Identification and classification of galaxies using a biologically-inspired neutral network

Recognition/Classification of galaxies is an important issue in the large-scale study of the Universe; it is not a simple task. According to estimates computed from the Hubble Deep Field (HDF), astronomers predict that the universe may potentially contain over 100 billion galaxies. Several techniques have been reported for the classification of galaxies. Parallel developments in the field of neural networks have come to a stage that they can participate well in the recognition of objects. Recently, the Pulse-Coupled Neural Network (PCNN) has been shown to be useful for image pre-processing. In this paper, we present a novel way to identify optical galaxies by presenting the images of the galaxies to a hierarchical neural network involving two PCNNs. The image is presented to the network to generate binary barcodes (one per iteration) of the galaxies; the barcodes are unique to the input galactic image. In the current study, we exploit this property to identify optical galaxies by comparing the signatures (binary barcode) from a corresponding database. This revised version was published online in July 2006 with corrections to the Cover Date.     

1D Solar Image Synthesis: A Multifrequency Analysis

The radio emission from the solar corona is related to the configuration of the inner atmosphere. By studying the Sun at multiple frequencies, different layers of plasma in solar atmosphere are probed. We use the Mauritius Radio Telescope. The quiet Sun period, difference maps using synthesized 1D maps reveal a certain regular feature, the origin of which is not thoroughly understood and which is attributed to the solar differential rotation. For the active Sun period, the coronal emission is linked to the magnetic field configuration originating from the inner atmosphere. As expected, a strong correlation exists between the MRT 151 MHz and Nancay 164 MHz radio emission. This revised version was published online in July 2006 with corrections to the Cover Date.     

A drought climatology for Mauritius using the standardized precipitation index

This study presents a high-resolution and multi-temporal drought climatology for Mauritius based on calculated standardized precipitation index (SPI) using mean monthly rainfall for the period 1953–2007. A monthly mean SPI varying from +3.4 to ?2.7 indicates the occurrence of extremely wet and dry conditions, and collocated SPI indicates more frequent mild drought conditions. Spatial maps of rainfall trends and SPI show mostly neutral to severely dry conditions, but sparse regions of extremely wet and dry conditions are also observed. An increase in the frequency of dry years after the 1990s is noted, while most of the extreme wet conditions are found to have occurred between 1972 and 1988. More frequent short-duration wet events are observed on the 3- and 6-month time scales compared to dry events. On the 12- and 24-month time scales the frequency of both dry and wet periods is almost the same, with the dry events lasting longer.     

Intra-event characteristics of extreme erosive rainfall on Mauritius

Mauritius is a volcanic island with a raised interior where extreme rainfall events dominate rainfall erosivity. Intra-event characteristics of the 120 highest erosive events at six selected locations between 2004 and 2008 were analyzed to provide the first detailed intra-storm data for a tropical island environment. On Mauritius, spatial variation is evident in the characteristics of extreme erosive rainfall recorded at the stations, with a noticeable increase in rainfall depth, duration, kinetic energy, and erosivity of extreme events with altitude. Extreme events in the raised interior (central plateau) show high variability of peak intensity over time as well as a higher percentage of events in which the greatest intensity occurs in the latter part of the event. Intra-event distribution of rainfall in the interior of the island shows that rainfall there has a higher potential to exceed infiltration rates as well as the ability to generate high peak runoff rates and cause substantial soil loss. The study suggests that even though within-event rainfall characteristics are complex, they have implications for soil erosion risk, and that, in tropical island environments, the within-storm distribution of rainfall should be incorporated in soil-loss modeling.     

A New Tool for Handling Astronomical Images

A variety of software exists for the manipulation ofastrophysical data. For example, we have theAstronomical Image Processing software (AIPS) which isused by astronomers. Other software like MATLAB arealso widely used to manipulate the astrophysicalimages. We demonstrate that there are tremendouspotentials for using the Geographic InformationSystems (GIS) to analyze astrophysical images at allfrequencies. To our knowledge, celestial objects havenot been studied so far using GIS. We have exploredthe possible use of a GIS to study the Sun and thesouthern sky (using data from the Mauritius RadioTelescope Low Resolution Survey and the PARKESObservatory). Most of the images at differentfrequencies available over the Internet were importedinto a GIS software (IDRISI, Version 4.0) for thestudy. A number of operations supported by GISsoftware were used for our studies. For instance,Principal Component Analysis has been used on a set ofCoronal White Light images in the tracking of the timeevolution of Coronal Mass Ejections and in `cleaning'images, in integrated flux density computations ofselected supernova remnants, and in supervisedclassification of solar images and supernova remnants.