John F. Wallin

Two new templates for epidemiology applications : linked micromap plots and conditioned choropleth maps

This paper describes two interactive templates for representing spatially indexed estimates. Both templates use a matrix layout of small panels. The first template, called linked micromap plots, can represent multivariate estimates associated with each spatially indexed study unit. The second template, called conditioned choropleth maps, shows the connection between a dependent variable, as represented in a classed choropleth map, and two explanatory variables. The paper describes the cognitive considerations that motivate the layouts and representation details. The discussion also addresses topics of data quality and access, hypothesis generation, and interactive features such as pan and zoom and dynamic conditioning via sliders. The examples show epidemiological (mortality rates) and environmental (toxic concentrations) applications.

Testing Gravity in the Outer Solar System: Results from Trans-Neptunian Objects

The inverse square law of gravity is poorly probed by experimental tests at distances of ~10 AU. Recent analysis of the trajectory of the Pioneer 10 and 11 spacecraft have shown an unmodeled acceleration directed toward the Sun, which was not explained by any obvious spacecraft systematics, and occurred when at distances greater than 20 AU from the Sun. If this acceleration represents a departure from Newtonian gravity or is indicative of an additional mass distribution in the outer solar system, it should be detectable in the orbits of trans-Neptunian objects (TNOs). To place limits on deviations from Newtonian gravity, we have selected a well-observed sample of TNOs found orbiting between 20 and 100 AU from the Sun. By examining their orbits with modified orbital fitting software, we place tight limits on the perturbations of gravity that could exist in this region of the solar system.

Can Minor Planets Be Used to Assess Gravity in the Outer Solar System

The twin Pioneer spacecraft have been tracked for over 30 years as they headed out of the solar system. After passing 20 AU from the Sun, both exhibited a systematic error in their trajectories that can be interpreted as a constant acceleration toward the Sun. This Pioneer effect is most likely explained by spacecraft systematics, but there have been no convincing arguments that that is the case. The alternative is that the Pioneer effect represents a real phenomenon and perhaps new physics. What is lacking is a means of measuring the effect, its variation, its potential anisotropies, and its region of influence. We show that minor planets provide an observational vehicle for investigating the gravitational field in the outer solar system and that a sustained observation campaign against properly chosen minor planets could confirm or refute the existence of the Pioneer effect. In addition, even if the Pioneer effect does not represent a new physical phenomenon, minor planets can be used to probe the gravitational field in the outer solar system, and since there are very few intermediate-range tests of gravity at the multiple-AU distance scale, this is a worthwhile endeavor in its own right.

Classification of large acoustic datasets using machine learning and crowdsourcing : application to whale calls

Vocal communication is a primary communication method of killer and pilot whales, and is used for transmitting a broad range of messages and information for short and long distance. The large variation in call types of these species makes it challenging to categorize them. In this study, sounds recorded by audio sensors carried by ten killer whales and eight pilot whales close to the coasts of Norway, Iceland, and the Bahamas were analyzed using computer methods and citizen scientists as part of the Whale FM project. Results show that the computer analysis automatically separated the killer whales into Icelandic and Norwegian whales, and the pilot whales were separated into Norwegian long-finned and Bahamas short-finned pilot whales, showing that at least some whales from these two locations have different acoustic repertoires that can be sensed by the computer analysis. The citizen science analysis was also able to separate the whales to locations by their sounds, but the separation was somewhat less accurate compared to the computer method.

Combining Human and Machine Learning for Morphological Analysis of Galaxy Images

AbstractThe increasing importance of digital sky surveys collecting many millions of galaxy images has reinforced the need for robust methods that can perform morphological analysis of large galaxy image databases. Citizen science initiatives such as Galaxy Zoo showed that large data sets of galaxy images can be analyzed effectively by nonscientist volunteers, but since databases generated by robotic telescopes grow much faster than the processing power of any group of citizen scientists, it is clear that computer analysis is required. Here, we propose to use citizen science data for training machine learning systems, and show experimental results demonstrating that machine learning systems can be trained with citizen science data. Our findings show that the performance of machine learning depends on the quality of the data, which can be improved by using samples that have a high degree of agreement between the citizen scientists. The source code of the method is publicly available.

How Well do We Know the Orbits of the Outer Planets

This paper deals with the problem of astrometric determination of the orbital elements of the outer planets, in particular by assessing the ability of astrometric observations to detect perturbations of the sort expected from the Pioneer effect or other small perturbations to gravity. We also show that while using simplified models of the dynamics can lead to some insights, one must be careful to not oversimplify the issues involved lest one be misled by the analysis onto false paths. Specifically, we show that the current ephemeris of Pluto does not preclude the existence of the Pioneer effect. We show that the orbit of Pluto is simply not well enough characterized at present to make such an assertion. A number of misunderstandings related to these topics have now propagated through the literature and have been used as a basis for drawing conclusions about the dynamics of the solar system. Thus, the objective of this paper is to address these issues. Finally, we offer some comments dealing with the complex topic of model selection and comparison.

The evolutionary history of the interacting Galaxy system NGC 7714/7715 (Arp 284)

The distribution and kinematics of atomic hydrogen in an interacting galaxy pair are studied to develop a model of its formation and assess its implications. H I gas peaks, bridges, and tails for NGC 7714/7715 (Arp 284) are identified with the VLA observations, and the velocity field appears to indicate that of an inclined rotating disk. A parabolic off-center collision is modeled for two disk galaxies with different masses, and formation scenario leads to results consistent with the observations. The point of closest approach occurred 1.1 x 10 exp 8 years ago, and the inclination angle for NGC 7714 is given at around 30 deg. This ring galaxys lack of star formation is attributed to the large impact parameter associated with the parabolic off-center collision considered for Arp 284. Star formation and the initial mass function of the interacting galaxy pair are studied to assess the age and composition of the objects.

Automatic detection and quantitative assessment of peculiar galaxy pairs in Sloan Digital Sky Survey

We applied computational tools for automatic detection of peculiar galaxy pairs. We rst detected in SDSS DR7 400,000 galaxy images with i magnitude <18 that had more than one point spread function, and then applied a machine learning algorithm that detected 26,000 galaxy images that had morphology similar to the morphology of galaxy mergers. That dataset was mined using a novelty detection algorithm, producing a short list of 500 most peculiar galaxies as quantitatively determined by the algorithm. Manual examination of these galaxies showed that while most of the galaxy pairs in the list were not necessarily peculiar, numerous unusual galaxy pairs were detected. In this paper we describe the protocol and computational tools used for the detection of peculiar mergers, and provide examples of peculiar galaxy pairs that were detected.

Galaxy Zoo: Mergers – Dynamical models of interacting galaxies

The dynamical history of most merging galaxies is not well understood. Correlations between galaxy interaction and star formation have been found in previous studies, but require the context of the physical history of merging systems for full insight into the processes that lead to enhanced star formation. We present the results of simulations that reconstruct the orbit trajectories and disturbed morphologies of pairs of interacting galaxies. With the use of a restricted three-body simulation code and the help of citizen scientists, we sample 105 points in parameter space for each system. We demonstrate a successful recreation of the morphologies of 62 pairs of interacting galaxies through the review of more than 3 million simulations. We examine the level of convergence and uniqueness of the dynamical properties of each system. These simulations represent the largest collection of models of interacting galaxies to date, providing a valuable resource for the investigation of mergers. This paper presents the simulation parameters generated by the project. They are now publicly available in electronic format at http://data.galaxyzoo.org/mergers.html. Though our best-fitting model parameters are not an exact match to previously published models, our method for determining uncertainty measurements will aid future comparisons between models. The dynamical clocks from our models agree with previous results of the time since the onset of star formation from starburst models in interacting systems and suggest that tidally induced star formation is triggered very soon after closest approach.

The New Computational and Data Sciences Undergraduate Program at George Mason University

We describe the new undergraduate science degree program in Computational and Data Sciences (CDS) at George Mason University (Mason), which began offering courses for both major (B.S.) and minor degrees in Spring 2008. The overarching theme and goal of the program are to train the next-generation scientists in the tools and techniques of cyber-enabled science (e-Science) to prepare them to confront the emerging petascale challenges of data-intensive science. The Mason CDS program has a significantly stronger focus on data-oriented approaches to science than do most computational science and engineering programs. The program has been designed specifically to focus both on simulation (Computational Science) and on data-intensive applications (Data Science). New courses include Introduction to Computational & Data Sciences, Scientific Data and Databases, Scientific Data & Information Visualization, Scientific Data Mining, and Scientific Modeling & Simulation. This is an interdisciplinary science program, drawing examples, classroom materials, and student activities from a broad range of physical and biological sciences. We will describe some of the motivations and early results from the program. More information is available at http://cds.gmu.edu/.