Search results for: Speed estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2436

Search results for: Speed estimation

1026 DWM-CDD: Dynamic Weighted Majority Concept Drift Detection for Spam Mail Filtering

Authors: Leili Nosrati, Alireza Nemaney Pour

Abstract:

Although e-mail is the most efficient and popular communication method, unwanted and mass unsolicited e-mails, also called spam mail, endanger the existence of the mail system. This paper proposes a new algorithm called Dynamic Weighted Majority Concept Drift Detection (DWM-CDD) for content-based filtering. The design purposes of DWM-CDD are first to accurate the performance of the previously proposed algorithms, and second to speed up the time to construct the model. The results show that DWM-CDD can detect both sudden and gradual changes quickly and accurately. Moreover, the time needed for model construction is less than previously proposed algorithms.

Keywords: Concept drift, Content-based filtering, E-mail, Spammail.

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1025 Soliton Interaction in Multi-Core Optical Fiber: Application to WDM System

Authors: S. Arun Prakash, V. Malathi, M. S. Mani Rajan

Abstract:

The analytical bright two soliton solution of the 3- coupled nonlinear Schrödinger equations with variable coefficients in birefringent optical fiber is obtained by Darboux transformation method. To the design of ultra-speed optical devices, Soliton interaction and control in birefringence fiber is investigated. Lax pair is constructed for N coupled NLS system through AKNS method. Using two-soliton solution, we demonstrate different interaction behaviors of solitons in birefringent fiber depending on the choice of control parameters. Our results shows that interactions of optical solitons have some specific applications such as construction of logic gates, optical computing, soliton switching, and soliton amplification in wavelength division multiplexing (WDM) system.

Keywords: Optical soliton, soliton interaction, soliton switching, WDM.

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1024 Unscented Transformation for Estimating the Lyapunov Exponents of Chaotic Time Series Corrupted by Random Noise

Authors: K. Kamalanand, P. Mannar Jawahar

Abstract:

Many systems in the natural world exhibit chaos or non-linear behavior, the complexity of which is so great that they appear to be random. Identification of chaos in experimental data is essential for characterizing the system and for analyzing the predictability of the data under analysis. The Lyapunov exponents provide a quantitative measure of the sensitivity to initial conditions and are the most useful dynamical diagnostic for chaotic systems. However, it is difficult to accurately estimate the Lyapunov exponents of chaotic signals which are corrupted by a random noise. In this work, a method for estimation of Lyapunov exponents from noisy time series using unscented transformation is proposed. The proposed methodology was validated using time series obtained from known chaotic maps. In this paper, the objective of the work, the proposed methodology and validation results are discussed in detail.

Keywords: Lyapunov exponents, unscented transformation, chaos theory, neural networks.

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1023 Estimating Shortest Circuit Path Length Complexity

Authors: Azam Beg, P. W. Chandana Prasad, S.M.N.A Senenayake

Abstract:

When binary decision diagrams are formed from uniformly distributed Monte Carlo data for a large number of variables, the complexity of the decision diagrams exhibits a predictable relationship to the number of variables and minterms. In the present work, a neural network model has been used to analyze the pattern of shortest path length for larger number of Monte Carlo data points. The neural model shows a strong descriptive power for the ISCAS benchmark data with an RMS error of 0.102 for the shortest path length complexity. Therefore, the model can be considered as a method of predicting path length complexities; this is expected to lead to minimum time complexity of very large-scale integrated circuitries and related computer-aided design tools that use binary decision diagrams.

Keywords: Monte Carlo circuit simulation data, binary decision diagrams, neural network modeling, shortest path length estimation

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1022 Comparison of Finite-Element and IEC Methods for Cable Thermal Analysis under Various Operating Environments

Authors: M. S. Baazzim, M. S. Al-Saud, M. A. El-Kady

Abstract:

In this paper, steady-state ampacity (current carrying capacity) evaluation of underground power cable system by using analytical and numerical methods for different conditions (depth of cable, spacing between phases, soil thermal resistivity, ambient temperature, wind speed), for two system voltage level were used 132 and 380 kV. The analytical method or traditional method that was used is based on the thermal analysis method developed by Neher-McGrath and further enhanced by International Electrotechnical Commission (IEC) and published in standard IEC 60287. The numerical method that was used is finite element method and it was recourse commercial software based on finite element method. 

Keywords: Cable ampacity, Finite element method, underground cable, thermal rating.

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1021 An Efficient Collocation Method for Solving the Variable-Order Time-Fractional Partial Differential Equations Arising from the Physical Phenomenon

Authors: Haniye Dehestani, Yadollah Ordokhani

Abstract:

In this work, we present an efficient approach for solving variable-order time-fractional partial differential equations, which are based on Legendre and Laguerre polynomials. First, we introduced the pseudo-operational matrices of integer and variable fractional order of integration by use of some properties of Riemann-Liouville fractional integral. Then, applied together with collocation method and Legendre-Laguerre functions for solving variable-order time-fractional partial differential equations. Also, an estimation of the error is presented. At last, we investigate numerical examples which arise in physics to demonstrate the accuracy of the present method. In comparison results obtained by the present method with the exact solution and the other methods reveals that the method is very effective.

Keywords: Collocation method, fractional partial differential equations, Legendre-Laguerre functions, pseudo-operational matrix of integration.

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1020 Multi-Context Recurrent Neural Network for Time Series Applications

Authors: B. Q. Huang, Tarik Rashid, M-T. Kechadi

Abstract:

this paper presents a multi-context recurrent network for time series analysis. While simple recurrent network (SRN) are very popular among recurrent neural networks, they still have some shortcomings in terms of learning speed and accuracy that need to be addressed. To solve these problems, we proposed a multi-context recurrent network (MCRN) with three different learning algorithms. The performance of this network is evaluated on some real-world application such as handwriting recognition and energy load forecasting. We study the performance of this network and we compared it to a very well established SRN. The experimental results showed that MCRN is very efficient and very well suited to time series analysis and its applications.

Keywords: Gradient descent method, recurrent neural network, learning algorithms, time series, BP

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1019 Kaikaku - Radical Improvement in Production

Authors: D. Gåsvaer, J. von Axelson

Abstract:

Considering today-s increasing speed of change, radical and innovative improvement - Kaikaku, is a necessity parallel to continuous incremental improvement - Kaizen, especially for SME-s in order to attain the competitive edge needed to be profitable. During 2011, a qualitative single case study with the objective of realizing a kaikaku in production has been conducted. The case study was run as a one year project using a collaborative approach including both researchers and company representatives. The case study was conducted with the purpose of gaining further knowledge about kaikaku realization as well as its implications. The empirical results provide insights about the great productivity results achieved by applying a specific kaikaku realization approach. However, it also sheds light on the difficulty and contradiction of combining innovation management and production system development.

Keywords: Kaikaku, Radical improvement, manufacturing, innovation capability

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1018 State of Charge Estimator Based On High-Gain Observer for Lithium-Ion Batteries

Authors: Jaeho Han, Moonjung Kim, Won-Ho Kim, Chang-Ho Hyun

Abstract:

This paper introduces a high-gain observer based state of charge(SOC) estimator for lithium-Ion batteries. The proposed SOC estimator has a high-gain observer(HGO) structure. The HGO scheme enhances the transient response speed and diminishes the effect of uncertainties. Furthermore, it guarantees that the output feedback controller recovers the performance of the state feedback controller when the observer gain is sufficiently high. In order to show the effectiveness of the proposed method, the linear RC battery model in ADVISOR is used. The performance of the proposed method is compared with that of the conventional linear observer(CLO) and some simulation result is given.

Keywords: SOC, high-gain, observer, uncertainties, robust

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1017 Ionanofluids as Novel Fluids for Advanced Heat Transfer Applications

Authors: S. M. Sohel Murshed, C. A. Nieto de Castro, M. J. V. Lourenço, J. França, A. P. C. Ribeiro, S. I. C.Vieira, C. S. Queirós

Abstract:

Ionanofluids are a new and innovative class of heat transfer fluids which exhibit fascinating thermophysical properties compared to their base ionic liquids. This paper deals with the findings of thermal conductivity and specific heat capacity of ionanofluids as a function of a temperature and concentration of nanotubes. Simulation results using ionanofluids as coolants in heat exchanger are also used to access their feasibility and performance in heat transfer devices. Results on thermal conductivity and heat capacity of ionanofluids as well as the estimation of heat transfer areas for ionanofluids and ionic liquids in a model shell and tube heat exchanger reveal that ionanofluids possess superior thermal conductivity and heat capacity and require considerably less heat transfer areas as compared to those of their base ionic liquids. This novel class of fluids shows great potential for advanced heat transfer applications.

Keywords: Heat transfer, Ionanofluids, Ionic liquids, Nanotubes, Thermal conductivity.

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1016 A Reliable FPGA-based Real-time Optical-flow Estimation

Authors: M. M. Abutaleb, A. Hamdy, M. E. Abuelwafa, E. M. Saad

Abstract:

Optical flow is a research topic of interest for many years. It has, until recently, been largely inapplicable to real-time applications due to its computationally expensive nature. This paper presents a new reliable flow technique which is combined with a motion detection algorithm, from stationary camera image streams, to allow flow-based analyses of moving entities, such as rigidity, in real-time. The combination of the optical flow analysis with motion detection technique greatly reduces the expensive computation of flow vectors as compared with standard approaches, rendering the method to be applicable in real-time implementation. This paper describes also the hardware implementation of a proposed pipelined system to estimate the flow vectors from image sequences in real time. This design can process 768 x 576 images at a very high frame rate that reaches to 156 fps in a single low cost FPGA chip, which is adequate for most real-time vision applications.

Keywords: Optical flow, motion detection, real-time systems, FPGA.

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1015 The Labeled Classification and its Application

Authors: M. Nemissi, H. Seridi, H. Akdag

Abstract:

This paper presents and evaluates a new classification method that aims to improve classifiers performances and speed up their training process. The proposed approach, called labeled classification, seeks to improve convergence of the BP (Back propagation) algorithm through the addition of an extra feature (labels) to all training examples. To classify every new example, tests will be carried out each label. The simplicity of implementation is the main advantage of this approach because no modifications are required in the training algorithms. Therefore, it can be used with others techniques of acceleration and stabilization. In this work, two models of the labeled classification are proposed: the LMLP (Labeled Multi Layered Perceptron) and the LNFC (Labeled Neuro Fuzzy Classifier). These models are tested using Iris, wine, texture and human thigh databases to evaluate their performances.

Keywords: Artificial neural networks, Fusion of neural networkfuzzysystems, Learning theory, Pattern recognition.

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1014 The Anti-Noise and Anti-Wear Systems for Railways

Authors: Brigita Altenbaher

Abstract:

In recent years there has been a continuous increase of axle loads, tonnage, train speed and train length which has increased both the productivity in the rail sector and the risk of rail breaks and derailments. On the other hand, the environmental requirements (e.g. noise reduction) for railway operations will become tighter in the future. In our research we developed a new composite material which does not change braking properties, is capable of taking extremely high pressure loads, reduces noise and is environmentally friendly. Part of our research was also the development of technology which will be able to apply this material to the rail. The result of our research was the system which reduces the wear out significantly and almost completely eliminates the squealing noise at the same time, and by using only one special material.

Keywords: Active protection, composite material, lubrication, noise reduction, reduction at source, railway.

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1013 Investigating Performance of Numerical Distance Relay with Higher Order Antialiasing Filter

Authors: Venkatesh C., K. Shanti Swarup

Abstract:

This paper investigates the impact on operating time delay and relay maloperation when 1st,2nd and 3rd order analog antialiasing filters are used in numerical distance protection. RC filter with cut-off frequency 90 Hz is used. Simulations are carried out for different SIR (Source to line Impedance Ratio), load, fault type and fault conditions using SIMULINK, where the voltage and current signals are fed online to the developed numerical distance relay model. Matlab is used for plotting the impedance trajectory. Investigation results shows that, about 75 % of the simulated cases, numerical distance relay operating time is not increased even-though there is a time delay when higher order filters are used. Relay maloperation (selectivity) also reduces (increases) when higher order filters are used in numerical distance protection.

Keywords: Antialiasing, capacitive voltage transformers, delay estimation, discrete Fourier transform (DFT), distance measurement, low-pass filters, source to line impedance ratio (SIR), protective relaying.

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1012 Using of Cavitation Disperser, for Porous Ceramic and Concrete Material Preparation

Authors: A. Shishkin, A. Korjakins, V. Mironovs

Abstract:

Present paper describes method of obtaining clay ceramic foam (CCF) and foam concrete (FC), by direct foaming with high speed mixer-disperser (HSMD). Three foaming agents (FA) are compared for the FC and CCF production: SCHÄUMUNGSMITTEL W 53 FLÜSSIG (Zschimmer & Schwarz Gmbh, Germany), SCF- 1245 (Sika, test sample, Latvia) and FAB-12 (Elade, Latvija). CCF were obtained at 950, 1000°C, 1150°C and 1150°C firing temperature and have mechanical compressive strength 1.2, 2.55 and 4.3 MPa and porosity 79.4, 75.1, 71.6%, respectively. Obtained FC has 6-14 MPa compressive strength and porosity 44-55%. The goal of this work was development of a sustainable and durable ceramic cellular structures using HSMD.

Keywords: Ceramic foam, foam concrete, clay foam, open cell, close cell, direct foaming.

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1011 Affine Radial Basis Function Neural Networks for the Robust Control of Hyperbolic Distributed Parameter Systems

Authors: Eleni Aggelogiannaki, Haralambos Sarimveis

Abstract:

In this work, a radial basis function (RBF) neural network is developed for the identification of hyperbolic distributed parameter systems (DPSs). This empirical model is based only on process input-output data and used for the estimation of the controlled variables at specific locations, without the need of online solution of partial differential equations (PDEs). The nonlinear model that is obtained is suitably transformed to a nonlinear state space formulation that also takes into account the model mismatch. A stable robust control law is implemented for the attenuation of external disturbances. The proposed identification and control methodology is applied on a long duct, a common component of thermal systems, for a flow based control of temperature distribution. The closed loop performance is significantly improved in comparison to existing control methodologies.

Keywords: Hyperbolic Distributed Parameter Systems, Radial Basis Function Neural Networks, H∞ control, Thermal systems.

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1010 Composite Programming for Electric Passenger Car Selection in Multiple Criteria Decision Making

Authors: C. Ardil

Abstract:

This paper discusses the use of the composite programming method to identify the optimum electric passenger automobile in multiple criteria decision making. With the composite programming approach, a set of alternatives are compared using an optimality measure that gauges how far apart they are from the optimum solution. In this paper, some key factors (range, battery, engine, maximum speed, acceleration) that customers should consider while purchasing an electric passenger car for daily use are discussed. A numerical illustration is provided to demonstrate the validity and applicability of the proximity measure approach

Keywords: electric passenger car selection, multiple criteria decision making, proximity measure method, composite programming, entropic weight method

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1009 Optimum Radio Capacity Estimation of a Single-Cell Spread Spectrum MIMO System under Rayleigh Fading Conditions

Authors: P. Varzakas

Abstract:

In this paper, the problem of estimating the optimal radio capacity of a single-cell spread spectrum (SS) multiple-inputmultiple- output (MIMO) system operating in a Rayleigh fading environment is examined. The optimisation between the radio capacity and the theoretically achievable average channel capacity (in the sense of information theory) per user of a MIMO single-cell SS system operating in a Rayleigh fading environment is presented. Then, the spectral efficiency is estimated in terms of the achievable average channel capacity per user, during the operation over a broadcast time-varying link, and leads to a simple novel-closed form expression for the optimal radio capacity value based on the maximization of the achieved spectral efficiency. Numerical results are presented to illustrate the proposed analysis.

Keywords: Channel capacity, MIMO systems, Radio capacity, Rayleigh fading, Spectral efficiency.

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1008 Transmitter Design for LMS-MIMO-MCCDMA Systems with Pilot Channel Estimates and Zero Forcing Equalizer

Authors: S.M. Bahri, F.T. Bendimerad

Abstract:

We propose a downlink multiple-input multipleoutput (MIMO) multi-carrier code division multiple access (MCCDMA) system with adaptive beamforming algorithm for smart antennas. The algorithm used in this paper is based on the Least Mean Square (LMS), with pilot channel estimation (PCE) and the zero forcing equalizer (ZFE) in the receiver, requiring reference signal and no knowledge channel. MC-CDMA is studied in a multiple antenna context in order to efficiently exploit robustness against multipath effects and multi-user flexibility of MC-CDMA and channel diversity offered by MIMO systems for radio mobile channels. Computer simulations, considering multi-path Rayleigh Fading Channel, interference inter symbol and interference are presented to verify the performance. Simulation results show that the scheme achieves good performance in a multi-user system.

Keywords: Adaptive Beamforming, LMS Algorithm, MCCDMA, MIMO System, Smart Antenna.

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1007 Analyzing and Formulation of Product Lead Time

Authors: B. Fahimnia, L.H.S. Luong, B. Motevallian, R. M. Marian, M. M. Esmaeil

Abstract:

Product Lead Time (PLT) is the period of time from receiving a customer's order to delivering the final product. PLT is an indicator of the manufacturing controllability, efficiency and performance. Due to the explosion in the rate of technological innovations and the rapid changes in the nature of manufacturing processes, manufacturing firms can bring the new products to market quicker only if they can reduce their PLT and speed up the rate at which they can design, plan, control, and manufacture. Although there is a substantial body of research on manufacturing relating to cost and quality issues, there is no much specific research conducted in relation to the formulation of PLT, despite its significance and importance. This paper analyzes and formulates PLT which can be used as a guideline for achieving the shorter PLT. Further more this paper identifies the causes of delay and factors that contributes to the increased product lead-time.

Keywords: Manufacturing Control, Manufacturing Lead Time, Manufacturing Planning, Product Design, and Product Lead Time.

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1006 A Modified Speech Enhancement Using Adaptive Gain Equalizer with Non linear Spectral Subtraction for Robust Speech Recognition

Authors: C. Ganesh Babu, P. T. Vanathi

Abstract:

In this paper we present an enhanced noise reduction method for robust speech recognition using Adaptive Gain Equalizer with Non linear Spectral Subtraction. In Adaptive Gain Equalizer method (AGE), the input signal is divided into a number of subbands that are individually weighed in time domain, in accordance to the short time Signal-to-Noise Ratio (SNR) in each subband estimation at every time instant. Instead of focusing on suppression the noise on speech enhancement is focused. When analysis was done under various noise conditions for speech recognition, it was found that Adaptive Gain Equalizer method algorithm has an obvious failing point for a SNR of -5 dB, with inadequate levels of noise suppression for SNR less than this point. This work proposes the implementation of AGE when coupled with Non linear Spectral Subtraction (AGE-NSS) for robust speech recognition. The experimental result shows that out AGE-NSS performs the AGE when SNR drops below -5db level.

Keywords: Adaptive Gain Equalizer, Non Linear Spectral Subtraction, Speech Enhancement, and Speech Recognition.

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1005 Segmentation of Piecewise Polynomial Regression Model by Using Reversible Jump MCMC Algorithm

Authors: Suparman

Abstract:

Piecewise polynomial regression model is very flexible model for modeling the data. If the piecewise polynomial regression model is matched against the data, its parameters are not generally known. This paper studies the parameter estimation problem of piecewise polynomial regression model. The method which is used to estimate the parameters of the piecewise polynomial regression model is Bayesian method. Unfortunately, the Bayes estimator cannot be found analytically. Reversible jump MCMC algorithm is proposed to solve this problem. Reversible jump MCMC algorithm generates the Markov chain that converges to the limit distribution of the posterior distribution of piecewise polynomial regression model parameter. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of piecewise polynomial regression model.

Keywords: Piecewise, Bayesian, reversible jump MCMC, segmentation.

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1004 Human Growth Curve Estimation through a Combination of Longitudinal and Cross-sectional Data

Authors: Sedigheh Mirzaei S., Debasis Sengupta

Abstract:

Parametric models have been quite popular for studying human growth, particularly in relation to biological parameters such as peak size velocity and age at peak size velocity. Longitudinal data are generally considered to be vital for fittinga parametric model to individual-specific data, and for studying the distribution of these biological parameters in a human population. However, cross-sectional data are easier to obtain than longitudinal data. In this paper, we present a method of combining longitudinal and cross-sectional data for the purpose of estimating the distribution of the biological parameters. We demonstrate, through simulations in the special case ofthePreece Baines model, how estimates based on longitudinal data can be improved upon by harnessing the information contained in cross-sectional data.We study the extent of improvement for different mixes of the two types of data, and finally illustrate the use of the method through data collected by the Indian Statistical Institute.

Keywords: Preece-Baines growth model, MCMC method, Mixed effect model

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1003 E-Voting: A Trustworthiness In Democratic; A View from Technology, Political and Social Issue

Authors: Sera Syarmila Sameon, Rohaini Ramli

Abstract:

A trustworthy voting process in democratic is important that each vote is recorded with accuracy and impartiality. The accuracy and impartiality are tallied in high rate with biometric system. One of the sign is a fingerprint. Fingerprint recognition is still a challenging problem, because of the distortions among the different impression of the same finger. Because of the trustworthy of biometric voting technologies, it may give a great effect on numbers of voter-s participation and outcomes of the democratic process. Hence in this study, the authors are interested in designing and analyzing the Electronic Voting System and the participation of the users. The system is based on the fingerprint minutiae with the addition of person ID number. This is in order to enhance the accuracy and speed of the voting process. The new design is analyzed by conducting pilot election among a class of students for selecting their representative.

Keywords: Biometric, FAR and FRR, democratic, voting

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1002 Analysis of CNT Bundle and its Comparison with Copper for FPGAs Interconnects

Authors: Kureshi Abdul Kadir, Mohd. Hasan

Abstract:

Each new semiconductor technology node brings smaller transistors and wires. Although this makes transistors faster, wires get slower. In nano-scale regime, the standard copper (Cu) interconnect will become a major hurdle for FPGA interconnect due to their high resistivity and electromigration. This paper presents the comprehensive evaluation of mixed CNT bundle interconnects and investigates their prospects as energy efficient and high speed interconnect for future FPGA routing architecture. All HSPICE simulations are carried out at operating frequency of 1GHz and it is found that mixed CNT bundle implemented in FPGAs as interconnect can potentially provide a substantial delay and energy reduction over traditional interconnects at 32nm process technology.

Keywords: CMOS, Copper Interconnect, Mixed CNT Bundle Interconnect, FPGAs.

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1001 Vector Control of Multimotor Drive

Authors: Archana S. Nanoty, A. R. Chudasama

Abstract:

Three-phase induction machines are today a standard for industrial electrical drives. Cost, reliability, robustness and maintenance free operation are among the reasons these machines are replacing dc drive systems. The development of power electronics and signal processing systems has eliminated one of the greatest disadvantages of such ac systems, which is the issue of control. With modern techniques of field oriented vector control, the task of variable speed control of induction machines is no longer a disadvantage. The need to increase system performance, particularly when facing limits on the power ratings of power supplies and semiconductors, motivates the use of phase number other than three, In this paper a novel scheme of connecting two, three phase induction motors in parallel fed by two inverters; viz. VSI and CSI and their vector control is presented.

Keywords: Field oriented control, multiphase induction motor, power electronics converter.

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1000 Vector Control Using Series Iron Loss Model of Induction, Motors and Power Loss Minimization

Authors: Kheldoun Aissa, Khodja Djalal Eddine

Abstract:

The iron loss is a source of detuning in vector controlled induction motor drives if the classical rotor vector controller is used for decoupling. In fact, the field orientation will not be satisfied and the output torque will not truck the reference torque mostly used by Loss Model Controllers (LMCs). In addition, this component of loss, among others, may be excessive if the vector controlled induction motor is driving light loads. In this paper, the series iron loss model is used to develop a vector controller immune to iron loss effect and then an LMC to minimize the total power loss using the torque generated by the speed controller.

Keywords: Field Oriented Controller, Induction Motor, Loss ModelController, Series Iron Loss.

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999 Restoration of Noisy Document Images with an Efficient Bi-Level Adaptive Thresholding

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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998 Bandwidth Estimation Algorithms for the Dynamic Adaptation of Voice Codec

Authors: Davide Pierattoni, Ivan Macor, Pier Luca Montessoro

Abstract:

In the recent years multimedia traffic and in particular VoIP services are growing dramatically. We present a new algorithm to control the resource utilization and to optimize the voice codec selection during SIP call setup on behalf of the traffic condition estimated on the network path. The most suitable methodologies and the tools that perform realtime evaluation of the available bandwidth on a network path have been integrated with our proposed algorithm: this selects the best codec for a VoIP call in function of the instantaneous available bandwidth on the path. The algorithm does not require any explicit feedback from the network, and this makes it easily deployable over the Internet. We have also performed intensive tests on real network scenarios with a software prototype, verifying the algorithm efficiency with different network topologies and traffic patterns between two SIP PBXs. The promising results obtained during the experimental validation of the algorithm are now the basis for the extension towards a larger set of multimedia services and the integration of our methodology with existing PBX appliances.

Keywords: Integrated voice-data communication, computernetwork performance, resource optimization.

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997 Identification of Aircraft Gas Turbine Engines Temperature Condition

Authors: Pashayev A., Askerov D., C. Ardil, Sadiqov R., Abdullayev P.

Abstract:

Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.

Keywords: Identification of a technical condition, aviation gasturbine engine, fuzzy logic and neural networks.

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