The shape and mechanics of curved fold origami structures

We develop recursion equations to describe the three-dimensional shape of a sheet upon which a series of concentric curved folds have been inscribed. In the case of no stretching outside the fold, the three-dimensional shape of a single fold prescribes the shape of the entire origami structure. To better explore these structures, we derive continuum equations, valid in the limit of vanishing spacing between folds, to describe the smooth surface intersecting all the mountain folds. We find that this surface has negative Gaussian curvature with magnitude equal to the square of the fold's torsion. A series of open folds with constant fold angle generate a helicoid

WiPal: Efficient Offline Merging of IEEE 802.11 Traces

Merging wireless traces is a fundamental step in measurement-based studies involving multiple packet sniffers. Existing merging tools either require a wired infrastructure or are limited in their usability. We propose WiPal, an offline merging tool for IEEE 802.11 traces that has been designed to be efficient and simple to use. WiPal is flexible in the sense that it does not require any specific services, neither from monitors (like synchronization, access to a wired network, or embedding specific software) nor from its software environment (e.g. an SQL server). We present WiPal's operation and show how its features - notably, its modular design - improve both ease of use and efficiency. Experiments on real traces show that WiPal is an order of magnitude faster than other tools providing the same features. To our knowledge, WiPal is the only offline trace merger that can be used by the research community in a straightforward fashion.Comment: 6 page

Collaborative sparse regression using spatially correlated supports - Application to hyperspectral unmixing

This paper presents a new Bayesian collaborative sparse regression method for linear unmixing of hyperspectral images. Our contribution is twofold; first, we propose a new Bayesian model for structured sparse regression in which the supports of the sparse abundance vectors are a priori spatially correlated across pixels (i.e., materials are spatially organised rather than randomly distributed at a pixel level). This prior information is encoded in the model through a truncated multivariate Ising Markov random field, which also takes into consideration the facts that pixels cannot be empty (i.e, there is at least one material present in each pixel), and that different materials may exhibit different degrees of spatial regularity. Secondly, we propose an advanced Markov chain Monte Carlo algorithm to estimate the posterior probabilities that materials are present or absent in each pixel, and, conditionally to the maximum marginal a posteriori configuration of the support, compute the MMSE estimates of the abundance vectors. A remarkable property of this algorithm is that it self-adjusts the values of the parameters of the Markov random field, thus relieving practitioners from setting regularisation parameters by cross-validation. The performance of the proposed methodology is finally demonstrated through a series of experiments with synthetic and real data and comparisons with other algorithms from the literature

Professores de matemática portugueses que adotam tecnologias digitais em seus atos curriculares

The article aims to understand the curriculum acts of two Mathematics teachers of Basic Education in public schools in the District of Lisbon in Portugal, regarding the use of digital technologies based on recent reforms in the country. The case study has a qualitative methodological bias and analyzes of the speeches of these teachers were carried out, which showed the dynamics of digital technologies in the approach of interdisciplinarity, within the scope of the Information Technology discipline, through Curricular Flexibility in mathematical and non-mathematical contexts. It also emerged the dissonance between the teachers' curriculum acts, Mathematical Education and the curricular proposals in force in the country, as well as the need to expand studies and research in the field of Digital Literacy and Computational Thinking, so that may be promoted practices that develop students' autonomy and creative process

Plausible Mobility: Inferring Movement from Contacts

We address the difficult question of inferring plausible node mobility based only on information from wireless contact traces. Working with mobility information allows richer protocol simulations, particularly in dense networks, but requires complex set-ups to measure, whereas contact information is easier to measure but only allows for simplistic simulation models. In a contact trace a lot of node movement information is irretrievably lost so the original positions and velocities are in general out of reach. We propose a fast heuristic algorithm, inspired by dynamic force-based graph drawing, capable of inferring a plausible movement from any contact trace, and evaluate it on both synthetic and real-life contact traces. Our results reveal that (i) the quality of the inferred mobility is directly linked to the precision of the measured contact trace, and (ii) the simple addition of appropriate anticipation forces between nodes leads to an accurate inferred mobility.Comment: 8 pages, 8 figures, 1 tabl