Gramáticas emocionais em trajetórias de engajamento no campo de direitos sexuais: compaixão e vitimização a partir de narrativas biográficas de intelectuais brasileiros

Esta tese analisa narrativas de trajetórias acadêmico-profissionais a partir de um banco de entrevistas com atores de destaque no campo intelectual latino-americano de direitos sexuais. Foi feito um recorte privilegiando os atores brasileiros, buscando compreender que gramática emotiva informa o discurso sobre a motivação no engajamento político e intelectual em temas ligados ao gênero e à sexualidade. Os conceitos de violência e compaixão emergem, na análise, como importantes noções que ajudam a explicar o engajamento nesses temas. O aporte teórico utilizado é o da bibliografia da antropologia das emoções, na qual se destacam os referenciais analíticos que discutem o papel das emoções em movimentos sociais. Este referencial é utilizado para pensar as narrativas, com foco na relação discursiva entre a emoção e escolhas profissionais nestas carreiras interseccionadas tanto por estudos temáticos em direitos sexuais, quanto pela interlocução com movimentos sociais em diálogo com estes temas. O objetivo é investir em uma análise discursiva focando na gramática emocional das narrativas sobre o engajamento nas temáticas da política, dos direitos sexuais e das questões de gênero e sexualidade, com ênfase nas articulações entre engajamento intelectual e engajamento político.

Teoria, proposta e aplicação de uma sequência didática em Educação Linguística: trabalhando os conceitos de língua, gramáticas e normas linguísticas no nono ano do Ensino Fundamental

O ensino-aprendizagem da disciplina Língua Portuguesa se apresenta como um desafio para professores e alunos; muito disso se deve à falta de reconhecimento da diversidade linguística (LIMA, 2014). Há uma tendência no ambiente escolar em se valorizar apenas uma norma linguística, ignorando as diferentes normas que fazem parte do convívio em sociedade. Com isso, os discentes entram em conflito, pois aquilo que é apresentado para eles como a Língua Portuguesa está bem distante da sua experiência pessoal com a língua. Em via de eliminar esse conflito, os PCNs e o PNLD estabelecem a inserção do tema variação linguística no conteúdo programático da disciplina Língua Portuguesa. Entretanto, ainda perdura uma lacuna no tratamento desse tema. A preocupação em preencher essa lacuna motivou este trabalho, que teve como objetivo principal propor e aplicar uma sequência didática que abordasse os seguintes temas: língua, gramáticas e normas linguísticas, a fim de contribuir com a realização de uma Educação Linguística eficaz (BAGNO; RANGEL, 2005). Esses três conteúdos principais geraram desdobramentos que proporcionaram a discussão dos seguintes tópicos: variação e preconceito linguísticos. A sequência didática elaborada é composta por oito etapas em que são intercalados momentos de aula expositiva e de atividades lúdicas. A aplicação da proposta de sequência didática ocorreu em uma turma de nono ano do Ensino Fundamental de um CIEP (Centro Integrado de Educação Pública) localizado na Zona Oeste da cidade do Rio de Janeiro. As ferramentas utilizadas para identificar os conteúdos assimilados pelos alunos foram a avaliação da participação da turma e os resultados de quatro atividades específicas. Considerando a complexidade e o ineditismo dos conceitos apresentados na sequência didática, o desempenho da classe foi satisfatório. Os alunos também responderam a dois questionários, um no início da sequência e outro ao final, que tinham o propósito de avaliar se houve mudança com relação ao entendimento da existência de variação linguística e do preconceito linguístico. O primeiro questionário revelou que a maioria dos alunos já havia sofrido e praticado preconceito linguístico; já o segundo mostrou que a maioria dos discentes assimilou a noção de preconceito linguístico e rompeu com a ideia de certo e errado na língua. Como objetivo secundário, este trabalho intentou deixar um legado para professores, pois com esta dissertação a ação não ficará limitada apenas ao nono ano daquele CIEP, mas poderá contribuir com o ensino linguístico de diversas escolas; e para pesquisadores, pois este registro descreve um modelo de trabalho acadêmico em que se pretendeu aplicar o princípio de indissociabilidade entre ensino, pesquisa e extensão. A expectativa é que, somados a trabalhos similares, seja possível abrir um precedente de trabalhos acadêmicos fundamentados teoricamente e desenvolvidos de forma prática, além de realizados com preocupações sociais e educacionais

Inference approach to grammar construction

A system of computer assisted grammar construction (CAGC) is presented in this paper. The CAGC system is designed to generate broad-coverage grammars for large natural language corpora by utilizing both an extended inside-outside algorithm and an automatic phrase bracketing (AUTO) system which is designed to provide the extended algorithm with constituent information during learning. This paper demonstrates the capability of the CAGC system to deal with realistic natural language problems and the usefulness of the AUTO system for constraining the inside-outside based grammar re-estimation. Performance results, including coverage, recall and precision, are presented for a grammar constructed for the Wall Street Journal (WSJ) corpus using the Penn Treebank.

Discriminative spoken language understanding using word confusion networks

Current commercial dialogue systems typically use hand-crafted grammars for Spoken Language Understanding (SLU) operating on the top one or two hypotheses output by the speech recogniser. These systems are expensive to develop and they suffer from significant degradation in performance when faced with recognition errors. This paper presents a robust method for SLU based on features extracted from the full posterior distribution of recognition hypotheses encoded in the form of word confusion networks. Following [1], the system uses SVM classifiers operating on n-gram features, trained on unaligned input/output pairs. Performance is evaluated on both an off-line corpus and on-line in a live user trial. It is shown that a statistical discriminative approach to SLU operating on the full posterior ASR output distribution can substantially improve performance both in terms of accuracy and overall dialogue reward. Furthermore, additional gains can be obtained by incorporating features from the previous system output. © 2012 IEEE.

basic research in computer science and software engineering at sklcs

The State Key Laboratory of Computer Science (SKLCS) is committed to basic research in computer science and software engineering. The research topics of the laboratory include: concurrency theory, theory and algorithms for real-time systems, formal specifications based on context-free grammars, semantics of programming languages, model checking, automated reasoning, logic programming, software testing, software process improvement, middleware technology, parallel algorithms and parallel software, computer graphics and human-computer interaction. This paper describes these topics in some detail and summarizes some results obtained in recent years.

使用概率规则文法评估人机界面可用性

提出一种在界面系统设计规约的基础上使用的可用性评估方法.首先使用有限状态自动机抽象界面系统设计,根据概率规则文法对有限状态自动机的状态转换概率进行预测;然后结合用户的熟练程度提出了界面可用性评估算法;最后讨论了一个手机界面的可用性计算实例.文中方法能够在界面系统生命周期的早期使用,以较早地对不同设计方案进行比较,降低开发风险.

data transformation and attribute subset selection: do they help make differences in software failure prediction?

IEEE, IEEE Comp Soc, Tech Council Software Engn

获取无意识结构知识的机制:主观熟悉感与刺激重复结构在人工语法学习中的作用

The nature of the distinction between conscious and unconscious knowledge is a core issue in the implicit learning field. Furthermore, the phenomenological experience associated with having knowledge is central to the conscious or unconscious status of that knowledge. Consistently, Dienes and Scott (2005) measured the conscious or unconscious status of structure knowledge using subjective measures. Believing that one is purely guessing when in fact one knows indicates unconscious knowledge. But unconscious structural knowledge can also be associated with feelings of intuition or familiarity. In this thesis, we explored whether phenomenological feelings, like familiarity, associated with unconscious structural knowledge could be used, paradoxically, to exert conscious control over the use of the knowledge, and whether people could obtain repetition structure knowledge. We also investigated the neural correlates of awareness of knowing, as measured phenomenologically. In study one, subjects were trained on two grammars and then asked to endorse strings from only one of the grammars. Subjects also rated how familiar each string they felt and reported whether or not they used familiarity to make their grammaticality judgment. We found subjects could endorse the strings of just one grammar and ignore the strings from the other. Importantly, when subjects said they were using familiarity, the rated familiarity for test strings consistent with their chosen grammar was greater than that for strings from the other grammar. Familiarity, subjectively defined, is sensitive to intentions and can play a key role in strategic control. In study two, we manipulated the structural characteristic of stings and explored whether participants could learn repetition structures in the grammatical strings. We measured phenomenology again and also ERPs. Deviant letters of ungrammatical strings violating the repetition structure elicited the N2 component; we took this to be an indication of knowledge, whether conscious or not. Strings which were attributed to conscious categories (rules and recollection) rather than phenomenology associated with unconscious structural knowledge (guessing, intuition and familiarity) elicited the P300 component. Different waveforms provided evidence for the neural correlates of different phenomenologies associated with knowledge of an artificial grammar.

Principles, Opportunism and Seeing in Design: A Computational Approach

This thesis introduces elements of a theory of design activity and a computational framework for developing design systems. The theory stresses the opportunistic nature of designing and the complementary roles of focus and distraction, the interdependence of evaluation and generation, the multiplicity of ways of seeing over the history of a design session versus the exclusivity of a given way of seeing over an arbitrarily short period, and the incommensurability of criteria used to evaluate a design. The thesis argues for a principle based rather than rule based approach to designing documents. The Discursive Generator is presented as a computational framework for implementing specific design systems, and a simple system for arranging blocks according to a set of formal principles is developed by way of illustration. Both shape grammars and constraint based systems are used to contrast current trends in design automation with the discursive approach advocated in the thesis. The Discursive Generator is shown to have some important properties lacking in other types of systems, such as dynamism, robustness and the ability to deal with partial designs. When studied in terms of a search metaphor, the Discursive Generator is shown to exhibit behavior which is radically different from some traditional search techniques, and to avoid some of the well-known difficulties associated with them.

Formalizing Triggers: A Learning Model for Finite Spaces

In a recent seminal paper, Gibson and Wexler (1993) take important steps to formalizing the notion of language learning in a (finite) space whose grammars are characterized by a finite number of parameters. They introduce the Triggering Learning Algorithm (TLA) and show that even in finite space convergence may be a problem due to local maxima. In this paper we explicitly formalize learning in finite parameter space as a Markov structure whose states are parameter settings. We show that this captures the dynamics of TLA completely and allows us to explicitly compute the rates of convergence for TLA and other variants of TLA e.g. random walk. Also included in the paper are a corrected version of GW's central convergence proof, a list of "problem states" in addition to local maxima, and batch and PAC-style learning bounds for the model.

A Note of Zipf's Law, Natural Languages, and Noncoding DNA Regions

In Phys. Rev. Letters (73:2), Mantegna et al. conclude on the basis of Zipf rank frequency data that noncoding DNA sequence regions are more like natural languages than coding regions. We argue on the contrary that an empirical fit to Zipf"s "law" cannot be used as a criterion for similarity to natural languages. Although DNA is a presumably "organized system of signs" in Mandelbrot"s (1961) sense, and observation of statistical featurs of the sort presented in the Mantegna et al. paper does not shed light on the similarity between DNA's "gramar" and natural language grammars, just as the observation of exact Zipf-like behavior cannot distinguish between the underlying processes of tossing an M-sided die or a finite-state branching process.

Learning by Failing to Explain

Explanation-based Generalization requires that the learner obtain an explanation of why a precedent exemplifies a concept. It is, therefore, useless if the system fails to find this explanation. However, it is not necessary to give up and resort to purely empirical generalization methods. In fact, the system may already know almost everything it needs to explain the precedent. Learning by Failing to Explain is a method which is able to exploit current knowledge to prune complex precedents, isolating the mysterious parts of the precedent. The idea has two parts: the notion of partially analyzing a precedent to get rid of the parts which are already explainable, and the notion of re-analyzing old rules in terms of new ones, so that more general rules are obtained.

Automated Program Recognition

The key to understanding a program is recognizing familiar algorithmic fragments and data structures in it. Automating this recognition process will make it easier to perform many tasks which require program understanding, e.g., maintenance, modification, and debugging. This report describes a recognition system, called the Recognizer, which automatically identifies occurrences of stereotyped computational fragments and data structures in programs. The Recognizer is able to identify these familiar fragments and structures, even though they may be expressed in a wide range of syntactic forms. It does so systematically and efficiently by using a parsing technique. Two important advances have made this possible. The first is a language-independent graphical representation for programs and programming structures which canonicalizes many syntactic features of programs. The second is an efficient graph parsing algorithm.

An Algorithm for Parsing Flow Graphs

This report describes research about flow graphs - labeled, directed, acyclic graphs which abstract representations used in a variety of Artificial Intelligence applications. Flow graphs may be derived from flow grammars much as strings may be derived from string grammars; this derivation process forms a useful model for the stepwise refinement processes used in programming and other engineering domains. The central result of this report is a parsing algorithm for flow graphs. Given a flow grammar and a flow graph, the algorithm determines whether the grammar generates the graph and, if so, finds all possible derivations for it. The author has implemented the algorithm in LISP. The intent of this report is to make flow-graph parsing available as an analytic tool for researchers in Artificial Intelligence. The report explores the intuitions behind the parsing algorithm, contains numerous, extensive examples of its behavior, and provides some guidance for those who wish to customize the algorithm to their own uses.