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

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.

Adaptive Sampling Algorithm for ANN-based Performance Modeling of Nano-scale CMOS Inverter

This paper presents an adaptive technique for generation of data required for construction of artificial neural network-based performance model of nano-scale CMOS inverter circuit. The training data are generated from the samples through SPICE simulation. The proposed algorithm has been compared to standard progressive sampling algorithms like arithmetic sampling and geometric sampling. The advantages of the present approach over the others have been demonstrated. The ANN predicted results have been compared with actual SPICE results. A very good accuracy has been obtained.

Molar Excess Volumes and Excess Isentropic Compressibilities of Ternary Mixtures Containing 2-Pyrrolidinone

Molar excess Volumes, VE ijk and speeds of sound , uijk of 2-pyrrolidinone (i) + benzene or toluene (j) + ethanol (k) ternary mixture have been measured as a function of composition at 308.15 K. The observed speeds of sound data have been utilized to determine excess isentropic compressiblities, ( E S κ )ijk of ternary (i + j + k) mixtures. Molar excess volumes, VE ijk and excess isentropic compressibilities, ( E S κ )ijk data have fitted to the Redlich-Kister equation to calculate ternary adjustable parameters and standard deviations. The Moelywn-Huggins concept (Huggins in Polymer 12: 389-399, 1971) of connectivity between the surfaces of the constituents of binary mixtures has been extended to ternary mixtures (using the concept of a connectivity parameter of third degree of molecules, 3ξ , which inturn depends on its topology) to obtain an expression that describes well the measured VE ijk and ( E S κ )ijk data.

Embedded Singly Diagonally Implicit Runge-Kutta –Nystrom Method Order 5(4) for the Integration of Special Second Order ODEs

In this paper a new embedded Singly Diagonally Implicit Runge-Kutta Nystrom fourth order in fifth order method for solving special second order initial value problems is derived. A standard set of test problems are tested upon and comparisons on the numerical results are made when the same set of test problems are reduced to first order systems and solved using the existing embedded diagonally implicit Runge-Kutta method. The results suggests the superiority of the new method.

Non-Rigid Registration of Medical Images Using an Automated Method

This paper presents the application of a signal intensity independent registration criterion for non-rigid body registration of medical images. The criterion is defined as the weighted ratio image of two images. The ratio is computed on a voxel per voxel basis and weighting is performed by setting the ratios between signal and background voxels to a standard high value. The mean squared value of the weighted ratio is computed over the union of the signal areas of the two images and it is minimized using the Chebyshev polynomial approximation. The geometric transformation model adopted is a local cubic B-splines based model.

Influence of Ambiguity Cluster on Quality Improvement in Image Compression

Image coding based on clustering provides immediate access to targeted features of interest in a high quality decoded image. This approach is useful for intelligent devices, as well as for multimedia content-based description standards. The result of image clustering cannot be precise in some positions especially on pixels with edge information which produce ambiguity among the clusters. Even with a good enhancement operator based on PDE, the quality of the decoded image will highly depend on the clustering process. In this paper, we introduce an ambiguity cluster in image coding to represent pixels with vagueness properties. The presence of such cluster allows preserving some details inherent to edges as well for uncertain pixels. It will also be very useful during the decoding phase in which an anisotropic diffusion operator, such as Perona-Malik, enhances the quality of the restored image. This work also offers a comparative study to demonstrate the effectiveness of a fuzzy clustering technique in detecting the ambiguity cluster without losing lot of the essential image information. Several experiments have been carried out to demonstrate the usefulness of ambiguity concept in image compression. The coding results and the performance of the proposed algorithms are discussed in terms of the peak signal-tonoise ratio and the quantity of ambiguous pixels.

Concrete Mix Design Using Neural Network

Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.

Calculation of the Ceramics Weibull Parameters

The paper deals with calculation of the parameters of ceramic material from a set of destruction tests of ceramic heads of total hip joint endoprosthesis. The standard way of calculation of the material parameters consists in carrying out a set of 3 or 4 point bending tests of specimens cut out from parts of the ceramic material to be analysed. In case of ceramic heads, it is not possible to cut out specimens of required dimensions because the heads are too small (if the cut out specimens were smaller than the normalised ones, the material parameters derived from them would exhibit higher strength values than those which the given ceramic material really has). On that score, a special testing jig was made, in which 40 heads were destructed. From the measured values of circumferential strains of the head-s external spherical surface under destruction, the state of stress in the head under destruction was established using the final elements method (FEM). From the values obtained, the sought for parameters of the ceramic material were calculated using Weibull-s weakest-link theory.

Transmission Lines Loading Enhancement Using ADPSO Approach

Discrete particle swarm optimization (DPSO) is a powerful stochastic evolutionary algorithm that is used to solve the large-scale, discrete and nonlinear optimization problems. However, it has been observed that standard DPSO algorithm has premature convergence when solving a complex optimization problem like transmission expansion planning (TEP). To resolve this problem an advanced discrete particle swarm optimization (ADPSO) is proposed in this paper. The simulation result shows that optimization of lines loading in transmission expansion planning with ADPSO is better than DPSO from precision view point.

Heat Stress Monitor by Using Low-Cost Temperature and Humidity Sensors

The aim of this study is to develop a cost-effective WBGT heat stress monitor which provides precise heat stress measurement. The proposed device employs SHT15 and DS18B20 as a temperature and humidity sensors, respectively, incorporating with ATmega328 microcontroller. The developed heat stress monitor was calibrated and adjusted to that of the standard temperature and humidity sensors in the laboratory. The results of this study illustrated that the mean percentage error and the standard deviation from the measurement of the globe temperature was 2.33 and 2.71 respectively, while 0.94 and 1.02 were those of the dry bulb temperature, 0.79 and 0.48 were of the wet bulb temperature, and 4.46 and 1.60 were of the relative humidity sensor. This device is relatively low-cost and the measurement error is acceptable.

Experimental Parallel Architecture for Rendering 3D Model into MPEG-4 Format

This paper will present the initial findings of a research into distributed computer rendering. The goal of the research is to create a distributed computer system capable of rendering a 3D model into an MPEG-4 stream. This paper outlines the initial design, software architecture and hardware setup for the system. Distributed computing means designing and implementing programs that run on two or more interconnected computing systems. Distributed computing is often used to speed up the rendering of graphical imaging. Distributed computing systems are used to generate images for movies, games and simulations. A topic of interest is the application of distributed computing to the MPEG-4 standard. During the course of the research, a distributed system will be created that can render a 3D model into an MPEG-4 stream. It is expected that applying distributed computing principals will speed up rendering, thus improving the usefulness and efficiency of the MPEG-4 standard

A New Voting Approach to Texture Defect Detection Based on Multiresolutional Decomposition

Wavelets have provided the researchers with significant positive results, by entering the texture defect detection domain. The weak point of wavelets is that they are one-dimensional by nature so they are not efficient enough to describe and analyze two-dimensional functions. In this paper we present a new method to detect the defect of texture images by using curvelet transform. Simulation results of the proposed method on a set of standard texture images confirm its correctness. Comparing the obtained results indicates the ability of curvelet transform in describing discontinuity in two-dimensional functions compared to wavelet transform

Computer Models of the Vestibular Head Tilt Response, and Their Relationship to EVestG and Meniere's Disease

This paper attempts to explain response components of Electrovestibulography (EVestG) using a computer simulation of a three-canal model of the vestibular system. EVestG is a potentially new diagnostic method for Meniere's disease. EVestG is a variant of Electrocochleography (ECOG), which has been used as a standard method for diagnosing Meniere's disease - it can be used to measure the SP/AP ratio, where an SP/AP ratio greater than 0.4-0.5 is indicative of Meniere-s Disease. In EVestG, an applied head tilt replaces the acoustic stimulus of ECOG. The EVestG output is also an SP/AP type plot, where SP is the summing potential, and AP is the action potential amplitude. AP is thought of as being proportional to the size of a population of afferents in an excitatory neural firing state. A simulation of the fluid volume displacement in the vestibular labyrinth in response to various types of head tilts (ipsilateral, backwards and horizontal rotation) was performed, and a simple neural model based on these simulations developed. The simple neural model shows that the change in firing rate of the utricle is much larger in magnitude than the change in firing rates of all three semi-circular canals following a head tilt (except in a horizontal rotation). The data suggests that the change in utricular firing rate is a minimum 2-3 orders of magnitude larger than changes in firing rates of the canals during ipsilateral/backward tilts. Based on these results, the neural response recorded by the electrode in our EVestG recordings is expected to be dominated by the utricle in ipsilateral/backward tilts (It is important to note that the effect of the saccule and efferent signals were not taken into account in this model). If the utricle response dominates the EVestG recordings as the modeling results suggest, then EVestG has the potential to diagnose utricular hair cell damage due to a viral infection (which has been cited as one possible cause of Meniere's Disease).

Innovation Knowledge and Capability, Work Efficiency of Accountants and the Success of SME Registered in Nakorn Pathom Province

The objectives of this research were to compare the success of SME registered in Nakorn Pathom Province divided in personal data also to study the relations between the innovation knowledge and capability and the success of SME registered in Nakorn Pathom Province and to study the relations between the work efficiency and the success of SME registered in Nakorn Pathom Province. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. Data were analyzed by using Statistical Package for the Social Sciences.The findings revealed that the majority of respondents were male with the age between 25-34 years old, hold undergraduate degree, married and stay together. The average income of respondents was between 10,001-20,000 baht. It also found that in terms of innovation knowledge and capability, there were two variables had an influence on the amount of innovation knowledge and capability, innovation evaluation which were physical characteristic and innovation process.

Stability Analysis of a Class of Nonlinear Systems Using Discrete Variable Structures and Sliding Mode Control

This paper presents the application of discrete-time variable structure control with sliding mode based on the 'reaching law' method for robust control of a 'simple inverted pendulum on moving cart' - a standard nonlinear benchmark system. The controllers designed using the above techniques are completely insensitive to parametric uncertainty and external disturbance. The controller design is carried out using pole placement technique to find state feedback gain matrix , which decides the dynamic behavior of the system during sliding mode. This is followed by feedback gain realization using the control law which is synthesized from 'Gao-s reaching law'. The model of a single inverted pendulum and the discrete variable structure control controller are developed, simulated in MATLAB-SIMULINK and results are presented. The response of this simulation is compared with that of the discrete linear quadratic regulator (DLQR) and the advantages of sliding mode controller over DLQR are also presented

Finite Element Modeling and Mechanical Properties of Aluminum Proceed by Equal Channel Angular Pressing Process

During the last decade ultrafine grained (UFG) and nano-structured (NS) materials have experienced a rapid development. In this research work finite element analysis has been carried out to investigate the plastic strain distribution in equal channel angular process (ECAP). The magnitudes of Standard deviation (S. D.) and inhomogeneity index (Ci) were compared for different ECAP passes. Verification of a three-dimensional finite element model was performed with experimental tests. Finally the mechanical property including impact energy of ultrafine grained pure commercially pure Aluminum produced by severe plastic deformation method has been examined. For this aim, equal channel angular pressing die with the channel angle, outer corner angle and channel diameter of 90°, 20° and 20mm had been designed and manufactured. Commercial pure Aluminum billets were ECAPed up to four passes by route BC at the ambient temperature. The results indicated that there is a great improvement at the hardness measurement, yield strength and ultimate tensile strength after ECAP process. It is found that the magnitudes of HV reach 67HV from 21HV after the final stage of process. Also, about 330% and 285% enhancement at the YS and UTS values have been obtained after the fourth pass as compared to the as-received conditions, respectively. On the other hand, the elongation to failure and impact energy have been reduced by 23% and 50% after imposing four passes of ECAP process, respectively.

Hybrid Machine Learning Approach for Text Categorization

Text categorization - the assignment of natural language documents to one or more predefined categories based on their semantic content - is an important component in many information organization and management tasks. Performance of neural networks learning is known to be sensitive to the initial weights and architecture. This paper discusses the use multilayer neural network initialization with decision tree classifier for improving text categorization accuracy. An adaptation of the algorithm is proposed in which a decision tree from root node until a final leave is used for initialization of multilayer neural network. The experimental evaluation demonstrates this approach provides better classification accuracy with Reuters-21578 corpus, one of the standard benchmarks for text categorization tasks. We present results comparing the accuracy of this approach with multilayer neural network initialized with traditional random method and decision tree classifiers.

Orthogonal Array Application and Response Surface Method Approach for Optimal Product Values: An Application for Oil Blending Process

This paper presents a methodical approach for designing and optimizing process parameters in oil blending industries. Twenty seven replicated experiments were conducted for production of A-Z crown super oil (SAE20W/50) employing L9 orthogonal array to establish process response parameters. Power law model was fitted to experimental data and the obtained model was optimized applying the central composite design (CCD) of response surface methodology (RSM). Quadratic model was found to be significant for production of A-Z crown supper oil. The study recognized and specified four new lubricant formulations that conform to ISO oil standard in the course of analyzing the batch productions of A-Z crown supper oil as: L1: KV = 21.8293Cst, BS200 = 9430.00Litres, Ad102=11024.00Litres, PVI = 2520 Litres, L2: KV = 22.513Cst, BS200 = 12430.00 Litres, Ad102 = 11024.00 Litres, PVI = 2520 Litres, L3: KV = 22.1671Cst, BS200 = 9430.00 Litres, Ad102 = 10481.00 Litres, PVI= 2520 Litres, L4: KV = 22.8605Cst, BS200 = 12430.00 Litres, Ad102 = 10481.00 Litres, PVI = 2520 Litres. The analysis of variance showed that quadratic model is significant for kinematic viscosity production while the R-sq value statistic of 0.99936 showed that the variation of kinematic viscosity is due to its relationship with the control factors. This study therefore resulted to appropriate blending proportions of lubricants base oil and additives and recommends the optimal kinematic viscosity of A-Z crown super oil (SAE20W/50) to be 22.86Cst.

Using Quality Models to Evaluate National ID systems: the Case of the UAE

This paper presents findings from the evaluation study carried out to review the UAE national ID card software. The paper consults the relevant literature to explain many of the concepts and frameworks explained herein. The findings of the evaluation work that was primarily based on the ISO 9126 standard for system quality measurement highlighted many practical areas that if taken into account is argued to more likely increase the success chances of similar system implementation projects.

DTC-SVM Scheme for Induction Motors Fedwith a Three-level Inverter

Direct Torque Control is a control technique in AC drive systems to obtain high performance torque control. The conventional DTC drive contains a pair of hysteresis comparators. DTC drives utilizing hysteresis comparators suffer from high torque ripple and variable switching frequency. The most common solution to those problems is to use the space vector depends on the reference torque and flux. In this Paper The space vector modulation technique (SVPWM) is applied to 2 level inverter control in the proposed DTC-based induction motor drive system, thereby dramatically reducing the torque ripple. Then the controller based on space vector modulation is designed to be applied in the control of Induction Motor (IM) with a three-level Inverter. This type of Inverter has several advantages over the standard two-level VSI, such as a greater number of levels in the output voltage waveforms, Lower dV/dt, less harmonic distortion in voltage and current waveforms and lower switching frequencies. This paper proposes a general SVPWM algorithm for three-level based on standard two-level SVPWM. The proposed scheme is described clearly and simulation results are reported to demonstrate its effectiveness. The entire control scheme is implemented with Matlab/Simulink.