A visibilidade das universidades portuguesas na web : estudo webométrico

Esta dissertação resulta de uma investigação que levou a cabo um estudo webométrico sobre a presença das universidades portuguesas na Web, avaliando a visibilidade das instituições através do cálculo de um indicador webométrico, o Web Impact Factor. A World Wide Web é, na atualidade, um dos principais meios de difusão de Informação. Os Estudos Métricos da Informação visam quantificar e avaliar a produção de Informação, objeto de estudo de disciplinas como a Infometria, a Cienciometria e a Bibliometria. Recentemente, surgiram a Cibermetria e a Webometria como novas disciplinas que estudam a produção e difusão da Informação no contexto do Ciberespaço e da World Wide Web, respetivamente. As universidades, enquanto polos privilegiados de produção e difusão de conhecimento, são o objeto de estudo natural da Webometria e a avaliação da sua presença na World Wide Web contribui para a análise do desempenho destas instituições. Para a realização deste trabalho foi adotada a metodologia proposta por Noruzi, que calcula três categorias de Web Impact Factor: o WIF Total, o WIF Revisto e o Selflink WIF. De modo a calcular estas categorias, foram recolhidos dados quantitativos de inlinks, selflinks, número total de páginas e número de páginas indexadas pelo motor de pesquisa. O motor de pesquisa utilizado foi o Altavista, tendo sido realizadas pesquisas de expressões booleanas durante o primeiro semestre de 2009. Após a recolha, os dados foram tratados estatisticamente e procedeu-se ao cálculo das categorias do WIF. Conclui-se que existe uma maior visibilidade das universidades públicas portuguesas porque obtêm melhores resultados ao nível de duas categorias do Web Impact Factor: o WIF Revisto e o Selflink WIF.

Networks of contextualised ontologies for the Semantic Web

Currently many ontologies are available for addressing different domains. However, it is not always possible to deploy such ontologies to support collaborative working, so that their full potential can be exploited to implement intelligent cooperative applications capable of reasoning over a network of context-specific ontologies. The main problem arises from the fact that presently ontologies are created in an isolated way to address specific needs. However we foresee the need for a network of ontologies which will support the next generation of intelligent applications/devices, and, the vision of Ambient Intelligence. The main objective of this paper is to motivate the design of a networked ontology (Meta) model which formalises ways of connecting available ontologies so that they are easy to search, to characterise and to maintain. The aim is to make explicit the virtual and implicit network of ontologies serving the Semantic Web.

GODIVA2: interactive visualization of environmental data on the Web

GODIVA2 is a dynamic website that provides visual access to several terabytes of physically distributed, four-dimensional environmental data. It allows users to explore large datasets interactively without the need to install new software or download and understand complex data. Through the use of open international standards, GODIVA2 maintains a high level of interoperability with third-party systems, allowing diverse datasets to be mutually compared. Scientists can use the system to search for features in large datasets and to diagnose the output from numerical simulations and data processing algorithms. Data providers around Europe have adopted GODIVA2 as an INSPIRE-compliant dynamic quick-view system for providing visual access to their data.

Effects of carbon dioxide on the searching behaviour of the root-feeding clover weevil Sitona lepidus (Coleoptera : Curculionidae)

The respiratory emission of CO2 from roots is frequently proposed as an attractant that allows soil-dwelling insects to locate host plant roots, but this role has recently become less certain. CO2 is emitted from many sources other than roots, so does not necessarily indicate the presence of host plants, and because of the high density of roots in the upper soil layers, spatial gradients may not always be perceptible by soil-dwelling insects. The role of CO2 in host location was investigated using the clover root weevil Sitona lepidus Gyllenhall and its host plant white clover (Trifolium repens L.) as a model system. Rhizochamber experiments showed that CO2 concentrations were approximately 1000 ppm around the roots of white clover, but significantly decreased with increasing distance from roots. In behavioural experiments, no evidence was found for any attraction by S. lepidus larvae to point emissions of CO2, regardless of emission rates. Fewer than 15% of larvae were attracted to point emissions of CO2, compared with a control response of 17%. However, fractal analysis of movement paths in constant CO2 concentrations demonstrated that searching by S. lepidus larvae significantly intensified when they experienced CO2 concentrations similar to those found around the roots of white clover (i.e. 1000 ppm). It is suggested that respiratory emissions of CO2 may act as a 'search trigger' for S. lepidus, whereby it induces larvae to search a smaller area more intensively, in order to detect location cues that are more specific to their host plant.

xhRank: ranking entities on the Semantic Web

In general, ranking entities (resources) on the Semantic Web (SW) is subject to importance, relevance, and query length. Few existing SW search systems cover all of these aspects. Moreover, many existing efforts simply reuse the technologies from conventional Information Retrieval (IR), which are not designed for SW data. This paper proposes a ranking mechanism, which includes all three categories of rankings and are tailored to SW data.

The effect of learning condition on perceptual anticipation, awareness, and visual search

The efficacy of explicit and implicit learning paradigms was examined during the very early stages of learning the perceptual-motor anticipation task of predicting ball direction from temporally occluded footage of soccer penalty kicks. In addition, the effect of instructional condition on point-of-gaze during learning was examined. A significant improvement in horizontal prediction accuracy was observed in the explicit learning group; however, similar improvement was evident in a placebo group who watched footage of soccer matches. Only the explicit learning intervention resulted in changes in eye movement behaviour and increased awareness of relevant postural cues. Results are discussed in terms of methodological and practical issues regarding the employment of implicit perceptual training interventions. (c) 2005 Elsevier B.V. All rights reserved.

Analysing Google rankings through search engine optimization data

Purpose - The purpose of this paper is to identify the most popular techniques used to rank a web page highly in Google. Design/methodology/approach - The paper presents the results of a study into 50 highly optimized web pages that were created as part of a Search Engine Optimization competition. The study focuses on the most popular techniques that were used to rank highest in this competition, and includes an analysis on the use of PageRank, number of pages, number of in-links, domain age and the use of third party sites such as directories and social bookmarking sites. A separate study was made into 50 non-optimized web pages for comparison. Findings - The paper provides insight into the techniques that successful Search Engine Optimizers use to ensure a page ranks highly in Google. Recognizes the importance of PageRank and links as well as directories and social bookmarking sites. Research limitations/implications - Only the top 50 web sites for a specific query were analyzed. Analysing more web sites and comparing with similar studies in different competition would provide more concrete results. Practical implications - The paper offers a revealing insight into the techniques used by industry experts to rank highly in Google, and the success or other-wise of those techniques. Originality/value - This paper fulfils an identified need for web sites and e-commerce sites keen to attract a wider web audience.

The effects of web logs and the semantic web on autonomous web agents

Search engines exploit the Web's hyperlink structure to help infer information content. The new phenomenon of personal Web logs, or 'blogs', encourage more extensive annotation of Web content. If their resulting link structures bias the Web crawling applications that search engines depend upon, there are implications for another form of annotation rapidly on the rise, the Semantic Web. We conducted a Web crawl of 160 000 pages in which the link structure of the Web is compared with that of several thousand blogs. Results show that the two link structures are significantly different. We analyse the differences and infer the likely effect upon the performance of existing and future Web agents. The Semantic Web offers new opportunities to navigate the Web, but Web agents should be designed to take advantage of the emerging link structures, or their effectiveness will diminish.

The influence of system designer intention over collaborative tagging. an analysis of tagging behaviour in CiteULike and Delicious

Tagging provides support for retrieval and categorization of online content depending on users' tag choice. A number of models of tagging behaviour have been proposed to identify factors that are considered to affect taggers, such as users' tagging history. In this paper, we use Semiotics Analysis and Activity theory, to study the effect the system designer has over tagging behaviour. The framework we use shows the components that comprise the tagging system and how they interact together to direct tagging behaviour. We analysed two collaborative tagging systems: CiteULike and Delicious by studying their components by applying our framework. Using datasets from both systems, we found that 35% of CiteULike users did not provide tags compared to only 0.1% of Delicious users. This was directly linked to the type of tools used by the system designer to support tagging.

Design and baseline characteristics of the Food4Me study: a web-based randomised controlled trial of personalised nutrition in seven European countries

Improving lifestyle behaviours has considerable potential for reducing the global burden of non-communicable diseases, promoting better health across the life-course and increasing well-being. However, realising this potential will require the development, testing and implementation of much more effective behaviour change interventions than are used conventionally. Therefore, the aim of this study was to conduct a multi-centre, web-based, proof-of-principle study of personalised nutrition (PN) to determine whether providing more personalised dietary advice leads to greater improvements in eating patterns and health outcomes compared to conventional population-based advice. A total of 5,562 volunteers were screened across seven European countries; the first 1,607 participants who fulfilled the inclusion criteria were recruited into the trial. Participants were randomly assigned to one of the following intervention groups for a 6-month period: Level 0-control group-receiving conventional, non-PN advice; Level 1-receiving PN advice based on dietary intake data alone; Level 2-receiving PN advice based on dietary intake and phenotypic data; and Level 3-receiving PN advice based on dietary intake, phenotypic and genotypic data. A total of 1,607 participants had a mean age of 39.8 years (ranging from 18 to 79 years). Of these participants, 60.9 % were women and 96.7 % were from white-European background. The mean BMI for all randomised participants was 25.5 kg m(-2), and 44.8 % of the participants had a BMI ≥ 25.0 kg m(-2). Food4Me is the first large multi-centre RCT of web-based PN. The main outcomes from the Food4Me study will be submitted for publication during 2015.

Enhanced effects of combined cognitive bias modification and computerised cognitive behaviour therapy on social anxiety

This study examines whether combined cognitive bias modification for interpretative biases (CBM-I) and computerised cognitive behaviour therapy (C-CBT) can produce enhanced positive effects on interpretation biases and social anxiety. Forty socially anxious students were randomly assigned into two conditions, an intervention group (positive CBM-I + C-CBT) or an active control (neutral CBM-I + C-CBT). At pre-test, participants completed measures of social anxiety, interpretative bias, cognitive distortions, and social and work adjustment. They were exposed to 6 × 30 min sessions of web-based interventions including three sessions of either positive or neutral CBM-I and three sessions of C-CBT, one session per day. At post-test and two-week follow-up, participants completed the baseline measures. A combined positive CBM-I + C-CBT produced less negative interpretations of ambiguous situations than neutral CBM-I + C-CBT. The results also showed that both positive CBM-I + C-CBT and neutral CBM-I + C-CBT reduced social anxiety and cognitive distortions as well as improving work and social adjustment. However, greater effect sizes were observed in the positive CBM-I + C-CBT condition than the control. This indicates that adding positive CBM-I to C-CBT enhanced the training effects on social anxiety, cognitive distortions, and social and work adjustment compared to the neutral CBM-I + C-CBT condition.

Effect of temperature and strain rate on the compressive behaviour of supramolecular polyurethane

Supramolecular polyurethanes (SPUs) possess thermoresponsive and thermoreversible properties, and those characteristics are highly desirable in both bulk commodity and value-added applications such as adhesives, shape-memory materials, healable coatings and lightweight, impact-resistant structures (e.g. protection for mobile electronics). A better understanding of the mechanical properties, especially the rate and temperature sensitivity, of these materials are required to assess their suitability for different applications. In this paper, a newly developed SPU with tuneable thermal properties was studied, and the response of this SPU to compressive loading over strain rates from 10−3 to 104 s−1 was presented. Furthermore, the effect of temperature on the mechanical response was also demonstrated. The sample was tested using an Instron mechanical testing machine for quasi-static loading, a home-made hydraulic system for moderate rates and a traditional split Hopkinson pressure bars (SHPBs) for high strain rates. Results showed that the compression stress-strain behaviour was affected significantly by the thermoresponsive nature of SPU, but that, as expected for polymeric materials, the general trends of the temperature and the rate dependence mirror each other. However, this behaviour is more complicated than observed for many other polymeric materials, as a result of the richer range of transitions that influence the behaviour over the range of temperatures and strain rates tested.

Environmental factors and features that influence visual search in a 3D WIMP interface

The challenge of moving past the classic Window Icons Menus Pointer (WIMP) interface, i.e. by turning it ‘3D’, has resulted in much research and development. To evaluate the impact of 3D on the ‘finding a target picture in a folder’ task, we built a 3D WIMP interface that allowed the systematic manipulation of visual depth, visual aides, semantic category distribution of targets versus non-targets; and the detailed measurement of lower-level stimuli features. Across two separate experiments, one large sample web-based experiment, to understand associations, and one controlled lab environment, using eye tracking to understand user focus, we investigated how visual depth, use of visual aides, use of semantic categories, and lower-level stimuli features (i.e. contrast, colour and luminance) impact how successfully participants are able to search for, and detect, the target image. Moreover in the lab-based experiment, we captured pupillometry measurements to allow consideration of the influence of increasing cognitive load as a result of either an increasing number of items on the screen, or due to the inclusion of visual depth. Our findings showed that increasing the visible layers of depth, and inclusion of converging lines, did not impact target detection times, errors, or failure rates. Low-level features, including colour, luminance, and number of edges, did correlate with differences in target detection times, errors, and failure rates. Our results also revealed that semantic sorting algorithms significantly decreased target detection times. Increased semantic contrasts between a target and its neighbours correlated with an increase in detection errors. Finally, pupillometric data did not provide evidence of any correlation between the number of visible layers of depth and pupil size, however, using structural equation modelling, we demonstrated that cognitive load does influence detection failure rates when there is luminance contrasts between the target and its surrounding neighbours. Results suggest that WIMP interaction designers should consider stimulus-driven factors, which were shown to influence the efficiency with which a target icon can be found in a 3D WIMP interface.