1,444 research outputs found

    Rights on news : expanding copyright on the internet

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    Defence date: 18 February 2020Examining Board: Prof. Giovanni Sartor, EUI (Supervisor); Prof. Pier Luigi Parcu, EUI; Prof. Lionel Bently, University of Cambridge; Prof. Christophe Geiger, University of StrasbourgThe internet and digital technologies have irreversibly changed the way we find and consume news. Legacy news organisations, publishers of newspapers, have moved to the internet. In the online news environment, however, they are no longer the exclusive suppliers of news. New digital intermediaries have emerged, search engines and news aggregators in particular. They select and display links and fragments of press publishers’ content as a part of their services, without seeking the news organisations’ prior consent. To shield themselves from exploitation by digital intermediaries, press publishers have begun to seek legal protection, and called for the introduction of a new right under the umbrella of copyright and related rights. Following these calls, the press publishers’ right was introduced into the EU copyright framework by the Directive on Copyright in the Digital Single Market in 2019

    Analysis and Extraction of Tempo-Spatial Events in an Efficient Archival CDN with Emphasis on Telegram

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    This paper presents an efficient archival framework for exploring and tracking cyberspace large-scale data called Tempo-Spatial Content Delivery Network (TS-CDN). Social media data streams are renewing in time and spatial dimensions. Various types of websites and social networks (i.e., channels, groups, pages, etc.) are considered spatial in cyberspace. Accurate analysis entails encompassing the bulk of data. In TS-CDN by applying the hash function on big data an efficient content delivery network is created. Using hash function rebuffs data redundancy and leads to conclude unique data archive in large-scale. This framework based on entered query allows for apparent monitoring and exploring data in tempo-spatial dimension based on TF-IDF score. Also by conformance from i18n standard, the Unicode problem has been dissolved. For evaluation of TS-CDN framework, a dataset from Telegram news channels from March 23, 2020 (1399-01-01), to September 21, 2020 (1399-06-31) on topics including Coronavirus (COVID-19), vaccine, school reopening, flood, earthquake, justice shares, petroleum, and quarantine exploited. By applying hash on Telegram dataset in the mentioned time interval, a significant reduction in media files such as 39.8% for videos (from 79.5 GB to 47.8 GB), and 10% for images (from 4 GB to 3.6 GB) occurred. TS-CDN infrastructure in a web-based approach has been presented as a service-oriented system. Experiments conducted on enormous time series data, including different spatial dimensions (i.e., Khabare Fouri, Khabarhaye Fouri, Akhbare Rouze Iran, and Akhbare Rasmi Telegram news channels), demonstrate the efficiency and applicability of the implemented TS-CDN framework

    A War of Words: The Forms and Functions of Voice-Over in the American World War II Film — An Interdisciplinary Analysis

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    Aside from being American World War II films, what else do the following films have in common? The Big Red One; Hacksaw Ridge; Harts War; Mister Roberts; Stalag 17; and The Thin Red Line — all have voice-over in them. These, and hundreds of other war films have voice-overs that are sometimes the thoughts of a fearful soldier; the wry observations of a participant-observer; or the declarations of all-knowing authoritative figures. There are voice-overs blasted out through a ships PA system; as the reading of a heart-breaking letter; or as the words of a dead comrade, heard again in the mind of a haunted soldier. This thesis questions why is voice-over such a recurring phenomenon in these films? Why is it conveyed in so many different forms? What are the terms for those different forms? What are their narrative functions? A core component of this thesis is a new taxonomy of the six distinct forms of voice-over: acousmatic, audioemic, epistolary, objective, omniscient, and subjective. However, the project is more than a structuralist taxonomy that merely serves to identify, and define those forms. It is also a close examination of their narrative functions beyond the unimaginative trope that voice-over in war films is simply a convenient storytelling device. Through interdisciplinarity — combined with a realist framework — I probe the correlations between: the conditions, codification, and suppression of speech within the U.S. military, and the manifestations of that experience through the cinematic device, and genre convention of voice-over. In addition, I present a radically new interpretation of the voice-overs in The Thin Red Line (Terrence Malick, 1998) as being both a choric meta-memorial to James Jones; and a Greek tragedy — with its replication of the stagecraft of Aeschylus, in its use of the cosmic frame, and the inclusion of a collective character, which I have named ‘The Chorus of Unknown Soldiers’. The overall result is a more logical, and nuanced explanation of the forms, functions, and prevalent use of voice-over in the American World War II film

    Behavior quantification as the missing link between fields: Tools for digital psychiatry and their role in the future of neurobiology

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    The great behavioral heterogeneity observed between individuals with the same psychiatric disorder and even within one individual over time complicates both clinical practice and biomedical research. However, modern technologies are an exciting opportunity to improve behavioral characterization. Existing psychiatry methods that are qualitative or unscalable, such as patient surveys or clinical interviews, can now be collected at a greater capacity and analyzed to produce new quantitative measures. Furthermore, recent capabilities for continuous collection of passive sensor streams, such as phone GPS or smartwatch accelerometer, open avenues of novel questioning that were previously entirely unrealistic. Their temporally dense nature enables a cohesive study of real-time neural and behavioral signals. To develop comprehensive neurobiological models of psychiatric disease, it will be critical to first develop strong methods for behavioral quantification. There is huge potential in what can theoretically be captured by current technologies, but this in itself presents a large computational challenge -- one that will necessitate new data processing tools, new machine learning techniques, and ultimately a shift in how interdisciplinary work is conducted. In my thesis, I detail research projects that take different perspectives on digital psychiatry, subsequently tying ideas together with a concluding discussion on the future of the field. I also provide software infrastructure where relevant, with extensive documentation. Major contributions include scientific arguments and proof of concept results for daily free-form audio journals as an underappreciated psychiatry research datatype, as well as novel stability theorems and pilot empirical success for a proposed multi-area recurrent neural network architecture.Comment: PhD thesis cop

    Deep Learning based Densenet Convolution Neural Network for Community Detection in Online Social Networks

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    Online Social Networks (OSNs) have become increasingly popular, with hundreds of millions of users in recent years. A community in a social network is a virtual group with shared interests and activities that they want to communicate. OSN and the growing number of users have also increased the need for communities. Community structure is an important topological property of OSN and plays an essential role in various dynamic processes, including the diffusion of information within the network. All networks have a community format, and one of the most continually addressed research issues is the finding of communities. However, traditional techniques didn't do a better community of discovering user interests. As a result, these methods cannot detect active communities.  To tackle this issues, in this paper presents Densenet Convolution Neural Network (DnetCNN) approach for community detection. Initially, we gather dataset from Kaggle repository. Then preprocessing the dataset to remove inconsistent and missing values. In addition to User Behavior Impact Rate (UBIR) technique to identify the user URL access, key term and page access. After that, Web Crawling Prone Factor Rate (WCPFR) technique is used find the malicious activity random forest and decision method. Furthermore, Spider Web Cluster Community based Feature Selection (SWC2FS) algorithm is used to choose finest attributes in the dataset. Based on the attributes, to find the community group using Densenet Convolution Neural Network (DnetCNN) approach. Thus, the experimental result produce better performance than other methods

    Internet censorship in the European Union

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    Diese Arbeit befasst sich mit Internetzensur innnerhalb der EU, und hier insbesondere mit der technischen Umsetzung, das heißt mit den angewandten Sperrmethoden und Filterinfrastrukturen, in verschiedenen EU-LĂ€ndern. Neben einer Darstellung einiger Methoden und Infrastrukturen wird deren Nutzung zur Informationskontrolle und die Sperrung des Zugangs zu Websites und anderen im Internet verfĂŒgbaren Netzdiensten untersucht. Die Arbeit ist in drei Teile gegliedert. ZunĂ€chst werden FĂ€lle von Internetzensur in verschiedenen EU-LĂ€ndern untersucht, insbesondere in Griechenland, Zypern und Spanien. Anschließend wird eine neue Testmethodik zur Ermittlung der Zensur mittels einiger Anwendungen, welche in mobilen Stores erhĂ€ltlich sind, vorgestellt. DarĂŒber hinaus werden alle 27 EU-LĂ€nder anhand historischer Netzwerkmessungen, die von freiwilligen Nutzern von OONI aus der ganzen Welt gesammelt wurden, öffentlich zugĂ€nglichen Blocklisten der EU-Mitgliedstaaten und Berichten von Netzwerkregulierungsbehörden im jeweiligen Land analysiert.This is a thesis on Internet censorship in the European Union (EU), specifically regarding the technical implementation of blocking methodologies and filtering infrastructure in various EU countries. The analysis examines the use of this infrastructure for information controls and the blocking of access to websites and other network services available on the Internet. The thesis follows a three-part structure. Firstly, it examines the cases of Internet censorship in various EU countries, specifically Greece, Cyprus, and Spain. Subsequently, this paper presents a new testing methodology for determining censorship of mobile store applications. Additionally, it analyzes all 27 EU countries using historical network measurements collected by Open Observatory of Network Interference (OONI) volunteers from around the world, publicly available blocklists used by EU member states, and reports issued by network regulators in each country
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