Search results for: feature point reduction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4005

Search results for: feature point reduction

3765 Improved Text-Independent Speaker Identification using Fused MFCC and IMFCC Feature Sets based on Gaussian Filter

Authors: Sandipan Chakroborty, Goutam Saha

Abstract:

A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for speech related applications. On a recent contribution by authors, it has been shown that the Inverted Mel- Frequency Cepstral Coefficients (IMFCC) is useful feature set for SI, which contains complementary information present in high frequency region. This paper introduces the Gaussian shaped filter (GF) while calculating MFCC and IMFCC in place of typical triangular shaped bins. The objective is to introduce a higher amount of correlation between subband outputs. The performances of both MFCC & IMFCC improve with GF over conventional triangular filter (TF) based implementation, individually as well as in combination. With GMM as speaker modeling paradigm, the performances of proposed GF based MFCC and IMFCC in individual and fused mode have been verified in two standard databases YOHO, (Microphone Speech) and POLYCOST (Telephone Speech) each of which has more than 130 speakers.

Keywords: Gaussian Filter, Triangular Filter, Subbands, Correlation, MFCC, IMFCC, GMM.

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3764 Improved Closed Set Text-Independent Speaker Identification by Combining MFCC with Evidence from Flipped Filter Banks

Authors: Sandipan Chakroborty, Anindya Roy, Goutam Saha

Abstract:

A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for SI applications. However, due to the structure of its filter bank, it captures vocal tract characteristics more effectively in the lower frequency regions. This paper proposes a new set of features using a complementary filter bank structure which improves distinguishability of speaker specific cues present in the higher frequency zone. Unlike high level features that are difficult to extract, the proposed feature set involves little computational burden during the extraction process. When combined with MFCC via a parallel implementation of speaker models, the proposed feature set outperforms baseline MFCC significantly. This proposition is validated by experiments conducted on two different kinds of public databases namely YOHO (microphone speech) and POLYCOST (telephone speech) with Gaussian Mixture Models (GMM) as a Classifier for various model orders.

Keywords: Complementary Information, Filter Bank, GMM, IMFCC, MFCC, Speaker Identification, Speaker Recognition.

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3763 The Study of Groundcover for Heat Reduction

Authors: Winai Mankhatitham

Abstract:

This research investigated groundcover on the roof (green roof) which can reduce the temperature and carbon monoxide. This study is divided into 3 main aspects: 1. Types of groundcover affecting heat reduction 2. The efficiency on heat reduction of 3 types of groundcover, i.e. lawn, arachis pintoi, and purslane 3. Database for designing green roof. This study has been designed as an experimental research by simulating the 3 types of groundcover in 3 trays placed in the green house for recording the temperature change for 24 hours. The results showed that the groundcover with the highest heat reduction efficiency was lawn. The dense of the lawn can protect the heat transfer to the soil. For the further study, there should be a comparative study of the thickness and the types of soil to get more information for the suitable types of groundcover and the soil for designing the energy saving green roof.

Keywords: Groundcover, Green Roof, Heat Reduction, Energy Saving.

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3762 Existence of Solution for Singular Two-point Boundary Value Problem of Second-order Differential Equation

Authors: Xiguang Li

Abstract:

In this paper, by constructing a special set and utilizing fixed point theory in coin, we study the existence of solution of singular two point’s boundary value problem for second-order differential equation, which improved and generalize the result of related paper.

Keywords: Singular differential equation, boundary value problem, coin, fixed point theory.

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3761 Performance Comparison between ĆUK and SEPIC Converters for Maximum Power Point Tracking Using Incremental Conductance Technique in Solar Power Applications

Authors: James Dunia, Bakari M. M. Mwinyiwiwa

Abstract:

Photovoltaic (PV) energy is one of the most important energy resources since it is clean, pollution free, and endless. Maximum Power Point Tracking (MPPT) is used in photovoltaic (PV) systems to maximize the photovoltaic output power, irrespective the variations of temperature and radiation conditions. This paper presents a comparison between Ćuk and SEPIC converter in maximum power point tracking (MPPT) of photovoltaic (PV) system. In the paper, advantages and disadvantages of both converters are described. Incremental conductance control method has been used as maximum power point tracking (MPPT) algorithm. The two converters and MPPT algorithm were modelled using MATLAB/Simulink software for simulation. Simulation results show that both Ćuk and SEPIC converters can track the maximum power point with some minor variations. 

Keywords: Ćuk Converter, Incremental Conductance, Maximum Power Point Tracking, PV Module, SEPIC Converter.

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3760 An Automatic Feature Extraction Technique for 2D Punch Shapes

Authors: Awais Ahmad Khan, Emad Abouel Nasr, H. M. A. Hussein, Abdulrahman Al-Ahmari

Abstract:

Sheet-metal parts have been widely applied in electronics, communication and mechanical industries in recent decades; but the advancement in sheet-metal part design and manufacturing is still behind in comparison with the increasing importance of sheet-metal parts in modern industry. This paper presents a methodology for automatic extraction of some common 2D internal sheet metal features. The features used in this study are taken from Unipunch ™ catalogue. The extraction process starts with the data extraction from STEP file using an object oriented approach and with the application of suitable algorithms and rules, all features contained in the catalogue are automatically extracted. Since the extracted features include geometry and engineering information, they will be effective for downstream application such as feature rebuilding and process planning.

Keywords: Feature Extraction, Internal Features, Punch Shapes, Sheet metal, STEP.

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3759 Graph Codes-2D Projections of Multimedia Feature Graphs for Fast and Effective Retrieval

Authors: Stefan Wagenpfeil, Felix Engel, Paul McKevitt, Matthias Hemmje

Abstract:

Multimedia Indexing and Retrieval is generally de-signed and implemented by employing feature graphs. These graphs typically contain a significant number of nodes and edges to reflect the level of detail in feature detection. A higher level of detail increases the effectiveness of the results but also leads to more complex graph structures. However, graph-traversal-based algorithms for similarity are quite inefficient and computation intensive, espe-cially for large data structures. To deliver fast and effective retrieval, an efficient similarity algorithm, particularly for large graphs, is mandatory. Hence, in this paper, we define a graph-projection into a 2D space (Graph Code) as well as the corresponding algorithms for indexing and retrieval. We show that calculations in this space can be performed more efficiently than graph-traversals due to a simpler processing model and a high level of parallelisation. In consequence, we prove that the effectiveness of retrieval also increases substantially, as Graph Codes facilitate more levels of detail in feature fusion. Thus, Graph Codes provide a significant increase in efficiency and effectiveness (especially for Multimedia indexing and retrieval) and can be applied to images, videos, audio, and text information.

Keywords: indexing, retrieval, multimedia, graph code, graph algorithm

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3758 Robot Vision Application based on Complex 3D Pose Computation

Authors: F. Rotaru, S. Bejinariu, C. D. Niţâ, R. Luca, I. Pâvâloi, C. Lazâr

Abstract:

The paper presents a technique suitable in robot vision applications where it is not possible to establish the object position from one view. Usually, one view pose calculation methods are based on the correspondence of image features established at a training step and exactly the same image features extracted at the execution step, for a different object pose. When such a correspondence is not feasible because of the lack of specific features a new method is proposed. In the first step the method computes from two views the 3D pose of feature points. Subsequently, using a registration algorithm, the set of 3D feature points extracted at the execution phase is aligned with the set of 3D feature points extracted at the training phase. The result is a Euclidean transform which have to be used by robot head for reorientation at execution step.

Keywords: features correspondence, registration algorithm, robot vision, triangulation method.

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3757 From Electroencephalogram to Epileptic Seizures Detection by Using Artificial Neural Networks

Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

Abstract:

Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: Artificial Neural Network, Data Mining, Electroencephalogram, Epilepsy, Feature Extraction, Seizure Detection, Signal Processing.

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3756 Optimum Design of Heat Exchanger in Diesel Engine Cold EGR for Pollutants Reduction

Authors: Nasser Ghassembaglou, Armin Rahmatfam, Faramarz Ranjbar

Abstract:

Using cold EGR method with variable venturi and turbocharger has a very significant effect on reduction of NOX and grime simultaneously. EGR cooler is one of the most important parts in the cold EGR circuit. In this paper optimum design of cooler for working in different percentages of EGR and for determining optimum temperature of exhausted gases, growth of efficiency, reduction of weight, dimension, expenditures, sediment and also optimum performance by using gasoil which has significant amounts of brimstone are investigated and optimized.

Keywords: Cold EGR, NOX, Cooler.

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3755 Genetic Algorithm for Feature Subset Selection with Exploitation of Feature Correlations from Continuous Wavelet Transform: a real-case Application

Authors: G. Van Dijck, M. M. Van Hulle, M. Wevers

Abstract:

A genetic algorithm (GA) based feature subset selection algorithm is proposed in which the correlation structure of the features is exploited. The subset of features is validated according to the classification performance. Features derived from the continuous wavelet transform are potentially strongly correlated. GA-s that do not take the correlation structure of features into account are inefficient. The proposed algorithm forms clusters of correlated features and searches for a good candidate set of clusters. Secondly a search within the clusters is performed. Different simulations of the algorithm on a real-case data set with strong correlations between features show the increased classification performance. Comparison is performed with a standard GA without use of the correlation structure.

Keywords: Classification, genetic algorithm, hierarchicalagglomerative clustering, wavelet transform.

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3754 Modeling Language for Constructing Solvers in Machine Learning: Reductionist Perspectives

Authors: Tsuyoshi Okita

Abstract:

For a given specific problem an efficient algorithm has been the matter of study. However, an alternative approach orthogonal to this approach comes out, which is called a reduction. In general for a given specific problem this reduction approach studies how to convert an original problem into subproblems. This paper proposes a formal modeling language to support this reduction approach in order to make a solver quickly. We show three examples from the wide area of learning problems. The benefit is a fast prototyping of algorithms for a given new problem. It is noted that our formal modeling language is not intend for providing an efficient notation for data mining application, but for facilitating a designer who develops solvers in machine learning.

Keywords: Formal language, statistical inference problem, reduction.

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3753 Hexavalent Chromium Pollution Abatement by use of Scrap Iron

Authors: Marius Gheju, Laura Cocheci

Abstract:

In this study, the reduction of Cr(VI) by use of scrap iron, a cheap and locally available industrial waste, was investigated in continuous system. The greater scrap iron efficiency observed for the first two sections of the column filling indicate that most of the reduction process was carried out in the bottom half of the column filling. This was ascribed to a constant decrease of Cr(VI) concentration inside the filling, as the water front passes from the bottom to the top end of the column. While the bottom section of the column filling was heavily passivated with secondary mineral phases, the top section was less affected by the passivation process; therefore the column filling would likely ensure the reduction of Cr(VI) for time periods longer than 216 hours. The experimental results indicate that fixed beds columns packed with scrap iron could be successfully used for the first step of Cr(VI) polluted wastewater treatment. However, the mass of scrap iron filling should be carefully estimated since it significantly affects the Cr(VI) reduction efficiency.

Keywords: hexavalent chromium, heavy metals, scrap iron, reduction capacity, wastewater treatment

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3752 Relevance Feedback within CBIR Systems

Authors: Mawloud Mosbah, Bachir Boucheham

Abstract:

We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-nearest neighbors algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing color moments on the RGB space. This compact descriptor, Color Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.

Keywords: CBIR, Category Search, Relevance Feedback (RFB), Query Point Movement, Standard Rocchio’s Formula, Adaptive Shifting Query, Feature Weighting, Optimization of the Parameters of Similarity Metric, Original KNN, Incremental KNN.

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3751 Multiple Peaks Tracking Algorithm using Particle Swarm Optimization Incorporated with Artificial Neural Network

Authors: Mei Shan Ngan, Chee Wei Tan

Abstract:

Due to the non-linear characteristics of photovoltaic (PV) array, PV systems typically are equipped with the capability of maximum power point tracking (MPPT) feature. Moreover, in the case of PV array under partially shaded conditions, hotspot problem will occur which could damage the PV cells. Partial shading causes multiple peaks in the P-V characteristic curves. This paper presents a hybrid algorithm of Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN) MPPT algorithm for the detection of global peak among the multiple peaks in order to extract the true maximum energy from PV panel. The PV system consists of PV array, dc-dc boost converter controlled by the proposed MPPT algorithm and a resistive load. The system was simulated using MATLAB/Simulink package. The simulation results show that the proposed algorithm performs well to detect the true global peak power. The results of the simulations are analyzed and discussed.

Keywords: Photovoltaic (PV), Partial Shading, Maximum Power Point Tracking (MPPT), Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN)

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3750 Reduction Conditions of Briquetted Solid Wastes Generated by the Integrated Iron and Steel Plant

Authors: Gökhan Polat, Dicle Kocaoğlu Yılmazer, Muhlis Nezihi Sarıdede

Abstract:

Iron oxides are the main input to produce iron in integrated iron and steel plants. During production of iron from iron oxides, some wastes with high iron content occur. These main wastes can be classified as basic oxygen furnace (BOF) sludge, flue dust and rolling scale. Recycling of these wastes has a great importance for both environmental effects and reduction of production costs. In this study, recycling experiments were performed on basic oxygen furnace sludge, flue dust and rolling scale which contain 53.8%, 54.3% and 70.2% iron respectively. These wastes were mixed together with coke as reducer and these mixtures are pressed to obtain cylindrical briquettes. These briquettes were pressed under various compacting forces from 1 ton to 6 tons. Also, both stoichiometric and twice the stoichiometric cokes were added to investigate effect of coke amount on reduction properties of the waste mixtures. Then, these briquettes were reduced at 1000°C and 1100°C during 30, 60, 90, 120 and 150 min in a muffle furnace. According to the results of reduction experiments, the effect of compacting force, temperature and time on reduction ratio of the wastes were determined. It is found that 1 ton compacting force, 150 min reduction time and 1100°C are the optimum conditions to obtain reduction ratio higher than 75%.

Keywords: Iron oxide wastes, reduction, coke, recycling.

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3749 A Hypercube Social Feature Extraction and Multipath Routing in Delay Tolerant Networks

Authors: S. Balaji, M. Rajaram, Y. Harold Robinson, E. Golden Julie

Abstract:

Delay Tolerant Networks (DTN) which have sufficient state information include trajectory and contact information, to protect routing efficiency. However, state information is dynamic and hard to obtain without a global and/or long-term collection process. To deal with these problems, the internal social features of each node are introduced in the network to perform the routing process. This type of application is motivated from several human contact networks where people contact each other more frequently if they have more social features in common. Two unique processes were developed for this process; social feature extraction and multipath routing. The routing method then becomes a hypercube–based feature matching process. Furthermore, the effectiveness of multipath routing is evaluated and compared to that of single-path routing.

Keywords: Delay tolerant networks, entropy, human contact networks, hyper cubes, multipath Routing, social features.

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3748 Simultaneous Clustering and Feature Selection Method for Gene Expression Data

Authors: T. Chandrasekhar, K. Thangavel, E. N. Sathishkumar

Abstract:

Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins. This method is used to analysis the gene expression, an important task in bioinformatics research. Cluster analysis of gene expression data has proved to be a useful tool for identifying co-expressed genes, biologically relevant groupings of genes and samples. In this work K-Means algorithms has been applied for clustering of Gene Expression Data. Further, rough set based Quick reduct algorithm has been applied for each cluster in order to select the most similar genes having high correlation. Then the ACV measure is used to evaluate the refined clusters and classification is used to evaluate the proposed method. They could identify compact clusters with feature selection method used to genes are selected.

Keywords: Clustering, Feature selection, Gene expression data, Quick reduct.

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3747 Amino Acid Coated Silver Nanoparticles: A Green Catalyst for Methylene Blue Reduction

Authors: Abhishek Chandra, Man Singh

Abstract:

Highly stable and homogeneously dispersed amino acid coated silver nanoparticles (ANP) of ≈ 10 nm diameter, ranging from 420 to 430 nm are prepared on AgNO3 solution addition to gum of Azadirachta indica solution at 373.15 K. The amino acids were selected based on their polarity. The synthesized nanoparticles were characterized by UV-Vis, FTIR spectroscopy, HR-TEM, XRD, SEM and 1H-NMR. The coated nanoparticles were used as catalyst for the reduction of methylene blue dye in presence of Sn(II) in aqueous, anionic and cationic micellar media. The rate of reduction of dye was determined by measuring the absorbance at 660 nm, spectrophotometrically and followed the order: Kcationic > Kanionic > Kwater. After 12 min and in absence of the ANP, only 2%, 3% and 6% of the dye reduction was completed in aqueous, anionic and cationic micellar media respectively while, in presence of ANP coated by polar neutral amino acid with non-polar -R group, the reduction completed to 84%, 95% and 98% respectively. The ANP coated with polar neutral amino acid having non-polar -R group, increased the rate of reduction of the dye by 94, 3205 and 6370 folds in aqueous, anionic and cationic micellar media respectively. Also, the rate of reduction of the dye increased by three folds when the micellar media was changed from anionic to cationic when the ANP is coated by a polar neutral amino acid having a non-polar -R group.

Keywords: Silver nanoparticle, surfactant, methylene blue, amino acid.

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3746 Reduction of Peak Input Currents during Charge Pump Boosting in Monolithically Integrated High-Voltage Generators

Authors: Jan Doutreloigne

Abstract:

This paper describes two methods for the reduction of the peak input current during the boosting of Dickson charge pumps. Both methods are implemented in the fully integrated Dickson charge pumps of a high-voltage display driver chip for smart-card applications. Experimental results reveal good correspondence with Spice simulations and show a reduction of the peak input current by a factor of 6 during boosting.

Keywords: Bi-stable display driver, Dickson charge pump, highvoltage generator, peak current reduction, sub-pump boosting, variable frequency boosting.

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3745 Ecological Risk Assessment of Heavy Metals in Contaminated Soil from a Point Source

Authors: S. A. Nta

Abstract:

The study assessed the levels of some heavy metals in the contaminated soil from a point source using pollution indices to measure the extent of pollution. The soil used was sandy-loam in texture. The contaminant used was landfill leachate, introduced as a point source through an entry point positioned at the center of top layer of the soil tank. Samples were collected after 50 days and analyzed for heavy metal (Zn, Ni, Cu and Cd) using standard methods. The mean concentration of Ni ranged from 5.55-2.65 mg/kg, Zn 3.67-0.85 mg/kg, Cu 1.60-0.93 mg/kg and Cd 1.60-0.15 mg/kg. The richness of metals was in decreasing order: Ni > Zn > Cu > Cd. The metals concentration was found to be maximum at 0.25 m radial distance from the point of leachate application. The geo-accumulation index (Igeo) studied revealed that all the metals recovered at 0.25 and 0.50 m radial distance and at 0.15, 0.30, 0.45 and 0.60 m depth from the point of application of leachate fall under unpolluted to moderately polluted range. Ecological risk assessment showed high ecological risk index with values higher than RI > 300. The RI shows that the ecological risk in this study was mostly contributed by Cd ranging from 9-96.

Keywords: Ecological risk, assessment, heavy metals, test soils, landfill leachate.

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3744 Integrated ACOR/IACOMV-R-SVM Algorithm

Authors: Hiba Basim Alwan, Ku Ruhana Ku-Mahamud

Abstract:

A direction for ACO is to optimize continuous and mixed (discrete and continuous) variables in solving problems with various types of data. Support Vector Machine (SVM), which originates from the statistical approach, is a present day classification technique. The main problems of SVM are selecting feature subset and tuning the parameters. Discretizing the continuous value of the parameters is the most common approach in tuning SVM parameters. This process will result in loss of information which affects the classification accuracy. This paper presents two algorithms that can simultaneously tune SVM parameters and select the feature subset. The first algorithm, ACOR-SVM, will tune SVM parameters, while the second IACOMV-R-SVM algorithm will simultaneously tune SVM parameters and select the feature subset. Three benchmark UCI datasets were used in the experiments to validate the performance of the proposed algorithms. The results show that the proposed algorithms have good performances as compared to other approaches.

Keywords: Continuous ant colony optimization, incremental continuous ant colony, simultaneous optimization, support vector machine.

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3743 Multivariable System Reduction Using Stability Equation Method and SRAM

Authors: D. Bala Bhaskar

Abstract:

An algorithm is proposed for the order reduction of large scale linear dynamic multi variable systems where the reduced order model denominator is obtained by using Stability equation method and numerator coefficients are obtained by using SRAM. The proposed algorithm produces a lower order model for an original stable high order multivariable system. The reduction procedure is easy to understand, efficient and computer oriented. To highlight the advantages of the approach, the algorithm is illustrated with the help of a numerical example and the results are compared with the other existing techniques in literature.

Keywords: Multi variable systems, order reduction, stability equation method, SRAM, time domain characteristics, ISE.

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3742 Industrial Compressor Anti-Surge Computer Control

Authors: Ventzas Dimitrios, Petropoulos George

Abstract:

The paper presents a compressor anti-surge control system, that results in maximizing compressor throughput with pressure standard deviation reduction, increased safety margin between design point and surge limit line and avoiding possible machine surge. Alternative control strategies are presented.

Keywords: Anti-surge, control, compressor, PID control, safety, fault tolerance, start-up, ESD.

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3741 Axisymmetric Nonlinear Analysis of Point Supported Shallow Spherical Shells

Authors: M. Altekin, R. F. Yükseler

Abstract:

Geometrically nonlinear axisymmetric bending of a shallow spherical shell with a point support at the apex under linearly varying axisymmetric load was investigated numerically. The edge of the shell was assumed to be simply supported or clamped. The solution was obtained by the finite difference and the Newton-Raphson methods. The thickness of the shell was considered to be uniform and the material was assumed to be homogeneous and isotropic. Sensitivity analysis was made for two geometrical parameters. The accuracy of the algorithm was checked by comparing the deflection with the solution of point supported circular plates and good agreement was obtained.

Keywords: Bending, nonlinear, plate, point support, shell.

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3740 A Reconfigurable Processing Element for Cholesky Decomposition and Matrix Inversion

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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3739 Mammogram Image Size Reduction Using 16-8 bit Conversion Technique

Authors: Ayman A. AbuBaker, Rami S.Qahwaji, Musbah J. Aqel, Mohmmad H. Saleh

Abstract:

Two algorithms are proposed to reduce the storage requirements for mammogram images. The input image goes through a shrinking process that converts the 16-bit images to 8-bits by using pixel-depth conversion algorithm followed by enhancement process. The performance of the algorithms is evaluated objectively and subjectively. A 50% reduction in size is obtained with no loss of significant data at the breast region.

Keywords: Breast cancer, Image processing, Image reduction, Mammograms, Image enhancement

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3738 Heterogeneous Attribute Reduction in Noisy System based on a Generalized Neighborhood Rough Sets Model

Authors: Siyuan Jing, Kun She

Abstract:

Neighborhood Rough Sets (NRS) has been proven to be an efficient tool for heterogeneous attribute reduction. However, most of researches are focused on dealing with complete and noiseless data. Factually, most of the information systems are noisy, namely, filled with incomplete data and inconsistent data. In this paper, we introduce a generalized neighborhood rough sets model, called VPTNRS, to deal with the problem of heterogeneous attribute reduction in noisy system. We generalize classical NRS model with tolerance neighborhood relation and the probabilistic theory. Furthermore, we use the neighborhood dependency to evaluate the significance of a subset of heterogeneous attributes and construct a forward greedy algorithm for attribute reduction based on it. Experimental results show that the model is efficient to deal with noisy data.

Keywords: attribute reduction, incomplete data, inconsistent data, tolerance neighborhood relation, rough sets

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3737 The Utility of Wavelet Transform in Surface Electromyography Feature Extraction -A Comparative Study of Different Mother Wavelets

Authors: Farzaneh Akhavan Mahdavi, Siti Anom Ahmad, Mohd Hamiruce Marhaban, Mohammad-R. Akbarzadeh-T

Abstract:

Electromyography (EMG) signal processing has been investigated remarkably regarding various applications such as in rehabilitation systems. Specifically, wavelet transform has served as a powerful technique to scrutinize EMG signals since wavelet transform is consistent with the nature of EMG as a non-stationary signal. In this paper, the efficiency of wavelet transform in surface EMG feature extraction is investigated from four levels of wavelet decomposition and a comparative study between different mother wavelets had been done. To recognize the best function and level of wavelet analysis, two evaluation criteria, scatter plot and RES index are recruited. Hereupon, four wavelet families, namely, Daubechies, Coiflets, Symlets and Biorthogonal are studied in wavelet decomposition stage. Consequently, the results show that only features from first and second level of wavelet decomposition yields good performance and some functions of various wavelet families can lead to an improvement in separability class of different hand movements.

Keywords: Electromyography signal, feature extraction, wavelettransform, means absolute value.

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3736 Practical Method for Digital Music Matching Robust to Various Sound Qualities

Authors: Bokyung Sung, Jungsoo Kim, Jinman Kwun, Junhyung Park, Jihye Ryeo, Ilju Ko

Abstract:

In this paper, we propose a practical digital music matching system that is robust to variation in sound qualities. The proposed system is subdivided into two parts: client and server. The client part consists of the input, preprocessing and feature extraction modules. The preprocessing module, including the music onset module, revises the value gap occurring on the time axis between identical songs of different formats. The proposed method uses delta-grouped Mel frequency cepstral coefficients (MFCCs) to extract music features that are robust to changes in sound quality. According to the number of sound quality formats (SQFs) used, a music server is constructed with a feature database (FD) that contains different sub feature databases (SFDs). When the proposed system receives a music file, the selection module selects an appropriate SFD from a feature database; the selected SFD is subsequently used by the matching module. In this study, we used 3,000 queries for matching experiments in three cases with different FDs. In each case, we used 1,000 queries constructed by mixing 8 SQFs and 125 songs. The success rate of music matching improved from 88.6% when using single a single SFD to 93.2% when using quadruple SFDs. By this experiment, we proved that the proposed method is robust to various sound qualities.

Keywords: Digital Music, Music Matching, Variation in Sound Qualities, Robust Matching method.

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