No maintenance activity can be performed without understanding at least the part of the program that needs to b emodified. Therefore, considering its cost, helping developers to understand programs is a must. Consequently, our research aims at building a business related model of the program semantics, which is grounded in Perkinsfi research in psychology. After a short reminder of our model, whose performance in helping developers to understand programs has been presented elsewhere, this paper presents the automatic instantiation of the model. This rests on the ontology technology a swell as on an innovative dynamic analysis technique. We present a use case to evaluate the performance of our technique.
Environmental taxes are often underexploited. This paper analyses the effectiveness of a garbage tax, assessing its effects on multiple outcomes as well as its acceptability. We study how a Supreme Court decision, mandating the Swiss Canton of Vaud to implement a tax on garbage, affects garbage production and beliefs about the tax. We adopt a difference-in-differences approach exploiting that parts of Vaud already implemented a garbage tax before the mandate. Pricing garbage by the bag (PGB) is highly effective, reducing unsorted garbage by 40%, increasing recycling of aluminium and organic waste, without causing negative spillovers on adjacent regions. The effects of PGB seem very persistent over time. Our assessment of PGB looks very favourable. It may surprise that PGB is not implemented more often. Hence, we look at people's perceptions. We find that people are very concerned with PGB ex ante. Public opposition seems to be the main obstacle to PGB. However, implementing PGB reduces concerns with effectiveness and fairness substantially. After implementing PGB, people accept 70% higher garbage taxes compared to before PGB. We argue that environmental taxes could be much more diffused, if people had the chance to experience their functioning and correct their beliefs.
Le projet "Grand Genève" peine à créer autour de lui un sentiment d'identification fort. La collaboration entre le canton de Genève, le canton de Vaud et les départements de la Haute-Savoie et de l'Ain reste depuis 2005 une entreprise qui apparaît lointaine et détachée de toute notion affective aux yeux de la population. L'étude des discours politiques et des textes institutionnels et médiatiques en lien avec le projet franco-valdo-genevois constitue ici un symptôme révélateur de cette situation.
We explore the benefits of operator splitting algorithms in the context of computational fluid dynamics. In particular, we exploit their capacity in handling free surface flows and a large variety of physical phenomena in a flexible way. A mathematical and computational framework is presented for the numerical simulation of free surface flows, where the operator splitting strategy allows to separate inertial effects from the other effects. The characteristics method on a fine structured grid is put forward to accurately approximate the inertial effects while continuous piecewise polynomial finite element subordinated to a coarser subdivision made of simplices is advocated for the other effects. In addition, the splitting strategy also allows to be modular and change the rheological model for the fluid in a straightforward manner.We will emphasize this flexibility by treating Newtonian flows, viscoelastic flows and multi-phase immiscible incompressible Newtonian flows based on multiple densities. The numerical framework is thoroughly presented; the test case of the filling of a cylindrical tube, with potential die swell in an extrusion process is taken as the main illustration of the advantages of operator splitting.
This paper focuses on the application of tractable route choice models and presents a set of methods for deriving relevant disaggregate and aggregate route choice indicators, namely link and route flows. Tractability is achieved at the disaggregate level by the recursive logit model and at the aggregate level by the mental representation item (MRI) approach. These two approaches are analyzed here, and extensions of the MRI approach are presented. The analysis elaborates on the features of each model and allows to draw insights into the use of a specific model, depending on the needs of the application and the data availability. The performance of the two models is tested on real data. The results demonstrate the validity of the MRI model that is intended for aggregate analysis.
The consensus that complexity begets stability in ecosystems was challenged in the seventies, a result recently extended to ecologically-inspired networks. The approaches assume the existence of a feasible equilibrium, i.e. with positive abundances. However, this key assumption has not been tested. We provide analytical results complemented by simulations which show that equilibrium feasibility vanishes in species rich systems. This result leaves us in the uncomfortable situation in which the existence of a feasible equilibrium assumed in local stability criteria is far from granted. We extend our analyses by changing interaction structure and intensity, and find that feasibility and stability is warranted irrespective of species richness with weak interactions. Interestingly, we find that the dynamical behaviour of ecologically inspired architectures is very different and richer than that of unstructured systems. Our results suggest that a general understanding of ecosystem dynamics requires focusing on the interplay between interaction strength and network architecture.
This paper analyzes and compares different policy scenarios as well as discusses price elasticities and willingness to pay and to accept using revealed preference (RP) data from the French new-car market in 2014 by means of a cross-nested logit (CNL) model. We focus particularly on electric and hybrid vehicles. We use interactions between the cost (both fixed and running costs) and the household income to analyze the sensitivity towards different policy scenarios per income level. Results show that the willingness to pay and to accept obtained in our study is consistent with the real-market conditions. We also find that the most effective scenario to increase the market shares of new sold electric vehicles is that of a major technological advance such as a decrease in price due to cheaper manufacturing costs and an increase in driving range, rather than a policy-based scenario. In addition, the market segment that has more potential to increase the market shares of electric vehicle purchase is the middle-income level. In the paper, we discuss how to overcome the difficulties of working with revealed preference data, and propose multiple imputations to impute the attributes of the unchosen alternatives, by drawing from their empirical distributions.
