1,310 research outputs found

    Stay Tuned: Whether Cloud-Based Service Providers Can Have Their Copyrighted Cake and Eat It Too

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    Copyright owners have the exclusive right to perform their works publicly and the ability to license their work to others who want to share that right. Subsections 106(4) and (5) of the Copyright Act govern this exclusive public performance right, but neither subsection elaborates on what constitutes a performance made “to the public” versus one that remains private. This lack of clarity has made it difficult for courts to apply the Copyright Act consistently, especially in the face of changing technology. Companies like Aereo, Inc. and AereoKiller, Inc. developed novel ways to transmit content over the internet to be viewed instantly by their subscribers and declined to procure the licenses that would have been required if these transmissions were being made “to the public.” However, while these companies claimed that their activities were outside of the purview of § 106(4) and (5), their rivals, copyright owners, and the U.S. Supreme Court disagreed. Likening Aereo to a cable company for purposes of § 106(4) and (5), the Supreme Court determined that the company would need to pay for the material it streamed. Perhaps more problematic for Aereo (and other similar companies) is the fact that the Court declined to categorize Aereo as an actual cable company, such that it would qualify to pay compulsory licensing fees—the more affordable option given to cable companies under § 111—to copyright holders. This Comment shows that, while the Court correctly ruled that companies like Aereo and AereoKiller should pay for the content transmitted, its failure to address whether Aereo is a cable company could frustrate innovation to the detriment of the public. It suggests, therefore, that these companies should be required to pay for the content that they transmit in the same way that cable companies do until Congress develops another system

    Television Remixed: The Controversy Over Commercial–Skipping

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    The disruptor's dilemma: TiVo and the U.S. television ecosystem

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    Firms introducing disruptive innovations into multisided ecosystems may confront the disruptor's dilemma – they must gain the support of the very incumbents they disrupt. We examine how these firms may address this dilemma through a longitudinal study of TiVo, a company that pioneered the Digital Video Recorder. Our analysis reveals how TiVo navigated co-opetitive tensions by continually adjusting its strategy, its technology platform, and its relational positioning within the evolving U.S. television industry ecosystem. We theorize how (a) disruption may affect not just specific incumbents, but also the entire ecosystem, (b) co-opetition is not just dyadic, but also multilateral and intertemporal, and (c) strategy is both a deliberative and emergent process involving continual adjustments, as the disruptor attempts to balance co-opetitive tensions over time

    Can we ID from CCTV? Image quality in digital CCTV and face identification performance

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    CCTV is used for an increasing number Of purposes, and the new generation of digital systems can be tailored to serve a wide range of security requirements. However, configuration decisions are often made without considering specific task requirements, e.g. the video quality needed for reliable person identification. Our Study investigated the relationship between video quality and the ability of untrained viewers to identify faces from digital CCTV images. The task required 80 participants to identify 64 faces belonging to 4 different ethnicities. Participants compared face images taken from a high quality photographs and low quality CCTV stills, which were recorded at 4 different video quality bit rates (32, 52, 72 and 92 Kbps). We found that the number of correct identifications decreased by 12 (similar to 18%) as MPEG-4 quality decreased from 92 to 32 Kbps, and by 4 (similar to 6%) as Wavelet video quality decreased from 92 to 32 Kbps. To achieve reliable and effective face identification, we recommend that MPEG-4 CCTV systems should be used over Wavelet, and video quality should not be lowered below 52 Kbps during video compression. We discuss the practical implications of these results for security, and contribute a contextual methodology for assessing CCTV video quality

    Augmenting data warehousing architectures with hadoop

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementAs the volume of available data increases exponentially, traditional data warehouses struggle to transform this data into actionable knowledge. Data strategies that include the creation and maintenance of data warehouses have a lot to gain by incorporating technologies from the Big Data’s spectrum. Hadoop, as a transformation tool, can add a theoretical infinite dimension of data processing, feeding transformed information into traditional data warehouses that ultimately will retain their value as central components in organizations’ decision support systems. This study explores the potentialities of Hadoop as a data transformation tool in the setting of a traditional data warehouse environment. Hadoop’s execution model, which is oriented for distributed parallel processing, offers great capabilities when the amounts of data to be processed require the infrastructure to expand. Horizontal scalability, which is a key aspect in a Hadoop cluster, will allow for proportional growth in processing power as the volume of data increases. Through the use of a Hive on Tez, in a Hadoop cluster, this study transforms television viewing events, extracted from Ericsson’s Mediaroom Internet Protocol Television infrastructure, into pertinent audience metrics, like Rating, Reach and Share. These measurements are then made available in a traditional data warehouse, supported by a traditional Relational Database Management System, where they are presented through a set of reports. The main contribution of this research is a proposed augmented data warehouse architecture where the traditional ETL layer is replaced by a Hadoop cluster, running Hive on Tez, with the purpose of performing the heaviest transformations that convert raw data into actionable information. Through a typification of the SQL statements, responsible for the data transformation processes, we were able to understand that Hadoop, and its distributed processing model, delivers outstanding performance results associated with the analytical layer, namely in the aggregation of large data sets. Ultimately, we demonstrate, empirically, the performance gains that can be extracted from Hadoop, in comparison to an RDBMS, regarding speed, storage usage and scalability potential, and suggest how this can be used to evolve data warehouses into the age of Big Data

    Film Viewing in the Interactive Age

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    Streaming films online has become a popular and unique way to view films. This study was designed to identify the uses and gratifications of using streaming film services, and identify any differences in quality of the streaming experience when compared to the original film. This study drew from past uses and gratifications research on film, television, VCRs, DVDs, and other film-related technologies to develop a survey determining the motivations of both streamers and non-streamers. Additionally a content analysis was used to determine the quality of film presentation when streaming a film online. The survey revealed that the main uses and gratifications for online film streaming could be broken down into five distinct categories. It also demonstrated that viewers are concerned about the quality of the film they are receiving, but it is not necessarily enough to cause them not to use a streaming service. The content analysis revealed that distinct differences exist between the quality of streaming films and the original film, including aspect ratio, color and sound quality, and picture clarit
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