Emulsion sheet doublets as interface trackers for the OPERA experiment

New methods for efficient and unambiguous interconnection between electronic counters and target units based on nuclear photographic emulsion films have been developed. The application to the OPERA experiment, that aims at detecting oscillations between mu neutrino and tau neutrino in the CNGS neutrino beam, is reported in this paper. In order to reduce background due to latent tracks collected before installation in the detector, on-site large-scale treatments of the emulsions ("refreshing") have been applied. Changeable Sheet (CSd) packages, each made of a doublet of emulsion films, have been designed, assembled and coupled to the OPERA target units ("ECC bricks"). A device has been built to print X-ray spots for accurate interconnection both within the CSd and between the CSd and the related ECC brick. Sample emulsion films have been extensively scanned with state-of-the-art automated optical microscopes. Efficient track-matching and powerful background rejection have been achieved in tests with electronically tagged penetrating muons. Further improvement of in-doublet film alignment was obtained by matching the pattern of low-energy electron tracks. The commissioning of the overall OPERA alignment procedure is in progress.Comment: 19 pages, 19 figure

Method and apparatus for predicting the direction of movement in machine vision

A computer-simulated cortical network is presented. The network is capable of computing the visibility of shifts in the direction of movement. Additionally, the network can compute the following: (1) the magnitude of the position difference between the test and background patterns; (2) localized contrast differences at different spatial scales analyzed by computing temporal gradients of the difference and sum of the outputs of paired even- and odd-symmetric bandpass filters convolved with the input pattern; and (3) the direction of a test pattern moved relative to a textured background. The direction of movement of an object in the field of view of a robotic vision system is detected in accordance with nonlinear Gabor function algorithms. The movement of objects relative to their background is used to infer the 3-dimensional structure and motion of object surfaces

What visual literacy is not!

This paper intends to help design educators reach a more informed understanding of visual literacy by stating what we already know it is not, in order to promote discussion on how it can be fostered. This paper is based on Jefferies’ PhD research from an empirical visual experiment carried out on a wide range of design practitioners, design students and the general public. Specific terms of influence such as ‘fixed’, ‘cross-disciplines’ and ‘accessibility’ were highlighted for discussion when considering what visual literacy is not, and were consequently used to frame the problem. When considering each of these influences in terms of seeing; (a) Viewing visual language as a ‘fixed’ vocabulary does not allow for each working context to have its own visual value system. (b) Literacy of ‘cross-disciplines’ may not enable a way of seeing to be transferred between each design discipline. (c) ‘Accessibility’ in terms of a student’s ability to read or write an image can not be determined from a designer’s final product, as each individual and context is different. It is proposed that debating the three identified areas will heighten design educators’ awareness and provide a valuable basis for future pedagogy practices

A Consistent Histogram Estimator for Exchangeable Graph Models

Exchangeable graph models (ExGM) subsume a number of popular network models. The mathematical object that characterizes an ExGM is termed a graphon. Finding scalable estimators of graphons, provably consistent, remains an open issue. In this paper, we propose a histogram estimator of a graphon that is provably consistent and numerically efficient. The proposed estimator is based on a sorting-and-smoothing (SAS) algorithm, which first sorts the empirical degree of a graph, then smooths the sorted graph using total variation minimization. The consistency of the SAS algorithm is proved by leveraging sparsity concepts from compressed sensing.Comment: 28 pages, 5 figure