Search results for: Matlab and Noise speech.

Authors: Abhijit Mitra

Abstract:

This paper proposes an efficient finite precision block floating point (BFP) treatment to the fixed coefficient finite impulse response (FIR) digital filter. The treatment includes effective implementation of all the three forms of the conventional FIR filters, namely, direct form, cascaded and par- allel, and a roundoff error analysis of them in the BFP format. An effective block formatting algorithm together with an adaptive scaling factor is pro- posed to make the realizations more simple from hardware view point. To this end, a generic relation between the tap weight vector length and the input block length is deduced. The implementation scheme also emphasises on a simple block exponent update technique to prevent overflow even during the block to block transition phase. The roundoff noise is also investigated along the analogous lines, taking into consideration these implementational issues. The simulation results show that the BFP roundoff errors depend on the sig- nal level almost in the same way as floating point roundoff noise, resulting in approximately constant signal to noise ratio over a relatively large dynamic range.

Keywords: Finite impulse response digital filters, Cascade structure, Parallel structure, Block floating point arithmetic, Roundoff error.

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Authors: M. Zerikat, S. Chekroun

Abstract:

This paper proposes an effective adaptation learning algorithm based on artificial neural networks for speed control of an induction motor assumed to operate in a high-performance drives environment. The structure scheme consists of a neural network controller and an algorithm for changing the NN weights in order that the motor speed can accurately track of the reference command. This paper also makes uses a very realistic and practical scheme to estimate and adaptively learn the noise content in the speed load torque characteristic of the motor. The availability of the proposed controller is verified by through a laboratory implementation and under computation simulations with Matlab-software. The process is also tested for the tracking property using different types of reference signals. The performance and robustness of the proposed control scheme have evaluated under a variety of operating conditions of the induction motor drives. The obtained results demonstrate the effectiveness of the proposed control scheme system performances, both in steady state error in speed and dynamic conditions, was found to be excellent and those is not overshoot.

Keywords: Electric drive, Induction motor, speed control, Adaptive control, neural network, High Performance.

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Authors: Ioannis Neokosmidis, Nikos Gkekas, Thomas Kamalakis, Thomas Sphicopoulos

Abstract:

In high powered dense wavelength division multiplexed (WDM) systems with low chromatic dispersion, four-wave mixing (FWM) can prove to be a major source of noise. The MultiCanonical Monte Carlo Method (MCMC) and the Split Step Fourier Method (SSFM) are combined to accurately evaluate the probability density function of the decision variable of a receiver, limited by FWM. The combination of the two methods leads to more accurate results, and offers the possibility of adding other optical noises such as the Amplified Spontaneous Emission (ASE) noise.

Keywords: Monte Carlo, Nonlinear optics, optical crosstalk, Wavelength-division Multiplexing (WDM).

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Authors: Doaa Hegazy, Joachim Denzler

Abstract:

SoftBoost is a recently presented boosting algorithm, which trades off the size of achieved classification margin and generalization performance. This paper presents a performance evaluation of SoftBoost algorithm on the generic object recognition problem. An appearance-based generic object recognition model is used. The evaluation experiments are performed using a difficult object recognition benchmark. An assessment with respect to different degrees of label noise as well as a comparison to the well known AdaBoost algorithm is performed. The obtained results reveal that SoftBoost is encouraged to be used in cases when the training data is known to have a high degree of noise. Otherwise, using Adaboost can achieve better performance.

Keywords: SoftBoost algorithm, AdaBoost algorithm, Generic object recognition.

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Authors: Youssef Khmou, Said Safi

Abstract:

In this paper, a fifth order propagator operators are proposed for estimating the Angles Of Arrival (AOA) of narrowband electromagnetic waves impinging on antenna array when its number of sensors is larger than the number of radiating sources.

The array response matrix is partitioned into five linearly dependent phases to construct the noise projector using five different propagators from non diagonal blocks of the spectral matrice of the received data; hence, five different estimators are proposed to estimate the angles of the sources. The simulation results proved the performance of the proposed estimators in the presence of white noise comparatively to high resolution eigen based spectra.

Keywords: DOA, narrowband, antenna, propagator, high resolution. Array, operator, angular, spectrum, goniometry.

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Authors: S. Selvaperumal, M. S. Sivagamasundari

Abstract:

In this paper, selective harmonic elimination pulse width modulation technique is employed to eliminate lower order harmonics like third by determination of solving non-linear equations. The cascaded H-bridge five level inverter is driven by the Peripheral Interface Controlled (PIC) Microcontroller 16F877A. The performance of single phase cascaded H-bridge five level inverter with relevant to harmonics and a variety of switches with solar cell as its input source is simulated by employing MATLAB/Simulink. A hardware model is developed to verify the performance of the developed system.

Keywords: Multilevel inverter, cascaded H-Bridge multilevel inverter, total harmonic distortion, selective harmonic elimination pulse width modulation, MATLAB.

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Authors: Mahesh Pal

Abstract:

In recent years, a number of works proposing the combination of multiple classifiers to produce a single classification have been reported in remote sensing literature. The resulting classifier, referred to as an ensemble classifier, is generally found to be more accurate than any of the individual classifiers making up the ensemble. As accuracy is the primary concern, much of the research in the field of land cover classification is focused on improving classification accuracy. This study compares the performance of four ensemble approaches (boosting, bagging, DECORATE and random subspace) with a univariate decision tree as base classifier. Two training datasets, one without ant noise and other with 20 percent noise was used to judge the performance of different ensemble approaches. Results with noise free data set suggest an improvement of about 4% in classification accuracy with all ensemble approaches in comparison to the results provided by univariate decision tree classifier. Highest classification accuracy of 87.43% was achieved by boosted decision tree. A comparison of results with noisy data set suggests that bagging, DECORATE and random subspace approaches works well with this data whereas the performance of boosted decision tree degrades and a classification accuracy of 79.7% is achieved which is even lower than that is achieved (i.e. 80.02%) by using unboosted decision tree classifier.

Keywords: Ensemble learning, decision tree, remote sensingclassification.

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Authors: Prasannakumar Palaniappan, Dong Ho Shin, Chul Gyu Song

Abstract:

The photoacoustic images are obtained from a custom developed linear array photoacoustic tomography system. The biological specimens are imitated by conducting phantom tests in order to retrieve a fully functional photoacoustic image. The acquired image undergoes the active region based contour filtering to remove the noise and accurately segment the object area for further processing. The universal back projection method is used as the image reconstruction algorithm. The active contour filtering is analyzed by evaluating the signal to noise ratio and comparing it with the other filtering methods.

Keywords: Contour filtering, linear array, photoacoustic tomography, universal back projection.

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Authors: Naveed Ur Rehman, Rehan Jamil, Irfan Jamil

Abstract:

In this paper, we regard as a coded transmission over a frequency-selective channel. We plan to study analytically the convergence of the turbo-detector using a maximum a posteriori (MAP) equalizer and a MAP decoder. We demonstrate that the densities of the maximum likelihood (ML) exchanged during the iterations are e-symmetric and output-symmetric. Under the Gaussian approximation, this property allows to execute a one-dimensional scrutiny of the turbo-detector. By deriving the analytical terminology of the ML distributions under the Gaussian approximation, we confirm that the bit error rate (BER) performance of the turbo-detector converges to the BER performance of the coded additive white Gaussian noise (AWGN) channel at high signal to noise ratio (SNR), for any frequency selective channel.

Keywords: MAP, ML, SNR, Decoder, BER, Coded transmission.

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Authors: JongKuk Kim, HernSoo Hahn, Uei-Joong Yoo, MyungJin Bae

Abstract:

In this paper, we propose a method of alter duration in frequency domain that control prosody in real time after pitch alteration. If there has a method to alteration duration freely among prosody information, that may used in several fields such as speech impediment person's pronunciation proof reading or language study. The pitch alteration method used control prosody altered by PSOLA synthesis method which is in time domain processing method. However, the duration of pitch alteration speech is changed by the frequency domain. In this paper, we altered the duration with the method of duration alteration by Fast Fourier Transformation in frequency domain. Consequently, the intelligibility of the pitch and duration are controlled has a slight decrease than the case when only pitch is changed, but the proposed algorithm obtained the higher MOS score about naturalness.

Keywords: PSOLA, Pitch Alteration, Duration Control.

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Authors: T. Y. Liu, C. H Lin., Y. M Ferng

Abstract:

Wind energy is one of the clean renewable energy. However, the low frequency (20-200HZ) noise generated from the wind turbine blades, which bothers the residents, becomes the major problem to be developed. It is useful for predicting the aerodynamic noise by flow field and pressure distribution analysis on the wind turbine blades. Therefore, the main objective of this study is to use different turbulence models to analyze the flow field and pressure distributions of the wing blades.

Three-dimensional Computation Fluid Dynamics (CFD) simulation of the flow field was used to calculate the flow phenomena for the National Renewable Energy Laboratory (NREL) Phase VI horizontal axis wind turbine rotor. Two different flow cases with different wind speeds were investigated: 7m/s with 72rpm and 15m/s with 72rpm.

Four kinds of RANS-based turbulence models, Standard k-ε, Realizable k-ε, SST k-ω, and v2f, were used to predict and analyze the results in the present work. The results show that the predictions on pressure distributions with SST k-ω and v2f turbulence models have good agreements with experimental data.

Keywords: Horizontal Axis Wind Turbine, turbulence model, noise.

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Authors: Adnan Al-Smadi

Abstract:

One of the primary uses of higher order statistics in signal processing has been for detecting and estimation of non- Gaussian signals in Gaussian noise of unknown covariance. This is motivated by the ability of higher order statistics to suppress additive Gaussian noise. In this paper, several methods to test for non- Gaussianity of a given process are presented. These methods include histogram plot, kurtosis test, and hypothesis testing using cumulants and bispectrum of the available sequence. The hypothesis testing is performed by constructing a statistic to test whether the bispectrum of the given signal is non-zero. A zero bispectrum is not a proof of Gaussianity. Hence, other tests such as the kurtosis test should be employed. Examples are given to demonstrate the performance of the presented methods.

Keywords: Non-Gaussian, bispectrum, kurtosis, hypothesistesting, histogram.

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Authors: Edward P. Guillen, Julián J. López, Cesar Y. Barahona

Abstract:

Powerline Communications –PLC– as an alternative method for broadband networking, has the advantage of transmitting over channels already used for electrical distribution or even transmission. But these channels have been not designed with usual wired channels requirements for broadband applications such as stable impedance or known attenuation, and the network have to reject noises caused by electrical appliances that share the same channel. Noise control standards are difficult to complain or simply do not exist on Latin-American environments. This paper analyzes PLC throughput for home connectivity by probing noisy channel scenarios in a PLC network and the statistical results are shown.

Keywords: Power Line Communications, OFDM, Noise Analysis, Throughput Analysis, PLC, Home Network.

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Authors: Jyh-Da Wei, Hsin-Chen Tsai

Abstract:

This work presents a novel means of extracting fixedlength parameters from voice signals, such that words can be recognized in linear time. The power and the zero crossing rate are first calculated segment by segment from a voice signal; by doing so, two feature sequences are generated. We then construct an FIR system across these two sequences. The parameters of this FIR system, used as the input of a multilayer proceptron recognizer, can be derived by recursive LSE (least-square estimation), implying that the complexity of overall process is linear to the signal size. In the second part of this work, we introduce a weighting factor λ to emphasize recent input; therefore, we can further recognize continuous speech signals. Experiments employ the voice signals of numbers, from zero to nine, spoken in Mandarin Chinese. The proposed method is verified to recognize voice signals efficiently and accurately.

Keywords: Speech Recognition, FIR system, Recursive LSE, Multilayer Perceptron

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Authors: Youguo Wang, Lenan Wu

Abstract:

Stochastic resonance (SR) is a phenomenon whereby the signal transmission or signal processing through certain nonlinear systems can be improved by adding noise. This paper discusses SR in nonlinear signal detection by a simple test statistic, which can be computed from multiple noisy data in a binary decision problem based on a maximum a posteriori probability criterion. The performance of detection is assessed by the probability of detection error Per . When the input signal is subthreshold signal, we establish that benefit from noise can be gained for different noises and confirm further that the subthreshold SR exists in nonlinear signal detection. The efficacy of SR is significantly improved and the minimum of Per can dramatically approach to zero as the sample number increases. These results show the robustness of SR in signal detection and extend the applicability of SR in signal processing.

Keywords: Probability of detection error, signal detection, stochastic resonance.

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Authors: Assem M. F. Sallam, Ah. El-S. Makled

Abstract:

In this paper, there is an implementation, verification, and graphical demonstration of a software application, which can be used swiftly over different preliminary orbit determination methods. A passive orbit determination method is used in this study to determine the location of a satellite or a flying body. It is named a passive orbit determination because it depends on observation without the use of any aids (radio and laser) installed on satellite. In order to understand how these methods work and how their output is accurate when compared with available verification data, the built models help in knowing the different inputs used with each method. Output from the different orbit determination methods (Gibbs, Lambert, and Gauss) will be compared with each other and verified by the data obtained from Satellite Tool Kit (STK) application. A modified model including all of the orbit determination methods using the same input will be introduced to investigate different models output (orbital parameters) for the same input (azimuth, elevation, and time). Simulation software is implemented using MATLAB. A Graphical User Interface (GUI) application named OrDet is produced using the GUI of MATLAB. It includes all the available used inputs and it outputs the current Classical Orbital Elements (COE) of satellite under observation. Produced COE are then used to propagate for a complete revolution and plotted on a 3-D view. Modified model which uses an adapter to allow same input parameters, passes these parameters to the preliminary orbit determination methods under study. Result from all orbit determination methods yield exactly the same COE output, which shows the equality of concept in determination of satellite’s location, but with different numerical methods.

Keywords: Orbit determination, STK, MATLAB-GUI, satellite tracking.

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Authors: K. Abuzayan, H. Alabed, K. Zarug

Abstract:

The objectives of this study (baseline study, n = 20) were to implement Matlab procedures for quantifying selected static  balance variables, establish baseline data of selected variables which characterize static balance activities in a population of healthy young adult males, and to examine any trial effects on these variables. The results indicated that the implementation of Matlab procedures for quantifying selected static balance variables was practical and enabled baseline data to be established for selected variables. There was no significant trial effect. Recommendations were made for suitable tests to be used in later studies. Specifically it was found that one foot-tiptoes tests either in static balance is too challenging for most participants in normal circumstances. A one foot-flat eyes open test was considered to be representative and challenging for static balance.

Keywords: Static Balance, Base of support, Baseline Data.

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Authors: Padmakumar S., Vivek Agarwal, Kallol Roy

Abstract:

With the advent of inexpensive 32 bit floating point digital signal processor-s availability in market, many computationally intensive algorithms such as Kalman filter becomes feasible to implement in real time. Dynamic simulation of a self excited DC motor using second order state variable model and implementation of Kalman Filter in a floating point DSP TMS320C6713 is presented in this paper with an objective to introduce and implement such an algorithm, for beginners. A fractional hp DC motor is simulated in both Matlab® and DSP and the results are included. A step by step approach for simulation of DC motor in Matlab® and “C" routines in CC Studio® is also given. CC studio® project file details and environmental setting requirements are addressed. This tutorial can be used with 6713 DSK, which is based on floating point DSP and CC Studio either in hardware mode or in simulation mode.

Keywords: DC motor, DSP, Dynamic simulation, Kalman Filter

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Authors: J. Y. Lee, J. Kim, H. J. Chang, J. M. Kim

Abstract:

People’s tendency towards living in apartment houses is increasing in a densely populated country. However, some residents living in apartment houses are bothered by noise coming from the houses above. In order to reduce noise pollution, the communities are increasingly imposing a bylaw, including the limitation of floor impact sound, minimum thickness of floors, and floor soundproofing solutions. This research effort focused on the specific long-time deflection of resilient materials in the floor sound insulation systems of apartment houses. The experimental program consisted of testing nine floor sound insulation specimens subjected to sustained load for 45 days. Two main parameters were considered in the experimental investigation: three types of resilient materials and magnitudes of loads. The test results indicated that the structural behavior of the floor sound insulation systems under long-time load was quite different from that the systems under short-time load. The loading period increased the deflection of floor sound insulation systems and the increasing rate of the long-time deflection of the systems with ethylene vinyl acetate was smaller than that of the systems with low density ethylene polystyrene.

Keywords: Resilient materials, floor sound insulation systems, long-time deflection, sustained load, noise pollution.

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Authors: Md Monir Hossain, Anne Staples, Kuya Takami, Tomonari Furukawa

Abstract:

Tire noise has a significant impact on ride quality and vehicle interior comfort, even at low frequency. Reduction of tire noise is especially important due to strict state and federal environmental regulations. The primary sources of tire noise are the low frequency structure-borne noise and the noise that originates from the release of trapped air between the tire tread and road surface during each revolution of the tire. The frequency response of the tire changes at low and high frequency. At low frequency, the tension and bending moment become dominant, while the internal structure and local deformation become dominant at higher frequencies. Here, we analyze tire response in terms of deformation and rolling velocity at low revolution frequency. An Abaqus FEA finite element model is used to calculate the static and dynamic response of a rolling tire under different rolling conditions. The natural frequencies and mode shapes of a deformed tire are calculated with the FEA package where the subspace-based steady state dynamic analysis calculates dynamic response of tire subjected to harmonic excitation. The analysis was conducted on the dynamic response at the road (contact point of tire and road surface) and side nodes of a static and rolling tire when the tire was excited with 200 N vertical load for a frequency ranging from 20 to 200 Hz. The results show that frequency has little effect on tire deformation up to 80 Hz. But between 80 and 200 Hz, the radial and lateral components of displacement of the road and side nodes exhibited significant oscillation. For the static analysis, the fluctuation was sharp and frequent and decreased with frequency. In contrast, the fluctuation was periodic in nature for the dynamic response of the rolling tire. In addition to the dynamic analysis, a steady state rolling analysis was also performed on the tire traveling at ground velocity with a constant angular motion. The purpose of the computation was to demonstrate the effect of rotating motion on deformation and rolling velocity with respect to a fixed Newtonian reference point. The analysis showed a significant variation in deformation and rolling velocity due to centrifugal and Coriolis acceleration with respect to a fixed Newtonian point on ground.

Keywords: Natural frequency, rotational motion, steady state rolling, subspace-based steady state dynamic analysis.

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Authors: R. Prakash, B. Meenakshipriya, R. Kumaravelan

Abstract:

Fresh water is one of the resources which is getting depleted day by day. A wise method to address this issue is by the application of renewable energy-sun irradiation and by means of decentralized, cheap, energetically self-sufficient, robust and simple to operate plants, distillates can be obtained from sea, river or even sewage. Solar desalination is a technique used to desalinate water using solar energy. The present work deals with the comprehensive design and simulation of solar tracking system using LabVIEW, temperature and mass flow rate control of the solar desalination plant using LabVIEW and also analysis of single phase inverter circuit with LC filters for solar pumping system in MATLAB. The main objective of this work is to improve the performance of solar desalination system using automatic tracking system, output control using temperature and mass flow rate control system and also to reduce the harmonic distortion in the solar pumping system by means of LC filters. The simulation of single phase inverter was carried out using MATLAB and the output waveforms were analyzed. Simulations were performed for optimum output temperature control, which in turn controls the mass flow rate of water in the thermal collectors. Solar tracking system was accomplished using LABVIEW and was tested successfully. The thermal collectors are tracked in accordance with the sun’s irradiance levels, thereby increasing the efficiency of the thermal collectors.

Keywords: Desalination, Electro dialysis, LabVIEW, MATLAB, PWM inverter, Reverse osmosis.

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Authors: Irtaza M. Syed, Kaamran Raahemifar

Abstract:

This paper presents a model predictive control (MPC) of a utility interactive (UI) single phase inverter (SPI) for a photovoltaic (PV) system at residential/distribution level. The proposed model uses single-phase phase locked loop (PLL) to synchronize SPI with the grid and performs MPC control in a dq reference frame. SPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a full bridge (FB) voltage source inverter (VSI). No PI regulators to tune and carrier and modulating waves are required to produce switching sequence. Instead, the operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a three kW PV system at the input of UI-SPI in Matlab/Simulink. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: Matlab/Simulink, Model Predictive Control, Phase Locked Loop, Single Phase Inverter, Voltage Source Inverter.

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Authors: Paula B. Harboe, Edilson da Silva, José R. Souza

Abstract:

This paper presents an investigation of the power penalties imposed by four-wave mixing (FWM) on G.652 (Single- Mode Fiber - SMF), G.653 (Dispersion-Shifted Fiber - DSF), and G.655 (Non-Zero Dispersion-Shifted Fiber - NZDSF) compliant fibers, considering the DWDM grids suggested by the ITU-T Recommendations G.692, and G.694.1, with uniform channel spacing of 100, 50, 25, and 12.5 GHz. The mathematical/numerical model assumes undepleted pumping, and shows very clearly the deleterious effect of FWM on the performance of DWDM systems, measured by the signal-to-noise ratio (SNR). The results make it evident that non-uniform channel spacing is practically mandatory for WDM systems based on DSF fibers.

Keywords: DWDM systems, Four-Wave Mixing (FWM), G.652, G.653, G.655 compliant fibers, Signal-to-noise ratio.

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Authors: Tetsuro Saeki, Yuichi Kato, Shoutarou Mizuno

Abstract:

STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table which is considered as a sample set obtained from the population of interest. Its usefulness has been confirmed by simulation experiments specifying rules in advance, and by comparison with conventional methods. However, scope for future development remains before STRIM can be applied to the analysis of real-world data sets. The first requirement is to determine the size of the dataset needed for inducting true rules, since finding statistically significant rules is the core of the method. The second is to examine the capacity of rule induction from datasets with contaminated attribute values created by missing data and noise, since real-world datasets usually contain such contaminated data. This paper examines the first problem theoretically, in connection with the rule length. The second problem is then examined in a simulation experiment, utilizing the critical size of dataset derived from the first step. The experimental results show that STRIM is highly robust in the analysis of datasets with contaminated attribute values, and hence is applicable to real-world data

Keywords: Rule induction, decision table, missing data, noise.

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Authors: Abhijit Mitra

Abstract:

An effective approach for extracting document images from a noisy background is introduced. The entire scheme is divided into three sub- stechniques – the initial preprocessing operations for noise cluster tightening, introduction of a new thresholding method by maximizing the ratio of stan- dard deviations of the combined effect on the image to the sum of weighted classes and finally the image restoration phase by image binarization utiliz- ing the proposed optimum threshold level. The proposed method is found to be efficient compared to the existing schemes in terms of computational complexity as well as speed with better noise rejection.

Keywords: Document image extraction, Preprocessing, Ratio of stan-dard deviations, Bi-level adaptive thresholding.

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Authors: Mohamed. A. Shrud, Ahmad H. Kharaz, Ahmed. S. Ashur, Ahmed Faris, Mustafa Benamar

Abstract:

This paper will focus on modeling, analysis and simulation of a 42V/14V dc/dc converter based architecture. This architecture is considered to be technically a viable solution for automotive dual-voltage power system for passenger car in the near further. An interleaved dc/dc converter system is chosen for the automotive converter topology due to its advantages regarding filter reduction, dynamic response, and power management. Presented herein, is a model based on one kilowatt interleaved six-phase buck converter designed to operate in a Discontinuous Conduction Mode (DCM). The control strategy of the converter is based on a voltagemode- controlled Pulse Width Modulation (PWM) with a Proportional-Integral-Derivative (PID). The effectiveness of the interleaved step-down converter is verified through simulation results using control-oriented simulator, MatLab/Simulink.

Keywords: Automotive, dc-to-dc power modules, design, interleaved, Matlab\Simulink and PID control.

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Authors: Ameneh Zare, Shahin Nematzadeh, Shahla Raghibdoust, Iran Kalbassi

Abstract:

Autism spectrum disorder is characterized by abnormalities in social communication, language abilities and repetitive behaviors. The present study focused on some grammatical deficits in autistic children. We evaluated the impairment of correct use of different Persian verb tenses in autistic children-s speech. Two standardized Language Test were administered then gathered data were analyzed. The main result of this study was significant difference between the mean scores of correct responses to present tense in comparison with past tense in Persian language. This study demonstrated that tense is severely impaired in autistic children-s speech. Our findings indicated those autistic children-s production of simple present/ past tense opposition to be better than production of future and past periphrastic forms (past perfect, present perfect, past progressive).

Keywords: Autism, Past, Persian Language, Present, Tense

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Authors: Essam Al-Daoud

Abstract:

Several combinations of the preprocessing algorithms, feature selection techniques and classifiers can be applied to the data classification tasks. This study introduces a new accurate classifier, the proposed classifier consist from four components: Signal-to- Noise as a feature selection technique, support vector machine, Bayesian neural network and AdaBoost as an ensemble algorithm. To verify the effectiveness of the proposed classifier, seven well known classifiers are applied to four datasets. The experiments show that using the suggested classifier enhances the classification rates for all datasets.

Keywords: AdaBoost, Bayesian neural network, Signal-to-Noise, support vector machine, MCMC.

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Authors: Yunjung Lee, Pil Un Kim, Gyhyoun Lee, Jin Ho Cho, Myoung Nam Kim

Abstract:

Various sounds generated in the chest are included in auscultation sound. Adaptive Noise Canceller (ANC) is one of the useful techniques for biomedical signal. But the ANC is not suitable for auscultation sound. Because the ANC needs two input channels as a primary signal and a reference signals, but a stethoscope can provide just one input sound. Therefore, in this paper, it was proposed the Single Input ANC (SIANC) for suppression of breath sound in a cardiac auscultation sound. For the SIANC, it was proposed that the reference generation system which included Heart Sound Detector, Control and Reference Generator. By experiment and comparison, it was confirmed that the proposed SIANC was efficient for heart sound enhancement and it was independent of variations of a heartbeat.

Keywords: Adaptive noise canceller, Auscultation, Breath soundsuppression, Signal enhancement.

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Authors: Wang Tong, He Pi-lian

Abstract:

This paper sets forth the possibility and importance about applying Data Mining in Web logs mining and shows some problems in the conventional searching engines. Then it offers an improved algorithm based on the original AprioriAll algorithm which has been used in Web logs mining widely. The new algorithm adds the property of the User ID during the every step of producing the candidate set and every step of scanning the database by which to decide whether an item in the candidate set should be put into the large set which will be used to produce next candidate set. At the meantime, in order to reduce the number of the database scanning, the new algorithm, by using the property of the Apriori algorithm, limits the size of the candidate set in time whenever it is produced. Test results show the improved algorithm has a more lower complexity of time and space, better restrain noise and fit the capacity of memory.

Keywords: Candidate Sets Pruning, Data Mining, ImprovedAlgorithm, Noise Restrain, Web Log

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