Search results for: Function Approximation Technique (FAT)
4812 The Automated Selective Acquisition System
Authors: Atisthan Wuttimanop, Suchada Rianmora
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To support design process for launching the product on time, reverse engineering (RE) process has been introduced for quickly generating 3D CAD model from its physical object. The accuracy of the 3D CAD model depends upon the data acquisition technique selected, contact or non-contact methods. In order to reduce times used for acquiring surface and eliminating noises, the automated selective acquisition system has been developed and presented in this research as the alternative channel for non-contact acquisition technique where the data is selectively and locally scanned contour by contour without performing data reduction process. The results present as the organized contour points which are directly used to generate 3D virtual model. The comparison between the proposed technique and another non-contact scanning technique has been presented and discussed.
Keywords: Automated selective acquisition system, Non-contact acquisition, Reverse engineering, 3D scanners.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16094811 Transmission Loss Allocation via Loss Function Decomposition and Current Projection Concept
Authors: M.R. Ebrahimi, Z. Ghofrani, M. Ehsan
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One of the major problems in liberalized power markets is loss allocation. In this paper, a different method for allocating transmission losses to pool market participants is proposed. The proposed method is fundamentally based on decomposition of loss function and current projection concept. The method has been implemented and tested on several networks and one sample summarized in the paper. The results show that the method is comprehensive and fair to allocating the energy losses of a power market to its participants.Keywords: Transmission loss, loss allocation, current projectionconcept, loss function decomposition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17454810 An Improved Quality Adaptive Rate Filtering Technique Based on the Level Crossing Sampling
Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin
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Mostly the systems are dealing with time varying signals. The Power efficiency can be achieved by adapting the system activity according to the input signal variations. In this context an adaptive rate filtering technique, based on the level crossing sampling is devised. It adapts the sampling frequency and the filter order by following the input signal local variations. Thus, it correlates the processing activity with the signal variations. Interpolation is required in the proposed technique. A drastic reduction in the interpolation error is achieved by employing the symmetry during the interpolation process. Processing error of the proposed technique is calculated. The computational complexity of the proposed filtering technique is deduced and compared to the classical one. Results promise a significant gain of the computational efficiency and hence of the power consumption.Keywords: Level Crossing Sampling, Activity Selection, Rate Filtering, Computational Complexity, Interpolation Error.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15584809 Application of Hybrid Genetic Algorithm Based on Simulated Annealing in Function Optimization
Authors: Panpan Xu, Shulin Sui, Zongjie Du
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Genetic algorithm is widely used in optimization problems for its excellent global search capabilities and highly parallel processing capabilities; but, it converges prematurely and has a poor local optimization capability in actual operation. Simulated annealing algorithm can avoid the search process falling into local optimum. A hybrid genetic algorithm based on simulated annealing is designed by combining the advantages of genetic algorithm and simulated annealing algorithm. The numerical experiment represents the hybrid genetic algorithm can be applied to solve the function optimization problems efficiently.Keywords: Genetic algorithm, Simulated annealing, Hybrid genetic algorithm, Function optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25504808 All-Optical Function Based on Self-Similar Spectral Broadening for 2R Regeneration in High-Bit-Rate Optical Transmission Systems
Authors: Leila Graini
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In this paper, we demonstrate basic all-optical functions for 2R regeneration (Re-amplification and Re-shaping) based on self-similar spectral broadening in low normal dispersion and highly nonlinear fiber (ND-HNLF) to regenerate the signal through optical filtering including the transfer function characteristics, and output extinction ratio. Our approach of all-optical 2R regeneration is based on those of Mamyshev. The numerical study reveals the self-similar spectral broadening very effective for 2R all-optical regeneration; the proposed design presents high stability compared to a conventional regenerator using SPM broadening with reduction of the intensity fluctuations and improvement of the extinction ratio.
Keywords: All-optical function, 2R optical regeneration, self-similar broadening, Mamyshev regenerator.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8194807 Design of a DCT-based Image Compression with Efficient Enhancement Filter
Authors: Yen-Yu Chen, Pao-Ching Chu, Ya-Ling Tsai
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The algorithm represents the DCT coefficients to concentrate signal energy and proposes combination and dictator to eliminate the correlation in the same level subband for encoding the DCT-based images. This work adopts DCT and modifies the SPIHT algorithm to encode DCT coefficients. The proposed algorithm also provides the enhancement function in low bit rate in order to improve the perceptual quality. Experimental results indicate that the proposed technique improves the quality of the reconstructed image in terms of both PSNR and the perceptual results close to JPEG2000 at the same bit rate.
Keywords: JPEG 2000, enhancement filter
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16934806 Speech Coding and Recognition
Authors: M. Satya Sai Ram, P. Siddaiah, M. Madhavi Latha
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This paper investigates the performance of a speech recognizer in an interactive voice response system for various coded speech signals, coded by using a vector quantization technique namely Multi Switched Split Vector Quantization Technique. The process of recognizing the coded output can be used in Voice banking application. The recognition technique used for the recognition of the coded speech signals is the Hidden Markov Model technique. The spectral distortion performance, computational complexity, and memory requirements of Multi Switched Split Vector Quantization Technique and the performance of the speech recognizer at various bit rates have been computed. From results it is found that the speech recognizer is showing better performance at 24 bits/frame and it is found that the percentage of recognition is being varied from 100% to 93.33% for various bit rates.Keywords: Linear predictive coding, Speech Recognition, Voice banking, Multi Switched Split Vector Quantization, Hidden Markov Model, Linear Predictive Coefficients.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18464805 Buzan Mind Mapping: An Efficient Technique for Note-Taking
Authors: T. K. Tee, M. N. A. Azman, S. Mohamed, Muhammad, M., M. M. Mohamad, J. Md Yunos, M. H. Yee, W. Othman
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Buzan mind mapping is an efficient system of note-taking that makes revision a fun thing to do for students. Tony Buzan has been teaching children all over the world for the past thirty years and has proved that mind maps are the magic formula in the classroom for everyone. The purpose of this paper is to discuss the importance of Buzan mind mapping as a note-taking technique for the secondary school students. This paper also examines the mind mapping technique, advantages and disadvantages of hand-drawn mind maps. Samples of students’ mind maps were presented and discussed.
Keywords: Buzan Mind Mapping, note-taking technique, hand-drawn mind maps.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 93894804 Cantor Interpolating Spline to Design Electronic Mail Boxes
Authors: Adil Al-Rammahi
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Electronic mail is very important in present time. Many researchers work for designing, improving, securing, fasting, goodness and others fields in electronic mail. This paper introduced new algorithm to use Cantor sets and cubic spline interpolating function in the electronic mail design. Cantor sets used as the area (or domain) of the mail, while spline function used for designing formula. The roots of spline function versus Cantor sets used as the controller admin. The roots calculated by the numerical Newton – Raphson's method. The result of this algorithm was promised.
Keywords: Cantor sets, spline, electronic mail design, Newton – Raphson's method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15974803 Frequency-Variation Based Method for Parameter Estimation of Transistor Amplifier
Authors: Akash Rathee, Harish Parthasarathy
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In this paper, a frequency-variation based method has been proposed for transistor parameter estimation in a commonemitter transistor amplifier circuit. We design an algorithm to estimate the transistor parameters, based on noisy measurements of the output voltage when the input voltage is a sine wave of variable frequency and constant amplitude. The common emitter amplifier circuit has been modelled using the transistor Ebers-Moll equations and the perturbation technique has been used for separating the linear and nonlinear parts of the Ebers-Moll equations. This model of the amplifier has been used to determine the amplitude of the output sinusoid as a function of the frequency and the parameter vector. Then, applying the proposed method to the frequency components, the transistor parameters have been estimated. As compared to the conventional time-domain least squares method, the proposed method requires much less data storage and it results in more accurate parameter estimation, as it exploits the information in the time and frequency domain, simultaneously. The proposed method can be utilized for parameter estimation of an analog device in its operating range of frequencies, as it uses data collected from different frequencies output signals for parameter estimation.Keywords: Perturbation Technique, Parameter estimation, frequency-variation based method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17554802 Exact Solutions of Steady Plane Flows of an Incompressible Fluid of Variable Viscosity Using (ξ, ψ)- Or (η, ψ)- Coordinates
Authors: Rana Khalid Naeem, Asif Mansoor, Waseem Ahmed Khan, Aurangzaib
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The exact solutions of the equations describing the steady plane motion of an incompressible fluid of variable viscosity for an arbitrary state equation are determined in the (ξ,ψ) − or (η,ψ )- coordinates where ψ(x,y) is the stream function, ξ and η are the parts of the analytic function, ϖ =ξ( x,y )+iη( x,y ). Most of the solutions involve arbitrary function/ functions indicating that the flow equations possess an infinite set of solutions.
Keywords: Exact solutions, Fluid of variable viscosity, Navier-Stokes equations, Steady plane flows
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34484801 Estimation of Attenuation and Phase Delay in Driving Voltage Waveform of a Digital-Noiseless, Ultra-High-Speed Image Sensor
Authors: V. T. S. Dao, T. G. Etoh, C. Vo Le, H. D. Nguyen, K. Takehara, T. Akino, K. Nishi
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Since 2004, we have been developing an in-situ storage image sensor (ISIS) that captures more than 100 consecutive images at a frame rate of 10 Mfps with ultra-high sensitivity as well as the video camera for use with this ISIS. Currently, basic research is continuing in an attempt to increase the frame rate up to 100 Mfps and above. In order to suppress electro-magnetic noise at such high frequency, a digital-noiseless imaging transfer scheme has been developed utilizing solely sinusoidal driving voltages. This paper presents highly efficient-yet-accurate expressions to estimate attenuation as well as phase delay of driving voltages through RC networks of an ultra-high-speed image sensor. Elmore metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE data, we found a simple expression that significantly improves the accuracy of the approximation. Similarly, another simple closed-form model to estimate phase delay through fundamental RC networks is also obtained. Estimation error of both expressions is much less than previous works, only less 2% for most of the cases . The framework of this analysis can be extended to address similar issues of other VLSI structures.
Keywords: Dimensional Analysis, ISIS, Digital-noiseless, RC network, Attenuation, Phase Delay, Elmore model
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14544800 Fast Approximate Bayesian Contextual Cold Start Learning (FAB-COST)
Authors: Jack R. McKenzie, Peter A. Appleby, Thomas House, Neil Walton
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Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To address this challenge, a contextual bandit algorithm – the Fast Approximate Bayesian Contextual Cold Start Learning algorithm (FAB-COST) – is proposed, which is designed to provide improved accuracy compared to the traditionally used Laplace approximation in the logistic contextual bandit, while controlling both algorithmic complexity and computational cost. To this end, FAB-COST uses a combination of two moment projection variational methods: Expectation Propagation (EP), which performs well at the cold start, but becomes slow as the amount of data increases; and Assumed Density Filtering (ADF), which has slower growth of computational cost with data size but requires more data to obtain an acceptable level of accuracy. By switching from EP to ADF when the dataset becomes large, it is able to exploit their complementary strengths. The empirical justification for FAB-COST is presented, and systematically compared to other approaches on simulated data. In a benchmark against the Laplace approximation on real data consisting of over 670, 000 impressions from autotrader.co.uk, FAB-COST demonstrates at one point increase of over 16% in user clicks. On the basis of these results, it is argued that FAB-COST is likely to be an attractive approach to cold-start recommendation systems in a variety of contexts.Keywords: Cold-start, expectation propagation, multi-armed bandits, Thompson sampling, variational inference.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5524799 A Review: Comparative Analysis of Different Categorical Data Clustering Ensemble Methods
Authors: S. Sarumathi, N. Shanthi, M. Sharmila
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Over the past epoch a rampant amount of work has been done in the data clustering research under the unsupervised learning technique in Data mining. Furthermore several algorithms and methods have been proposed focusing on clustering different data types, representation of cluster models, and accuracy rates of the clusters. However no single clustering algorithm proves to be the most efficient in providing best results. Accordingly in order to find the solution to this issue a new technique, called Cluster ensemble method was bloomed. This cluster ensemble is a good alternative approach for facing the cluster analysis problem. The main hope of the cluster ensemble is to merge different clustering solutions in such a way to achieve accuracy and to improve the quality of individual data clustering. Due to the substantial and unremitting development of new methods in the sphere of data mining and also the incessant interest in inventing new algorithms, makes obligatory to scrutinize a critical analysis of the existing techniques and the future novelty. This paper exposes the comparative study of different cluster ensemble methods along with their features, systematic working process and the average accuracy and error rates of each ensemble methods. Consequently this speculative and comprehensive analysis will be very useful for the community of clustering practitioners and also helps in deciding the most suitable one to rectify the problem in hand.
Keywords: Clustering, Cluster Ensemble methods, Co-association matrix, Consensus function, Median partition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26034798 Unmanned Aerial Vehicle Landing Based on Ultra-Wideband Localization System and Optimal Strategy for Searching Optimal Landing Point
Authors: Meng Wu
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Unmanned aerial vehicle (UAV) landing technology is a common task that is required to be fulfilled by fly robots. In this paper, the Crazyflie 2.0 is located by ultra-wideband (UWB) localization system that contains four UWB anchors. Another UWB anchor is introduced and installed on a stationary platform. One cost function is designed to find the minimum distance between Crazyflie 2.0 and the anchor installed on the stationary platform. The coordinates of the anchor are unknown in advance, and the goal of the cost function is to define the location of the anchor, which can be considered as an optimal landing point. When the cost function reaches the minimum value, the corresponding coordinates of the UWB anchor fixed on the stationary platform can be calculated and defined as the landing point. The simulation shows the effectiveness of the method in this paper.
Keywords: Unmanned aerial vehicle landing, ultra-wideband localization system, ultra-wideband anchor, cost function, stationary platform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 174797 Effects of Various Wavelet Transforms in Dynamic Analysis of Structures
Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar
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Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.
Keywords: Wavelet transform, computational error, computational duration, strong ground motion data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13734796 A Distance Function for Data with Missing Values and Its Application
Authors: Loai AbdAllah, Ilan Shimshoni
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Missing values in data are common in real world applications. Since the performance of many data mining algorithms depend critically on it being given a good metric over the input space, we decided in this paper to define a distance function for unlabeled datasets with missing values. We use the Bhattacharyya distance, which measures the similarity of two probability distributions, to define our new distance function. According to this distance, the distance between two points without missing attributes values is simply the Mahalanobis distance. When on the other hand there is a missing value of one of the coordinates, the distance is computed according to the distribution of the missing coordinate. Our distance is general and can be used as part of any algorithm that computes the distance between data points. Because its performance depends strongly on the chosen distance measure, we opted for the k nearest neighbor classifier to evaluate its ability to accurately reflect object similarity. We experimented on standard numerical datasets from the UCI repository from different fields. On these datasets we simulated missing values and compared the performance of the kNN classifier using our distance to other three basic methods. Our experiments show that kNN using our distance function outperforms the kNN using other methods. Moreover, the runtime performance of our method is only slightly higher than the other methods.
Keywords: Missing values, Distance metric, Bhattacharyya distance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27514795 PSO Based Weight Selection and Fixed Structure Robust Loop Shaping Control for Pneumatic Servo System with 2DOF Controller
Authors: Randeep Kaur, Jyoti Ohri
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This paper proposes a new technique to design a fixed-structure robust loop shaping controller for the pneumatic servosystem. In this paper, a new method based on a particle swarm optimization (PSO) algorithm for tuning the weighting function parameters to design an H∞ controller is presented. The PSO algorithm is used to minimize the infinity norm of the transfer function of the nominal closed loop system to obtain the optimal parameters of the weighting functions. The optimal stability margin is used as an objective in PSO for selecting the optimal weighting parameters; it is shown that the proposed method can simplify the design procedure of H∞ control to obtain optimal robust controller for pneumatic servosystem. In addition, the order of the proposed controller is much lower than that of the conventional robust loop shaping controller, making it easy to implement in practical works. Also two-degree-of-freedom (2DOF) control design procedure is proposed to improve tracking performance in the face of noise and disturbance. Result of simulations demonstrates the advantages of the proposed controller in terms of simple structure and robustness against plant perturbations and disturbances.
Keywords: Robust control, Pneumatic Servosystem, PSO, H∞ control, 2DOF.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24244794 A Multi-objective Fuzzy Optimization Method of Resource Input Based on Genetic Algorithm
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With the increasing complexity of engineering problems, the traditional, single-objective and deterministic optimization method can not meet people-s requirements. A multi-objective fuzzy optimization model of resource input is built for M chlor-alkali chemical eco-industrial park in this paper. First, the model is changed into the form that can be solved by genetic algorithm using fuzzy theory. And then, a fitness function is constructed for genetic algorithm. Finally, a numerical example is presented to show that the method compared with traditional single-objective optimization method is more practical and efficient.Keywords: Fitness function, genetic algorithm, multi-objectivefuzzy optimization, satisfaction degree membership function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13554793 Order Reduction using Modified Pole Clustering and Pade Approximations
Authors: C.B. Vishwakarma
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The authors present a mixed method for reducing the order of the large-scale dynamic systems. In this method, the denominator polynomial of the reduced order model is obtained by using the modified pole clustering technique while the coefficients of the numerator are obtained by Pade approximations. This method is conceptually simple and always generates stable reduced models if the original high-order system is stable. The proposed method is illustrated with the help of the numerical examples taken from the literature.
Keywords: Modified pole clustering, order reduction, padeapproximation, stability, transfer function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29804792 A Cost Function for Joint Blind Equalization and Phase Recovery
Authors: Reza Berangi, Morteza Babaee, Majid Soleimanipour
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In this paper a new cost function for blind equalization is proposed. The proposed cost function, referred to as the modified maximum normalized cumulant criterion (MMNC), is an extension of the previously proposed maximum normalized cumulant criterion (MNC). While the MNC requires a separate phase recovery system after blind equalization, the MMNC performs joint blind equalization and phase recovery. To achieve this, the proposed algorithm maximizes a cost function that considers both amplitude and phase of the equalizer output. The simulation results show that the proposed algorithm has an improved channel equalization effect than the MNC algorithm and simultaneously can correct the phase error that the MNC algorithm is unable to do. The simulation results also show that the MMNC algorithm has lower complexity than the MNC algorithm. Moreover, the MMNC algorithm outperforms the MNC algorithm particularly when the symbols block size is small.Keywords: Blind equalization, maximum normalized cumulant criterion (MNC), intersymbol interference (ISI), modified MNC criterion (MMNC), phase recovery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17644791 Application of Load Transfer Technique for Distribution Power Flow Analysis
Authors: Udomsak Thongkrajay, Padej Pao-La-Or, Thanatchai Kulworawanichpong
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Installation of power compensation equipment in some cases places additional buses into the system. Therefore, a total number of power flow equations and voltage unknowns increase due to additional locations of installed devices. In this circumstance, power flow calculation is more complicated. It may result in a computational convergence problem. This paper presents a power flow calculation by using Newton-Raphson iterative method together with the proposed load transfer technique. This concept is to eliminate additional buses by transferring installed loads at the new buses to existing two adjacent buses. Thus, the total number of power flow equations is not changed. The overall computational speed is expectedly shorter than that of solving the problem without applying the load transfer technique. A 15-bus test system is employed for test to evaluate the effectiveness of the proposed load transfer technique. As a result, the total number of iteration required and execution time is significantly reduced.Keywords: Load transfer technique, Newton-Raphson power flow, ill-condition
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16504790 The Active Imagination Technique for Bruxism Treatment
Authors: Lyra S. R., Zaura-Bremm T., Boleta-Ceranto D. C. F.
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The research purpose was to evaluate the effect of Active Imagination Technique (AIT) for bruxism treatment. This project was approved by the Ethics Committee on Human Research (CAAE: 05619512.9.0000.0109). Twenty-one volunteers using interocclusal splint completed the study. Initially they filled in a questionnaire about their condition, composed of objective questions on signs and symptoms. Following they were underwent asingle session of AIT. After 15 days, the volunteers met again the same initial questionnaire. The results were compared and showed that the vast majority had pain symptoms, difficulty opening the mouth, pain when chewing, reduced, some of the participants abandoned the interocclusal splint during the evaluate period. It is concluded that the technique can be used in bruxism treatment. Results seem to be promising and demonstrates the need of highlighting Active Imagination Technique since it points a possibility of bruxism cure and that is unprecedented.Keywords: Active Imagination, bruxism, orofacial pain, treatment
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21734789 MPSO based Model Order Formulation Technique for SISO Continuous Systems
Authors: S. N. Deepa, G. Sugumaran
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This paper proposes a new version of the Particle Swarm Optimization (PSO) namely, Modified PSO (MPSO) for model order formulation of Single Input Single Output (SISO) linear time invariant continuous systems. In the General PSO, the movement of a particle is governed by three behaviors namely inertia, cognitive and social. The cognitive behavior helps the particle to remember its previous visited best position. In Modified PSO technique split the cognitive behavior into two sections like previous visited best position and also previous visited worst position. This modification helps the particle to search the target very effectively. MPSO approach is proposed to formulate the higher order model. The method based on the minimization of error between the transient responses of original higher order model and the reduced order model pertaining to the unit step input. The results obtained are compared with the earlier techniques utilized, to validate its ease of computation. The proposed method is illustrated through numerical example from literature.Keywords: Continuous System, Model Order Formulation, Modified Particle Swarm Optimization, Single Input Single Output, Transfer Function Approach
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17824788 Determinate Fuzzy Set Ranking Analysis for Combat Aircraft Selection with Multiple Criteria Group Decision Making
Authors: C. Ardil
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Using the aid of Hausdorff distance function and Minkowski distance function, this study proposes a novel method for selecting combat aircraft for Air Force. In order to do this, the proximity measure method was developed with determinate fuzzy degrees based on the relationship between attributes and combat aircraft alternatives. The combat aircraft selection attributes were identified as payloadability, maneuverability, speedability, stealthability, and survivability. Determinate fuzzy data from the combat aircraft attributes was then aggregated using the determinate fuzzy weighted arithmetic average operator. For the selection of combat aircraft, correlation analysis of the ranking order patterns of options was also examined. A numerical example from military aviation is used to demonstrate the applicability and effectiveness of the proposed method.
Keywords: Combat aircraft selection, multiple criteria decision making, fuzzy sets, determinate fuzzy sets, intuitionistic fuzzy sets, proximity measure method, Hausdorff distance function, Minkowski distance function, PMM, MCDM
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3554787 Retaining Structural System Active Vibration Control
Authors: Ming-Hui Lee, Shou-Jen Hsu
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This study presents an active vibration control technique to reduce the earthquake responses of a retained structural system. The proposed technique is a synthesis of the adaptive input estimation method (AIEM) and linear quadratic Gaussian (LQG) controller. The AIEM can estimate an unknown system input online. The LQG controller offers optimal control forces to suppress wall-structural system vibration. The numerical results show robust performance in the active vibration control technique.Keywords: Active vibration control, AIEM, LQG, Optimal control
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18694786 Fast Calculation for Particle Interactions in SPH Simulations: Outlined Sub-domain Technique
Authors: Buntara Sthenly Gan, Naohiro Kawada
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A simple and easy algorithm is presented for a fast calculation of kernel functions which required in fluid simulations using the Smoothed Particle Hydrodynamic (SPH) method. Present proposed algorithm improves the Linked-list algorithm and adopts the Pair-Wise Interaction technique, which are widely used for evaluating kernel functions in fluid simulations using the SPH method. The algorithm is easy to be implemented without any complexities in programming. Some benchmark examples are used to show the simulation time saved by using the proposed algorithm. Parametric studies on the number of divisions for sub-domains, smoothing length and total amount of particles are conducted to show the effectiveness of the present technique. A compact formulation is proposed for practical usage.
Keywords: Technique, fluid simulation, smoothing particle hydrodynamic (SPH), particle interaction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16304785 Understanding Charge Dynamics in Elastomers Adopting Pulsed Electro Acoustic (PEA) Technique
Authors: R. Sarathi, M. G. Danikas, Y. Chen, T. Tanaka
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In the present work, Pulsed Electro Acoustic (PEA) technique was adopted to understand the space charge dynamics in elastomeric material. It is observed that the polarity of the applied DC voltage voltage and its magnitude alters the space charge dynamics in insulation structure. It is also noticed that any addition of compound to the base material/processing technique have characteristic variation in the space charge injection process. It could be concluded based on the present work that the plasticizer could inject heterocharges into the insulation medium. Also it is realized that space charge magnitude is less with the addition of plasticizer. In the PEA studies, it is observed that local electric field in the insulating material can be much more than applied electric field due to space charge formation. One of the important conclusions arrived at based on PEA technique is that one could understand the safe operating electric field of an insulation material and the charge trap sites.Keywords: Pulsed electro acoustic technique, space charge, DCvoltage, elastomers, Electric field, high voltage.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14464784 Diagnosis of the Abdominal Aorta Aneurysm in Magnetic Resonance Imaging Images
Authors: W. Kultangwattana, K. Somkantha, P. Phuangsuwan
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This paper presents a technique for diagnosis of the abdominal aorta aneurysm in magnetic resonance imaging (MRI) images. First, our technique is designed to segment the aorta image in MRI images. This is a required step to determine the volume of aorta image which is the important step for diagnosis of the abdominal aorta aneurysm. Our proposed technique can detect the volume of aorta in MRI images using a new external energy for snakes model. The new external energy for snakes model is calculated from Law-s texture. The new external energy can increase the capture range of snakes model efficiently more than the old external energy of snakes models. Second, our technique is designed to diagnose the abdominal aorta aneurysm by Bayesian classifier which is classification models based on statistical theory. The feature for data classification of abdominal aorta aneurysm was derived from the contour of aorta images which was a result from segmenting of our snakes model, i.e., area, perimeter and compactness. We also compare the proposed technique with the traditional snakes model. In our experiment results, 30 images are trained, 20 images are tested and compared with expert opinion. The experimental results show that our technique is able to provide more accurate results than 95%.
Keywords: Adbominal Aorta Aneurysm, Bayesian Classifier, Snakes Model, Texture Feature.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15924783 Modeling of a UAV Longitudinal Dynamics through System Identification Technique
Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad
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System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc. This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.
Keywords: Black box modeling, fixed wing aircraft, least square error, longitudinal dynamics, system identification.
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