997 resultados para Big Sowing Pool


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Gel dosimetry and plastic chemical dosimeters such as PresageTM are capable of very accurately mapping dose distributions in three dimensions. Combined with their near tissue equivalence one would expect that after several decades of development they would be the dosimeter of choice for dosimetry, however they have not achieve widespread clinical use. This presentation will include a brief description and history of developments in gels and 3D plastics for dosimetry, the limitations and advantages, and their role in the future.

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Big data is certainly the buzz term in executive networking circles at the moment. Heralded by management consultancies and research organisations alike as the next big thing in business efficiency, it is shooting up the Gartner hype cycle to the giddy heights of the peak of inflated expectations before it tumbles down in to the trough of disillusionment

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One cannot help but be impressed by the inroads that digital oilfield technologies have made into the exploration and production (E&P) industry in the past decade. Today’s production systems can be monitored by “smart” sensors that allow engineers to observe almost any aspect of performance in real time. Our understanding of how reservoirs are behaving has improved considerably since the dawn of this revolution, and the industry has been able to move away from point answers to more holistic “big picture” integrated solutions. Indeed, the industry has already reaped the rewards of many of these kinds of investments. Many billions of dollars of value have been delivered by this heightened awareness of what is going on within our assets and the world around them (Van Den Berg et al. 2010).

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Metaphors are a common instrument of human cognition, activated when seeking to make sense of novel and abstract phenomena. In this article we assess some of the values and assumptions encoded in the framing of the term big data, drawing on the framework of conceptual metaphor. We first discuss the terms data and big data and the meanings historically attached to them by different usage communities and then proceed with a discourse analysis of Internet news items about big data. We conclude by characterizing two recurrent framings of the concept: as a natural force to be controlled and as a resource to be consumed.

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The basic principles and equations are developed for elementary finance, based on the concept of compound interest. The five quantities of interest in such problems are present value, future value, amount of periodic payment, number of periods and the rate of interest per period. We consider three distinct means of computing each of these five quantities in Excel 2007: (i) use of algebraic equations, (ii) by recursive schedule and the Goal Seek facility, and (iii) use of Excel's intrinsic financial functions. The paper is intended to be used as the basis for a lesson plan and contains many examples and solved problems. Comment is made regarding the relative difficulty of each approach, and a prominent theme is the systematic use of more than one method to increase student understanding and build confidence in the answer obtained. Full instructions to build each type of model are given and a complete set of examples and solutions may be downloaded (Examples.xlsx and Solutions.xlsx).

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Notwithstanding the problems with identifying audiences (c.f. Hartley, 1987), nor with sampling them (c.f. Turner, 2005), we contend that by using social media, it is at least possible to gain an understanding of the habits of those who chose to engage with content through social media. In this chapter, we will broadly outline the ways in which networks such as Twitter and Facebook can stand as proxies for audiences in a number of scenarios, and enable content creators, networks and researchers to understand the ways in which audiences come into existence, change over time, and engage with content. Beginning with the classic audience – television – we will consider the evolution of metrics from baseline volume metrics to the more sophisticated ‘telemetrics’ that are the focus of our current work. We discuss the evolution of these metrics, from principles developed in the field of ‘sabermetrics’, and highlight their effectiveness as both a predictor and a baseline for producers and networks to measure the success of their social media campaigns. Moving beyond the evaluation of the audiences engagement, we then move to consider the ‘audiences’ themselves. Building on Hartley’s argument that audiences are “imagined” constructs (1987, p. 125), we demonstrate the continual shift of Australian television audiences, from episode to episode and series to series, demonstrating through our map of the Australian Twittersphere (Bruns, Burgess & Highfield, 2014) both the variation amongst those who directly engage with television content, and those who are exposed to it through their social media networks. Finally, by exploring overlaps between sporting events (such as the NRL and AFL Grand Finals), reality TV (such as Big Brother, My Kitchen Rules & Biggest Loser), soaps (e.g. Bold & The Beautiful, Home & Away), and current affairs programming (e.g. Morning Television & A Current Affair), we discuss to what extent it is possible to profile and categorize Australian television audiences. Finally, we move beyond television audiences to consider audiences around social media platforms themselves. Building on our map of the Australian Twittersphere (Bruns, Burgess & Highfield, 2014), and a pool of 5000 active Australian accounts, we discuss the interconnectedness of audiences around particular subjects, and how specific topics spread throughout the Twitter Userbase. Also, by using Twitter as a proxy, we consider the career of a number of popular YouTuber’s, utilizing a method we refer to as Twitter Accession charts (Bruns & Woodford, 2014) to identify the growth curves, and relate them to specific events in the YouTubers career, be that ‘viral’ videos or collaborations, to discuss how audiences form around specific content creators.

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What does the future look like for music festivals in Australia? This article examines the decline of the large festivals that have grown to dominate the scene in Australia in the last twenty years, and the rise of small, specialized festivals that offer a boutique experience.

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In recent years, increasing focus has been made on making good business decisions utilizing the product of data analysis. With the advent of the Big Data phenomenon, this is even more apparent than ever before. But the question is how can organizations trust decisions made on the basis of results obtained from analysis of untrusted data? Assurances and trust that data and datasets that inform these decisions have not been tainted by outside agency. This study will propose enabling the authentication of datasets specifically by the extension of the RESTful architectural scheme to include authentication parameters while operating within a larger holistic security framework architecture or model compliant to legislation.

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Twitter ist eine besonders nützliche Quelle für Social-Media-Daten: mit dem Twitter-API (dem Application Programming Interface, das einen strukturierten Zugang zu Kommunikationsdaten in standardisierten Formaten bietet) ist es Forschern möglich, mit ein wenig Mühe und ausreichenden technische Ressourcen sehr große Archive öffentlich verbreiteter Tweets zu bestimmten Themen, Interessenbereichen, oder Veranstaltungen aufzubauen. Grundsätzlich liefert das API sehr langen Listen von Hunderten, Tausenden oder Millionen von Tweets und den Metadaten zu diesen Tweets; diese Daten können dann auf verschiedentlichste Weise extrahiert, kombiniert, und visualisiert werden, um die Dynamik der Social-Media-Kommunikation zu verstehen. Diese Forschung ist häufig um althergebrachte Fragestellungen herum aufgebaut, wird aber in der Regel in einem bislang unbekannt großen Maßstab durchgeführt. Die Projekte von Medien- und Kommunikationswissenschaftlern wie Papacharissi und de Fatima Oliveira (2012), Wood und Baughman (2012) oder Lotan et al. (2011) – um nur eine Handvoll der letzten Beispiele zu nennen – sind grundlegend auf Twitterdatensätze aufgebaut, die jetzt routinemäßig Millionen von Tweets und zugehörigen Metadaten umfassen, erfaßt nach einer Vielzahl von Kriterien. Was allen diesen Fällen gemein ist, ist jedoch die Notwendigkeit, neue methodische Wege in der Verarbeitung und Analyse derart großer Datensätze zur medienvermittelten sozialen Interaktion zu gehen.

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Reality television, alongside shows such as Q&A – which may be Reality TV in all but name – frequently drives social media conversations about the Australian television industry. Big Brother, currently screening on Channel 9, is consistently among the shows with the highest levels of chatter in that regard. The precise Facebook data is hard to quantify but the Official Big Brother page boasts 805,400 likes and more than 59,000 comments since the start of the series, suggesting it has established a firm presence on that platform too...

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Can I write across media? Yes and no. No, I can’t begin writing a sentence with a pen on paper and then use that pen to write on a screen. I have to change my tools. But, I can use those different tools to write a story that begins in paper and ends on the screen. At it most fundamental level, this is transmedia. Transmedia is not synonymous with digital media as it often involves both digital and nondigital media. A transmedia writer is also not synonymous with writers who write both screenplays and novels. Instead, transmedia often involves the continuation of a story across media.

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Health Information Exchange (HIE) is an interesting phenomenon. It is a patient centric health and/or medical information management scenario enhanced by integration of Information and Communication Technologies (ICT). While health information systems are repositioning complex system directives, in the wake of the ‘big data’ paradigm, extracting quality information is challenging. It is anticipated that in this talk, ICT enabled healthcare scenarios with big data analytics will be shared. In addition, research and development regarding big data analytics, such as current trends of using these technologies for health care services and critical research challenges when extracting quality of information to improve quality of life will be discussed.

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YouTube is contemplating the launch of a new music service. But how would such a service fare against established music services like Spotify, Rdio, and Pandora? All these services are referred to as “access-based music services”. They offer music listeners access to millions of songs they can listen to as much as they want for free (with advertising and only basic functionality) or for a monthly subscription fee (without advertising)...