Modelling adaptive web applications

Conceptual Modelling approaches for the web need extensions to specify dynamic personalization properties in order to design more powerful web applications. Current approaches provide techniques to support dynamic personalization, usually focused on implementation details. This article presents an extension of the OO-H conceptual modeling approach to address the particulars associated with the design and specification of dynamic personalization. The main benefit is that this specification can be modified without recompile the rest of the application modules. We describe how conventional navigation and presentation diagrams are influenced by personalization properties. In order to model the variable part of the interface logic OO-H has a personalization architecture that leans on a rule engine. Rules are defined based on a User Model and a Reference Model.

3D visual sensing of human hand for remote operation of a robotic hand

New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.

RGBD Human-Hand recognition for the Interaction with Robot-Hand

New low cost sensors and the new open free libraries for 3D image processing are permitting to achieve important advances for robot vision applications such as tridimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a method to recognize the human hand and to track the fingers is proposed. This new method is based on point clouds from range images, RGBD. It does not require visual marks, camera calibration, environment knowledge and complex expensive acquisition systems. Furthermore, this method has been implemented to create a human interface in order to move a robot hand. The human hand is recognized and the movement of the fingers is analyzed. Afterwards, it is imitated from a Barret hand, using communication events programmed from ROS.

Evaluación del contenido sobre educación alimentaria en páginas web de servicios de catering: estudio piloto en el ámbito escolar

Introducción: Analizar la calidad de las páginas web de los servicios de catering en el ámbito escolar y su contenido en educación alimentaria, y tener una primera experiencia con la herramienta de evaluación EDALCAT. Material y métodos: Estudio descriptivo transversal. La población de estudio son páginas web de empresas de catering encargadas de la gestión de los comedores escolares. La muestra se obtuvo utilizando el buscador Google y un Ranking de las principales empresas de catering por facturación, escogiendo aquellas que tenían página web. Para la prueba piloto se seleccionaron diez páginas web según proximidad geográfica a la ciudad de Alicante y nivel de facturación. Para la evaluación de los sitios web se diseñó un cuestionario (EDALCAT), compuesto de un primer bloque de predictores de calidad con 19 variables de fiabilidad, diseño y navegación; y de un segundo bloque de contenidos específicos de educación alimentaria con 19 variables de contenido y actividades educativas. Resultados: Se han obtenido resultados positivos en 31 de las 38 variables del cuestionario, excepto en los ítems: “Buscador”, “Idioma” (40%) y “Ayuda” (10%) del bloque predictores de calidad y en los ítems: “Talleres”, “Recetario”, “Web alimentación-nutrición” (40%) y “Ejemplos” (30%) del bloque de contenidos específicos de educación alimentaria. Todas las páginas web evaluadas superan valores del 50% de cumplimiento de criterios de calidad y de contenidos mínimos en educación alimentaria, y sólo una de ellas, incumple el nivel de actividad mínimo establecido. Conclusiones: Los predictores de calidad y los contenidos específicos en educación alimentaria dieron buenos resultados en todas las páginas web evaluadas. La mayoría de ellas obtuvieron una alta puntuación en su valoración, y en su análisis individual por bloques. Tras el estudio piloto el cuestionario se ha modificado y se obtiene el EDALCAT definitivo. En líneas generales EDALCAT parece ser adecuado para evaluar la calidad de las páginas web de servicios de catering y su contenido en educación alimentaria, sin embargo el presente estudio no puede considerarse como validación del mismo.

Towards a real-time 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors

In this project, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: the system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The range of algorithms and applications to be implemented and integrated will be quite broad, ranging from the acquisition, outlier removal or filtering of the input data and the segmentation or characterization of regions of interest in the scene to the very object recognition and pose estimation. Furthermore, in order to validate the proposed system, we will create a 3D object dataset. It will be composed by a set of 3D models, reconstructed from common household objects, as well as a handful of test scenes in which those objects appear. The scenes will be characterized by different levels of occlusion, diverse distances from the elements to the sensor and variations on the pose of the target objects. The creation of this dataset implies the additional development of 3D data acquisition and 3D object reconstruction applications. The resulting system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human-computer interaction (HCI) systems based on visual information.