Search results for "Communication science"

showing 10 items of 117 documents

Gewaltbilder in den Medien: Vertretbar oder verwerflich? Argumentation in der Wissenschaft, unter Journalisten und beim Deutschen Presserat

2015

Taglich erreichen Gewaltbilder aus der ganzen Welt die Redaktionen. Als Gatekeeper mussen Journalisten abwagen: Konnen, sollen, durfen oder mussen wir diese Bilder zeigen? Entscheiden sie sich fur die Publikation, wird ihnen schnell Sensationsgier unterstellt. Jedoch verlangt der journalistische Auftrag, auch in Bildern uber Gewalt, Leid und Tod zu berichten. Die Journalisten stehen vor einem bildethischen Dilemma. Der Beitrag nimmt sich dieser Problematik an und fragt, welche Argumente fur und gegen die Veroffentlichung von Gewaltbildern in den Massenmedien sprechen. Betrachtet wird dazu der bildethische Diskurs in der Kommunikationswissenschaft, unter Journalisten und beim Deutschen Press…

Psychiatry and Mental healthNeuropsychology and Physiological Psychologymedia_common.quotation_subjectSensationalismArt historyContext (language use)Communication sciencesArtHumanitiesmedia_commonCommunicatio Socialis
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Online Black-Markets: An Investigation of a Digital Infrastructure in the Dark

2021

AbstractThis paper investigates the functioning of Online Black-Markets (OBMs), i.e. a digital infrastructure operating in the Dark Net that enables the exchange of illegal goods such as drugs, weapons and fake digital identities. OBMs exist notwithstanding adverse conditions such as police interventions, scams and market breakdowns. Relying on a longitudinal case study, we focus on the dynamics of interactions among actors and marketplace technologies and we identify three mechanisms explaining OBMs operations. In particular, we show that OBMs infrastructure is the result of commoditization, platformization and resilience processes. Our contribution relies on the identification of communit…

ResilienceComputer Networks and CommunicationsAdverse conditionsDarknetDarknetSocial commerceMarketplaceSocial commerceArticleDigital infrastructureTheoretical Computer ScienceIdentification (information)VDP::Mathematics and natural science: 400::Information and communication science: 420BusinessCommoditizationResilience (network)SoftwareIndustrial organizationDigital infrastructure Darknet Marketplace Resilience Social commerceInformation Systems
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Broadband Internet Access via Multi-Hop Wireless Mesh Networks: Design, Protocol and Experiments

2010

Published version of an article from the journal: Wireless Personal Communications. The original publication is available at Spingerlink. http://dx.doi.org/10.1007/s11277-009-9907-9 While bandwidth for Internet access in urban areas is steadily increasing in recent years, many rural areas are still suffering from the effect of the digital divide. This paper presents a broadband Internet access paradigm developed in the context of the ADHOCSYS project, which was financed by the European Commission under the 6th Framework Program Information and Society Technologies, within the strategic objective of Broadband for All. Aiming at providing reliable Internet access in rural and mountainous regi…

Routing protocolbusiness.product_categoryBroadband networksComputer scienceMesh networkingHop (networking)law.inventionlawVDP::Technology: 500::Information and communication technology: 550::Telecommunication: 552BroadbandInternet accessWi-FiElectrical and Electronic EngineeringVDP::Mathematics and natural science: 400::Information and communication science: 420::Communication and distributed systems: 423Network architectureWireless mesh networkbusiness.industryWireless networkQuality of serviceWireless WANOrder One Network ProtocolComputer Science ApplicationsInternet Connection SharingDigital subscriber lineNetwork access pointHazy Sighted Link State Routing ProtocolRural areabusinessTelecommunicationsMunicipal wireless networkComputer network
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A Learning Automata Based Solution to Service Selection in Stochastic Environments

2010

Published version of a paper published in the book: Trends in Applied Intelligent Systems. Also available on SpringerLink: http://dx.doi.org/10.1007/978-3-642-13033-5_22 With the abundance of services available in today’s world, identifying those of high quality is becoming increasingly difficult. Reputation systems can offer generic recommendations by aggregating user provided opinions about service quality, however, are prone to ballot stuffing and badmouthing . In general, unfair ratings may degrade the trustworthiness of reputation systems, and changes in service quality over time render previous ratings unreliable. In this paper, we provide a novel solution to the above problems based …

Scheme (programming language)Computational complexity theoryComputer sciencemedia_common.quotation_subject0102 computer and information sciences02 engineering and technologyMachine learningcomputer.software_genreComputer security01 natural sciences0202 electrical engineering electronic engineering information engineeringQuality (business)Simplicitymedia_commoncomputer.programming_languageService qualityLearning automatabusiness.industryVDP::Technology: 500::Information and communication technology: 550VDP::Mathematics and natural science: 400::Information and communication science: 420::Knowledge based systems: 425010201 computation theory & mathematics020201 artificial intelligence & image processingStochastic optimizationArtificial intelligencebusinesscomputerReputation
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Discretized Bayesian Pursuit – A New Scheme for Reinforcement Learning

2012

Published version of a chapter in the book: Advanced Research in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-31087-4_79 The success of Learning Automata (LA)-based estimator algorithms over the classical, Linear Reward-Inaction ( L RI )-like schemes, can be explained by their ability to pursue the actions with the highest reward probability estimates. Without access to reward probability estimates, it makes sense for schemes like the L RI to first make large exploring steps, and then to gradually turn exploration into exploitation by making progressively smaller learning steps. However, this behavior becomes counter-intuitive wh…

Scheme (programming language)Mathematical optimizationDiscretizationLearning automataComputer sciencebusiness.industryVDP::Mathematics and natural science: 400::Information and communication science: 420::Algorithms and computability theory: 422estimator algorithmsBayesian probabilityBayesian reasoninglearning automataEstimatorVDP::Technology: 500::Information and communication technology: 550discretized learningBayesian inferenceAction (physics)Reinforcement learningArtificial intelligencepursuit schemesbusinesscomputercomputer.programming_language
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Solving Non-Stationary Bandit Problems by Random Sampling from Sibling Kalman Filters

2010

Published version of an article from Lecture Notes in Computer Science. Also available at SpringerLink: http://dx.doi.org/10.1007/978-3-642-13033-5_21 The multi-armed bandit problem is a classical optimization problem where an agent sequentially pulls one of multiple arms attached to a gambling machine, with each pull resulting in a random reward. The reward distributions are unknown, and thus, one must balance between exploiting existing knowledge about the arms, and obtaining new information. Dynamically changing (non-stationary) bandit problems are particularly challenging because each change of the reward distributions may progressively degrade the performance of any fixed strategy. Alt…

Scheme (programming language)Mathematical optimizationOptimization problemComputer scienceBayesian probabilityVDP::Technology: 500::Information and communication technology: 550Kalman filterBayesian inferenceMulti-armed banditVDP::Mathematics and natural science: 400::Information and communication science: 420::Knowledge based systems: 425computerThompson samplingOptimal decisioncomputer.programming_language
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A mutual GrabCut method to solve co-segmentation

2013

Publised version of an article from the journal:Eurasip Journal on Image and Video Processing. Also available on SpringerLink:http://dx.doi.org/10.1186/1687-5281-2013-20. Open Access Co-segmentation aims at segmenting common objects from a group of images. Markov random field (MRF) has been widely used to solve co-segmentation, which introduces a global constraint to make the foreground similar to each other. However, it is difficult to minimize the new model. In this paper, we propose a new Markov random field-based co-segmentation model to solve co-segmentation problem without minimization problem. In our model, foreground similarity constraint is added into the unary term of MRF model ra…

Similarity (geometry)Markov random fieldComputer sciencebusiness.industryVDP::Mathematics and natural science: 400::Information and communication science: 420::Algorithms and computability theory: 422ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONVDP::Technology: 500::Information and communication technology: 550Pattern recognitionFunction (mathematics)Term (time)Constraint (information theory)GrabCutComputer Science::Computer Vision and Pattern RecognitionCutSignal ProcessingSegmentationArtificial intelligenceElectrical and Electronic EngineeringbusinessInformation SystemsEURASIP Journal on Image and Video Processing
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The Impact of Shadowing and the Severity of Fading on the First and Second Order Statistics of the Capacity of OSTBC MIMO Nakagami-Lognormal Channels

2011

Published version of an article in Wireless Personal Communications (2011), 1-16. Also available from the publisher at http://dx.doi.org/10.1007/s11277-011-0275-x This article presents a thorough statistical analysis of the capacity of orthogonal space-time block coded (OSTBC) multiple-input multiple-output (MIMO) Nakagami- lognormal (NLN) channels. The NLN channel model allows to study the joint effects of fast fading and shadowing on the statistical properties of the channel capacity. We have derived exact analytical expressions for the probability density function (PDF), cumulative distribution function (CDF), level-crossing rate (LCR), and average duration of fades (ADF) of the capacity…

Spatial correlationComputer scienceCumulative distribution functionMIMONakagami distributionComputer Science ApplicationsAverage duration of fades channel capacity land mobile terrestrial channels level-crossing rate Nakagami-lognormal channels shadowing effectsChannel capacityVDP::Mathematics and natural science: 400::Information and communication science: 420StatisticsFadingElectrical and Electronic EngineeringComputer Science::Information TheoryCommunication channelWireless Personal Communications
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Ultimate Order Statistics-Based Prototype Reduction Schemes

2013

Published version of a chapter in the book: AI 2013: Advances in Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-319-03680-9_42 The objective of Prototype Reduction Schemes (PRSs) and Border Identification (BI) algorithms is to reduce the number of training vectors, while simultaneously attempting to guarantee that the classifier built on the reduced design set performs as well, or nearly as well, as the classifier built on the original design set. In this paper, we shall push the limit on the field of PRSs to see if we can obtain a classification accuracy comparable to the optimal, by condensing the information in the data set into a single tr…

Training setComputer scienceVDP::Mathematics and natural science: 400::Information and communication science: 420::Algorithms and computability theory: 422Order statisticcomputer.software_genreSupport vector machineData setBayes' theoremclassification using Order Statistics (OS)CMOSPrototype Reduction SchemesData miningmoments of OSClassifier (UML)computerParametric statistics
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On achieving near-optimal “Anti-Bayesian” Order Statistics-Based classification fora asymmetric exponential distributions

2013

Published version of a Chapter in the book: Computer Analysis of Images and Patterns. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-40261-6_44 This paper considers the use of Order Statistics (OS) in the theory of Pattern Recognition (PR). The pioneering work on using OS for classification was presented in [1] for the Uniform distribution, where it was shown that optimal PR can be achieved in a counter-intuitive manner, diametrically opposed to the Bayesian paradigm, i.e., by comparing the testing sample to a few samples distant from the mean - which is distinct from the optimal Bayesian paradigm. In [2], we showed that the results could be extended for a few sym…

Uniform distribution (continuous)Cumulative distribution functionBayesian probabilityOrder statistic02 engineering and technology01 natural sciencesVDP::Mathematics and natural science: 400::Mathematics: 410::Analysis: 411Combinatorics010104 statistics & probabilityBayes' theoremExponential familyclassification using Order Statistics (OS)VDP::Mathematics and natural science: 400::Information and communication science: 420::Knowledge based systems: 4250202 electrical engineering electronic engineering information engineeringApplied mathematics020201 artificial intelligence & image processing0101 mathematicsNatural exponential familymoments of OSBeta distributionMathematics
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