3,736 research outputs found
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
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