Search results for: Latin Squares
205 Short-Term Electric Load Forecasting Using Multiple Gaussian Process Models
Authors: Tomohiro Hachino, Hitoshi Takata, Seiji Fukushima, Yasutaka Igarashi
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This paper presents a Gaussian process model-based short-term electric load forecasting. The Gaussian process model is a nonparametric model and the output of the model has Gaussian distribution with mean and variance. The multiple Gaussian process models as every hour ahead predictors are used to forecast future electric load demands up to 24 hours ahead in accordance with the direct forecasting approach. The separable least-squares approach that combines the linear least-squares method and genetic algorithm is applied to train these Gaussian process models. Simulation results are shown to demonstrate the effectiveness of the proposed electric load forecasting.
Keywords: Direct method, electric load forecasting, Gaussian process model, genetic algorithm, separable least-squares method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1984204 Calibration Method for an Augmented Reality System
Authors: S. Malek, N. Zenati-Henda, M. Belhocine, S. Benbelkacem
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In geometrical camera calibration, the objective is to determine a set of camera parameters that describe the mapping between 3D references coordinates and 2D image coordinates. In this paper, a technique of calibration and tracking based on both a least squares method is presented and a correlation technique developed as part of an augmented reality system. This approach is fast and it can be used for a real time systemKeywords: Camera calibration, pinhole model, least squares method, augmented reality, strong calibration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2001203 Transformer Top-Oil Temperature Modeling and Simulation
Authors: T. C. B. N. Assunção, J. L. Silvino, P. Resende
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The winding hot-spot temperature is one of the most critical parameters that affect the useful life of the power transformers. The winding hot-spot temperature can be calculated as function of the top-oil temperature that can estimated by using the ambient temperature and transformer loading measured data. This paper proposes the estimation of the top-oil temperature by using a method based on Least Squares Support Vector Machines approach. The estimated top-oil temperature is compared with measured data of a power transformer in operation. The results are also compared with methods based on the IEEE Standard C57.91-1995/2000 and Artificial Neural Networks. It is shown that the Least Squares Support Vector Machines approach presents better performance than the methods based in the IEEE Standard C57.91-1995/2000 and artificial neural networks.Keywords: Artificial Neural Networks, Hot-spot Temperature, Least Squares Support Vector, Top-oil Temperature.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2491202 Dynamic Process Monitoring of an Ammonia Synthesis Fixed-Bed Reactor
Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin
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This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.Keywords: Ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1922201 A Robust LS-SVM Regression
Authors: József Valyon, Gábor Horváth
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In comparison to the original SVM, which involves a quadratic programming task; LS–SVM simplifies the required computation, but unfortunately the sparseness of standard SVM is lost. Another problem is that LS-SVM is only optimal if the training samples are corrupted by Gaussian noise. In Least Squares SVM (LS–SVM), the nonlinear solution is obtained, by first mapping the input vector to a high dimensional kernel space in a nonlinear fashion, where the solution is calculated from a linear equation set. In this paper a geometric view of the kernel space is introduced, which enables us to develop a new formulation to achieve a sparse and robust estimate.Keywords: Support Vector Machines, Least Squares SupportVector Machines, Regression, Sparse approximation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2063200 A Framework for Teaching Distributed Requirements Engineering in Latin American Universities
Authors: G. Sevilla, S. Zapata, F. Giraldo, E. Torres, C. Collazos
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This work describes a framework for teaching of global software engineering (GSE) in university undergraduate programs. This framework proposes a method of teaching that incorporates adequate techniques of software requirements elicitation and validated tools of communication, critical aspects to global software development scenarios. The use of proposed framework allows teachers to simulate small software development companies formed by Latin American students, which build information systems. Students from three Latin American universities played the roles of engineers by applying an iterative development of a requirements specification in a global software project. The proposed framework involves the use of a specific purpose Wiki for asynchronous communication between the participants of the process. It is also a practice to improve the quality of software requirements that are formulated by the students. The additional motivation of students to participate in these practices, in conjunction with peers from other countries, is a significant additional factor that positively contributes to the learning process. The framework promotes skills for communication, negotiation, and other complementary competencies that are useful for working on GSE scenarios.Keywords: Requirements analysis, distributed requirements engineering, practical experiences, collaborative support.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 705199 Application of the Least Squares Method in the Adjustment of Chlorodifluoromethane (HCFC-142b) Regression Models
Authors: L. J. de Bessa Neto, V. S. Filho, J. V. Ferreira Nunes, G. C. Bergamo
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There are many situations in which human activities have significant effects on the environment. Damage to the ozone layer is one of them. The objective of this work is to use the Least Squares Method, considering the linear, exponential, logarithmic, power and polynomial models of the second degree, to analyze through the coefficient of determination (R²), which model best fits the behavior of the chlorodifluoromethane (HCFC-142b) in parts per trillion between 1992 and 2018, as well as estimates of future concentrations between 5 and 10 periods, i.e. the concentration of this pollutant in the years 2023 and 2028 in each of the adjustments. A total of 809 observations of the concentration of HCFC-142b in one of the monitoring stations of gases precursors of the deterioration of the ozone layer during the period of time studied were selected and, using these data, the statistical software Excel was used for make the scatter plots of each of the adjustment models. With the development of the present study, it was observed that the logarithmic fit was the model that best fit the data set, since besides having a significant R² its adjusted curve was compatible with the natural trend curve of the phenomenon.
Keywords: Chlorodifluoromethane (HCFC-142b), ozone (O3), least squares method, regression models.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 827198 Reliability Evaluation of Composite Electric Power System Based On Latin Hypercube Sampling
Authors: R. Ashok Bakkiyaraj, N. Kumarappan
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This paper investigates the suitability of Latin Hypercube sampling (LHS) for composite electric power system reliability analysis. Each sample generated in LHS is mapped into an equivalent system state and used for evaluating the annualized system and load point indices. DC loadflow based state evaluation model is solved for each sampled contingency state. The indices evaluated are loss of load probability, loss of load expectation, expected demand not served and expected energy not supplied. The application of the LHS is illustrated through case studies carried out using RBTS and IEEE-RTS test systems. Results obtained are compared with non-sequential Monte Carlo simulation and state enumeration analytical approaches. An error analysis is also carried out to check the LHS method’s ability to capture the distributions of the reliability indices. It is found that LHS approach estimates indices nearer to actual value and gives tighter bounds of indices than non-sequential Monte Carlo simulation.
Keywords: Composite power system, Latin Hypercube sampling, Monte Carlo simulation, Reliability evaluation, Variance analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3109197 Influence of Probiotics on Dairy Cows Diet
Authors: V. A. Vieira, M. P. Sforcini, V. Endo, G. C. Magioni, M. D. S. Oliveira
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The main goal of this paper was evaluate the effect of diets containing different levels of probiotic on performance and milk composition of lactating cows. Eight Holstein cows were distributed in two 4x4 Latin square. The diets were based on corn silage, concentrate and the treatment (0, 3, 6 or 9 grams of probiotic/animal/day). It was evaluated the dry matter intake of nutrients, milk yield and composition. The use of probiotics did not affect the nutrient intake (p>0.05) neither the daily milk production or corrected to 4% fat (p>0.05). However, it was observed that there was a significant fall in milk composition with higher levels of probiotics supplementation. These results emphasize the need of further studies with different experimental designs or improve the number of Latin square with longer periods of adaptation.
Keywords: Dairy cow, milk composition, probiotics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3627196 Voltage Problem Location Classification Using Performance of Least Squares Support Vector Machine LS-SVM and Learning Vector Quantization LVQ
Authors: Khaled Abduesslam. M, Mohammed Ali, Basher H Alsdai, Muhammad Nizam, Inayati
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This paper presents the voltage problem location classification using performance of Least Squares Support Vector Machine (LS-SVM) and Learning Vector Quantization (LVQ) in electrical power system for proper voltage problem location implemented by IEEE 39 bus New- England. The data was collected from the time domain simulation by using Power System Analysis Toolbox (PSAT). Outputs from simulation data such as voltage, phase angle, real power and reactive power were taken as input to estimate voltage stability at particular buses based on Power Transfer Stability Index (PTSI).The simulation data was carried out on the IEEE 39 bus test system by considering load bus increased on the system. To verify of the proposed LS-SVM its performance was compared to Learning Vector Quantization (LVQ). The results showed that LS-SVM is faster and better as compared to LVQ. The results also demonstrated that the LS-SVM was estimated by 0% misclassification whereas LVQ had 7.69% misclassification.
Keywords: IEEE 39 bus, Least Squares Support Vector Machine, Learning Vector Quantization, Voltage Collapse.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2405195 Near-Infrared Hyperspectral Imaging Spectroscopy to Detect Microplastics and Pieces of Plastic in Almond Flour
Authors: H. Apaza, L. Chévez, H. Loro
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Plastic and microplastic pollution in human food chain is a big problem for human health that requires more elaborated techniques that can identify their presences in different kinds of food. Hyperspectral imaging technique is an optical technique than can detect the presence of different elements in an image and can be used to detect plastics and microplastics in a scene. To do this statistical techniques are required that need to be evaluated and compared in order to find the more efficient ones. In this work, two problems related to the presence of plastics are addressed, the first is to detect and identify pieces of plastic immersed in almond seeds, and the second problem is to detect and quantify microplastic in almond flour. To do this we make use of the analysis hyperspectral images taken in the range of 900 to 1700 nm using 4 unmixing techniques of hyperspectral imaging which are: least squares unmixing (LSU), non-negatively constrained least squares unmixing (NCLSU), fully constrained least squares unmixing (FCLSU), and scaled constrained least squares unmixing (SCLSU). NCLSU, FCLSU, SCLSU techniques manage to find the region where the plastic is found and also manage to quantify the amount of microplastic contained in the almond flour. The SCLSU technique estimated a 13.03% abundance of microplastics and 86.97% of almond flour compared to 16.66% of microplastics and 83.33% abundance of almond flour prepared for the experiment. Results show the feasibility of applying near-infrared hyperspectral image analysis for the detection of plastic contaminants in food.
Keywords: Food, plastic, microplastic, NIR hyperspectral imaging, unmixing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1188194 An Accurate Method for Phylogeny Tree Reconstruction Based on a Modified Wild Dog Algorithm
Authors: Essam Al Daoud
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This study solves a phylogeny problem by using modified wild dog pack optimization. The least squares error is considered as a cost function that needs to be minimized. Therefore, in each iteration, new distance matrices based on the constructed trees are calculated and used to select the alpha dog. To test the suggested algorithm, ten homologous genes are selected and collected from National Center for Biotechnology Information (NCBI) databanks (i.e., 16S, 18S, 28S, Cox 1, ITS1, ITS2, ETS, ATPB, Hsp90, and STN). The data are divided into three categories: 50 taxa, 100 taxa and 500 taxa. The empirical results show that the proposed algorithm is more reliable and accurate than other implemented methods.Keywords: Least squares, neighbor joining, phylogenetic tree, wild dogpack.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1392193 An Iterative Method for the Symmetric Arrowhead Solution of Matrix Equation
Authors: Minghui Wang, Luping Xu, Juntao Zhang
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In this paper, according to the classical algorithm LSQR for solving the least-squares problem, an iterative method is proposed for least-squares solution of constrained matrix equation. By using the Kronecker product, the matrix-form LSQR is presented to obtain the like-minimum norm and minimum norm solutions in a constrained matrix set for the symmetric arrowhead matrices. Finally, numerical examples are also given to investigate the performance.Keywords: Symmetric arrowhead matrix, iterative method, like-minimum norm, minimum norm, Algorithm LSQR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1409192 Solving SPDEs by a Least Squares Method
Authors: Hassan Manouzi
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We present in this paper a useful strategy to solve stochastic partial differential equations (SPDEs) involving stochastic coefficients. Using the Wick-product of higher order and the Wiener-Itˆo chaos expansion, the SPDEs is reformulated as a large system of deterministic partial differential equations. To reduce the computational complexity of this system, we shall use a decomposition-coordination method. To obtain the chaos coefficients in the corresponding deterministic equations, we use a least square formulation. Once this approximation is performed, the statistics of the numerical solution can be easily evaluated.
Keywords: Least squares, Wick product, SPDEs, finite element, Wiener chaos expansion, gradient method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1801191 Design of Variable Fractional-Delay FIR Differentiators
Authors: Jong-Jy Shyu, Soo-Chang Pei, Min-Han Chang
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In this paper, the least-squares design of variable fractional-delay (VFD) finite impulse response (FIR) digital differentiators is proposed. The used transfer function is formulated so that Farrow structure can be applied to realize the designed system. Also, the symmetric characteristics of filter coefficients are derived, which leads to the complexity reduction by saving almost a half of the number of coefficients. Moreover, all the elements of related vectors or matrices for the optimal process can be represented in closed forms, which make the design easier. Design example is also presented to illustrate the effectiveness of the proposed method.
Keywords: Differentiator, variable fractional-delay filter, FIR filter, least-squares method, Farrow structure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1415190 Assessment Tool for Social Responsibility Performance According to the ISO 26000
Authors: W. Fethallah, L. Chraibi, N. Sefiani
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The present paper is concerned with a statistical approach involving latent and manifest variables applied in order to assess the organization's social responsibility performance. The main idea is to develop an assessment tool and a measurement of the Social Responsibility Performance, enabling the company to characterize her performance regarding to the ISO 26000 standard's seven core subjects. For this, we conceptualize a structural equation modeling (SEM) which describes various causal connections between the Social Responsibility’s components. The SEM’s resolution is based on the Partial Least squares (PLS) method and the implementation is running in the XLSTAT software.Keywords: Corporate social responsibility, latent and manifest variable, partial least squares, structural equation model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1224189 From Mother Tongue Education to Multilingual Higher Education
Authors: Mario R. Acevedo Amaya, Fernanda M. Martinez Reyes
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Through the time, the higher education has changed the learning system since mother tongue to bilingual, and in this new century has been coming develop a multilingual education. All as part of globalization process of the countries and the education. Nevertheless, this change only has been effectively in countries of the first world, the rest have been lagging. Therefore, these countries require strengthen their higher education systems through models that give way to multilingual and bilingual education. In this way, shows a new model adapted from a systemic form to allow a higher bilingual and multilingual education in Latin America. This systematization aims to increase the skills and competencies student’s, decrease the time learning of a second tongue, add to multilingualism in the American Latin Universities, also, contribute to position the region´s countries in a better global status, and stimulate the development of new research in this area.Keywords: Bilingual Education, Higher Education, Multilingual Education, Multilingual Education Model
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1932188 Application of the Total Least Squares Estimation Method for an Aircraft Aerodynamic Model Identification
Authors: Zaouche Mohamed, Amini Mohamed, Foughali Khaled, Aitkaid Souhila, Bouchiha Nihad Sarah
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The aerodynamic coefficients are important in the evaluation of an aircraft performance and stability-control characteristics. These coefficients also can be used in the automatic flight control systems and mathematical model of flight simulator. The study of the aerodynamic aspect of flying systems is a reserved domain and inaccessible for the developers. Doing tests in a wind tunnel to extract aerodynamic forces and moments requires a specific and expensive means. Besides, the glaring lack of published documentation in this field of study makes the aerodynamic coefficients determination complicated. This work is devoted to the identification of an aerodynamic model, by using an aircraft in virtual simulated environment. We deal with the identification of the system, we present an environment framework based on Software In the Loop (SIL) methodology and we use MicrosoftTM Flight Simulator (FS-2004) as the environment for plane simulation. We propose The Total Least Squares Estimation technique (TLSE) to identify the aerodynamic parameters, which are unknown, variable, classified and used in the expression of the piloting law. In this paper, we define each aerodynamic coefficient as the mean of its numerical values. All other variations are considered as modeling uncertainties that will be compensated by the robustness of the piloting control.
Keywords: Aircraft aerodynamic model, Microsoft flight simulator, MQ-1 Predator, total least squares estimation, piloting the aircraft.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1667187 The Inverse Problem of Nonsymmetric Matrices with a Submatrix Constraint and its Approximation
Authors: Yongxin Yuan, Hao Liu
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In this paper, we first give the representation of the general solution of the following least-squares problem (LSP): Given matrices X ∈ Rn×p, B ∈ Rp×p and A0 ∈ Rr×r, find a matrix A ∈ Rn×n such that XT AX − B = min, s. t. A([1, r]) = A0, where A([1, r]) is the r×r leading principal submatrix of the matrix A. We then consider a best approximation problem: given an n × n matrix A˜ with A˜([1, r]) = A0, find Aˆ ∈ SE such that A˜ − Aˆ = minA∈SE A˜ − A, where SE is the solution set of LSP. We show that the best approximation solution Aˆ is unique and derive an explicit formula for it. Keyw
Keywords: Inverse problem, Least-squares solution, model updating, Singular value decomposition (SVD), Optimal approximation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1647186 Optimization of Parametric Studies Using Strategies of Sampling Techniques
Authors: Lenka Ševelová, Aleš Florian
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To improve the efficiency of parametric studies or tests planning the method is proposed, that takes into account all input parameters, but only a few simulation runs are performed to assess the relative importance of each input parameter. For K input parameters with N input values the total number of possible combinations of input values equals NK. To limit the number of runs, only some (totally N) of possible combinations are taken into account. The sampling procedure Updated Latin Hypercube Sampling is used to choose the optimal combinations. To measure the relative importance of each input parameter, the Spearman rank correlation coefficient is proposed. The sensitivity and the influence of all parameters are analyzed within one procedure and the key parameters with the largest influence are immediately identified.Keywords: Concrete, pavement, simulation, reliability, Latin Hypercube Sampling, parametric studies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1332185 Alternative Robust Estimators for the Shape Parameters of the Burr XII Distribution
Authors: F. Z. Doğru, O. Arslan
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In general, classical methods such as maximum likelihood (ML) and least squares (LS) estimation methods are used to estimate the shape parameters of the Burr XII distribution. However, these estimators are very sensitive to the outliers. To overcome this problem we propose alternative robust estimators based on the M-estimation method for the shape parameters of the Burr XII distribution. We provide a small simulation study and a real data example to illustrate the performance of the proposed estimators over the ML and the LS estimators. The simulation results show that the proposed robust estimators generally outperform the classical estimators in terms of bias and root mean square errors when there are outliers in data.
Keywords: Burr XII distribution, robust estimator, M-estimator, maximum likelihood, least squares.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2658184 Performance Analysis of Adaptive OFDM Pre and Post-FTT Beamforming System
Authors: S. Elnobi, Iman El-Zahaby, Amr M. Mahros
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In mobile communication systems, performance and capacity are affected by multi-path fading, delay spread and Co-Channel Interference (CCI). For this reason Orthogonal Frequency Division Multiplexing (OFDM) and adaptive antenna array are used is required. The goal of the OFDM is to improve the system performance against Inter-Symbol Interference (ISI). An array of adaptive antennas has been employed to suppress CCI by spatial technique. To suppress CCI in OFDM systems two main schemes the pre-FFT and the post-FFT have been proposed. In this paper, through a system level simulation, the behavior of the pre-FFT and post-FFT beamformers for OFDM system has been investigated based on two algorithms namely, Least Mean Squares (LMS) and Recursive Least Squares (RLS). The performance of the system is also discussed in multipath fading channel system specified by 3GPP Long Term Evolution (LTE).
Keywords: OFDM, Beamforming, Adaptive Antennas Array.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2440183 Accurate Dimensional Measurement of 3D Round Holes Based on Stereo Vision
Authors: Zhiguo Ren, Lilong Cai
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This paper present an effective method to accurately reconstruct and measure the 3D curve edges of small industrial parts based on stereo vision. To effectively fit the curve of the measured parts using a series of line segments in the images, a strategy from coarse to fine is employed based on multi-scale curve fitting. After reconstructing the 3D curve of a hole through a curved surface, its axis is adjusted so that it is parallel to the Z axis with least squares error and the dimensions of the hole can be calculated on the XY plane easily. Experimental results show that the presented method can accurately measure the dimensions of round holes through a curved surface.
Keywords: Stereo Vision, 3D Round Hole Measurement, Curve Fitting, 3D Curve Reconstruction, Least Squares Error.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1627182 Model Predictive Fuzzy Control of Air-ratio for Automotive Engines
Authors: Hang-cheong Wong, Pak-kin Wong, Chi-man Vong, Zhengchao Xie, Shaojia Huang
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Automotive engine air-ratio plays an important role of emissions and fuel consumption reduction while maintains satisfactory engine power among all of the engine control variables. In order to effectively control the air-ratio, this paper presents a model predictive fuzzy control algorithm based on online least-squares support vector machines prediction model and fuzzy logic optimizer. The proposed control algorithm was also implemented on a real car for testing and the results are highly satisfactory. Experimental results show that the proposed control algorithm can regulate the engine air-ratio to the stoichiometric value, 1.0, under external disturbance with less than 5% tolerance.Keywords: Air-ratio, Fuzzy logic, online least-squares support vector machine, model predictive control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1809181 Equity Risk Premiums and Risk Free Rates in Modelling and Prediction of Financial Markets
Authors: Mohammad Ghavami, Reza S. Dilmaghani
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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.Keywords: Prediction of financial markets, Adaptive methods, MSE, LSE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1020180 Unit Root Tests Based On the Robust Estimator
Authors: Wararit Panichkitkosolkul
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The unit root tests based on the robust estimator for the first-order autoregressive process are proposed and compared with the unit root tests based on the ordinary least squares (OLS) estimator. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of Type I error and powers of the unit root tests are estimated via Monte Carlo simulation. Simulation results show that all unit root tests can control the probability of Type I error for all situations. The empirical power of the unit root tests based on the robust estimator are higher than the unit root tests based on the OLS estimator.
Keywords: Autoregressive, Ordinary least squares, Type I error, Power of the test, Monte Carlo simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1788179 Online Prediction of Nonlinear Signal Processing Problems Based Kernel Adaptive Filtering
Authors: Hamza Nejib, Okba Taouali
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This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.Keywords: KLMS, online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1052178 Design of Two-Channel Quadrature Mirror Filter Banks Using Digital All-Pass Filters
Authors: Ju-Hong Lee, Yi-Lin Shieh
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The paper deals with the minimax design of two-channel linear-phase (LP) quadrature mirror filter (QMF) banks using infinite impulse response (IIR) digital all-pass filters (DAFs). Based on the theory of two-channel QMF banks using two IIR DAFs, the design problem is appropriately formulated to result in an appropriate Chebyshev approximation for the desired group delay responses of the IIR DAFs and the magnitude response of the low-pass analysis filter. Through a frequency sampling and iterative approximation method, the design problem can be solved by utilizing a weighted least squares approach. The resulting two-channel QMF banks can possess approximately LP response without magnitude distortion. Simulation results are presented for illustration and comparison.
Keywords: Chebyshev approximation, Digital All-Pass Filter, Quadrature Mirror Filter, Weighted Least Squares.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2741177 Are Economic Crises and Government Changes Related? A Descriptive Statistic Analysis
Authors: Şakir Görmüş, Ali Kabasakal
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The main purpose of this study is to provide a detailed statistical overview of the time and regional distribution, relative timing occurrence of economic crises and government changes in 51 economies over the 1990–2007 periods. At the same time, the predictive power of the economic crises on set government changes will be examined using “signal approach". The result showed that the percentage of government changes is highest in transition economies (86 percent of observations) and lowest in Latin American economies (39 percent of observations). The percentages of government changes are same in both developed and developing countries (43 percent of observations). However, average crises per year (frequency of crises) are higher (lower) in developing (developed) countries than developed (developing) countries. Also, the predictive power of economic crises about the onset of a government change is highest in Transition economies (81 percent) and lowest in Latin American countries (30 percent). The predictive power of economic crises in developing countries (43 percent) is lower than developed countries (55 percent).Keywords: Economic crises, Government Changes, PoliticalEconomy, Signal Approach.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1446176 Word Base Line Detection in Handwritten Text Recognition Systems
Authors: Kamil R. Aida-zade, Jamaladdin Z. Hasanov
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An approach is offered for more precise definition of base lines- borders in handwritten cursive text and general problems of handwritten text segmentation have also been analyzed. An offered method tries to solve problems arose in handwritten recognition with specific slant or in other words, where the letters of the words are not on the same vertical line. As an informative features, some recognition systems use ascending and descending parts of the letters, found after the word-s baseline detection. In such recognition systems, problems in baseline detection, impacts the quality of the recognition and decreases the rate of the recognition. Despite other methods, here borders are found by small pieces containing segmentation elements and defined as a set of linear functions. In this method, separate borders for top and bottom border lines are found. At the end of the paper, as a result, azerbaijani cursive handwritten texts written in Latin alphabet by different authors has been analyzed.
Keywords: Azeri, azerbaijani, latin, segmentation, cursive, HWR, handwritten, recognition, baseline, ascender, descender, symbols.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2479