Generation Y: Unchartered Territory

Businesses continue to be challenged with workforce diversity and how to best manage the differences that exist in race, religion, gender, disability, sexual orientation, color, etc.  The general theme is that managers should focus on minimizing tension that exists resulting from generational differences.  Unfortunately, there is more agreement and discussion as to how generations are different than there is on how to manage these differences.&nbsp

Coal Miners and Third-Party Politics in Illinois, 1880-1924: A Statistical Analysis of Voting Behavior

http://deepblue.lib.umich.edu/bitstream/2027.42/50857/1/76.pd

Application of Artificial Neural Network to Search for Gravitational-Wave Signals Associated with Short Gamma-Ray Bursts

We apply a machine learning algorithm, the artificial neural network, to the search for gravitational-wave signals associated with short gamma-ray bursts. The multi-dimensional samples consisting of data corresponding to the statistical and physical quantities from the coherent search pipeline are fed into the artificial neural network to distinguish simulated gravitational-wave signals from background noise artifacts. Our result shows that the data classification efficiency at a fixed false alarm probability is improved by the artificial neural network in comparison to the conventional detection statistic. Therefore, this algorithm increases the distance at which a gravitational-wave signal could be observed in coincidence with a gamma-ray burst. In order to demonstrate the performance, we also evaluate a few seconds of gravitational-wave data segment using the trained networks and obtain the false alarm probability. We suggest that the artificial neural network can be a complementary method to the conventional detection statistic for identifying gravitational-wave signals related to the short gamma-ray bursts.Comment: 30 pages, 10 figure

The Effect of Star Formation History on the Inferred Initial Stellar Mass Function

Peaks and lulls in the star formation rate (SFR) over the history of the Galaxy produce plateaux and declines in the present day mass function (PDMF) where the main-sequence lifetime overlaps the age and duration of the SFR variation. These PDMF features can be misinterpreted as the form of the intrinsic stellar initial mass function (IMF) if the star formation rate is assumed to be constant or slowly varying with time. This effect applies to all regions that have formed stars for longer than the age of the most massive stars, including OB associations, star complexes, and especially galactic field stars. Related problems may apply to embedded clusters. Evidence is summarized for temporal SFR variations from parsec scales to entire galaxies, all of which should contribute to inferred IMF distortions. We give examples of various star formation histories to demonstrate the types of false IMF structures that might be seen. These include short-duration bursts, stochastic histories with log-normal amplitude distributions, and oscillating histories with various periods and phases. The inferred IMF should appear steeper than the intrinsic IMF over mass ranges where the stellar lifetimes correspond to times of decreasing SFRs; shallow portions of the inferred IMF correspond to times of increasing SFRs. If field regions are populated by dispersed clusters and defined by their low current SFRs, then they should have steeper inferred IMFs than the clusters. The SFRs required to give the steep field IMFs in the LMC and SMC are determined. Structure observed in several determinations of the Milky Way field star IMF can be accounted for by a stochastic and bursty star formation history.Comment: accepted by ApJ for 1 Jan 2006, Vol 636, 12 pages + 6 figure

Observations and Implications of the Star Formation History of the LMC

We present derivations of star formation histories based on color-magnitude diagrams of three fields in the LMC from HST/WFPC2 observations. A significant component of stars older than 4 Gyr is required to match the observed color-magnitude diagrams. Models with a dispersion-free age-metallicity relation are unable to reproduce the width of the observed main sequence; models with a range of metallicity at a given age provide a much better fit. Such models allow us to construct complete ``population boxes'' for the LMC based entirely on color-magnitude diagrams; remarkably, these qualitatively reproduce the age-metallicity relation observed in LMC clusters. We discuss some of the uncertainties in deriving star formation histories. We find, independently of the models, that the LMC bar field has a larger relative component of older stars than the outer fields. The main implications suggested by this study are: 1) the star formation history of field stars appears to differ from the age distribution of clusters, 2) there is no obvious evidence for bursty star formation, but our ability to measure bursts shorter in duration than $\sim$ 25% of any given age is limited by the statistics of the observed number of stars, 3) there may be some correlation of the star formation rate with the last close passage of the LMC/SMC/Milky Way, but there is no dramatic effect, and 4) the derived star formation history is probably consistent with observed abundances, based on recent chemical evolution models.Comment: Accepted by AJ, 36 pages including 12 figure

Informatics and data mining tools and strategies for the Human Connectome Project

The Human Connectome Project (HCP) is a major endeavor that will acquire and analyze connectivity data plus other neuroimaging, behavioral, and genetic data from 1,200 healthy adults. It will serve as a key resource for the neuroscience research community, enabling discoveries of how the brain is wired and how it functions in different individuals. To fulfill its potential, the HCP consortium is developing an informatics platform that will handle: 1) storage of primary and processed data, 2) systematic processing and analysis of the data, 3) open access data sharing, and 4) mining and exploration of the data. This informatics platform will include two primary components. ConnectomeDB will provide database services for storing and distributing the data, as well as data analysis pipelines. Connectome Workbench will provide visualization and exploration capabilities. The platform will be based on standard data formats and provide an open set of application programming interfaces (APIs) that will facilitate broad utilization of the data and integration of HCP services into a variety of external applications. Primary and processed data generated by the HCP will be openly shared with the scientific community, and the informatics platform will be available under an open source license. This paper describes the HCP informatics platform as currently envisioned and places it into the context of the overall HCP vision and agenda