Annonce en lien avec l’Action/le Réseau : aucun
Laboratoire/Entreprise : University of Technology Troyes, Institut Charles Delaunay
Durée : 36 mois
Contact : eddie.soulier@utt.fr
Date limite de publication : 2018-12-31
Contexte :
Two distinct entities cannot occupy exactly the same point of a geographical scope. The distance is a key variable of any social space. Space has some attributes (scale, metric, topic…). Space is thus not absolute, it is relative and must be calculated. There are two methods to minimize the distance between two social realities which is the cost function to be optimized: colocation and mobility. Finally, space only fully exist if it is used by actor or involved in some activity (spatiality). Space and spatiality is a multi-dimensional complex network termed as assemblage.
Space and spatiality are also defined by a space value. The city illustrates the relevance of this model. In space term, the city is a spatial object which privileges the colocation: it gives access to a maximum of social realities in a minimum of time and cost. To search colocation aims to increase economic efficiency, development of social interactions or improvement of city management. In terms of spatiality, the city can be defined by its urbanity (Levy and Lussault, 2003), i.e. by the conjunction of two factors: density and diversity of the co-located objects. The search of colocation produces growth of density and increase of the diversity of the co-located objects. Conversely, the simultaneous increase in mobility (displacement, telecommunication) privileges connectivity compared to immediate contact and leads to urban sprawl, and thus to the weakening of densities and, often, diversity.
The city engine concept proposed in this research has the objective to calculate, for some specified urban situations (use cases), the space and spatiality hypergraph which minimizes the distance and optimizes urbanity, while taking into account mobility. Use cases could be: crime map, mobility management, improving cycling safety, smart elderly care system, smart commuting, personal emergency response, interactive street sensing, stimulating green behavior, etc.
Sujet :
2) Objective and challenges
Hypernetworks generalize the concept of a relation between two things to relations between many things. Relational simplices have multi-dimensional connectivity related to hypergraphs, simplicial complexes and the Galois lattice of maximally connected sets of elements. This structure acts as a kind of backcloth for the dynamic system traffic represented by numerical mappings, where the topology of the backcloth constraints the dynamics of the traffic. Simplices provide a way of defining multilevel structure. Multilevel hypernetworks provide a significant generalization of network theory and set theory, enabling the integration of relational structure that are likely to be necessary for a science of
complex multilevel socio-technical systems. Theory of hypernetworks is based on previous work of Ron Atkin, following the ideas of Clifford Hugh Dowker, generalized by J. Johnson (2013).
Two main challenges are to be considered:
1. Tools for manipulating simplicial complexes and hypernetworks.
2. Implement relational algebras to analyze massive heterogeneous data sets.
Profil du candidat :
Academic Requirements:
Persons with a Master’s Degree or equivalent degree of higher education (Curriculum Vitae)
Algorithmic, Data Science, Machine Learning
Programming (Python, C/C++, Java)
Mathematical skills
Knowledge in probabilities and statistics
Formation et compétences requises :
Successful candidates should have a master degree in mathematical/statistical
sciences, Machine learning, statistical signal processing, or a closely related area,
Adresse d’emploi :
CNRS « Institut Charles Delaunay ». UTT – Université de Technologie de Troyes 12 rue Marie Curie – CS 42060 – 10004 TROYES CEDEX (and/or PARIS)
Document attaché : PhD-Proposal-ENGIE-UTT-V1.pdf