Institution
Mitre Corporation
Company•Bedford, Massachusetts, United States•
About: Mitre Corporation is a company organization based out in Bedford, Massachusetts, United States. It is known for research contribution in the topics: Air traffic control & National Airspace System. The organization has 4884 authors who have published 6053 publications receiving 124808 citations. The organization is also known as: Mitre & MITRE.
Topics: Air traffic control, National Airspace System, Information system, Air traffic management, Communications system
Papers published on a yearly basis
Papers
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01 Jan 2003TL;DR: The work described here is focused on measuring the uncertainty in sector demand predictions under current operational conditions, and on applying those measurements towards improving the performance and human factors of TFM decision support systems.
Abstract: Traffic flow management (TFM) in the U.S. is the process by which the Federal Aviation Administration (FAA), with the participation of airspace users, seeks to balance the capacity of airspace and airport resources with the demand for these resources. This is a difficult process, complicated by the presence of severe weather or unusually high demand. TFM in en-route airspace is concerned with managing airspace demand, specifically the number of flights handled by air traffic control (ATC) sectors; a sector is the volume of airspace managed by an air traffic controller or controller team. Therefore, effective decision-making requires accurate sector demand predictions. While it is commonly accepted that the sector demand predictions used by current and proposed TFM decision support systems contain significant uncertainty, this uncertainty is typically not quantified or taken into account in any meaningful way. The work described here is focused on measuring the uncertainty in sector demand predictions under current operational conditions, and on applying those measurements towards improving the performance and human factors of TFM decision support systems.
73 citations
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TL;DR: The architecture for a radix- R fast Fourier transform algorithm using a residue number system over Z[\omega] , where \omega is a primitive R th root of unity, is developed; and range and error estimates for this algorithm are derived.
Abstract: A new method is described for computing an N = R^{m} = 2^{\upsilon m} -point complex discrete Fourier transform that uses quantization within a dense ring of algebraic integers in conjunction with a residue number system over this ring The algebraic and analytic foundations for the technique are derived and discussed The architecture for a radix- R fast Fourier transform algorithm using a residue number system over Z[\omega] , where \omega is a primitive R th root of unity, is developed; and range and error estimates for this algorithm are derived
73 citations
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TL;DR: No-reference image quality measures, which quantify quality inherent to a single image, are assessed, finding two families of quality measure that were most effective: one based on Natural Scene Statistics and one originally developed to measure distortion caused by image compression.
Abstract: Neuroimagery must be visually checked for unacceptable levels of distortion prior to processing. However, inspection is time-consuming, unreliable for detecting subtle distortions and often subjective. With the increasing volume of neuroimagery, objective measures of quality are needed in order to automate screening. To address this need, we have assessed the effectiveness of no-reference image quality measures, which quantify quality inherent to a single image. A data set of 1001 magnetic resonance images (MRIs) recorded from 143 subjects was used for this evaluation. The MRI images were artificially distorted with two levels of either additive Gaussian noise or intensity nouniformity created from a linear model. A total of 239 different quality measures were defined from seven overall families and used to discriminate images for the type and level of distortion. Analysis of Variance identified two families of quality measure that were most effective: one based on Natural Scene Statistics and one originally developed to measure distortion caused by image compression. Measures from both families reliably discriminated among undistorted images, noisy images, and images distorted by intensity nonuniformity. The best quality measures were sensitive only to the distortion category and were not significantly affected by other factors. The results are encouraging enough that several quality measures are being incorporated in a real world MRI test bed.
73 citations
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TL;DR: In this paper, a national traffic flow management (TFM) strategy that reduces both congestion and delay in the National Airspace System (NAS) is proposed to reduce both traffic growth and changes in traffic patterns.
Abstract: Traffic growth and changes in traffic patterns have caused increasing congestion and delay in the National Airspace System (NAS). A national traffic flow management (TFM) strategy that reduces both...
72 citations
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01 Mar 1995TL;DR: This paper introduces two more detailed studies on VLISP and summarizes the basic techniques that were used repeatedly throughout the effort, presenting scientific conclusions about the applicability of the these techniques as well as engineering conclusion about the crucial choices that allowed the verification to succeed.
Abstract: The VLISP project showed how to produce a comprehensively verified implementation for a programming language, namely Scheme. This paper introduces two more detailed studies on VLISP [13, 21]. It summarizes the basic techniques that were used repeatedly throughout the effort. It presents scientific conclusions about the applicability of the these techniques as well as engineering conclusions about the crucial choices that allowed the verification to succeed.
72 citations
Authors
Showing all 4896 results
Name | H-index | Papers | Citations |
---|---|---|---|
Sushil Jajodia | 101 | 664 | 35556 |
Myles R. Allen | 82 | 295 | 32668 |
Barbara Liskov | 76 | 204 | 25026 |
Alfred D. Steinberg | 74 | 295 | 20974 |
Peter T. Cummings | 69 | 521 | 18942 |
Vincent H. Crespi | 63 | 287 | 20347 |
Michael J. Pazzani | 62 | 183 | 28036 |
David Goldhaber-Gordon | 58 | 192 | 15709 |
Yeshaiahu Fainman | 57 | 648 | 14661 |
Jonathan Anderson | 57 | 195 | 10349 |
Limsoon Wong | 55 | 367 | 13524 |
Chris Clifton | 54 | 160 | 11501 |
Paul Ward | 52 | 408 | 12400 |
Richard M. Fujimoto | 52 | 290 | 13584 |
Bhavani Thuraisingham | 52 | 563 | 10562 |