Due to the increase of users the efficient usage of spectrum plays an important role in digital terrestrial television networks. In digital video broadcasting, local and global content are transmitted by single frequency network and multifrequency network respectively. Multifrequency network support transmission of global content and it consumes large spectrum. Similarly local content are well ...

Objective: Many studies have suggested that there is a relationship between coherence and cognitive processes. This study aims at investigating this hypothesis through assessing the relationship between cognitive variables and coherence in the discourse of two groups of Persian-speaking younger and older adults. Methods: In order to evaluate our participants' cognitive capabilities, we recrui...

Topic models assert that documents are distributions over latent topics and words. A nested document collection has inside a higher order structure such as articles in journals, podcasts within authors, or web pages sites. In single of documents, global shared across all documents. For sites, topic frequencies likely vary sites site, almost certainly from page to page. hierarchical prior for th...

Text categorisation is challenging, due to the complex structure with heterogeneous, changing topics in documents. The performance of text categorisation relies on the quality of samples, effectiveness of document features, and the topic coverage of categories, depending on the employing strategies; supervised or unsupervised; single labelled or multi-labelled. Attempting to deal with these rel...

We present Global-Local POS tagging, a framework to train generative stochastic Part-of-Speech models on large corpora. Global Taggers offer several advantages over their counter parts trained on small, curated corpus, including the ability to automatically extend and update their models to new text. Global Taggers also avoid a fundamental limitation of current models, whose performance heavily...

Most of the existing word embedding models only consider the relationships between words and their local contexts (e.g. ten words around the target word). However, information beyond local contexts (global contexts), which reflect the rich semantic meanings of words, are usually ignored. In this paper, we present a general framework for utilizing global information to learn word and text repres...

background and purpose: a 3-unit course is dedicated to general language in medical universities and the vocabulary and text structure of the courses have usually no relation to medical language. we examine whether teaching general language will be as effective as medical language as assessed through recall of general and medical vocabulary and text structure knowledge. methods: an experimental...

In this paper, we propose a filtering method for feature selection called ALOFT (At Least One FeaTure). The proposed method focuses on specific characteristics of text categorization domain. Also, it ensures that every document in the training set is represented by at least one feature and the number of selected features is determined in a data-driven way. We compare the effectiveness of the pr...

Three experiments were conducted to study on a more fine-grained level how processing a picture facilitates learning from text. In Experiment 1 (N 1⁄4 85), results from a drawing task revealed that the global spatial structure of a pulley system picture was extracted even from its brief inspection (for 600 ms, 2 s). In Experiment 2 (N 1⁄4 105), students who initially inspected the pulley system...

The main purpose of ...