A categoria cena é utilizada neste trabalho para auxiliar na descrição da sociabilidade e dos espaços usados pelos pixadores em Vitória. Esta categoria de análise é descrita tanto a partir de uma abordagem do conceito de Will Straw, e da forma como o termo aparece nas interlocuções. A pixação é compreendida nesta pesquisa como uma das vertentes do graffiti, e por isso trazemos uma discussão bibliográfica sobre os usos dos termos graffiti e pixação. Para apresentar a cena da pixação em Vitória, partimos territorialmente do aglomerado metropolitano de Vitória. Devido à maneira como a cena da pixação se conforma em Vitória realizamos uma aproximação histórica da cena do graffiti e sobre o entrelaçamento das cenas do graffiti e da pixação ao longo do tempo e os momentos em que tornam-se autônomas, a cena do graffiti em relação ao hip hop e a da pixação em relação ao graffiti. / The scene category is used in this work to assist in describing the sociability and spaces used by the pixadores in Vitoria. This category of analysis is described both from an approach to the concept of Will Straw, and from the way the term appears in interlocutions. The pixação is understood in this research like one of the slopes of the graffiti, and therefore we bring a bibliographical discussion on the uses of the terms graffiti and pixação. In order to present the scene of the pixação in Vitoria, we depart territorially of the agglomerate metropolitan of Vitoria. Due to the way in which the scene of the pixação is conformed in Vitoria we make a historical approximation of the graffiti scene and the interweaving of the scenes of graffiti and the pixação through the time and the moments in which they become autonomous, the graffiti scene in relation to hip hop and graffiti.

A categoria cena é utilizada neste trabalho para auxiliar na descrição da sociabilidade e dos espaços usados pelos pixadores em Vitória. Esta categoria de análise é descrita tanto a partir de uma abordagem do conceito de Will Straw, e da forma como o termo aparece nas interlocuções. A pixação é compreendida nesta pesquisa como uma das vertentes do graffiti, e por isso trazemos uma discussão bibliográfica sobre os usos dos termos graffiti e pixação. Para apresentar a cena da pixação em Vitória, partimos territorialmente do aglomerado metropolitano de Vitória. Devido à maneira como a cena da pixação se conforma em Vitória realizamos uma aproximação histórica da cena do graffiti e sobre o entrelaçamento das cenas do graffiti e da pixação ao longo do tempo e os momentos em que tornam-se autônomas, a cena do graffiti em relação ao hip hop e a da pixação em relação ao graffiti. / The scene category is used in this work to assist in describing the sociability and spaces used by the pixadores in Vitoria. This category of analysis is described both from an approach to the concept of Will Straw, and from the way the term appears in interlocutions. The pixação is understood in this research like one of the slopes of the graffiti, and therefore we bring a bibliographical discussion on the uses of the terms graffiti and pixação. In order to present the scene of the pixação in Vitoria, we depart territorially of the agglomerate metropolitan of Vitoria. Due to the way in which the scene of the pixação is conformed in Vitoria we make a historical approximation of the graffiti scene and the interweaving of the scenes of graffiti and the pixação through the time and the moments in which they become autonomous, the graffiti scene in relation to hip hop and graffiti.

The most intriguing problems in genetics epidemiology are to predict genetic disease susceptibility and to associate single nucleotide polymorphisms (SNPs) with diseases. In such these studies, it is necessary to resolve the ambiguities in genetic data. The primary obstacle for ambiguity resolution is that the physical methods for separating two haplotypes from an individual genotype (phasing) are too expensive. Although computational haplotype inference is a well-explored problem, high error rates continue to deteriorate association accuracy. Secondly, it is essential to use a small subset of informative SNPs (tag SNPs) accurately representing the rest of the SNPs (tagging). Tagging can achieve budget savings by genotyping only a limited number of SNPs and computationally inferring all other SNPs. Recent successes in high throughput genotyping technologies drastically increase the length of available SNP sequences. This elevates importance of informative SNP selection for compaction of huge genetic data in order to make feasible fine genotype analysis. Finally, even if complete and accurate data is available, it is unclear if common statistical methods can determine the susceptibility of complex diseases. The dissertation explores above computational problems with a variety of methods, including linear algebra, graph theory, linear programming, and greedy methods. The contributions include (1)significant speed-up of popular phasing tools without compromising their quality, (2)stat-of-the-art tagging tools applied to disease association, and (3)graph-based method for disease tagging and predicting disease susceptibility.

This study focuses how the MLR-tagging for statistical covering, i.e. either maximizing average R2 for certain number of requested tags or minimizing number of tags such that for any non-tag SNP there exists a highly correlated (squared correlation R2 > 0.8) tag SNP. We compare with tagger, a software for selecting tags in hapMap project. MLR-tagging needs less number of tags than tagger in all 6 cases of the given test sets except 2. Meanwhile, Biologists can detect or collect data only from a small set. So, this will bring a problem for scientists that the estimates accuracy of tag SNPs when constructing the complete human haplotype map. This study investigates how the MLR-tagging for statistically coverage performs under unbias study. The experiment results shows MLR-tagging still select small amount of SNPs very well even without observing the entire SNP in the sample.

We present a measurement of the top anti-top quark (ttbar)production cross section in the dilepton final states from proton-proton collisions at a center of mass energy at 7 TeV at the LHC. A b-tagging algorithm based on tracks displaced from the event interaction vertex is applied to identify bottom quark jets from top quark decay and reject background events. Given the relatively pure sample of bottom quark jets in ttbar dilepton final states, a new technique to measure in-situ the b-tagging efficiency is introduced that uses the distribution of the number of observed b-tagged jets. We present results with data collected at the ATLAS detector in 2010 with an integrated luminosity of 35 pb-1. The measured ttbar cross section is 176 +22/-21 (stat.) ± 20 (syst.) ± 6 (lum.) pb in the dilepton channel. We will also discuss the future prospects of this measurement.

We present a measurement of the top anti-top quark (ttbar)production cross section in the dilepton final states from proton-proton collisions at a center of mass energy at 7 TeV at the LHC. A b-tagging algorithm based on tracks displaced from the event interaction vertex is applied to identify bottom quark jets from top quark decay and reject background events. Given the relatively pure sample of bottom quark jets in ttbar dilepton final states, a new technique to measure in-situ the b-tagging efficiency is introduced that uses the distribution of the number of observed b-tagged jets. We present results with data collected at the ATLAS detector in 2010 with an integrated luminosity of 35 pb-1. The measured ttbar cross section is 176 +22/-21 (stat.) ± 20 (syst.) ± 6 (lum.) pb in the dilepton channel. We will also discuss the future prospects of this measurement.

Tagging is widely adopted in so-called "collaborative-tagging" systems which are one of the Web 2.0 applications that have achieved lots of attention lately. They provide services for users to store, manage and search web resources with the help of freely chosen keywords, called "tags". Because of the high-volume usage of these systems and the annotations that users provide by their tags, these systems are regarded as good targets for disciplines like knowledge discovery. Roughly, two lines of research have been pursued so far on collaborative tagging: to study the structure of tags and to study their functionality in web search. In this research we investigated tagging structures in a popular collaborative-tagging system, called del.icio.us, by focusing on the relations of "tags", "users" and "web resources", three main components of any collaborative-tagging system. Particularly we are interested in finding whether there are social structures that could be used to increase the usability of these systems for content retrieval and navigation. Our results show that people mainly use tags for their own informational needs which are personal rather than social. Any social structure or communities around tags and users is rare and weak which suggests that collaborative tagging has not added much to personal bookmarking. However, we show some regularities in tagging behavior that could be utilized for user experience improvement. / Thesis (Master, Computing) -- Queen's University, 2008-12-04 14:34:37.537

The use of multimedia content on the web has grown significantly in recent years. Websites such as Facebook, YouTube and Flickr cater for enormous amounts of multimedia content uploaded by users. This vast amount of multimedia content requires comprehensive content modelling otherwise retrieving relevant content will be challenging. Modelling multimedia content can be an extremely time consuming task that may seem impossible particularly when undertaken by individual users. However, the advent of Web 2.0 and associated communities, such as YouTube and Flickr, has shown that users appear to be more willing to collaborate in order to take on enormous tasks such as multimedia content modelling. Harnessing the power of communities to achieve comprehensive content modelling is the primary focus of this research. The aim of this thesis is to explore collaborative multimedia content modelling and in particular the effectiveness of existing multimedia content modelling tools, taking into account the key development challenges of existing collaborative content modelling research and the associated modelling tools. Four research objectives are pursued in order to achieve this; first, design a user experiment to study users’ tagging behaviour with existing multimedia tagging tools and identify any relationships between such user behaviour; second, design and develop a framework for MPEG-7 content modelling communities based on the results of the experiment; third, implement an online service as a proof of concept of the framework; fourth, validate the framework through the online service during a repeat of the initial user experiment. This research contributes first, a conceptual model of user behaviour visualised as a fuzzy cognitive map and, second, an MPEG-7 framework for multimedia content modelling communities (MC2) and its proof of concept as an online service. The fuzzy cognitive model embodies relationships between user tagging behaviour and context and provides an understanding of user priorities in the description of content features and the relationships that exist between them. The MC2 framework, developed based on the fuzzy cognitive model, is deep-rooted in user content modelling behaviour and content preferences. A proof of concept of the MC2 framework is implemented as an online service in which all metadata is modelled using MPEG-7. The online service is validated, first, empirically with the same group of users and through the same experiment that led to the development of the fuzzy cognitive model and, second, functionally against the folksonomy and MPEG-7 content modelling tools used in the initial experiment. The validation demonstrates that MC2 has the advantages without the shortcomings of existing multimedia tagging tools by harnessing the ease of use of folksonomy tools while producing comprehensive structured metadata.

Im akademischen Bereich sind in Social-Software-Anwendungen wie Connotea, CiteULike und BibSonony umfangreiche Sammlungen von nutzergenerierten Metadaten entstanden. Im Vergleich zu kontrollierten Vokabularen, wie der Schlagwortnormdatei, handelt es sich dabei um personalisierte und in weiten Teilen „chaotische“ Inhaltserschließung. An der Universitätsbibliothek Mannheim wurde in einem DFG-Projekt untersucht, inwieweit das Potential dieser Art von Metadaten für eine bessere und nutzerorientierte Präsentation von Informationsressourcen eingesetzt werden kann. Ein Kernstück der Untersuchung war die Analyse von Tag-Daten des Systems BibSonomy. Es zeigte sich, dass nicht nur die mangelnde semantische Strukturiertheit der Tags, sondern auch ihre heterogene Gestalt einen limitierenden Faktor für die Verwendung in der bibliothekarischen Sacherschließung darstellt. Der Beitrag gibt anhand von Beispielen Einblick in das qualitative und strukturelle Chaos der untersuchten Tags und fasst die Ergebnisse des Projekts zusammen.

Tagging has become one of the key activities in next generation websites which allow users selecting short labels to annotate, manage, and share multimedia information such as photos, videos and bookmarks. Tagging does not require users any prior training before participating in the annotation activities as they can freely choose any terms which best represent the semantic of contents without worrying about any formal structure or ontology. However, the practice of free-form tagging can lead to several problems, such as synonymy, polysemy and ambiguity, which potentially increase the complexity of managing the tags and retrieving information. To solve these problems, this research aims to construct a lightweight indexing scheme to structure tags by identifying and disambiguating the meaning of terms and construct a knowledge base or dictionary. News has been chosen as the primary domain of application to demonstrate the benefits of using structured tags for managing the rapidly changing and dynamic nature of news information. One of the main outcomes of this work is an automatically constructed vocabulary that defines the meaning of each named entity tag, which can be extracted from a news article (including person, location and organisation), based on experts suggestions from major search engines and the knowledge from public database such as Wikipedia. To demonstrate the potential applications of the vocabulary, we have used it to provide more functionalities in an online news website, including topic-based news reading, intuitive tagging, clipping and sharing of interesting news, as well as news filtering or searching based on named entity tags. The evaluation results on the impact of disambiguating tags have shown that the vocabulary can help to significantly improve news searching performance. The preliminary results from our user study have demonstrated that users can benefit from the additional functionalities on the news websites as they are able to retrieve more relevant news, clip and share news with friends and families effectively.