Search results for: wasteless method of ores processing.

Authors: Sergei Aleinik, Mikhail Stolbov

Abstract:

In this work, a method of time delay estimation for  dual-channel acoustic signals (speech, music, etc.) recorded under  reverberant conditions is investigated. Standard methods based on  cross-correlation of the signals show poor results in cases involving  strong reverberation, large distances between microphones and  asynchronous recordings. Under similar conditions, a method based  on cross-correlation of temporal envelopes of the signals delivers a  delay estimation of acceptable quality. This method and its properties  are described and investigated in detail, including its limits of  applicability. The method’s optimal parameter estimation and a  comparison with other known methods of time delay estimation are  also provided.

 

Keywords: Cross-correlation, delay estimation, signal envelope, signal processing.

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Authors: Kamaruddin Malik Mohamad, Sapiee Haji Jamel, Mustafa Mat Deris

Abstract:

Memory forensic is important in digital investigation. The forensic is based on the data stored in physical memory that involve memory management and processing time. However, the current forensic tools do not consider the efficiency in terms of storage management and the processing time. This paper shows the high redundancy of data found in the physical memory that cause inefficiency in processing time and memory management. The experiment is done using Borland C compiler on Windows XP with 512 MB of physical memory.

Keywords: Digital Evidence, Memory Forensics.

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Authors: M. Omer, D. Wilson

Abstract:

Creating a database scheme is essentially a manual process. From a requirement specification the information contained within has to be analyzed and reduced into a set of tables, attributes and relationships. This is a time consuming process that has to go through several stages before an acceptable database schema is achieved. The purpose of this paper is to implement a Natural Language Processing (NLP) based tool to produce a relational database from a requirement specification. The Stanford CoreNLP version 3.3.1 and the Java programming were used to implement the proposed model. The outcome of this study indicates that a first draft of a relational database schema can be extracted from a requirement specification by using NLP tools and techniques with minimum user intervention. Therefore this method is a step forward in finding a solution that requires little or no user intervention.

Keywords: Information Extraction, Natural Language Processing, Relation Extraction.

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Authors: Zeynep Orhan, Zeynep Altan

Abstract:

Word sense disambiguation is an important intermediate stage for many natural language processing applications. The senses of an ambiguous word are the classification of usages for that specific word. This paper deals with the methodologies of determining the senses for a given word if they can not be obtained from an already available resource like WordNet. We offer a method that helps us to determine the sense boundaries gradually. In this method, first we decide on some features that are thought to be effective on the senses and divide the instances first into two, then according to the results of evaluations we continue dividing instances gradually. In a second method we use the pseudo words. We devise artificial words depending on some criteria and evaluate classification algorithms on these previously classified words.

Keywords: Word sense disambiguation, sense determination, pseudo words, sense granularity.

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Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

Abstract:

Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: Connected component labeling, image processing, morphological processing, optical musical recognition.

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Authors: Toktam Zoughi, Reza Boostani

Abstract:

Determining depth of anesthesia is a challenging problem in the context of biomedical signal processing. Various methods have been suggested to determine a quantitative index as depth of anesthesia, but most of these methods suffer from high sensitivity during the surgery. A novel method based on energy scattering of samples in the wavelet domain is suggested to represent the basic content of electroencephalogram (EEG) signal. In this method, first EEG signal is decomposed into different sub-bands, then samples are squared and energy of samples sequence is constructed through each scale and time, which is normalized and finally entropy of the resulted sequences is suggested as a reliable index. Empirical Results showed that applying the proposed method to the EEG signals can classify the awake, moderate and deep anesthesia states similar to BIS.

Keywords: Depth of anesthesia, EEG, BIS, Wavelet transforms.

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Authors: Hongyan Dai

Abstract:

This work presents a matched field processing (MFP) algorithm based on Dopplerlet transform for estimating the motion parameters of a sound source moving along a straight line and with a constant speed by using a piecewise strategy, which can significantly reduce the computational burden. Monte Carlo simulation results and an experimental result are presented to verify the effectiveness of the algorithm advocated.

Keywords: matched field processing; Dopplerlet transform; motion parameter estimation; piecewise strategy

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Authors: C. Bisu, M. Zapciu, A. Gérard

Abstract:

This paper proposes a method to vibration analysis in order to on-line monitoring and predictive maintenance during the milling process. Adapting envelope method to diagnostics and the analysis for milling tool materials is an important contribution to the qualitative and quantitative characterization of milling capacity and a step by modeling the three-dimensional cutting process. An experimental protocol was designed and developed for the acquisition, processing and analyzing three-dimensional signal. The vibration envelope analysis is proposed to detect the cutting capacity of the tool with the optimization application of cutting parameters. The research is focused on Hilbert transform optimization to evaluate the dynamic behavior of the machine/ tool/workpiece.

Keywords: diagnostics, envelope, milling, vibration

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Authors: Saeed Hosseini, Ali Reza Tahavvor

Abstract:

Sound processing is one the subjects that newly attracts a lot of researchers. It is efficient and usually less expensive than other methods. In this paper the flow generated sound is used to estimate the flow speed of free flows. Many sound samples are gathered. After analyzing the data, a parameter named wave power is chosen. For all samples the wave power is calculated and averaged for each flow speed. A curve is fitted to the averaged data and a correlation between the wave power and flow speed is found. Test data are used to validate the method and errors for all test data were under 10 percent. The speed of the flow can be estimated by calculating the wave power of the flow generated sound and using the proposed correlation.

Keywords: Flow generated sound, sound processing, speed, wave power.

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Authors: Sheng-Hsiu Kuo, Pao-Hsiung Chiu, Reui-Kuo Lin, Yan-Ting Lin

Abstract:

A one-step conservative level set method, combined with a global mass correction method, is developed in this study to simulate the incompressible two-phase flows. The present framework do not need to solve the conservative level set scheme at two separated steps, and the global mass can be exactly conserved. The present method is then more efficient than two-step conservative level set scheme. The dispersion-relation-preserving schemes are utilized for the advection terms. The pressure Poisson equation solver is applied to GPU computation using the pCDR library developed by National Center for High-Performance Computing, Taiwan. The SMP parallelization is used to accelerate the rest of calculations. Three benchmark problems were done for the performance evaluation. Good agreements with the referenced solutions are demonstrated for all the investigated problems.

Keywords: Conservative level set method, two-phase flow, dispersion-relation-preserving, graphics processing unit (GPU), multi-threading.

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Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

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In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: Text mining, topic extraction, independent, incremental, independent component analysis.

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Authors: Zhichao Zhao, Yi Liu, Shunping Xiao

Abstract:

A new data fusion method called joint probability density matrix (JPDM) is proposed, which can associate and fuse measurements from spatially distributed heterogeneous sensors to identify the real target in a surveillance region. Using the probabilistic grids representation, we numerically combine the uncertainty regions of all the measurements in a general framework. The NP-hard multisensor data fusion problem has been converted to a peak picking problem in the grids map. Unlike most of the existing data fusion method, the JPDM method dose not need association processing, and will not lead to combinatorial explosion. Its convergence to the CRLB with a diminishing grid size has been proved. Simulation results are presented to illustrate the effectiveness of the proposed technique.

Keywords: Cramer-Rao lower bound (CRLB), data fusion, probabilistic grids, joint probability density matrix, localization, sensor network.

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Authors: Homayoon Zarshenas, Mahdi Bamdad, Hadi Grailu, Akbar A. Shakoori

Abstract:

In this study we focus on improvement performance of a cue based Motor Imagery Brain Computer Interface (BCI). For this purpose, data fusion approach is used on results of different classifiers to make the best decision. At first step Distinction Sensitive Learning Vector Quantization method is used as a feature selection method to determine most informative frequencies in recorded signals and its performance is evaluated by frequency search method. Then informative features are extracted by packet wavelet transform. In next step 5 different types of classification methods are applied. The methodologies are tested on BCI Competition II dataset III, the best obtained accuracy is 85% and the best kappa value is 0.8. At final step ordered weighted averaging (OWA) method is used to provide a proper aggregation classifiers outputs. Using OWA enhanced system accuracy to 95% and kappa value to 0.9. Applying OWA just uses 50 milliseconds for performing calculation.

Keywords: BCI, EEG, Classifier, Fuzzy operator, OWA.

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Authors: András Barta, István Vajk

Abstract:

In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.

Keywords: Object recognition, Bayesian network, Wavelets, Document processing.

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Authors: Soham De, Nupur Biswas, Abhijit Sanyal, Pulak Ray, Alokmay Datta

Abstract:

Particle detection in very noisy and low contrast images is an active field of research in image processing. In this article, a method is proposed for the efficient detection and sizing of subsurface spherical particles, which is used for the processing of softly fused Au nanoparticles. Transmission Electron Microscopy is used for imaging the nanoparticles, and the proposed algorithm has been tested with the two-dimensional projected TEM images obtained. Results are compared with the data obtained by transmission optical spectroscopy, as well as with conventional circular object detection algorithms.

Keywords: Transmission Electron Microscopy, Circular Hough Transform, Au Nanoparticles, Median Filter, Laplacian Sharpening Filter, Canny Edge Detection

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Authors: András Barta, István Vajk

Abstract:

In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.

Keywords: Object recognition, Bayesian network, Wavelets, Document processing.

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Authors: Yee Yee Htun, Dr. Khaing Khaing Aye

Abstract:

Morphological operators transform the original image into another image through the interaction with the other image of certain shape and size which is known as the structure element. Mathematical morphology provides a systematic approach to analyze the geometric characteristics of signals or images, and has been applied widely too many applications such as edge detection, objection segmentation, noise suppression and so on. Fuzzy Mathematical Morphology aims to extend the binary morphological operators to grey-level images. In order to define the basic morphological operations such as fuzzy erosion, dilation, opening and closing, a general method based upon fuzzy implication and inclusion grade operators is introduced. The fuzzy morphological operations extend the ordinary morphological operations by using fuzzy sets where for fuzzy sets, the union operation is replaced by a maximum operation, and the intersection operation is replaced by a minimum operation. In this work, it consists of two articles. In the first one, fuzzy set theory, fuzzy Mathematical morphology which is based on fuzzy logic and fuzzy set theory; fuzzy Mathematical operations and their properties will be studied in details. As a second part, the application of fuzziness in Mathematical morphology in practical work such as image processing will be discussed with the illustration problems.

Keywords: Binary Morphological, Fuzzy sets, Grayscalemorphology, Image processing, Mathematical morphology.

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Authors: Khaled Harrar, Rachid Jennane

Abstract:

The purpose of this study is the discrimination of 28 postmenopausal with osteoporotic femoral fractures from an agematched control group of 28 women using texture analysis based on fractals. Two pre-processing approaches are applied on radiographic images; these techniques are compared to highlight the choice of the pre-processing method. Furthermore, the values of the fractal dimension are compared to those of the fractal signature in terms of the classification of the two populations. In a second analysis, the BMD measure at proximal femur was compared to the fractal analysis, the latter, which is a non-invasive technique, allowed a better discrimination; the results confirm that the fractal analysis of texture on calcaneus radiographs is able to discriminate osteoporotic patients with femoral fracture from controls. This discrimination was efficient compared to that obtained by BMD alone. It was also present in comparing subgroups with overlapping values of BMD.

Keywords: Osteoporosis, fractal dimension, fractal signature, bone mineral density.

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Authors: Aki Happonen, Adrian Burian, Erwin Hemming

Abstract:

Fixed-point simulation results are used for the performance measure of inverting matrices by Cholesky decomposition. The fixed-point Cholesky decomposition algorithm is implemented using a fixed-point reconfigurable processing element. The reconfigurable processing element provides all mathematical operations required by Cholesky decomposition. The fixed-point word length analysis is based on simulations using different condition numbers and different matrix sizes. Simulation results show that 16 bits word length gives sufficient performance for small matrices with low condition number. Larger matrices and higher condition numbers require more dynamic range for a fixedpoint implementation.

Keywords: Cholesky Decomposition, Fixed-point, Matrix inversion, Reconfigurable processing.

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Authors: S. Hellam, Y. Oulahrir, F. El Mounchid, A. Sadiq, S. Mbarki

Abstract:

In this paper, we propose a method for three-dimensional (3-D)-model indexing based on defining a new descriptor, which we call new descriptor using spherical harmonics. The purpose of the method is to minimize, the processing time on the database of objects models and the searching time of similar objects to request object. Firstly we start by defining the new descriptor using a new division of 3-D object in a sphere. Then we define a new distance which will be used in the search for similar objects in the database.

Keywords: 3D indexation, spherical harmonic, similarity of 3D objects.

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Authors: Duy Cuong Nguyen, Ali Makke, Guillaume Montay

Abstract:

This work presents an improved single fiber pull-out test for fiber/matrix interface characterization. This test has been used to study the Inter-Facial Shear Strength ‘IFSS’ of hemp fibers reinforced polypropylene (PP). For this aim, the fiber diameter has been carefully measured using a tomography inspired method. The fiber section contour can then be approximated by a circle or a polygon. The results show that the IFSS is overestimated if the circular approximation is used. The Influence of the molding temperature on the IFSS has also been studied. We find that a molding temperature of 183◦C leads to better interfacial properties. Above or below this temperature the interface strength is reduced.

Keywords: Interface, pull-out, processing, temperature, hemp, polypropylene, composite.

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Authors: Seongsoo Lee

Abstract:

Motion estimation occupies the heaviest computation in HEVC (high efficiency video coding). Many fast algorithms such as TZS (test zone search) have been proposed to reduce the computation. Still the huge computation of the motion estimation is a critical issue in the implementation of HEVC video codec. In this paper, motion estimator architecture with optimized number of PEs (processing element) is presented by exploiting early termination. It also reduces hardware size by exploiting parallel processing. The presented motion estimator architecture has 8 PEs, and it can efficiently perform TZS with very high utilization of PEs.

Keywords: Motion estimation, test zone search, high efficiency video coding, processing element, optimization.

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Authors: See Zi Siang, Khairul Hazrin Hashim, Harold Thwaites, Lee Xia Sheng, Ooi Wooi Har

Abstract:

The paper explores the development of an optimization of method and apparatus for retrieving extended high dynamic range from digital negative image. Architectural photo imaging can benefit from high dynamic range imaging (HDRI) technique for preserving and presenting sufficient luminance in the shadow and highlight clipping image areas. The HDRI technique that requires multiple exposure images as the source of HDRI rendering may not be effective in terms of time efficiency during the acquisition process and post-processing stage, considering it has numerous potential imaging variables and technical limitations during the multiple exposure process. This paper explores an experimental method and apparatus that aims to expand the dynamic range from digital negative image in HDRI environment. The method and apparatus explored is based on a single source of RAW image acquisition for the use of HDRI post-processing. It will cater the optimization in order to avoid and minimize the conventional HDRI photographic errors caused by different physical conditions during the photographing process and the misalignment of multiple exposed image sequences. The study observes the characteristics and capabilities of RAW image format as digital negative used for the retrieval of extended high dynamic range process in HDRI environment.

Keywords: High Dynamic Range Image, Photography Workflow Optimization, Digital Negative Image, Architectural Image

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Authors: Nisar Ahmed Memon

Abstract:

Embedding and extraction of a secret information as well as the restoration of the original un-watermarked image is highly desirable in sensitive applications like military, medical, and law enforcement imaging. This paper presents a novel reversible data-hiding method for digital images using integer to integer wavelet transform and companding technique which can embed and recover the secret information as well as can restore the image to its pristine state. The novel method takes advantage of block based watermarking and iterative optimization of threshold for companding which avoids histogram pre and post-processing. Consequently, it reduces the associated overhead usually required in most of the reversible watermarking techniques. As a result, it keeps the distortion small between the marked and the original images. Experimental results show that the proposed method outperforms the existing reversible data hiding schemes reported in the literature.

Keywords: Adaptive Thresholding, Companding Technique, Integer Wavelet Transform, Reversible Watermarking

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Authors: Sara Felloni, Giuliano Strini

Abstract:

We explore entanglement in composite quantum systems and how its peculiar properties are exploited in quantum information and communication protocols by means of Diagrams of States, a novel method to graphically represent and analyze how quantum information is elaborated during computations performed by quantum circuits. We present quantum diagrams of states for Bell states generation, measurements and projections, for dense coding and quantum teleportation, for probabilistic quantum machines designed to perform approximate quantum cloning and universal NOT and, finally, for quantum privacy amplification based on entanglement purification. Diagrams of states prove to be a useful approach to analyze quantum computations, by offering an intuitive graphic representation of the processing of quantum information. They also help in conceiving novel quantum computations, from describing the desired information processing to deriving the final implementation by quantum gate arrays.

Keywords: Diagrams of states, entanglement, quantum circuits, quantum information.

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Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

Abstract:

Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, medial temporal atrophy, LOO Cycle.

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Authors: Fan Gao, Lior Pachter

Abstract:

The primary tool currently used to pre-process 10X chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing single-cell ATAC-seq data that is 15 to 18 times faster than Cell Ranger on mouse and human samples. Our tool can also calculate chromatin interaction potential matrices and generate open chromatin signal and interaction traces for cell groups. We use scATAK tool to explore the chromatin regulatory landscape of a healthy adult human brain and unveil cell-type specific features, and show that it provides a convenient and computational efficient approach for pre-processing single-cell ATAC-seq data.

Keywords: single-cell, ATAC-seq, bioinformatics, open chromatin landscape, chromatin interactome

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Authors: Marcin Michalak

Abstract:

Biclustering is the way of two-dimensional data analysis. For several years it became possible to express such issue in terms of Boolean reasoning, for processing continuous, discrete and binary data. The mathematical backgrounds of such approach — proved ability of induction of exact and inclusion–maximal biclusters fulfilling assumed criteria — are strong advantages of the method. Unfortunately, the core of the method has quite high computational complexity. In the paper the basics of Boolean reasoning approach for biclustering are presented. In such context the problems of computation parallelization are risen.

Keywords: Boolean reasoning, biclustering, parallelization, prime implicant.

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Authors: Cherif Haddad, Faouzi Ben Charrada

Abstract:

Large-scale systems such as Grids offer infrastructures for both data distribution and parallel processing. The use of Grid infrastructures is a more recent issue that is already impacting the Distributed Database Management System industry. In DBMS, distributed query processing has emerged as a fundamental technique for ensuring high performance in distributed databases. Database placement is particularly important in large-scale systems because it reduces communication costs and improves resource usage. In this paper, we propose a dynamic database placement policy that depends on query patterns and Grid sites capabilities. We evaluate the performance of the proposed database placement policy using simulations. The obtained results show that dynamic database placement can significantly improve the performance of distributed query processing.

Keywords: Large-scale systems, Grid environment, Distributed Databases, Distributed query processing, Database placement

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Authors: Parisa Shooshtari, Gelareh Mohamadi, Behnam Molaee Ardekani, Mohammad Bagher Shamsollahi

Abstract:

EEG signal is one of the oldest measures of brain activity that has been used vastly for clinical diagnoses and biomedical researches. However, EEG signals are highly contaminated with various artifacts, both from the subject and from equipment interferences. Among these various kinds of artifacts, ocular noise is the most important one. Since many applications such as BCI require online and real-time processing of EEG signal, it is ideal if the removal of artifacts is performed in an online fashion. Recently, some methods for online ocular artifact removing have been proposed. One of these methods is ARMAX modeling of EEG signal. This method assumes that the recorded EEG signal is a combination of EOG artifacts and the background EEG. Then the background EEG is estimated via estimation of ARMAX parameters. The other recently proposed method is based on adaptive filtering. This method uses EOG signal as the reference input and subtracts EOG artifacts from recorded EEG signals. In this paper we investigate the efficiency of each method for removing of EOG artifacts. A comparison is made between these two methods. Our undertaken conclusion from this comparison is that adaptive filtering method has better results compared with the results achieved by ARMAX modeling.

Keywords: Ocular Artifacts, EEG, Adaptive Filtering, ARMAX

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