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Convective weather avoidance modeling for low-altitude routes

Published in:
MIT Lincoln Laboratory Report ATC-376

Summary

Thunderstorms are a leading cause of delay in the National Airspace System (NAS), and significant research has been conducted to predict the areas pilots will avoid during a storm. An example of such research is the Convective Weather Avoidance Model (CWAM), which provides the likelihood of pilot deviation due to convective weather in a given area. This report extends the scope of CWAM to include low-altitude flights, which typically occur below the tops of convective weather and have slightly differentoperational constraints. In general, the set of low-altitude flights include short-hop routes and low-altitude escape routes used to reduce the impact of convective weather in the termnial area. For classification, low altitude flights are identified as either deviations or non-deviations, and the corresponding weather features are analyzed. Precipitation intensity is observed to be the best predictor of deviation in the low-altitude flight regime, as compared to the differenc ein altitude between the flight and the echo tops for en route flights. Additionally, the low-altitude CWAM performs better than the departure CWAM currently used in the Route Availability Planning Tool (RAPT) when tested on deterministic weather data.
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Summary

Thunderstorms are a leading cause of delay in the National Airspace System (NAS), and significant research has been conducted to predict the areas pilots will avoid during a storm. An example of such research is the Convective Weather Avoidance Model (CWAM), which provides the likelihood of pilot deviation due to...

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Estimation of potential IDRP benefits during convective weather SWAP

Published in:
MIT Lincoln Laboratory Report ATC-381

Summary

This document presents a preliminary analysis of potential departure delay reduction benefits in New York as the result of the use of the Integrated Departure Route Planning (IDRP) tool during convective severe weather avoidance programs (SWAP). The analysis is based on weather impact and air traffic data from operations between May and September 2010 in the New York metroplex region. Two methodologies were employed in the analysis: "flight pool" and "resource pool." In the flight pool methodology, individual flights with excessive taxi times were identified, and opportunities to find potential alternative reroutes using information that IDRP will provide were assessed. In the resource pool methodology, route impact minutes were tallied over several days, based on the judgment of a human analysis, and opportunities to recover capacity lost to route impacts via IDRP-identified reroutes were estimated. The flight pool methodology estimated that approximately 156 hours of delay could be saved through the use of IDRP over a full SWAP season. The resource pool methodology estimated that approximately 15% of capacity lost to convective weather impacts could be recovered via IDRP-based reroutes. It should be noted that the potential benefits are based on several assumptions that are described in detail in the text of the report. The estimation of delay savings due to reroute is also speculative. It is very difficult to ascertain when the assignment of a reroute actually makes use of underutilized capacity and when the reroute simply shifts the problem from one congested resource to another. Further research is needed to develop reliable metrics that can guide the assessment of reroute impacts on overall traffic management performance.
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Summary

This document presents a preliminary analysis of potential departure delay reduction benefits in New York as the result of the use of the Integrated Departure Route Planning (IDRP) tool during convective severe weather avoidance programs (SWAP). The analysis is based on weather impact and air traffic data from operations between...

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Making departure management weather impact models airspace-adaptable: adapting the New York Route Availability Planning Tool (RAPT) to Chicago departure airspace

Summary

The Route Availability Planning Tool (RAPT) operational prototype was deployed to Chicago in the summer of 2010, the first RAPT deployment outside of the New York departure airspace for which it was originally developed. The goal of the deployment was to evaluate the adaptability of RAPT's airspace definition, departure management and weather impact models to different terminal areas throughout the National Airspace System (NAS). This report presents the results of a summer-long evaluation of the Chicago RAPT operational prototype, in which the performance of RAPT algorithms and the effectiveness of the RAPT Concept of Operations were assessed. The evaluation included observations made by researchers simultaneously stationed at O'Hare terminal (ORD), the Chicago TRACON (C90), and the Chicago Air Route Traffic Control Center (ZAU) during several days of convective weather impact and post-event analysis of air traffic data from the Enhanced Traffic Management System (ETMS) and RAPT weather impact predictions and departure management guidance. The study found that significant departure delay reduction could be achieved through the use of RAPT in Chicago, and that RAPT effectiveness in "typical" corner post airspaces like Chicago could be further increased with some modifications to the Concept of Operations, user training, and site adaptation.
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Summary

The Route Availability Planning Tool (RAPT) operational prototype was deployed to Chicago in the summer of 2010, the first RAPT deployment outside of the New York departure airspace for which it was originally developed. The goal of the deployment was to evaluate the adaptability of RAPT's airspace definition, departure management...

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Uni-traveling-carrier variable confinement waveguide photodiodes

Summary

Uni-traveling-carrier waveguide photodiodes (PDs) with a variable optical confinement mode size transformer are demonstrated. The optical mode is large at the input for minimal front-end saturation and the mode transforms as the light propagates so that the absorption profile is optimized for both high-power and high-speed performance. Two differently designed PDs are presented. PD A demonstrates a 3-dB bandwidth of 12.6 GHz, and saturation currents of 40 mA at 1 GHz and 34 mA at 10 GHz. PD B demonstrates a 3-dB bandwidth of 2.5 GHz, a saturation current greater than 100 mA at 1 GHz, a peak RF output power of + 19 dBm, and a third-order output intercept point of 29.1 dBm at a photocurrent of 60 mA.
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Summary

Uni-traveling-carrier waveguide photodiodes (PDs) with a variable optical confinement mode size transformer are demonstrated. The optical mode is large at the input for minimal front-end saturation and the mode transforms as the light propagates so that the absorption profile is optimized for both high-power and high-speed performance. Two differently designed...

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Virtuoso: narrowing the semantic gap in virtual machine introspection

Published in:
2011 IEEE Symp. on Security and Privacy, 22-25 May 2011, pp. 297-312.

Summary

Introspection has featured prominently in many recent security solutions, such as virtual machine-based intrusion detection, forensic memory analysis, and low-artifact malware analysis. Widespread adoption of these approaches, however, has been hampered by the semantic gap: in order to extract meaningful information about the current state of a virtual machine, detailed knowledge of the guest operating system's inner workings is required. In this paper, we present a novel approach for automatically creating introspection tools for security applications with minimal human effort. By analyzing dynamic traces of small, in-guest programs that compute the desired introspection information, we can produce new programs that retrieve the same information from outside the guest virtual machine. We demonstrate the efficacy of our techniques by automatically generating 17 programs that retrieve security information across 3 different operating systems, and show that their functionality is unaffected by the compromise of the guest system. Our technique allows introspection tools to be effortlessly generated for multiple platforms, and enables the development of rich introspection-based security applications.
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Summary

Introspection has featured prominently in many recent security solutions, such as virtual machine-based intrusion detection, forensic memory analysis, and low-artifact malware analysis. Widespread adoption of these approaches, however, has been hampered by the semantic gap: in order to extract meaningful information about the current state of a virtual machine, detailed...

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A time-warping framework for speech turbulence-noise component estimation during aperiodic phonation

Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP, 22-27 May 2011, pp. 5404-5407.

Summary

The accurate estimation of turbulence noise affects many areas of speech processing including separate modification of the noise component, analysis of degree of speech aspiration for treating pathological voice, the automatic labeling of speech voicing, as well as speaker characterization and recognition. Previous work in the literature has provided methods by which such a high-quality noise component may be estimated in near-periodic speech, but it is known that these methods tend to leak aperiodic phonation (with even slight deviations from periodicity) into the noise-component estimate. In this paper, we improve upon existing algorithms in conditions of aperiodicity by introducing a time-warping based approach to speech noise-component estimation, demonstrating the results on both natural and synthetic speech examples.
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Summary

The accurate estimation of turbulence noise affects many areas of speech processing including separate modification of the noise component, analysis of degree of speech aspiration for treating pathological voice, the automatic labeling of speech voicing, as well as speaker characterization and recognition. Previous work in the literature has provided methods...

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Assessing the speaker recognition performance of naive listeners using Mechanical Turk

Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP, 22-27 May 2011, pp. 5916-5919.

Summary

In this paper we attempt to quantify the ability of naive listeners to perform speaker recognition in the context of the NIST evaluation task. We describe our protocol: a series of listening experiments using large numbers of naive listeners (432) on Amazon's Mechanical Turk that attempts to measure the ability of the average human listener to perform speaker recognition. Our goal was to compare the performance of the average human listener to both forensic experts and state-of-the- art automatic systems. We show that naive listeners vary substantially in their performance, but that an aggregation of listener responses can achieve performance similar to that of expert forensic examiners.
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Summary

In this paper we attempt to quantify the ability of naive listeners to perform speaker recognition in the context of the NIST evaluation task. We describe our protocol: a series of listening experiments using large numbers of naive listeners (432) on Amazon's Mechanical Turk that attempts to measure the ability...

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Informative dialect recognition using context-dependent pronunciation modeling

Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP, 22-27 May 2011, pp. 4396-4399.

Summary

We propose an informative dialect recognition system that learns phonetic transformation rules, and uses them to identify dialects. A hidden Markov model is used to align reference phones with dialect specific pronunciations to characterize when and how often substitutions, insertions, and deletions occur. Decision tree clustering is used to find context-dependent phonetic rules. We ran recognition tasks on 4 Arabic dialects. Not only do the proposed systems perform well on their own, but when fused with baselines they improve performance by 21-36% relative. In addition, our proposed decision-tree system beats the baseline monophone system in recovering phonetic rules by 21% relative. Pronunciation rules learned by our proposed system quantify the occurrence frequency of known rules, and suggest rule candidates for further linguistic studies.
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Summary

We propose an informative dialect recognition system that learns phonetic transformation rules, and uses them to identify dialects. A hidden Markov model is used to align reference phones with dialect specific pronunciations to characterize when and how often substitutions, insertions, and deletions occur. Decision tree clustering is used to find...

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NAP for high level language identification

Published in:
ICASSP 2011, IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, 22-27 May 2011, pp. 4392-4395.

Summary

Varying channel conditions present a difficult problem for many speech technologies such as language identification (LID). Channel compensation techniques have been shown to significantly improve performance in LID for acoustic systems. For high-level token systems, nuisance attribute projection (NAP) has been shown to perform well in the context of speaker identification. In this work, we describe a novel approach to dealing with the high dimensional sparse NAP training problem as applied to a 4-gram phonotactic LID system run on the NIST 2009 Language Recognition Evaluation (LRE) task. We demonstrate performance gains on the Voice of America (VOA) portion of the 2009 LRE data.
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Summary

Varying channel conditions present a difficult problem for many speech technologies such as language identification (LID). Channel compensation techniques have been shown to significantly improve performance in LID for acoustic systems. For high-level token systems, nuisance attribute projection (NAP) has been shown to perform well in the context of speaker...

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The MIT LL 2010 speaker recognition evaluation system: scalable language-independent speaker recognition

Published in:
Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, ICASSP, 22-27 May 2011, pp. 5272-5275.

Summary

Research in the speaker recognition community has continued to address methods of mitigating variational nuisances. Telephone and auxiliary-microphone recorded speech emphasize the need for a robust way of dealing with unwanted variation. The design of recent 2010 NIST-SRE Speaker Recognition Evaluation (SRE) reflects this research emphasis. In this paper, we present the MIT submission applied to the tasks of the 2010 NIST-SRE with two main goals--language-independent scalable modeling and robust nuisance mitigation. For modeling, exclusive use of inner product-based and cepstral systems produced a language-independent computationally-scalable system. For robustness, systems that captured spectral and prosodic information, modeled nuisance subspaces using multiple novel methods, and fused scores of multiple systems were implemented. The performance of the system is presented on a subset of the NIST SRE 2010 core tasks.
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Summary

Research in the speaker recognition community has continued to address methods of mitigating variational nuisances. Telephone and auxiliary-microphone recorded speech emphasize the need for a robust way of dealing with unwanted variation. The design of recent 2010 NIST-SRE Speaker Recognition Evaluation (SRE) reflects this research emphasis. In this paper, we...

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