48 research outputs found

    A Comparison of Different Machine Transliteration Models

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    Machine transliteration is a method for automatically converting words in one language into phonetically equivalent ones in another language. Machine transliteration plays an important role in natural language applications such as information retrieval and machine translation, especially for handling proper nouns and technical terms. Four machine transliteration models -- grapheme-based transliteration model, phoneme-based transliteration model, hybrid transliteration model, and correspondence-based transliteration model -- have been proposed by several researchers. To date, however, there has been little research on a framework in which multiple transliteration models can operate simultaneously. Furthermore, there has been no comparison of the four models within the same framework and using the same data. We addressed these problems by 1) modeling the four models within the same framework, 2) comparing them under the same conditions, and 3) developing a way to improve machine transliteration through this comparison. Our comparison showed that the hybrid and correspondence-based models were the most effective and that the four models can be used in a complementary manner to improve machine transliteration performance

    Propuesta de modelo de negocio de un food truck de venta de desayunos en una universidad privada de Chiclayo, 2016

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    El presente trabajo tiene como objetivo establecer un modelo de negocio para un food truck de desayunos en una universidad privada de Chiclayo. La metodología aplicada para la investigación es cualitativa – exploratoria, se fundamenta en un proceso inductivo (explorar, describir y luego generar perspectivas teóricas), es decir va de lo particular a lo general; esta metodología permite obtener información en base a entrevistas realizadas a la comunidad universitaria. La investigación busca conocer la aceptación del modelo de food truck de venta de desayuno, se basó en el modelo Lean Canvas, desarrollado en el libro Running Lean de Ash Maurya, nos da un enfoque de nueve (9) dimensiones para tener en cuenta y poder lograr un modelo de negocio de éxito. La propuesta de valor obtenida, consiste en vender productos saludables que les ayude a promover la calidad y bienestar de la salud de nuestros clientes, por ello se ofrecerán desayunos elaborados a base de frutas, cereales andinos y sándwich preparados al instante, ofrecidos en unos envases biodegradables, cumpliendo con los estándares de salubridad. Asimismo se tendrá variedad en los productos a ofrecer, para que el cliente pueda escoger y se brindará una atención rápida y personalizada con la finalidad de cumplir con uno de los aspectos que los clientes valoran.Tesi

    Discovering the Language of Wine Reviews: A Text Mining Account

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    It is widely held that smells and flavors are impossible to put into words. In this paper we test this claim by seeking predictive patterns in wine reviews, which ostensibly aim to provide guides to perceptual content. Wine reviews have previously been critiqued as random and meaningless. We collected an English corpus of wine reviews with their structured metadata, and applied machine learning techniques to automatically predict the winetextquotesingles color, grape variety, and country of origin. To train the three supervised classifiers, three different information sources were incorporated: lexical bag-of-words features, domain-specific terminology features, and semantic word embedding features. In addition, using regression analysis we investigated basic review properties, i.e., review length, average word length, and their relationship to the scalar values of price and review score. Our results show that wine experts do share a common vocabulary to describe wines and they use this in a consistent way, which makes it possible to automatically predict wine characteristics based on the review text alone. This means that odors and flavors may be more expressible in language than typically acknowledged

    Autophagy–physiology and pathophysiology

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    “Autophagy” is a highly conserved pathway for degradation, by which wasted intracellular macromolecules are delivered to lysosomes, where they are degraded into biologically active monomers such as amino acids that are subsequently re-used to maintain cellular metabolic turnover and homeostasis. Recent genetic studies have shown that mice lacking an autophagy-related gene (Atg5 or Atg7) cannot survive longer than 12 h after birth because of nutrient shortage. Moreover, tissue-specific impairment of autophagy in central nervous system tissue causes massive loss of neurons, resulting in neurodegeneration, while impaired autophagy in liver tissue causes accumulation of wasted organelles, leading to hepatomegaly. Although autophagy generally prevents cell death, our recent study using conditional Atg7-deficient mice in CNS tissue has demonstrated the presence of autophagic neuron death in the hippocampus after neonatal hypoxic/ischemic brain injury. Thus, recent genetic studies have shown that autophagy is involved in various cellular functions. In this review, we introduce physiological and pathophysiological roles of autophagy

    TRANSLATION BETWEEN LINGUISTIC STRUCTURES AND SHAPE STRUCTURES FOR BIDIRECTIONAL DESIGN

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    In upstream design, we generate a blueprint as a preparatory step in deciding on the concept of shape [Pahl and Beitz, 1988]. This process is important in forming the whole design object. When we construct a shape image, a negotiation occurs between the linguistic world and the shape world. Tomes et al. concluded, according to the results of an interview with an experienced designer, that suc
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