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Section: New Software and Platforms
Platforms
The Dream project-team, in collaboration with their applicative partners, has proposed and maintains several important software platforms for its main research topics.
Platform: Environmental decision-support systems
Participants : Marie-Odile Cordier, Christine Largouët, Véronique Masson.
SACADEAU
Système d'Acquisition des Connaissances pour l'Aide à la Décision sur la qualité de l'EAU
Functional Description
the Sacadeau system is an environmental decision software that implements the Sacadeau transfer model. The Sacadeau simulation model couples two qualitative models, a transfer model describing the pesticide transfer through the catchment and a management model describing the farmer decisions. Giving as inputs a climate file, a topological description of a catchment, and a cadastral repartition of the plots, the Sacadeau model simulates the application of herbicides by the farmers on the maize plots, and the transfer of these pollutants through the catchment until the river. The two main simulated processes are the runoff and the leaching. The output of the model simulation is the quantity of herbicides arriving daily to the stream and its concentration at the outlets. The originality of the model is the representation of water and pesticide runoffs with tree structures where leaves and roots are respectively up-streams and down-streams of the catchment.
EcoMata
Functional Description
The EcoMata tool-box provides means for qualitative modeling and exploring ecosystems and for aiding to design environmental guidelines.We have proposed a new qualitative approach for ecosystem modeling based on timed automata (TA) formalism combined to a high-level query language for exploring scenarios.
PaturMata
Keywords: Bioinformatics - Biology
Scientific Description
In the PaturMata software, users can create a pasture system description by entering herds and plots information. For each herd, the only parameter is the number of animals. For each plot, users should enter the surface, the density, the herb height, the distance to the milking shed, a herb growth profile and an accessibility degree.
Users then specify pasturing and fertilization strategies. Finally, users can launch a pasture execution. PaturMata displays the results and a detailed trace of pasture. Users can launch a batch of different strategies and compare the results in order to find the best pasture strategy.
PaturMata is developed in Java (Swing for the GUI) and the model-checker that is called for the timed properties verification is UPPAAL .
Functional Description
The Paturmata tool-box provides means for qualitative modeling and exploring agrosystems, specifically management of herd based on pasture. The system is modelled using a hierarchical hybrid model described in timed automata formalism.
Platform: Pattern Mining
Participants : Thomas Guyet, René Quiniou.
QTempIntMiner
Temporal pattern mining in sequences
Scientific Description
The QTempIntMiner data mining software implements several algorithms (QTIAPriori and QTIPrefixSpan ). The software is mainly implemented in Matlab. It uses the Mixmod toolbox to compute multi-dimensional Gaussian distributions. The main features of QTempIntMiner are:
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a tool for generating synthetic noisy sequences of temporal events,
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an implementation of the QTempIntMiner , QTIAPriori and QTIPrefixSpan algorithms,
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a graphical interface that enables the user to generate or import data set and to define the parameters of the algorithm and that displays the extracted temporal patterns.
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a sequence transformer to process long sequences of temporal events. Long sequences are transformed into a database of short temporal sequences that are used as input instances for the available algorithms.
The software includes one new algorithm based on the separation of the set of interval to extract more efficiently but less accurately the time interval in temporal patterns. This new algorithm version is still under evaluation on simulated and real datasets.
This year, an APP deposit of the early version (in Matlab) of this framework has been done. In parallel, we started the developement of a C++ version of the framework.
Platform: Diagnostic and Monitoring Systems
Participants : Marie-Odile Cordier, René Quiniou, Sophie Robin, Laurence Rozé.
ManageYourself
Functional Description
The ManageYourself software comes from a collaborative project between Dream and the Telelogos company aiming at monitoring smartphones from a stream of observations made on the smartphone state.
Today’s smartphones are able to perform calls, as well as to realize much more complex activities. They are small computers. But as in computers, the set of applications embedded on the smartphone can lead to problems. The aim of the project ManageYourself is to monitor smartphones in order to avoid problems or to detect problems and to repair them. To this end, a model of the martphone system is learned and updated incrementally.
Odisseptale
Keywords: Biology - Health
Functional Description
The Odisseptale software implements disease detectors using monitoring of data provided by sensors placed on calves or cows. Sensors record streams of data such as body temperature, physical activity, feeding behavior, etc. These data are transmitted regularly to a monitoring software that aims to detect if a noticeable change has occurred on the data streams. Several detectors can be simultaneously active and each contribute to the final decision (detection of a disease). Two kinds of detectors have been implemented: a generic detector based on adaptive CUSUM and a symbolic pattern-based detector. Odisseptale provides also facilities for parameter setting and performance evaluation.