This paper describes how to translate the compiler directives for conditional compilation in automated source-to-source translation between high-level programming languages. The directives for conditional compilation of the source language are translated into the corresponding directives of the target language, and the source program text of each branch of conditional compilation is translated ...

Text Retrieval Conference (TREC), organised by National Institute for Standards and Technology (NIST), is a set of tracks that represent different areas of text retrieval. These tracks provide a way to measure systems progress in certain fields in text retrieval such as crosslanguage retrieval, retrieval filtering and genomics. We participated in the question answering track. The questions in t...

text classification is an important research field in information retrieval and text mining. the main task in text classification is to assign text documents in predefined categories based on documents’ contents and labeled-training samples. since word detection is a difficult and time consuming task in persian language, bayesian text classifier is an appropriate approach to deal with different...

Steganography is the ability to hide secret information in a cover-media such as sound, pictures and text. A new approach is proposed to hide a secret into Arabic text cover media using "Kashida", an Arabic extension character. The proposed approach is an attempt to maximize the use of "Kashida" to hide more information in Arabic text cover-media. To approach this, some algorithms have been des...

PURPOSE To investigate the impact of clinical target volume (CTV) shape and size on CTV to planning target volume (PTV) margin expansion. METHODS AND MATERIALS Using numerical integration methods, margins accounting for random errors and systematic errors were calculated for CTVs of different shapes and sizes. We use k(r-95) and k(s-95) to represent the coefficients, for random errors and sys...

The term “process” in translation refers to the dynamic meaning of translation, which can be divided into special and general translation. Special process translator’s conversion specific text, is, from original text final target text. understanding re-expression are two basic steps this process. is not only a simple languages conversion, but also involves selection, research, interpretation, g...

Accent Conversion (AC) seeks to change the accent of speech from one (source) another (target) while preserving content and speaker identity. However, many existing AC approaches rely on source-target parallel data during training or reference at run-time. We propose a novel conversion framework without need for either speech. Specifically, text-to-speech (TTS) system is first pretrained with t...

Transfer learning as a new machine learning paradigm has gained increasing attention lately. In situations where the training data in a target domain are not sufficient to learn predictive models effectively, transfer learning leverages auxiliary source data from other related source domains for learning. While most of the existing works in this area only focused on using the source data with t...

The main objective is to propose a text classification based on the features selection and preprocessing thereby reducing the dimensionality of the Feature vector and increase the classification accuracy. Text classification is the process of assigning a document to one or more target categories, based on its contents. In the proposed method, machine learning methods for text classification is ...

Text simplification aims at reducing the lexical, grammatical and structural complexity of a text while keeping the same meaning. In the context of machine translation, we introduce the idea of simplified translations in order to boost the learning ability of deep neural translation models. We conduct preliminary experiments showing that translation complexity is actually reduced in a translati...