Using surplus nuclear power for hydrogen mobility and power-to-gas in France

Opportunities exist to utilise excess electricity from renewable and nuclear power generation for producing hydrogen. France in particular has a very high penetration of nuclear power plant, some of which is regularly turned down to follow the electricity demand profile. This excess nuclear electricity could be utilised via the electrolysis of water to satisfy the emerging French market for low-carbon hydrogen (principally for mobility applications and the injection of synthetic gas into the natural gas grid). The described analysis examines the use of electrolysers to progressively ‘valley fill’ nuclear load profiles and so limit the need for turning down nuclear plant in France. If an electrolyser capacity of approximately 20 GW is installed, there is already sufficient excess nuclear electricity available now to meet the predicted hydrogen mobility fuel demand for 2050, plus achieve a 5% concentration (by volume) of hydrogen in the gas grid, plus produce approximately 33 TWh p.a. of synthetic methane (via the methanation of hydrogen with carbon dioxide). The pattern of electrolyser utilisation requires operation mostly at a variable part load condition, necessitating the adoption of flexible, efficient, rapid response electrolysers. The proposed approach more fully utilises the substantial existing nuclear power assets of France and provides an additional pathway to renewables for reducing the CO2 emissions of hydrogen production

A graph-based mathematical morphology reader

This survey paper aims at providing a "literary" anthology of mathematical morphology on graphs. It describes in the English language many ideas stemming from a large number of different papers, hence providing a unified view of an active and diverse field of research

STV-based Video Feature Processing for Action Recognition

In comparison to still image-based processes, video features can provide rich and intuitive information about dynamic events occurred over a period of time, such as human actions, crowd behaviours, and other subject pattern changes. Although substantial progresses have been made in the last decade on image processing and seen its successful applications in face matching and object recognition, video-based event detection still remains one of the most difficult challenges in computer vision research due to its complex continuous or discrete input signals, arbitrary dynamic feature definitions, and the often ambiguous analytical methods. In this paper, a Spatio-Temporal Volume (STV) and region intersection (RI) based 3D shape-matching method has been proposed to facilitate the definition and recognition of human actions recorded in videos. The distinctive characteristics and the performance gain of the devised approach stemmed from a coefficient factor-boosted 3D region intersection and matching mechanism developed in this research. This paper also reported the investigation into techniques for efficient STV data filtering to reduce the amount of voxels (volumetric-pixels) that need to be processed in each operational cycle in the implemented system. The encouraging features and improvements on the operational performance registered in the experiments have been discussed at the end

Side-View Face Recognition

Side-view face recognition is a challenging problem with many applications. Especially in real-life scenarios where the environment is uncontrolled, coping with pose variations up to side-view positions is an important task for face recognition. In this paper we discuss the use of side view face recognition techniques to be used in house safety applications. Our aim is to recognize people as they pass through a door, and estimate their location in the house. Here, we compare available databases appropriate for this task, and review current methods for profile face recognition