Skill set profile clustering based on student capability vectors computed from online tutoring data

In educational research, a fundamental goal is identifying which skills students have mastered, which skills they have not, and which skills they are in the process of mastering. As the number of examinees, items, and skills increases, the estimation of even simple cognitive diagnosis models becomes difficult. To address this, we introduce a capability matrix showing for each skill the proportion correct on all items tried by each student involving that skill. We apply variations of common clustering methods to this matrix and discuss conditioning on sparse subspaces. We demonstrate the feasibility and scalability of our method on several simulated datasets and illustrate the difficulties inherent in real data using a subset of online mathematics tutor data. We also comment on the interpretability and application of the results for teachers

Skill set profile clustering: the empty K-means algorithm with automatic specification of starting cluster centers

While students’ skill set profiles can be estimated with formal cognitive diagnosis models [8], their computational complexity makes simpler proxy skill estimates attractive [1, 4, 6]. These estimates can be clustered to generate groups of similar students. Often hierarchical agglomerative clustering or k-means clustering is utilized, requiring, for K skills, the specification of 2^K clusters. The number of skill set profiles/clusters can quickly become computationally intractable. Moreover, not all profiles may be present in the population. We present a flexible version of k-means that allows for empty clusters. We also specify a method to determine efficient starting centers based on the Q-matrix. Combining the two substantially improves the clustering results and allows for analysis of data sets previously thought impossible

User manual for the Earth observations Division R and D to OLPARS dot data conversion

There are no author-identified significant results in this report

The Yarkovsky Drift's Influence on NEAs: Trends and Predictions with NEOWISE Measurements

We used WISE-derived geometric albedos (p_V) and diameters, as well as geometric albedos and diameters from the literature, to produce more accurate diurnal Yarkovsky drift predictions for 540 near-Earth asteroids (NEAs) out of the current sample of \sim 8,800 known objects. As ten of the twelve objects with the fastest predicted rates have observed arcs of less than a decade, we list upcoming apparitions of these NEAs to facilitate observations.Comment: Accepted for publication by The Astronomical Journal. 41 pages, 3 figure

Main Belt Asteroids with WISE/NEOWISE: Near-Infrared Albedos

We present revised near-infrared albedo fits of 2835 Main Belt asteroids observed by WISE/NEOWISE over the course of its fully cryogenic survey in 2010. These fits are derived from reflected-light near-infrared images taken simultaneously with thermal emission measurements, allowing for more accurate measurements of the near-infrared albedos than is possible for visible albedo measurements. As our sample requires reflected light measurements, it undersamples small, low albedo asteroids, as well as those with blue spectral slopes across the wavelengths investigated. We find that the Main Belt separates into three distinct groups of 6%, 16%, and 40% reflectance at 3.4 um. Conversely, the 4.6 um albedo distribution spans the full range of possible values with no clear grouping. Asteroid families show a narrow distribution of 3.4 um albedos within each family that map to one of the three observed groupings, with the (221) Eos family being the sole family associated with the 16% reflectance 3.4 um albedo group. We show that near-infrared albedos derived from simultaneous thermal emission and reflected light measurements are an important indicator of asteroid taxonomy and can identify interesting targets for spectroscopic followup.Comment: Accepted for publication in ApJ; full version of Table1 to be published electronically in the journa

Pressures measured in flight on the aft fuselage and external nozzle of a twin-jet fighter

Fuselage, boundary layer, and nozzle pressures were measured in flight for a twin jet fighter over a Mach number range from 0.60 to 2.00 at test altitudes of 6100, 10,700, and 13,700 meters for angles of attack ranging from 0 deg to 7 deg. Test data were analyzed to find the effects of the propulsion system geometry. The flight variables, and flow interference. The aft fuselage flow field was complex and showed the influence of the vertical tail, nacelle contour, and the wing. Changes in the boattail angle of either engine affected upper fuselage and lower fuselage pressure coefficients upstream of the nozzle. Boundary layer profiles at the forward and aft locations on the upper nacelles were relatively insensitive to Mach number and altitude. Boundary layer thickness decreased at both stations as angle of attack increased above 4 deg. Nozzle pressure coefficient was influenced by the vertical tail, horizontal tail boom, and nozzle interfairing; the last two tended to separate flow over the top of the nozzle from flow over the bottom of the nozzle. The left nozzle axial force coefficient was most affected by Mach number and left nozzle boattail angle. At Mach 0.90, the nozzle axial force coefficient was 0.0013

Resolution Study

Resolution effects on cartographic data using conventional stereoplotters with photographs taken at orbital height

Influence of Confinement on Dynamical Heterogeneities in Dense Colloidal Samples

We study a dense colloidal suspension confined between two quasiparallel glass plates as a model system for a supercooled liquid in confined geometries. We directly observe the three-dimensional Brownian motion of the colloidal particles using laser scanning confocal microscopy. The particles form dense layers along the walls, but crystallization is avoided as we use a mixture of two particle sizes. A normally liquid-like sample, when confined, exhibits slower diffusive motion. Particle rearrangements are spatially heterogeneous, and the shapes of the rearranging regions are strongly influenced by the layering. These rearranging regions become more planar upon confinement. The wall-induced layers and changing character of the spatially heterogeneous dynamics appear strongly connected to the confinement induced glassiness.Comment: revised version describes particle-wall interactions in more detail, among other change

Could There Be A Hole In Type Ia Supernovae?

In the favored progenitor scenario, Type Ia supernovae arise from a white dwarf accreting material from a non-degenerate companion star. Soon after the white dwarf explodes, the ejected supernova material engulfs the companion star; two-dimensional hydrodynamical simulations by Marietta et. al. show that, in the interaction, the companion star carves out a conical hole of opening angle 30-40 degrees in the supernova ejecta. In this paper we use multi-dimensional Monte Carlo radiative transfer calculations to explore the observable consequences of an ejecta-hole asymmetry. We calculate the variation of the spectrum, luminosity, and polarization with viewing angle for the aspherical supernova near maximum light. We find that the supernova looks normal from almost all viewing angles except when one looks almost directly down the hole. In the latter case, one sees into the deeper, hotter layers of ejecta. The supernova is relatively brighter and has a peculiar spectrum characterized by more highly ionized species, weaker absorption features, and lower absorption velocities. The spectrum viewed down the hole is comparable to the class of SN 1991T-like supernovae. We consider how the ejecta-hole asymmetry may explain the current spectropolarimetric observations of SNe Ia, and suggest a few observational signatures of the geometry. Finally, we discuss the variety currently seen in observed SNe Ia and how an ejecta-hole asymmetry may fit in as one of several possible sources of diversity.Comment: 11 pages, 9 figures, submitted to Ap