New York University

About: New York University is a education organization based out in New York, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 72380 authors who have published 165545 publications receiving 8334030 citations. The organization is also known as: NYU & University of the City of New York.

Modernization: Theories and Facts

Abstract: What makes political regimes rise, endure, and fall? The main question is whether the observed close relation between levels of economic development and the incidence of democratic regimes is due to democracies being more likely to emerge or only more likely to survive in the more developed countries. We answer this question using data concerning 135 countries that existed at any time between 1950 and 1990. We find that the level of economic development does not affect the probability of transitions to democracy but that affluence does make democratic regimes more stable. The relation between affluence and democratic stability is monotonic, and the breakdown of democracies at middle levels of development is a phenomenon peculiar to the Southern Cone of Latin America. These patterns also appear to have been true of the earlier period, but dictatorships are more likely to survive in wealthy countries that became independent only after 1950. We conclude that modernization need not generate democracy but democracies survive in countries that are modern.

The measurement of user information satisfaction

Abstract: This paper critically reviews measures of user information satisfaction and selects one for replication and extension. A survey of production managers is used to provide additional support for the instrument, eliminate scales that are psychometrically unsound, and develop a standard short form for use when only an overall assessment of information satisfaction is required and survey time is limited.

The mixed logit model: the state of practice

Abstract: The mixed logit model is considered to be the most promising state of the art discrete choice model currently available. Increasingly researchers and practitioners are estimating mixed logit models of various degrees of sophistication with mixtures of revealed preference and stated choice data. It is timely to review progress in model estimation since the learning curve is steep and the unwary are likely to fall into a chasm if not careful. These chasms are very deep indeed given the complexity of the mixed logit model. Although the theory is relatively clear, estimation and data issues are far from clear. Indeed there is a great deal of potential mis-inference consequent on trying to extract increased behavioural realism from data that are often not able to comply with the demands of mixed logit models. Possibly for the first time we now have an estimation method that requires extremely high quality data if the analyst wishes to take advantage of the extended behavioural capabilities of such models. This paper focuses on the new opportunities offered by mixed logit models and some issues to be aware of to avoid misuse of such advanced discrete choice methods by the practitioner.

Torch7: A Matlab-like Environment for Machine Learning

Abstract: Torch7 is a versatile numeric computing framework and machine learning library that extends Lua. Its goal is to provide a flexible environment to design and train learning machines. Flexibility is obtained via Lua, an extremely lightweight scripting language. High performance is obtained via efficient OpenMP/SSE and CUDA implementations of low-level numeric routines. Torch7 can easily be interfaced to third-party software thanks to Lua’s light interface.

The Sixth Data Release of the Sloan Digital Sky Survey

Abstract: This paper describes the Sixth Data Release of the Sloan Digital Sky Survey. With this data release, the imaging of the northern Galactic cap is now complete. The survey contains images and parameters of roughly 287 million objects over 9583 deg(2), including scans over a large range of Galactic latitudes and longitudes. The survey also includes 1.27 million spectra of stars, galaxies, quasars, and blank sky ( for sky subtraction) selected over 7425 deg2. This release includes much more stellar spectroscopy than was available in previous data releases and also includes detailed estimates of stellar temperatures, gravities, and metallicities. The results of improved photometric calibration are now available, with uncertainties of roughly 1% in g, r, i, and z, and 2% in u, substantially better than the uncertainties in previous data releases. The spectra in this data release have improved wavelength and flux calibration, especially in the extreme blue and extreme red, leading to the qualitatively better determination of stellar types and radial velocities. The spectrophotometric fluxes are now tied to point-spread function magnitudes of stars rather than fiber magnitudes. This gives more robust results in the presence of seeing variations, but also implies a change in the spectrophotometric scale, which is now brighter by roughly 0.35 mag. Systematic errors in the velocity dispersions of galaxies have been fixed, and the results of two independent codes for determining spectral classifications and red-shifts are made available. Additional spectral outputs are made available, including calibrated spectra from individual 15 minute exposures and the sky spectrum subtracted from each exposure. We also quantify a recently recognized underestimation of the brightnesses of galaxies of large angular extent due to poor sky subtraction; the bias can exceed 0.2 mag for galaxies brighter than r = 14 mag.