2,737 research outputs found

    How to Host a Data Competition: Statistical Advice for Design and Analysis of a Data Competition

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    Data competitions rely on real-time leaderboards to rank competitor entries and stimulate algorithm improvement. While such competitions have become quite popular and prevalent, particularly in supervised learning formats, their implementations by the host are highly variable. Without careful planning, a supervised learning competition is vulnerable to overfitting, where the winning solutions are so closely tuned to the particular set of provided data that they cannot generalize to the underlying problem of interest to the host. This paper outlines some important considerations for strategically designing relevant and informative data sets to maximize the learning outcome from hosting a competition based on our experience. It also describes a post-competition analysis that enables robust and efficient assessment of the strengths and weaknesses of solutions from different competitors, as well as greater understanding of the regions of the input space that are well-solved. The post-competition analysis, which complements the leaderboard, uses exploratory data analysis and generalized linear models (GLMs). The GLMs not only expand the range of results we can explore, they also provide more detailed analysis of individual sub-questions including similarities and differences between algorithms across different types of scenarios, universally easy or hard regions of the input space, and different learning objectives. When coupled with a strategically planned data generation approach, the methods provide richer and more informative summaries to enhance the interpretation of results beyond just the rankings on the leaderboard. The methods are illustrated with a recently completed competition to evaluate algorithms capable of detecting, identifying, and locating radioactive materials in an urban environment.Comment: 36 page

    The Spitzer c2d Survey of Nearby Dense Cores. IX. Discovery of a Very Low Luminosity Object Driving a Molecular Outflow in the Dense Core L673-7

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    We present new infrared, submillimeter, and millimeter observations of the dense core L673-7 and report the discovery of a low-luminosity, embedded Class 0 protostar driving a molecular outflow. L673-7 is seen in absorption against the mid-infrared background in 5.8, 8, and 24 micron Spitzer images, allowing for a derivation of the column density profile and total enclosed mass of L673-7, independent of dust temperature assumptions. Estimates of the core mass from these absorption profiles range from 0.2-4.5 solar masses. Millimeter continuum emission indicates a mass of about 2 solar masses, both from a direct calculation assuming isothermal dust and from dust radiative transfer models constrained by the millimeter observations. We use dust radiative transfer models to constrain the internal luminosity of L673-7, defined to be the luminosity of the central source and excluding the luminosity from external heating, to be 0.01-0.045 solar luminosities, with 0.04 solar luminosities the most likely value. L673-7 is thus classified as a very low luminosity object (VeLLO), and is among the lowest luminosity VeLLOs yet studied. We calculate the kinematic and dynamic properties of the molecular outflow in the standard manner, and we show that the expected accretion luminosity based on these outflow properties is greater than or equal to 0.36 solar luminosities. The discrepancy between this expected accretion luminosity and the internal luminosity derived from dust radiative transfer models indicates that the current accretion rate is much lower than the average rate over the lifetime of the outflow. Although the protostar embedded within L673-7 is consistent with currently being substellar, it is unlikely to remain as such given the substantial mass reservoir remaining in the core.Comment: 19 pages, 14 figures. Accepted by Ap

    Digital First: The Ontological Reversal and New Challenges for IS Research

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    The classical view of an information system is that it represents and reflects physical reality. We suggest this classical view is increasingly obsolete: digital technologies are now creating and shaping physical reality. We call this phenomenon the ontological reversal. The ontological reversal is where the digital version is created first, and the physical version second (if needed). This ontological reversal challenges us to think about the role of humans and technology in society. It also challenges us to think about our role as IS scholars in this digital world and what it means for our research agendas

    Composite Spectral Energy Distributions and Infrared-Optical Colors of Type 1 and Type 2 Quasars

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    We present observed mid-infrared and optical colors and composite spectral energy distributions (SEDs) of type 1 (broad-line) and 2 (narrow-line) quasars selected from Sloan Digital Sky Survey (SDSS) spectroscopy. A significant fraction of powerful quasars are obscured by dust, and are difficult to detect in optical photometric or spectroscopic surveys. However these may be more easily identified on the basis of mid-infrared (MIR) colors and SEDs. Using samples of SDSS type 1 type 2 matched in redshift and [OIII] luminosity, we produce composite rest-frame 0.2-15 micron SEDs based on SDSS, UKIDSS, and Wide-Field Infrared Survey Explorer (WISE) photometry and perform model fits using simple galaxy and quasar SED templates. The SEDs of type 1 and 2 quasars are remarkably similar, with the differences explained primarily by the extinction of the quasar component in the type 2 systems. For both types of quasar, the flux of the AGN relative to the host galaxy increases with AGN luminosity (L_[OIII]) and redder observed MIR color, but we find only weak dependencies of the composite SEDs on mechanical jet power as determined through radio luminosity. We conclude that luminous quasars can be effectively selected using simple MIR color criteria similar to those identified previously (W1-W2 > 0.7 [Vega]), although these criteria miss many heavily obscured objects. Obscured quasars can be further identified based on optical-IR colors (for example, (u-W3 [AB]) > 1.4(W1-W2 [Vega])+3.2). These results illustrate the power of large statistical studies of obscured quasars selected on the basis of mid-IR and optical photometry.Comment: Accepted for publication in ApJ; 14 pages, 9 figures, 2 tables; composite Type 1 and Type 2 quasar SEDs available at http://www.dartmouth.edu/~hickox/Hickox2017_QSO_SED_Table1.tx

    SETTING OUR RESEARCH AGENDAS: INSTITUTIONAL ECOLOGY, INFORMING SCIENCES, OR MANAGEMENT FASHION THEORY?

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    A new reflexive discourse is emerging in the IS research community concerning how we, as academic scholars in the information systems field, set and pursue our research agendas. How should we choose our research topics, how should we conduct our research, and how should we communicate our research results? This panel will present and debate the merits of three distinct perspectives concerning the setting of our research agendas in information systems. There will be three short rounds of presentations by the three panelists: Richard Baskerville, Grandon Gill and Neil Ramiller. Following these presentations, Michael Myers (panel chair) will briefly summarize the discussion so far and give his own views with respect to the merits of the three arguments. After suggesting some key points for debate, he will then facilitate what promises to be an interesting and lively discussion with the audience

    Vapor Sensing Characteristics of Nanoelectromechanical Chemical Sensors Functionalized Using Surface-Initiated Polymerization

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    Surface-initiated polymerization has been used to grow thick, uniform poly(methyl methacrylate) films on nanocantilever sensors. Cantilevers with these coatings yielded significantly greater sensitivity relative to bare devices as well as relative to devices that had been coated with drop-cast polymer films. The devices with surface-initiated polymer films also demonstrated high selectivity toward polar analytes. Surface-initiated polymerization can therefore provide a straightforward, reproducible method for large-scale functionalization of nanosensors
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