Modeling Robustness of Business Ecosystem of End of Life Vehicles Players

End of life vehicles (ELVs) recycling infrastructure is a business ecosystem of players that similar to a biological ecosystem, the sustainability of this structure depends on the interaction among players. For evaluation, the robustness of this ecosystem, not only economic sustainability of players but also the environmental and social impacts of their strategies should be considered. Moreover, this assessment should involve market forces, the impact of government policies and society needs as well as technology market. In this study, we introduced a framework for modelling robustness of the business ecosystem of automobile recycling players considering the response to dynamical effects, stability and learning outcomes. The descriptions of building blocks of the model are adapted for modelling the car passenger recycling infrastructure in US; however, the architecture of the model can be used in other regions or even in other industries

Modélisation 3D des façades de bâtiments des anciennes Médina

Le LIDAR (Light Detecting and Ranging) terrestre statique est un outil de levé présentant actuellement une source de données 3D indispensable dans l’évaluation et la surveillance des bâtiments patrimoniaux. A travers des processus automatiques de modélisation 3D, la manipulation de cette source de données dans des outils de communication devient plus souple. Le processus de modélisation 3D impose des sous missions indispensables dont la segmentation. Une grande partie des approches de segmentation se focalisent sur l’emploi des composantes géométriques en exploitant la représentation mathématique d’une surface plane ou courbée. En raison de la complexité de l’architecture des façades, une segmentation utilisant uniquement l’aspect géométrique reste insuffisante. Ainsi, une nouvelle approche de segmentation est développée équilibrant les résultats de l’extraction des surfaces homogènes. Ceci, en se basant sur l’ensemble des composantes d’un nuage de points coloriés à savoir les composantes géométriques, les valeurs RGB et les intensités laser des détails constituant les façades des bâtiments des anciennes Médina. Le processus s’initialise par l’extraction des segments plans à l’aide de l’algorithme RANSAC. Le résultat fera l’objet d’une deuxième segmentation radiométrique basée sur l’introduction du critère de similarité couleur dans l’algorithme de croissance de région. Enfin une fusion de classes sera effectuée en fonction de la similarité de l’intensité laser.    The static terrestrial LIDAR is a tool of surveying which present a vital source of 3D data in the heritage buildings evaluation and monitoring. Through automated  3D modeling process, manipulating this data source in communication tools becomes more flexible. The 3D modeling process imposes on essential tasks including segmentation. Much of segmentation approaches focus on the use of geometric components by exploiting the mathematical representation of a plane or curved area. Due to the complexity of the facades architecture, segmentation using only the geometrical aspect is insufficient. Thus, a new segmentation approach is developed balancing the results of extracting homogeneous areas based on all colored point cloud components namely geometric data, the RGB values and intensities of facades details especially in old Medina building. The process consists of the planar segments extracting using the RANSAC algorithm. The result will be subject to radiometric segmentation through the introduction of color similarity criterion in the region growing algorithm and finally a fusion of classes based on the intensity’s similarity

Securing Water, Sustaining Growth: Report of the GWP/OECD Task Force on Water Security and Sustainable Growth

Peer Revie

The sustainable worldwide offshore wind energy potential: A systematic review

The offshore wind industry is expanding rapidly around the world due to several factors enabling this source of renewable energy. Stronger wind resources in offshore areas, lack of social and geographical constraints related to onshore wind power, the evolution of technology, and increasing demand for electricity in coastal regions as a result of a massive increase in population are some of the factors favoring the use of wind energy. The assessment of the potential global capacity that considers the different economic, environmental, and social factors and the dynamics of market, policy, and technology are vital for estimating the competitiveness of offshore wind energy in the future energy profile. There are several studies and technical reports that evaluate the potential of offshore wind energy in different countries or regions. They used a different source of data, metrics, and quantitative approaches in appraising the potential offshore wind power capacity and its cost efficiency. The critical factors that have been considered are geographical, technical, economic, environmental, and social and market elements. This paper provides a systematic review for analyzing the studies that address the potential offshore wind energy around the world and published during the 2000–2016 period. This study highlights the key criteria for assessing the potential for offshore wind energy deployment and the related tools and methods