We train multi-task autoencoders on linguistic tasks and analyze the learned hidden sentence representations. The representations change significantly when translation and part-of-speech decoders are added. The more decoders a model employs, the better it clusters sentences according to their syntactic similarity, as the representation space becomes less entangled. We explore the structure of t...

For the mode mixing problem caused by intermittency signal in empirical mode decomposition (EMD), a novel filtering method is proposed in this paper. In this new method, the original data is pretreated by using wavelet denoising method to avoid the mode mixture in the subsequent EMD procedure. Because traditional wavelet threshold denoising may exhibit pseudo-Gibbs phenomena in the neighborhood...

A Teichmüller lattice is the orbit of a point in Teichmüller space under the action of the mapping class group. We show that the proportion of lattice points in a ball of radius r which are not pseudo-Anosov tends to zero as r tends to infinity. In fact, we show that if R is a subset of the mapping class group, whose elements have an upper bound on their translation length on the complex of cur...

this research was conducted to examine whether there was a significant difference between the quality of translations produced by translation students who used bilingual (english to farsi) dictionaries with that of those using monolingual (english to english) dictionaries. to this end, 78 senior undergraduate students of english translation took part in a piloted english proficiency test, 60 of...

the present article reports a study carried out to investigate whether or not awareness of functional translation theories has any impact on the translation quality of translator trainees. 2oo iranian undergraduate students took part in this study. they were divided into four groups -two- experimental and two control groups. after homogenizing the participants by a toefl test, a translation pre...

Unsupervised domain adaptation (UDA) is essential since manually labeling pixel-level annotations consuming and expensive. Since the discrepancies have not been well solved, existing UDA approaches yield poor performance compared with supervised learning approaches. In this paper, we propose a novel sequential network (SLNet) for unsupervised cross-scene aerial image segmentation. The whole sys...