3 resultados para format

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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Our paper asks the question: Does mode of instruction format (live or online format) effect test scores in the principles of macroeconomics classes? Our data are from several sections of principles of macroeconomics, some in live format, some in online format, and all taught by the same instructor. We find that test scores for the online format, when corrected for sample selection bias, are four points higher than for the live format, and the difference is statistically significant. One possible explanation for this is that there was slightly higher human capital in the classes that had the online format. A Oaxaca decomposition of this difference in grades was conducted to see how much was due to human capital and how much was due to the differences in the rates of return to human capital. This analysis reveals that 25% of the difference was due to the higher human capital with the remaining 75% due to differences in the returns to human capital. It is possible that for the relatively older student with the appropriate online learning skill set, and with schedule constrains created by family and job, the online format provides them with a more productive learning environment than does the alternative traditional live class format. Also, because our data are limited to the student s academic transcript, we recommend future research include data on learning style characteristics, and the constraints formed by family and job choices.

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All previous studies comparing online and face-to-face format for instruction of economics compared courses that were either online or face-to-face format and regressed exam scores on selected student characteristics. This approach is subject to the econometric problems of self-selection omitted unobserved variables. Our study uses two methods to deal with these problems. First we eliminate self-selection bias by using students from a course that uses both instruction formats. Second, we use the exam questions as the unit of observation, and eliminate omitted variable bias by using an indicator variable for each student to capture the effect of differences in unobserved student characteristics on learning outcomes. We report the finding that students had a significantly greater chance of answering a question correctly if it came from a chapter covered online.