960 resultados para Word Sense Disambguaion, WSD, Natural Language Processing
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This special issue is a testament to the recent burgeoning interest by theoretical linguists, language acquisitionists and teaching practitioners in the neuroscience of language. It offers a highly valuable, state-of-the-art overview of the neurophysiological methods that are currently being applied to questions in the field of second language (L2) acquisition, teaching and processing. Research in the area of neurolinguistics has developed dramatically in the past twenty years, providing a wealth of exciting findings, many of which are discussed in the papers in this volume. The goal of this commentary is twofold. The first is to critically assess the current state of neurolinguistic data from the point of view of language acquisition and processing—informed by the papers that comprise this special issue and the literature as a whole—pondering how the neuroscience of language/processing might inform us with respect to linguistic and language acquisition theories. The second goal is to offer some links from implications of exploring the first goal towards informing language teachers and the creation of linguistically and neurolinguistically-informed evidence-based pedagogies for non-native language teaching.
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Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two types of learning algorithms: cross-situational learning, in which the individuals determine the meaning of a word by looking for something in common across all observed uses of that word, and supervised operant conditioning learning, in which there is strong feedback between individuals about the intended meaning of the words. Despite the stark differences between these learning schemes, we show that they yield the same communication accuracy in the limits of large N and H, which coincides with the result of the classical occupancy problem of randomly assigning N objects to H words.
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Nowadays, where the market competition requires products with better quality and a constant search for cost savings and a better use of raw materials, the research for more efficient control strategies becomes vital. In Natural Gas Processin Units (NGPUs), as in the most chemical processes, the quality control is accomplished through their products composition. However, the chemical composition analysis has a long measurement time, even when performed by instruments such as gas chromatographs. This fact hinders the development of control strategies to provide a better process yield. The natural gas processing is one of the most important activities in the petroleum industry. The main economic product of a NGPU is the liquefied petroleum gas (LPG). The LPG is ideally composed by propane and butane, however, in practice, its composition has some contaminants, such as ethane and pentane. In this work is proposed an inferential system using neural networks to estimate the ethane and pentane mole fractions in LPG and the propane mole fraction in residual gas. The goal is to provide the values of these estimated variables in every minute using a single multilayer neural network, making it possibly to apply inferential control techniques in order to monitor the LPG quality and to reduce the propane loss in the process. To develop this work a NGPU was simulated in HYSYS R software, composed by two distillation collumns: deethanizer and debutanizer. The inference is performed through the process variables of the PID controllers present in the instrumentation of these columns. To reduce the complexity of the inferential neural network is used the statistical technique of principal component analysis to decrease the number of network inputs, thus forming a hybrid inferential system. It is also proposed in this work a simple strategy to correct the inferential system in real-time, based on measurements of the chromatographs which may exist in process under study
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Natural gas, although basically composed by light hydrocarbons, also presents in its composition gaseous contaminants such as CO2 (carbon dioxide) and H2S (hydrogen sulfide). Hydrogen sulfide, which commonly occurs in oil and gas exploration and production activities, besides being among the gases that are responsible by the acid rain and greenhouse effect, can also cause serious harm to health, leading even to death, and damages to oil and natural gas pipelines. Therefore, the removal of hydrogen sulfide will significantly reduce operational costs and will result in oil with best quality to be sent to refinery, thereby resulting in economical, environmental, and social benefits. These factors highlight the need for the development and improvement of hydrogen sulfide sequestrating agents to be used in the oil industry. Nowadays there are several procedures for hydrogen sulfide removal from natural gas used by the petroleum industry. However, they produce derivatives of amines that are harmful to the distillation towers, form insoluble precipitates that cause pipe clogging and produce wastes of high environmental impact. Therefore, the obtaining of a stable system, in inorganic or organic reaction media, that is able to remove hydrogen sulfide without forming by-products that affect the quality and costs of natural gas processing, transport and distribution is of great importance. In this context, the evaluation of the kinetics of H2S removal is a valuable procedure for the treatment of natural gas and disposal of the byproducts generated by the process. This evaluation was made in an absorption column packed with Raschig ring, where natural gas with H2S passes through a stagnant solution, being the contaminant absorbed by it. The content of H2S in natural gas in column output was monitored by an H2S analyzer. The comparison between the obtained curves and the study of the involved reactions have not only allowed to determine the efficiency and mass transfer controlling step of the involved processes but also make possible to effect a more detailed kinetic study and evaluate the commercial potential of each reagent
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During natural gas processing, water removal is considered as a fundamental step in that combination of hydrocarbons and water favors the formation of hydrates. The gas produced in the Potiguar Basin (Brazil) presents high water content (approximately 15000 ppm) and its dehydration is achieved via absorption and adsorption operations. This process is carried out at the Gas Treatment Unit (GTU) in Guamaré (GMR), in the State of Rio Grande do Norte. However, it is a costly process, which does not provide satisfactory results when water contents as low as 0.5 ppm are required as the exit of the GTU. In view of this, microemulsions research is regarded as an alternative to natural gas dehydration activities. Microemulsions can be used as desiccant fluids because of their unique proprieties, namely solubilization enhancement, reduction in interfacial tensions and large interfacial area between continuous and dispersed phases. These are actually important parameters to ensure the efficiency of an absorption column. In this work, the formulation of the desiccant fluid was determined via phases diagram construction, employing there nonionic surfactants (RDG 60, UNTL L60 and AMD 60) and a nonpolar fluid provided by Petrobras GMR (Brazil) typically comprising low-molecular weight liquid hydrocarbons ( a solvent commonly know as aguarrás ). From the array of phases diagrams built, four representative formulations have been selected for providing better results: 30% RDG 60-70% aguarrás; 15% RDG 60-15% AMD 60-70% aguarrás, 30% UNTL L60-70% aguarrás, 15% UNTL L60-15% AMD 60-70% aguarrás. Since commercial natural gas is already processed, and therefore dehydrated, it was necessary to moister some sample prior to all assays. It was then allowed to cool down to 13ºC and interacted with wet 8-12 mesh 4A molecular sieve, thus enabling the generation of gas samples with water content (approximately 15000 ppm). The determination of the equilibrium curves was performed based on the dynamic method, which stagnated liquid phase and gas phase at a flow rate of 200 mL min-1. The hydrodynamic study was done with the aim of established the pressure drop and dynamic liquid hold-up. This investigation allowed are to set the working flow rates at 840 mL min-1 for the gas phase and 600 mLmin-1 for the liquid phase. The mass transfer study indicated that the system formed by UNTL L60- turpentine-natural gas the highest value of NUT
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Natural gas, although basically composed by light hydrocarbons, also presents contaminant gases in its composition, such as CO2 (carbon dioxide) and H2S (hydrogen sulfide). The H2S, which commonly occurs in oil and gas exploration and production activities, causes damages in oil and natural gas pipelines. Consequently, the removal of hydrogen sulfide gas will result in an important reduction in operating costs. Also, it is essential to consider the better quality of the oil to be processed in the refinery, thus resulting in benefits in economic, environmental and social areas. All this facts demonstrate the need for the development and improvement in hydrogen sulfide scavengers. Currently, the oil industry uses several processes for hydrogen sulfide removal from natural gas. However, these processes produce amine derivatives which can cause damage in distillation towers, can cause clogging of pipelines by formation of insoluble precipitates, and also produce residues with great environmental impact. Therefore, it is of great importance the obtaining of a stable system, in inorganic or organic reaction media, able to remove hydrogen sulfide without formation of by-products that can affect the quality and cost of natural gas processing, transport, and distribution steps. Seeking the study, evaluation and modeling of mass transfer and kinetics of hydrogen removal, in this study it was used an absorption column packed with Raschig rings, where the natural gas, with H2S as contaminant, passed through an aqueous solution of inorganic compounds as stagnant liquid, being this contaminant gas absorbed by the liquid phase. This absorption column was coupled with a H2S detection system, with interface with a computer. The data and the model equations were solved by the least squares method, modified by Levemberg-Marquardt. In this study, in addition to the water, it were used the following solutions: sodium hydroxide, potassium permanganate, ferric chloride, copper sulfate, zinc chloride, potassium chromate, and manganese sulfate, all at low concentrations (»10 ppm). These solutions were used looking for the evaluation of the interference between absorption physical and chemical parameters, or even to get a better mass transfer coefficient, as in mixing reactors and absorption columns operating in counterflow. In this context, the evaluation of H2S removal arises as a valuable procedure for the treatment of natural gas and destination of process by-products. The study of the obtained absorption curves makes possible to determine the mass transfer predominant stage in the involved processes, the mass transfer volumetric coefficients, and the equilibrium concentrations. It was also performed a kinetic study. The obtained results showed that the H2S removal kinetics is greater for NaOH. Considering that the study was performed at low concentrations of chemical reagents, it was possible to check the effect of secondary reactions in the other chemicals, especially in the case of KMnO4, which shows that your by-product, MnO2, acts in H2S absorption process. In addition, CuSO4 and FeCl3 also demonstrated to have good efficiency in H2S removal
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The need for the representation of both semantics and common sense and its organization in a lexical database or knowledge base has motivated the development of large projects, such as Wordnets, CYC and Mikrokosmos. Besides the generic bases, another approach is the construction of ontologies for specific domains. Among the advantages of such approach there is the possibility of a greater and more detailed coverage of a specific domain and its terminology. Domain ontologies are important resources in several tasks related to the language processing, especially in those related to information retrieval and extraction in textual bases. Information retrieval or even question and answer systems can benefit from the domain knowledge represented in an ontology. Besides embracing the terminology of the field, the ontology makes the relationships among the terms explicit. Copyright 2007 ACM.
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Esta pesquisa teve como objetivo identificar e analisar quais as possíveis dificuldades advindas da linguagem que alunos enfrentam na conversão da língua natural para a linguagem matemática. A investigação foi realizada ao longo do ano letivo de 2008 em classes de Ensino Médio de duas escolas públicas da cidade de Belém, onde foram coletadas informações por meio de registros produzidos pelos alunos em testes e avaliações bimestrais. Para subsidiar a investigação foram utilizadas, como aporte teórico, idéias de Raymond Duval acerca da teoria dos registros de representação semiótica; o conceito de significado ligado a filosofia da linguagem segundo Wittgenstein; algumas considerações feitas por Gottlob Frege sobre a distinção entre sentido e referência assim como algumas idéias do filósofo Gilles-Gaston Granger no que concerne ao problema das significações e do aspecto formal da linguagem matemática. As análises das informações que foram coletadas no decorrer do processo investigativo revelaram que, na perspectiva dos alunos, a conversão da língua natural para a linguagem matemática se depara com quatro tipos de dificuldades: a primeira apontou para o fato de existirem em cada registro de representação de um mesmo objeto matemático, diferentes conteúdos a serem mobilizados; a segunda mostrou que os alunos fracassam ao realizar a conversão da língua natural para a linguagem matemática quando não interpretam corretamente as regras matemáticas implícitas no enunciado de uma situação problema; a terceira surgiu do fato de existirem no texto de uma situação problema, palavras que os alunos não compreendiam o seu significado ou que geravam ambigüidade de sentidos; a quarta surgiu a partir do fato dos alunos não conseguirem compreender o significado matemático das letras utilizadas nos enunciados dos problemas.
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Pós-graduação em Ciência da Informação - FFC
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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While the use of statistical physics methods to analyze large corpora has been useful to unveil many patterns in texts, no comprehensive investigation has been performed on the interdependence between syntactic and semantic factors. In this study we propose a framework for determining whether a text (e.g., written in an unknown alphabet) is compatible with a natural language and to which language it could belong. The approach is based on three types of statistical measurements, i.e. obtained from first-order statistics of word properties in a text, from the topology of complex networks representing texts, and from intermittency concepts where text is treated as a time series. Comparative experiments were performed with the New Testament in 15 different languages and with distinct books in English and Portuguese in order to quantify the dependency of the different measurements on the language and on the story being told in the book. The metrics found to be informative in distinguishing real texts from their shuffled versions include assortativity, degree and selectivity of words. As an illustration, we analyze an undeciphered medieval manuscript known as the Voynich Manuscript. We show that it is mostly compatible with natural languages and incompatible with random texts. We also obtain candidates for keywords of the Voynich Manuscript which could be helpful in the effort of deciphering it. Because we were able to identify statistical measurements that are more dependent on the syntax than on the semantics, the framework may also serve for text analysis in language-dependent applications.
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Data coming out from various researches carried out over the last years in Italy on the problem of school dispersion in secondary school show that difficulty in studying mathematics is one of the most frequent reasons of discomfort reported by students. Nevertheless, it is definitely unrealistic to think we can do without such knowledge in today society: mathematics is largely taught in secondary school and it is not confined within technical-scientific courses only. It is reasonable to say that, although students may choose academic courses that are, apparently, far away from mathematics, all students will have to come to terms, sooner or later in their life, with this subject. Among the reasons of discomfort given by the study of mathematics, some mention the very nature of this subject and in particular the complex symbolic language through which it is expressed. In fact, mathematics is a multimodal system composed by oral and written verbal texts, symbol expressions, such as formulae and equations, figures and graphs. For this, the study of mathematics represents a real challenge to those who suffer from dyslexia: this is a constitutional condition limiting people performances in relation to the activities of reading and writing and, in particular, to the study of mathematical contents. Here the difficulties in working with verbal and symbolic codes entail, in turn, difficulties in the comprehension of texts from which to deduce operations that, once combined together, would lead to the problem final solution. Information technologies may support this learning disorder effectively. However, these tools have some implementation limits, restricting their use in the study of scientific subjects. Vocal synthesis word processors are currently used to compensate difficulties in reading within the area of classical studies, but they are not used within the area of mathematics. This is because the vocal synthesis (or we should say the screen reader supporting it) is not able to interpret all that is not textual, such as symbols, images and graphs. The DISMATH software, which is the subject of this project, would allow dyslexic users to read technical-scientific documents with the help of a vocal synthesis, to understand the spatial structure of formulae and matrixes, to write documents with a technical-scientific content in a format that is compatible with main scientific editors. The system uses LaTex, a text mathematic language, as mediation system. It is set up as LaTex editor, whose graphic interface, in line with main commercial products, offers some additional specific functions with the capability to support the needs of users who are not able to manage verbal and symbolic codes on their own. LaTex is translated in real time into a standard symbolic language and it is read by vocal synthesis in natural language, in order to increase, through the bimodal representation, the ability to process information. The understanding of the mathematic formula through its reading is made possible by the deconstruction of the formula itself and its “tree” representation, so allowing to identify the logical elements composing it. Users, even without knowing LaTex language, are able to write whatever scientific document they need: in fact the symbolic elements are recalled by proper menus and automatically translated by the software managing the correct syntax. The final aim of the project, therefore, is to implement an editor enabling dyslexic people (but not only them) to manage mathematic formulae effectively, through the integration of different software tools, so allowing a better teacher/learner interaction too.
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The general aim of the thesis was to investigate how and to what extent the characteristics of action organization are reflected in language, and how they influence language processing and understanding. Even though a huge amount of research has been devoted to the study of the motor effects of language, this issue is very debated in literature. Namely, the majority of the studies have focused on low-level motor effects such as effector-relatedness of action, whereas only a few studies have started to systematically investigate how specific aspects of action organization are encoded and reflected in language. After a review of previous studies on the relationship between language comprehension and action (chapter 1) and a critical discussion of some of them (chapter 2), the thesis is composed by three experimental chapters, each devoted to a specific aspect of action organization. Chapter 3 presents a study designed with the aim to disentangle the effective time course of the involvement of the motor system during language processing. Three kinematics experiments were designed in order to determine whether and, at which stage of motor planning and execution effector-related action verbs influence actions executed with either the same or a different effector. Results demonstrate that the goal of an action can be linguistically re-activated, producing a modulation of the motor response. In chapter 4, a second study investigates the interplay between the role of motor perspective (agent) and the organization of action in motor chains. More specifically, this kinematics study aims at deepening how goal can be translated in language, using as stimuli simple sentences composed by a pronoun (I, You, He/She) and a verb. Results showed that the perspective activated by the pronoun You reflects the motor pattern of the “agent” combined with the chain structure of the verb. These data confirm an early involvement of the motor system in language processing, suggesting that it is specifically modulated by the activation of the agent’s perspective. In chapter 5, the issue of perspective is specifically investigated, focusing on its role in language comprehension. In particular, this study aimed at determining how a specific perspective (induced for example by a personal pronoun) modulates motor behaviour during and after language processing. A classical compatibility effect (the Action-sentence compatibility effect) has been used to this aim. In three behavioural experiments the authors investigated how the ACE is modulated by taking first or third person perspective. Results from these experiments showed that the ACE effect occurs only when a first-person perspective is activated by the sentences used as stimuli. Overall, the data from this thesis contributed to disentangle several aspects of how action organization is translated in language, and then reactivated during language processing. This constitutes a new contribution to the field, adding lacking information on how specific aspects such as goal and perspective are linguistically described. In addition, these studies offer a new point of view to understand the functional implications of the involvement of the motor system during language comprehension, specifically from the point of view of our social interactions.
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We examined aesthetic preference for reproductions of paintings among frontotemporal dementia (FTD) patients, in two sessions separated by 2 weeks. The artworks were in three different styles: representational, quasirepresentational, and abstract. Stability of preference for the paintings was equivalent to that shown by a matched group of Alzheimer's disease patients and a group of healthy controls drawn from an earlier study. We expected that preference for representational art would be affected by disruptions in language processes in the FTD group. However, this was not the case and the FTD patients, despite severe language processing deficits, performed similarly across all three art styles. These data show that FTD patients maintain a sense of aesthetic appraisal despite cognitive impairment and should be amenable to therapies and enrichment activities involving art.