What do we know from the literature on public e-services?.

Public e-services are a broad and growing research field in which scholars and practitioners from different domains are involved. However, the increasing attention devoted to public e-services only partially captures the extreme variety of aspects and implications of the diffusion of information and communication technologies at all levels of public administrations. The paper aims to develop a meta-analysis of the literature on the delivery, diffusion, adoption and impact of public e-services and examines current research trends in terms of differences in methodologies, approaches and key indicators across five service platforms: eGovernment, eEducation, eHealth, Infomobility and eProcurement. We examined 751 articles appeared in 2000-2010 in the top international academic journals listed in the Social Science Citation Index (SSCI) of the Institute for Scientific Information (ISI), as classified in the following fields: Communication, Economics, Education, Environmental Studies, Geography, Health Policy & Services, Information Science & Library Science, Law, Management, Planning & Development, Public Administration, Transportation and Urban Studies. We highlight a significant heterogeneity in scientific production across service domains, countries covered by empirical analyses, indicators used, and affiliation of authors. We also show an increasing diffusion of quantitative methods applied to different research fields which still appears to be constrained by data limitations. The overall picture emerging from the analysis is one characterized by largely unexplored service domains as well as scarcely analyzed issues both across and within individual service platforms (e.g. front vs. back office issues). Thus many research opportunities seem to emerge and need to be exploited from different disciplinary perspectives in this field of analysis.eGovernment, eEducation, eHealth, Infomobility, eProcurement, Bibliometrics, Metaanalysis, Innovation in services, Public e-services

Optical tomography: Image improvement using mixed projection of parallel and fan beam modes

Mixed parallel and fan beam projection is a technique used to increase the quality images. This research focuses on enhancing the image quality in optical tomography. Image quality can be defined by measuring the Peak Signal to Noise Ratio (PSNR) and Normalized Mean Square Error (NMSE) parameters. The findings of this research prove that by combining parallel and fan beam projection, the image quality can be increased by more than 10%in terms of its PSNR value and more than 100% in terms of its NMSE value compared to a single parallel beam

A review of the characteristics of 108 author-level bibliometric indicators

An increasing demand for bibliometric assessment of individuals has led to a growth of new bibliometric indicators as well as new variants or combinations of established ones. The aim of this review is to contribute with objective facts about the usefulness of bibliometric indicators of the effects of publication activity at the individual level. This paper reviews 108 indicators that can potentially be used to measure performance on the individual author level, and examines the complexity of their calculations in relation to what they are supposed to reflect and ease of end-user application.Comment: to be published in Scientometrics, 201

Folks in Folksonomies: Social Link Prediction from Shared Metadata

Web 2.0 applications have attracted a considerable amount of attention because their open-ended nature allows users to create light-weight semantic scaffolding to organize and share content. To date, the interplay of the social and semantic components of social media has been only partially explored. Here we focus on Flickr and Last.fm, two social media systems in which we can relate the tagging activity of the users with an explicit representation of their social network. We show that a substantial level of local lexical and topical alignment is observable among users who lie close to each other in the social network. We introduce a null model that preserves user activity while removing local correlations, allowing us to disentangle the actual local alignment between users from statistical effects due to the assortative mixing of user activity and centrality in the social network. This analysis suggests that users with similar topical interests are more likely to be friends, and therefore semantic similarity measures among users based solely on their annotation metadata should be predictive of social links. We test this hypothesis on the Last.fm data set, confirming that the social network constructed from semantic similarity captures actual friendship more accurately than Last.fm's suggestions based on listening patterns.Comment: http://portal.acm.org/citation.cfm?doid=1718487.171852

JuxtaLearn D3.2 Performance Framework

This deliverable, D3.2, for Work Package 3 incorporating the pedagogy from WP2 and orchestration factors mapped in D3.1 reviews aspects of performance in the context of participative video making. It reviews literature on curiosity and engagement characteristics of interaction mechanisms for public displays and anticipates requirements for social network analysis of relevant public videos from WP6 task 6.3. Thus, to support JuxtaLearn performance it proposes a reflective performance framework that encompasses the material environment and objects required, the participants, and the knowledge needed