1000 resultados para Breton language
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Background The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes. Results In this paper, the DL method is used to analyze the whole-proteome phylogeny of 124 large dsDNA viruses and 30 parvoviruses, two data sets with large difference in genome size. The trees from our analyses are in good agreement to the latest classification of large dsDNA viruses and parvoviruses by the International Committee on Taxonomy of Viruses (ICTV). Conclusions The present method provides a new way for recovering the phylogeny of large dsDNA viruses and parvoviruses, and also some insights on the affiliation of a number of unclassified viruses. In comparison, some alignment-free methods such as the CV Tree method can be used for recovering the phylogeny of large dsDNA viruses, but they are not suitable for resolving the phylogeny of parvoviruses with a much smaller genome size.
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When we attempt to speak about the relationship between language, literacy, and the brain, we find ourselves ill equipped to deal with these conceptually and qualitatively different phenomena. Immediately we must straddle different academic traditions that treat each of these as separate “things”. Broadly speaking, the study of language firstly belongs to the domain of biology, then to anthropology, sociology, and linguistics. At its most functional, a study of literacy education is a study of a particular technology, its diffusion techniques, and the abilities and motivations of people to adopt, or adapt themselves to, this technology. The brain is most commonly studied in the field of neurology, which is also a sub-discipline of biology, biochemistry, and medicine.
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The advent of e-learning has seen the adaptation and use of a plethora of educational techniques. Of these, online discussion forums have met with success and been used widely in both undergraduate and postgraduate education. The authors of this paper, having previously used online discussion forums in the postgraduate arena with success, adopted this approach for the design and subsequent delivery of a learning and teaching subject. This learning and teaching subject, however, was part of an international collaboration and designed for nurse academics in another country – Vietnam. With the nursing curriculum in Vietnam currently moving to adopt a competency based approach, two learning and teaching subjects were designed by an Australian university for Vietnamese nurse academics. Subject materials constituted a DVD which arrived by post and access to an online platform. Assessment for the subject included (but was not limited to) mandatory participation in online discussion with the other nurse academics enrolled in the subject. The purpose behind the online discussion was to generate discourse between the Vietnamese nurse academics located across Vietnam. Consequently the online discussions occurred in both Vietnamese and English; the Australian academic moderating the discussion did so in Australia with a Vietnamese translator. For the Australian University delivering this subject the difference between this and past online discussions were twofold: delivery was in a foreign language; and the teaching experience of the Vietnamese nurse teachers was mixed and frequently very limited. This paper will provide a discussion addressing the design of an online learning environment for foreign correspondents, the resources and translation required to maximise the success of the online discussion, the lessons learnt and consequent changes made, as well as the rationale of delivering complex content in a foreign language. While specifically addressing the first iteration of the first learning module designed, this paper will also address subsequent changes made for the second iteration of the first module and comment on their success. While a translator is clearly a key component of success, the elements of simplicity and clarity in hand with supportive online moderation must not be overlooked.
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Thirty-five years ago, a landmark article entitled 'What The "Good Language Learner" Can Teach Us' suggested that if more was known about what 'successful learners' did, then those strategies could be taught to poorer learners to enhance learning (Rubin, 1975, p. 42). Since publication of Rubin's article, language instruction has begun to encompass technological applications (Chinnery, 2006) through mobile-assisted language learning (MALL or m-learning) like podcasts. Podcasting extends the classroom, offers convenience for diverse learners, and provides authentic listening opportunities. Although the effects of podcasting in higher education have yet to be investigated (Educause, 2007), this article describes how action research lead to the creation of a student learning strategy webpage featuring peer podcasts and successful language learning strategies in higher education.
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Despite many incidents about fake online consumer reviews have been reported, very few studies have been conducted to date to examine the trustworthiness of online consumer reviews. One of the reasons is the lack of an effective computational method to separate the untruthful reviews (i.e., spam) from the legitimate ones (i.e., ham) given the fact that prominent spam features are often missing in online reviews. The main contribution of our research work is the development of a novel review spam detection method which is underpinned by an unsupervised inferential language modeling framework. Another contribution of this work is the development of a high-order concept association mining method which provides the essential term association knowledge to bootstrap the performance for untruthful review detection. Our experimental results confirm that the proposed inferential language model equipped with high-order concept association knowledge is effective in untruthful review detection when compared with other baseline methods.
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In response to concerns about the quality of English Language Learning (ELL) education at tertiary level, the Chinese Ministry of Education (CMoE) launched the College English Reform Program (CERP) in 2004. By means of a press release (CMoE, 2005) and a guideline document titled College English Curriculum Requirements (CECR) (CMoE, 2007), the CERP proposed two major changes to the College English assessment policy, which were: (1) the shift to optional status for the compulsory external test, the College English Test Band 4 (CET4); and (2) the incorporation of formative assessment into the existing summative assessment framework. This study investigated the interactions between the College English assessment policy change, the theoretical underpinnings, and the assessment practices within two Chinese universities (one Key University and one Non-Key University). It adopted a sociocultural theoretical perspective to examine the implementation process as experienced by local actors of institutional and classroom levels. Systematic data analysis using a constant comparative method (Merriam, 1998) revealed that contextual factors and implementation issues did not lead to significant differences in the two cases. Lack of training in assessment and the sociocultural factors such as the traditional emphasis on the product of learning and hierarchical teacher/students relationship are decisive and responsible for the limited effect of the reform.
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Concerns raised in educational reports about school science in terms of students. outcomes and attitudes, as well as science teaching practices prompted investigation into science learning and teaching practices at the foundational level of school science. Without science content and process knowledge, understanding issues of modern society and active participation in decision-making is difficult. This study contended that a focus on the development of the language of science could enable learners to engage more effectively in learning science and enhance their interest and attitudes towards science. Furthermore, it argued that explicit teaching practices where science language is modelled and scaffolded would facilitate the learning of science by young children at the beginning of their formal schooling. This study aimed to investigate science language development at the foundational level of school science learning in the preparatory-school with students aged five and six years. It focussed on the language of science and science teaching practices in early childhood. In particular, the study focussed on the capacity for young students to engage with and understand science language. Previous research suggests that students have difficulty with the language of science most likely because of the complexities and ambiguities of science language. Furthermore, literature indicates that tensions transpire between traditional science teaching practices and accepted early childhood teaching practices. This contention prompted investigation into means and models of pedagogy for learning foundational science language, knowledge and processes in early childhood. This study was positioned within qualitative assumptions of research and reported via descriptive case study. It was located in a preparatory-school classroom with the class teacher, teacher-aide, and nineteen students aged four and five years who participated with the researcher in the study. Basil Bernstein.s pedagogical theory coupled with Halliday.s Systemic Functional Linguistics (SFL) framed an examination of science pedagogical practices for early childhood science learning. Students. science learning outcomes were gauged by focussing a Hallydayan lens on their oral and reflective language during 12 science-focussed episodes of teaching. Data were collected throughout the 12 episodes. Data included video and audio-taped science activities, student artefacts, journal and anecdotal records, semi-structured interviews and photographs. Data were analysed according to Bernstein.s visible and invisible pedagogies and performance and competence models. Additionally, Halliday.s SFL provided the resource to examine teacher and student language to determine teacher/student interpersonal relationships as well as specialised science and everyday language used in teacher and student science talk. Their analysis established the socio-linguistic characteristics that promoted science competencies in young children. An analysis of the data identified those teaching practices that facilitate young children.s acquisition of science meanings. Positive indications for modelling science language and science text types to young children have emerged. Teaching within the studied setting diverged from perceived notions of common early childhood practices and the benefits of dynamic shifting pedagogies were validated. Significantly, young students demonstrated use of particular specialised components of school-science language in terms of science language features and vocabulary. As well, their use of language demonstrated the students. knowledge of science concepts, processes and text types. The young students made sense of science phenomena through their incorporation of a variety of science language and text-types in explanations during both teacher-directed and independent situations. The study informs early childhood science practices as well as practices for foundational school science teaching and learning. It has exposed implications for science education policy, curriculum and practices. It supports other findings in relation to the capabilities of young students. The study contributes to Systemic Functional Linguistic theory through the development of a specific resource to determine the technicality of teacher language used in teaching young students. Furthermore, the study contributes to methodology practices relating to Bernsteinian theoretical perspectives and has demonstrated new ways of depicting and reporting teaching practices. It provides an analytical tool which couples Bernsteinian and Hallidayan theoretical perspectives. Ultimately, it defines directions for further research in terms of foundation science language learning, ongoing learning of the language of science and learning science, science teaching and learning practices, specifically in foundational school science, and relationships between home and school science language experiences.
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The Wikipedia has become the most popular online source of encyclopedic information. The English Wikipedia collection, as well as some other languages collections, is extensively linked. However, as a multilingual collection the Wikipedia is only very weakly linked. There are few cross-language links or cross-dialect links (see, for example, Chinese dialects). In order to link the multilingual-Wikipedia as a single collection, automated cross language link discovery systems are needed – systems that identify anchor-texts in one language and targets in another. The evaluation of Link Discovery approaches within the English version of the Wikipedia has been examined in the INEX Link the-Wiki track since 2007, whilst both CLEF and NTCIR emphasized the investigation and the evaluation of cross-language information retrieval. In this position paper we propose a new virtual evaluation track: Cross Language Link Discovery (CLLD). The track will initially examine cross language linking of Wikipedia articles. This virtual track will not be tied to any one forum; instead we hope it can be connected to each of (at least): CLEF, NTCIR, and INEX as it will cover ground currently studied by each. The aim is to establish a virtual evaluation environment supporting continuous assessment and evaluation, and a forum for the exchange of research ideas. It will be free from the difficulties of scheduling and synchronizing groups of collaborating researchers and alleviate the necessity to travel across the globe in order to share knowledge. We aim to electronically publish peer-reviewed publications arising from CLLD in a similar fashion: online, with open access, and without fixed submission deadlines.
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Language Modeling (LM) has been successfully applied to Information Retrieval (IR). However, most of the existing LM approaches only rely on term occurrences in documents, queries and document collections. In traditional unigram based models, terms (or words) are usually considered to be independent. In some recent studies, dependence models have been proposed to incorporate term relationships into LM, so that links can be created between words in the same sentence, and term relationships (e.g. synonymy) can be used to expand the document model. In this study, we further extend this family of dependence models in the following two ways: (1) Term relationships are used to expand query model instead of document model, so that query expansion process can be naturally implemented; (2) We exploit more sophisticated inferential relationships extracted with Information Flow (IF). Information flow relationships are not simply pairwise term relationships as those used in previous studies, but are between a set of terms and another term. They allow for context-dependent query expansion. Our experiments conducted on TREC collections show that we can obtain large and significant improvements with our approach. This study shows that LM is an appropriate framework to implement effective query expansion.
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Intuitively, any ‘bag of words’ approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies have been mixed or inconclusive. To improve the situation, this paper shows how the natural language properties of the target documents can be used to transform and enrich the term dependencies to more useful statistics. This is done in three steps. The term co-occurrence statistics of queries and documents are each represented by a Markov chain. The paper proves that such a chain is ergodic, and therefore its asymptotic behavior is unique, stationary, and independent of the initial state. Next, the stationary distribution is taken to model queries and documents, rather than their initial distributions. Finally, ranking is achieved following the customary language modeling paradigm. The main contribution of this paper is to argue why the asymptotic behavior of the document model is a better representation then just the document’s initial distribution. A secondary contribution is to investigate the practical application of this representation in case the queries become increasingly verbose. In the experiments (based on Lemur’s search engine substrate) the default query model was replaced by the stable distribution of the query. Just modeling the query this way already resulted in significant improvements over a standard language model baseline. The results were on a par or better than more sophisticated algorithms that use fine-tuned parameters or extensive training. Moreover, the more verbose the query, the more effective the approach seems to become.
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Beryl & Gael discuss the ‘new’ metalanguage for knowledge about language presented in the Australian Curriculum English (ACARA, 2010). Their discussion connects to practice by recounting how one teacher scaffolds her students through detailed understandings of noun and adjective groups in reading activities. The stimulus text is the novel ‘A wrinkle in time’ (L’Engle, 1962, reproduced 2007) and the purpose is to build students’ understandings so they can work towards ‘expressing and developing ideas’ in written text (ACARA, 2010).
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This paper reports results from a study exploring the multimedia search functionality of Chinese language search engines. Web searching in Chinese (Mandarin) is a growing research area and a technical challenge for popular commercial Web search engines. Few studies have been conducted on Chinese language search engines. We investigate two research questions: which Chinese language search engines provide multimedia searching, and what multimedia search functionalities are available in Chinese language Web search engines. Specifically, we examine each Web search engine's (1) features permitting Chinese language multimedia searches, (2) extent of search personalization and user control of multimedia search variables, and (3) the relationships between Web search engines and their features in the Chinese context. Key findings show that Chinese language Web search engines offer limited multimedia search functionality, and general search engines provide a wider range of features than specialized multimedia search engines. Study results have implications for Chinese Web users, Website designers and Web search engine developers. © 2009 Elsevier Ltd. All rights reserved.
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The Lingodroids are a pair of mobile robots that evolve a language for places and relationships between places (based on distance and direction). Each robot in these studies has its own understanding of the layout of the world, based on its unique experiences and exploration of the environment. Despite having different internal representations of the world, the robots are able to develop a common lexicon for places, and then use simple sentences to explain and understand relationships between places even places that they could not physically experience, such as areas behind closed doors. By learning the language, the robots are able to develop representations for places that are inaccessible to them, and later, when the doors are opened, use those representations to perform goal-directed behavior.