A generalized wavelet extrema representation

The wavelet extrema representation originated by Stephane Mallat is a unique framework for low-level and intermediate-level (feature) processing. In this paper, we present a new form of wavelet extrema representation generalizing Mallat`s original work. The generalized wavelet extrema representation is a feature-based multiscale representation. For a particular choice of wavelet, our scheme can be interpreted as representing a signal or image by its edges, and peaks and valleys at multiple scales. Such a representation is shown to be stable -- the original signal or image can be reconstructed with very good quality. It is further shown that a signal or image can be modeled as piecewise monotonic, with all turning points between monotonic segments given by the wavelet extrema. A new projection operator is introduced to enforce piecewise inonotonicity of a signal in its reconstruction. This leads to an enhancement to previously developed algorithms in preventing artifacts in reconstructed signal

Pro-environmental behaviors and well-being in everyday life

Individual and household behaviors are key targets for climate change mitigation efforts, and studies suggest that people who enact more pro-environmental behaviors tend to experience higher levels of well-being. Yet these studies have typically used coarse-grained, retrospective reports that offer limited insight into the immediate impacts of specific behaviors. In three studies (total N = 8,522 observations, N = 1,353 US and UK participants) we adopted a highly fine-grained approach. Using the day reconstruction method, we zoomed in on particular moments in everyday life to examine links between specific behaviors and different aspects of well-being. This revealed generally positive associations, but also substantial variation. Pro-environmental behaviors are more closely and consistently associated with positive and especially "eudaimonic" dimensions of well-being. And more active, effortful, and social behaviors tended to show stronger positive associations. Although the relationships between pro-environmental behaviors and well-being are considerably more complex than prior research has indicated, these findings continue to suggest that ecological and individual well-being can be pursued in tandem

Analysis of Piezoresistive Effects in Silicon Structures Using Multidimensional Process and Device Simulation

Abstract With the view to analyzing piezoresistive effects in silicon microstructures we implemented a rigorous physically-based model in the multidimensional general purpose device simulator DESSIS'~~. In this model, the dependence of the piezoresistive coefficients on temperahue and doping concentration is included in a numerically hactable way. Using a commercial TCAD system (ISE), the practicability of the approach is demonstrated by performing a complete simulation sequence for realistic microdevices ranging from the layout design up to the analysis of the device operation

Shape Matching and Object Recognition

We approach recognition in the framework of deformable shape matching, relying on a new algorithm for finding correspondences between feature points. This algorithm sets up correspondence as an integer quadratic programming problem, where the cost function has terms based on similarity of corresponding geometric blur point descriptors as well as the geometric distortion between pairs of corresponding feature points. The algorithm handles outliers, and thus enables matching of exemplars to query images in the presence of occlusion and clutter. Given the correspondences, we estimate an aligning transform, typically a regularized thin plate spline, resulting in a dense correspondence between the two shapes. Object recognition is handled in a nearest neighbor framework where the distance between exemplar and query is the matching cost between corresponding points. We show results on two datasets. One is the Caltech 101 dataset (Li, Fergus and Perona), a challenging dataset with large intraclass variation. Our approach yields a 45 % correct classification rate in addition to localization. We also show results for localizing frontal and profile faces that are comparable to special purpose approaches tuned to faces

Recent developments in Behavioural Public Policy: IBPPC 2022

Editorial