Estimation of State-of-Charge and Capacity of Used Lithium-Ion Cells

We describe an approach to estimate state-of-charge and faded capacity of cobalt-based lithium-ion cell based on timedomain analysis of a short-term transient. This approach requires a relatively short-duration test and is suitable for repurposing cells for less demanding applications. The successful estimation requires previous characterization of the cells for the given family because lithium ion chemistries differ significantly. Two algorithms were considered for estimation of unknown state-of-charge and capacity: Bayesian inference and boosted regression trees. The achieved accuracy was 95 % of capacity estimations; estimations were within 2 % of the nominal cell capacity from the true value

LSST Science Book, Version 2.0

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

Controlling and evaluating inpainting with attentional models

At present, there does not exist an accepted quantitative method for inpainting evaluation. Psychophysical experiments show, however, that human opinion can be reliably predicted by computational models of human attention. Furthermore, adopting these psychophysical concepts in the design of inpainting algorithms can improve their output quality and efficiency. Thus, by emphasizing human observation of inpainted imagery rather than fitting purely geometric or physics-based models, it is possible to drastically improve the state-of-the-art in inpainting. This material is based upon work supported by Eastman Kodak Gifts and NYSTAR Award #C040130. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the above named organizations

Using Conditional Random Fields for Decision-Theoretic Planning

We propose a means of extending Conditional Random Field modeling to decision-theoretic planning where valuation is dependent upon fully observable factors. Representation is discussed, and a comparison with existing decision problem methodologies is presented. Included are exact and inexact message passing schemes for policy making, examples of decision making in practice, extensions to solving general decision problems, and suggestions for future use

Controlling and evaluating inpainting with attentional models

Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 2010.At present, there does not exist an accepted quantitative method for inpainting evaluation. Psychophysical experiments show, however, that human opinion can be reliably predicted by computational models of human attention. Furthermore, adopting these psychophysical concepts in the design of inpainting algorithms can improve their output quality and efficiency. Thus, by emphasizing human observation of inpainted imagery rather than tting purely geometric or physics-based models, it is possible to drastically improve the state-of-the-art in inpainting