A sociologia da modernidade líquida de Zygmunt Bauman (1925 ) é, segundo o autor, um modo possível de articular o conhecimento científico sobre a sociedade com o conhecimento comum da vida cotidiana. Em virtude de sua natureza, seus textos têm despertado grande interesse em um público de leitores não habituados a esse campo disciplinar, a ponto de ser apresentado, por suas casas publicadoras, como um verdadeiro best-seller. Este estudo, situado no âmbito da sociologia da cultura, visa compreender, por meio da análise da sociologia de Bauman, o estado atual do campo sociológico em suas relações com a cultura de massa, tendo por pressuposto a lógica cultural contemporânea em que a distinção tradicional entre alta e baixa cultura ou entre ciência e senso comum parece perder legitimidade. Como resultado, a sociologia da modernidade líquida, a despeito de sua pretensão científica, aproximar-se-ia das práticas de vulgarização da ciência, fenômeno mais amplo e difuso nos diversos domínios disciplinares e que encontraria no esquema teórico de Bauman sua expressão no campo sociológico. / The liquid modernity sociology of Zygmunt Bauman (1925 -) is, according to the author, a possible way to linking scientific knowledge about society with common knowledge of everyday life. Due to their nature, his texts have aroused great interest in an audience of readers not familiar with this disciplinary field, about to be presented, by his publishers, like a true best-seller. This study, situated within the sociology of culture, aims to understand, through the analysis of the Baumans sociology, the current state of the sociological field in its relations to the mass culture, admitting a cultural logic contemporary that the traditional distinction between high and low culture - or between science and common sense - seems to lose legitimacy. As a result, the sociology of liquid modernity, despite its scientific pretensions, would bring the practices of scientific literacy, broader phenomenon and diffuse in different disciplinary domains and find that thetheoretical scheme of Bauman expression in sociological field.

abstract: Image Understanding is a long-established discipline in computer vision, which encompasses a body of advanced image processing techniques, that are used to locate (“where”), characterize and recognize (“what”) objects, regions, and their attributes in the image. However, the notion of “understanding” (and the goal of artificial intelligent machines) goes beyond factual recall of the recognized components and includes reasoning and thinking beyond what can be seen (or perceived). Understanding is often evaluated by asking questions of increasing difficulty. Thus, the expected functionalities of an intelligent Image Understanding system can be expressed in terms of the functionalities that are required to answer questions about an image. Answering questions about images require primarily three components: Image Understanding, question (natural language) understanding, and reasoning based on knowledge. Any question, asking beyond what can be directly seen, requires modeling of commonsense (or background/ontological/factual) knowledge and reasoning. Knowledge and reasoning have seen scarce use in image understanding applications. In this thesis, we demonstrate the utilities of incorporating background knowledge and using explicit reasoning in image understanding applications. We first present a comprehensive survey of the previous work that utilized background knowledge and reasoning in understanding images. This survey outlines the limited use of commonsense knowledge in high-level applications. We then present a set of vision and reasoning-based methods to solve several applications and show that these approaches benefit in terms of accuracy and interpretability from the explicit use of knowledge and reasoning. We propose novel knowledge representations of image, knowledge acquisition methods, and a new implementation of an efficient probabilistic logical reasoning engine that can utilize publicly available commonsense knowledge to solve applications such as visual question answering, image puzzles. Additionally, we identify the need for new datasets that explicitly require external commonsense knowledge to solve. We propose the new task of Image Riddles, which requires a combination of vision, and reasoning based on ontological knowledge; and we collect a sufficiently large dataset to serve as an ideal testbed for vision and reasoning research. Lastly, we propose end-to-end deep architectures that can combine vision, knowledge and reasoning modules together and achieve large performance boosts over state-of-the-art methods. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2018

Common‒sense knowledge is a collection of non‒expert and agreed‒upon facts and information about the world shared among most people past early childhood based on their experiences. It includes uses of objects, their properties, parts and materials, their locations, spatial arrangements among them; location and duration of events; arguments, preconditions and effects of actions; urges and emotions of people, etc. In creating 3D worlds and especially text‒ to‒scene and text‒to‒animation systems, this knowledge is essential to eliminate the tedious and low‒level tasks, thus allowing users to focus on their creativity and imagination. We address tasks related to five categories of common‒sense knowledge that is required by such systems including: (1) spatial role labeling to automatically identify and annotate a set of spatial signals within a scene description in natural language; (2) grounding spatial relations to automatically position an object in 3D world; (3) inferring spatial relations to extract symbolic spatial relation between objects to answer questions regarding a 3D world; (4) recommending objects and their relative spatial relations given a recent manipulated object to auto‒complete a scene design; (5) learning physical attributes (e.g., size, weight, and speed) of objects and their corresponding distribution. We approach these tasks by using deep learning and probabilistic graphical models and exploit existing datasets and web content to learn the corresponding common‒sense knowledge.

abstract: While in recent years deep learning (DL) based approaches have been the popular approach in developing end-to-end question answering (QA) systems, such systems lack several desired properties, such as the ability to do sophisticated reasoning with knowledge, the ability to learn using less resources and interpretability. In this thesis, I explore solutions that aim to address these drawbacks. Towards this goal, I work with a specific family of reading comprehension tasks, normally referred to as the Non-Extractive Reading Comprehension (NRC), where the given passage does not contain enough information and to correctly answer sophisticated reasoning and ``additional knowledge" is required. I have organized the NRC tasks into three categories. Here I present my solutions to the first two categories and some preliminary results on the third category. Category 1 NRC tasks refer to the scenarios where the required ``additional knowledge" is missing but there exists a decent natural language parser. For these tasks, I learn the missing ``additional knowledge" with the help of the parser and a novel inductive logic programming. The learned knowledge is then used to answer new questions. Experiments on three NRC tasks show that this approach along with providing an interpretable solution achieves better or comparable accuracy to that of the state-of-the-art DL based approaches. The category 2 NRC tasks refer to the alternate scenario where the ``additional knowledge" is available but no natural language parser works well for the sentences of the target domain. To deal with these tasks, I present a novel hybrid reasoning approach which combines symbolic and natural language inference (neural reasoning) and ultimately allows symbolic modules to reason over raw text without requiring any translation. Experiments on two NRC tasks shows its effectiveness. The category 3 neither provide the ``missing knowledge" and nor a good parser. This thesis does not provide an interpretable solution for this category but some preliminary results and analysis of a pure DL based approach. Nonetheless, the thesis shows beyond the world of pure DL based approaches, there are tools that can offer interpretable solutions for challenging tasks without using much resource and possibly with better accuracy. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2019

abstract: Significance of real-world knowledge for Natural Language Understanding(NLU) is well-known for decades. With advancements in technology, challenging tasks like question-answering, text-summarizing, and machine translation are made possible with continuous efforts in the field of Natural Language Processing(NLP). Yet, knowledge integration to answer common sense questions is still a daunting task. Logical reasoning has been a resort for many of the problems in NLP and has achieved considerable results in the field, but it is difficult to resolve the ambiguities in a natural language. Co-reference resolution is one of the problems where ambiguity arises due to the semantics of the sentence. Another such problem is the cause and result statements which require causal commonsense reasoning to resolve the ambiguity. Modeling these type of problems is not a simple task with rules or logic. State-of-the-art systems addressing these problems use a trained neural network model, which claims to have overall knowledge from a huge trained corpus. These systems answer the questions by using the knowledge embedded in their trained language model. Although the language models embed the knowledge from the data, they use occurrences of words and frequency of co-existing words to solve the prevailing ambiguity. This limits the performance of language models to solve the problems in common-sense reasoning task as it generalizes the concept rather than trying to answer the problem specific to its context. For example, "The painting in Mark's living room shows an oak tree. It is to the right of a house", is a co-reference resolution problem which requires knowledge. Language models can resolve whether "it" refers to "painting" or "tree", since "house" and "tree" are two common co-occurring words so the models can resolve "tree" to be the co-reference. On the other hand, "The large ball crashed right through the table. Because it was made of Styrofoam ." to resolve for "it" which can be either "table" or "ball", is difficult for a language model as it requires more information about the problem. In this work, I have built an end-to-end framework, which uses the automatically extracted knowledge based on the problem. This knowledge is augmented with the language models using an explicit reasoning module to resolve the ambiguity. This system is built to improve the accuracy of the language models based approaches for commonsense reasoning. This system has proved to achieve the state of the art accuracy on the Winograd Schema Challenge. / Dissertation/Thesis / Masters Thesis Computer Science 2019

Zero-shot Natural Language-Video Localization (NLVL) has shown promising results in training NLVL models solely with raw video data through dynamic video segment proposal generation and pseudo-query annotations. However, existing pseudo-queries lack grounding in the source video and suffer from a lack of common ground due to their unstructured nature. In this work, we investigate the effectiveness of commonsense reasoning in zero-shot NLVL. Specifically, we present CORONET, a zero-shot NLVL framework that utilizes commonsense information to bridge the gap between videos and generated pseudo-queries through a commonsense enhancement module. Our approach employs Graph Convolutional Networks (GCN) to encode commonsense information extracted from a knowledge graph, conditioned on the video, and cross-attention mechanisms to enhance the encoded video and pseudo-query vectors prior to localization. Through empirical evaluations on two benchmark datasets, we demonstrate that our model surpasses both zero-shot and weakly supervised baselines. These results underscore the significance of leveraging commonsense reasoning abilities in multimodal understanding tasks. / Master of Science / Natural Language Video Localization (NLVL) is the task of retrieving relevant video segments from an untrimmed video given a user text query. To train an NLVL system, traditional methods demand annotations on the input videos, which include video segment spans (i.e., start and end timestamps) and the accompanying text query describing the segment. These annotations are laborious to collect for any domain and video length. To alleviate this, zero-shot NLVL methods generate the aforementioned annotations dynamically. However, current zero-shot NLVL approaches suffer from poor alignment between the video and the dynamically generated query, which can introduce noise in the localization process. To this end, this work aims to investigate the impact of implicit commonsensical knowledge, which humans innately possess, on zero-shot NLVL. We introduce CORONET, a zero-shot NLVL framework that utilizes commonsense information to bridge the gap between videos and generated pseudo-queries. Experiments on two benchmark datasets, containing diverse themes of videos, highlight the effectiveness of leveraging commonsense information.

Desde a última década, o tema aprendizagem organizacional tem recebido atenção de profissionais e pesquisadores. No entanto, a aprendizagem que ocorre nas organizações vai além da de natureza pragmática, que entende a aprendizagem a partir de modelos normativos somente com o intuito de gerar mudanças. Em contraponto a essa linha, existe, na literatura, a busca pela compreensão da aprendizagem como um processo, seja ele técnico ou social. Dentre outras, convém o uso da teoria da estética organizacional para a concepção da aprendizagem que emerge a partir das interações sociais. Esta teoria caracteriza-se por contestar o pensamento positivista-funcionalista e vai obtendo mais espaço, à medida que vem sendo aprofundada e empregada por pesquisadores, a fim de compreenderem os fenômenos organizacionais. Meu objetivo nesse estudo foi identificar e analisar, à luz da teoria da estética organizacional, os processos de aprendizagem, a partir das práticas de trabalho de profissionais que atuam em uma revenda de móveis planejados. Para isso, além de identificar e descrever as práticas de trabalho das funções organizacionais dos sujeitos pesquisados, também foi preciso identificar e analisar as dimensões referentes aos artefatos e à linguagem da cultura organizacional da revenda, assim como identificar e compreender as percepções estéticas dos profissionais atuantes em campo. Para a viabilidade da pesquisa, desenvolvi um estudo etnográfico, realizado entre os meses de fevereiro de 2011 e janeiro de 2012, em uma revenda de móveis planejados, situada em Porto Alegre (RS). De modo complementar, esclareço algumas noções importantes do ramo da arquitetura, principalmente de interiores, e de aspectos do ato de ‘habitar’. Após fazer referência às faculdades perceptivas dos sujeitos pesquisados e como estas permitem a realização dos juízos estéticos, esclareço como a estética organizacional pode ser compreendida como um critério de decisão e conexão. A partir das dinâmicas de relacionamentos e da contínua construção de um ‘espírito do lugar’, discuto como esses aspectos consentem à arquitetura dos processos de aprendizagem na organização pesquisada, ressaltando a ‘reflexividade estética’. / Since last decade, the theme organizational learning has received attention from professionals and researchers. However, the learning that occurs in the organizations goes beyond the one of pragmatic nature, what understands learning from the normative models only with the intention of generating changes. Counterpointing to this line, there is in literature the search for the learning comprehension as a process, being it technical or social. Among others, it is advisable the use of the theory of organizational esthetics for the learning conception that emerges from the social interactions. This theory is characterized for questioning the positive-functionalist thought and is obtaining more space, as it is being deepen and used by researchers, aiming to understand the organizational phenomena. My objective in this study was to identify and analyze the learning processes from the working practices of professionals who act in a planned furniture store by the theory of organizational esthetics. For that, beyond identifying and describing the working practices from the organizational functions of the researched individuals, it was also necessary to identify and analyze the dimensions referring to the artifacts and to the language of the organizational culture of resale, as well as the identification and comprehension of the esthetics perceptions of the professionals who were acting in the area. To the research feasibility I developed an ethnographic study, performed between the months of February 2011 and January 2012 at a planned furniture store, located in Porto Alegre (RS). To complement, I clarify some important notions in the field of architecture, mainly of interiors, and about the aspects of the act of ‘inhabiting’. After making reference to the perceptive faculties of the researched individuals and how they allow the realization of esthetical commonsense, I explain how the organizational esthetics can be understood as a criterion of decision and connection. Beyond that, from the dynamics of relationship and the continuous construction of a ‘spirit of the place’, I discuss how these aspects agree to the architecture of learning processes in the organization researched, highlighting the ‘esthetic reflexivity’.

abstract: Turing test has been a benchmark scale for measuring the human level intelligence in computers since it was proposed by Alan Turing in 1950. However, for last 60 years, the applications such as ELIZA, PARRY, Cleverbot and Eugene Goostman, that claimed to pass the test. These applications are either based on tricks to fool humans on a textual chat based test or there has been a disagreement between AI communities on them passing the test. This has led to the school of thought that it might not be the ideal test for predicting the human level intelligence in machines. Consequently, the Winograd Schema Challenge has been suggested as an alternative to the Turing test. As opposed to deciding the intelligent behavior with the help of chat servers, like it was done in the Turing test, the Winograd Schema Challenge is a question answering test. It consists of sentence and question pairs such that the answer to the question depends on the resolution of a definite pronoun or adjective in the sentence. The answers are fairly intuitive for humans but they are difficult for machines because it requires some sort of background or commonsense knowledge about the sentence. In this thesis, I propose a novel technique to solve the Winograd Schema Challenge. The technique has three basic modules at its disposal, namely, a Semantic Parser that parses the English text (both sentences and questions) into a formal representation, an Automatic Background Knowledge Extractor that extracts the Background Knowledge pertaining to the given Winograd sentence, and an Answer Set Programming Reasoning Engine that reasons on the given Winograd sentence and the corresponding Background Knowledge. The applicability of the technique is illustrated by solving a subset of Winograd Schema Challenge pertaining to a certain type of Background Knowledge. The technique is evaluated on the subset and a notable accuracy is achieved. / Dissertation/Thesis / Masters thesis defense presentation slides / Masters Thesis Computer Science 2014

Background The district nurse has a key role in caring and supporting patients with different kinds of health problems. A personcentered approach in the patient education facilitates for the patient to participate in self-care and management of the illness. Aim The aim of the study was to examine patients’ illness perceptions and management of their illness. Method Nine patients who has either hypertention, type 2 diabetes or chronic obstructive pulmonary disease were interviewed. The interviews were analyzed by qualitative content analysis with an inductive and deductive approach. Results The results were presented from Leventhal´s five dimensions in The Common Sense Model of Self-Regulation: identity, time-line, consequence, cause and control. The Participants´ describings were formulated into ten categories: the illness is present, mental image, cognitive coping, illness duration, daily impact, behavioral coping, thoughts about cause, coping strategy, meaning of the treatment and coping - seeking social support. Conclusion This study showed that there are different coping strategies to manage illness: The participants used distancing, accepting responsibility, planful problem solving, positive reappraisal and/or seeking social support

Desde a última década, o tema aprendizagem organizacional tem recebido atenção de profissionais e pesquisadores. No entanto, a aprendizagem que ocorre nas organizações vai além da de natureza pragmática, que entende a aprendizagem a partir de modelos normativos somente com o intuito de gerar mudanças. Em contraponto a essa linha, existe, na literatura, a busca pela compreensão da aprendizagem como um processo, seja ele técnico ou social. Dentre outras, convém o uso da teoria da estética organizacional para a concepção da aprendizagem que emerge a partir das interações sociais. Esta teoria caracteriza-se por contestar o pensamento positivista-funcionalista e vai obtendo mais espaço, à medida que vem sendo aprofundada e empregada por pesquisadores, a fim de compreenderem os fenômenos organizacionais. Meu objetivo nesse estudo foi identificar e analisar, à luz da teoria da estética organizacional, os processos de aprendizagem, a partir das práticas de trabalho de profissionais que atuam em uma revenda de móveis planejados. Para isso, além de identificar e descrever as práticas de trabalho das funções organizacionais dos sujeitos pesquisados, também foi preciso identificar e analisar as dimensões referentes aos artefatos e à linguagem da cultura organizacional da revenda, assim como identificar e compreender as percepções estéticas dos profissionais atuantes em campo. Para a viabilidade da pesquisa, desenvolvi um estudo etnográfico, realizado entre os meses de fevereiro de 2011 e janeiro de 2012, em uma revenda de móveis planejados, situada em Porto Alegre (RS). De modo complementar, esclareço algumas noções importantes do ramo da arquitetura, principalmente de interiores, e de aspectos do ato de ‘habitar’. Após fazer referência às faculdades perceptivas dos sujeitos pesquisados e como estas permitem a realização dos juízos estéticos, esclareço como a estética organizacional pode ser compreendida como um critério de decisão e conexão. A partir das dinâmicas de relacionamentos e da contínua construção de um ‘espírito do lugar’, discuto como esses aspectos consentem à arquitetura dos processos de aprendizagem na organização pesquisada, ressaltando a ‘reflexividade estética’. / Since last decade, the theme organizational learning has received attention from professionals and researchers. However, the learning that occurs in the organizations goes beyond the one of pragmatic nature, what understands learning from the normative models only with the intention of generating changes. Counterpointing to this line, there is in literature the search for the learning comprehension as a process, being it technical or social. Among others, it is advisable the use of the theory of organizational esthetics for the learning conception that emerges from the social interactions. This theory is characterized for questioning the positive-functionalist thought and is obtaining more space, as it is being deepen and used by researchers, aiming to understand the organizational phenomena. My objective in this study was to identify and analyze the learning processes from the working practices of professionals who act in a planned furniture store by the theory of organizational esthetics. For that, beyond identifying and describing the working practices from the organizational functions of the researched individuals, it was also necessary to identify and analyze the dimensions referring to the artifacts and to the language of the organizational culture of resale, as well as the identification and comprehension of the esthetics perceptions of the professionals who were acting in the area. To the research feasibility I developed an ethnographic study, performed between the months of February 2011 and January 2012 at a planned furniture store, located in Porto Alegre (RS). To complement, I clarify some important notions in the field of architecture, mainly of interiors, and about the aspects of the act of ‘inhabiting’. After making reference to the perceptive faculties of the researched individuals and how they allow the realization of esthetical commonsense, I explain how the organizational esthetics can be understood as a criterion of decision and connection. Beyond that, from the dynamics of relationship and the continuous construction of a ‘spirit of the place’, I discuss how these aspects agree to the architecture of learning processes in the organization researched, highlighting the ‘esthetic reflexivity’.