Made available in DSpace on 2016-04-28T19:33:59Z (GMT). No. of bitstreams: 1 Elaine Aparecida dos Santos Estracieri.pdf: 7333160 bytes, checksum: d7798b818e75d4994fe45ff0ef34d20e (MD5) Previous issue date: 2015-09-02 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / This work is part of the research line Text and Discourse on Oral and Written Procedures , the Postgraduate Program in Portuguese at the Pontifical Catholic University of São Paulo. The Theme of this research is The constitution of the feminine ethos in The Yellow Bag , Lygia Bojunga and born of the initial belief linked to the construction of social discourses. In this paper we analyse a literary work here considered as a representation of the world through words. In the discursive level, it is the female speech introjection that rhetorical tricks, as they reflect the being in existence, leverage the instituting discourse and sediment, by moving the passions, new ways of saying and understand the world. The Yellow Bag, published in 1976, still reverberates powerfully valid one speech to think the status of women today in presenting indisputable rhetorical force in the development of the main character s arguments, Rachel girl. Thus, the analysis undertaken in this study adopts a perspective centered in the speech of female character-child, by checking a rhetorical process of constituting an ethos created fictitiously by an adult, the writer Lygia Bojunga. As we observed, handling the language the author demonstrates enough discursive ability to move within the limits of a literary text, the dominant discourse and create instituting apeeches that highlight the condition of being a woman in today s world. Raquel, through the rant, makes its effective argument, causes the pathos (passion) and the auditorium, by setting out a line originated from the interior of a child, it becomes benevolent with the narrated facts. For present itself in the robes of a literary text, passion compels the audience to accept one or more conclusions about a woman nowadays. This attitude of acceptance presupposes driving through reasoning, albeit sharp appeal to the listener s emotions. The analysis addresses, then two facets: the recreation of speech in child communicative interaction situation and fictional view of how a child is imposed discursively to constitute its ethos in the narrative. Constituted as an analytical base studies of Aristotles (2000), Perelman and Olbrechts-Tyteca (2005), that guide research Reboul (2004), Meyer (2007) and Ferreira (2010). To create the historical context, draws up an overview of women, children and the family, through Bassanezi studies (1986), Aries (2012) and Santarcangelo (1980). For proof of persuasive means, analyses through features allowed by the rhetoric analisys, the efficacy of the speech by the girl-woman speaker called Raquel. At the end of the investigation it was concluded that, in the Yellow Bag, as imagined in the case of this study, the condition of women, historically marked by devaluation, submission and subservience, is partially abandoned to make way for discursive construction of a scenario that portends changes social and significant contemporany female professionals in the act. It appears, too, that the character Rachel is constructed rhetorically to highlight an ethos that seduces (movere) the auditorium to present as girl-child (delectare) and proposes questions that culminate in reflections (docere) to the auditorium / Esta dissertação insere-se na linha de pesquisa Texto e Discurso nas Modalidades Oral e Escrita , do Programa de Pós-Graduados em Língua Portuguesa da Pontifícia Universidade Católica de São Paulo. O tema desta pesquisa é A constituição do ethos feminino no livro A Bolsa Amarela , de Lygia Bojunga, surgida de uma crença inicial ligada à construção dos discursos sociais. Neste trabalho, analisamos uma obra literária aqui considerada como representação do mundo por meio da palavra. No plano discursivo, é pela introjeção do discurso feminino que as artimanhas retóricas, enquanto refletem o estar na existência, potencializam o discurso instituinte e sedimentam, pelo movimentar das paixões, novas formas de dizer e compreender o mundo. O livro A Bolsa Amarela, publicado em 1976, ainda reverbera um discurso potentemente válido para pensar a condição da mulher em nossos dias, ao apresentar indiscutível força retórica na elaboração dos argumentos da personagem principal, a menina Raquel. Assim, a análise empreendida neste trabalho adota uma perspectiva centrada na fala de uma personagem-criança do sexo feminino, por meio da verificação de um processo retórico de constituição de um ethos criado ficticiamente por um adulto, a escritora Lygia Bojunga. Como foi possível verificar, o manuseio da língua pela autora demonstra habilidade discursiva suficiente para movimentar, nos limites de um texto literário, o discurso dominante e criar discursos instituintes que ressaltam na condição de ser mulher no mundo atual. Raquel, por meio do discurso retórico, torna sua argumentação eficaz, provoca o pathos (paixões) e o auditório, por enunciar uma fala originada do interior de uma criança, torna-se benevolente com os fatos narrados. Por se apresentar sob as vestes de um texto literário, a paixão compele o auditório a aceitar uma ou mais conclusões sobre o ser mulher na contemporaneidade. Essa atitude de aceitação pressupõe a condução por meio de raciocínios, ainda que de nítido apelo à emoção do ouvinte. A análise aborda, então, duas facetas: a recriação da fala infantil em situação de interação comunicativa e uma visão ficcional da forma como uma criança se impõe discursivamente para constituir seu ethos na narrativa. Constituíram como base analítica os estudos de Aristóteles (2000), Perelman e Olbrechts-Tyteca (2005), que orientam as pesquisas de Reboul (2004), Meyer (2007) e Ferreira (2010). À criação do contexto histórico, traça-se um panorama geral da mulher, da criança e da família, por meio dos estudos de Bassanezi (1986), Ariès (2012) e Santarcangelo (1980). À comprovação dos meios persuasivos, analisa-se, por meio de recursos permitidos pela análise retórica, a eficácia do discurso proferido pela oradora menina-mulher chamada Raquel. Ao término da investigação conclui-se que, em A Bolsa Amarela, como se imaginava na hipótese deste trabalho, a condição feminina, historicamente marcada pela desvalorização, submissão e subserviência, é parcialmente abandonada para dar lugar à edificação discursiva de um cenário que prenuncia mudanças sociais e profissionais significativas no agir feminino contemporâneo. Constata-se, também, que a personagem Raquel é construída retoricamente para ressaltar um ethos que seduz (movere) o auditório ao se apresentar como menina-criança (delectare) e propõe questionamentos que culminam em reflexões (docere) para o auditório

Today focus on the environemnt is bigger than ever before. UN writes in their climate agenda that they by 2030want to cut the food waste per capita in half. There are strict regulations today regarding how food needs to betransported and stored, but as soon as the consument takes, for example, milk from the frigde at a store there areonly a few guidelines about how the product should be stored. If a chilled or frozen product is not kept insidethe range of the given temperature, a microbilogical growth will begin. This leads to that the food goes bad or,in worst case, that the consumer gets poisoned. There is a change happening today in how the consumers shoptheir food and more focus is layed upon the customer to handle their grocery shopping by themselves. This project focuses on developing a solution that will help the consumer to keep their food at the right temperatureduring an extended period of time. The project is carried out in Stockholm during 20 weeks in collaborationwith IKEA of Sweden in Älmhult. The target group in this project is IKEA’s broad customer group.With help from a Human Centered Design process this project goes through the three phases; inspiration,ideation and implementation. The project has been formed with interaction through workshops with differentexternal actors like users and focus groups. The ideation resulted in four simpler concepts that verged in to twothrough external decision making with supervisors from IKEA of Sweden. During the project, the prototypeshave been used together with users to evaluate the usability of the concepts. The result consists of two concepts; Behålla and Blåsa, that are aimed to meet two different users that hasbeen identified through surveys and interviews. Behålla is a smaller product that is target towards the user thatbrings food with them to work or school, also to those who buys less groceries at the store. Blåsa is, in contrastto Behålla, a bigger product that is targeted towards the customers that buys a bigger set of chilled and frozengroceries. Additionally four color variations has been created to offer IKEA alternative executions. These conceptsare visualized with renderings through Adobe Illustratior. With these concepts IKEA can enlarge theirsustainability profile and offer their customers two new products to keep their chilled and frozen foods cold. / Fokus på miljön är idag större än någonsin. FN skriver i sin klimat agenda att de till 2030 siktar på att halveramatsvinnet per capita. Idag finns det hårda regleringar om hur livsmedel ska transporte-ras och förvaras, menfrån den sekund konsumenten tar ut exempelvis ett mjölkpaket ur kyldisken finns det bara få riktlinjer om hurprodukten bör förvaras. Om en kyld eller fryst produkt inte hålls inom det angivna temperaturspannet skerdet en ökning i den mikrobiologiska tillväxten i livsmed-let. Detta leder i sin tur att matvaran blir dålig eller, ivärsta fall, att konsumenten blir förgiftad. Idag sker det också en förändring i hur konsumenterna handlar sinalivsmedel och allt större vikt läggs på att konsumenten för sig själv ska genomföra sitt köp. Detta projekt fokuserar på att utveckla en lösning som ska hjälpa konsumenten att hålla sina matvaror tempereradeunder en viss tid. Projektet är genomfört i Stockholm under 20 veckor i samarbete med IKEA ofSweden i Älmhult. Målgruppen i detta projekt är den breda kundgrupp som IKEA erhåller. Med hjälp av enanvändarcentrerad designprocess går det här projektet genom de tre designfaserna; inspiration, idégenereringoch slutligen implementering. Projektet har formats av interaktion genom workshops med olika externa aktörerså som användare och fokusgrupper. Idégenereringsfasen resulterade i fyra stycken enklare koncept somavgränsades till två genom extern beslutsfattning med handledare från IKEA of Sweden. Under projektets gånghar prototyper använts tillsammans med användare för att evaluera användarvänligheten hos koncepten. Resultatet består av två stycken koncept; Behålla och Blåsa, som är ämnade att möta två olika kundgrupper somhar identifierats genom enkäter och intervjuer. Behålla är en mindre produkt som riktar sig till de användaresom tar med sig matlåda till jobbet eller skolan samt till dem som köper färre matvaror i butiken. Blåsa är, ikontrast till Behålla en större produkt, skapad med fokus på de kunder som köper fler kylda och frysta matvaror.Utöver detta har fyra färgvariation skapats av produkterna för att erbjuda IKEA alternativa utföranden. Dessakoncept är visualiserade med hjälp av renderingar som har gjort i Adobe Illustrator. Med dessa koncept kanIKEA utöka sin hållbarhets profil och erbjuda sina kunder två nya produkter för att hålla deras kylda och frystamatvaror kalla.

A good image representation is vital for image comparision and classification; it may affect the classification accuracy and efficiency. The purpose of this thesis was to explore novel and appropriate image representations. Another aim was to investigate these representations for image classification. Finally, novel features were examined for improving image classification accuracy. Images of interest to this thesis were textile design images. The motivation of analysing textile design images is to help designers browse images, fuel their creativity, and improve their design efficiency. In recent years, bag-of-words model has been shown to be a good base for image representation, and there have been many attempts to go beyond this representation. Bag-of-words models have been used frequently in the classification of image data, due to good performance and simplicity. “Words” in images can have different definitions and are obtained through steps of feature detection, feature description, and codeword calculation. The model represents an image as an orderless collection of local features. However, discarding the spatial relationships of local features limits the power of this model. This thesis exploited novel image representations, bag of shapes and region label graphs models, which were based on bag-of-words model. In both models, an image was represented by a collection of segmented regions, and each region was described by shape descriptors. In the latter model, graphs were constructed to capture the spatial information between groups of segmented regions and graph features were calculated based on some graph theory. Novel elements include use of MRFs to extract printed designs and woven patterns from textile images, utilisation of the extractions to form bag of shapes models, and construction of region label graphs to capture the spatial information. The extraction of textile designs was formulated as a pixel labelling problem. Algorithms for MRF optimisation and re-estimation were described and evaluated. A method for quantitative evaluation was presented and used to compare the performance of MRFs optimised using alpha-expansion and iterated conditional modes (ICM), both with and without parameter re-estimation. The results were used in the formation of the bag of shapes and region label graphs models. Bag of shapes model was a collection of MRFs' segmented regions, and the shape of each region was described with generic Fourier descriptors. Each image was represented as a bag of shapes. A simple yet competitive classification scheme based on nearest neighbour class-based matching was used. Classification performance was compared to that obtained when using bags of SIFT features. To capture the spatial information, region label graphs were constructed to obtain graph features. Regions with the same label were treated as a group and each group was associated uniquely with a vertex in an undirected, weighted graph. Each region group was represented as a bag of shape descriptors. Edges in the graph denoted either the extent to which the groups' regions were spatially adjacent or the dissimilarity of their respective bags of shapes. Series of unweighted graphs were obtained by removing edges in order of weight. Finally, an image was represented using its shape descriptors along with features derived from the chromatic numbers or domination numbers of the unweighted graphs and their complements. Linear SVM classifiers were used for classification. Experiments were implemented on data from Liberty Art Fabrics, which consisted of more than 10,000 complicated images mainly of printed textile designs and woven patterns. Experimental data was classified into seven classes manually by assigning each image a text descriptor based on content or design type. The seven classes were floral, paisley, stripe, leaf, geometric, spot, and check. The result showed that reasonable and interesting regions were obtained from MRF segmentation in which alpha-expansion with parameter re-estimation performs better than alpha-expansion without parameter re-estimation or ICM. This result was not only promising for textile CAD (Computer-Aided Design) to redesign the textile image, but also for image representation. It was also found that bag of shapes model based on MRF segmentation can obtain comparable classification accuracy with bag of SIFT features in the framework of nearest neighbour class-based matching. Finally, the result indicated that incorporation of graph features extracted by constructing region label graphs can improve the classification accuracy compared to both bag of shapes model and bag of SIFT models.

The intention of this thesis is to provide an alternative counter-narrative to the mainstream histories of punk that center white men. By focusing on the contributions of fem queer and POC punks, I aim to legitimize punk music as a form of resistance against systems of oppression that are oppositional to the commodified forms of mainstream punk. Using Alice Bag, as my central case study as a fem queer punk that is often left out of punk historical narratives, I contextualize her work through feminist, queer, and media studies lenses to bridge the gap between academia and forgotten personal experience.

Die vorliegende Dissertation beinhaltet eine umfassende Untersuchung der Entscheidbarkeit und Komplexität der Probleme, die sich durch eine statische Analyse von monadischem Datalog auf endlichen gefärbten Bäumen stellen. Statische Analyse bedeutet hierbei Anfrageoptimierung ohne Blick auf konkrete Instanzen, aber mit Rücksicht auf deren zugrunde liegende Struktur. Im Kern beinhaltet dies die Lösung der drei folgenden Probleme: das Leerheitsproblem (die Frage, ob eine Anfrage auf jeder Instanz ein leeres Ergebnis liefert), das Äquivalenzproblem (die Frage, ob zwei Anfragen auf jeder Instanz das gleiche Ergebnis liefern) und das Query-Containment-Problem (die Frage, ob das Ergebnis der einen Anfrage auf jeder Datenbank im Ergebnis der anderen Anfrage enthalten ist). Von Interesse ist dabei, ob die Fragen für eine gegebene Anfragesprache entscheidbar sind und wenn ja, welche Komplexität ihnen innewohnt. Wir betrachten diese Probleme für monadisches Datalog auf unterschiedlichen Repräsentationen für endliche gefärbte Bäume. Hierbei unterscheiden wir zwischen ungeordneten und geordneten Bäumen, welche die Achsen child bzw. firstchild und nextsibling und deren Erweiterung um die descendant-Achse nutzen. Außerdem unterscheiden wir Alphabete mit und ohne Rang. Monadisches Datalog ist eine Anfragesprache, die in Abhängigkeit vom gewählten Schema die Ausdrucksstärke der monadischen Logik zweiter Stufe (MSO) erreicht und dennoch effizient ausgewertet werden kann. Wir zeigen, dass unter in der Datenbanktheorie üblichen Mengensemantik die drei genannten Probleme für alle Schemata ohne descendant-Achse EXPTIME-vollständig sind und lösbar in 2EXPTIME, falls die descendant-Achse involviert ist. Eine passende untere Schranke wird für fast alle Schemata gezeigt. Unter Multimengensemantik lassen sich die obigen Ergebnisse für das Leerheitsproblem übertragen, während das Query-Containment-Problem für alle betrachteten Schemata unentscheidbar ist. / This thesis provides a comprehensive investigation into the decidability and complexity of the fundamental problems entailed by static analysis of monadic datalog on finite labeled trees. Static analysis is used for optimizing queries without considering concrete database instances but exploiting information about the represented structure. Static analysis relies on three basic decision problems. First, the emptiness problem, whose task is to decide whether a query returns the empty result on every database. Second, the equivalence problem asking if the result of two given queries always coincides on every database. And finally, the query containment problem where it is to decide whether on every database a given query produces a subset of the results of a second given query. We are interested in finding out whether these problems are decidable and, if so, what their complexity is. We consider the aforementioned problems for monadic datalog on different representations of finite labeled trees. We distinguish unordered and ordered trees which use the axis child, as well as the axes firstchild and nextsibling, respectively. An extension of the schemas by the descendant-axis is also considered. Furthermore, we distinguish ranked and unranked labeling alphabets. Depending on the schema, the query language monadic datalog can reach the expressive power of monadic second order logic but remains efficiently evaluable. Under set semantics, we show EXPTIME-completness for all used schemas where the descendant-axis is omitted. If the descendant-axis is involved, we present an algorithm that solves the problem within 2-fold exponential time. A matching lower bound is proven for virtually all schemas. Finally, we prove that the complexity of the emptiness problem of monadic datalog on finite trees under bag semantics is the same as under set semantics. Furthermore, we show that the query containment problem of monadic datalog under bag semantics is undecidable in general.

Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained object classification. The contributions of the thesis are three-fold. First, we introduce two databases of high-resolution images of arthropod specimens we collected to promote the development of highly accurate fine-grained recognition methods. Second, we give a literature review on the development of Bag-of-words (BOW) approaches to image classification and present the stacked evidence tree approach we developed for the fine-grained classification task. We draw connections and analyze differences between those two genres of approaches, which leads to a better understanding about the design of image classification approaches. Third, benchmark results on our two datasets are pre- sented. We further analyze the influence of two important variables on the performance of fine-grained classification. The experiments corroborate our hypotheses that a) high resolution images and b) more aggressive information extraction, such as finer descriptor encoding with large dictionaries or classifiers based on raw descriptors, is required to achieve good fine-grained categorization accuracy. / Graduation date: 2013

En la presente Tesis Doctoral se estudió la capacidad de conservación y la calidad sensorial de diversos platos preparados a base de carne o pescado cocinados mediante la tecnología sous vide y conservados en refrigeración. El objetivo fue estudiar el deterioro y determinar la vida comercial con el fin de introducir mejoras tecnológicas. Se determinaron diversos parámetros microbiológicos (enterobacterias totales, aerobios y anaerobios psicrófilos, bacterias ácido lácticas y mohos y levaduras), físico-químicos (pH, aw, acidez, textura instrumental y color CIELab) y sensoriales (análisis descriptivo cuantitativo del aspecto, olor, olor, sabor y textura). Los resultados obtenidos indican que los tiempos y temperaturas recomendados para cocinar la carne y/o el pescado sous vide aseguraron una correcta pasteurización. No se detectaron cambios apreciables de humedad, acidez, color o textura. Sólo el análisis sensorial permitió evaluar el deterioro de la carne y/o pescado sous vide durante su almacenamiento. La tecnología sous vide proporcionó platos refrigerados a base de carne y/o pescado con una alta aceptación y una vida comercial adecuada para su distribución en sistemas de catering. / The present PhD thesis analyses the preserving capacity and the sensory quality of different meat-or-fish-based dishes which are cooked by using the sous vide method and recreating the conditions of catering industry.The aim was to study the spoilage and to determine the shelf-life of these products to introduce technological improvements. For this purpose, several parameters were established: microbiological (aerobic and anaerobic psychrotrophs, lactic acid bacteria, Enterobacteriaceae, mould and yeasts), physical-chemical (pH, aw, acidity, instrumental texture and colour CIELab) and sensory (QDA of the appearance, colour, odour, flavour and texture). The results indicated that the periods of time and temperatures which are recommended to cook sous vide meat or fish guaranteed a correct pasteurization which prevented the proliferation, at 2 ºC, of Enterobacteriaceae and altering microorganisms. Only the sensory analysis permitted the evaluation of the spoilage of the sous vide cooked meat or fish during their storage. All this would leave a considerable safety margin in the cooking process so that the sensory quality could be adjusted. Besides, no noticeable variations of humidity, acidity, colour or texture were detected by the physical-chemical techniques, which were employed.

A growing number of 3D graphic applications have an impact on today's society. These applications are being used in several domains ranging from digital entertainment, computer aided design, to medical applications. In this context, a 3D object search engine with a good performance in time consuming and results becomes mandatory. We propose a novel approach for 3D-model retrieval based on closed curves. Then we enhance our method to handle partial 3D-model retrieval. Our method starts by the definition of an invariant mapping function. The important properties of a mapping function are its invariance to rigid and non rigid transformations, the correct description of the 3D-model, its insensitivity to noise, its robustness to topology changes, and its independance on parameters. However, current state-of-the-art methods do not respect all these properties. To respect these properties, we define our mapping function based on the diffusion and the commute-time distances. To prove the properties of this function, we compute the Reeb graph of the 3D-models. To describe the whole 3D-model, using our mapping function, we generate indexed closed curves from a source point detected automatically at the center of a 3D-model. Each curve describes a small region of the 3D-model. These curves lead to create an invariant descriptor to different transformations. To show the robustness of our method on various classes of 3D-models with different poses, we use shapes from SHREC 2012. We also compare our approach to existing methods in the state-of-the-art with a dataset from SHREC 2010. For partial 3D-model retrieval, we enhance the proposed method using the Bag-Of-Features built with all the extracted closed curves, and show the accurate performances using the same dataset

No description available.

Usually, human beings are able to quickly distinguish between different places, solely from their visual appearance. This is due to the fact that they can organize their space as composed of discrete units. These units, called ''semantic places'', are characterized by their spatial extend and their functional unity. Such a semantic category can thus be used as contextual information which fosters object detection and recognition. Recent works in semantic place recognition seek to endow the robot with similar capabilities. Contrary to classical localization and mapping works, this problem is usually addressed as a supervised learning problem. The question of semantic places recognition in robotics - the ability to recognize the semantic category of a place to which scene belongs to - is therefore a major requirement for the future of autonomous robotics. It is indeed required for an autonomous service robot to be able to recognize the environment in which it lives and to easily learn the organization of this environment in order to operate and interact successfully. To achieve that goal, different methods have been already proposed, some based on the identification of objects as a prerequisite to the recognition of the scenes, and some based on a direct description of the scene characteristics. If we make the hypothesis that objects are more easily recognized when the scene in which they appear is identified, the second approach seems more suitable. It is however strongly dependent on the nature of the image descriptors used, usually empirically derived from general considerations on image coding.Compared to these many proposals, another approach of image coding, based on a more theoretical point of view, has emerged the last few years. Energy-based models of feature extraction based on the principle of minimizing the energy of some function according to the quality of the reconstruction of the image has lead to the Restricted Boltzmann Machines (RBMs) able to code an image as the superposition of a limited number of features taken from a larger alphabet. It has also been shown that this process can be repeated in a deep architecture, leading to a sparse and efficient representation of the initial data in the feature space. A complex problem of classification in the input space is thus transformed into an easier one in the feature space. This approach has been successfully applied to the identification of tiny images from the 80 millions image database of the MIT. In the present work, we demonstrate that semantic place recognition can be achieved on the basis of tiny images instead of conventional Bag-of-Word (BoW) methods and on the use of Deep Belief Networks (DBNs) for image coding. We show that after appropriate coding a softmax regression in the projection space is sufficient to achieve promising classification results. To our knowledge, this approach has not yet been investigated for scene recognition in autonomous robotics. We compare our methods with the state-of-the-art algorithms using a standard database of robot localization. We study the influence of system parameters and compare different conditions on the same dataset. These experiments show that our proposed model, while being very simple, leads to state-of-the-art results on a semantic place recognition task.