The Influence of Anglicism on French Language——Enrichment or Danger

The phenomenon of Anglicism is one of the hot linguistic topics which exists in almost every language in the world, especially in the French language. We look back to the history of English and French, and introduce the definition and classification of Anglicism. Considering the predominant place of the UK and the USA in many fields, the English language undoubtedly becomes Lingua franca in recent years.In certain high-tech domains, there are some irreplaceable words or the words which can't be translated properly in the target language. In order to introduce relative concepts, we have to ask the original language for help. That's how the Anglicism appears. And since then, the Anglicism has grown rapidly.By analyzing the history of the two languages, the origin of Anglicism and its development, we try to find out whether the phenomenon of Anglicism causes positive or negative effects for the French language

Space-Invariant Projection in Streaming Network Embedding

Newly arriving nodes in dynamics networks would gradually make the node embedding space drifted and the retraining of node embedding and downstream models indispensable. An exact threshold size of these new nodes, below which the node embedding space will be predicatively maintained, however, is rarely considered in either theory or experiment. From the view of matrix perturbation theory, a threshold of the maximum number of new nodes that keep the node embedding space approximately equivalent is analytically provided and empirically validated. It is therefore theoretically guaranteed that as the size of newly arriving nodes is below this threshold, embeddings of these new nodes can be quickly derived from embeddings of original nodes. A generation framework, Space-Invariant Projection (SIP), is accordingly proposed to enables arbitrary static MF-based embedding schemes to embed new nodes in dynamics networks fast. The time complexity of SIP is linear with the network size. By combining SIP with four state-of-the-art MF-based schemes, we show that SIP exhibits not only wide adaptability but also strong empirical performance in terms of efficiency and efficacy on the node classification task in three real datasets

Chinese Language Teacher Professional Growth: A Case Study

Chinese language teachers grow with certain characteristics in their professional development. Knowing these characteristics can reveal a teacher’s developmental needs which can inform the teachers and the teacher development facilitators. This case study examines the professional development of one Chinese language teacher that works in a high school in the United States. The Five-Stage Theory is employed to direct the examination of the teacher’s growing path. Findings cover the challenges, efforts to cope with the changes, successes, and failures

SFLM: A mix of a Functional Linear Model and of a Spatial Autoregressive Model for spatially correlated functional data

International audienc

Entropy-Based Maximally Stable Extremal Regions for Robust Feature Detection

Maximally stable extremal regions (MSER) is a state-of-the-art method in local feature detection. However, this method is sensitive to blurring because, in blurred images, the intensity values in region boundary will vary more slowly, and this will undermine the stability criterion that the MSER relies on. In this paper, we propose a method to improve MSER, making it more robust to image blurring. To find back the regions missed by MSER in the blurred image, we utilize the fact that the entropy of probability distribution function of intensity values increases rapidly when the local region expands across the boundary, while the entropy in the central part remains small. We use the entropy averaged by the regional area as a measure to reestimate regions missed by MSER. Experiments show that, when dealing with blurred images, the proposed method has better performance than the original MSER, with little extra computational effort