33,171 research outputs found
Local framings
Framings provide a way to construct Quillen functors from simplicial sets to any given model category. A more structured set-up studies stable frames giving Quillen functors from spectra to stable model categories. We will investigate how this is compatible with Bousfield localisation to gain insight into the deeper structure of the stable homotopy category. We further show how these techniques relate to rigidity questions and how they can be used to study algebraic model categories
Synopsis of current satellite snow mapping techniques, with emphasis on the application of near-infrared data
The Skylab EREP S192 Multispectral Scanner data have provided for the first time an opportunity to examine the reflectance characteristics of snowcover in several spectral bands extending from the visible into the near-infrared spectral region. The analysis of the S192 imagery and digital tape data indicates a sharp drop in reflectance of snow in the near-infrared, with snow becoming essentially nonreflective in Bands 11 (1.55-1.75 micron) and 12 (2.10-2.35 micron). Two potential applications to snow mapping of measurements in the near-infrared spectral region are possible: (1) the use of a near-infrared band in conjunction with a visible band to distinguish automatically between snow and water droplet clouds; and (2) the use of one or more near-infrared bands to detect areas of melting snow
An integrated model for green partner selection and supply chain construction
Stricter governmental regulations and rising public awareness of environmental issues are pressurising firms to make their supply chains greener. Partner selection is a critical activity in constructing a green supply chain because the environmental performance of the whole supply chain is significantly affected by all its constituents. The paper presents a model for green partner selection and supply chain construction by combining analytic network process (ANP) and multi-objective programming (MOP) methodologies. The model offers a new way of solving the green partner selection and supply chain construction problem both effectively and efficiently as it enables decision-makers to simultaneously minimize the negative environmental impact of the supply chain whilst maximizing its business performance. The paper also develops an additional decision-making tool in the form of the environmental difference, the business difference and the eco-efficiency ratio which quantify the trade-offs between environmental and business performance. The applicability and practicability of the model is demonstrated in an illustration of its use in the Chinese electrical appliance and equipment manufacturing industry
Helioseismology of Pre-Emerging Active Regions II: Average Emergence Properties
We report on average subsurface properties of pre-emerging active regions as
compared to areas where no active region emergence was detected. Helioseismic
holography is applied to samples of the two populations (pre-emergence and
without emergence), each sample having over 100 members, which were selected to
minimize systematic bias, as described in Leka et al. We find that there are
statistically significant signatures (i.e., difference in the means of more
than a few standard errors) in the average subsurface flows and the apparent
wave speed that precede the formation of an active region. The measurements
here rule out spatially extended flows of more than about 15 m/s in the top 20
Mm below the photosphere over the course of the day preceding the start of
visible emergence. These measurements place strong constraints on models of
active region formation.Comment: 15 pages, 10 figures, ApJ (published
Unleashing the Power of Distributed CPU/GPU Architectures: Massive Astronomical Data Analysis and Visualization case study
Upcoming and future astronomy research facilities will systematically
generate terabyte-sized data sets moving astronomy into the Petascale data era.
While such facilities will provide astronomers with unprecedented levels of
accuracy and coverage, the increases in dataset size and dimensionality will
pose serious computational challenges for many current astronomy data analysis
and visualization tools. With such data sizes, even simple data analysis tasks
(e.g. calculating a histogram or computing data minimum/maximum) may not be
achievable without access to a supercomputing facility.
To effectively handle such dataset sizes, which exceed today's single machine
memory and processing limits, we present a framework that exploits the
distributed power of GPUs and many-core CPUs, with a goal of providing data
analysis and visualizing tasks as a service for astronomers. By mixing shared
and distributed memory architectures, our framework effectively utilizes the
underlying hardware infrastructure handling both batched and real-time data
analysis and visualization tasks. Offering such functionality as a service in a
"software as a service" manner will reduce the total cost of ownership, provide
an easy to use tool to the wider astronomical community, and enable a more
optimized utilization of the underlying hardware infrastructure.Comment: 4 Pages, 1 figures, To appear in the proceedings of ADASS XXI, ed.
P.Ballester and D.Egret, ASP Conf. Serie
The application of ERTS imagery to mapping snow cover in the western United States
The author has identified the following significant results. In much of the western United States a large part of the utilized water comes from accumulated mountain snowpacks; thus, accurate measurements of snow distributions are required for input to streamflow prediction models. The application of ERTS-1 imagery for mapping snow has been evaluated for two geographic areas, the Salt-Verde watershed in central Arizona and the southern Sierra Nevada in California. Techniques have been developed to identify snow and to differentiate between snow and cloud. The snow extent for these two drainage areas has been mapped from the MSS-5 (0.6 - 0.7 microns) imagery and compared with aerial survey snow charts, aircraft photography, and ground-based snow measurements. The results indicate that ERTS imagery has substantial practical applications for snow mapping. Snow extent can be mapped from ERTS-1 imagery in more detail than is depicted on aerial survey snow charts. Moreover, in Arizona and southern California cloud obscuration does not appear to be a serious deterrent to the use of satellite data for snow survey. The costs involved in deriving snow maps from ERTS-1 imagery appear to be very reasonable in comparison with existing data collection methods
A study to develop improved spacecraft show survey methods using Skylab/EREP data: Demonstration of the utility of the S190 and S192 data
The author has identified the following significant results. This interim report provides a demonstration of the utility of spacecraft acquired Skylab S190A and S190B photography and S192 imagery for mapping areal extent of snow cover in western United States test site areas. The data sample is from the SL-2 mission flown in June 1973. Results of the investigation indicate that areal snow cover extent can be mapped more accurately from the S190A and S190B photography than from any other spacecraft system, including ERTS. The results of a qualitative analysis of the S192 imagery indicate considerable potential for the utility of multispectral snow cover analysis; the potential for distinguishing snow from clouds automatically is particularly significant
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