97,227 research outputs found

    Is Content Publishing in BitTorrent Altruistic or Profit-Driven

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    BitTorrent is the most popular P2P content delivery application where individual users share various type of content with tens of thousands of other users. The growing popularity of BitTorrent is primarily due to the availability of valuable content without any cost for the consumers. However, apart from required resources, publishing (sharing) valuable (and often copyrighted) content has serious legal implications for user who publish the material (or publishers). This raises a question that whether (at least major) content publishers behave in an altruistic fashion or have other incentives such as financial. In this study, we identify the content publishers of more than 55k torrents in 2 major BitTorrent portals and examine their behavior. We demonstrate that a small fraction of publishers are responsible for 66% of published content and 75% of the downloads. Our investigations reveal that these major publishers respond to two different profiles. On one hand, antipiracy agencies and malicious publishers publish a large amount of fake files to protect copyrighted content and spread malware respectively. On the other hand, content publishing in BitTorrent is largely driven by companies with financial incentive. Therefore, if these companies lose their interest or are unable to publish content, BitTorrent traffic/portals may disappear or at least their associated traffic will significantly reduce

    Image mining: trends and developments

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    [Abstract]: Advances in image acquisition and storage technology have led to tremendous growth in very large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining

    Do we really drive as we feel?

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    Learning to drive has been conceptualised as a series of stages which take the learner from mastery of the basic mechanics of driving, through anticipation of other road user's behaviour, to the development of a driving style consistent with the skill achieved in the first two stages (Parker & Stradling, 2002). Deery (1999) suggests that hazard perception is one of the main skills to be acquired in the second stage and that this skill is poorly developed in the inexperienced (and usually young) driver

    Safe Compositional Specification of Network Systems With Polymorphic, Constrained Types

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    In the framework of iBench research project, our previous work created a domain specific language TRAFFIC [6] that facilitates specification, programming, and maintenance of distributed applications over a network. It allows safety property to be formalized in terms of types and subtyping relations. Extending upon our previous work, we add Hindley-Milner style polymorphism [8] with constraints [9] to the type system of TRAFFIC. This allows a programmer to use for-all quantifier to describe types of network components, escalating power and expressiveness of types to a new level that was not possible before with propositional subtyping relations. Furthermore, we design our type system with a pluggable constraint system, so it can adapt to different application needs while maintaining soundness. In this paper, we show the soundness of the type system, which is not syntax-directed but is easier to do typing derivation. We show that there is an equivalent syntax-directed type system, which is what a type checker program would implement to verify the safety of a network flow. This is followed by discussion on several constraint systems: polymorphism with subtyping constraints, Linear Programming, and Constraint Handling Rules (CHR) [3]. Finally, we provide some examples to illustrate workings of these constraint systems.National Science Foundation (CCR-0205294

    Quantifying subjective quality evaluations for mobile video watching in a semi-living lab context

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    This paper discusses results from an exploratory study in which Quality of Experience aspects related to mobile video watching were investigated in a semi-living lab setting. More specifically, we zoom in on usage patterns in a natural research context and on the subjective evaluation of high and low-resolution movie trailers that are transferred to a mobile device using two transmission protocols for video (i.e., real-time transport protocol and progressive download using HTTP). User feedback was collected by means of short questionnaires on the mobile device, combined with traditional pen and paper diaries. The subjective evaluations regarding the general technical quality, perceived distortion, fluentness of the video, and loading speed are studied and the influence of the transmission protocol and video resolution on these evaluations is analyzed. Multinomial logistic regression results in a model to estimate the subjective evaluations regarding the perceived distortion and loading speed based on objectively-measured parameters of the video session

    Introduction to the special issue on cross-language algorithms and applications

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    With the increasingly global nature of our everyday interactions, the need for multilingual technologies to support efficient and efective information access and communication cannot be overemphasized. Computational modeling of language has been the focus of Natural Language Processing, a subdiscipline of Artificial Intelligence. One of the current challenges for this discipline is to design methodologies and algorithms that are cross-language in order to create multilingual technologies rapidly. The goal of this JAIR special issue on Cross-Language Algorithms and Applications (CLAA) is to present leading research in this area, with emphasis on developing unifying themes that could lead to the development of the science of multi- and cross-lingualism. In this introduction, we provide the reader with the motivation for this special issue and summarize the contributions of the papers that have been included. The selected papers cover a broad range of cross-lingual technologies including machine translation, domain and language adaptation for sentiment analysis, cross-language lexical resources, dependency parsing, information retrieval and knowledge representation. We anticipate that this special issue will serve as an invaluable resource for researchers interested in topics of cross-lingual natural language processing.Postprint (published version

    “Feeling my Sister’s Pain”: Perceived Victim Suffering Moderates the Impact of Sexualized Music Videos on Fijian Women’s Responses to Men’s Intimate Partner Violence against Women

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    To better understand how sexualized music videos affect women’s responses to intimate partner violence (IPV), we examined the role of individual variability in perceived victim pain and perceived victim culpability in moderating and mediating (respectively) the priming effects of sexual music videos on women. Female Fijian college students (n = 243) were randomly assigned to one of three viewing conditions: stereotyped sexual music videos, non-stereotyped/non-sexual music videos, or neutral videos. All participants then read a portrayal of a male-toward-female IPV episode and their perceptions of the female victim and male perpetrator were assessed. Only women who minimized the victim’s pain were adversely affected by exposure to the stereotyped sexual videos. Specifically, for women who perceived low victim pain, those in the stereotyped video condition perceived the victim as more culpable and reported greater perpetrator-directed favorable responding than those in the other two conditions. For these women who perceived low victim pain, perceptions of victim culpability mediated the impact of video type on perpetrator-favorable responding. The findings help us better understand susceptibility to the negative impact of stereotypical sexual videos and highlight areas, such as emphasizing the suffering of victims and reducing myths about victim culpability, which may be worthy of particular emphasis in interventions
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