Image processing algorithm for the identification of Martian dust devil tracks in MOC and HiRISE images

This paper presents a method for automatic identification of dust devils tracks in MOC NA and HiRISE images of Mars. The method is based on Mathematical Morphology and is able to successfully process those images despite their difference in spatial resolution or size of the scene. A dataset of 200 images from the surface of Mars representative of the diversity of those track features was considered for developing, testing and evaluating our method, confronting the outputs with reference images made manually. Analysis showed a mean accuracy of about 92%. We also give some examples on how to use the results to get information about dust devils, namelly mean width, main direction of movement and coverage per scene. (c) 2012 Elsevier Ltd. All rights reserved.

Dynamical evolution of Saturn's F ring dust particles

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Orbital evolution of the mu and nu dust ring particles of Uranus

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

First-order formalism for dark energy and dust

This work deals with a first-order formalism for dark energy and dust in standard cosmology, for models described by a real scalar field in the presence of dust in spatially flat space. The field dynamics may be standard or tachyonic, and we show how the equations of motion can be solved by first-order differential equations. We investigate a model to illustrate how the dustlike matter may affect the cosmic evolution using this framework.

A study on automatic methods based on mathematical morphology for Martian dust devil tracks detection

This paper presents three methods for automatic detection of dust devils tracks in images of Mars. The methods are mainly based on Mathematical Morphology and results of their performance are analyzed and compared. A dataset of 21 images from the surface of Mars representative of the diversity of those track features were considered for developing, testing and evaluating our methods, confronting their outputs with ground truth images made manually. Methods 1 and 3, based on closing top-hat and path closing top-hat, respectively, showed similar mean accuracies around 90% but the time of processing was much greater for method 1 than for method 3. Method 2, based on radial closing, was the fastest but showed worse mean accuracy. Thus, this was the tiebreak factor. © 2011 Springer-Verlag.

Automated determination of the orientation of dust devil tracks in mars orbiter images

The paper presents and evaluates three methods for automatically estimating the main orientation of Martian dust devil tracks in MOC and HiRISE images. Inferring such information about dust devils from their tracks is important to better understand the near surface wind. The methods considered were based on gradient direction, directional openings and morphological granulometry. The accuracy of the methods was asserted by comparing the results to a set of directions estimated visually and assumed to be the ground truth. The higher accuracy was reached using directional openings. Besides, the directions inferred by this method were compared to those predicted by the GCM and the results agreed. © 2013 COSPAR.

Detecção automática de rastros de Dust Devils na superfície de Marte

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Extensive computation of albedo contrast between martian dust devil tracks and their neighboring regions

We have developed a method to compute the albedo contrast between dust devil tracks and their surrounding regions on Mars. It is mainly based on Mathematical Morphology operators and uses all the points of the edges of the tracks to compute the values of the albedo contrast. It permits the extraction of more accurate and complete information, when compared to traditional point sampling, not only providing better statistics but also permitting the analysis of local variations along the entirety of the tracks. This measure of contrast, based on relative quantities, is much more adequate to establish comparisons at regional scales and in multi-temporal basis using imagery acquired in rather different environmental and operational conditions. Also, the substantial increase in the details extracted may permit quantifying differential depositions of dust by computing local temporal fading of the tracks with consequences on a better estimation of the thickness of the top most layer of dust and the minimum value needed to create dust devils tracks. The developed tool is tested on 110 HiRISE images depicting regions in the Aeolis, Argyre, Eridania, Noachis and Hellas quadrangles. As a complementary evaluation, we also performed a temporal analysis of the albedo in a region of Russell crater, where high seasonal dust devil activity was already observed before, comprising the years 2007-2012. The mean albedo of the Russell crater is in this case indicative of dust devil tracks presence and, therefore, can be used to quantify dust devil activity. (C) 2014 Elsevier Inc. All rights reserved.

O fluxo da consciência em Ask the dust, de John Fante

The purpose of this research is to present de narrative techniques of the Stream of Consciousness in the novel Ask the dust, by American writer John Fante, as well as analyzing the technique applying it to the character/narrator Arturo Bandini. Among others, the emphasys was given to the interior monologue technique, for its large and intense use throughout the analyzed novel. This research was based specially on O Fluxo da consciência (1976), by Robert Humphrey, and Foco narrativo e fluxo da consciência (2012), de Alfredo Leme Coelho de Carvalho, both important researchers in the studied theme. This research, therefore, intends to demonstrate the geniality of the still little-known John Fante and point out the peculiarities of the so-called 'psychological fiction', that in the early 20th century united literature and psychology studies, becoming very popular in modern literature, with exponents like Virginia Woolf and James Joyce