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A classic problem in the field of pattern recognition is that of
handwritten digit recognition. The heart of the problem lies within
the ability to design an efficient algorithm that can recognize
digits written and submitted by users via a tablet, scanner, and
other digital devices. Previous studies have shown that the digits
can be modeled as points in a high dimensional space which can
adequately approximated by linear structures. In Chapters 2 and 3,
we present two previously established algorithms rooted in two
distinct geometric frameworks. In Chapter 4, we introduce a novel
approach to the problem based on the linear structure that arises
for the Grassmann manifold. From this framework, we developed three
separate algorithms. We then tested our algorithms on the publicly
available MNIST database and benchmarked our results with the
algorithm described in Chapters 2 and 3. Without any preprocessing
of the images, one of the Grassmann-based algorithms simultaneously
achieved the highest classification rate and one of the fastest
processing times.
This is a reproduction of a book published before 1923. This book
may have occasional imperfections such as missing or blurred pages,
poor pictures, errant marks, etc. that were either part of the
original artifact, or were introduced by the scanning process. We
believe this work is culturally important, and despite the
imperfections, have elected to bring it back into print as part of
our continuing commitment to the preservation of printed works
worldwide. We appreciate your understanding of the imperfections in
the preservation process, and hope you enjoy this valuable book.
Tuberculosis is still a significant health and economic problem in
Central Asia, despite some recent progress that may be due to
improvements of the overall economic situation in these countries,
and partial adoption of the DOTS Strategy recommended by WHO. Over
50,000 new cases have been detected in 2003 and over 7,000 people
died due to TB in the four countries studied. This study has
confirmed that it is highly unlikely that these Central Asian
republics will succeed in achieving the global targets for
tuberculosis control in the short term, particularly with regard to
case detection. In the meantime, the epidemic continues to have a
serious epidemiological impact and affects the economies of these
countries, which incur productivity losses and indirect costs that
are estimated to range from 0.5 to 0.8 percent of GDP annually.
'Stopping Tuberculosis in Central Asia' reviews the epidemiological
situation, control efforts, and financing of tuberculosis programs
in Kazakhstan, Kyrgyz Republic, Tajikistan, and Uzbekistan. It was
based on a review of existing statistics and reports, and on
consultation with key stakeholders Governments, NGOs, and donors in
Central Asia. This work contributes an agenda for action to address
the impending epidemiological crisis that has been posed by the
sudden increase in cases of HIV/AIDS infection combined with a
prevalent epidemic of TB."
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