El surgimiento de HTML5; un nuevo paradigma en los estándares Web

Gracias al crecimiento, expansión y popularización de la World Wide Web, su desarrollo tecnológico tiene una creciente importancia en la sociedad. La simbiosis que protagonizan estos dos entornos ha propiciado una mayor influencia social en las innovaciones de la plataforma y un enfoque mucho más práctico. Nuestro objetivo en este artículo es describir, caracterizar y analizar el surgimiento y difusión del nuevo estándar de hipertexto que rige la Web; HTML5. Al mismo tiempo exploramos este proceso a la luz de varias teorías que aúnan tecnología y sociedad. Dedicamos especial atención a los usuarios de la World Wide Web y al uso genérico que realizan de los Medios Sociales o "Social Media". Sugerimos que el desarrollo de los estándares web está influenciado por el uso cotidiano de este nuevo tipo de tecnologías y aplicaciones. 

D6.1 – Ecosystem Software Platform with Underlying Software Repository, Digital Library and Media Archive

The objective of D6.1 is to make the Ecosystem software platform with underlying Software Repository, Digital Library and Media Archive available to the degree, that the RAGE project can start collecting content in the form of software assets, and documents of various media types. This paper describes the current state of the Ecosystem as of month 12 of the project, and documents the structure of the Ecosystem, individual components, integration strategies, and overall approach. The deliverable itself is the deployment of the described components, which is now available to collect and curate content. Whilst this version is not yet feature complete, full realization is expected within the next few months. Following this development, WP6 will continue to add features driven by the business models to be defined by WP7 later on in the project.

Nurturing communities of inquiry: A formative study of the DojoIBL platform

Full paper presented at EC-TEL 2016

Video anomaly detection in real-time on a Power-Aware Heterogeneous Platform

FPGAs and GPUs are often used when real-time performance in video processing is required. An accelerated processor is chosen based on task-specific priorities (power consumption, processing time and detection accuracy), and this decision is normally made once at design time. All three characteristics are important, particularly in battery-powered systems. Here we propose a method for moving selection of processing platform from a single design-time choice to a continuous run time one.We implement Histogram of Oriented Gradients (HOG) detectors for cars and people and Mixture of Gaussians (MoG) motion detectors running across FPGA, GPU and CPU in a heterogeneous system. We use this to detect illegally parked vehicles in urban scenes. Power, time and accuracy information for each detector is characterised. An anomaly measure is assigned to each detected object based on its trajectory and location, when compared to learned contextual movement patterns. This drives processor and implementation selection, so that scenes with high behavioural anomalies are processed with faster but more power hungry implementations, but routine or static time periods are processed with power-optimised, less accurate, slower versions. Real-time performance is evaluated on video datasets including i-LIDS. Compared to power-optimised static selection, automatic dynamic implementation mapping is 10% more accurate but draws 12W extra power in our testbed desktop system.