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Report without cover page Created by Zengjie Xia on 30/01/2018. Copyright © 2018 Zengjie Xia. All rights reserved.

Estudio de los procesos termodinámicos que conllevan una máquina de expreso. Se utiliza solo agua, sin el filtro de café para utilizar solo la densidad del agua. Se encuentra que es similar a un proceso de Carnot, pero como un ciclo abierto.

In the last few years the resolution of NLP tasks with architectures composed of neural models has taken vogue. There are many advantages to using these approaches especially because there is no need to do features engineering. In this paper, we make a survey of a Deep Learning architecture that propose a resolutive approach to some classical tasks of the NLP. The Deep Learning architecture is based on a cutting-edge model that exploits both word-level and character-level representations through the combination of bidirectional LSTM, CNN and CRF. This architecture has provided cutting-edge performance in several sequential labeling activities for the English language. The architecture that will be treated uses the same approach for the Italian language. The same guideline is extended to perform a multi-task learning involving PoS labeling and sentiment analysis. The results show that the system performs well and achieves good results in all activities. In some cases it exceeds the best systems previously developed for Italian.

This paper is describing a short view on the given case – You are in a modern national state where you have the democratic power to suggest/ put forward that “democracy and equality”, OR “democracy and freedom” are the highest values and norms in your society (the group chooses which of the two alternatives you want to answer on). What would your arguments and examples be to people of your country?

The entity registry system (ERS) is a decentralized entity registry that can be used to replace the Web as a platform for publishing linked data when the latter is not available. In developing countries, where off-line is the default mode of operation, centralized linked data solutions fail to address the needs of the communities. Although the features are mostly completed, the system is not yet ready for deployment. This project aims to provide extensive tests and scalability investigations that would make it ready for a real scenario.

Este artigo tem como objetivo relatar e detalhar a construção de um conversor buck-boost. Cuja a função deste é converter uma tensão cc (corrente contínua) de entrada, em outra tensão cc em sua saída, de valor mais elevado ou inferior dependendo de sua configuração. Destaca-se aqui o uso de um semi condutor MOSFET que funciona como uma chave controladora. Na elabiração deste está destacada o funcionamento, principais características e toda a parte de simulação e comprovação prática deste conversor.

Although the analysis of data is a task that has gained the interest of the statistical community in recent years and whose familiarity with the statistical computing environment, they encourage the current statistical community (to students and teachers of the area) to complete statistical analysis reproducible by means of the tool R. However for years there has been a gap between the calculation of matrices on a large scale and the term "big data", in this work the Normalized Cut algorithm for images is applied. Despite the expected, the R environment to do image analysis is poorly, in comparison with other computing platforms such as the Python language or with specialized software such as OpenCV. Being well known the absence of such function, in this work we share an implementation of the Normalized Cut algorithm in the R environment with extensions to programs and processes performed in C ++, to provide the user with a friendly interface in R to segment images. The article concludes by evaluating the current implementation and looking for ways to generalize the implementation for a large scale context and reuse the developed code. Key words: Normaliced Cut, image segmentation, Lanczos algorithm, eigenvalues and eigenvectors, graphs, similarity matrix, R (the statistical computing environment), open source, large scale and big data.

JERARQUIZACIÓN DE PRODUCTOS EN AMAZON

Transferencia de calor en intercambiadores depasos múltiples