Spectrophotometric characterization of human impacted surface waters in the Moselle watershed

In order to characterize the pollution discharged into the Moselle River and some of its tributaries, spectroscopic techniques, namely UV-vis spectroscopy and synchronous fluorescence spectroscopy, have been combined. UV-visible spectra were analysed using the maximum of the second derivative at 225 nm (related to nitrates), the SUVA254 and E2/E3 indices (related to the nature of organic matter). Synchronous fluorescence spectra (delta lambda = 50 nm) presented different shapes depending upon the type of pollution. The pollution results from anthropogenic activities: untreated domestic sewage due to misconnections in a periurban river, effluent from urban WWTPS, agricultural runoff (nitrates) in several streams, discharge from a paper mill (humic-like substances due to wood processing) and from steel mills (PAHs).     

Flow profile measurement in microchannel using the optical feedback interferometry sensing technique

The need to accurately measure flow profiles in microfluidic channels is well recognised. In this work, we present a new optical feedback interferometry (OFI) flow sensor that accurately measures local velocity in fluids and enables reconstruction of a velocity profile inside a microchannel. OFI is a self-aligned interferometric technique that uses the laser as both the transmitter and the receiver thus offering high sensitivity, fast response, and a simple and compact optical design. The system described here is based on a commercial semiconductor laser and has been designed to achieve a micrometer-range spatial resolution. The sensor performance was validated by reconstructing the velocity profile inside a circular cross-section flow-channel with 320  $\upmu $ m internal diameter, with a relative error smaller than 1.8 %. The local flow velocity is directly measured, thus avoiding the need for model based profile calculation and uncertainties inherent to this approach. The system was validated by successfully extracting the flow profiles in both Newtonian and shear-thinning liquids.     

Characterization of AlPO systems,precursors of the novel basic catalyst family AlPON

XPS and DRIFTS (diffuse reflectance infrared spectroscopy) spectra of AlPO systems, formally AlPO₄-Al₂O₃, obtained by the sol-gel method have been studied in order to understand their geometric and electronic structure. Both DRIFTS and XPS demonstrate that the acidbase character of these samples depends on a structural modification. For low phosphorus content an amorphous spinel-like solid is proposed. This geometric arrangement alters the electronic density of oxide ions and phosphorus cations and hence their Lewis acid-base properties with respect to the amorphous solid having aluminium and phosphorus only in tetrahedral arrangement.     

Discrimination between accelerated life models via Approximate Bayesian Computation

Accelerated life testing (ALT) is widely used in high-reliability product estimation to get relevant information about an item's performance and its failure mechanisms. To analyse the observed ALT data, reliability practitioners need to select a suitable accelerated life model based on the nature of the stress and the physics involved. A statistical model consists of (i) a lifetime distribution that represents the scatter in product life and (ii) a relationship between life and stress. In practice, several accelerated life models could be used for the same failure mode and the choice of the best model is far from trivial. For this reason, an efficient selection procedure to discriminate between a set of competing accelerated life models is of great importance for practitioners. In this paper, accelerated life model selection is approached by using the Approximate Bayesian Computation (ABC) method and a likelihood-based approach for comparison purposes. To demonstrate the efficiency of the ABC method in calibrating and selecting accelerated life model, an extensive Monte Carlo simulation study is carried out using different distances to measure the discrepancy between the empirical and simulated times of failure data. Then, the ABC algorithm is applied to real accelerated fatigue life data in order to select the most likely model among five plausible models. It has been demonstrated that the ABC method outperforms the likelihood-based approach in terms of reliability predictions mainly at lower percentiles particularly useful in reliability engineering and risk assessment applications. Moreover, it has shown that ABC could mitigate the effects of model misspecification through an appropriate choice of the distance function.     

Preserving correctness during business process model configuration

A configurable process model captures a family of related process models in a single artifact. Such models are intended to be configured to fit the requirements of specific organizations or projects, leading to individualized process models that are subsequently used for domain analysis or solution design. This article proposes a formal foundation for individualizing configurable process models incrementally, while preserving correctness, both with respect to syntax and behavioral semantics. Specifically, assuming the configurable process model is behaviorally sound, the individualized process models are guaranteed to be sound. The theory is first developed in the context of Petri nets and then extended to a process modeling notation widely used in practice, namely Event-driven Process Chains.     

A new framework for sharp and efficient resolution of NCSP with manifolds of solutions

When numerical CSPs are used to solve systems of n equations with n variables, the preconditioned interval Newton operator plays two key roles: First it allows handling the n equations as a global constraint, hence achieving a powerful contraction. Second it can prove rigorously the existence of solutions. However, none of these advantages can be used for under-constrained systems of equations, which have manifolds of solutions. A new framework is proposed in this paper to extend the advantages of the preconditioned interval Newton to under-constrained systems of equations. This is achieved simply by allowing domains of the NCSP to be parallelepipeds, which generalize the boxes usually used as domains.     

Co-constructing with stakeholders a role-playing game to initiate collective management of erosive runoff risks at the watershed scale

Erosive runoff is a recurring problem and is a source of sometimes deadly muddy floods in the Pays de Caux (France). The risk results from a conjunction of natural factors and human activity. Efficient actions against runoff in agricultural watersheds are well known. However they are still difficult to implement as they require co-operation between stakeholders. Local actors thus need tools to help them understand the collective consequences of their individual decisions and help to initiate a process of negotiation between them. We decided to use a participatory approach called companion modelling (ComMod), and, in close collaboration with one of the first group of local stakeholders, to create a role-playing game (RPG) to facilitate negotiations on the future management of erosive runoff. This paper describes and discusses the development of the RPG and its use with other groups of local stakeholders within the framework of two game sessions organized by two different watershed management committees. During the joint construction step, stakeholders shared their viewpoints about the environment, agents, rules, and how to model runoff in preparation for the creation of the RPG. During the RPG sessions, two groups of eight players, including farmers, mayors and watershed advisors, were confronted with disastrous runoff in a fictive agricultural watershed. Results showed that they managed to reduce runoff by 20–50% by engaging a dialogue about grass strips, storage ponds and management of the intercrop period. However, further progress is still needed to better control runoff through the implementation of better agricultural practices because, during the RPG sessions, the watershed advisors did not encourage farmers to do so. Because of the complexity of management problems, results of jointly constructing the game and the RPG sessions showed that modelling and simulation can be a very useful way of accompanying the collective learning process. This new way of working was welcomed by the participants who expressed their interest in organizing further RPG sessions.     

APROMORE: An advanced process model repository

Business process models are becoming available in large numbers due to their widespread use in many industrial applications such as enterprise and quality engineering projects. On the one hand, this raises a challenge as to their proper management: how can it be ensured that the proper process model is always available to the interested stakeholder? On the other hand, the richness of a large set of process models also offers opportunities, for example with respect to the re-use of existing model parts for new models. This paper describes the functionality and architecture of an advanced process model repository, named APROMORE. This tool brings together a rich set of features for the analysis, management and usage of large sets of process models, drawing from state-of-the art research in the field of process modeling. A prototype of the platform is presented in this paper, demonstrating its feasibility, as well as an outlook on the further development of APROMORE.     

A knowledge base model for complex forging die machining

Recent evolutions on forging process induce more complex shape on forging die. These evolutions, combined with High Speed Machining (HSM) process of forging die lead to important increase in time for machining preparation. In this context, an original approach for generating machining process based on machining knowledge is proposed in this paper. The core of this approach is to decompose a CAD model of complex forging die in geometrical features. Technological data and topological relations are aggregated to a geometrical feature in order to create machining features. Technological data, such as material, surface roughness and form tolerance are defined during forging process and dies design. These data are used to choose cutting tools and machining strategies. Topological relations define relative positions between the surfaces of the die CAD model. After machining features identification cutting tools and machining strategies currently used in HSM of forging die, are associated to them in order to generate machining sequences. A machining process model is proposed to formalize the links between information imbedded in the machining features and the parameters of cutting tools and machining strategies. At last machining sequences are grouped and ordered to generate the complete die machining process. In this paper the identification of geometrical features is detailed. Geometrical features identification is based on machining knowledge formalization which is translated in the generation of maps from STL models. A map based on the contact area between cutting tools and die shape gives basic geometrical features which are connected or not according to the continuity maps. The proposed approach is illustrated by an application on an industrial study case which was accomplished as part of collaboration.     

Configurable multi-perspective business process models

A configurable process model provides a consolidated view of a family of business processes. It promotes the reuse of proven practices by providing analysts with a generic modeling artifact from which to derive individual process models. Unfortunately, the scope of existing notations for configurable process modeling is restricted, thus hindering their applicability. Specifically, these notations focus on capturing tasks and control-flow dependencies, neglecting equally important ingredients of business processes such as data and resources. This research fills this gap by proposing a configurable process modeling notation incorporating features for capturing resources, data and physical objects involved in the performance of tasks. The proposal has been implemented in a toolset that assists analysts during the configuration phase and guarantees the correctness of the resulting process models. The approach has been validated by means of a case study from the film industry.