La formación de recursos humanos como estrategia de apoyo a la Seguridad Alimentaria y Nutricional (SAN). El caso de la educación superior en Honduras

El presente estudio fue concebido con el objetivo de contribuir a una educación superior más pertinente en Honduras; especialmente con relación a la seguridad alimentaria y nutricional. En primer lugar, fue desarrollado un estudio de percepciones y una consulta con informantes claves, cuyo resultado fue que existe una desvinculación entre la oferta y demanda de formación en seguridad alimentaria. Basándose en ese resultado, se propone un programa formativo que responda adecuadamente a la demanda de profesionales existente en Honduras. Dicho programa consiste en un “Diplomado en Seguridad Alimentaria y Nutricional (SAN), basado en competencias”. Este diplomado debería ser el inicio de un proceso de formación que posteriormente evolucione a la implementación de un sistema de certificación de profesionales en seguridad alimentaria y nutricional. Abstract The present study was designed with the objective of contributing to higher education more pertinent in Honduras, especially in relation to food security and nutritional. It was made a perceptions study and consultations with key informants, the result was that there is a disconnection between offer and demand for food security training. Based on these results, we propose a training program that responds adequately to the demand for professionals in Honduras; we propose a “Competency-based training in Food Security and Nutritional”; this program should be the beginning of a process that progresses to the implementation of a certification system for food security professionals.

Competence Training in Higher Education: The case of the Technological Master "Prestación de Servicios Profesionales" from the Colegio de Postgraduados (México).

The Competency-Based Education in the context of training is intended as a comprehensive approach that seeks to link education with the productive sector and increase the potential of individuals, in the face of social, economic, political and cultural transformations that suffers the world and the contemporary society; this is how educational services associated to the rural area takes part of the global revalorization of the role of learning and knowledge. Under the competence approach and taking into account the CONOCER model, we design a Technological Master from the “Colegio de Postgraduados” identifying the competences needed so that the students, professional from different areas of knowledge, managed to develop them, but mainly to achieve the goal of developing the capacities of producers in Mexican rural area.

e-MIS Contents: Multimedia Contents for e-Learning Environments in Minimally Invasive Surgery

This work describes the design and application of multimedia contents for web technologies-based training in minimally invasive surgery (MIS). The chosen strategy allows knowing the deficiencies of the current training methods so new multimedia contents can cover them. This study is concluded with the definition of three different types of multimedia contents accordingly to the development degree and didactic objectives that they present: Didactic resources are basic contents such as videos or documents that can be enhanced with contributions of users. On the other hand, case reports and didactic units have a defined structure. Didactic resources and case reports provide an informal training while didactic units are included in a more regulated training.

UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand- avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions.

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand-avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

Analyzing training dependencies and posterior fusion in discriminant classification of apnoea patients based on sustained and connected speech

We present a novel approach using both sustained vowels and connected speech, to detect obstructive sleep apnea (OSA) cases within a homogeneous group of speakers. The proposed scheme is based on state-of-the-art GMM-based classifiers, and acknowledges specifically the way in which acoustic models are trained on standard databases, as well as the complexity of the resulting models and their adaptation to specific data. Our experimental database contains a suitable number of utterances and sustained speech from healthy (i.e control) and OSA Spanish speakers. Finally, a 25.1% relative reduction in classification error is achieved when fusing continuous and sustained speech classifiers. Index Terms: obstructive sleep apnea (OSA), gaussian mixture models (GMMs), background model (BM), classifier fusion.