Análise do uso do Portal de Periódicos da CAPES na perspectiva de mestres e doutores formados pelo Programa de Pós-graduação em Administração da UFRN

The Brazilian CAPES Journal Portal aims to provide Information in Science and Technology (IST) for academic users. Thus, it is considered a relevant instrument for post-graduation dynamics and the country´s Science and Technology (S&T) development. Despite its importance, there are still few studies that focus on the policy analysis and efficiency of these resources. This research aims to fill in this gap once it proposes an analysis of the use of the CAPES Journal Portal done on behalf of the master´s and doctoral alumni of the Post Graduate Program in Management (PPGA) at the Federal University of Rio Grande do Norte (UFRN). The operationalization of the research´s main objective was possible through the specific objectives: characterize graduate profile as CAPES Journal Portal users b) identify motivation for the use of CAPES Journal Portal c) detect graduate satisfaction degree in information seeking done at CAPES Journal Portal d) verify graduate satisfaction regarding the use of the CAPES Journal Portal e) verify the use of the information that is obtained by graduates in the development of their academic activities. The research is of descriptive nature employing a mixed methodological strategy in which quantitative approach predominates. Data collection was done through a web survey questionnaire. Quantitative data analysis was made possible through the use of a statistical method. As for qualitative analysis, there was use of the Brenda Dervin´s sense-making approach as well as content analysis in open ended questions. The research samples were composed by 90 graduate students who had defended their dissertation/thesis in the PPGA program at UFRN in the time span of 2010-2013. This represented by 88% of this population. As for user profile, the analysis has made evident that there are no quantitative differences related to gender. There is predominance of male graduates that were aged 26 to 30 years old. As for female graduates, the great majority were 31 o 35 years old. Most graduates had Master´s degree scholarship in order to support their study. It was also seen that the great majority claim to use the Portal during their post graduation studies. The main reasons responsible for non use was: preference for the use of other data bases and lack of knowledge regarding the Portal. It was observed that the most used information resources were theses and dissertations. Data also indicate preference for complete text. Those who have used the Portal also claimed to have used other electronic information fonts in order to fulfill their information needs. The information fonts that were researched outside in the Portal were monographs, dissertations and thesis. Scielo was the most used information font. Results reveal that access and use of the Portal has been done in a regular manner during post graduation studies. But on the other hand, graduates also make use of other electronic information fonts in order to meet their information needs. The study also confirmed the important mission performed by the Portal regarding Brazilian scientific communication production. This was seen even though users have reported the need for improvement in some aspects such as: periodic training in order to promote, encourage and teach more effective use of the portal; investment aiming the expansion of Social Sciences Collection in the Portal as well as the need to implement continuous evaluation process related to user satisfaction in regarding the services provided.

O perfil sociodemográfico de pacientes em pós-operatório imediato de prostatectomia

Identificar o perfil sociodemográfico de pacientes submetidos à prostatectomia. Método: estudo quantitativo, transversal e descritivo, realizado na clínica cirúrgica de um Hospital Universitário na cidade de Natal/RN/Brasil, com 50 indivíduos em pós-operatório imediato de prostatectomia. A coleta de dados deu-se com um roteiro de anamnese e exame físico. Para a análise estatística dos dados foi utilizado o Programa Statistical Package for the Social Sciences, versão 16.0. O projeto de pesquisa foi aprovado pelo Comitê de Ética da Universidade Federal do Rio Grande do Norte, protocolo nº 130/10 CEP/UFRN. Resultados: os homens entrevistados tinham idade média de 67,78 anos, 80% tinham companheiros, com número de filhos variando de zero a quatro (56%). Conclusão: o conhecimento do perfil sociodemográfico dos pacientes prostatectomizados proporciona um direcionamento das ações de enfermagem frente à realidade de vida dessa clientela, uma vez que os pacientes estudados apresentaram perfil similar ao observado em outras cidades brasileiras

O perfil sociodemográfico de pacientes em pós-operatório imediato de prostatectomia

Identificar o perfil sociodemográfico de pacientes submetidos à prostatectomia. Método: estudo quantitativo, transversal e descritivo, realizado na clínica cirúrgica de um Hospital Universitário na cidade de Natal/RN/Brasil, com 50 indivíduos em pós-operatório imediato de prostatectomia. A coleta de dados deu-se com um roteiro de anamnese e exame físico. Para a análise estatística dos dados foi utilizado o Programa Statistical Package for the Social Sciences, versão 16.0. O projeto de pesquisa foi aprovado pelo Comitê de Ética da Universidade Federal do Rio Grande do Norte, protocolo nº 130/10 CEP/UFRN. Resultados: os homens entrevistados tinham idade média de 67,78 anos, 80% tinham companheiros, com número de filhos variando de zero a quatro (56%). Conclusão: o conhecimento do perfil sociodemográfico dos pacientes prostatectomizados proporciona um direcionamento das ações de enfermagem frente à realidade de vida dessa clientela, uma vez que os pacientes estudados apresentaram perfil similar ao observado em outras cidades brasileiras

Building an Australian user community for VIVO

The Australian National Data Service (ANDS) was established in 2008 and aims to: influence national policy in the area of data management in the Australian research community; inform best practice for the curation of data, and, transform the disparate collections of research data around Australia into a cohesive collection of research resources One high profile ANDS activity is to establish the population of Research Data Australia, a set of web pages describing data collections produced by or relevant to Australian researchers. It is designed to promote visibility of research data collections in search engines, in order to encourage their re-use. As part of activities associated with the Australian National Data Service, an increasing number of Australian Universities are choosing to implement VIVO, not as a platform to profile information about researchers, but as a 'metadata store' platform to profile information about institutional research data sets, both locally and as part of a national data commons. To date, the University of Melbourne, Griffith University, the Queensland University of Technology, and the University of Western Australia have all chosen to implement VIVO, with interest from other Universities growing.

User profiling based on folksonomy information in Web 2.0 for personalized recommender systems

Information overload has become a serious issue for web users. Personalisation can provide effective solutions to overcome this problem. Recommender systems are one popular personalisation tool to help users deal with this issue. As the base of personalisation, the accuracy and efficiency of web user profiling affects the performances of recommender systems and other personalisation systems greatly. In Web 2.0, the emerging user information provides new possible solutions to profile users. Folksonomy or tag information is a kind of typical Web 2.0 information. Folksonomy implies the users‘ topic interests and opinion information. It becomes another source of important user information to profile users and to make recommendations. However, since tags are arbitrary words given by users, folksonomy contains a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise makes it difficult to profile users accurately or to make quality recommendations. This thesis investigates the distinctive features and multiple relationships of folksonomy and explores novel approaches to solve the tag quality problem and profile users accurately. Harvesting the wisdom of crowds and experts, three new user profiling approaches are proposed: folksonomy based user profiling approach, taxonomy based user profiling approach, hybrid user profiling approach based on folksonomy and taxonomy. The proposed user profiling approaches are applied to recommender systems to improve their performances. Based on the generated user profiles, the user and item based collaborative filtering approaches, combined with the content filtering methods, are proposed to make recommendations. The proposed new user profiling and recommendation approaches have been evaluated through extensive experiments. The effectiveness evaluation experiments were conducted on two real world datasets collected from Amazon.com and CiteULike websites. The experimental results demonstrate that the proposed user profiling and recommendation approaches outperform those related state-of-the-art approaches. In addition, this thesis proposes a parallel, scalable user profiling implementation approach based on advanced cloud computing techniques such as Hadoop, MapReduce and Cascading. The scalability evaluation experiments were conducted on a large scaled dataset collected from Del.icio.us website. This thesis contributes to effectively use the wisdom of crowds and expert to help users solve information overload issues through providing more accurate, effective and efficient user profiling and recommendation approaches. It also contributes to better usages of taxonomy information given by experts and folksonomy information contributed by users in Web 2.0.

Parallel user profiling based on folksonomy for Large Scaled Recommender Systems : an implimentation of Cascading MapReduce

The Large scaled emerging user created information in web 2.0 such as tags, reviews, comments and blogs can be used to profile users’ interests and preferences to make personalized recommendations. To solve the scalability problem of the current user profiling and recommender systems, this paper proposes a parallel user profiling approach and a scalable recommender system. The current advanced cloud computing techniques including Hadoop, MapReduce and Cascading are employed to implement the proposed approaches. The experiments were conducted on Amazon EC2 Elastic MapReduce and S3 with a real world large scaled dataset from Del.icio.us website.

Acquiring user information needs for recommender systems

Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based filtering approach tries to recommend items that are similar to new users' profiles. The fundamental issues include how to profile new users, and how to deal with the over-specialization in content-based recommender systems. Indeed, the terms used to describe items can be formed as a concept hierarchy. Therefore, we aim to describe user profiles or information needs by using concepts vectors. This paper presents a new method to acquire user information needs, which allows new users to describe their preferences on a concept hierarchy rather than rating items. It also develops a new ranking function to recommend items to new users based on their information needs. The proposed approach is evaluated on Amazon book datasets. The experimental results demonstrate that the proposed approach can largely improve the effectiveness of recommender systems.

Utilizing voting systems for ranking user tweets

Twitter is a very popular social network website that allows users to publish short posts called tweets. Users in Twitter can follow other users, called followees. A user can see the posts of his followees on his Twitter profile home page. An information overload problem arose, with the increase of the number of followees, related to the number of tweets available in the user page. Twitter, similar to other social network websites, attempts to elevate the tweets the user is expected to be interested in to increase overall user engagement. However, Twitter still uses the chronological order to rank the tweets. The tweets ranking problem was addressed in many current researches. A sub-problem of this problem is to rank the tweets for a single followee. In this paper we represent the tweets using several features and then we propose to use a weighted version of the famous voting system Borda-Count (BC) to combine several ranked lists into one. A gradient descent method and collaborative filtering method are employed to learn the optimal weights. We also employ the Baldwin voting system for blending features (or predictors). Finally we use the greedy feature selection algorithm to select the best combination of features to ensure the best results.

Open Personalization: Involving Third Parties in Improving the User Experience of Websites

Traditional software development captures the user needs during the requirement analysis. The Web makes this endeavour even harder due to the difficulty to determine who these users are. In an attempt to tackle the heterogeneity of the user base, Web Personalization techniques are proposed to guide the users’ experience. In addition, Open Innovation allows organisations to look beyond their internal resources to develop new products or improve existing processes. This thesis sits in between by introducing Open Personalization as a means to incorporate actors other than webmasters in the personalization of web applications. The aim is to provide the technological basis that builds up a trusty environment for webmasters and companion actors to collaborate, i.e. "an architecture of participation". Such architecture very much depends on these actors’ profile. This work tackles three profiles (i.e. software partners, hobby programmers and end users), and proposes three "architectures of participation" tuned for each profile. Each architecture rests on different technologies: a .NET annotation library based on Inversion of Control for software partners, a Modding Interface in JavaScript for hobby programmers, and finally, a domain specific language for end-users. Proof-of-concept implementations are available for the three cases while a quantitative evaluation is conducted for the domain specific language.

Understanding Online Audio-Visual Content: A European Initiative, Media Literacy and the User

Recent debates about media literacy and the internet have begun to acknowledge the importance of active user-engagement and interaction. It is not enough simply to access material online, but also to comment upon it and re-use. Yet how do these new user expectations fit within digital initiatives which increase access to audio-visual-content but which prioritise access and preservation of archives and online research rather than active user-engagement? This article will address these issues of media literacy in relation to audio-visual content. It will consider how these issues are currently being addressed, focusing particularly on the high-profile European initiative EUscreen. EUscreen brings together 20 European television archives into a single searchable database of over 40,000 digital items. Yet creative re-use restrictions and copyright issues prevent users from re-working the material they find on the site. Instead of re-use, EUscreen instead offers access and detailed contextualisation of its collection of material. But if the emphasis for resources within an online environment rests no longer upon access but on user-engagement, what does EUscreen and similar sites offer to different users?

A New Gridding Technique for High Density Microarray Images Using Intensity Projection Profile of Best Sub Image

As the technologies for the fabrication of high quality microarray advances rapidly, quantification of microarray data becomes a major task. Gridding is the first step in the analysis of microarray images for locating the subarrays and individual spots within each subarray. For accurate gridding of high-density microarray images, in the presence of contamination and background noise, precise calculation of parameters is essential. This paper presents an accurate fully automatic gridding method for locating suarrays and individual spots using the intensity projection profile of the most suitable subimage. The method is capable of processing the image without any user intervention and does not demand any input parameters as many other commercial and academic packages. According to results obtained, the accuracy of our algorithm is between 95-100% for microarray images with coefficient of variation less than two. Experimental results show that the method is capable of gridding microarray images with irregular spots, varying surface intensity distribution and with more than 50% contamination

User-friendly free-text keystroke dynamics authentication for practical applications

This paper introduces a novel approach for free-text keystroke dynamics authentication which incorporates the use of the keyboard’s key-layout. The method extracts timing features from specific key-pairs. The Euclidean distance is then utilized to find the level of similarity between a user’s profile data and his/her test data. The results obtained from this method are reasonable for free-text authentication while maintaining the maximum level of user relaxation. Moreover, it has been proven in this study that flight time yields better authentication results when compared with dwell time. In particular, the results were obtained with only one training sample for the purpose of practicality and ease of real life application.

Transparent Provenance Derivation for User Decisions

It is rare for data's history to include computational processes alone. Even when software generates data, users ultimately decide to execute software procedures, choose their configuration and inputs, reconfigure, halt and restart processes, and so on. Understanding the provenance of data thus involves understanding the reasoning of users behind these decisions, but demanding that users explicitly document decisions could be intrusive if implemented naively, and impractical in some cases. In this paper, therefore, we explore an approach to transparently deriving the provenance of user decisions at query time. The user reasoning is simulated, and if the result of the simulation matches the documented decision, the simulation is taken to approximate the actual reasoning. The plausibility of this approach requires that the simulation mirror human decision -making, so we adopt an automated process explicitly modelled on human psychology. The provenance of the decision is modelled in OPM, allowing it to be queried as part of a larger provenance graph, and an OPM profile is provided to allow consistent querying of provenance across user decisions.

AALUMO: a user model ontology for ambient assisted living services supported in next-generation networks

Ambient Assisted Living (AAL) services are emerging as context-awareness solutions to support elderly people?s autonomy. The context-aware paradigm makes applications more user-adaptive. In this way, context and user models expressed in ontologies are employed by applications to describe user and environment characteristics. The rapid advance of technology allows creating context server to relieve applications of context reasoning techniques. Specifically, the Next Generation Networks (NGN) provides by means of the presence service a framework to manage the current user's state as well as the user's profile information extracted from Internet and mobile context. This paper propose a user modeling ontology for AAL services which can be deployed in a NGN environment with the aim at adapting their functionalities to the elderly's context information and state.