Bioética en experimentación animal

Treball presentat a l'assignatura de Deontologia i Veterinària Legal (21223

Elaboration of a Marketing Plan for the Food Industry

PòsterJun

La Web 2.0 en las bibliotecas nórdicas

Objective: The use of social networks and other communication technologies of the libraries of the Nordic countries was analyzed, in order to identify their level of use.Design/Methodology/Approach: We identified 579 library websites and documentation centers in Denmark, Finland, Sweden and Iceland. The scientific production on social networks in the libraries of these countries was searched for the purpose of analyzing the implementation of the main social networks on their websites.Results/Discussion: The majority of the Nordic libraries rely on social networks as a means of communication. The contents are disseminated through news, online courses, and reminders of the latest events in the library. The main social networks used are Facebook, Twitter, Instagram and YouTube. It was identified that the benefit of these social networks lies in the diffusion of information to users, who receive alerts on their mobile phones.Conclusions: The libraries of the Nordic countries have relied on Web 2.0 technologies to meet the needs of their users. They especially use social networks as a means of communication and dissemination of content, as well as a way to facilitate the online viewing of documents.Originality/Value: The large sample of libraries analyzed leads us to some well-founded conclusions. It highlights the important use of Web 2.0 technologies in these libraries to keep their users informed of the news. This commitment to online communication can serve as an example of good practices for libraries in other countries.Objetivo: Se analizó el uso de las redes sociales y otras tecnologías de comunicación de las bibliotecas de los países nórdicos, en vistas a identificar su nivel de uso.Diseño/Metodología/Enfoque: Se identificaron 579 sitios web de bibliotecas y centros de documentación de Dinamarca, Finlandia, Suecia e Islandia. Se buscó la producción científica sobre redes sociales en las bibliotecas de estos países, con la finalidad de analizar la implementación de las principales redes sociales en sus sitios web. Resultados/Discusión: La mayoría de las bibliotecas nórdicas se apoyan en las redes sociales como medio de comunicación. Los contenidos son difundidos mediante noticias, cursos en línea, y recordatorios de los últimos eventos de la biblioteca. Las principales redes sociales usadas son Facebook, Twitter, Instagram y YouTube. Se identificó que el beneficio de estas redes sociales radica en la emisión de información a los usuarios, los cuales reciben alertas en sus móviles.Conclusiones: Las bibliotecas de los países nórdicos se han apoyado en las tecnologías Web 2.0 para satisfacer las necesidades de sus usuarios. Especialmente usan las redes sociales como medio de comunicación y difusión de contenidos, así como vía para facilitar la visualización en línea de documentos.Originalidad/Valor: La amplia muestra de bibliotecas analizadas nos conduce a unas conclusiones fundamentadas. Se resalta el importante uso de las tecnologías Web 2.0 en estas bibliotecas para mantener a sus usuarios informados de las novedades. Esta apuesta por la comunicación en línea puede servir de ejemplo de buenas prácticas para las bibliotecas de otros países

Segmentation-Free Streaming Machine Translation

Streaming Machine Translation (MT) is the task of translating an unbounded input text stream in real-time. The traditional cascade approach, which combines an Automatic Speech Recognition (ASR) and an MT system, relies on an intermediate segmentation step which splits the transcription stream into sentence-like units. However, the incorporation of a hard segmentation constrains the MT system and is a source of errors. This paper proposes a Segmentation-Free framework that enables the model to translate an unsegmented source stream by delaying the segmentation decision until the translation has been generated. Extensive experiments show how the proposed Segmentation-Free framework has better quality-latency trade-off than competing approaches that use an independent segmentation model. Software, data and models will be released upon paper acceptance.Comment: 11 pages, 5 figure

Handwriting word recognition using windowed Bernoulli HMMs

[EN] Hidden Markov Models (HMMs) are now widely used for off-line handwriting recognition in many lan- guages. As in speech recognition, they are usually built from shared, embedded HMMs at symbol level, where state-conditional probability density functions in each HMM are modeled with Gaussian mixtures. In contrast to speech recognition, however, it is unclear which kind of features should be used and, indeed, very different features sets are in use today. Among them, we have recently proposed to directly use columns of raw, binary image pixels, which are directly fed into embedded Bernoulli (mixture) HMMs, that is, embedded HMMs in which the emission probabilities are modeled with Bernoulli mix- tures. The idea is to by-pass feature extraction and to ensure that no discriminative information is filtered out during feature extraction, which in some sense is integrated into the recognition model. In this work, column bit vectors are extended by means of a sliding window of adequate width to better capture image context at each horizontal position of the word image. Using these windowed Bernoulli mixture HMMs, good results are reported on the well-known IAM and RIMES databases of Latin script, and in particular, state-of-the-art results are provided on the IfN/ENIT database of Arabic handwritten words.Giménez Pastor, A.; Alkhoury, I.; Andrés Ferrer, J.; Juan Císcar, A. (2014). Handwriting word recognition using windowed Bernoulli HMMs. Pattern Recognition Letters. 35:149-156. doi:10.1016/j.patrec.2012.09.002S1491563

Comparison of Data Selection Techniques for the Translation of Video Lectures

[EN] For the task of online translation of scientific video lectures, using huge models is not possible. In order to get smaller and efficient models, we perform data selection. In this paper, we perform a qualitative and quantitative comparison of several data selection techniques, based on cross-entropy and infrequent n-gram criteria. In terms of BLEU, a combination of translation and language model cross-entropy achieves the most stable results. As another important criterion for measuring translation quality in our application, we identify the number of out-ofvocabulary words. Here, infrequent n-gram recovery shows superior performance. Finally, we combine the two selection techniques in order to benefit from both their strengths.The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no 287755 (transLectures), and the Spanish MINECO Active2Trans (TIN2012-31723) research project.Wuebker, J.; Ney, H.; Martínez-Villaronga, A.; Giménez Pastor, A.; Juan Císcar, A.; Servan, C.; Dymetman, M.... (2014). Comparison of Data Selection Techniques for the Translation of Video Lectures. Association for Machine Translation in the Americas. http://hdl.handle.net/10251/54431

Comparison of Data Selection Techniques for the Translation of Video Lectures

[EN] For the task of online translation of scientific video lectures, using huge models is not possible. In order to get smaller and efficient models, we perform data selection. In this paper, we perform a qualitative and quantitative comparison of several data selection techniques, based on cross-entropy and infrequent n-gram criteria. In terms of BLEU, a combination of translation and language model cross-entropy achieves the most stable results. As another important criterion for measuring translation quality in our application, we identify the number of out-ofvocabulary words. Here, infrequent n-gram recovery shows superior performance. Finally, we combine the two selection techniques in order to benefit from both their strengths.The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no 287755 (transLectures), and the Spanish MINECO Active2Trans (TIN2012-31723) research project.Wuebker, J.; Ney, H.; Martínez-Villaronga, A.; Giménez Pastor, A.; Juan Císcar, A.; Servan, C.; Dymetman, M.... (2014). Comparison of Data Selection Techniques for the Translation of Video Lectures. Association for Machine Translation in the Americas. http://hdl.handle.net/10251/54431