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This book recognizes Mexico's effects and challenges in a natural
disaster and offers empirical risk-reduction methods in critical
cases. The proposals considered here include real and detailed
analysis, a set of models, frameworks, strategies, and findings in
the three stages of the disaster (before-during-after). This book:
describes the methodology to find secure locations for the Regional
Humanitarian Response Depot; offers recommendations for the sites
and creation of an Export Logistics Cluster; shows how to use
available technology and information to locate volunteers in the
right spots describes mathematical models to help to allocate
procedure of resources for restoring the affected community and
proposes actions to create resilience in the country's main
economic sectors, including agriculture and industry. The processes
applied at recent disasters such as the 19S earthquake and their
results are used as case studies, identifying possibilities for
further improvement. The book also describes new trends for Mexico
due to climate change and makes suggestions for mitigating future
disasters. The proposals are also replicable to other highly
populated societies with similar socio-economic structures.
Finally, this book is the basis for generating more innovative
recommendations by researchers, graduate students, academics,
professionals, and practitioners to obtain better planning and
better collaboration between all the humanitarian chain actors.
This book intends to be of interest as a fundamental tool for
decision-makers, governments, non-governmental organizations, and
enterprises.
This book recognizes Mexico's effects and challenges in a natural
disaster and offers empirical risk-reduction methods in critical
cases. The proposals considered here include real and detailed
analysis, a set of models, frameworks, strategies, and findings in
the three stages of the disaster (before-during-after). This book:
describes the methodology to find secure locations for the Regional
Humanitarian Response Depot; offers recommendations for the sites
and creation of an Export Logistics Cluster; shows how to use
available technology and information to locate volunteers in the
right spots describes mathematical models to help to allocate
procedure of resources for restoring the affected community and
proposes actions to create resilience in the country's main
economic sectors, including agriculture and industry. The processes
applied at recent disasters such as the 19S earthquake and their
results are used as case studies, identifying possibilities for
further improvement. The book also describes new trends for Mexico
due to climate change and makes suggestions for mitigating future
disasters. The proposals are also replicable to other highly
populated societies with similar socio-economic structures.
Finally, this book is the basis for generating more innovative
recommendations by researchers, graduate students, academics,
professionals, and practitioners to obtain better planning and
better collaboration between all the humanitarian chain actors.
This book intends to be of interest as a fundamental tool for
decision-makers, governments, non-governmental organizations, and
enterprises.
Dysarthria is a motor speech disorder characterized by weakness,
paralysis, or poor coordination of the muscles responsible for
speech. Although automatic speech recognition (ASR) systems have
been developed for disordered speech, factors such as low
intelligibility and limited phonemic repertoire decrease speech
recognition accuracy. Furthermore, conventional speaker adaptation
algorithms that improve normal speech recognition may not perform
as well on dysarthric speakers. Instead of adapting the system, two
main techniques are proposed to model the pronunciation errors made
by the speaker: (1) a set of discrete hidden markov models (termed
as "metamodels") that incorporate a model of the speaker's phonetic
confusion-matrix into the ASR process; and (2) a network of
Weighted Finite-State Transducers (WFSTs) at the confusion-matrix,
word and language levels. These error modelling techniques attempt
to correct the errors made at the phonetic level and make use of a
language model to find the best estimate of the correct word
sequence. Hence, these techniques when integrated into the speech
recognition process performed significant error correction and
improved speech recognition
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