Search results for: constant modulus algorithm

Authors: D. P. Sharma, A. Chaturvedi, G.Purohit , R.Shivarudraswamy

Abstract:

In today scenario, to meet enhanced demand imposed by domestic, commercial and industrial consumers, various operational & control activities of Radial Distribution Network (RDN) requires a focused attention. Irrespective of sub-domains research aspects of RDN like network reconfiguration, reactive power compensation and economic load scheduling etc, network performance parameters are usually estimated by an iterative process and is commonly known as load (power) flow algorithm. In this paper, a simple mechanism is presented to implement the load flow analysis (LFA) algorithm. The reported algorithm utilizes graph theory principles and is tested on a 69- bus RDN.

Keywords: Radial Distribution network, Graph, Load-flow, Array.

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Authors: Mhand Hifi, Hedi Mhalla, Mustapha Michaphy

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In this paper, we study the multi-scenario knapsack problem, a variant of the well-known NP-Hard single knapsack problem. We investigate the use of an adaptive algorithm for solving heuristically the problem. The used method combines two complementary phases: a size reduction phase and a dynamic 2- opt procedure one. First, the reduction phase applies a polynomial reduction strategy; that is used for reducing the size problem. Second, the adaptive search procedure is applied in order to attain a feasible solution Finally, the performances of two versions of the proposed algorithm are evaluated on a set of randomly generated instances.

Keywords: combinatorial optimization, max-min optimization, knapsack, heuristics, problem reduction

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Authors: Mike Sewell, Jagath Samarabandu, Ranga Rodrigo, Kenneth McIsaac

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A novel method of individual level adaptive mutation rate control called the rank-scaled mutation rate for genetic algorithms is introduced. The rank-scaled mutation rate controlled genetic algorithm varies the mutation parameters based on the rank of each individual within the population. Thereby the distribution of the fitness of the papulation is taken into consideration in forming the new mutation rates. The best fit mutate at the lowest rate and the least fit mutate at the highest rate. The complexity of the algorithm is of the order of an individual adaptation scheme and is lower than that of a self-adaptation scheme. The proposed algorithm is tested on two common problems, namely, numerical optimization of a function and the traveling salesman problem. The results show that the proposed algorithm outperforms both the fixed and deterministic mutation rate schemes. It is best suited for problems with several local optimum solutions without a high demand for excessive mutation rates.

Keywords: Genetic algorithms, mutation rate control, adaptive mutation.

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Authors: P. Phokharatkul, K. Sankhuangaw, S. Somkuarnpanit, S. Phaiboon, C. Kimpan

Abstract:

Much research into handwritten Thai character recognition have been proposed, such as comparing heads of characters, Fuzzy logic and structure trees, etc. This paper presents a system of handwritten Thai character recognition, which is based on the Ant-minor algorithm (data mining based on Ant colony optimization). Zoning is initially used to determine each character. Then three distinct features (also called attributes) of each character in each zone are extracted. The attributes are Head zone, End point, and Feature code. All attributes are used for construct the classification rules by an Ant-miner algorithm in order to classify 112 Thai characters. For this experiment, the Ant-miner algorithm is adapted, with a small change to increase the recognition rate. The result of this experiment is a 97% recognition rate of the training set (11200 characters) and 82.7% recognition rate of unseen data test (22400 characters).

Keywords: Hand written, Thai character recognition, Ant-mineralgorithm, distinct feature.

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Authors: Basant Kumar, Animesh Anand, S.P. Singh, Anand Mohan

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This paper presents a new spread-spectrum watermarking algorithm for digital images in discrete wavelet transform (DWT) domain. The algorithm is applied for embedding watermarks like patient identification /source identification or doctors signature in binary image format into host digital radiological image for potential telemedicine applications. Performance of the algorithm is analysed by varying the gain factor, subband decomposition levels, and size of watermark. Simulation results show that the proposed method achieves higher watermarking capacity.

Keywords: Watermarking, spread-spectrum, discrete wavelettransform, telemedicine

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Authors: Konstantinos Metaxiotis, Konstantinos Liagkouras

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The objective of this study is to examine the performance of three well-known multiobjective evolutionary algorithms for solving optimization problems. The first algorithm is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the second one is the Strength Pareto Evolutionary Algorithm 2 (SPEA-2), and the third one is the Multiobjective Evolutionary Algorithms based on decomposition (MOEA/D). The examined multiobjective algorithms are analyzed and tested on the ZDT set of test functions by three performance metrics. The results indicate that the NSGA-II performs better than the other two algorithms based on three performance metrics.

Keywords: MOEAs, Multiobjective optimization, ZDT test functions, performance metrics.

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Authors: C. Chitra, P. Subbaraj

Abstract:

The shortest path routing problem is a multiobjective nonlinear optimization problem with constraints. This problem has been addressed by considering Quality of service parameters, delay and cost objectives separately or as a weighted sum of both objectives. Multiobjective evolutionary algorithms can find multiple pareto-optimal solutions in one single run and this ability makes them attractive for solving problems with multiple and conflicting objectives. This paper uses an elitist multiobjective evolutionary algorithm based on the Non-dominated Sorting Genetic Algorithm (NSGA), for solving the dynamic shortest path routing problem in computer networks. A priority-based encoding scheme is proposed for population initialization. Elitism ensures that the best solution does not deteriorate in the next generations. Results for a sample test network have been presented to demonstrate the capabilities of the proposed approach to generate well-distributed pareto-optimal solutions of dynamic routing problem in one single run. The results obtained by NSGA are compared with single objective weighting factor method for which Genetic Algorithm (GA) was applied.

Keywords: Multiobjective optimization, Non-dominated Sorting Genetic Algorithm, Routing, Weighted sum.

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Authors: A. Peveri

Abstract:

The curvature space-time by the presence of material, this deformation must present a pattern of deformation, not random. Space is uniform, elastic and any modification that occurs in one part, causes a change in another.

This deformation exists, must be a constant value and is independent of the observer, and relates the amount of matter, the force caused by the curvature of space and surface space. This unit of space is defined in this study as PIL and represents a constant area of space, deformable in the direction and sense of the center of mass of the body. The PIL is curved and connected to the center of mass of the Earth, to get to that point, through all matter, thus forming part of any place between particles at atomic and subatomic levels. At these levels the space between each particle is flat, unlike the macro where the space curves.

Keywords: Space flat, Space curved, Unit of space, Deformation.

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Authors: R. Sahraian, A. Karampour Haghighi, E. Ghasemi

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Process planning and production scheduling play important roles in manufacturing systems. In this paper a multiobjective mixed integer linear programming model is presented for the integrated planning and scheduling of multi-product. The aim is to find a set of high-quality trade-off solutions. This is a combinatorial optimization problem with substantially large solution space, suggesting that it is highly difficult to find the best solutions with the exact search method. To account for it, a PSO-based algorithm is proposed by fully utilizing the capability of the exploration search and fast convergence. To fit the continuous PSO in the discrete modeled problem, a solution representation is used in the algorithm. The numerical experiments have been performed to demonstrate the effectiveness of the proposed algorithm.

Keywords: Integrated process planning and scheduling, multi objective, MILP, Particle swarm optimization

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Authors: Jonmichael A. Weaver, David A. Miller

Abstract:

Ultra High Molecular Weight Polyethylene (UHMWPE) presents several distinct advantages as a material with a high strength to weight ratio, durability, and neutron stability. Understanding the change in the mechanical performance of UHMWPE due to environmental exposure is key to safety for future applications. Dyneema® HB-210, a 15 µm diameter UHMWPE multi-filament fiber laid up in a polyurethane matrix in [0/ 90]2, with a thickness of 0.17 mm is compared to the same fiber and orientation system, HB-212, with a rubber-based matrix under UV aging conditions. UV aging tests according to ASTM-G154 were performed on both HB-210 and HB-212 to interrogate the change in mechanical properties, as measured through dynamic mechanical analysis and imaged using a scanning electron microscope. These results showed a decrease in both the storage modulus and loss modulus of the aged material compared to the unaged, even though the tan δ slightly increased. Material degradation occurred at a higher rate in Dyneema® HB-212 compared to HB-210. The HB-210 was characterized for the effects of 100 hours of UV aging via dynamic mechanical analysis. Scanning electron microscope images were taken of the HB-210 and HB-212 to identify the primary damage mechanisms in the matrix. Embrittlement and matrix spall were the products of prolonged UV exposure and erosion, resulting in decreased mechanical properties.

Keywords: Composite materials, material characterization, UV aging, UHMWPE.

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Authors: Alireza Gholami, Amir H. D. Markazi

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In this paper, an observer-based direct adaptive fuzzy sliding mode (OAFSM) algorithm is proposed. In the proposed algorithm, the zero-input dynamics of the plant could be unknown. The input connection matrix is used to combine the sliding surfaces of individual subsystems, and an adaptive fuzzy algorithm is used to estimate an equivalent sliding mode control input directly. The fuzzy membership functions, which were determined by time consuming try and error processes in previous works, are adjusted by adaptive algorithms. The other advantage of the proposed controller is that the input gain matrix is not limited to be diagonal, i.e. the plant could be over/under actuated provided that controllability and observability are preserved. An observer is constructed to directly estimate the state tracking error, and the nonlinear part of the observer is constructed by an adaptive fuzzy algorithm. The main advantage of the proposed observer is that, the measured outputs is not limited to the first entry of a canonical-form state vector. The closed-loop stability of the proposed method is proved using a Lyapunov-based approach. The proposed method is applied numerically on a multi-link robot manipulator, which verifies the performance of the closed-loop control. Moreover, the performance of the proposed algorithm is compared with some conventional control algorithms.

Keywords: Adaptive algorithm, fuzzy systems, membership functions, observer.

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Authors: V.P.Subramanyam Rallabandi, S.K.Sett

Abstract:

An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of independent non-Gaussian densities. The algorithm estimates the data density in each class by using parametric nonlinear functions that fit to the non-Gaussian structure of the data. This improves classification accuracy compared with standard Gaussian mixture models. When applied to textures, the algorithm can learn basis functions for images that capture the statistically significant structure intrinsic in the images. We apply this technique to the problem of unsupervised texture classification and segmentation.

Keywords: Gaussian Mixture Model, Independent Component Analysis, Segmentation, Unsupervised Classification.

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Authors: S. Vural, H. Yamauchi

Abstract:

Current systems for face recognition techniques often use either SVM or Adaboost techniques for face detection part and use PCA for face recognition part. In this paper, we offer a novel method for not only a powerful face detection system based on Six-segment-filters (SSR) and Adaboost learning algorithms but also for a face recognition system. A new exclusive face detection algorithm has been developed and connected with the recognition algorithm. As a result of it, we obtained an overall high-system performance compared with current systems. The proposed algorithm was tested on CMU, FERET, UNIBE, MIT face databases and significant performance has obtained.

Keywords: Adaboost, Face Detection, Face recognition, SVM, Gabor filters, PCA-ICA.

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Authors: David Avis, Luc Devroye, Kazuo Iwama

Abstract:

We consider a cooperative game played by n players against a referee. The players names are randomly distributed among n lockers, with one name per locker. Each player can open up to half the lockers and each player must find his name. Once the game starts the players may not communicate. It has been previously shown that, quite surprisingly, an optimal strategy exists for which the success probability is never worse than 1 − ln 2 ≈ 0.306. In this paper we consider an extension where the number of lockers is greater than the number of players, so that some lockers are empty. We show that the players may still win with positive probability even if there are a constant k number of empty lockers. We show that for each fixed probability p, there is a constant c so that the players can win with probability at least p if they are allowed to open cn lockers.

Keywords: Locker problem, pointer-following algorithms.

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Authors: Ivan C. Mustakerov, Daniela I. Borissova

Abstract:

The paper proposes an approach to ranking a set of potential countries to invest taking into account the investor point of view about importance of different economic indicators. For the goal, a ranking algorithm that contributes to rational decision making is proposed. The described algorithm is based on combinatorial optimization modeling and repeated multi-criteria tasks solution. The final result is list of countries ranked in respect of investor preferences about importance of economic indicators for investment attractiveness. Different scenarios are simulated conforming to different investors preferences. A numerical example with real dataset of indicators is solved. The numerical testing shows the applicability of the described algorithm. The proposed approach can be used with any sets of indicators as ranking criteria reflecting different points of view of investors. 

Keywords: Combinatorial optimization modeling, economics investment attractiveness, economics ranking algorithm, multi-criteria problems.

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Authors: Khaled M.EL-Naggar

Abstract:

In power systems, protective relays must filter their inputs to remove undesirable quantities and retain signal quantities of interest. This job must be performed accurate and fast. A new method for filtering the undesirable components such as DC and harmonic components associated with the fundamental system signals. The method is s based on a dynamic filtering algorithm. The filtering algorithm has many advantages over some other classical methods. It can be used as dynamic on-line filter without the need of parameters readjusting as in the case of classic filters. The proposed filter is tested using different signals. Effects of number of samples and sampling window size are discussed. Results obtained are presented and discussed to show the algorithm capabilities.

Keywords: Protection, DC-offset, Dynamic Filter, Estimation.

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Authors: M. Pourahmadi

Abstract:

The performance of time-reversal MUSIC algorithm will be dramatically degrades in presence of strong noise and multiple scattering (i.e. when scatterers are close to each other). This is due to error in determining the number of scatterers. The present paper provides a new approach to alleviate such a problem using an information theoretic criterion referred as minimum description length (MDL). The merits of the novel approach are confirmed by the numerical examples. The results indicate the time-reversal MUSIC yields accurate estimate of the target locations with considerable noise and multiple scattering in the received signals.

Keywords: Microwave imaging, Time reversal, MUSIC algorithm, Minimum Description Length (MDL).

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Authors: K. Kasiri, M. J. Dehghani

Abstract:

In this paper we propose a blind algorithm for peakto- average power ratio (PAPR) reduction in OFDM systems, based on selected mapping (SLM) algorithm as a distortionless method. The main drawback of the conventional SLM technique is the need for transmission of several side information bits, for each data block, which results in loss in data rate transmission. In the proposed method some special number of carriers in the OFDM frame is reserved to be rotated with one of the possible phases according to the number of phase sequence blocks in SLM algorithm. Reserving some limited number of carriers wont effect the reduction in PAPR of OFDM signal. Simulation results show using ML criteria at the receiver will lead to the same system-performance as the conventional SLM algorithm, while there is no need to send any side information to the receiver.

Keywords: Orthogonal Frequency Division Multiplexing(OFDM), Peak-to-Average Power Ratio (PAPR), Selected Mapping(SLM), Blind SLM (BSLM).

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Authors: Mohamed Al Mahdi Eshtawie, Masuri Bin Othman

Abstract:

Finite impulse response (FIR) filters have the advantage of linear phase, guaranteed stability, fewer finite precision errors, and efficient implementation. In contrast, they have a major disadvantage of high order need (more coefficients) than IIR counterpart with comparable performance. The high order demand imposes more hardware requirements, arithmetic operations, area usage, and power consumption when designing and fabricating the filter. Therefore, minimizing or reducing these parameters, is a major goal or target in digital filter design task. This paper presents an algorithm proposed for modifying values and the number of non-zero coefficients used to represent the FIR digital pulse shaping filter response. With this algorithm, the FIR filter frequency and phase response can be represented with a minimum number of non-zero coefficients. Therefore, reducing the arithmetic complexity needed to get the filter output. Consequently, the system characteristic i.e. power consumption, area usage, and processing time are also reduced. The proposed algorithm is more powerful when integrated with multiplierless algorithms such as distributed arithmetic (DA) in designing high order digital FIR filters. Here the DA usage eliminates the need for multipliers when implementing the multiply and accumulate unit (MAC) and the proposed algorithm will reduce the number of adders and addition operations needed through the minimization of the non-zero values coefficients to get the filter output.

Keywords: Pulse shaping Filter, Distributed Arithmetic, Optimization algorithm.

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Authors: Shilpi Lavania, Deepak Nagaria

Abstract:

A mixed method for model order reduction is presented in this paper. The denominator polynomial is derived by matching both Markov parameters and time moments, whereas numerator polynomial derivation and error minimization is done using Genetic Algorithm. The efficiency of the proposed method can be investigated in terms of closeness of the response of reduced order model with respect to that of higher order original model and a comparison of the integral square error as well.

Keywords: Model Order Reduction (MOR), control theory, Markov parameters, time moments, genetic algorithm, Single Input Single Output (SISO).

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Authors: Marianna I. Triantou, Petroula A. Tarantili

Abstract:

In this research work, poly (acrylonitrile-butadienestyrene)/ polypropylene (ABS/PP) blends were processed by melt compounding in a twin-screw extruder. Upgrading of the thermal characteristics of the obtained materials was attempted by the incorporation of organically modified montmorillonite (OMMT), as well as, by the addition of two types of compatibilizers; polypropylene grafted with maleic anhydride (PP-g-MAH) and ABS grafted with maleic anhydride (ABS-g-MAH). The effect of the above treatments was investigated separately and in combination. Increasing the PP content in ABS matrix seems to increase the thermal stability of their blend and the glass transition temperature (Tg) of SAN phase of ABS. From the other part, the addition of ABS to PP promotes the formation of its β-phase, which is maximum at 30 wt% ABS concentration, and increases the crystallization temperature (Tc) of PP. In addition, it increases the crystallization rate of PP.The β-phase of PP in ABS/PP blends is reduced by the addition of compatibilizers or/and organoclay reinforcement. The incorporation of compatibilizers increases the thermal stability of PP and reduces its melting (ΔΗm) and crystallization (ΔΗc) enthalpies. Furthermore it decreases slightly the Tgs of PP and SAN phases of ABS/PP blends. Regarding the storage modulus of the ABS/PP blends, it presents a change in their behavior at about 10°C and return to their initial behavior at ~110°C. The incorporation of OMMT to no compatibilized and compatibilized ABS/PP blends enhances their storage modulus.

Keywords: Acrylonitrile, butadiene, styrene terpolymer, compatibilizer, organoclay, polypropylene.

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Authors: Saimir Heta, Ilma Robo, Rialda Xhizdari, Kers Kapaj

Abstract:

The stability of an ideal disinfectant should be constant regardless of the change in the atmospheric conditions of the environment where it is kept. If the conditions such as temperature or humidity change, it is understood that it will also be necessary to approach possible changes in the holding materials such as plastic or glass bottles with the aim of protecting the disinfectant, for example, from the excessive lighting of the environment, which can also be translated as an increase in the temperature of disinfectant as a fluid. In this study, an attempt was made to find the most recent published data about the best possible combination of disinfectants indicated for use after dental procedures. This purpose of the study was realized by comparing the basic literature that is studied in the field of dentistry by students with the most published data in the literature of recent years about this topic. Each disinfectant is represented by a number called the disinfectant count, in which different factors can influence the increase or reduction of variables whose production remains a specific statistic for a specific disinfectant. The changes in the atmospheric conditions where the disinfectant is deposited and stored in the environment are known to affect the stability of the disinfectant as a fluid; this fact is known and even cited in the leaflets accompanying the manufactured boxes of disinfectants. It is these cares, in the form of advice, which are based not only on the preservation of the disinfectant but also on the application in order to have the desired clinical result. Aldehydes have the highest constant among the types of disinfectants, followed by acids. The lowest value of the constant belongs to the class of glycols, the predecessors of which were the halogens, in which class there are some representatives with disinfection applications. The class of phenols and acids have almost the same intervals of constants. If the goal were to find the ideal disinfectant among the large variety of disinfectants produced, a good starting point would be to find something unchanging or a fixed, unchanging element on the basis of which the comparison can be made properties of different disinfectants. Precisely based on the results of this study, the role of the specific constant according to the specific disinfectant is highlighted. Finding an ideal disinfectant, like finding a medication or the ideal antibiotic, is an ongoing but unattainable goal.

Keywords: Different disinfectants, phenols, aldehydes, specific constant, dental procedures.

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Authors: A.Larabi, M.S. Boucherit

Abstract:

In this paper, we investigated vector control of an induction machine taking into account discretization problems of the command. In the purpose to show how to include in a discrete model of this current control and with rotor time constant update. The results of simulation obtained are very satisfaisant. That was possible thanks to the good choice of the values of the parameters of the regulators used which shows, the founded good of the method used, for the choice of the parameters of the discrete regulators. The simulation results are presented at the end of this paper.

Keywords: Induction motor, discrete vector control, PIRegulator, transformation of park, PWM.

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Authors: Mona Heydari, Ehsan Motamedian, Seyed Abbas Shojaosadati

Abstract:

Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain.

Keywords: Metabolic network, gene knockout, flux balance analysis, microarray data, integration.

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Authors: Gregor A. Morrison, Dominic P. Searson, Mark J. Willis

Abstract:

The purpose of this paper is to demonstrate the ability of a genetic programming (GP) algorithm to evolve a team of data classification models. The GP algorithm used in this work is “multigene" in nature, i.e. there are multiple tree structures (genes) that are used to represent team members. Each team member assigns a data sample to one of a fixed set of output classes. A majority vote, determined using the mode (highest occurrence) of classes predicted by the individual genes, is used to determine the final class prediction. The algorithm is tested on a binary classification problem. For the case study investigated, compact classification models are obtained with comparable accuracy to alternative approaches.

Keywords: classification, genetic programming.

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Authors: Qing Lyu, Hang Zhu

Abstract:

Various flows in the network require to go through different types of middlebox. The improper placement of network middlebox and path assignment for flows could greatly increase the network latency and also decrease the performance of network. Minimizing the total end to end latency of all the ows requires to assign path for the incoming flows. In this paper, the flow path assignment problem in regard to the placement of various kinds of middlebox is studied. The flow path assignment problem is formulated to a linear programming problem, which is very time consuming. On the other hand, a naive greedy algorithm is studied. Which is very fast but causes much more latency than the linear programming algorithm. At last, the paper presents a heuristic algorithm named FPA, which takes bottleneck link information and estimated bandwidth occupancy into consideration, and achieves near optimal latency in much less time. Evaluation results validate the effectiveness of the proposed algorithm.

Keywords: Latency, Fast path assignment, Bottleneck link.

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Authors: A. A. Hossam-Eldin, E. N. Abdallah, M. S. El-Nozahy

Abstract:

The identification and elimination of bad measurements is one of the basic functions of a robust state estimator as bad data have the effect of corrupting the results of state estimation according to the popular weighted least squares method. However this is a difficult problem to handle especially when dealing with multiple errors from the interactive conforming type. In this paper, a self adaptive genetic based algorithm is proposed. The algorithm utilizes the results of the classical linearized normal residuals approach to tune the genetic operators thus instead of making a randomized search throughout the whole search space it is more likely to be a directed search thus the optimum solution is obtained at very early stages(maximum of 5 generations). The algorithm utilizes the accumulating databases of already computed cases to reduce the computational burden to minimum. Tests are conducted with reference to the standard IEEE test systems. Test results are very promising.

Keywords: Bad Data, Genetic Algorithms, Linearized Normal residuals, Observability, Power System State Estimation.

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Authors: Zong Chen

Abstract:

Motion estimation is a key problem in video processing and computer vision. Optical flow motion estimation can achieve high estimation accuracy when motion vector is small. Three-step search algorithm can handle large motion vector but not very accurate. A joint algorithm was proposed in this paper to achieve high estimation accuracy disregarding whether the motion vector is small or large, and keep the computation cost much lower than full search.

Keywords: Motion estimation, Block Matching, Optical flow, Three step search.

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Authors: J. Liu, Z. P. Yu, L. Xiong, Y. Feng, J. He

Abstract:

According to the independence, accuracy and controllability of the driving/braking torque of the distributed drive electric vehicle, a control strategy of differential drive assisted steering was designed. Firstly, the assisted curve under different speed and steering wheel torque was developed and the differential torques were distributed to the right and left front wheels. Then the steering return ability assisted control algorithm was designed. At last, the joint simulation was conducted by CarSim/Simulink. The result indicated: the differential drive assisted steering algorithm could provide enough steering drive-assisted under low speed and improve the steering portability. Along with the increase of the speed, the provided steering drive-assisted decreased. With the control algorithm, the steering stiffness of the steering system increased along with the increase of the speed, which ensures the driver’s road feeling. The control algorithm of differential drive assisted steering could avoid the understeer under low speed effectively.

Keywords: Differential assisted steering, control strategy, distributed drive electric vehicle.

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Authors: N. Arulanand, P. Dhara

Abstract:

Optimizing the parameters in the controller plays a vital role in the control theory and its applications. Optimizing the PID parameters is finding out the best value from the feasible solutions. Finding the optimal value is an optimization problem. Inverted Pendulum is a very good platform for control engineers to verify and apply different logics in the field of control theory. It is necessary to find an optimization technique for the controller to tune the values automatically in order to minimize the error within the given bounds. In this paper, the algorithmic concepts of Harmony search (HS) and Genetic Algorithm (GA) have been analyzed for the given range of values. The experimental results show that HS performs well than GA.

Keywords: Genetic Algorithm, Harmony Search Algorithm, Inverted Pendulum, PID Controller.

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