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A nanoparticle convective directed assembly process for the fabrication of periodic surface enhanced Raman spectroscopy substrates

Summary

A highly scalable approach for producing surface-enhanced Raman spectroscopy substrates is introduced. The novel method involves assembling individual nanoparticles in pre-defined templates, one particle per template, forming a high denisity of nanogaps over large areas, while decoupling nanostructure synthesis from placement.
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Summary

A highly scalable approach for producing surface-enhanced Raman spectroscopy substrates is introduced. The novel method involves assembling individual nanoparticles in pre-defined templates, one particle per template, forming a high denisity of nanogaps over large areas, while decoupling nanostructure synthesis from placement.

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Robustness of optimized collision avoidance logic to modeling errors

Published in:
29th Digital Avionics System Conf., 3-7 October 2010.

Summary

Collision avoidance systems, whether for manned or unmanned aircraft, must reliably prevent collision while minimizing alerts. Deciding what action to execute at a particular instant may be framed as a multiple-objective optimization problem that can be solved offline by computers. Prior work has explored methods of efficiently computing the optimal collision avoidance logic from a probabilistic model of aircraft behavior and a cost function. One potential concern with using a probabilistic model to construct the logic is that the model may not adequately represent the real world. Inaccuracies in the model could lead to vulnerabilities in the system when deployed. This paper evaluates the robustness of collision avoidance optimization to modeling errors.
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Summary

Collision avoidance systems, whether for manned or unmanned aircraft, must reliably prevent collision while minimizing alerts. Deciding what action to execute at a particular instant may be framed as a multiple-objective optimization problem that can be solved offline by computers. Prior work has explored methods of efficiently computing the optimal...

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A statistical learning approach to the modeling of aircraft taxi time

Published in:
29th Digital Avionics Systems Conf., 3 October 2010.

Summary

Modeling aircraft taxi operations is an important element in understanding current airport performance and where opportunities may lie for improvements. A statistical learning approach to modeling aircraft taxi time is presented in this paper. This approach allows efficient identification of relatively simple and easily interpretable models of aircraft taxi time, which are shown to yield remarkably accurate predictions when tested on actual data.
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Summary

Modeling aircraft taxi operations is an important element in understanding current airport performance and where opportunities may lie for improvements. A statistical learning approach to modeling aircraft taxi time is presented in this paper. This approach allows efficient identification of relatively simple and easily interpretable models of aircraft taxi time...

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Hogs and slackers: using operations balance in a genetic algorithm to optimize sparse algebra computation on distributed architectures

Published in:
Parallel Comput., Vol. 36, No. 10-11, October-November 2010, pp. 635-644.

Summary

We present a framework for optimizing the distributed performance of sparse matrix computations. These computations are optimally parallelized by distributing their operations across processors in a subtly uneven balance. Because the optimal balance point depends on the non-zero patterns in the data, the algorithm, and the underlying hardware architecture, it is difficult to determine. The Hogs and Slackers genetic algorithm (GA) identifies processors with many operations - hogs, and processors with few operations - slackers. Its intelligent operation-balancing mutation operator swaps data blocks between hogs and slackers to explore new balance points. We show that this operator is integral to the performance of the genetic algorithm and use the framework to conduct an architecture study that varies network specifications. The Hogs and Slackers GA is itself a parallel algorithm with near linear speedup on a large computing cluster.
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Summary

We present a framework for optimizing the distributed performance of sparse matrix computations. These computations are optimally parallelized by distributing their operations across processors in a subtly uneven balance. Because the optimal balance point depends on the non-zero patterns in the data, the algorithm, and the underlying hardware architecture, it...

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Graph-embedding for speaker recognition

Published in:
INTERSPEECH 2010, 11th Annual Conference of the International Speech Communication Association, 26-30 September 2010, pp. 2742-2745.

Summary

Popular methods for speaker classification perform speaker comparison in a high-dimensional space, however, recent work has shown that most of the speaker variability is captured by a low-dimensional subspace of that space. In this paper we examine whether additional structure in terms of nonlinear manifolds exist within the high-dimensional space. We will use graph embedding as a proxy to the manifold and show the use of the embedding in data visualization and exploration. ISOMAP will be used to explore the existence and dimension of the space. We also examine whether the manifold assumption can help in two classification tasks: data-mining and standard NIST speaker recognition evaluations (SRE). Our results show that the data lives on a manifold and that exploiting this structure can yield significant improvements on the data-mining task. The improvement in preliminary experiments on all trials of the NIST SRE Eval-06 core task are less but significant.
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Summary

Popular methods for speaker classification perform speaker comparison in a high-dimensional space, however, recent work has shown that most of the speaker variability is captured by a low-dimensional subspace of that space. In this paper we examine whether additional structure in terms of nonlinear manifolds exist within the high-dimensional space...

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Field & (data) stream: a method for functional evolution of the Air Traffic Management Route Availability Planning Tool (RAPT)

Published in:
HFES 2010, Proc. of the 54th Human Factors and Ergonomics Society Annual Mtg., 27 September 2010, pp. 104-108.

Summary

A method coupling field evaluation with operations data analysis is presented as an effective means to functionally evolve a decision support system. The case study used to illustrate this method is the evaluation of the Route Availability Planning Tool (RAPT), a decision support tool to improve departure efficiency in convective weather in New York air traffic facilities. It was only through a combination of quantitative performance data analysis and field observations to identify key elements of the decision making process that the designers were able to determine the most critical departure management decision requiring support, leading to significant improvements in departure efficiency.
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Summary

A method coupling field evaluation with operations data analysis is presented as an effective means to functionally evolve a decision support system. The case study used to illustrate this method is the evaluation of the Route Availability Planning Tool (RAPT), a decision support tool to improve departure efficiency in convective...

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Simple and efficient speaker comparison using approximate KL divergence

Published in:
INTERSPEECH 2010, 11th Annual Conference of the International Speech Communication Association, 26-30 September 2010, pp. 362-365.

Summary

We describe a simple, novel, and efficient system for speaker comparison with two main components. First, the system uses a new approximate KL divergence distance extending earlier GMM parameter vector SVM kernels. The approximate distance incorporates data-dependent mixture weights as well as the standard MAP-adapted GMM mean parameters. Second, the system applies a weighted nuisance projection method for channel compensation. A simple eigenvector method of training is presented. The resulting speaker comparison system is straightforward to implement and is computationally simple? only two low-rank matrix multiplies and an inner product are needed for comparison of two GMM parameter vectors. We demonstrate the approach on a NIST 2008 speaker recognition evaluation task. We provide insight into what methods, parameters, and features are critical for good performance.
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Summary

We describe a simple, novel, and efficient system for speaker comparison with two main components. First, the system uses a new approximate KL divergence distance extending earlier GMM parameter vector SVM kernels. The approximate distance incorporates data-dependent mixture weights as well as the standard MAP-adapted GMM mean parameters. Second, the...

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Multi-pitch estimation by a joint 2-D representation of pitch and pitch dynamics

Published in:
INTERSPEECH 2010, 11th Annual Conference of the International Speech Communication Association, 26-30 September 2010, pp. 645-648.

Summary

Multi-pitch estimation of co-channel speech is especially challenging when the underlying pitch tracks are close in pitch value (e.g., when pitch tracks cross). Building on our previous work, we demonstrate the utility of a two-dimensional (2-D) analysis method of speech for this problem by exploiting its joint representation of pitch and pitch-derivative information from distinct speakers. Specifically, we propose a novel multi-pitch estimation method consisting of 1) a data-driven classifier for pitch candidate selection, 2) local pitch and pitch-derivative estimation by k-means clustering, and 3) a Kalman filtering mechanism for pitch tracking and assignment. We evaluate our method on a database of all-voiced speech mixtures and illustrate its capability to estimate pitch tracks in cases where pitch tracks are separate and when they are close in pitch value (e.g., at crossings).
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Summary

Multi-pitch estimation of co-channel speech is especially challenging when the underlying pitch tracks are close in pitch value (e.g., when pitch tracks cross). Building on our previous work, we demonstrate the utility of a two-dimensional (2-D) analysis method of speech for this problem by exploiting its joint representation of pitch...

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Transcript-dependent speaker recognition using mixer 1 and 2

Published in:
INTERSPEECH 2010, 11th Annual Conference of the International Speech Communication Association, 26-30 September 2010, pp. 2102-2015.

Summary

Transcript-dependent speaker-recognition experiments are performed with the Mixer 1 and 2 read-transcription corpus using the Lincoln Laboratory speaker recognition system. Our analysis shows how widely speaker-recognition performance can vary on transcript-dependent data compared to conversational data of the same durations, given enrollment data from the same spontaneous conversational speech. A description of the techniques used to deal with the unaudited data in order to create 171 male and 198 female text-dependent experiments from the Mixer 1 and 2 read transcription corpus is given.
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Summary

Transcript-dependent speaker-recognition experiments are performed with the Mixer 1 and 2 read-transcription corpus using the Lincoln Laboratory speaker recognition system. Our analysis shows how widely speaker-recognition performance can vary on transcript-dependent data compared to conversational data of the same durations, given enrollment data from the same spontaneous conversational speech. A...

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A decision-theoretic approach to developing robust collision avoidance logic

Published in:
2010 13th Int. IEEE Annual Conf. on Intelligent Transportation Systems, 19-22 September 2010, pp. 1837-1842.

Summary

All large transport aircraft are required to be equipped with a collision avoidance system that instructs pilots how to maneuver to avoid collision with other aircraft. The uncertainty in the behavior of the intruding aircraft makes developing a robust collision avoidance logic challenging. This paper presents an automated approach for optimizing collision avoidance logic based on probabilistic models of aircraft behavior and a performance metric that balances the competing objectives of maximizing safety and minimizing alert rate. The approach involves framing the problem of collision avoidance as a Markov decision process that is solved using dynamic programming. Although this paper focuses on airborne collision avoidance for manned aircraft, the methods may be applied to collision avoidance for other categories of vehicles, both manned and unmanned.
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Summary

All large transport aircraft are required to be equipped with a collision avoidance system that instructs pilots how to maneuver to avoid collision with other aircraft. The uncertainty in the behavior of the intruding aircraft makes developing a robust collision avoidance logic challenging. This paper presents an automated approach for...

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