characteristics of the channel. In addition to sparsity, mmWave channels may exhibit angular spreads over the angle of arrival, angle of departure, and elevation domains. In this paper, we show that angular spreads give rise to a useful low-rank structure that, along with the sparsity, can be simultaneously utilized to reduce the sample complexity, i.e., the number of samples needed to successfully recover the mmWave channel. Specifically, to effectively leverage the joint sparse and low-rank structure, we develop a two-stage compressed sensing method for mmWave channel estimation, where the sparse and low-rank properties are respectively utilized in two consecutive stages, namely, a matrix completion stage and a sparse recovery stage. Our theoretical analysis reveals that the proposed two-stage scheme can achieve a lower sample complexity than a conventional compressed sensing method that exploits only the sparse structure of the mmWave channel. Simulation results are provided to corroborate our theoretical results and to show the superiority of the proposed two-stage method.

125 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