Search results for: Gabor function
1895 Probability Density Estimation Using Advanced Support Vector Machines and the Expectation Maximization Algorithm
Authors: Refaat M Mohamed, Ayman El-Baz, Aly A. Farag
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This paper presents a new approach for the prob-ability density function estimation using the Support Vector Ma-chines (SVM) and the Expectation Maximization (EM) algorithms.In the proposed approach, an advanced algorithm for the SVM den-sity estimation which incorporates the Mean Field theory in the learning process is used. Instead of using ad-hoc values for the para-meters of the kernel function which is used by the SVM algorithm,the proposed approach uses the EM algorithm for an automatic optimization of the kernel. Experimental evaluation using simulated data set shows encouraging results.
Keywords: Density Estimation, SVM, Learning Algorithms, Parameters Estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25131894 Kinematic Hardening Parameters Identification with Respect to Objective Function
Authors: Marina Franulovic, Robert Basan, Bozidar Krizan
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Constitutive modeling of material behavior is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behavior of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behavior modeling.
Keywords: Genetic algorithm, kinematic hardening, material model, objective function
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 38071893 Traffic Signs
Authors: A. Gutiérrez, A. Castillo, J. M. Gómez, J. M. Gutiérrez, A. García-Cabot
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Road signs are the elements of roads with a lot of influence in driver-s behavior. So that signals can fulfill its function, they must overcome visibility and durability requirements, particularly needed at night, when the coefficient of retroreflection becomes a decisive factor in ensuring road safety. Accepting that the visibility of the signage has implications for people-s safety, we understand the importance to fulfill its function: to foster the highest standards of service and safety in drivers. The usual conditions of perception of any sign are determined by: age of the driver, reflective material, luminosity, vehicle speed and emplacement. In this way, this paper evaluates the different signals to increase the safety road.Keywords: Luminosity, orientation, retroreflection, traffic signs.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16621892 A Robust Salient Region Extraction Based on Color and Texture Features
Authors: Mingxin Zhang, Zhaogan Lu, Junyi Shen
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In current common research reports, salient regions are usually defined as those regions that could present the main meaningful or semantic contents. However, there are no uniform saliency metrics that could describe the saliency of implicit image regions. Most common metrics take those regions as salient regions, which have many abrupt changes or some unpredictable characteristics. But, this metric will fail to detect those salient useful regions with flat textures. In fact, according to human semantic perceptions, color and texture distinctions are the main characteristics that could distinct different regions. Thus, we present a novel saliency metric coupled with color and texture features, and its corresponding salient region extraction methods. In order to evaluate the corresponding saliency values of implicit regions in one image, three main colors and multi-resolution Gabor features are respectively used for color and texture features. For each region, its saliency value is actually to evaluate the total sum of its Euclidean distances for other regions in the color and texture spaces. A special synthesized image and several practical images with main salient regions are used to evaluate the performance of the proposed saliency metric and other several common metrics, i.e., scale saliency, wavelet transform modulus maxima point density, and important index based metrics. Experiment results verified that the proposed saliency metric could achieve more robust performance than those common saliency metrics.Keywords: salient regions, color and texture features, image segmentation, saliency metric
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15731891 A Model-following Adaptive Controller for Linear/Nonlinear Plantsusing Radial Basis Function Neural Networks
Authors: Yuichi Masukake, Yoshihisa Ishida
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In this paper, we proposed a method to design a model-following adaptive controller for linear/nonlinear plants. Radial basis function neural networks (RBF-NNs), which are known for their stable learning capability and fast training, are used to identify linear/nonlinear plants. Simulation results show that the proposed method is effective in controlling both linear and nonlinear plants with disturbance in the plant input.Keywords: Linear/nonlinear plants, neural networks, radial basisfunction networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14881890 Object Recognition on Horse Riding Simulator System
Authors: Kyekyung Kim, Sangseung Kang, Suyoung Chi, Jaehong Kim
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In recent years, IT convergence technology has been developed to get creative solution by combining robotics or sports science technology. Object detection and recognition have mainly applied to sports science field that has processed by recognizing face and by tracking human body. But object detection and recognition using vision sensor is challenge task in real world because of illumination. In this paper, object detection and recognition using vision sensor applied to sports simulator has been introduced. Face recognition has been processed to identify user and to update automatically a person athletic recording. Human body has tracked to offer a most accurate way of riding horse simulator. Combined image processing has been processed to reduce illumination adverse affect because illumination has caused low performance in detection and recognition in real world application filed. Face has recognized using standard face graph and human body has tracked using pose model, which has composed of feature nodes generated diverse face and pose images. Face recognition using Gabor wavelet and pose recognition using pose graph is robust to real application. We have simulated using ETRI database, which has constructed on horse riding simulator.
Keywords: Horse riding simulator, Object detection, Object recognition, User identification, Pose recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20951889 Effect of Leaf Essential Oil of Citrus sinensis at Different Harvest Time on Some Liver and Kidney Function Indices of Diabetic Rats
Authors: O. Soji-Omoniwa, N. O. Muhammad, L. A. Usman, B. P. Omoniwa
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This study was conducted to investigate the effect of the leaf essential oil of C. sinensis harvested at 7.00a.m and 4.00p.m on some Liver and Kidney function indices of diabetic rats as well as investigate the effect of time of harvest on the observed effect. Experimental animals were divided into 4 groups (A, B, C and D). Diabetes mellitus was induced in all animals, except the normal control group (Group A), by injecting 150mg/kg body weight of alloxan monohydrate intraperitoneally. Group A received distilled water while group B (diabetic control group) was not treated. Group C and D were treated with leaf essential oil of C. sinensis harvested at 7.00 a.m and 4.00p.m respectively at a dose of 110 mg/kg body weight every other day for 15 days. Alkaline phosphatase (ALP), Alanine Transaminase (ALT) and Aspartate Transaminase (AST) activity was evaluated in the serum, Liver and Kidney of studied animals. Total and Direct Bilirubin level, Total Protein and Globulin, Creatinine and Urea level were also evaluated. Result showed that creatinine and urea, serum ALP, AST and ALT levels was significantly reduced (p < 0.05), while the levels of total Protein and Globulin increased significantly (p < 0.05) for the treated animals compared to the diabetic control group. In conclusion, the leaf essential oil of Citrus sinensis ameliorated the impaired renal and liver function; however, the time of harvest of the leaf does not significantly affect its ameliorative effect.
Keywords: C. sinensis, Function indices, Harvest time, Leaf essential oil.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25141888 Sensitivity Analysis during the Optimization Process Using Genetic Algorithms
Authors: M. A. Rubio, A. Urquia
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Genetic algorithms (GA) are applied to the solution of high-dimensional optimization problems. Additionally, sensitivity analysis (SA) is usually carried out to determine the effect on optimal solutions of changes in parameter values of the objective function. These two analyses (i.e., optimization and sensitivity analysis) are computationally intensive when applied to high-dimensional functions. The approach presented in this paper consists in performing the SA during the GA execution, by statistically analyzing the data obtained of running the GA. The advantage is that in this case SA does not involve making additional evaluations of the objective function and, consequently, this proposed approach requires less computational effort than conducting optimization and SA in two consecutive steps.Keywords: Optimization, sensitivity, genetic algorithms, model calibration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14801887 Approximations to the Distribution of the Sample Correlation Coefficient
Authors: John N. Haddad, Serge B. Provost
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Given a bivariate normal sample of correlated variables, (Xi, Yi), i = 1, . . . , n, an alternative estimator of Pearson’s correlation coefficient is obtained in terms of the ranges, |Xi − Yi|. An approximate confidence interval for ρX,Y is then derived, and a simulation study reveals that the resulting coverage probabilities are in close agreement with the set confidence levels. As well, a new approximant is provided for the density function of R, the sample correlation coefficient. A mixture involving the proposed approximate density of R, denoted by hR(r), and a density function determined from a known approximation due to R. A. Fisher is shown to accurately approximate the distribution of R. Finally, nearly exact density approximants are obtained on adjusting hR(r) by a 7th degree polynomial.Keywords: Sample correlation coefficient, density approximation, confidence intervals.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22791886 Measurement Fractional Order Sallen-Key Filters
Authors: Ahmed Soltan, Ahmed G. Radwan, Ahmed M. Soliman
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This work aims to generalize the integer order Sallen-Key filters into the fractional-order domain. The analysis in the case of two different fractional-order elements introduced where the general transfer function becomes four terms which is unusual in the conventional case. In addition, the effect of the transfer function parameters on the filter poles and hence the stability is introduced and closed forms for the filter critical frequencies are driven. Finally, different examples for the fractional order Sallen-Key filter design are presented with circuit simulations using ADS where a great matching between the numerical and simulation results is obtained.
Keywords: Analog Filter, Low-Pass Filter, Fractance, Sallen-Key, Stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31511885 Turing Pattern in the Oregonator Revisited
Authors: Elragig Aiman, Dreiwi Hanan, Townley Stuart, Elmabrook Idriss
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In this paper, we reconsider the analysis of the Oregonator model. We highlight an error in this analysis which leads to an incorrect depiction of the parameter region in which diffusion driven instability is possible. We believe that the cause of the oversight is the complexity of stability analyses based on eigenvalues and the dependence on parameters of matrix minors appearing in stability calculations. We regenerate the parameter space where Turing patterns can be seen, and we use the common Lyapunov function (CLF) approach, which is numerically reliable, to further confirm the dependence of the results on diffusion coefficients intensities.Keywords: Diffusion driven instability, common Lyapunov function (CLF), turing pattern, positive-definite matrix.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10511884 On Solution of Interval Valued Intuitionistic Fuzzy Assignment Problem Using Similarity Measure and Score Function
Authors: Gaurav Kumar, Rakesh Kumar Bajaj
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The primary objective of the paper is to propose a new method for solving assignment problem under uncertain situation. In the classical assignment problem (AP), zpqdenotes the cost for assigning the qth job to the pth person which is deterministic in nature. Here in some uncertain situation, we have assigned a cost in the form of composite relative degree Fpq instead of and this replaced cost is in the maximization form. In this paper, it has been solved and validated by the two proposed algorithms, a new mathematical formulation of IVIF assignment problem has been presented where the cost has been considered to be an IVIFN and the membership of elements in the set can be explained by positive and negative evidences. To determine the composite relative degree of similarity of IVIFS the concept of similarity measure and the score function is used for validating the solution which is obtained by Composite relative similarity degree method. Further, hypothetical numeric illusion is conducted to clarify the method’s effectiveness and feasibility developed in the study. Finally, conclusion and suggestion for future work are also proposed.
Keywords: Assignment problem, Interval-valued Intuitionistic Fuzzy Sets, Similarity Measures, score function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30181883 A New Nonlinear PID Controller and its Parameter Design
Authors: Yongping Ren, Zongli Li, Fan Zhang
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A new nonlinear PID controller and its stability analysis are presented in this paper. A nonlinear function is deduced from the similarities between the control effort and the electric-field effect of a capacitor. The conventional linear PID controller can be modified into a nonlinear one by this function. To analyze the stability of the nonlinear PID controlled system, an idea of energy equivalence is adapted to avoid the conservativeness which is usually arisen from some traditional theorems and Criterions. The energy equivalence is naturally related with the conceptions of Passivity and T-Passivity. As a result, an engineering guideline for the parameter design of the nonlinear PID controller is obtained. An inverted pendulum system is tested to verify the nonlinear PID control scheme.Keywords: Nonlinear PID controller, stability, gain equivalence, dissipative, T-Passivity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31851882 Comparison of Anti-Shadoo Antibodies – Where is the Endogenous Shadoo protein?
Authors: Eszter Tóth, Ervin Welker
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Shadoo protein (Sho) was described in 2003 as the newest member of Prion protein superfamily [1]. Sho has similar structural motifs like prion protein (PrP) that is known for its central role in transmissible spongiform enchephalopathies. Although a great number of functions have been proposed, the exact physiological function of PrP is not known yet. Investigation of the function and localization of Sho may help us to understand the function of the Prion protein superfamily. Analyzing the subcellular localization of YFP-tagged forms of Sho, we detected the protein in the plasma membrane and in the nucleus of various cell lines. To reveal the localization of the endogenous protein we generated antibodies against Shadoo as well as employed commercially available anti-Shadoo antibodies: i) EG62 anti-mouse Shadoo antibody generated by Eurogentec Ltd.; ii) S-12 anti-human Shadoo antibody by Santa Cruz Biotechnology Inc.; iii) R-12 anti-mouse Shadoo antibody by Santa Cruz Biotechnology Inc.; iv) SPRN antibody against human Shadoo by Abgent Inc. We carried out immunocytochemistry on non-transfected HeLa, Zpl 2-1, Zw 3-5, GT1-1, GT1-7 and SHSY5Y cells as well as on YFP-Sho, Sho-YFP, and YFP-GPI transfected HeLa cells. Their specificity (in antibody-peptide competition assay) and co-localization (with the YFP signal) were assessed.
Keywords: Shadoo, prion protein, immunocytochemistry, antibody-peptide competition assay, antibody.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17141881 Pruning Method of Belief Decision Trees
Authors: Salsabil Trabelsi, Zied Elouedi, Khaled Mellouli
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The belief decision tree (BDT) approach is a decision tree in an uncertain environment where the uncertainty is represented through the Transferable Belief Model (TBM), one interpretation of the belief function theory. The uncertainty can appear either in the actual class of training objects or attribute values of objects to classify. In this paper, we develop a post-pruning method of belief decision trees in order to reduce size and improve classification accuracy on unseen cases. The pruning of decision tree has a considerable intention in the areas of machine learning.Keywords: machine learning, uncertainty, belief function theory, belief decision tree, pruning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19151880 Improved Stability Criteria for Neural Networks with Two Additive Time-Varying Delays
Authors: Miaomiao Yang, Shouming Zhong
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This paper studies the problem of stability criteria for neural networks with two additive time-varying delays.A new Lyapunov-Krasovskii function is constructed and some new delay dependent stability criterias are derived in the terms of linear matrix inequalities(LMI), zero equalities and reciprocally convex approach.The several stability criterion proposed in this paper is simpler and effective. Finally,numerical examples are provided to demonstrate the feasibility and effectiveness of our results.
Keywords: Stability, Neural networks, Linear Matrix Inequalities (LMI) , Lyapunov function, Time-varying delays
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14571879 Single Zone Model for HCCI Engine Fueled with n-Heptane
Authors: Thanapiyawanit Bancha, Lu Jau-Huai
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In this study, we developed a model to predict the temperature and the pressure variation in an internal combustion engine operated in HCCI (Homogeneous charge compression ignition) mode. HCCI operation begins from aspirating of homogeneous charge mixture through intake valve like SI (Spark ignition) engine and the premixed charge is compressed until temperature and pressure of mixture reach autoignition point like diesel engine. Combustion phase was described by double-Wiebe function. The single zone model coupled with an double-Wiebe function were performed to simulated pressure and temperature between the period of IVC (Inlet valve close) and EVO (Exhaust valve open). Mixture gas properties were implemented using STANJAN and transfer the results to main model. The model has considered the engine geometry and enables varying in fuelling, equivalence ratio, manifold temperature and pressure. The results were compared with the experiment and showed good correlation with respect to combustion phasing, pressure rise, peak pressure and temperature. This model could be adapted and use to control start of combustion for HCCI engine.Keywords: Double-Wiebe function, HCCI, Ignition enhancer, Single zone model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28081878 Modeling of Statistically Multiplexed Non Uniform Activity VBR Video
Authors: J. P. Dubois
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This paper reports the feasibility of the ARMA model to describe a bursty video source transmitting over a AAL5 ATM link (VBR traffic). The traffic represents the activity of the action movie "Lethal Weapon 3" transmitted over the ATM network using the Fore System AVA-200 ATM video codec with a peak rate of 100 Mbps and a frame rate of 25. The model parameters were estimated for a single video source and independently multiplexed video sources. It was found that the model ARMA (2, 4) is well-suited for the real data in terms of average rate traffic profile, probability density function, autocorrelation function, burstiness measure, and the pole-zero distribution of the filter model.Keywords: ARMA, ATM networks, burstiness, multimediatraffic, VBR video.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13731877 A Study of the Effectiveness of the Routing Decision Support Algorithm
Authors: Wayne Goodridge, Alexander Nikov, Ashok Sahai
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Multi criteria decision making (MCDM) methods like analytic hierarchy process, ELECTRE and multi-attribute utility theory are critically studied. They have irregularities in terms of the reliability of ranking of the best alternatives. The Routing Decision Support (RDS) algorithm is trying to improve some of their deficiencies. This paper gives a mathematical verification that the RDS algorithm conforms to the test criteria for an effective MCDM method when a linear preference function is considered.
Keywords: Decision support systems, linear preference function, multi-criteria decision-making algorithm, analytic hierarchy process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15881876 Distributed e-Learning System with Client-Server and P2P Hybrid Architecture
Authors: Kazunari Meguro, Shinichi Motomura, Takao Kawamura, Kazunori Sugahara
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We have developed a distributed asynchronous Web based training system. In order to improve the scalability and robustness of this system, all contents and a function are realized on mobile agents. These agents are distributed to computers, and they can use a Peer to Peer network that modified Content-Addressable Network. In this system, all computers offer the function and exercise by themselves. However, the system that all computers do the same behavior is not realistic. In this paper, as a solution of this issue, we present an e-Learning system that is composed of computers of different participation types. Enabling the computer of different participation types will improve the convenience of the system.Keywords: Distributed Multimedia Systems, e-Learning, P2P, Mobile Agen
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23441875 The Investigations of Water-ethanol Mixture by Monte Carlo Method
Authors: Atamas N. A., Atamas A. A.
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Energetic and structural results for ethanol-water mixtures as a function of the mole fraction were calculated using Monte Carlo methodology. Energy partitioning results obtained for equimolar water-ethanol mixture and ether organic liquids are compared. It has been shown that at xet=0.22 the RDFs for waterethanol and ethanol-ethanol interactions indicated strong hydrophobic interactions between ethanol molecules and the local structure of solution is less structured at this concentration as at ether ones. Results obtained for ethanol-water mixture as a function of concentration are in good agreement with the experimental data.
Keywords: Ethanol, molecular liquids, Monte Carlo, water, thermodynamics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22511874 An Implementation of MacMahon's Partition Analysis in Ordering the Lower Bound of Processing Elements for the Algorithm of LU Decomposition
Authors: Halil Snopce, Ilir Spahiu, Lavdrim Elmazi
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A lot of Scientific and Engineering problems require the solution of large systems of linear equations of the form bAx in an effective manner. LU-Decomposition offers good choices for solving this problem. Our approach is to find the lower bound of processing elements needed for this purpose. Here is used the so called Omega calculus, as a computational method for solving problems via their corresponding Diophantine relation. From the corresponding algorithm is formed a system of linear diophantine equalities using the domain of computation which is given by the set of lattice points inside the polyhedron. Then is run the Mathematica program DiophantineGF.m. This program calculates the generating function from which is possible to find the number of solutions to the system of Diophantine equalities, which in fact gives the lower bound for the number of processors needed for the corresponding algorithm. There is given a mathematical explanation of the problem as well. Keywordsgenerating function, lattice points in polyhedron, lower bound of processor elements, system of Diophantine equationsand : calculus.
Keywords: generating function, lattice points in polyhedron, lower bound of processor elements, system of Diophantine equations and calculus.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14781873 PID Parameter Optimization of an UAV Longitudinal Flight Control System
Authors: Kamran Turkoglu, Ugur Ozdemir, Melike Nikbay, Elbrous M. Jafarov
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In this paper, an automatic control system design based on Integral Squared Error (ISE) parameter optimization technique has been implemented on longitudinal flight dynamics of an UAV. It has been aimed to minimize the error function between the reference signal and the output of the plant. In the following parts, objective function has been defined with respect to error dynamics. An unconstrained optimization problem has been solved analytically by using necessary and sufficient conditions of optimality, optimum PID parameters have been obtained and implemented in control system dynamics.Keywords: Optimum Design, KKT Conditions, UAV, Longitudinal Flight Dynamics, ISE Parameter Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37531872 A Stochastic Diffusion Process Based on the Two-Parameters Weibull Density Function
Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos
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Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.Keywords: Diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion equation, trends functions, bi-parameters Weibull density function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19741871 Implementation of an Associative Memory Using a Restricted Hopfield Network
Authors: Tet H. Yeap
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An analog restricted Hopfield Network is presented in this paper. It consists of two layers of nodes, visible and hidden nodes, connected by directional weighted paths forming a bipartite graph with no intralayer connection. An energy or Lyapunov function was derived to show that the proposed network will converge to stable states. By introducing hidden nodes, the proposed network can be trained to store patterns and has increased memory capacity. Training to be an associative memory, simulation results show that the associative memory performs better than a classical Hopfield network by being able to perform better memory recall when the input is noisy.Keywords: Associative memory, Hopfield network, Lyapunov function, Restricted Hopfield network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4971870 An Effective Framework for Chinese Syntactic Parsing
Authors: Xing Li, Chengqing Zong
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This paper presents an effective framework for Chinesesyntactic parsing, which includes two parts. The first one is a parsing framework, which is based on an improved bottom-up chart parsingalgorithm, and integrates the idea of the beam search strategy of N bestalgorithm and heuristic function of A* algorithm for pruning, then get multiple parsing trees. The second is a novel evaluation model, which integrates contextual and partial lexical information into traditional PCFG model and defines a new score function. Using this model, the tree with the highest score is found out as the best parsing tree. Finally,the contrasting experiment results are given. Keywords?syntactic parsing, PCFG, pruning, evaluation model.
Keywords: syntactic parsing, PCFG, pruning, evaluation model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12261869 An Estimation of Variance Components in Linear Mixed Model
Authors: Shuimiao Wan, Chao Yuan, Baoguang Tian
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In this paper, a linear mixed model which has two random effects is broken up into two models. This thesis gets the parameter estimation of the original model and an estimation’s statistical qualities based on these two models. Then many important properties are given by comparing this estimation with other general estimations. At the same time, this paper proves the analysis of variance estimate (ANOVAE) about σ2 of the original model is equal to the least-squares estimation (LSE) about σ2 of these two models. Finally, it also proves that this estimation is better than ANOVAE under Stein function and special condition in some degree.Keywords: Linear mixed model, Random effects, Parameter estimation, Stein function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18221868 Hybrid Function Method for Solving Nonlinear Fredholm Integral Equations of the Second Kind
Authors: jianhua Hou, Changqing Yang, and Beibo Qin
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A numerical method for solving nonlinear Fredholm integral equations of second kind is proposed. The Fredholm type equations which have many applications in mathematical physics are then considered. The method is based on hybrid function approximations. The properties of hybrid of block-pulse functions and Chebyshev polynomials are presented and are utilized to reduce the computation of nonlinear Fredholm integral equations to a system of nonlinear. Some numerical examples are selected to illustrate the effectiveness and simplicity of the method.
Keywords: Hybrid functions, Fredholm integral equation, Blockpulse, Chebyshev polynomials, product operational matrix.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14081867 Improved Robust Stability Criteria of a Class of Neutral Lur’e Systems with Interval Time-Varying Delays
Authors: Longqiao Zhou, Zixin Liu, Shu Lü
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This paper addresses the robust stability problem of a class of delayed neutral Lur’e systems. Combined with the property of convex function and double integral Jensen inequality, a new tripe integral Lyapunov functional is constructed to derive some new stability criteria. Compared with some related results, the new criteria established in this paper are less conservative. Finally, two numerical examples are presented to illustrate the validity of the main results.
Keywords: Lur’e system, Convex function, Jensen integral inequality, Triple-integral method, Exponential stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15261866 Analysis of Train Passenger Seat Using Ergonomic Function Deployment Method
Authors: Robertoes K. K. Wibowo, Siswoyo Soekarno, Irma Puspitasari
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Indonesian people use trains for their transportation, especially they use economy class train transportation because it is cheaper and has a more precise schedule than any other ground transportation. Nevertheless, the economy class passenger seat raises some inconvenience issues for passengers. This is due to the design of the chair on the economic class of trains that did not adjusted to the shape of anthropometry of Indonesian people. Thus, research needs to be conducted on the design of the seats in the economic class of trains. The purpose of this research is to make the design of economy class passenger seats ergonomic. This research method uses questionnaires and anthropometry measurements. The data obtained is processed using House of Quality of Ergonomic Function Development. From the results of analysis and data processing were obtained important changes from the original design. Ergonomic chair design according to the analysis is a stainless steel frame, seat height 390 mm, with a seat width for each passenger of 400 mm and a depth of 400 mm. Design of the backrest has a height of 840 mm, width of 430 mm and length of 300 mm that can move at the angle of 105-115 degrees. The width of the footrest is 42 mm and 400 mm length. The thickness of the seat cushion is 100 mm.
Keywords: Chair, ergonomics, function development, train passenger.
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