4 resultados para Barry Boehm

em University of Connecticut - USA


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Source materials like fine art, over-sized, fragile maps, and delicate artifacts have traditionally been digitally converted through the use of controlled lighting and high resolution scanners and camera backs. In addition the capture of items such as general and special collections bound monographs has recently grown both through consortial efforts like the Internet Archive's Open Content Alliance and locally at the individual institution level. These projects, in turn, have introduced increasingly higher resolution consumer-grade digital single lens reflex cameras or "DSLRs" as a significant part of the general cultural heritage digital conversion workflow. Central to the authors' discussion is the fact that both camera backs and DSLRs commonly share the ability to capture native raw file formats. Because these formats include such advantages as access to an image's raw mosaic sensor data within their architecture, many institutions choose raw for initial capture due to its high bit-level and unprocessed nature. However to date these same raw formats, so important to many at the point of capture, have yet to be considered "archival" within most published still imaging standards, if they are considered at all. Throughout many workflows raw files are deleted and thrown away after more traditionally "archival" uncompressed TIFF or JPEG 2000 files have been derived downstream from their raw source formats [1][2]. As a result, the authors examine the nature of raw anew and consider the basic questions, Should raw files be retained? What might their role be? Might they in fact form a new archival format space? Included in the discussion is a survey of assorted raw file types and their attributes. Also addressed are various sustainability issues as they pertain to archival formats with a special emphasis on both raw's positive and negative characteristics as they apply to archival practices. Current common archival workflows versus possible raw-based ones are investigated as well. These comparisons are noted in the context of each approach's differing levels of usable captured image data, various preservation virtues, and the divergent ideas of strictly fixed renditions versus the potential for improved renditions over time. Special attention is given to the DNG raw format through a detailed inspection of a number of its various structural components and the roles that they play in the format's latest specification. Finally an evaluation is drawn of both proprietary raw formats in general and DNG in particular as possible alternative archival formats for still imaging.

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Nutrient leaching studies are expensive and require expertise in water collection and analyses. Less expensive or easier methods that estimate leaching losses would be desirable. The objective of this study was to determine if anion-exchange membranes (AEMs) and reflectance meters could predict nitrate (NO3-N) leaching losses from a cool-season lawn turf. A two-year field study used an established 90% Kentucky bluegrass (Poa pratensis L.)-10% creeping red fescue (Festuca rubra L.) turf that received 0 to 98 kg N ha-1 month-1, from May through November. Soil monolith lysimeters collected leachate that was analyzed for NO3-N concentration. Soil NO3-N was estimated with AEMs. Spectral reflectance measurements of the turf were obtained with chlorophyll and chroma meters. No significant (p > 0.05) increase in percolate flow-weighted NO3-N concentration (FWC) or mass loss occurred when AEM desorbed soil NO3-N was below 0.84 µg cm-2 d-1. A linear increase in FWC and mass loss (p < 0.0001) occurred, however, when AEM soil NO3-N was above this value. The maximum contaminant level (MCL) for drinking water (10 mg L-1 NO3-N) was reached with an AEM soil NO3-N value of 1.6 µg cm-2 d-1. Maximum meter readings were obtained when AEM soil NO3 N reached or exceeded 2.3 µg cm-2 d-1. As chlorophyll index and hue angle (greenness) increased, there was an increased probability of exceeding the NO3-N MCL. These data suggest that AEMs and reflectance meters can serve as tools to predict NO3-N leaching losses from cool-season lawn turf, and to provide objective guides for N fertilization.

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University of Connecticut Health Center, Central Administrative Services, Annual Report, Fiscal Year 2006-2007; Submitted by Barry Feldman, Vice President & Chief Operation Officer, University of Connecticut, and Susan Whetstone, Chief Administrative Officer, UConn Health Center, August 2007