SEINIT Security for Heterogeneous Mobile Network Services

This paper presents a model for securing mobile services using heterogeneous access networks, and implementing sample solutions using this framework. This is a project that is defining new security models and policies to address the new issues of the pervasive computing world. The security models and policies are implemented over IPv6 infrastructures to cover various business cases and assessed against real life scenarios. SEINIT is developing a trusted and dependable security framework with the end-user as the focus

INSPEX: Make environment perception available as a portable system

International audienceObstacle avoidance systems for autonomous vehicles combine multiple sensing technologies (i.e. LiDAR, Radar, Ultrasound and Visual) to detect different types of obstacles across the full range of lighting and weather conditions. Sensor data are fused with vehicle orientation (obtained for instance from an Inertial Measurement Unit and/or compass) and navigation subsystems. Power hungry, they require powerful computational capability, which limits their use to high-end vehicles and robots. 2 INSPEX ambition The H2020 INSPEX project plans to make obstacle detection capabilities available as a personal portable multi-sensors, miniaturised, low power device. This device will detect, locate and warn of obstacles under different environmental conditions, in indoor/outdoor environments, with static and mobile obstacles. Potential applications range from safer human navigation in reduced visibility conditions (e.g. for first responders and fire brigades), small robot/drone obstacle avoidance systems to navigation for the visually and mobility impaired people. As primary demonstrator (Fig.1), we will plug the INSPEX device on a white cane (see Fig. 1) for Visually Impaired and Blind (VIB) people to detect obstacle over the whole person height, provide audio feedback about harmful obstacles, improve their mobility confidence and reduce injuries, especially at waist and head levels [1]. The device will offer a "safety cocoon" to its user

3rd ICTs and Society Meeting; Paper Session - Theorizing the Internet; Paper 1: Toward Trust as Result. A Transdisciplinary Research Agenda for the 'Future Internet'

Trust has emerged as one of the key challenges for the Future Internet and as a key theme of European research. We are convinced that a transdisciplinary research agenda - that we define to as Trust as Result - shared by Sociology and Computer Science, is of paramount importance for devising sustainable Trust solutions for the (Future) Internet stakeholders. The scope of this paper is to present some elements we consider important for building such an agenda

Towards a portable smart spatial exploration system for environment perception

International audienc

INSPEX: Make environment perception available as a portable system

Obstacle avoidance systems for autonomous vehicles combine multiple sensing technologies (i.e. LiDAR, Radar, Ultrasound and Visual) to detect different types of obstacles across the full range of lighting and weather conditions. Sensor data are fused with vehicle orientation (obtained for instance from an Inertial Measurement Unit and/or compass) and navigation subsystems. Power hungry, they require powerful computational capability, which limits their use to high-end vehicles and robots

Advances in diffusion MRI acquisition and processing in the Human Connectome Project

The Human Connectome Project (HCP) is a collaborative 5-year effort to map human brain connections and their variability in healthy adults. A consortium of HCP investigators will study a population of 1200 healthy adults using multiple imaging modalities, along with extensive behavioral and genetic data. In this overview, we focus on diffusion MRI (dMRI) and the structural connectivity aspect of the project. We present recent advances in acquisition and processing that allow us to obtain very high-quality in-vivo MRI data, whilst enabling scanning of a very large number of subjects. These advances result from 2 years of intensive efforts in optimising many aspects of data acquisition and processing during the piloting phase of the project. The data quality and methods described here are representative of the datasets and processing pipelines that will be made freely available to the community at quarterly intervals, beginning in 2013