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  • 1
    Language: English
    In: Neurocomputing, Nov 1, 2015, Vol.167, p.158(7)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.neucom.2015.04.083 Byline: Alexandros Iosifidis Abstract: This paper proposes a novel method for supervised subspace learning based on Single-hidden Layer Feedforward Neural networks. The proposed method calculates appropriate network target vectors by formulating a Bayesian model exploiting both the labeling information available for the training data and geometric properties of the training data, when represented in the feature space determined by the network's hidden layer outputs. After the calculation of the network target vectors, Extreme Learning Machine-based neural network training is applied and classification is performed using a Nearest Neighbor classifier. Experimental results on publicly available data sets show that the proposed approach consistently outperforms the standard ELM approach, as well as other standard methods. Author Affiliation: Department of Signal Processing, Tampere University of Technology, Finland Article History: Received 5 November 2014; Revised 23 February 2015; Accepted 29 April 2015 Article Note: (miscellaneous) Communicated by Ning Wang
    Keywords: Artificial Neural Networks – Analysis
    ISSN: 0925-2312
    Source: Cengage Learning, Inc.
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  • 2
    Language: English
    In: European Journal of Communication, March 2011, Vol.26(1), pp.3-17
    Description: This article argues that national policies for digital television (DTV) are largely determined by markets, political contexts and supra-national influences, notably European Union (EU) audiovisual policy, which puts pressure on member states to speed up digital switchover.This creates a tension between the push of the EU to harmonize the switchover process and set target dates and the struggle of some of the countries to comply with this policy. In terms of the strategies that could be employed to accelerate digital uptake, the article points to setting a prompt date for analogue switch-off, subsidizing the relevant equipment to receive DTV, offering triple play services, ensuring active management to complete conversion effectively and, above all, adopting free-to-view DTV. The wide reach free-to-air model, in which public broadcasters have a leading role, ensures that the universality principle is maintained in the digital age.
    Keywords: Public Service Broadcasting ; Digital Television ; Free-to-Air Model ; Switchover ; Universal Service ; Journalism & Communications
    ISSN: 0267-3231
    E-ISSN: 1460-3705
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  • 3
    Language: English
    In: Media, Culture & Society, July 2015, Vol.37(5), pp.720-736
    Description: Based on seven different sports broadcasting markets (Australia, Brazil, Italy, India, South Africa, United Kingdom and the United States), this article provides a comparative analysis of the regulation of television sports broadcasting. The article examines how contrasting perspectives on television and sport – economic and sociocultural – have been reflected in two main approaches to the regulation of sports broadcasting, namely competition law and major events legislation. The results of this analysis suggest that in many cases, the balance between commerce and culture in sports broadcasting has shifted too far in favour of the commercial interests of dominant pay-TV operators and sports organisations. Here, the case is made for the pursuit of an approach to sports broadcasting regulation that seeks to balance the commercial priorities of broadcasters and sports organisations with the wider sociocultural benefits citizens gain from free-to-air sports broadcasting.
    Keywords: Comparative Analysis ; Competition Law ; Major Events Legislation ; Sports Broadcasting ; Sports Rights ; Television Regulation ; Sociology & Social History ; Journalism & Communications
    ISSN: 0163-4437
    E-ISSN: 1460-3675
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  • 4
    Language: English
    In: European Journal of Communication, October 2016, Vol.31(5), pp.536-550
    Description: Using examples from a number of different European countries, this article analyses the increasingly prominent position of traditional telecommunications companies, such as British Telecom (UK), Deutsche Telekom (Germany), France Telecom/Orange (France) and Telefonica (Spain), in the contemporary sports media rights market. The first part of the article examines the commercial strategies of telecommunications operators and highlights how their acquisition of sports rights has been driven by the need to ensure a competitive position within an increasingly converged communications market. The second part of the article then moves on to consider the regulation of the sports media rights market. Most significantly, this section emphasises the need for further regulatory intervention to ensure that increased competition for sports rights leads to improved services and lower prices for consumers, rather than merely endlessly spiralling fees for the exclusive ownership of premium rights that are then passed on to sports channel and/or broadband subscribers.
    Keywords: Competition Regulation ; Essential Facilities Doctrine ; Pay-TV ; Sports Rights ; Telecommunications ; Journalism & Communications
    ISSN: 0267-3231
    E-ISSN: 1460-3705
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  • 5
    Language: English
    In: IEEE Communications Magazine, August 2011, Vol.49(8), pp.128-135
    Description: Dynamic spectrum markets of the future will involve complex spectrum transactions among operators and users. The nontrivial dynamics in channel quality and spatiotemporal spectrum availability call for new ways of spectrum allocation. In this article, we advocate that auction theory can play a decisive role in shaping this evolving landscape since auctions are agnostic to user utility functions, and can build versatile and lightweight allocation mechanisms. Starting from auction preliminaries, we discuss how various intrinsic features of spectrum markets can be addressed with a modified version of auctions.
    Keywords: Resource Management ; Cost Accounting ; Spread Spectrum Communication ; Wireless Networks ; Channel Allocation ; Dynamic Scheduling ; Marketing Management ; Engineering
    ISSN: 0163-6804
    E-ISSN: 1558-1896
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  • 6
    Language: English
    In: European Journal of Pediatrics, 2010, Vol.169(7), pp.867-874
    Description: Emergence of multidrug-resistant Gram-negative nosocomial pathogens has led to resurgence of colistin use. Safety and efficacy data regarding colistin use in pediatric patients are sparse, while optimal dosage has not been defined. We present a case series of neonates and children without cystic fibrosis treated with various doses of colistin intravenously. The records of patients who received colistin in a tertiary-care hospital from January 2007 to March 2009 were reviewed. Thirteen patients (median age 5 years, range 22 days to 14 years) received 19 courses of colistin as treatment of pneumonia, central nervous system infection, bacteremia, or complicated soft tissue infection. The isolated pathogens were Acinetobacter baumannii , Enterobacter cloacae , Klebsiella pneumoniae , Pseudomonas aeruginosa , and Stenotrophomonas maltophilia . Daily dose of colistin (colistimethate) ranged between 40,000 and 225,000 IU/kg. Duration of administration ranged from 1 to 133 days. Other antimicrobials were co-administered in 18/19 courses. Increase of serum creatinine in one patient was associated with co-administration of colistin and gentamicin. Sixteen of 19 courses had a favorable outcome, and only two of the three deaths were infection-related. Colistin intravenous administration appears well tolerated even at higher than previously recommended doses and of prolonged duration.
    Keywords: Colistin ; Colistimethate ; Multidrug resistant ; Gram-negative bacteria ; Nosocomial infections ; Intraventricular administration
    ISSN: 0340-6199
    E-ISSN: 1432-1076
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  • 7
    Language: English
    In: Neurocomputing, Dec 9, 2013, Vol.121, p.344(10)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.neucom.2013.05.021 Byline: Alexandros Iosifidis, Anastasios Tefas, Ioannis Pitas Abstract: In this paper, a method aiming at view-independent human action recognition is presented. Actions are described as series of successive human body poses. Action videos representation is based on fuzzy vector quantization, while action classification is performed by a novel classification algorithm, the so-called Sparsity-based Learning Machine (SbLM), involving two optimization steps. The first one determines a non-linear data mapping to a high-dimensional feature space determined by an l1-minimization process exploiting an overcomplete dictionary formed by the training samples. The second one, involves a training process in order to determine the optimal separating hyperplanes in the resulted high-dimensional feature space. The performance of the proposed human action recognition method is evaluated on two publicly available action recognition databases aiming at different application scenarios. Author Affiliation: Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece Article History: Received 15 October 2012; Revised 22 April 2013; Accepted 2 May 2013 Article Note: (miscellaneous) Communicated by Ran He
    Keywords: Algorithms
    ISSN: 0925-2312
    Source: Cengage Learning, Inc.
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  • 8
    Language: English
    In: Pattern Recognition Letters, Nov 1, 2013, Vol.34(15), p.1890(9)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.patrec.2012.10.019 Byline: Alexandros Iosifidis, Anastasios Tefas, Ioannis Pitas Keywords: Activity recognition; Dynamic classification; Fuzzy vector quantization; Extreme Learning Machine Abstract: a* Action recognition is performed by a novel dynamic classification scheme. a* Dynamic classification involves determination of the optimal training data and ANNs. a* Fast and efficient dynamic action classification is performed by employing the Extreme Learning Machine algorithm.
    Keywords: Algorithms
    ISSN: 0167-8655
    Source: Cengage Learning, Inc.
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  • 9
    Language: English
    In: Pattern Recognition Letters, 15 December 2015, Vol.68, pp.205-210
    Description: In this paper, we describe an approximate method for reducing the time and memory complexities of the kernel Extreme Learning Machine variants. We show that, by adopting a Nyström-based kernel ELM matrix approximation, we can define an ELM space exploiting properties of the kernel ELM space that can be subsequently used to apply several optimization schemes proposed in the literature for ELM network training. The resulted ELM network can achieve good performance, which is comparable to that of its standard kernel ELM counterpart, while overcoming the time and memory restrictions on kernel ELM algorithms that render their application in large-scale learning problems prohibitive.
    Keywords: Kernel Extreme Learning Machine ; Nyström Approximation ; Graph-Based Regularization ; Engineering ; Computer Science
    ISSN: 0167-8655
    E-ISSN: 1872-7344
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  • 10
    Language: English
    In: Neurocomputing, Dec 5, 2014, Vol.145, p.250(13)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.neucom.2014.05.036 Byline: Alexandros Iosifidis, Anastasios Tefas, Ioannis Pitas Abstract: In this paper, three novel classification algorithms aiming at (semi-)supervised action classification are proposed. Inspired by the effectiveness of discriminant subspace learning techniques and the fast and efficient Extreme Learning Machine (ELM) algorithm for Single-hidden Layer Feedforward Neural networks training, the ELM algorithm is extended by incorporating discrimination criteria in its optimization process, in order to enhance its classification performance. The proposed Discriminant ELM algorithm is extended, by incorporating proper regularization in its optimization process, in order to exploit information appearing in both labeled and unlabeled action instances. An iterative optimization scheme is proposed in order to address multi-view action classification. The proposed classification algorithms are evaluated on three publicly available action recognition databases providing state-of-the-art performance in all the cases. Author Affiliation: Department of Informatics, Aristotle University of Thessaloniki, Box 451, 54124 Thessaloniki, Greece Article History: Received 14 May 2013; Revised 19 December 2013; Accepted 12 May 2014 Article Note: (miscellaneous) Communicated by L. Shao
    Keywords: Artificial Neural Networks ; Algorithms
    ISSN: 0925-2312
    Source: Cengage Learning, Inc.
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