In this paper, we propose a novel reversible data hiding framework to hide secret data into a binary codestream of VQ indices invertibly, in which matrix encoding is used to efficiently embed secret data, and error correction coding (ECC) is employed for lossless restoration of the marked codestream at the receiver side. Due to the unchanged structure of the codestream during the embedding proc...

This paper addresses the problem of dealing with a collection of labeled training documents, especially annotating negative training documents and presents a method of text classification from positive and unlabeled data. We applied an error detection and correction technique to the results of positive and negative documents classified by the Support Vector Machines (SVM). The results using Reu...

The annotation of documents with linguistic information requires time-consuming and therefore expensive manual annotation. Especially, a complex task, like coreference resolution, needs large data sets for the training of supervised machine learning methods. We present a tool which combines visualization techniques and unsupervised machine learning to support the annotation of documents with co...

A new ensemble of support vector machines (SVM) based on random subspace (RS) and feature selection is developed and applied to the problem of differential diagnosis of erythemato-squamous diseases. Each classifier has a ‘‘favourite’’ class. To find the feature subset for the classifier Di with ‘‘favourite’’ class wi, we calculate the best features to discriminate this class (wi) from all the o...

This study aimed at investigating the effects of grammatical error correction on EFL learners’ accuracy. Twenty-two male and female senior students were chosen randomly to respond to a questionnaire investigating their beliefs about immediate grammatical error correction.  Actually, the study was conducted in order to answer this question: what is the effect of grammatical error feedback on stu...

The present paper analyzes the existence of a long-run relationship between the trade balance and exchange rate of Iran and South Korea by a new approach. It proposes an asymmetric co-integrating NARDL model by two positive and negative partial sum decompositions which can use mixed I (0) and I (1) variables by bounds testing approach. The proposed tests are based on calculated F –statistics an...

We present a pronunciation error detection method for second language learners of English (L2 learners). The method is a combination of confidence scoring and landmark-based Support Vector Machines (SVMs). Landmark-based SVMs were implemented to specialize the method for the specific phonemes with which L2 learners make frequent errors. The method was trained for the difficult phonemes for Kore...

This short note examines some time series evidence relating prices of exports and imports to the aggregate US wage over 34 years of falling tariffs starting in the mid 1960s. The cointegrated unit root series lead to error correction and vector autoregression models. The lost protection and changing traded prices lowered the US wage very slightly, by less than 1%. © 2007 Elsevier Inc. All right...

This paper investigates the effects of shocks to U.S. monetary policy on the dollar/yen exchange rate, using structural Vector Error Correction Model (VECM) methods. We compare our estimates of the impulse responses with those based on levels Vector Autoregression. We also compare results from short run and long run restrictions imposed on the structural VECM. We find evidence of overshooting b...