Measurement scale for colour perception

5 pagesInternational audienceThe colour, with the particularity to be defined simultaneously as a physical quantity and as a psychophysical quantity, is one of the concepts that can link hard sciences and behavioural sciences. From the viewpoint of behavioural sciences colours are basically measured with nominal scales, and in hard science colours are measured with interval scales. Our hypothesis is that the main relation that must be preserved during colour measurement is a metric. We suggest then that colours must be measured with metrical scales. The fuzzy metrical scale is preferred due to the possibility to define it like a nominal scale

Expression of uncertainty in fuzzy scales based measurements

International audienceFuzzy scales were introduced as a transition between weak scales and strong scales. Preceding studies on fuzzy scales considered only ideal exact measurement without any consideration of uncertainty. The goal of this paper is to present a general approach for the management of uncertainty within the context of fuzzy scale based measurements. After a short reminder on fuzzy scales, a method to define a probability density function or a possibility function on indications given by a fuzzy scale based measurement is exposed. Finally, a method based on the evidence theory is applied to build simultaneously a probability density function and an associated possibility function

Reconfiguration of Distributed Information Fusion System ? A case study

Information Fusion Systems are now widely used in different fusion contexts, like scientific processing, sensor networks, video and image processing. One of the current trends in this area is to cope with distributed systems. In this context, we have defined and implemented a Dynamic Distributed Information Fusion System runtime model. It allows us to cope with dynamic execution supports while trying to maintain the functionalities of a given Dynamic Distributed Information Fusion System. The paper presents our system, the reconfiguration problems we are faced with and our solutions.Comment: 6 pages - Preprint versio

Random effects compound Poisson model to represent data with extra zeros

This paper describes a compound Poisson-based random effects structure for modeling zero-inflated data. Data with large proportion of zeros are found in many fields of applied statistics, for example in ecology when trying to model and predict species counts (discrete data) or abundance distributions (continuous data). Standard methods for modeling such data include mixture and two-part conditional models. Conversely to these methods, the stochastic models proposed here behave coherently with regards to a change of scale, since they mimic the harvesting of a marked Poisson process in the modeling steps. Random effects are used to account for inhomogeneity. In this paper, model design and inference both rely on conditional thinking to understand the links between various layers of quantities : parameters, latent variables including random effects and zero-inflated observations. The potential of these parsimonious hierarchical models for zero-inflated data is exemplified using two marine macroinvertebrate abundance datasets from a large scale scientific bottom-trawl survey. The EM algorithm with a Monte Carlo step based on importance sampling is checked for this model structure on a simulated dataset : it proves to work well for parameter estimation but parameter values matter when re-assessing the actual coverage level of the confidence regions far from the asymptotic conditions.Comment: 4

Processorless Smart Sensors with Distributed Intelligence

International audienceIn the proposed approach, smart sensors own the definition of the software functionalities but are no longer able to execute them locally. Thanks to the network, these software functionalities are sent to a smart sensor, to a smart actuator or to a common resource that has computation facilities

A dedicated language for distributed intelligence based fuzzy sensors

International audienceThis paper presents a concept of distribution of the computational activity over a networked set of fuzzy sensors. This concept is based on the separation of the concept of intelligence and the computational capability. The PLICAS language specially created to apply this concept and its fuzzy processing capabilities are presented. This concept is applied to the fuzzy description of comfort measurement from temperature and humidity measurements

Fuzzy Nominal Scales

International audienceThis paper presents how a representation with fuzzy subsets of symbols can be used to build a scale. Then, the incidence of the fuzziness on this new kind of nominal scale, called fuzzy nominal scale, is analysed