Institution
North Carolina State University
Education•Raleigh, North Carolina, United States•
About: North Carolina State University is a education organization based out in Raleigh, North Carolina, United States. It is known for research contribution in the topics: Population & Thin film. The organization has 44161 authors who have published 101744 publications receiving 3456774 citations. The organization is also known as: NCSU & North Carolina State University at Raleigh.
Topics: Population, Thin film, Gene, Context (language use), Computer science
Papers published on a yearly basis
Papers
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TL;DR: The theory-guided data science (TGDS) paradigm as mentioned in this paper is an emerging paradigm that aims to leverage the wealth of scientific knowledge for improving the effectiveness of data science models in enabling scientific discovery.
Abstract: Data science models, although successful in a number of commercial domains, have had limited applicability in scientific problems involving complex physical phenomena. Theory-guided data science (TGDS) is an emerging paradigm that aims to leverage the wealth of scientific knowledge for improving the effectiveness of data science models in enabling scientific discovery. The overarching vision of TGDS is to introduce scientific consistency as an essential component for learning generalizable models. Further, by producing scientifically interpretable models, TGDS aims to advance our scientific understanding by discovering novel domain insights. Indeed, the paradigm of TGDS has started to gain prominence in a number of scientific disciplines such as turbulence modeling, material discovery, quantum chemistry, bio-medical science, bio-marker discovery, climate science, and hydrology. In this paper, we formally conceptualize the paradigm of TGDS and present a taxonomy of research themes in TGDS. We describe several approaches for integrating domain knowledge in different research themes using illustrative examples from different disciplines. We also highlight some of the promising avenues of novel research for realizing the full potential of theory-guided data science.
532 citations
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24 Apr 2000TL;DR: The notion of a trust negotiation strategy is introduced and examined with respect to an abstract model of trust negotiation, and a language of credential expressions is presented.
Abstract: Distributed software subjects face the problem of determining one another's trustworthiness. The problem considered is managing the exchange of credentials between strangers for the purpose of property-based authentication and authorization when credentials are sensitive. An architecture for trust negotiation between client and server is presented. The notion of a trust negotiation strategy is introduced and examined with respect to an abstract model of trust negotiation. Two strategies with very different properties are defined and analyzed. A language of credential expressions is presented, with two example negotiations illustrating the two negotiation strategies. Ongoing work on policies governing credential disclosure and trust negotiation is summarized.
531 citations
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TL;DR: A new class of multidimensional representation systems, called shearlets, obtained by applying the actions of dilation, shear transformation and translation to a fixed function, and exhibit the geometric and mathematical properties, e.g., directionality, elongated shapes, scales, oscillations are described.
Abstract: In this paper we describe a new class of multidimensional
representation systems, called shearlets. They are obtained by
applying the actions of dilation, shear transformation and
translation to a fixed function, and exhibit the geometric and
mathematical properties, e.g., directionality, elongated shapes,
scales, oscillations, recently advocated by many authors for
sparse image processing applications. These systems can be studied
within the framework of a generalized multiresolution analysis.
This approach leads to a recursive algorithm for the
implementation of these systems, that generalizes the classical
cascade algorithm.
530 citations
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TL;DR: In this paper, the authors evaluate daily price linkages among four corn and four soybean markets in North Carolina and find strong support for market integration, though adjustments following shocks may take many days to be complete.
Abstract: A large body of research has evaluated price linkages in spatially separate markets. Much recent research has applied models appropriate for nonstationary data. Such analyses have been criticized for their ignorance of transactions costs, which may inhibit price adjustments and thus affect tests of integration. This analysis utilizes threshold autoregression and cointegration models to account for a neutral band representing transactions costs. We evaluate daily price linkages among four corn and four soybean markets in North Carolina. Nonlinear impulse response functions are used to investigate dynamic patterns of adjustments to shocks. Our results confirm the presence of thresholds and indicate strong support for market integration, though adjustments following shocks may take many days to be complete. In every case, the threshold models suggest much faster adjustments in response to deviations from equilibrium than is the case when threshold behavior is ignored. A large amount of empirical research has evaluated the extent to which spatially separate markets are integrated. Though the term is used loosely in the literature, tests of “market integration” usually consider the extent to which shocks are transmitted among spatially separate markets. The integration of markets can have important implications for price discovery and the operation of the market since persistent deviations from integration may imply riskless profit opportunities for spatial traders.
529 citations
Authors
Showing all 44525 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yi Cui | 220 | 1015 | 199725 |
Jing Wang | 184 | 4046 | 202769 |
Rodney S. Ruoff | 164 | 666 | 194902 |
Carlos Bustamante | 161 | 770 | 106053 |
David W. Johnson | 160 | 2714 | 140778 |
Joseph Wang | 158 | 1282 | 98799 |
David Tilman | 158 | 340 | 149473 |
Jay Hauser | 155 | 2145 | 132683 |
James M. Tour | 143 | 859 | 91364 |
Joseph T. Hupp | 141 | 731 | 82647 |
Bin Liu | 138 | 2181 | 87085 |
Rudolph E. Tanzi | 135 | 638 | 85376 |
Richard C. Boucher | 129 | 490 | 54509 |
David B. Allison | 129 | 836 | 69697 |
Robert W. Heath | 128 | 1049 | 73171 |