Search results for: model updating method

Authors: Ricardo Espinosa

Abstract:

The coherent Self-Averaging (CSA), is a new method proposed in this work; applied to simulated signals evoked potentials related to events (ERP) to find the wave P300, useful systems in the brain computer interface (BCI). The CSA method cleans signal in the time domain of white noise through of successive averaging of a single signal. The method is compared with the traditional method, coherent averaging or synchronized (CA), showing optimal results in the improvement of the signal to noise ratio (SNR). The method of CSA is easy to implement, robust and applicable to any physiological time series contaminated with white noise

Keywords: Evoked potentials, wave P300, Coherent Self-averaging, brain - computer interface (BCI).

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Authors: Yuan-Jye Tseng, Yen-Jung Wang

Abstract:

A product development for green logistics model using the fuzzy analytic network process method is presented for evaluating the relationships among the product design, the manufacturing activities, and the green supply chain. In the product development stage, there can be alternative ways to design the detailed components to satisfy the design concept and product requirement. In different design alternative cases, the manufacturing activities can be different. In addition, the manufacturing activities can affect the green supply chain of the components and product. In this research, a fuzzy analytic network process evaluation model is presented for evaluating the criteria in product design, manufacturing activities, and green supply chain. The comparison matrices for evaluating the criteria among the three groups are established. The total relational values between the three groups represent the relationships and effects. In application, the total relational values can be used to evaluate the design alternative cases for decision-making to select a suitable design case and the green supply chain. In this presentation, an example product is illustrated. It shows that the model is useful for integrated evaluation of design and manufacturing and green supply chain for the purpose of product development for green logistics.

Keywords: Supply chain management, green supply chain, product development for logistics, fuzzy analytic network process.

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Authors: Sepideh Fazeli, Fariba Bahrami

Abstract:

Investigating language acquisition is one of the most challenging problems in the area of studying language. Syllable learning as a level of language acquisition has a considerable significance since it plays an important role in language acquisition. Because of impossibility of studying language acquisition directly with children, especially in its developmental phases, computer models will be useful in examining language acquisition. In this paper a computer model of early language learning for syllable learning is proposed. It is guided by a conceptual model of syllable learning which is named Directions Into Velocities of Articulators model (DIVA). The computer model uses simple associational and reinforcement learning rules within neural network architecture which are inspired by neuroscience. Our simulation results verify the ability of the proposed computer model in producing phonemes during babbling and early speech. Also, it provides a framework for examining the neural basis of language learning and communication disorders.

Keywords: Brain modeling, computer models, language acquisition, reinforcement learning.

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Authors: Minghui Wang, Juntao Zhang

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An inversion-free iterative algorithm is presented for solving nonlinear matrix equation with a stepsize parameter t. The existence of the maximal solution is discussed in detail, and the method for finding it is proposed. Finally, two numerical examples are reported that show the efficiency of the method.

Keywords: Inversion-free method, Hermitian positive definite solution, Maximal solution, Convergence.

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Authors: Eduardo F. Arias, William Cooke III, Zhaofei Fan, William Kingery

Abstract:

During the last decade Panicum virgatum, known as Switchgrass, has been broadly studied because of its remarkable attributes as a substitute pasture and as a functional biofuel source. The objective of this investigation was to establish soil suitability for Switchgrass in the State of Mississippi. A linear weighted additive model was developed to forecast soil suitability. Multicriteria analysis and Sensitivity analysis were utilized to adjust and optimize the model. The model was fit using seven years of field data associated with soils characteristics collected from Natural Resources Conservation System - United States Department of Agriculture (NRCS-USDA). The best model was selected by correlating calculated biomass yield with each model's soils-based output for Switchgrass suitability. Coefficient of determination (r2) was the decisive factor used to establish the 'best' soil suitability model. Coefficients associated with the 'best' model were implemented within a Geographic Information System (GIS) to create a map of relative soil suitability for Switchgrass in Mississippi. A Geodatabase associated with soil parameters was built and is available for future Geographic Information System use.

Keywords: Aptness, GIS, sensitivity analysis, switchgrass, soil.

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Authors: Prateek Maheshwari, Nitin Seth, Anoop Kumar Gupta

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The objective of present research paper is to highlight the importance of measuring advertisement effectiveness in print media and to develop a conceptual model for advertisement effectiveness. The developed model is based on dimensions on which advertisement effectiveness depends and on the dimensions which are used to measure the effectiveness. An in-depth and extensive literature review is carried out to understand the concept of advertisement effectiveness and its various determinants in context of print media. Based on the insights gained, a conceptual framework for advertisement effectiveness is presented. The model is an attempt to uncover the relatively less explored area of advertisement effectiveness in Indian advertising scenario. It is believed that present work will encourage scholars and academicians to further explore the area and will offer conceptual assistance and a fresh direction in the domain of advertisement effectiveness.

Keywords: Advertisement Effectiveness, Conceptual Model, Effectiveness Dimensions, Print Media.

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Authors: Wei Dong, Guo-Ying Gu, Xiangyang Zhu, Han Ding

Abstract:

This paper presents preliminary results on modeling and control of a quadrotor UAV. With aerodynamic concepts, a mathematical model is firstly proposed to describe the dynamics of the quadrotor UAV. Parameters of this model are identified by experiments with Matlab Identify Toolbox. A group of PID controllers are then designed based on the developed model. To verify the developed model and controllers, simulations and experiments for altitude control, position control and trajectory tracking are carried out. The results show that the quadrotor UAV well follows the referenced commands, which clearly demonstrates the effectiveness of the proposed approach.

Keywords: Quadrotor UAV, Modeling, Control, Aerodynamics, System Identification.

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Authors: Ying Shen, Weihua Zhu

Abstract:

Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Keywords: Magnetic Resonance Image, C-means model, image segmentation, information entropy.

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Authors: R. Prakash, B. Meenakshipriya, R. Kumaravelan

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This paper presents modeling and simulation of Grid Connected Photovoltaic (PV) system by using improved mathematical model. The model is used to study different parameter variations and effects on the PV array including operating temperature and solar irradiation level. In this paper stepped P&O algorithm is proposed for MPPT control. This algorithm will identify the suitable duty ratio in which the DC-DC converter should be operated to maximize the power output. Photo voltaic array with proposed stepped P&O-MPPT controller can operate in the maximum power point for the whole range of solar data (irradiance and temperature).

Keywords: Photovoltaic (PV), Maximum Power Point Tracking (MPPT), Boost converter, Stepped Perturb & Observe method (Stepped P&O).

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

Abstract:

Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: Feature selection, multi-objective evolutionary computation, unsupervised classification, behavior assessment system for children.

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Authors: Rasaki O. Olanrewaju

Abstract:

The driven processes of Wiener and Lévy are known self-standing Gaussian-Markov processes for fitting non-linear dynamical Vasciek model. In this paper, a coincidental Gaussian density stationarity condition and autocorrelation function of the two driven processes were established. This led to the conflation of Wiener and Lévy processes so as to investigate the efficiency of estimates incorporated into the one-dimensional Vasciek model that was estimated via the Maximum Likelihood (ML) technique. The conditional laws of drift, diffusion and stationarity process was ascertained for the individual Wiener and Lévy processes as well as the commingle of the two processes for a fixed effect and Autoregressive like Vasciek model when subjected to financial series; exchange rate of Naira-CFA Franc. In addition, the model performance error of the sub-merged driven process was miniature compared to the self-standing driven process of Wiener and Lévy.

Keywords: Wiener process, Lévy process, Vasciek model, drift, diffusion, Gaussian density stationary.

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Authors: Jun Wan, Zehua Chen, Yingwu Chen, Zhidong Bai

Abstract:

This paper proposes a novel feature extraction method, based on Discrete Wavelet Transform (DWT) and K-L Seperability (KLS), for the classification of Functional Data (FD). This method combines the decorrelation and reduction property of DWT and the additive independence property of KLS, which is helpful to extraction classification features of FD. It is an advanced approach of the popular wavelet based shrinkage method for functional data reduction and classification. A theory analysis is given in the paper to prove the consistent convergence property, and a simulation study is also done to compare the proposed method with the former shrinkage ones. The experiment results show that this method has advantages in improving classification efficiency, precision and robustness.

Keywords: classification, functional data, feature extraction, K-Lseperability, wavelet.

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Authors: Amir Abolfazl Suratgar, Mohammad Bagher Tavakoli, Abbas Hoseinabadi

Abstract:

In this paper a modification on Levenberg-Marquardt algorithm for MLP neural network learning is proposed. The proposed algorithm has good convergence. This method reduces the amount of oscillation in learning procedure. An example is given to show usefulness of this method. Finally a simulation verifies the results of proposed method.

Keywords: Levenberg-Marquardt, modification, neural network, variable learning rate.

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Authors: L. Sriphong, A. Chaidedgumjorn, K. Chaisuroj

Abstract:

A spectrophotometric method was developed for simultaneous quantification of pseudoephedrine hydrochloride (PSE) triprolidine hydrochloride (TRI) using second derivative method (zero-crossing technique). The second derivative amplitudes of PSE and TRI were measured at 271 and 321 nm, respectively. The calibration curves were linear in the range of 200 to 1,000 g/ml for PSE and 10 to 50 g/ml for TRI. The method was validated for specificity, accuracy, precision, limit of detection and limit of quantitation. The proposed method was applied to the assaying and dissolution of PSE and TRI in commercial tablets without any chemical separation. The results were compared with those obtained by the official USP31 method and statistical tests showed that there is no significant between the methods at 95% confidence level. The proposed method is simple, rapid and suitable for the routine quality control application. KeywordsTriprolidine, Pseudoephedrine, Derivative spectrophotometry, Dissolution testing.

Keywords: Triprolidine, Pseudoephedrine, Derivative spectrophotometry, Dissolution testing.

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Authors: Yasser F. Hassan

Abstract:

The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: Rough Sets, Rough Neural Networks, Cellular Automata, Image Processing.

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Authors: Milan Rippel, Petr Teply

Abstract:

This paper focuses on operational risk measurement techniques and on economic capital estimation methods. A data sample of operational losses provided by an anonymous Central European bank is analyzed using several approaches. Loss Distribution Approach and scenario analysis method are considered. Custom plausible loss events defined in a particular scenario are merged with the original data sample and their impact on capital estimates and on the financial institution is evaluated. Two main questions are assessed – What is the most appropriate statistical method to measure and model operational loss data distribution? and What is the impact of hypothetical plausible events on the financial institution? The g&h distribution was evaluated to be the most suitable one for operational risk modeling. The method based on the combination of historical loss events modeling and scenario analysis provides reasonable capital estimates and allows for the measurement of the impact of extreme events on banking operations.

Keywords: operational risk, scenario analysis, economic capital, loss distribution approach, extreme value theory, stress testing

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Authors: B. Chemali, B. Tiliouine

Abstract:

This article presents the main results of a numerical investigation on the uncertainty of dynamic response of structures with statistically correlated random damping Gamma distributed. A computational method based on a Linear Statistical Model (LSM) is implemented to predict second order statistics for the response of a typical industrial building structure. The significance of random damping with correlated parameters and its implications on the sensitivity of structural peak response in the neighborhood of a resonant frequency are discussed in light of considerable ranges of damping uncertainties and correlation coefficients. The results are compared to those generated using Monte Carlo simulation techniques. The numerical results obtained show the importance of damping uncertainty and statistical correlation of damping coefficients when obtaining accurate probabilistic estimates of dynamic response of structures. Furthermore, the effectiveness of the LSM model to efficiently predict uncertainty propagation for structural dynamic problems with correlated damping parameters is demonstrated.

Keywords: Correlated random damping, linear statistical model, Monte Carlo simulation, uncertainty of dynamic response.

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Authors: Zanariah Abdul Majid, Mohamed Suleiman

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The aim of this paper is to investigate the performance of the developed two point block method designed for two processors for solving directly non stiff large systems of higher order ordinary differential equations (ODEs). The method calculates the numerical solution at two points simultaneously and produces two new equally spaced solution values within a block and it is possible to assign the computational tasks at each time step to a single processor. The algorithm of the method was developed in C language and the parallel computation was done on a parallel shared memory environment. Numerical results are given to compare the efficiency of the developed method to the sequential timing. For large problems, the parallel implementation produced 1.95 speed-up and 98% efficiency for the two processors.

Keywords: Numerical methods, parallel method, block method, higher order ODEs.

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Authors: A.V.Naresh Babu, S.Sivanagaraju, Ch.Padmanabharaju, T.Ramana

Abstract:

The interline power flow controller (IPFC) is one of the latest generation flexible AC transmission systems (FACTS) controller used to control power flows of multiple transmission lines. This paper presents a mathematical model of IPFC, termed as power injection model (PIM). This model is incorporated in Newton- Raphson (NR) power flow algorithm to study the power flow control in transmission lines in which IPFC is placed. A program in MATLAB has been written in order to extend conventional NR algorithm based on this model. Numerical results are carried out on a standard 2 machine 5 bus system. The results without and with IPFC are compared in terms of voltages, active and reactive power flows to demonstrate the performance of the IPFC model.

Keywords: flexible AC transmission systems (FACTS), interline power flow controller (IPFC), power injection model (PIM), power flow control.

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Authors: Sung-Chul Hwang, Di Ren, Sang-Moon Yoon, Jong-Chun Park, Abbas Khayyer, Hitoshi Gotoh

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This paper presents a fully Lagrangian coupled Fluid-Structure Interaction (FSI) solver for simulations of fluid-structure interactions, which is based on the Moving Particle Semi-implicit (MPS) method to solve the governing equations corresponding to incompressible flows as well as elastic structures. The developed solver is verified by reproducing the high velocity impact loads of deformable thin wedges with three different materials such as mild steel, aluminium and tin during water entry. The present simulation results for aluminium are compared with analytical solution derived from the hydrodynamic Wagner model and linear Wan’s theory. And also, the impact pressure and strain on the water entry wedge with three different materials, such as mild steel, aluminium and tin, are simulated and the effects of hydro-elasticity are discussed.

Keywords: Fluid-structure interaction (FSI), Moving Particle Semi-implicit (MPS) method, Elastic structure, Incompressible fluid Wedge slamming impact.

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Authors: Prabh Preet Singh, Harpreet Kaur

Abstract:

This paper presents a method for single image dehazing based on dark channel prior (DCP). The property that the intensity of the dark channel gives an approximate thickness of the haze is used to estimate the transmission and atmospheric light. Instead of constant atmospheric light, the proposed method employs scene depth to estimate spatially varying atmospheric light as it truly occurs in nature. Haze imaging model together with the soft matting method has been used in this work to produce high quality haze free image. Experimental results demonstrate that the proposed approach produces better results than the classic DCP approach as color fidelity and contrast of haze free image are improved and no over-saturation in the sky region is observed. Further, lifting Haar wavelet transform is employed to reduce overall execution time by a factor of two to three as compared to the conventional approach.

Keywords: Depth based atmospheric light, dark channel prior, lifting wavelet.

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Authors: Chen Wu, Komal Narejo, Dandan Li

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Some extended rough set models in incomplete information system cannot distinguish the two objects that have few known attributes and more unknown attributes; some cannot make a flexible and accurate discrimination. In order to solve this problem, this paper suggests an improved limited tolerance rough set model using two thresholds to control what two objects have a relationship between them in limited tolerance relation and to classify objects. Our practical study case shows the model can get fine and reasonable decision results.

Keywords: Decision rule, incomplete information system, limited tolerance relation, rough set model.

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Authors: Smarajit Ghosh , Karma Sonam Sherpa

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This paper reports a new and accurate method for load-flow solution of radial distribution networks with minimum data preparation. The node and branch numbering need not to be sequential like other available methods. The proposed method does not need sending-node, receiving-node and branch numbers if these are sequential. The proposed method uses the simple equation to compute the voltage magnitude and has the capability to handle composite load modelling. The proposed method uses the set of nodes of feeder, lateral(s) and sub lateral(s). The effectiveness of the proposed method is compared with other methods using two examples. The detailed load-flow results for different kind of load-modellings are also presented.

Keywords: Load−flow, Feeder, Lateral, Power, Voltage, Composite, Exponential

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Authors: Nitish Kumar Vaja, Oumar Barry, Brian DeJong

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Aeolian vibrations are the major cause for the failure of conductor cables. Using a Stockbridge damper reduces these vibrations and increases the life span of the conductor cable. Designing an efficient Stockbridge damper that suits the conductor cable requires a robust mathematical model with minimum assumptions. However it is not easy to analytically model the complex geometry of the messenger. Therefore an equivalent stiffness must be determined so that it can be used in the analytical model. This paper examines the bending stiffness of the cable and discusses the effect of this stiffness on the natural frequencies. The obtained equivalent stiffness compensates for the assumption of modeling the messenger as a rod. The results from the free vibration analysis of the analytical model with the equivalent stiffness is validated using the full scale finite element model of the Stockbridge damper.

Keywords: Equivalent stiffness, finite element model, free vibration response, Stockbridge damper.

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Authors: S.H. Nasseri, E. Ardil

Abstract:

Fuzzy linear programming is an application of fuzzy set theory in linear decision making problems and most of these problems are related to linear programming with fuzzy variables. A convenient method for solving these problems is based on using of auxiliary problem. In this paper a new method for solving fuzzy variable linear programming problems directly using linear ranking functions is proposed. This method uses simplex tableau which is used for solving linear programming problems in crisp environment before.

Keywords: Fuzzy variable linear programming, fuzzy number, ranking function, simplex method.

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Authors: L. Richter, J. Lübkemann, P. Nyhuis

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In order to remain competitive in what is a turbulent environment; businesses must be able to react rapidly to change. The past response to volatile market conditions was to introduce an element of flexibility to production. Nowadays, what is often required is a redesign of factory structures in order to cope with the state of constant flux. The Institute of Production Systems and Logistics is currently developing a descriptive and causal model for the redesign of plant structures as part of an ongoing research project. This article presents the first research findings attained in devising this model.

Keywords: Causal model, change driven factory redesign, factory planning, plant structure.

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Authors: H. Rong, X. C. Yin, J. Yang, Y. N. Shen

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Based on Rayleigh beam theory, the sub-impacts of a free-free beam struck horizontally by a round-nosed rigid mass is simulated by the finite difference method and the impact-separation conditions. In order to obtain the sub-impact force, a uniaxial compression elastic-plastic contact model is employed to analyze the local deformation field on contact zone. It is found that the horizontal impact is a complicated process including the elastic plastic sub-impacts in sequence. There are two sub-zones of sub-impact. In addition, it found that the elastic energy of the free-free beam is more suitable for the Poisson collision hypothesis to explain compression and recovery processes.

Keywords: beam, sub-impact, elastic-plastic deformation, finite difference method.

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Authors: M. Alauddin, M. A. Ullah, M. Alom, M. N. Islam

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The rivers in Bangladesh are highly unstable having loose boundaries, mild slope of water surface and bed, irregular siltation of huge sediment coming from upstream, among others. The groins are installed in the river bank to deflect the flowing water away from the vulnerable zones. The conventional groins are found to be unstable and ineffective. The combined groin having both impermeable and permeable components in the same structure improves the flow field to function better over others. The main goal of this study is to analyze the hydraulic characteristics induced by the combined groins of different alignments by using a 2D numerical model, iRIC Nays2DH. In this numerical simulation, the K-ε model for turbulence and Cubic Interpolation Pseudo-particle (CIP) method for advective terms are utilized. A particular flow condition is applied in the channel for all sets of groins with different alignments. The simulation results reveal that the combined groins alter the flow patterns considerably, with no significant recirculation of flow in the groin field. The effect of different alignments of groins is found somewhat different. Based on hydraulic features caused by the groins, the combined groin that aligns the permeable component towards slightly downstream performs better over others.

Keywords: Combined groin, alignment, hydraulic characteristics, numerical model.

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Authors: Yang Liu, Jinfeng Wang, Hong Li, Wei Gao, Siriguleng He

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A new numerical scheme based on the H1-Galerkin mixed finite element method for a class of second-order pseudohyperbolic equations is constructed. The proposed procedures can be split into three independent differential sub-schemes and does not need to solve a coupled system of equations. Optimal error estimates are derived for both semidiscrete and fully discrete schemes for problems in one space dimension. And the proposed method dose not requires the LBB consistency condition. Finally, some numerical results are provided to illustrate the efficacy of our method.

Keywords: Pseudo-hyperbolic equations, splitting system, H1-Galerkin mixed method, error estimates.

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Authors: Abdullah A. AlShaher

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In this paper, we demonstrate how regression curves can be used to recognize 2D non-rigid handwritten shapes. Each shape is represented by a set of non-overlapping uniformly distributed landmarks. The underlying models utilize 2^nd order of polynomials to model shapes within a training set. To estimate the regression models, we need to extract the required coefficients which describe the variations for a set of shape class. Hence, a least square method is used to estimate such modes. We then proceed by training these coefficients using the apparatus Expectation Maximization algorithm. Recognition is carried out by finding the least error landmarks displacement with respect to the model curves. Handwritten isolated Arabic characters are used to evaluate our approach.

Keywords: Shape recognition, Arabic handwritten characters, regression curves, expectation maximization algorithm.

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