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required. Roger worked closely with various Rockwell Collins
engineering departments and IDC management to establish
the initial flight management system and displays work packages
for the IDC.
“The engineering team has met
our expectations and challenges
in a number of avionics and
electronics related areas.
The IDC engineers provide value
to our projects and programs
and to the company overall.”
Roger French
Principal Engineering Manager
Rockwell Collins
Benefits
Today, it is clear that the IDC engineering team is motivated and highly
respectful of the quality that goes into Rockwell Collins aerospace
avionics, electronics and communications products. They are eager
to learn as much as possible from tenured Rockwell Collins engineers
about our products and systems and the processes we use to develop
them. Now Rockwell Collins Commercial Systems is able to give larger,
more complete segments of work to the IDC unlike when we contract
with outside engineering firms. And with cost effective IDC labor rates,
programs are beginning to benefit. Going forward, Roger believes the
IDC will be integral in enabling Rockwell Collins to remain extremely
competitive in the global marketplace.
Rockwell Collins India Design Center organization and facility
Rockwell Collins’ India Design Center is a part of the Rockwell Collins International Business organization led by Walter (Woody) Hogle,
Senior Vice President, reporting to Clay Jones, Chairman, President and CEO. The India Design Center enables Rockwell Collins to present
the best of breed solutions across our entire enterprise to our customers in India and worldwide. Rockwell Collins’ IDC facility is 90,000
square feet and can house 500 engineers. The networking and communications infrastructure within the facility is state of the art and
has built-in redundancy and communications and network monitoring systems.
147-1008-000 08/09 500 BUS © Copyright 2009, Rockwell Collins, Inc. All rights reserved. Printed in the USA.
Building trust every day.
Rockwell Collins delivers smart communication and aviation
electronic solutions to customers worldwide. Backed by a global
network of service and support, we stand committed to putting
technology and practical innovation to work for you whenever and
wherever you need us. In this way, working together, we build trust.
Every day.
For more information, contact:
Rockwell Collins (India) Enterprises Pvt. Ltd.
Phase-II, 7th Floor, Block-3
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Automatic Summary Evaluation without Human Models
Annie Louis
University of Pennsylvania
Philadelphia, PA 19104, USA
lannie@seas.upenn.edu
Ani Nenkova
University of Pennsylvania
Philadelphia, PA 19104, USA
nenkova@seas.upenn.edu
Abstract
We present a fully automatic approach for summarization
evaluation that does not require the creation
of human model summaries.1 Our work capitalizes
on the fact that a summary contains the most representative
information from the input and so it is
reasonable to expect that the distribution of terms in
the input and a good summary are similar to each
other. To compare the term distributions, we use
KL and Jensen-Shannon divergence, cosine similarity,
as well as unigram and multinomial models of
text. Our results on a large scale evaluation from the
Text Analysis Conference show that input-summary
comparisons can be very effective. They can be used
to rank participating systems very similarly to manual
model-based evaluations (pyramid evaluation) as
well as to manual human judgments of summary
quality without reference to a model. Our best feature,
Jensen-Shannon divergence, leads to a correlation
as high as 0.9 with manual evaluations.
1 Introduction
Automatic text summarizers are expected to produce a
condensed form of an input, retaining the most important
content and presenting the information in a coherent
fashion. The development of suitable and efficient
evaluations of summary content and organization is crucial
and necessary to guide system development. Ideally,
summary quality would be measured through extrinsic
evaluations where the usefulness of a system summary
is assessed in specific task scenarios such as reading
comprehension (Morris et al., 1992), relevance judgements
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