Search results for: Linear co-positive Lyapunov functions
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2834

Search results for: Linear co-positive Lyapunov functions

2114 Multi-Agent Coverage Control with Bounded Gain Forgetting Composite Adaptive Controller

Authors: Mert Turanli, Hakan Temeltas

Abstract:

In this paper, we present an adaptive controller for decentralized coordination problem of multiple non-holonomic agents. The performance of the presented Multi-Agent Bounded Gain Forgetting (BGF) Composite Adaptive controller is compared against the tracking error criterion with a Feedback Linearization controller. By using the method, the sensor nodes move and reconfigure themselves in a coordinated way in response to a sensed environment. The multi-agent coordination is achieved through Centroidal Voronoi Tessellations and Coverage Control. Also, a consensus protocol is used for synchronization of the parameter vectors. The two controllers are given with their Lyapunov stability analysis and their stability is verified with simulation results. The simulations are carried out in MATLAB and ROS environments. Better performance is obtained with BGF Adaptive Controller.

Keywords: Adaptive control, Centroidal Voronoi Tessellations, composite adaptation, coordination.

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2113 Design of Nonlinear Observer by Using Chebyshev Interpolation based on Formal Linearization

Authors: Kazuo Komatsu, Hitoshi Takata

Abstract:

This paper discusses a design of nonlinear observer by a formal linearization method using an application of Chebyshev Interpolation in order to facilitate processes for synthesizing a nonlinear observer and to improve the precision of linearization. A dynamic nonlinear system is linearized with respect to a linearization function, and a measurement equation is transformed into an augmented linear one by the formal linearization method which is based on Chebyshev interpolation. To the linearized system, a linear estimation theory is applied and a nonlinear observer is derived. To show effectiveness of the observer design, numerical experiments are illustrated and they indicate that the design shows remarkable performances for nonlinear systems.

Keywords: nonlinear system, nonlinear observer, formal linearization, Chebyshev interpolation.

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2112 Pushover Analysis of Masonry Infilled Reinforced Concrete Frames for Performance Based Design for Near Field Earthquakes

Authors: Alok Madan, Ashok Gupta, Arshad K. Hashmi

Abstract:

Non-linear dynamic time history analysis is considered as the most advanced and comprehensive analytical method for evaluating the seismic response and performance of multi-degree-of-freedom building structures under the influence of earthquake ground motions. However, effective and accurate application of the method requires the implementation of advanced hysteretic constitutive models of the various structural components including masonry infill panels. Sophisticated computational research tools that incorporate realistic hysteresis models for non-linear dynamic time-history analysis are not popular among the professional engineers as they are not only difficult to access but also complex and time-consuming to use. In addition, commercial computer programs for structural analysis and design that are acceptable to practicing engineers do not generally integrate advanced hysteretic models which can accurately simulate the hysteresis behavior of structural elements with a realistic representation of strength degradation, stiffness deterioration, energy dissipation and ‘pinching’ under cyclic load reversals in the inelastic range of behavior. In this scenario, push-over or non-linear static analysis methods have gained significant popularity, as they can be employed to assess the seismic performance of building structures while avoiding the complexities and difficulties associated with non-linear dynamic time-history analysis. “Push-over” or non-linear static analysis offers a practical and efficient alternative to non-linear dynamic time-history analysis for rationally evaluating the seismic demands. The present paper is based on the analytical investigation of the effect of distribution of masonry infill panels over the elevation of planar masonry infilled reinforced concrete [R/C] frames on the seismic demands using the capacity spectrum procedures implementing nonlinear static analysis [pushover analysis] in conjunction with the response spectrum concept. An important objective of the present study is to numerically evaluate the adequacy of the capacity spectrum method using pushover analysis for performance based design of masonry infilled R/C frames for near-field earthquake ground motions.

Keywords: Nonlinear analysis, capacity spectrum method, response spectrum, seismic demand, near-field earthquakes.

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2111 Improvement of Learning Motivation and Negotiation of Learning Disorders of Students Using Integrative Teaching Methodology

Authors: Juris Porozovs, Daina Voita, Anda Kauliņa, Toms Voits, Evita Vaļēviča

Abstract:

Integrative teaching methodology is based on connecting and summarizing knowledge from different subjects in order to create better understanding of different disciplines and improvement of competences in general. Integrative teaching methodology was implemented and realised during one academic year in 17 Latvian schools according with specially worked out programme by specialists of different fields for adaptation in social environment of children and young people with learning, cognitive functions and motor disorders. Implemented integrative teaching methodology consisted from three subsections which were specialised for adaptation in social environment, improvement of cognitive functions and improvement and harmonization of personality. The results of investigation showed that the use of integrative teaching methodology is an effective way for improvement of learning motivation and negotiation of learning disorders of different age schoolchildren.

Keywords: Adaptation in social environment, integrative teaching methodology, learning disorders, learning motivation.

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2110 Library Aware Power Conscious Realization of Complementary Boolean Functions

Authors: Padmanabhan Balasubramanian, C. Ardil

Abstract:

In this paper, we consider the problem of logic simplification for a special class of logic functions, namely complementary Boolean functions (CBF), targeting low power implementation using static CMOS logic style. The functions are uniquely characterized by the presence of terms, where for a canonical binary 2-tuple, D(mj) ∪ D(mk) = { } and therefore, we have | D(mj) ∪ D(mk) | = 0 [19]. Similarly, D(Mj) ∪ D(Mk) = { } and hence | D(Mj) ∪ D(Mk) | = 0. Here, 'mk' and 'Mk' represent a minterm and maxterm respectively. We compare the circuits minimized with our proposed method with those corresponding to factored Reed-Muller (f-RM) form, factored Pseudo Kronecker Reed-Muller (f-PKRM) form, and factored Generalized Reed-Muller (f-GRM) form. We have opted for algebraic factorization of the Reed-Muller (RM) form and its different variants, using the factorization rules of [1], as it is simple and requires much less CPU execution time compared to Boolean factorization operations. This technique has enabled us to greatly reduce the literal count as well as the gate count needed for such RM realizations, which are generally prone to consuming more cells and subsequently more power consumption. However, this leads to a drawback in terms of the design-for-test attribute associated with the various RM forms. Though we still preserve the definition of those forms viz. realizing such functionality with only select types of logic gates (AND gate and XOR gate), the structural integrity of the logic levels is not preserved. This would consequently alter the testability properties of such circuits i.e. it may increase/decrease/maintain the same number of test input vectors needed for their exhaustive testability, subsequently affecting their generalized test vector computation. We do not consider the issue of design-for-testability here, but, instead focus on the power consumption of the final logic implementation, after realization with a conventional CMOS process technology (0.35 micron TSMC process). The quality of the resulting circuits evaluated on the basis of an established cost metric viz., power consumption, demonstrate average savings by 26.79% for the samples considered in this work, besides reduction in number of gates and input literals by 39.66% and 12.98% respectively, in comparison with other factored RM forms.

Keywords: Reed-Muller forms, Logic function, Hammingdistance, Algebraic factorization, Low power design.

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2109 A Survey: Clustering Ensembles Techniques

Authors: Reza Ghaemi , Md. Nasir Sulaiman , Hamidah Ibrahim , Norwati Mustapha

Abstract:

The clustering ensembles combine multiple partitions generated by different clustering algorithms into a single clustering solution. Clustering ensembles have emerged as a prominent method for improving robustness, stability and accuracy of unsupervised classification solutions. So far, many contributions have been done to find consensus clustering. One of the major problems in clustering ensembles is the consensus function. In this paper, firstly, we introduce clustering ensembles, representation of multiple partitions, its challenges and present taxonomy of combination algorithms. Secondly, we describe consensus functions in clustering ensembles including Hypergraph partitioning, Voting approach, Mutual information, Co-association based functions and Finite mixture model, and next explain their advantages, disadvantages and computational complexity. Finally, we compare the characteristics of clustering ensembles algorithms such as computational complexity, robustness, simplicity and accuracy on different datasets in previous techniques.

Keywords: Clustering Ensembles, Combinational Algorithm, Consensus Function, Unsupervised Classification.

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2108 Unsupervised Feature Selection Using Feature Density Functions

Authors: Mina Alibeigi, Sattar Hashemi, Ali Hamzeh

Abstract:

Since dealing with high dimensional data is computationally complex and sometimes even intractable, recently several feature reductions methods have been developed to reduce the dimensionality of the data in order to simplify the calculation analysis in various applications such as text categorization, signal processing, image retrieval, gene expressions and etc. Among feature reduction techniques, feature selection is one the most popular methods due to the preservation of the original features. In this paper, we propose a new unsupervised feature selection method which will remove redundant features from the original feature space by the use of probability density functions of various features. To show the effectiveness of the proposed method, popular feature selection methods have been implemented and compared. Experimental results on the several datasets derived from UCI repository database, illustrate the effectiveness of our proposed methods in comparison with the other compared methods in terms of both classification accuracy and the number of selected features.

Keywords: Feature, Feature Selection, Filter, Probability Density Function

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2107 Presidential Interactions with Faculty Senates: Expectations and Practices

Authors: Michael T. Miller, G. David Gearhart

Abstract:

Shared governance is an important element in higher education decision making. Through the joint decision making process, faculty members are provided an opportunity to help shape the future of an institution while increasing support for decisions that are made. Presidents, those leaders who are legally bound to guide their institutions, must find ways to collaborate effectively with faculty members in making decisions, and the first step in this process is understanding when and how presidents and faculty leaders interact. In the current study, a national sample of college presidents reported their preparation for the presidency, their perceptions of the functions of a faculty senate, and ultimately, the locations for important interactions between presidents and faculty senates. Results indicated that presidents, regardless of their preparation, found official functions to be the most important for communicating, although, those presidents with academic backgrounds were more likely to perceive faculty senates as having a role in all aspects of an institutions management.

Keywords: College faculty, college president, faculty senate, leadership.

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2106 Self-Tuning Power System Stabilizer Based on Recursive Least Square Identification and Linear Quadratic Regulator

Authors: J. Ritonja

Abstract:

Available commercial applications of power system stabilizers assure optimal damping of synchronous generator’s oscillations only in a small part of operating range. Parameters of the power system stabilizer are usually tuned for the selected operating point. Extensive variations of the synchronous generator’s operation result in changed dynamic characteristics. This is the reason that the power system stabilizer tuned for the nominal operating point does not satisfy preferred damping in the overall operation area. The small-signal stability and the transient stability of the synchronous generators have represented an attractive problem for testing different concepts of the modern control theory. Of all the methods, the adaptive control has proved to be the most suitable for the design of the power system stabilizers. The adaptive control has been used in order to assure the optimal damping through the entire synchronous generator’s operating range. The use of the adaptive control is possible because the loading variations and consequently the variations of the synchronous generator’s dynamic characteristics are, in most cases, essentially slower than the adaptation mechanism. The paper shows the development and the application of the self-tuning power system stabilizer based on recursive least square identification method and linear quadratic regulator. Identification method is used to calculate the parameters of the Heffron-Phillips model of the synchronous generator. On the basis of the calculated parameters of the synchronous generator’s mathematical model, the synthesis of the linear quadratic regulator is carried-out. The identification and the synthesis are implemented on-line. In this way, the self-tuning power system stabilizer adapts to the different operating conditions. A purpose of this paper is to contribute to development of the more effective power system stabilizers, which would replace currently used linear stabilizers. The presented self-tuning power system stabilizer makes the tuning of the controller parameters easier and assures damping improvement in the complete operating range. The results of simulations and experiments show essential improvement of the synchronous generator’s damping and power system stability.

Keywords: Adaptive control, linear quadratic regulator, power system stabilizer, recursive least square identification.

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2105 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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2104 A New Face Recognition Method using PCA, LDA and Neural Network

Authors: A. Hossein Sahoolizadeh, B. Zargham Heidari, C. Hamid Dehghani

Abstract:

In this paper, a new face recognition method based on PCA (principal Component Analysis), LDA (Linear Discriminant Analysis) and neural networks is proposed. This method consists of four steps: i) Preprocessing, ii) Dimension reduction using PCA, iii) feature extraction using LDA and iv) classification using neural network. Combination of PCA and LDA is used for improving the capability of LDA when a few samples of images are available and neural classifier is used to reduce number misclassification caused by not-linearly separable classes. The proposed method was tested on Yale face database. Experimental results on this database demonstrated the effectiveness of the proposed method for face recognition with less misclassification in comparison with previous methods.

Keywords: Face recognition Principal component analysis, Linear discriminant analysis, Neural networks.

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2103 Model Order Reduction of Linear Time Variant High Speed VLSI Interconnects using Frequency Shift Technique

Authors: J.V.R.Ravindra, M.B.Srinivas,

Abstract:

Accurate modeling of high speed RLC interconnects has become a necessity to address signal integrity issues in current VLSI design. To accurately model a dispersive system of interconnects at higher frequencies; a full-wave analysis is required. However, conventional circuit simulation of interconnects with full wave models is extremely CPU expensive. We present an algorithm for reducing large VLSI circuits to much smaller ones with similar input-output behavior. A key feature of our method, called Frequency Shift Technique, is that it is capable of reducing linear time-varying systems. This enables it to capture frequency-translation and sampling behavior, important in communication subsystems such as mixers, RF components and switched-capacitor filters. Reduction is obtained by projecting the original system described by linear differential equations into a lower dimension. Experiments have been carried out using Cadence Design Simulator cwhich indicates that the proposed technique achieves more % reduction with less CPU time than the other model order reduction techniques existing in literature. We also present applications to RF circuit subsystems, obtaining size reductions and evaluation speedups of orders of magnitude with insignificant loss of accuracy.

Keywords: Model order Reduction, RLC, crosstalk

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2102 Orthogonal Regression for Nonparametric Estimation of Errors-in-Variables Models

Authors: Anastasiia Yu. Timofeeva

Abstract:

Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.

Keywords: Grade point average, orthogonal regression, penalized regression spline, locally weighted regression.

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2101 Investigation of Heating Behaviour of E-textile Structures

Authors: H. Sezgin, S. Kursun Bahadır, Y. E. Boke, F. Kalaoğlu

Abstract:

By textile science incorporating with electronic industry, developed textile products start to take part in different areas such as industry, military, space, medical etc. for health, protection, defense, communication and automation. Electronic textiles (e-textiles) are fabrics that contain electronics and interconnections with them. In this study, two types of base yarns (cotton and acrylic) and three types of conductive steel yarns with different linear resistance values (14Ω/m, 30Ω/m, 70Ω/m) were used to investigate the effect of base yarn type and linear resistance of conductive yarns on thermal behavior of e-textile structures. Thermal behavior of samples was examined by thermal camera.

Keywords: Conductive yarn, e-textiles, smart textiles, thermal analysis.

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2100 A Study on the Application of TRIZ to CAD/CAM System

Authors: Yuan L. Lai, Jian H. Chen, Jui P. Hung

Abstract:

This study created new graphical icons and operating functions in a CAD/CAM software system by analyzing icons in some of the popular systems, such as AutoCAD, AlphaCAM, Mastercam and the 1st edition of LiteCAM. These software systems all focused on geometric design and editing, thus how to transmit messages intuitively from icon itself to users is an important function of graphical icons. The primary purpose of this study is to design innovative icons and commands for new software. This study employed the TRIZ method, an innovative design method, to generate new concepts systematically. Through literature review, it then investigated and analyzed the relationship between TRIZ and idea development. Contradiction Matrix and 40 Principles were used to develop an assisting tool suitable for icon design in software development. We first gathered icon samples from the selected CAD/CAM systems. Then grouped these icons by meaningful functions, and compared useful and harmful properties. Finally, we developed new icons for new software systems in order to avoid intellectual property problem.

Keywords: Icon, TRIZ, CAD/CAM.

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2099 A Boundary Backstepping Control Design for 2-D, 3-D and N-D Heat Equation

Authors: Aziz Sezgin

Abstract:

We consider the problem of stabilization of an unstable heat equation in a 2-D, 3-D and generally n-D domain by deriving a generalized backstepping boundary control design methodology. To stabilize the systems, we design boundary backstepping controllers inspired by the 1-D unstable heat equation stabilization procedure. We assume that one side of the boundary is hinged and the other side is controlled for each direction of the domain. Thus, controllers act on two boundaries for 2-D domain, three boundaries for 3-D domain and ”n” boundaries for n-D domain. The main idea of the design is to derive ”n” controllers for each of the dimensions by using ”n” kernel functions. Thus, we obtain ”n” controllers for the ”n” dimensional case. We use a transformation to change the system into an exponentially stable ”n” dimensional heat equation. The transformation used in this paper is a generalized Volterra/Fredholm type with ”n” kernel functions for n-D domain instead of the one kernel function of 1-D design.

Keywords: Backstepping, boundary control, 2-D, 3-D, n-D heat equation, distributed parameter systems.

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2098 A Data Driven Approach for the Degradation of a Lithium-Ion Battery Based on Accelerated Life Test

Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

Abstract:

Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: Accelerated life test, inverse power law, lithium ion battery, reliability evaluation, Weibull distribution.

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2097 Evolutionary Techniques for Model Order Reduction of Large Scale Linear Systems

Authors: S. Panda, J. S. Yadav, N. P. Patidar, C. Ardil

Abstract:

Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Order Reduction, Stability, Transfer Function, Integral Squared Error.

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2096 Fuzzy Tuned PID Controller with D-Q-O Reference Frame Technique Based Active Power Filter

Authors: Kavala Kiran Kumar, R. Govardhana Rao

Abstract:

Active power filter continues to be a powerful tool to control harmonics in power systems thereby enhancing the power quality. This paper presents a fuzzy tuned PID controller based shunt active filter to diminish the harmonics caused by non linear loads like thyristor bridge rectifiers and imbalanced loads. Here Fuzzy controller provides the tuning of PID, based on firing of thyristor bridge rectifiers and variations in input rms current. The shunt APF system is implemented with three phase current controlled Voltage Source Inverter (VSI) and is connected at the point of common coupling for compensating the current harmonics by injecting equal but opposite filter currents. These controllers are capable of controlling dc-side capacitor voltage and estimating reference currents. Hysteresis Current Controller (HCC) is used to generate switching signals for the voltage source inverter. Simulation studies are carried out with non linear loads like thyristor bridge rectifier along with unbalanced loads and the results proved that the APF along with fuzzy tuned PID controller work flawlessly for different firing angles of non linear load.

Keywords: Active power filters (APF), Fuzzy logic controller (FLC), Hysteresis current controller (HCC), PID, Total harmonic Distortion (THD), Voltage source inverter (VSI).

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2095 Angles of Arrival Estimation with Unitary Partial Propagator

Authors: Youssef Khmou, Said Safi

Abstract:

In this paper, we investigated the effect of real valued transformation of the spectral matrix of the received data for Angles Of Arrival estimation problem.  Indeed, the unitary transformation of Partial Propagator (UPP) for narrowband sources is proposed and applied on Uniform Linear Array (ULA).

Monte Carlo simulations proved the performance of the UPP spectrum comparatively with Forward Backward Partial Propagator (FBPP) and Unitary Propagator (UP). The results demonstrates that when some of the sources are fully correlated and closer than the Rayleigh angular limit resolution of the broadside array, the UPP method outperforms the FBPP in both of spatial resolution and complexity.

Keywords: DOA, Uniform Linear Array, Narrowband, Propagator, Real valued transformation, Subspace, Unitary Operator.

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2094 A Modified Decoupled Semi-Analytical Approach Based On SBFEM for Solving 2D Elastodynamic Problems

Authors: M. Fakharian, M. I. Khodakarami

Abstract:

In this paper, a new trend for improvement in semianalytical method based on scale boundaries in order to solve the 2D elastodynamic problems is provided. In this regard, only the boundaries of the problem domain discretization are by specific subparametric elements. Mapping functions are uses as a class of higherorder Lagrange polynomials, special shape functions, Gauss-Lobatto- Legendre numerical integration, and the integral form of the weighted residual method, the matrix is diagonal coefficients in the equations of elastodynamic issues. Differences between study conducted and prior research in this paper is in geometry production procedure of the interpolation function and integration of the different is selected. Validity and accuracy of the present method are fully demonstrated through two benchmark problems which are successfully modeled using a few numbers of DOFs. The numerical results agree very well with the analytical solutions and the results from other numerical methods.

Keywords: 2D Elastodynamic Problems, Lagrange Polynomials, G-L-Lquadrature, Decoupled SBFEM.

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2093 Note to the Global GMRES for Solving the Matrix Equation AXB = F

Authors: Fatemeh Panjeh Ali Beik

Abstract:

In the present work, we propose a new projection method for solving the matrix equation AXB = F. For implementing our new method, generalized forms of block Krylov subspace and global Arnoldi process are presented. The new method can be considered as an extended form of the well-known global generalized minimum residual (Gl-GMRES) method for solving multiple linear systems and it will be called as the extended Gl-GMRES (EGl- GMRES). Some new theoretical results have been established for proposed method by employing Schur complement. Finally, some numerical results are given to illustrate the efficiency of our new method.

Keywords: Matrix equation, Iterative method, linear systems, block Krylov subspace method, global generalized minimum residual (Gl-GMRES).

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2092 A New Method for Multiobjective Optimization Based on Learning Automata

Authors: M. R. Aghaebrahimi, S. H. Zahiri, M. Amiri

Abstract:

The necessity of solving multi dimensional complicated scientific problems beside the necessity of several objective functions optimization are the most motive reason of born of artificial intelligence and heuristic methods. In this paper, we introduce a new method for multiobjective optimization based on learning automata. In the proposed method, search space divides into separate hyper-cubes and each cube is considered as an action. After gathering of all objective functions with separate weights, the cumulative function is considered as the fitness function. By the application of all the cubes to the cumulative function, we calculate the amount of amplification of each action and the algorithm continues its way to find the best solutions. In this Method, a lateral memory is used to gather the significant points of each iteration of the algorithm. Finally, by considering the domination factor, pareto front is estimated. Results of several experiments show the effectiveness of this method in comparison with genetic algorithm based method.

Keywords: Function optimization, Multiobjective optimization, Learning automata.

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2091 Exploration of the Communication Area of Infrared Short-Range Communication Systems for Intervehicle Communication

Authors: Wern-Yarng Shieh, Hsin-Chuan Chen, Ti-Ho Wang, Bo-Wei Chen

Abstract:

Infrared communication in the wavelength band 780- 950 nm is very suitable for short-range point-to-point communications. It is a good choice for vehicle-to-vehicle communication in several intelligent-transportation-system (ITS) applications such as cooperative driving, collision warning, and pileup-crash prevention. In this paper, with the aid of a physical model established in our previous works, we explore the communication area of an infrared intervehicle communication system utilizing a typical low-cost cormmercial lightemitting diodes (LEDs) as the emitter and planar p-i-n photodiodes as the receiver. The radiation pattern of the emitter fabricated by aforementioned LEDs and the receiving pattern of the receiver are approximated by a linear combination of cosinen functions. This approximation helps us analyze the system performance easily. Both multilane straight-road conditions and curved-road conditions with various radius of curvature are taken into account. The condition of a small car communicating with a big truck, i.e., there is a vertical mounting height difference between the emitter and the receiver, is also considered. Our results show that the performance of the system meets the requirement of aforementioned ITS applications in terms of the communication area.

Keywords: Dedicated short-range communication (DSRC), infrared communication, intervehicle communication, intelligent transportation system (ITS).

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2090 An Approximate Solution of the Classical Van der Pol Oscillator Coupled Gyroscopically to a Linear Oscillator Using Parameter-Expansion Method

Authors: Mohammad Taghi Darvishi, Samad Kheybari

Abstract:

In this article, we are dealing with a model consisting of a classical Van der Pol oscillator coupled gyroscopically to a linear oscillator. The major problem is analyzed. The regular dynamics of the system is considered using analytical methods. In this case, we provide an approximate solution for this system using parameter-expansion method. Also, we find approximate values for frequencies of the system. In parameter-expansion method the solution and unknown frequency of oscillation are expanded in a series by a bookkeeping parameter. By imposing the non-secularity condition at each order in the expansion the method provides different approximations to both the solution and the frequency of oscillation. One iteration step provides an approximate solution which is valid for the whole solution domain.

Keywords: Parameter-expansion method, classical Van der Pol oscillator.

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2089 Optimal Trailing Edge Flap Positions of Helicopter Rotor for Various Thrust Coefficients to Solidity (Ct/σ) Ratios

Authors: Saijal K. K., K. Prabhakaran Nair

Abstract:

This study aims to determine change in optimal locations of dual trailing-edge flaps for various thrust coefficient to solidity (Ct /σ) ratios of helicopter to achieve minimum hub vibration levels, with low penalty in terms of required trailing-edge flap control power. Polynomial response functions are used to approximate hub vibration and flap power objective functions. Single objective and multiobjective optimization is carried with the objective of minimizing hub vibration and flap power. The optimization result shows that the inboard flap location at low Ct /σ ratio move farther from the baseline value and at high Ct /σ ratio move towards the root of the blade for minimizing hub vibration.

Keywords: Helicopter rotor, Trailing-edge flap, Thrust coefficient to solidity (Ct /σ) ratio, Optimization.

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2088 Environmental Interference Cancellation of Speech with the Radial Basis Function Networks: An Experimental Comparison

Authors: Nima Hatami

Abstract:

In this paper, we use Radial Basis Function Networks (RBFN) for solving the problem of environmental interference cancellation of speech signal. We show that the Second Order Thin- Plate Spline (SOTPS) kernel cancels the interferences effectively. For make comparison, we test our experiments on two conventional most used RBFN kernels: the Gaussian and First order TPS (FOTPS) basis functions. The speech signals used here were taken from the OGI Multi-Language Telephone Speech Corpus database and were corrupted with six type of environmental noise from NOISEX-92 database. Experimental results show that the SOTPS kernel can considerably outperform the Gaussian and FOTPS functions on speech interference cancellation problem.

Keywords: Environmental interference, interference cancellation of speech, Radial Basis Function networks, Gaussian and TPS kernels.

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2087 Chaos Theory and Application in Foreign Exchange Rates vs. IRR (Iranian Rial)

Authors: M. A. Torkamani, S. Mahmoodzadeh, S. Pourroostaei, C. Lucas

Abstract:

Daily production of information and importance of the sequence of produced data in forecasting future performance of market causes analysis of data behavior to become a problem of analyzing time series. But time series that are very complicated, usually are random and as a result their changes considered being unpredictable. While these series might be products of a deterministic dynamical and nonlinear process (chaotic) and as a result be predictable. Point of Chaotic theory view, complicated systems have only chaotically face and as a result they seem to be unregulated and random, but it is possible that they abide by a specified math formula. In this article, with regard to test of strange attractor and biggest Lyapunov exponent probability of chaos on several foreign exchange rates vs. IRR (Iranian Rial) has been investigated. Results show that data in this market have complex chaotic behavior with big degree of freedom.

Keywords: Chaos, Exchange Rate, Nonlinear Models.

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2086 Application of Wavelet Neural Networks in Optimization of Skeletal Buildings under Frequency Constraints

Authors: Mohammad Reza Ghasemi, Amin Ghorbani

Abstract:

The main goal of the present work is to decrease the computational burden for optimum design of steel frames with frequency constraints using a new type of neural networks called Wavelet Neural Network. It is contested to train a suitable neural network for frequency approximation work as the analysis program. The combination of wavelet theory and Neural Networks (NN) has lead to the development of wavelet neural networks. Wavelet neural networks are feed-forward networks using wavelet as activation function. Wavelets are mathematical functions within suitable inner parameters, which help them to approximate arbitrary functions. WNN was used to predict the frequency of the structures. In WNN a RAtional function with Second order Poles (RASP) wavelet was used as a transfer function. It is shown that the convergence speed was faster than other neural networks. Also comparisons of WNN with the embedded Artificial Neural Network (ANN) and with approximate techniques and also with analytical solutions are available in the literature.

Keywords: Weight Minimization, Frequency Constraints, Steel Frames, ANN, WNN, RASP Function.

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2085 A New Concept for Deriving the Expected Value of Fuzzy Random Variables

Authors: Liang-Hsuan Chen, Chia-Jung Chang

Abstract:

Fuzzy random variables have been introduced as an imprecise concept of numeric values for characterizing the imprecise knowledge. The descriptive parameters can be used to describe the primary features of a set of fuzzy random observations. In fuzzy environments, the expected values are usually represented as fuzzy-valued, interval-valued or numeric-valued descriptive parameters using various metrics. Instead of the concept of area metric that is usually adopted in the relevant studies, the numeric expected value is proposed by the concept of distance metric in this study based on two characters (fuzziness and randomness) of FRVs. Comparing with the existing measures, although the results show that the proposed numeric expected value is same with those using the different metric, if only triangular membership functions are used. However, the proposed approach has the advantages of intuitiveness and computational efficiency, when the membership functions are not triangular types. An example with three datasets is provided for verifying the proposed approach.

Keywords: Fuzzy random variables, Distance measure, Expected value.

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