Central catadioptric image processing with geodesic metric

Because of the distortions produced by the insertion of a mirror, catadioptric images cannot be processed similarly to classical perspective images. Now, although the equivalence between such images and spherical images is well known, the use of spherical harmonic analysis often leads to image processing methods which are more difficult to implement. In this paper, we propose to define catadioptric image processing from the geodesic metric on the unitary sphere. We show that this definition allows to adapt very simply classical image processing methods. We focus more particularly on image gradient estimation, interest point detection, and matching. More generally, the proposed approach extends traditional image processing techniques based on Euclidean metric to central catadioptric images. We show in this paper the efficiency of the approach through different experimental results and quantitative evaluations.     

Metaphors and Context-Aware Information Access

Metaphors are often used to provide the user with a mental model to ease the use of computers. An example of such a metaphor is the commonly used “Desktop Metaphor”. Metaphors also can be used to ease context-aware information access for the users of mobile information systems. In this paper we present a taxonomy that allows the categorisation of such metaphors. Furthermore, we give an overview of existing metaphors and their implementations. After introducing some new metaphors we conclude our considerations with a classification of new and existing metaphors using our taxonomy.     

Relational Analysis and Precision via Probabilistic Abstract Interpretation

Within the context of a quantitative generalisation of the well established framework of Abstract Interpretation – i.e. Probabilistic Abstract Interpretation – we investigate a quantitative notion of precision which allows us to compare analyses on the basis of their expected exactness for a given program. We illustrate this approach by considering various types of numerical abstractions of the values of variables for independent analysis as well as weakly and fully relational analysis. We utilise for this a linear operator semantics of a simple imperative programming language. In this setting, fully relational dependencies are realised via the tensor product. Independent analyses and weakly relational analyses are realised as abstractions of the fully relational analysis.     

Bringing Scheme programming to the iPhone—Experience

The iPhone SDK provides a powerful platform for the development of applications that make use of iPhone capabilities, such as sensors, GPS, Wi‐Fi, or Bluetooth connectivity. We observe that so far the development of iPhone applications has mostly been restricted to using Objective‐C. However, developing applications in plain Objective‐C on the iPhone OS suffers from limitations, such as the need for explicit memory management and lack of syntactic extension mechanism. Moreover, when developing distributed applications in Objective‐C, programmers have to manually deal with distribution concerns, such as service discovery, remote communication, and failure handling. In this paper, we discuss our experience in porting the Scheme programming language to the iPhone OS and how it can be used together with Objective‐C to develop iPhone applications. To support the interaction between Scheme programs and the underlying iPhone APIs, we have implemented a language symbiosis layer that enables programmers to access the iPhone SDK libraries from Scheme. In addition, we have designed high‐level distribution constructs to ease the development of distributed iPhone applications in an event‐driven style. We validate and discuss these constructs with a series of examples, including an iPod controller, a maps application, and a distributed multiplayer Scrabble‐like game. We discuss the lessons learned from this experience for other programming language ports to mobile platforms. Copyright © 2011 John Wiley & Sons, Ltd.     

GPU Shape Grammars

GPU Shape Grammars provide a solution for interactive procedural generation, tuning and visualization of massive environment elements for both video games and production rendering. Our technique generates detailed models without explicit geometry storage. To this end we reformulate the grammar expansion for generation of detailed models at the tesselation control and geometry shader stages. Using the geometry generation capabilities of modern graphics hardware, our technique generated massive, highly detailed models. GPU Shape Grammars integrate within a scalable framework by introducing automatic generation of levels of detail at reduced cost. We apply our solution for interactive generation and rendering of scenes containing thousands of buildings and trees.     

Finite Volume Time Domain modelling of microwave breakdown and plasma formation in a metallic aperture

The modelling of plasma formation during microwave breakdown is a difficult task because of the strong non-linear coupling between Maxwell?s equations and plasma equations, and of the large plasma density gradients that form during breakdown. An original Finite Volume Time Domain (FVTD) method has been developed to solve Maxwell?s equations coupled with a simplified fluid plasma model and is described in this paper. This method is illustrated with the study of the shielding of a metallic aperture by the plasma generated by an incident high power electromagnetic wave. Typical results obtained with the FVTD method for this shielding problem are shown.     

Control-oriented modeling of a three-way catalytic converter with observation of the relative oxygen level profile

The paper presents a novel control-oriented, first-principle model of a three-way catalytic converter (TWC). The model accurately predicts the air–fuel ratio downstream of the catalyst and provides insights into the relative oxygen level (ROL) profile along the catalyst. The reaction mechanism of the TWC model is simplified to only two reactions, with oxygen being the only species stored on the active surface of the catalyst. All the information about the gas composition is taken from the upstream wide-range oxygen sensor. Additional model inputs are the exhaust gas temperature and the exhaust mass flow. The model is parameterized with only a few measurements from an engine test bench. Exact values of gas concentrations are not needed at any point.The ROL profile is a good indicator for the condition of the TWC. It can therefore be used to derive optimal TWC depletion strategies after fuel cut-off phases. Since the model is real-time capable, the ROL profile can even be used for on-line control strategies. Based thereon, a causal strategy is proposed with results that match those of the non-causal strategies found in off-line optimizations.     

Dynamic Spar Elements and Discrete Element Methods in Two Dimensions for the Modeling of Soil-Inclusion Problems

Discrete element methods (DEMs) provide new numerical means to study the behavior of soil-inclusion systems. In some cases, however, the classic DEM fails to model specific aspects of the inclusions. That is why a model based on spar elements is introduced, designed specifically for inclusions. In this model, the movement of the inclusion is considered as a dynamic process and is computed step by step in the same way as in the DEM. The model can be coupled with a DEM code, thus enabling one to simulate the interaction between an inclusion and a disk assembly. Contact laws at the contacts between disks and spar elements describe the interface constitutive behavior. Finally, the results obtained by simulating a geosynthetic anchorage in two different ways are reported. In the first case the inclusion is represented by disks, while in the last case it is represented by spar elements. The comparison shows that spar elements are much more versatile and can simplify the calibration of the discrete models used to simulate soil-inclusion systems.