177 research outputs found
Net Neutrality
This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. Chris Marsden maneuvers through the hype articulated by Netwrok Neutrality advocates and opponents. He offers a clear-headed analysis of the high stakes in this debate about the Internet's future, and fearlessly refutes the misinformation and misconceptions that about' Professor Rob Freiden, Penn State University Net Neutrality is a very heated and contested policy principle regarding access for content providers to the Internet end-user, and potential discrimination in that access where the end-user's ISP (or another ISP) blocks that access in part or whole. The suggestion has been that the problem can be resolved by either introducing greater competition, or closely policing conditions for vertically integrated service, such as VOIP. However, that is not the whole story, and ISPs as a whole have incentives to discriminate between content for matters such as network management of spam, to secure and maintain customer experience at current levels, and for economic benefit from new Quality of Service standards. This includes offering a ‘priority lane' on the network for premium content types such as video and voice service. The author considers market developments and policy responses in Europe and the United States, draws conclusions and proposes regulatory recommendations
Music and Digital Media
Anthropology has neglected the study of music. Music and Digital Media shows how and why this should be redressed. It does so by enabling music to expand the horizons of digital anthropology, demonstrating how the field can build interdisciplinary links to music and sound studies, digital/media studies, and science and technology studies.
Music and Digital Media is the first comparative ethnographic study of the impact of digital media on music worldwide. It offers a radical and lucid new theoretical framework for understanding digital media through music, showing that music is today where the promises and problems of the digital assume clamouring audibility. The book contains ten chapters, eight of which present comprehensive original ethnographies; they are bookended by an authoritative introduction and a comparative postlude. Five chapters address popular, folk, art and crossover musics in the global South and North, including Kenya, Argentina, India, Canada and the UK. Three chapters bring the digital experimentally to the fore, presenting pioneering ethnographies of anextra-legal peer-to-peer site and the streaming platform Spotify, a series of prominent internet-mediated music genres, and the first ethnography of a global software package, the interactive music platform Max.
The book is unique in bringing ethnographic research on popular, folk, art and crossover musics from the global North and South into a comparative framework on a large scale, and creates an innovative new paradigm for comparative anthropology. It shows how music enlarges anthropology while demanding to be understood with reference to classic themes of anthropological theory.
Praise for Music and Digital Media
‘Music and Digital Media is a groundbreaking update to our understandings of sound, media, digitization, and music. Truly transdisciplinary and transnational in scope, it innovates methodologically through new models for collaboration, multi-sited ethnography, and comparative work. It also offers an important defense of—and advancement of—theories of mediation.’ Jonathan Sterne, Communication Studies and Art History, McGill University
'Music and Digital Media is a nuanced exploration of the burgeoning digital music scene across both the global North and the global South. Ethnographically rich and theoretically sophisticated, this collection will become the new standard for this field.' Anna Tsing, Anthropology, University of California at Santa Cruz 'The global drama of music's digitisation elicits extreme responses – from catastrophe to piratical opportunism – but between them lie more nuanced perspectives. This timely, absolutely necessary collection applies anthropological understanding to a deliriously immersive field, bringing welcome clarity to complex processes whose impact is felt far beyond what we call music.' David Toop, London College of Communication, musician and writer
‘Spanning continents and academic disciplines, the rich ethnographies contained in Music and Digital Media makes it obligatory reading for anyone wishing to understand the complex, contradictory, and momentous effects that digitization is having on musical cultures.’ Eric Drott, Music, University of Texas, Austin
‘This superb collection, with an authoritative overview as its introduction, represents the state of the art in studies of the digitalisation of music. It is also a testament to what anthropology at its reflexive best can offer the rest of the social sciences and humanities.’ David Hesmondhalgh, Media and Communication, University of Leeds
‘This exciting volume forges new ground in the study of local conditions, institutions, and sounds of digital music in the Global South and North. The book’s planetary scope and its commitment to the “messiness” of ethnographic sites and concepts amplifies emergent configurations and meanings of music, the digital, and the aesthetic.’ Marina Peterson, Anthropology, University of Texas, Austi
Aproximační algoritmy pro submodulární optimalizaci a aplikace
This study proposes approximation algorithms by using several strategies such as streaming, improved-greedy, stop-and-stare, and reverse influence sampling ( \RIS ) to solve three variants of the submodular optimization problem, and perform experiments of these algorithms on the well-known application problems of submodular optimization such as Influence Threshold ( \IT ) and Influence Maximization ( \IM) . Specifically, in the first problem, we propose the two single-pass streaming algorithms ( \StrA and \StrM ) for minimizing the cost of the submodular cover problem under the multiplicative and additive noise models. \StrA and \StrM provide bicriteria approximation solutions. These algorithms effectively increase performance computing the objective function, reduce complexity, and apply to big data. For the second problem, we focus on maximizing a submodular function on fairness constraints. This problem is also known as the problem of fairness budget distribution for influence maximization. We design three algorithms ( \FBIM1 , \FBIM2 , and \FBIM3 ) by combining several strategies such as the threshold greedy algorithm, dynamic stop-and-stare technique, generating samplings by reverse influence sampling framework, and seeds selection to ensure max coverage. \FBIM1 , \FBIM2 , and \FBIM3 perform effectively on big data, provide -approximation to the optimum solutions, and require complexities of the comparison algorithms. Finally, we devise two effective streaming algorithm ( \StrI and \StrII ) to maximize the Diminishing Returns submodular (DR-submodular) function with a cardinality constraint on the integer lattice for the third problem. \StrI and \StrII provide -approximation ratio and -approximation ratio, respectively. Simultaneously, compared with the state-of-the-art, these two algorithms have reduced complexity, superior runtime performance, and negligible difference in objective function values. In each problem, we further investigate the performance of our proposed algorithms by conducting many experiments. The experimental results have indicated that our approximation algorithms provide high-efficiency solutions, outperform the-state-of-art algorithms in complexity, runtime, and satisfy the specified constraints. Some of the results have been confirmed through five publications at the Scopus international conferences (RIVF 2021, ICABDE 2021) and the SCIE journals (Computer Standards Interfaces (Elsevier) and Mathematics (MDPI)).Tato studie navrhuje aproximační algoritmy pomocí několika strategií, jako je streamování, vylepšená chamtivost, stop-and-stare a vzorkování zpětného vlivu ( \RIS ) k vyřešení tří variant submodulárního optimalizačního problému a provádění experimentů s těmito algoritmy na dobře známé aplikační problémy submodulární optimalizace, jako je práh vlivu ( \IT ) a maximalizace vlivu ( \IM) . Konkrétně v prvním problému navrhujeme dva jednoprůchodové streamovací algoritmy ( \StrA a \StrM ) pro minimalizaci nákladů na problém submodulárního pokrytí v rámci multiplikativních a aditivních šumových modelů. \StrA a \StrM poskytují řešení aproximace bikriterií. Tyto algoritmy efektivně zvyšují výkon při výpočtu cílové funkce, snižují složitost a aplikují se na velká data. U druhého problému se zaměřujeme na maximalizaci submodulární funkce na omezeních spravedlnosti. Tento problém je také známý jako problém spravedlivého rozdělení rozpočtu pro maximalizaci vlivu. Navrhujeme tři algoritmy ( \FBIM1 , \FBIM2 a \FBIM3 ) kombinací několika strategií, jako je prahový greedy algoritmus, dynamická technika stop-and-stare, generování vzorkování pomocí rámce vzorkování s obráceným vlivem a semena výběr pro zajištění maximálního pokrytí. \FBIM1 , \FBIM2 a \FBIM3 fungují efektivně na velkých datech, poskytují -přiblížení optimálním řešením a vyžadují složitost srovnávacích algoritmů. Nakonec jsme navrhli dva efektivní streamovací algoritmy ( \StrI a \StrII ), abychom maximalizovali submodulární (DR-submodulární) funkci klesající návraty s omezením mohutnosti na celočíselné mřížce pro třetí problém. \StrI a \StrII poskytují poměr přiblížení a poměr přiblížení . Současně mají tyto dva algoritmy ve srovnání s nejmodernějšími algoritmy sníženou složitost, vyšší výkon za běhu a zanedbatelný rozdíl v hodnotách objektivních funkcí. V každém problému dále zkoumáme výkon námi navrhovaných algoritmů prováděním mnoha experimentů. Experimentální výsledky ukázaly, že naše aproximační algoritmy poskytují vysoce účinná řešení, překonávají nejmodernější algoritmy ve složitosti, době běhu a splňují specifikovaná omezení. Některé z výsledků byly potvrzeny prostřednictvím pěti publikací na mezinárodních konferencích Scopus (RIVF 2021, ICABDE 2021) a v časopisech SCIE (Computer Standards Interfaces (Elsevier) a Mathematics (MDPI)).460 - Katedra informatikyvyhově
Music and Digital Media: A planetary anthropology
Anthropology has neglected the study of music. Music and Digital Media shows how and why this should be redressed. It does so by enabling music to expand the horizons of digital anthropology, demonstrating how the field can build interdisciplinary links to music and sound studies, digital/media studies, and science and technology studies.
Music and Digital Media is the first comparative ethnographic study of the impact of digital media on music worldwide. It offers a radical and lucid new theoretical framework for understanding digital media through music, showing that music is today where the promises and problems of the digital assume clamouring audibility. The book contains ten chapters, eight of which present comprehensive original ethnographies; they are bookended by an authoritative introduction and a comparative postlude. Five chapters address popular, folk, art and crossover musics in the global South and North, including Kenya, Argentina, India, Canada and the UK. Three chapters bring the digital experimentally to the fore, presenting pioneering ethnographies of an extra-legal peer-to-peer site and the streaming platform Spotify, a series of prominent internet-mediated music genres, and the first ethnography of a global software package, the interactive music platform Max.
The book is unique in bringing ethnographic research on popular, folk, art and crossover musics from the global North and South into a comparative framework on a large scale, and creates an innovative new paradigm for comparative anthropology. It shows how music enlarges anthropology while demanding to be understood with reference to classic themes of anthropological theory
Efektivní algoritmy pro problémy se sociálním vlivem u velkých sítí
In recent years, the dizzying explosion of data and information results from social networks with millions to billions of users, such as Facebook, YouTube, Twitter, and LinkedIn. Users can use online social networks (OSNs) to quickly trade information, communicate with other users, and keep their information up-to-date. The challenge of spreading information on social networks that arises in practice requires effective information management solutions, such as disseminating useful information, maximizing the influence of information transmission, and preventing disinformation, rumors, and viruses from being disseminated. Motivated by the above issues, we investigate the problem of information diffusion on OSNs. We study this problem based on two models, Independent Cascade (IC) and Linear Threshold (LT), and classical Influence Maximization (IM) in online social networks. In addition, we investigate various aspects of IM problems, such as budget variations, topics of interest, multiple competitors, and others. Moreover, we also investigate and apply the theory of combinatorial optimization problems to solve one of the current concerns in social networks, maximizing the influence on the groups and topics in social networks.
In general, the main goals of the Ph.D thesis proposal are as follows.
1. We investigate the Multi-Threshold problem for IM, which is a variant of the IM problem with threshold constraints. We propose an efficient algorithm that IM for multiple thresholds in the social network. In particular, we develop a novel algorithmic framework that can use the solution to a smaller threshold to find that of larger ones.
2. We study the Group Influence Maximization problem and introduce an efficient group influence maximization algorithm with more advantages than each node’s influence in networks, using a novel sampling technique to estimate the epsilon group function. We also devised an approximation algorithm to estimate multiple candidate solutions with theoretical guarantee.
3. We investigate an approach for Influence Maximization problem with k-topic under constraints in social network. More specifically, we also study a streaming algorithm that combines an optimization algorithm to improve the approximation algorithm and theoretical guarantee in terms of solution quality and running time.V posledních letech je závratná exploze dat a informací výsledkem sociálních sítí s miliony až miliardami uživatelů, jako jsou Facebook, YouTube, Twitter a LinkedIn. Uživatelé mohou využívat online sociální sítě (OSNs) k rychlému obchodování s informacemi, komunikaci s ostatními uživateli a udržování jejich informací v aktuálním stavu. Výzva šíření informací na sociálních sítích, která se v praxi objevuje, vyžaduje efektivní řešení správy informací, jako je šíření užitečných informací, maximalizace vlivu přenosu informací a zabránění šíření dezinformací, fám a virů. Motivováni výše uvedenými problémy zkoumáme problém šíření informací na OSN. Tento problém studujeme na základě dvou modelů, Independent Cascade (IC) a Linear Threshold (LT) a klasické Influence Maximization (IM) v online sociálních sítích. Kromě toho zkoumáme různé aspekty problémů s rychlým zasíláním zpráv, jako jsou změny rozpočtu, témata zájmu, více konkurentů a další. Kromě toho také zkoumáme a aplikujeme teorii kombinatorických optimalizačních problémů k vyřešení jednoho ze současných problémů v sociálních sítích, maximalizujeme vliv na skupiny a témata v sociálních sítích.
Obecně lze říci, že hlavní cíle Ph.D. návrh diplomové práce je následující.
1. Zkoumáme problém Multi-Threshold pro IM, což je varianta problému IM s prahovými omezeními. Navrhujeme účinný algoritmus, který IM pro více prahů v sociální síti. Zejména vyvíjíme nový algoritmický rámec, který může použít řešení pro menší práh k nalezení prahu většího.
2. Studujeme problém maximalizace vlivu skupiny a zavádíme účinný algoritmus maxima- lizace vlivu skupiny s více výhodami, než je vliv každého uzlu v sítích, pomocí nové vzorkovací techniky k odhadu funkce skupiny epsilon. Navrhujeme také aproximační algoritmus pro odhad více kandidátních řešení s teoretickou zárukou.
3. Zkoumáme přístup pro maximalizaci vlivu s k-téma pod omezeními v rozsáhlé síti. Konkrétněji budeme studovat novou metriku, která kombinuje optimalizační algoritmus pro zlepšení aproximačního algoritmu z hlediska kvality řešení a doby běhu na základě kliky a komunity v komplexních sítích.460 - Katedra informatikyvyhově
Axmedis 2005
The AXMEDIS conference aims to promote discussions and interactions among researchers, practitioners, developers and users of tools, technology transfer experts, and project managers, to bring together a variety of participants. The conference focuses on the challenges in the cross-media domain (which include production, protection, management, representation, formats, aggregation, workflow, distribution, business and transaction models), and the integration of content management systems and distribution chains, with particular emphasis on cost reduction and effective solutions for complex cross-domain problems
THE IDEOLOGICAL BACKGROUND OF BITCOIN: the unintended, but predicted, convenience of anonymity for criminal activities
Bitcoin, a primeira criptomoeda e a primeira aplicação conhecida do Blockchain, está relacionada de perto com o movimento contracultural chamado Cypherpunks. O ativismo dos Cypherpunks, como consta em seu manifesto, foi - e ainda é – dedicado ao desenvolvimento de ferramentas para proporcionar um ambiente onde a privacidade seja protegida. Para eles, privacidade não é sigilo; privacidade é o poder de se revelar seletivamente para o mundo. Bitcoin é um resultado direto dessa aspiração, já que Satoshi Nakamoto – enquanto desenvolvia a Bitcoin – empenhou seus esforços para criar um software que refletisse essa ambição e foi bem sucedido no desenvolvimento de um que, de uma só vez: (i) abrigou a privacidade através do pseudoanonimato, (ii) forneceu um registro público inalterável de todas as transações concluídas com Bitcoin e (iii) desafiou a política monetária estadocêntrica e o sistema bancário tradicional através de uma rede descentralizada de nós operacionais que funcionam como validadores das informações contidas no registro público. Neste artigo, por meio do estabelecimento de relações entre a ideologia Cypherpunk e Bitcoin, eu defendo que a conveniência do uso do Bitcoin em atividades criminosas é, originalmente, um efeito não intencional da ideologia que lastreou o desenvolvimento das criptomoedas mas, provavelmente, um risco colateral que o criador estava disposto a correr
Evaluating latent content within unstructured text: an analytical methodology based on a temporal network of associated topics
Abstract In this research various concepts from network theory and topic modelling are combined, to provision a temporal network of associated topics. This solution is presented as a step-by-step process to facilitate the evaluation of latent topics from unstructured text, as well as the domain area that textual documents are sourced from. In addition to ensuring shifts and changes in the structural properties of a given corpus are visible, non-stationary classes of cooccurring topics are determined, and trends in topic prevalence, positioning, and association patterns are evaluated over time. The aforementioned capabilities extend the insights fostered from stand-alone topic modelling outputs, by ensuring latent topics are not only identified and summarized, but more systematically interpreted, analysed, and explained, in a transparent and reliable way
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