Transcript Diapositive 1

Université de Corse
Pascal Paoli
23/06/2008
HISTORICAL CONTEXT
• Historical opening : 1765 – 1768
• Re-opening in 1981 : 350 students
•
in 1988 : 1500 students
•
in 1998 : 3500 students
• End of the 90’s : Focus on Environnemental studies
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University : Today
• 4300 studentss
•
234 researchers/teachers
137 adminstrative people
•
More than 240 PhD students
•
More than 50 different nationalities on the campus
More than 100 University partners in the world
•
•
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University : today
3
sites
 33 000 m²
Grand Bastia
Palazzu Naziunale
Campus Mariani
Carghjese
Campus Grimaldi
Vignola
New Campus
4
Research
Research : Strategy
• Research oriented around 6 projects
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International Scientific topics
Corsica Developemnt problematics
Projets
Labs
Research organisation
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Forest Fires
Water Management and
Valorisation
Territories Dynamics and
Sustainable Development
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Identities and Cultures
Renewable Energies
Natural Ressources
Technologies of Information and
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Communication
Research Valorisation
Each project involves a valorisation part :
 Project Fire : fire professionals and institutions
Project Water Management : aquaculture (aquarium)
Projet TD : Territory management (tourism,agriculture,
etc…)
Project Renewable Energies : CAP-ENERGIES Pôle
de Compétitivité
Project Natural Resources : Actions ADEC : PAM
Project IdC : InCorsu+ (DVD) and Mediatec
Project TIC : environnemental studies
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Research
New Organisation since 1 st January 2008
• CNRS Labelisation
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UMR SPE « Sciences Pour l’Environnement »
UMR LISA « Lieux, Identités, eSpaces, Activités »
Fédération de recherche « Environnement et société »
UMS Cargèse
• l’INRA, l’INSERM, l’IFREMER Partnerships
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Bilan du contrat 2004/2007
New Organisation since 1st January 2008
INSERM
INRA
IFREMER
Fédération de recherche CNRS
Environnement et société
UMR CNRS SPE
Renewable Energies
Forest Fires
Natural Ressources
Water Management
Technologies of Information and
Communication
UMR CNRS LISA
Identities and cultures
Territories dynamics
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UMR LISA
Central Topics : IdC et DTDD
Competences: Economical Sciences, Law Studies, anthropology, archaology , linguistics,
Projects:
DT and Identities and Cultures
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LA FÉDÉRATION DE RECHERCHE ENVIRONNEMENT
ET SOCIÉTE : F. R. E. S
• Members : 4 research entities from the Corsican Region :
UMR CNRS Sciences Pour l’Environnement ;
UMR CNRS Lieux, Identités, eSpaces, Activités ;
INRA Centre de Corse San Giulianu
INRA Centre de Corse Corte) soit plus de 300 chercheurs.
• Main Objective : Pluridisciplinary research
1/5
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RESEARCH-TEACHING
UMR SPE, UMR LISA
FRES, Projets
Drive
MASTERS
PhD Students belonging the ED
ENVIRONNEMENT ET SOCIETE
Grants/year:
2 MRT
12 from CTC
1 autre (CNRS, CIFRE, CEA,
ADEME…)
6 post doc
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Teaching
Teaching
Six domains , more than 80 diplomass
LLASH, SEG, Droit, Sciences et Technologies, STAPS, Santé
Inscriptions administratives
4400
4327
4300
Répartition LMD
en 2006/2007
4200
4161
L
4100
M
D
6%
4000
3900
4013
28%
3896
66%
3855
3800
3813
3700
3600
3500
2001/2002
2002/2003
2003/2004
2004/2005
2005/2006
2006/2007
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Conclusion
University of Corsica
 Increasing
results in research (structuration,
visibility) and teaching (attractivity)
 Corsican
society impact
(qualification level increasing, corisan language and
culture development, environnemental topics)
 Contribution
to the elaboration of a knowledge
corsican society
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T.I.C.
Computer Sciences : Research at the
University of Corsica
Detailed Presentation of the T.I.C Project
This project involves two aspects :
 Scientific one : development of generic concepts and tools for
the study of complex systems according to national and
international computer sciences problematics :
• Modeling and Simulation of systems
• Multi representation of spatial data
• Wireless sensors networks
 Technological one : validation of the previous concepts and
tools on concrete applications linked to regional problematics.
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Scientific Aspects
1 Modeling and Simulation
Définition of a generic approach for modleing and simulation from the
DEVS (Discrete Event Specification) formalism
DEVS and Fuzzy sets
Multi Layers DEVS
Concurrent DEVS
DEVS models Aided Design (libraries, Web,etc..)
DEVS and MDA (Model Driven Architecture)
DEVS, SMA and GIS
Dynamic DEVS
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DEVS formalism
The DEVS formalism (Discrete EVent system Specification) was
introduced by B.P. Zeigler into the 70’s.
DEVS is a multi formalism of modeling and of simulation
based on systems theory, it allows the representation of complex
systems in a modular and hierarchical form.
This approach uses the concepts of Atomic Model, Coupled
Model and Abstract Simulator.
The simulation is drive by event.
Evt => (port, value, time)
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DEVS Formalism
• Modelling formalism based upon discret
events theory
• A system is described using :
A
time base
 Inputs
 Outputs
 A set of states
 Some transition functions
• Coupled model : composed of atomic models
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DEVS Formalism
• This formalism emphasizes on the change of
variables : an event is described as a change of the
value of a variable
• Simulation : use of a scheduler giving all the
events chronologically
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Modelling and simulation using DEVS
The purpose of modeling and simulation is to simplify the
components of a system, in order to reproduce its behavior.
Real System
modelling
Model
validation
simulation
(Black box)
(Equation)
Simulator
(Result)
Three entities of the modeling
and simulation process
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DEVS formalism
The atomic model is defined by:
(1) AM = < X, Y, S, ta, δint, δext, λ >
1) Atomic
Model
2) Coupled
Model
3) Abstract
Simulator
Where :
- X is the input ports set, through which external events are received;
- Y is the output ports set, through which external events are sent;
- S is the states set of the system ;
- ta is the time advance function (or of lifespan of a state) ;
- δint is the internal transition function;
- δext is the external transition function;
- λ is the output function;
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DEVS formalism
The coupled model is defined by:
(2) CM = < X, Y, C, EIC, EOC, IC, L >
Where :
1) Atomic
Model
2) Coupled
Model
3) Abstract
Simulator
- X is the input ports set;
AM1
X
CM1
Y
- Y is the output ports set;
- C is the set of all component models;
IC
EIC
AM2
EOC
- EIC is the external input coupling relation which connects the input
ports of
the coupled model to one or more of the input ports of its
internal components;
- EOC is the external output coupling relation which connects the
output ports of the internal components to the output ports of the
coupled model;
- IC : is the internal coupling relation which connects the output ports
of the internal components to the input ports of other components;
- L is the list of priorities between components ;
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DEVS formalism
B.P. Zeigler
Simulator.
1) Atomic
Model
define
a
abstract
The major advantage of such a
simulator is that its conception is
independent of the model.
2) Coupled
Model
3) Abstract
Simulator
Nevertheless :
When DEVS formalism is replaced in the specific context of applicability
field, it is too often abstract, it is then necessary to enrich its syntax
Example : for the study of fuzzy systems.
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Modeling and Simulation
:
MSOO : object oriented Modeling and Simulation
RdN : Neural Networks
GIS : Geographic Information Systems
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Methodology
Object Oriented Modeling of
natural systems
Principles :
Decomposition of the natural
systems into interconnection
of basic models
Models representation using
object technology
Use of Neural Networks
Links to GIS
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METHODOLOGY
Simulation of the models
Principles :
Automatic generation of the
simulators associated with the
models.
Use of the Object Oriented
Programming and Discrete Event
Simulation
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Collaborative
Research
Collaborative Software
Specialist
of a Domain
Modelisator 1
Physician
Mathmatician
Economist
…
Modelisator 2
Responsible for the
modeling phase :
define the global
model from the
Reusable
components
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How to work
GIS, Simulation, DATA FUSION
Satellite
Data Fusion
GIS
Acquisition
GPS
Observation
Simulation MSOO
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Scientific Aspects
2 Multi Representation of Spatial Data
Definition and solving of problems linked to the represention of
temporal spatial data at several scales
How to deal with data at different levels of temporality
How to deal with data at different levels of abstraction
How to deal with data coming from differents domains and
different semantics
Development of a software allowing : (1) the automatic
transformation between levels of abstraction and levels of
temporality ; (2) to take into account several kinds of semantics
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2 Multi Representation of Spatial
Data
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Basic Concepts (I)
• Abstraction hierarchy : a way to describe a system
at different levels of details
1
Leve l N
A
3
2
A1
A3
2.1
2.2
A2
3.1
3.2
Decomposition
1.1
1.2
Leve l N- 1
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Basic Concepts (II)
• Description hierarchy : a way to subdivide a
system
1
Leve l N
A
3
2
Description
1
A1
A3
2
A2
3
Leve l N-1
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BASIC CONCEPTS (III)
• Use of Transfer Functions to translate between a
representation More (less) detailed to
representation Less (more) detailed
Representation 1
Representation 2
(more detail)
(less detail)
Level N -1
Level N
Transfer Functions
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IMPLEMENTATION (I)
• Realization of a prototype of a software called
GIS-ARCHAEO-ASTRO developed in Visual
Basic (three kinds of semantics : archaeology,
anthropology and astronomy)
• Validation was carried out starting from a
concrete example concerning the archaeological
site of Monte Revincu
• The site of Monte Revincu is located in the area
of Agriate at the North of Corsica
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Monte Revincu
#
#
#
#
#
#
#
#
#
##
##
#
#
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IMPLEMENTATION (II)
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IMPLEMENTATION (III)
• The user use the decomposition to generate a new
representation R2, by using the button “UP”
R1. 1pt
Use decomposition
Need more details
Level 1
R2. 3 pt
Level 2
Archaeological field
R3
Dolmen
No-dolmenic tombs
Level 3
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IMPLEMENTATION (IV)
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IMPLEMENTATION (V)
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3 Wireless Sensors Network
Development of tools dedicated to the control of systems using
wireless sensors network
Study of communication protocols
Distant based Monitoring
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3 Wireless Sensors Network
Design and implementation of sensors network
Study of the structure of communication protocols
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3 Wireless Sensors Network
• Possible application of Wireless Sensor Network
(WSN) in several areas (forest fire, wind turbine
control, water management, sustainable tourism
• Need to simulate functional behavior of node
components and environmental conditions.
• Find routing protocol adapted for different scenarii
and analysis of deployment strategies.
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Project T.I.C.
Technological Aspects
These aspects concern the validation of the
previous concepts through concrete
applications
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Modeling and Simulation
Fires
Electronic Systems Testing
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Modeling and Simulation
Wireless sensor Network Study
Electric Circuits Design
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Modeling and Simulation
• Water Managment
• Computer Aided Design of Agro products
Corsican Cheese fabrication modeling
Fuzzy Data
Résults : 2 golden
medals 2005,2006.
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Modeling and Simulation
• Anthropolical systems
Myths transformation study
from the C. Levi Strauss
Canonical Formula:
fx(a) : fy(b) :: fx(b) : fa-1(y)
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Multi Representation of Spatial Data
• Study of the orientations of
•megaliths using GIS
•Integration of 3D pictures in an
Astronomical software
Example : 4200BC from Orca
dolmen
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Multi Representation of Spatial Data
: GIS for cultural data
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Multi Representation of Spatial Data :
GIS cultural and environmental data
Spatial data server :
GPS
MapInfo
DB
Client
Web
Server
Client
•Géology
•Water quality data
•Données végétation
•Old Maps
•Toponymy
• remarquable natural sites
• folktales
• Intervisibility
•Archéoastronomy, etc…
Client
Client
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Wireless Sensors Network
Sensor
Two applications :
1- Fires prevention
Base Station MBI510
2- Wind turbine Parc Management
Collaboration Univ. de Gènes
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Wireless Sensors Network
The captation of the mimophony gestures and voice synthesis process.
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Wireless Sensors Network
• Gesture capture system
A
receive/transmit wireless system
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Wireless Sensors Network
• Conception of Two DataGloves
 Five
bend sensors and one accelerometer
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Wireless Sensors Network :
perspectives
Goals : submarine monitoring
- Implementation of submarine wireless
sensors networks
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Conclusions
•Team : 10 pemanent researchers : 3 PR+ 2Mcf HDR, 5 McF, 6 PhD
•Contracts :
•1996-1999 : BELSIGN European Network- VHDL (as Leader)
•2000-2003 : EOARD – VHDL as Leader
•1999-2002 : Alcatel-Paris – Telecom Design as leader
•2002 -2006 : European Project Water Management (leader)
• 2008-2010 : PEPS CNRS Sensors Network (leader)
•2005-2008 : ANR Feux (participant)
•2002-2005 : Industrial : Fromagerie Ottavi - leader
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