Asteroids Observed by The Sloan Digital Sky Survey

We announce the first public release of the SDSS Moving Object Catalog, with SDSS observations for 58,117 asteroids. The catalog lists astrometric and photometric data for moving objects observed prior to Dec 15, 2001, and also includes orbital elements for 10,592 previously known objects. We analyze the correlation between the orbital parameters and optical colors for the known objects, and confirm that asteroid dynamical families, defined as clusters in orbital parameter space, also strongly segregate in color space. Their distinctive optical colors indicate that the variations in chemical composition within a family are much smaller than the compositional differences between families, and strongly support earlier suggestions that asteroids belonging to a particular family have a common origin.Comment: 6 pages, 1 color figure, to be presented at "Astronomical Telescopes & Instrumentation", SPIE 200

A Modified Magnitude System that Produces Well-Behaved Magnitudes, Colors, and Errors Even for Low Signal-to-Noise Ratio Measurements

We describe a modification of the usual definition of astronomical magnitudes, replacing the usual logarithm with an inverse hyperbolic sine function; we call these modified magnitudes `asinh magnitudes'. For objects detected at signal-to-noise ratios of greater than about five, our modified definition is essentially identical to the traditional one; for fainter objects (including those with a formally negative flux) our definition is well behaved, tending to a definite value with finite errors as the flux goes to zero. This new definition is especially useful when considering the colors of faint objects, as the difference of two `asinh' magnitudes measures the usual flux ratio for bright objects, while avoiding the problems caused by dividing two very uncertain values for faint objects. The Sloan Digital Sky Survey (SDSS) data products will use this scheme to express all magnitudes in their catalogs.Comment: 11 pages, including 3 postscript figures. Submitted to A

An Efficient Targeting Strategy for Multiobject Spectrograph Surveys: the Sloan Digital Sky Survey "Tiling" Algorithm

Large surveys using multiobject spectrographs require automated methods for deciding how to efficiently point observations and how to assign targets to each pointing. The Sloan Digital Sky Survey (SDSS) will observe around 10 6 spectra from targets distributed over an area of about 10,000 deg2, using a multiobject fiber spectrograph that can simultaneously observe 640 objects in a circular field of view (referred to as a "tile") 1°.49 in radius. No two fibers can be placed closer than 55Prime; during the same observation; multiple targets closer than this distance are said to "collide." We present here a method of allocating fibers to desired targets given a set of tile centers that includes the effects of collisions and that is nearly optimally efficient and uniform. Because of large-scale structure in the galaxy distribution (which form the bulk of the SDSS targets), a naive covering of the sky with equally spaced tiles does not yield uniform sampling. Thus, we present a heuristic for perturbing the centers of the tiles from the equally spaced distribution that provides more uniform completeness. For the SDSS sample, we can attain a sampling rate of greater than 92% for all targets, and greater than 99% for the set of targets that do not collide with each other, with an efficiency greater than 90% (defined as the fraction of available fibers assigned to targets). The methods used here may prove useful to those planning other large surveys

Early-type galaxies in the SDSS. II. Correlations between observables

A magnitude limited sample of nearly 9000 early-type galaxies, in the redshift range 0.01 < z < 0.3, was selected from the Sloan Digital Sky Survey using morphological and spectral criteria. The sample was used to study how early-type galaxy observables, including luminosity L, effective radius R_o, surface brightness I_o, color, and velocity dispersion sigma, are correlated with one another. Measurement biases are understood with mock catalogs which reproduce all of the observed scaling relations and their dependences on fitting technique. At any given redshift, the intrinsic distribution of luminosities, sizes and velocity dispersions in our sample are all approximately Gaussian. A maximum likelihood analysis shows that sigma ~ L^{0.25\pm 0.012}, R_o ~ L^{0.63\pm 0.025}, and R_o ~ I^{-0.75\pm 0.02} in the r* band. In addition, the mass-to-light ratio within the effective radius scales as M_o/L ~ L^{0.14\pm 0.02} or M_o/L ~ M_o^{0.22\pm 0.05}, and galaxies with larger effective masses have smaller effective densities: Delta_o ~ M_o^{-0.52\pm 0.03}. These relations are approximately the same in the g*, i* and z* bands. Relative to the population at the median redshift in the sample, galaxies at lower and higher redshifts have evolved only little, with more evolution in the bluer bands. The luminosity function is consistent with weak passive luminosity evolution and a formation time of about 9 Gyrs ago.Comment: 29 pages, 11 figures. Accepted by AJ (scheduled for April 2003). This paper is part II of a revised version of astro-ph/011034

In good company: risk, security and choice in young people's drug decisions

This article draws on original empirical research with young people to question the degree to which 'individualisation of risk', as developed in the work of Beck and Giddens, adequately explains the risks young people bear and take. It draws on alternative understandings and critiques of 'risk' not to refute the notion of the reflexive individual upon which 'individualisation of risk' is based but to re-read that reflexivity in a more hermeneutic way. It explores specific risk-laden moments – young people's drug use decisions – in their natural social and cultural context of the friendship group. Studying these decisions in context, it suggests, reveals the meaning of 'risk' to be not given, but constructed through group discussion, disagreement and consensus and decisions taken to be rooted in emotional relations of trust, mutual accountability and common security. The article concludes that 'the individualisation of risk' fails to take adequate account of the significance of intersubjectivity in risk-decisions. It argues also that addressing the theoretical overemphasis on the individual bearer of risk requires not only further empirical testing of the theory but appropriate methodological reflection

Personal data broker instead of blockchain for students’ data privacy assurance

Data logs about learning activities are being recorded at a growing pace due to the adoption and evolution of educational technologies (Edtech). Data analytics has entered the field of education under the name of learning analytics. Data analytics can provide insights that can be used to enhance learning activities for educational stakeholders, as well as helping online learning applications providers to enhance their services. However, despite the goodwill in the use of Edtech, some service providers use it as a means to collect private data about the students for their own interests and benefits. This is showcased in recent cases seen in media of bad use of students’ personal information. This growth in cases is due to the recent tightening in data privacy regulations, especially in the EU. The students or their parents should be the owners of the information about them and their learning activities online. Thus they should have the right tools to control how their information is accessed and for what purposes. Currently, there is no technological solution to prevent leaks or the misuse of data about the students or their activity. It seems appropriate to try to solve it from an automation technology perspective. In this paper, we consider the use of Blockchain technologies as a possible basis for a solution to this problem. Our analysis indicates that the Blockchain is not a suitable solution. Finally, we propose a cloud-based solution with a central personal point of management that we have called Personal Data Broker.Peer ReviewedPostprint (author's final draft