Search results for: mathematical algorithm
3366 Multi-VSS Scheme by Shifting Random Grids
Authors: Joy Jo-Yi Chang, Justie Su-Tzu Juan
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Visual secret sharing (VSS) was proposed by Naor and Shamir in 1995. Visual secret sharing schemes encode a secret image into two or more share images, and single share image can’t obtain any information about the secret image. When superimposes the shares, it can restore the secret by human vision. Due to the traditional VSS have some problems like pixel expansion and the cost of sophisticated. And this method only can encode one secret image. The schemes of encrypting more secret images by random grids into two shares were proposed by Chen et al. in 2008. But when those restored secret images have much distortion, those schemes are almost limited in decoding. In the other words, if there is too much distortion, we can’t encrypt too much information. So, if we can adjust distortion to very small, we can encrypt more secret images. In this paper, four new algorithms which based on Chang et al.’s scheme be held in 2010 are proposed. First algorithm can adjust distortion to very small. Second algorithm distributes the distortion into two restored secret images. Third algorithm achieves no distortion for special secret images. Fourth algorithm encrypts three secret images, which not only retain the advantage of VSS but also improve on the problems of decoding.
Keywords: Visual cryptography, visual secret sharing, random grids, multiple, secret image sharing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15263365 Sensorless Speed Based on MRAS with Tuning of IP Speed Controller in FOC of Induction Motor Drive Using PSO
Authors: Youcef Bekakra, Djilani Ben attous
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In this paper, a field oriented control (FOC) induction motor drive is presented. In order to eliminate the speed sensor, an adaptation algorithm for tuning the rotor speed is proposed. Based on the Model Reference Adaptive System (MRAS) scheme, the rotor speed is tuned to obtain an exact FOC induction motor drive. The reference and adjustable models, developed in stationary stator reference frame, are used in the MRAS scheme to estimate induction rotor speed from measured terminal voltages and currents. The Integral Proportional (IP) gains speed controller are tuned by a modern approach that is the Particle Swarm Optimization (PSO) algorithm in order to optimize the parameters of the IP controller. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. The proposed algorithm has been tested by numerical simulation, showing the capability of driving load.
Keywords: Induction motor drive, field oriented control, model reference adaptive system (MRAS), particle swarm optimization (PSO).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20113364 Heuristic Search Algorithm (HSA) for Enhancing the Lifetime of Wireless Sensor Networks
Authors: Tripatjot S. Panag, J. S. Dhillon
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The lifetime of a wireless sensor network can be effectively increased by using scheduling operations. Once the sensors are randomly deployed, the task at hand is to find the largest number of disjoint sets of sensors such that every sensor set provides complete coverage of the target area. At any instant, only one of these disjoint sets is switched on, while all other are switched off. This paper proposes a heuristic search method to find the maximum number of disjoint sets that completely cover the region. A population of randomly initialized members is made to explore the solution space. A set of heuristics has been applied to guide the members to a possible solution in their neighborhood. The heuristics escalate the convergence of the algorithm. The best solution explored by the population is recorded and is continuously updated. The proposed algorithm has been tested for applications which require sensing of multiple target points, referred to as point coverage applications. Results show that the proposed algorithm outclasses the existing algorithms. It always finds the optimum solution, and that too by making fewer number of fitness function evaluations than the existing approaches.Keywords: Coverage, disjoint sets, heuristic, lifetime, scheduling, wireless sensor networks, WSN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18413363 Simulated Annealing Algorithm for Data Aggregation Trees in Wireless Sensor Networks and Comparison with Genetic Algorithm
Authors: Ladan Darougaran, Hossein Shahinzadeh, Hajar Ghotb, Leila Ramezanpour
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In ad hoc networks, the main issue about designing of protocols is quality of service, so that in wireless sensor networks the main constraint in designing protocols is limited energy of sensors. In fact, protocols which minimize the power consumption in sensors are more considered in wireless sensor networks. One approach of reducing energy consumption in wireless sensor networks is to reduce the number of packages that are transmitted in network. The technique of collecting data that combines related data and prevent transmission of additional packages in network can be effective in the reducing of transmitted packages- number. According to this fact that information processing consumes less power than information transmitting, Data Aggregation has great importance and because of this fact this technique is used in many protocols [5]. One of the Data Aggregation techniques is to use Data Aggregation tree. But finding one optimum Data Aggregation tree to collect data in networks with one sink is a NP-hard problem. In the Data Aggregation technique, related information packages are combined in intermediate nodes and form one package. So the number of packages which are transmitted in network reduces and therefore, less energy will be consumed that at last results in improvement of longevity of network. Heuristic methods are used in order to solve the NP-hard problem that one of these optimization methods is to solve Simulated Annealing problems. In this article, we will propose new method in order to build data collection tree in wireless sensor networks by using Simulated Annealing algorithm and we will evaluate its efficiency whit Genetic Algorithm.
Keywords: Data aggregation, wireless sensor networks, energy efficiency, simulated annealing algorithm, genetic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16833362 Applying Fuzzy FP-Growth to Mine Fuzzy Association Rules
Authors: Chien-Hua Wang, Wei-Hsuan Lee, Chin-Tzong Pang
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In data mining, the association rules are used to find for the associations between the different items of the transactions database. As the data collected and stored, rules of value can be found through association rules, which can be applied to help managers execute marketing strategies and establish sound market frameworks. This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth) to derive from fuzzy association rules. At first, we apply fuzzy partition methods and decide a membership function of quantitative value for each transaction item. Next, we implement FFP-growth to deal with the process of data mining. In addition, in order to understand the impact of Apriori algorithm and FFP-growth algorithm on the execution time and the number of generated association rules, the experiment will be performed by using different sizes of databases and thresholds. Lastly, the experiment results show FFPgrowth algorithm is more efficient than other existing methods.Keywords: Data mining, association rule, fuzzy frequent patterngrowth.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18003361 Contourlet versus Wavelet Transform for a Robust Digital Image Watermarking Technique
Authors: Ibrahim A. El rube, Mohamad Abou El Nasr , Mostafa M. Naim, Mahmoud Farouk
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In this paper, a watermarking algorithm that uses the wavelet transform with Multiple Description Coding (MDC) and Quantization Index Modulation (QIM) concepts is introduced. Also, the paper investigates the role of Contourlet Transform (CT) versus Wavelet Transform (WT) in providing robust image watermarking. Two measures are utilized in the comparison between the waveletbased and the contourlet-based methods; Peak Signal to Noise Ratio (PSNR) and Normalized Cross-Correlation (NCC). Experimental results reveal that the introduced algorithm is robust against different attacks and has good results compared to the contourlet-based algorithm.
Keywords: image watermarking; discrete wavelet transform, discrete contourlet transform, multiple description coding, quantization index modulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20673360 On One Mathematical Model for Filtration of Weakly Compressible Chemical Compound in the Porous Heterogeneous 3D Medium. Part I: Model Construction with the Aid of the Ollendorff Approach
Authors: Sharif E. Guseynov, Jekaterina V. Aleksejeva, Janis S. Rimshans
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A filtering problem of almost incompressible liquid chemical compound in the porous inhomogeneous 3D domain is studied. In this work general approaches to the solution of twodimensional filtering problems in ananisotropic, inhomogeneous and multilayered medium are developed, and on the basis of the obtained results mathematical models are constructed (according to Ollendorff method) for studying the certain engineering and technical problem of filtering the almost incompressible liquid chemical compound in the porous inhomogeneous 3D domain. For some of the formulated mathematical problems with additional requirements for the structure of the porous inhomogeneous medium, namely, its isotropy, spatial periodicity of its permeability coefficient, solution algorithms are proposed. Continuation of the current work titled ”On one mathematical model for filtration of weakly compressible chemical compound in the porous heterogeneous 3D medium. Part II: Determination of the reference directions of anisotropy and permeabilities on these directions” will be prepared in the shortest terms by the authors.
Keywords: Porous media, filtering, permeability, elliptic PDE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17553359 A New Distribution Network Reconfiguration Approach using a Tree Model
Authors: E. Dolatdar, S. Soleymani, B. Mozafari
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Power loss reduction is one of the main targets in power industry and so in this paper, the problem of finding the optimal configuration of a radial distribution system for loss reduction is considered. Optimal reconfiguration involves the selection of the best set of branches to be opened ,one each from each loop, for reducing resistive line losses , and reliving overloads on feeders by shifting the load to adjacent feeders. However ,since there are many candidate switching combinations in the system ,the feeder reconfiguration is a complicated problem. In this paper a new approach is proposed based on a simple optimum loss calculation by determining optimal trees of the given network. From graph theory a distribution network can be represented with a graph that consists a set of nodes and branches. In fact this problem can be viewed as a problem of determining an optimal tree of the graph which simultaneously ensure radial structure of each candidate topology .In this method the refined genetic algorithm is also set up and some improvements of algorithm are made on chromosome coding. In this paper an implementation of the algorithm presented by [7] is applied by modifying in load flow program and a comparison of this method with the proposed method is employed. In [7] an algorithm is proposed that the choice of the switches to be opened is based on simple heuristic rules. This algorithm reduce the number of load flow runs and also reduce the switching combinations to a fewer number and gives the optimum solution. To demonstrate the validity of these methods computer simulations with PSAT and MATLAB programs are carried out on 33-bus test system. The results show that the performance of the proposed method is better than [7] method and also other methods.
Keywords: Distribution System, Reconfiguration, Loss Reduction , Graph Theory , Optimization , Genetic Algorithm
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37823358 Loop Back Connected Component Labeling Algorithm and Its Implementation in Detecting Face
Authors: A. Rakhmadi, M. S. M. Rahim, A. Bade, H. Haron, I. M. Amin
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In this study, a Loop Back Algorithm for component connected labeling for detecting objects in a digital image is presented. The approach is using loop back connected component labeling algorithm that helps the system to distinguish the object detected according to their label. Deferent than whole window scanning technique, this technique reduces the searching time for locating the object by focusing on the suspected object based on certain features defined. In this study, the approach was also implemented for a face detection system. Face detection system is becoming interesting research since there are many devices or systems that require detecting the face for certain purposes. The input can be from still image or videos, therefore the sub process of this system has to be simple, efficient and accurate to give a good result.Keywords: Image processing, connected components labeling, face detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23003357 Making Computer Learn Color
Authors: Rinaldo Christian Tanumara, Ming Xie
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Color categorization is shared among members in a society. This allows communication of color, especially when using natural language such as English. Hence sociable robot, to live coexist with human in human society, must also have the shared color categorization. To achieve this, many works have been done relying on modeling of human color perception and mathematical complexities. In contrast, in this work, the computer as brain of the robot learns color categorization through interaction with humans without much mathematical complexities.Keywords: Color categorization, color learning, machinelearning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14413356 Resource-Constrained Heterogeneous Workflow Scheduling Algorithm for Heterogeneous Computing Clusters
Authors: Lei Wang, Jiahao Zhou
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The development of heterogeneous computing clusters provides robust computational support for large-scale workflows, commonly seen in domains such as scientific computing and artificial intelligence. However, the tasks within these large-scale workflows are increasingly heterogeneous, exhibiting varying demands on computing resources. This shift necessitates the integration of resource-constrained considerations into the workflow scheduling problem on heterogeneous computing platforms. In this study, we propose a scheduling algorithm designed to minimize the makespan under heterogeneous constraints, employing a greedy strategy to effectively address the scheduling challenges posed by heterogeneous workflows. We evaluate the performance of the proposed algorithm using randomly generated heterogeneous workflows and a corresponding heterogeneous computing platform. The experimental results demonstrate a 15.2% improvement in performance compared to existing state-of-the-art methods.
Keywords: Heterogeneous Computing, Workflow Scheduling, Constrained Resources, Minimal Makespan.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 283355 Dynamic Routing to Multiple Destinations in IP Networks using Hybrid Genetic Algorithm (DRHGA)
Authors: K. Vijayalakshmi, S. Radhakrishnan
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In this paper we have proposed a novel dynamic least cost multicast routing protocol using hybrid genetic algorithm for IP networks. Our protocol finds the multicast tree with minimum cost subject to delay, degree, and bandwidth constraints. The proposed protocol has the following features: i. Heuristic local search function has been devised and embedded with normal genetic operation to increase the speed and to get the optimized tree, ii. It is efficient to handle the dynamic situation arises due to either change in the multicast group membership or node / link failure, iii. Two different crossover and mutation probabilities have been used for maintaining the diversity of solution and quick convergence. The simulation results have shown that our proposed protocol generates dynamic multicast tree with lower cost. Results have also shown that the proposed algorithm has better convergence rate, better dynamic request success rate and less execution time than other existing algorithms. Effects of degree and delay constraints have also been analyzed for the multicast tree interns of search success rate.
Keywords: Dynamic Group membership change, Hybrid Genetic Algorithm, Link / node failure, QoS Parameters.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14483354 Error Effects on SAR Image Resolution using Range Doppler Imaging Algorithm
Authors: Su Su Yi Mon, Fang Jiancheng
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Synthetic Aperture Radar (SAR) is an imaging radar form by taking full advantage of the relative movement of the antenna with respect to the target. Through the simultaneous processing of the radar reflections over the movement of the antenna via the Range Doppler Algorithm (RDA), the superior resolution of a theoretical wider antenna, termed synthetic aperture, is obtained. Therefore, SAR can achieve high resolution two dimensional imagery of the ground surface. In addition, two filtering steps in range and azimuth direction provide accurate enough result. This paper develops a simulation in which realistic SAR images can be generated. Also, the effect of velocity errors in the resulting image has also been investigated. Taking some velocity errors into account, the simulation results on the image resolution would be presented. Most of the times, algorithms need to be adjusted for particular datasets, or particular applications.
Keywords: Synthetic Aperture Radar (SAR), Range Doppler Algorithm (RDA), Image Resolution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33483353 Optimal Embedded Generation Allocation in Distribution System Employing Real Coded Genetic Algorithm Method
Authors: Mohd Herwan Sulaiman, Omar Aliman, Siti Rafidah Abdul Rahim
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This paper proposes a new methodology for the optimal allocation and sizing of Embedded Generation (EG) employing Real Coded Genetic Algorithm (RCGA) to minimize the total power losses and to improve voltage profiles in the radial distribution networks. RCGA is a method that uses continuous floating numbers as representation which is different from conventional binary numbers. The RCGA is used as solution tool, which can determine the optimal location and size of EG in radial system simultaneously. This method is developed in MATLAB. The effect of EG units- installation and their sizing to the distribution networks are demonstrated using 24 bus system.Keywords: Embedded generation (EG), load flow study, optimal allocation, real coded genetic algorithm (RCGA).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19033352 Wavelet-Based Despeckling of Synthetic Aperture Radar Images Using Adaptive and Mean Filters
Authors: Syed Musharaf Ali, Muhammad Younus Javed, Naveed Sarfraz Khattak
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In this paper we introduced new wavelet based algorithm for speckle reduction of synthetic aperture radar images, which uses combination of undecimated wavelet transformation, wiener filter (which is an adaptive filter) and mean filter. Further more instead of using existing thresholding techniques such as sure shrinkage, Bayesian shrinkage, universal thresholding, normal thresholding, visu thresholding, soft and hard thresholding, we use brute force thresholding, which iteratively run the whole algorithm for each possible candidate value of threshold and saves each result in array and finally selects the value for threshold that gives best possible results. That is why it is slow as compared to existing thresholding techniques but gives best results under the given algorithm for speckle reduction.
Keywords: Brute force thresholding, directional smoothing, direction dependent mask, undecimated wavelet transformation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28803351 Optimized Delay Constrained QoS Routing
Authors: P. S. Prakash, S. Selvan
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QoS Routing aims to find paths between senders and receivers satisfying the QoS requirements of the application which efficiently using the network resources and underlying routing algorithm to be able to find low-cost paths that satisfy given QoS constraints. The problem of finding least-cost routing is known to be NP-hard or complete and some algorithms have been proposed to find a near optimal solution. But these heuristics or algorithms either impose relationships among the link metrics to reduce the complexity of the problem which may limit the general applicability of the heuristic, or are too costly in terms of execution time to be applicable to large networks. In this paper, we concentrate an algorithm that finds a near-optimal solution fast and we named this algorithm as optimized Delay Constrained Routing (ODCR), which uses an adaptive path weight function together with an additional constraint imposed on the path cost, to restrict search space and hence ODCR finds near optimal solution in much quicker time.Keywords: QoS, Delay, Routing, Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12133350 Robust Parameter and Scale Factor Estimation in Nonstationary and Impulsive Noise Environment
Authors: Zoran D. Banjac, Branko D. Kovacevic
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The problem of FIR system parameter estimation has been considered in the paper. A new robust recursive algorithm for simultaneously estimation of parameters and scale factor of prediction residuals in non-stationary environment corrupted by impulsive noise has been proposed. The performance of derived algorithm has been tested by simulations.
Keywords: Adaptive filtering, Non-Gaussian filtering, Robustestimation, Scale factor estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17073349 Mass Transfer of Paracetamol from the Crosslinked Carrageenan-Polyvinyl Alcohol Film
Authors: Sperisa Distantina, Rieke Ulfha Noviyanti, Sri Sutriyani, Fadilah Fadilah, Mujtahid Kaavessina
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In this research, carrageenan extracted from seaweed Eucheuma cottonii was mixed with polyvinyl alcohol (PVA) and then crosslinked using glutaraldehyde (GA). The obtained hydrogel films were applied to control the drug release rate of paracetamol. The aim of this research was to develop a mathematical model that can be used to describe the mass transfer rate of paracetamol from the hydrogel film into buffer solution. The effect of weight ratio carrageenan-PVA (5: 0, 1: 0.5, 1: 1, 1: 2, 0: 5) on the parameters of the mathematical model was investigated also. Based on the experimental data, the proposed mathematical model could describe the mass transfer rate of paracetamol. The weight ratio of carrageenan-PVA greatly affected the amount of paracetamol absorbed in the hydrogel film and the mass transfer rate of paracetamol.Keywords: Carrageenan-PVA, crosslinking, hydrogel, glutaraldehyde, paracetamol, mass transfer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11053348 A Modified Genetic Based Technique for Solving the Power System State Estimation Problem
Authors: A. A. Hossam-Eldin, E. N. Abdallah, M. S. El-Nozahy
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Power system state estimation is the process of calculating a reliable estimate of the power system state vector composed of bus voltages' angles and magnitudes from telemetered measurements on the system. This estimate of the state vector provides the description of the system necessary for the operation and security monitoring. Many methods are described in the literature for solving the state estimation problem, the most important of which are the classical weighted least squares method and the nondeterministic genetic based method; however both showed drawbacks. In this paper a modified version of the genetic algorithm power system state estimation is introduced, Sensitivity of the proposed algorithm to genetic operators is discussed, the algorithm is applied to case studies and finally it is compared with the classical weighted least squares method formulation.Keywords: Genetic algorithms, ill-conditioning, state estimation, weighted least squares.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17133347 An Algorithm for Estimating the Stable Operation Conditions of the Synchronous Motor of the Ore Mill Electric Drive
Authors: M. Baghdasaryan, A. Sukiasyan
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An algorithm for estimating the stable operation conditions of the synchronous motor of the ore mill electric drive is proposed. The stable operation conditions of the synchronous motor are revealed, taking into account the estimation of the q angle change and the technological factors. The stability condition obtained allows to ensure the stable operation of the motor in the synchronous mode, taking into account the nonlinear character of the mill loading. The developed algorithm gives an opportunity to present the undesirable phenomena, arising in the electric drive system. The obtained stability condition can be successfully applied for the optimal control of the electromechanical system of the mill.Keywords: Electric drive, synchronous motor, ore mill, stability, technological factors.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8963346 Maximum Power Point Tracking by ANN Controller for a Standalone Photovoltaic System
Authors: K. Ranjani, M. Raja, B. Anitha
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In this paper, ANN controller for maximum power point tracking of photovoltaic (PV) systems is proposed and PV modeling is discussed. Maximum power point tracking (MPPT) methods are used to maximize the PV array output power by tracking continuously the maximum power point. ANN controller with hill-climbing algorithm offers fast and accurate converging to the maximum operating point during steady-state and varying weather conditions compared to conventional hill-climbing. The proposed algorithm gives a good maximum power operation of the PV system. Simulation results obtained are presented and compared with the conventional hill-climbing algorithm. Simulation results show the effectiveness of the proposed technique.
Keywords: Artificial neural network (ANN), hill-climbing, maximum power-point tracking (MPPT), photovoltaic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31553345 A Technique for Improving the Performance of Median Smoothers at the Corners Characterized by Low Order Polynomials
Authors: E. Srinivasan, D. Ebenezer
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Median filters with larger windows offer greater smoothing and are more robust than the median filters of smaller windows. However, the larger median smoothers (the median filters with the larger windows) fail to track low order polynomial trends in the signals. Due to this, constant regions are produced at the signal corners, leading to the loss of fine details. In this paper, an algorithm, which combines the ability of the 3-point median smoother in preserving the low order polynomial trends and the superior noise filtering characteristics of the larger median smoother, is introduced. The proposed algorithm (called the combiner algorithm in this paper) is evaluated for its performance on a test image corrupted with different types of noise and the results obtained are included.
Keywords: Image filtering, detail preservation, median filters, nonlinear filters, order statistics filtering, Rank order filtering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13743344 High Quality Speech Coding using Combined Parametric and Perceptual Modules
Authors: M. Kulesza, G. Szwoch, A. Czyżewski
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A novel approach to speech coding using the hybrid architecture is presented. Advantages of parametric and perceptual coding methods are utilized together in order to create a speech coding algorithm assuring better signal quality than in traditional CELP parametric codec. Two approaches are discussed. One is based on selection of voiced signal components that are encoded using parametric algorithm, unvoiced components that are encoded perceptually and transients that remain unencoded. The second approach uses perceptual encoding of the residual signal in CELP codec. The algorithm applied for precise transient selection is described. Signal quality achieved using the proposed hybrid codec is compared to quality of some standard speech codecs.
Keywords: CELP residual coding, hybrid codec architecture, perceptual speech coding, speech codecs comparison.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15303343 Mathematical Modeling of Gas Turbine Blade Cooling
Authors: А. Pashayev, C. Ardil, D. Askerov, R. Sadiqov, A. Samedov
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In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.Keywords: Mathematical Modeling, Gas Turbine Blade Cooling, Neural Networks, BIEM and FDM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20923342 Improved Multi–Objective Firefly Algorithms to Find Optimal Golomb Ruler Sequences for Optimal Golomb Ruler Channel Allocation
Authors: Shonak Bansal, Prince Jain, Arun Kumar Singh, Neena Gupta
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Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength division multiplexing (WDM) systems in order to minimize the adverse four–wave mixing (FWM) crosstalk effect. The simulation results conclude that the proposed optimization algorithm has superior performance compared to the existing conventional computing and nature–inspired optimization algorithms to find OGRs in terms of ruler length, total optical channel bandwidth and computation time.Keywords: Channel allocation, conventional computing, four–wave mixing, nature–inspired algorithm, optimal Golomb ruler, Lévy flight distribution, optimization, improved multi–objective Firefly algorithms, Pareto optimal.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11583341 A Hybrid Approach for Selection of Relevant Features for Microarray Datasets
Authors: R. K. Agrawal, Rajni Bala
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Developing an accurate classifier for high dimensional microarray datasets is a challenging task due to availability of small sample size. Therefore, it is important to determine a set of relevant genes that classify the data well. Traditionally, gene selection method often selects the top ranked genes according to their discriminatory power. Often these genes are correlated with each other resulting in redundancy. In this paper, we have proposed a hybrid method using feature ranking and wrapper method (Genetic Algorithm with multiclass SVM) to identify a set of relevant genes that classify the data more accurately. A new fitness function for genetic algorithm is defined that focuses on selecting the smallest set of genes that provides maximum accuracy. Experiments have been carried on four well-known datasets1. The proposed method provides better results in comparison to the results found in the literature in terms of both classification accuracy and number of genes selected.
Keywords: Gene selection, genetic algorithm, microarray datasets, multi-class SVM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20583340 Seismic Response Reduction of Structures using Smart Base Isolation System
Authors: H.S. Kim
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In this study, control performance of a smart base isolation system consisting of a friction pendulum system (FPS) and a magnetorheological (MR) damper has been investigated. A fuzzy logic controller (FLC) is used to modulate the MR damper so as to minimize structural acceleration while maintaining acceptable base displacement levels. To this end, a multi-objective optimization scheme is used to optimize parameters of membership functions and find appropriate fuzzy rules. To demonstrate effectiveness of the proposed multi-objective genetic algorithm for FLC, a numerical study of a smart base isolation system is conducted using several historical earthquakes. It is shown that the proposed method can find optimal fuzzy rules and that the optimized FLC outperforms not only a passive control strategy but also a human-designed FLC and a conventional semi-active control algorithm.Keywords: Fuzzy logic controller, genetic algorithm, MR damper, smart base isolation system
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22003339 Model-Based Software Regression Test Suite Reduction
Authors: Shiwei Deng, Yang Bao
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In this paper, we present a model-based regression test suite reducing approach that uses EFSM model dependence analysis and probability-driven greedy algorithm to reduce software regression test suites. The approach automatically identifies the difference between the original model and the modified model as a set of elementary model modifications. The EFSM dependence analysis is performed for each elementary modification to reduce the regression test suite, and then the probability-driven greedy algorithm is adopted to select the minimum set of test cases from the reduced regression test suite that cover all interaction patterns. Our initial experience shows that the approach may significantly reduce the size of regression test suites.Keywords: Dependence analysis, EFSM model, greedy algorithm, regression test.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19213338 Computing a Time Based Effective Radius-of-Curvature for Roadways
Authors: Gary D. Cantrell, E. Alex Baylot
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The radius-of-curvature (ROC) defines the degree of curvature along the centerline of a roadway whereby a travelling vehicle must follow. Roadway designs must encompass ROC in mitigating the cost of earthwork associated with construction while also allowing vehicles to travel at maximum allowable design speeds. Thus, a road will tend to follow natural topography where possible, but curvature must also be optimized to permit fast, but safe vehicle speeds. The more severe the curvature of the road, the slower the permissible vehicle speed. For route planning, whether for urban settings, emergency operations, or even parcel delivery, ROC is a necessary attribute of road arcs for computing travel time. It is extremely rare for a geo-spatial database to contain ROC. This paper will present a procedure and mathematical algorithm to calculate and assign ROC to a segment pair and/or polyline.Keywords: linear features, radius-of-curvature, roads, routing, traffic, turning
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15943337 Optimal Control of Viscoelastic Melt Spinning Processes
Authors: Shyam S.N. Perera
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The optimal control problem for the viscoelastic melt spinning process has not been reported yet in the literature. In this study, an optimal control problem for a mathematical model of a viscoelastic melt spinning process is considered. Maxwell-Oldroyd model is used to describe the rheology of the polymeric material, the fiber is made of. The extrusion velocity of the polymer at the spinneret as well as the velocity and the temperature of the quench air and the fiber length serve as control variables. A constrained optimization problem is derived and the first–order optimality system is set up to obtain the adjoint equations. Numerical solutions are carried out using a steepest descent algorithm. A computer program in MATLAB is developed for simulations.Keywords: Fiber spinning, Maxwell-Oldroyd, Optimal control, First-order optimality system, Adjoint system
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1888