1 2538-4201 Research Center on Developing Advanced Technologies 734 Paper A POS Tagging System in the Persian Language 1 3 2010 6 2 13 26 20 03 2010 19 02 2018 Abstract: Part-Of-Speech (POS) tagging is essential work for many models and methods in other areas in natural language processing such as machine translation, spell checker, text-to-speech, automatic speech recognition, etc. So far, high accurate POS taggers have been created in many languages. In this paper, we focus on POS tagging in the Persian language. Because of problems in Persian POS tagging, a comprehensive plan is proposed to reach a high efficient POS tagger in this language. Afterward, morphological analysis is investigated in Persian and it is shown that using a morphological analyzer in inflection level, POS tagging has been improved greatly. The results describe the fruitfulness of the proposed method.
735 Paper Automatic Classification of Lung Tissue Patterns in HRCT Images of Patients Affected with ILD 1 3 2010 6 2 27 38 20 03 2010 19 02 2018 Abstract: The purpose of this study was to apply recurrence plots on event related potentials (ERPs) recorded during memory recognition tests. EEG signals recorded during memory retrieval in four scalp region were used. Two most important ERP’s components corresponding to memory retrieval, FN400 and LPC, were detected in recurrence plots computed for single-trial EEGs. In addition, the RQA was used to quantify changes in signal dynamic structure during memory retrieval, and measures of complexity as RQA variables were computed. Given the stimulus, amplitude of the RQA variables increases around 400ms, corresponding to dimension reduction of system. Furthermore, after 800ms these amplitudes decreased which can be as a consequence of an increase in system dimension and complexity and back to its basic state. The mean amplitude of Old items was more than New one. Furthermore we applied statistical analysis (t-test) to find meaningful difference between features extracted from nonlinear measures. Using this method, we found its ability to detect memory components of EEG signals and to do a distinction between Old/ New items. In contrast with linear techniques, recurrence plots and RQA do not need large number of recorded trials, and they can indicate changes in even single-trial EEGs. RQA can also show differences between old and new events in a memory process. 727 Paper TTS speech databases 1 3 2010 6 2 35 12 20 03 2010 19 02 2018 Abstract Speech databases are part of the concatenative text to speech synthesis systems. Phonetic quality of the databases plays a significant role in the naturalness of the synthesized speech. This paper introduces two syllable and diphone speech databases for Persian and investigates the way of their development and their specifications and their advantages to each other. Abstract Speech databases are part of the concatenative text to speech synthesis systems. Phonetic quality of the databases plays a significant role in the naturalness of the synthesized speech. This paper introduces two syllable and diphone speech databases for Persian and investigates the way of their development and their specifications and their advantages to each other. 736 Paper Applying Recurrence Plots for Identifying Memory Components in Single-Trial EEGs 1 3 2010 6 2 39 52 20 03 2010 21 02 2018 Abstract: The purpose of this study was to apply recurrence plots on event related potentials (ERPs) recorded during memory recognition tests. EEG signals recorded during memory retrieval in four scalp region were used. Two most important ERP’s components corresponding to memory retrieval, FN400 and LPC, were detected in recurrence plots computed for single-trial EEGs. In addition, the RQA was used to quantify changes in signal dynamic structure during memory retrieval, and measures of complexity as RQA variables were computed. Given the stimulus, amplitude of the RQA variables increases around 400ms, corresponding to dimension reduction of system. Furthermore, after 800ms these amplitudes decreased which can be as a consequence of an increase in system dimension and complexity and back to its basic state. The mean amplitude of Old items was more than New one. Furthermore we applied statistical analysis (t-test) to find meaningful difference between features extracted from nonlinear measures. Using this method, we found its ability to detect memory components of EEG signals and to do a distinction between Old/ New items. In contrast with linear techniques, recurrence plots and RQA do not need large number of recorded trials, and they can indicate changes in even single-trial EEGs. RQA can also show differences between old and new events in a memory process. 737 Paper A Neural Network Model of Mapping from 1 3 2010 6 2 53 62 20 03 2010 19 02 2018 Abstract: Medial entorhinal cortex is known to be the hub of a brain system for navigation and spatial representation. These cells increase firing frequency at multiple regions in the environment, arranged in regular triangular grids. Each cell has some properties including spacing, orientation, and phase shift of the nodes of its grid. Entorhinal cortex is commonly perceived to be the major input and output structure of hippocampal formation; grid cells are one synapse upstream of place cells in hippocampus. The problem is how single confined place fields can be generated from the repetitive activity of grid cells. In this article we have proposed an artificial neural network model based on radial basis function, which allows for the single confined place fields of hippocampal pyramidal cells to be emerged from the activities of grid cells. In order to evaluate the performance of the model, it was considered in two steps in a one-dimensional and two-dimensional environment. Simulations were done considering different characteristics of grid cells and the model demonstrated a good performance in generating single spot activity for place fields. 738 Paper An Introduction of New DESICA Algorithm for Blind Speech Separation in Dynamic Case 1 3 2010 6 2 63 74 20 03 2010 19 02 2018 Abstract: We consider a new scenario in blind speech separation problem in which the number and the features of active sources change with time in opposite to the previous methods in which all sources are active all the time. Accordingly, we propose the new DESICA algorithm for source separation which is a compound of the ICA and DESPRIT algorithms. In this algorithm, using the ICA, the separation process is performed initially and then using the DESPRIT algorithm, the binary mask of silence intervals is calculated. Finally, by applying the binary mask to the separated signals, the final separation is obtained. Simulation results show that the DESICA algorithm improves the SDR and SIR about 6dB compared to those of the DESPRIT algorithm. Also, the SEN is improved about 11 and 17dB with respect to those of the ICA and DESPRIT algorithms. 739 Paper Review of JPEG Steganography Methods and Their Security Analysis 1 3 2010 6 2 75 98 20 03 2010 19 02 2018 Abstract: JPEG is the most applicable image format in digital communication. In recent years, various steganography methods have been proposed for it. This paper aims to study and classify JPEG steganography schemes and introduce different methods to improve their security based on cover. Accordingly, the effective factors in security that are related to the cover such as double compression, spatial frequencies and quality factor have been evaluated theoretically and experimentally. Also some well-known steganography algorithms and software tools have been introduced, evaluated and classified based on different criteria. Some of these algorithms have been implemented in Stegotest software and the destruction effects of steganography in different methods have been compared.