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