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method</title> <meta name="description" content="Search results for: variational method"> <meta name="keywords" content="variational method"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="variational method"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 18960</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: variational method</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18960</span> Numerical Solutions of Generalized Burger-Fisher Equation by Modified Variational Iteration Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20O.%20Olayiwola">M. O. Olayiwola</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Numerical solutions of the generalized Burger-Fisher are obtained using a Modified Variational Iteration Method (MVIM) with minimal computational efforts. The computed results with this technique have been compared with other results. The present method is seen to be a very reliable alternative method to some existing techniques for such nonlinear problems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=burger-fisher" title="burger-fisher">burger-fisher</a>, <a href="https://publications.waset.org/abstracts/search?q=modified%20variational%20iteration%20method" title=" modified variational iteration method"> modified variational iteration method</a>, <a href="https://publications.waset.org/abstracts/search?q=lagrange%20multiplier" title=" lagrange multiplier"> lagrange multiplier</a>, <a href="https://publications.waset.org/abstracts/search?q=Taylor%E2%80%99s%20series" title=" Taylor’s series"> Taylor’s series</a>, <a href="https://publications.waset.org/abstracts/search?q=partial%20differential%20equation" title=" partial differential equation"> partial differential equation</a> </p> <a href="https://publications.waset.org/abstracts/3943/numerical-solutions-of-generalized-burger-fisher-equation-by-modified-variational-iteration-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3943.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">430</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18959</span> Variational Evolutionary Splines for Solving a Model of Temporomandibular Disorders</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alberto%20Hananel">Alberto Hananel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this work is to modelize the occlusion of a person with temporomandibular disorders as an evolutionary equation and approach its solution by the construction and characterizing of discrete variational splines. To formulate the problem, certain boundary conditions have been considered. After showing the existence and the uniqueness of the solution of such a problem, a convergence result of a discrete variational evolutionary spline is shown. A stress analysis of the occlusion of a human jaw with temporomandibular disorders by finite elements is carried out in FreeFem++ in order to prove the validity of the presented method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=approximation" title="approximation">approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20PDE" title=" evolutionary PDE"> evolutionary PDE</a>, <a href="https://publications.waset.org/abstracts/search?q=Finite%20Element%20Method" title=" Finite Element Method"> Finite Element Method</a>, <a href="https://publications.waset.org/abstracts/search?q=temporomandibular%20disorders" title=" temporomandibular disorders"> temporomandibular disorders</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20spline" title=" variational spline"> variational spline</a> </p> <a href="https://publications.waset.org/abstracts/51438/variational-evolutionary-splines-for-solving-a-model-of-temporomandibular-disorders" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51438.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">378</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18958</span> Postbuckling Analysis of End Supported Rods under Self-Weight Using Intrinsic Coordinate Finite Elements</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=C.%20Juntarasaid">C. Juntarasaid</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Pulngern"> T. Pulngern</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Chucheepsakul"> S. Chucheepsakul</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A formulation of postbuckling analysis of end supported rods under self-weight has been presented by the variational method. The variational formulation involving the strain energy due to bending and the potential energy of the self-weight, are expressed in terms of the intrinsic coordinates. The variational formulation is accomplished by introducing the Lagrange multiplier technique to impose the boundary conditions. The finite element method is used to derive a system of nonlinear equations resulting from the stationary of the total potential energy and then Newton-Raphson iterative procedure is applied to solve this system of equations. The numerical results demonstrate the postbluckled configurations of end supported rods under self-weight. This finite element method based on variational formulation expressed in term of intrinsic coordinate is highly recommended for postbuckling analysis of end-supported rods under self-weight. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=postbuckling" title="postbuckling">postbuckling</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20element%20method" title=" finite element method"> finite element method</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20method" title=" variational method"> variational method</a>, <a href="https://publications.waset.org/abstracts/search?q=intrinsic%20coordinate" title=" intrinsic coordinate"> intrinsic coordinate</a> </p> <a href="https://publications.waset.org/abstracts/112297/postbuckling-analysis-of-end-supported-rods-under-self-weight-using-intrinsic-coordinate-finite-elements" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/112297.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">158</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18957</span> Numerical Iteration Method to Find New Formulas for Nonlinear Equations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kholod%20Mohammad%20Abualnaja">Kholod Mohammad Abualnaja</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A new algorithm is presented to find some new iterative methods for solving nonlinear equations F(x)=0 by using the variational iteration method. The efficiency of the considered method is illustrated by example. The results show that the proposed iteration technique, without linearization or small perturbation, is very effective and convenient. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=variational%20iteration%20method" title="variational iteration method">variational iteration method</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20equations" title=" nonlinear equations"> nonlinear equations</a>, <a href="https://publications.waset.org/abstracts/search?q=Lagrange%20multiplier" title=" Lagrange multiplier"> Lagrange multiplier</a>, <a href="https://publications.waset.org/abstracts/search?q=algorithms" title=" algorithms "> algorithms </a> </p> <a href="https://publications.waset.org/abstracts/12184/numerical-iteration-method-to-find-new-formulas-for-nonlinear-equations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12184.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">545</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18956</span> A New Computational Method for the Solution of Nonlinear Burgers' Equation Arising in Longitudinal Dispersion Phenomena in Fluid Flow through Porous Media</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Olayiwola%20Moruf%20Oyedunsi">Olayiwola Moruf Oyedunsi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper discusses the Modified Variational Iteration Method (MVIM) for the solution of nonlinear Burgers’ equation arising in longitudinal dispersion phenomena in fluid flow through porous media. The method is an elegant combination of Taylor’s series and the variational iteration method (VIM). Using Maple 18 for implementation, it is observed that the procedure provides rapidly convergent approximation with less computational efforts. The result shows that the concentration C(x,t) of the contaminated water decreases as distance x increases for the given time t. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=modified%20variational%20iteration%20method" title="modified variational iteration method">modified variational iteration method</a>, <a href="https://publications.waset.org/abstracts/search?q=Burger%E2%80%99s%20equation" title=" Burger’s equation"> Burger’s equation</a>, <a href="https://publications.waset.org/abstracts/search?q=porous%20media" title=" porous media"> porous media</a>, <a href="https://publications.waset.org/abstracts/search?q=partial%20differential%20equation" title=" partial differential equation"> partial differential equation</a> </p> <a href="https://publications.waset.org/abstracts/44343/a-new-computational-method-for-the-solution-of-nonlinear-burgers-equation-arising-in-longitudinal-dispersion-phenomena-in-fluid-flow-through-porous-media" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44343.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">321</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18955</span> Multiscale Simulation of Ink Seepage into Fibrous Structures through a Mesoscopic Variational Model </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Athmane%20Bakhta">Athmane Bakhta</a>, <a href="https://publications.waset.org/abstracts/search?q=Sebastien%20Leclaire"> Sebastien Leclaire</a>, <a href="https://publications.waset.org/abstracts/search?q=David%20Vidal"> David Vidal</a>, <a href="https://publications.waset.org/abstracts/search?q=Francois%20Bertrand"> Francois Bertrand</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Cheriet"> Mohamed Cheriet</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work presents a new three-dimensional variational model proposed for the simulation of ink seepage into paper sheets at the fiber level. The model, inspired by the Hising model, takes into account a finite volume of ink and describes the system state through gravity, cohesion, and adhesion force interactions. At the mesoscopic scale, the paper substrate is modeled using a discretized fiber structure generated using a numerical deposition procedure. A modified Monte Carlo method is introduced for the simulation of the ink dynamics. Besides, a multiphase lattice Boltzmann method is suggested to fine-tune the mesoscopic variational model parameters, and it is shown that the ink seepage behaviors predicted by the proposed model can resemble those predicted by a method relying on first principles. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fibrous%20media" title="fibrous media">fibrous media</a>, <a href="https://publications.waset.org/abstracts/search?q=lattice%20Boltzmann" title=" lattice Boltzmann"> lattice Boltzmann</a>, <a href="https://publications.waset.org/abstracts/search?q=modelling%20and%20simulation" title=" modelling and simulation"> modelling and simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo" title=" Monte Carlo"> Monte Carlo</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20model" title=" variational model"> variational model</a> </p> <a href="https://publications.waset.org/abstracts/129077/multiscale-simulation-of-ink-seepage-into-fibrous-structures-through-a-mesoscopic-variational-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/129077.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">147</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18954</span> Approximations of Fractional Derivatives and Its Applications in Solving Non-Linear Fractional Variational Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Harendra%20Singh">Harendra Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Rajesh%20Pandey"> Rajesh Pandey</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper presents a numerical method based on operational matrix of integration and Ryleigh method for the solution of a class of non-linear fractional variational problems (NLFVPs). Chebyshev first kind polynomials are used for the construction of operational matrix. Using operational matrix and Ryleigh method the NLFVP is converted into a system of non-linear algebraic equations, and solving these equations we obtained approximate solution for NLFVPs. Convergence analysis of the proposed method is provided. Numerical experiment is done to show the applicability of the proposed numerical method. The obtained numerical results are compared with exact solution and solution obtained from Chebyshev third kind. Further the results are shown graphically for different fractional order involved in the problems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=non-linear%20fractional%20variational%20problems" title="non-linear fractional variational problems">non-linear fractional variational problems</a>, <a href="https://publications.waset.org/abstracts/search?q=Rayleigh-Ritz%20method" title=" Rayleigh-Ritz method"> Rayleigh-Ritz method</a>, <a href="https://publications.waset.org/abstracts/search?q=convergence%20analysis" title=" convergence analysis"> convergence analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=error%20analysis" title=" error analysis"> error analysis</a> </p> <a href="https://publications.waset.org/abstracts/57497/approximations-of-fractional-derivatives-and-its-applications-in-solving-non-linear-fractional-variational-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57497.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">298</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18953</span> A Study on the Solutions of the 2-Dimensional and Forth-Order Partial Differential Equations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=O.%20Acan">O. Acan</a>, <a href="https://publications.waset.org/abstracts/search?q=Y.%20Keskin"> Y. Keskin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, we will carry out a comparative study between the reduced differential transform method, the adomian decomposition method, the variational iteration method and the homotopy analysis method. These methods are used in many fields of engineering. This is been achieved by handling a kind of 2-Dimensional and forth-order partial differential equations called the Kuramoto–Sivashinsky equations. Three numerical examples have also been carried out to validate and demonstrate efficiency of the four methods. Furthermost, it is shown that the reduced differential transform method has advantage over other methods. This method is very effective and simple and could be applied for nonlinear problems which used in engineering. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reduced%20differential%20transform%20method" title="reduced differential transform method">reduced differential transform method</a>, <a href="https://publications.waset.org/abstracts/search?q=adomian%20decomposition%20method" title=" adomian decomposition method"> adomian decomposition method</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20iteration%20method" title=" variational iteration method"> variational iteration method</a>, <a href="https://publications.waset.org/abstracts/search?q=homotopy%20analysis%20method" title=" homotopy analysis method"> homotopy analysis method</a> </p> <a href="https://publications.waset.org/abstracts/17555/a-study-on-the-solutions-of-the-2-dimensional-and-forth-order-partial-differential-equations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17555.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">433</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18952</span> Human Action Recognition Using Variational Bayesian HMM with Dirichlet Process Mixture of Gaussian Wishart Emission Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wanhyun%20Cho">Wanhyun Cho</a>, <a href="https://publications.waset.org/abstracts/search?q=Soonja%20Kang"> Soonja Kang</a>, <a href="https://publications.waset.org/abstracts/search?q=Sangkyoon%20Kim"> Sangkyoon Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Soonyoung%20Park"> Soonyoung Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=human%20action%20recognition" title="human action recognition">human action recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=Bayesian%20HMM" title=" Bayesian HMM"> Bayesian HMM</a>, <a href="https://publications.waset.org/abstracts/search?q=Dirichlet%20process%20mixture%20model" title=" Dirichlet process mixture model"> Dirichlet process mixture model</a>, <a href="https://publications.waset.org/abstracts/search?q=Gaussian-Wishart%20emission%20model" title=" Gaussian-Wishart emission model"> Gaussian-Wishart emission model</a>, <a href="https://publications.waset.org/abstracts/search?q=Variational%20Bayesian%20inference" title=" Variational Bayesian inference"> Variational Bayesian inference</a>, <a href="https://publications.waset.org/abstracts/search?q=prior%20distribution%20and%20approximate%20posterior%20distribution" title=" prior distribution and approximate posterior distribution"> prior distribution and approximate posterior distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=KTH%20dataset" title=" KTH dataset"> KTH dataset</a> </p> <a href="https://publications.waset.org/abstracts/49713/human-action-recognition-using-variational-bayesian-hmm-with-dirichlet-process-mixture-of-gaussian-wishart-emission-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49713.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">353</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18951</span> Short-Term Load Forecasting Based on Variational Mode Decomposition and Least Square Support Vector Machine</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jiangyong%20Liu">Jiangyong Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiangxiang%20Xu"> Xiangxiang Xu</a>, <a href="https://publications.waset.org/abstracts/search?q=Bote%20Luo"> Bote Luo</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaoxue%20Luo"> Xiaoxue Luo</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiang%20Zhu"> Jiang Zhu</a>, <a href="https://publications.waset.org/abstracts/search?q=Lingzhi%20Yi"> Lingzhi Yi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To address the problems of non-linearity and high randomness of the original power load sequence causing the degradation of power load forecasting accuracy, a short-term load forecasting method is proposed. The method is based on the Least Square Support Vector Machine optimized by an Improved Sparrow Search Algorithm combined with the Variational Mode Decomposition proposed in this paper. The application of the variational mode decomposition technique decomposes the raw power load data into a series of Intrinsic Mode Functions components, which can reduce the complexity and instability of the raw data while overcoming modal confounding; the proposed improved sparrow search algorithm can solve the problem of difficult selection of learning parameters in the least Square Support Vector Machine. Finally, through comparison experiments, the results show that the method can effectively improve prediction accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=load%20forecasting" title="load forecasting">load forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20mode%20decomposition" title=" variational mode decomposition"> variational mode decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=improved%20sparrow%20search%20algorithm" title=" improved sparrow search algorithm"> improved sparrow search algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20square%20support%20vector%20machine" title=" least square support vector machine"> least square support vector machine</a> </p> <a href="https://publications.waset.org/abstracts/170283/short-term-load-forecasting-based-on-variational-mode-decomposition-and-least-square-support-vector-machine" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170283.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">108</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18950</span> Vibration of a Beam on an Elastic Foundation Using the Variational Iteration Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Desmond%20Adair">Desmond Adair</a>, <a href="https://publications.waset.org/abstracts/search?q=Kairat%20Ismailov"> Kairat Ismailov</a>, <a href="https://publications.waset.org/abstracts/search?q=Martin%20Jaeger"> Martin Jaeger</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Modelling of Timoshenko beams on elastic foundations has been widely used in the analysis of buildings, geotechnical problems, and, railway and aerospace structures. For the elastic foundation, the most widely used models are one-parameter mechanical models or two-parameter models to include continuity and cohesion of typical foundations, with the two-parameter usually considered the better of the two. Knowledge of free vibration characteristics of beams on an elastic foundation is considered necessary for optimal design solutions in many engineering applications, and in this work, the efficient and accurate variational iteration method is developed and used to calculate natural frequencies of a Timoshenko beam on a two-parameter foundation. The variational iteration method is a technique capable of dealing with some linear and non-linear problems in an easy and efficient way. The calculations are compared with those using a finite-element method and other analytical solutions, and it is shown that the results are accurate and are obtained efficiently. It is found that the effect of the presence of the two-parameter foundation is to increase the beam’s natural frequencies and this is thought to be because of the shear-layer stiffness, which has an effect on the elastic stiffness. By setting the two-parameter model’s stiffness parameter to zero, it is possible to obtain a one-parameter foundation model, and so, comparison between the two foundation models is also made. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Timoshenko%20beam" title="Timoshenko beam">Timoshenko beam</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20iteration%20method" title=" variational iteration method"> variational iteration method</a>, <a href="https://publications.waset.org/abstracts/search?q=two-parameter%20elastic%20foundation%20model" title=" two-parameter elastic foundation model"> two-parameter elastic foundation model</a> </p> <a href="https://publications.waset.org/abstracts/95779/vibration-of-a-beam-on-an-elastic-foundation-using-the-variational-iteration-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95779.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">194</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18949</span> Further Results on Modified Variational Iteration Method for the Analytical Solution of Nonlinear Advection Equations</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20W.%20Gbolagade">A. W. Gbolagade</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20O.%20Olayiwola"> M. O. Olayiwola</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20O.%20Kareem"> K. O. Kareem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, further to our result on recent paper on the solution of nonlinear advection equations, we present further results on the nonlinear nonhomogeneous advection equations using a modified variational iteration method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=lagrange%20multiplier" title="lagrange multiplier">lagrange multiplier</a>, <a href="https://publications.waset.org/abstracts/search?q=non-homogeneous%20equations" title=" non-homogeneous equations"> non-homogeneous equations</a>, <a href="https://publications.waset.org/abstracts/search?q=advection%20equations" title=" advection equations"> advection equations</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematics" title=" mathematics"> mathematics</a> </p> <a href="https://publications.waset.org/abstracts/3945/further-results-on-modified-variational-iteration-method-for-the-analytical-solution-of-nonlinear-advection-equations" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3945.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">301</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18948</span> Deep learning with Noisy Labels : Learning True Labels as Discrete Latent Variable</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Azeddine%20El-Hassouny">Azeddine El-Hassouny</a>, <a href="https://publications.waset.org/abstracts/search?q=Chandrashekhar%20Meshram"> Chandrashekhar Meshram</a>, <a href="https://publications.waset.org/abstracts/search?q=Geraldin%20Nanfack"> Geraldin Nanfack</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=label%20noise" title="label noise">label noise</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=discrete%20latent%20variable" title=" discrete latent variable"> discrete latent variable</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20inference" title=" variational inference"> variational inference</a>, <a href="https://publications.waset.org/abstracts/search?q=MNIST" title=" MNIST"> MNIST</a>, <a href="https://publications.waset.org/abstracts/search?q=CIFAR32" title=" CIFAR32"> CIFAR32</a> </p> <a href="https://publications.waset.org/abstracts/142809/deep-learning-with-noisy-labels-learning-true-labels-as-discrete-latent-variable" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/142809.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">128</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18947</span> New Variational Approach for Contrast Enhancement of Color Image</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wanhyun%20Cho">Wanhyun Cho</a>, <a href="https://publications.waset.org/abstracts/search?q=Seongchae%20Seo"> Seongchae Seo</a>, <a href="https://publications.waset.org/abstracts/search?q=Soonja%20Kang"> Soonja Kang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, we propose a variational technique for image contrast enhancement which utilizes global and local information around each pixel. The energy functional is defined by a weighted linear combination of three terms which are called on a local, a global contrast term and dispersion term. The first one is a local contrast term that can lead to improve the contrast of an input image by increasing the grey-level differences between each pixel and its neighboring to utilize contextual information around each pixel. The second one is global contrast term, which can lead to enhance a contrast of image by minimizing the difference between its empirical distribution function and a cumulative distribution function to make the probability distribution of pixel values becoming a symmetric distribution about median. The third one is a dispersion term that controls the departure between new pixel value and pixel value of original image while preserving original image characteristics as well as possible. Second, we derive the Euler-Lagrange equation for true image that can achieve the minimum of a proposed functional by using the fundamental lemma for the calculus of variations. And, we considered the procedure that this equation can be solved by using a gradient decent method, which is one of the dynamic approximation techniques. Finally, by conducting various experiments, we can demonstrate that the proposed method can enhance the contrast of colour images better than existing techniques. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=color%20image" title="color image">color image</a>, <a href="https://publications.waset.org/abstracts/search?q=contrast%20enhancement%20technique" title=" contrast enhancement technique"> contrast enhancement technique</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20approach" title=" variational approach"> variational approach</a>, <a href="https://publications.waset.org/abstracts/search?q=Euler-Lagrang%20equation" title=" Euler-Lagrang equation"> Euler-Lagrang equation</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20approximation%20method" title=" dynamic approximation method"> dynamic approximation method</a>, <a href="https://publications.waset.org/abstracts/search?q=EME%20measure" title=" EME measure"> EME measure</a> </p> <a href="https://publications.waset.org/abstracts/10574/new-variational-approach-for-contrast-enhancement-of-color-image" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10574.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">450</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18946</span> Explicit Iterative Scheme for Approximating a Common Solution of Generalized Mixed Equilibrium Problem and Fixed Point Problem for a Nonexpansive Semigroup in Hilbert Space</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Farid">Mohammad Farid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we introduce and study an explicit iterative method based on hybrid extragradient method to approximate a common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup in Hilbert space. Further, we prove that the sequence generated by the proposed iterative scheme converge strongly to the common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup. This common solution is the unique solution of a variational inequality problem and is the optimality condition for a minimization problem. The results presented in this paper are the supplement, extension and generalization of the previously known results in this area. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=generalized%20mixed%20equilibrium%20problem" title="generalized mixed equilibrium problem">generalized mixed equilibrium problem</a>, <a href="https://publications.waset.org/abstracts/search?q=fixed-point%20problem" title=" fixed-point problem"> fixed-point problem</a>, <a href="https://publications.waset.org/abstracts/search?q=nonexpansive%20semigroup" title=" nonexpansive semigroup"> nonexpansive semigroup</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20inequality%20problem" title=" variational inequality problem"> variational inequality problem</a>, <a href="https://publications.waset.org/abstracts/search?q=iterative%20algorithms" title=" iterative algorithms"> iterative algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20extragradient%20method" title=" hybrid extragradient method"> hybrid extragradient method</a> </p> <a href="https://publications.waset.org/abstracts/14070/explicit-iterative-scheme-for-approximating-a-common-solution-of-generalized-mixed-equilibrium-problem-and-fixed-point-problem-for-a-nonexpansive-semigroup-in-hilbert-space" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14070.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">475</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18945</span> Multinomial Dirichlet Gaussian Process Model for Classification of Multidimensional Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wanhyun%20Cho">Wanhyun Cho</a>, <a href="https://publications.waset.org/abstracts/search?q=Soonja%20Kang"> Soonja Kang</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanggoon%20Kim"> Sanggoon Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Soonyoung%20Park"> Soonyoung Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered an efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multinomial%20dirichlet%20classification%20model" title="multinomial dirichlet classification model">multinomial dirichlet classification model</a>, <a href="https://publications.waset.org/abstracts/search?q=Gaussian%20process%20priors" title=" Gaussian process priors"> Gaussian process priors</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20Bayesian%20approximation" title=" variational Bayesian approximation"> variational Bayesian approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=importance%20sampling" title=" importance sampling"> importance sampling</a>, <a href="https://publications.waset.org/abstracts/search?q=approximate%20posterior%20distribution" title=" approximate posterior distribution"> approximate posterior distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=marginal%20likelihood%20evidence" title=" marginal likelihood evidence"> marginal likelihood evidence</a> </p> <a href="https://publications.waset.org/abstracts/33816/multinomial-dirichlet-gaussian-process-model-for-classification-of-multidimensional-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33816.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">444</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18944</span> Numerical Pricing of Financial Options under Irrational Exercise Times and Regime-Switching Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Saber%20Rohi">Mohammad Saber Rohi</a>, <a href="https://publications.waset.org/abstracts/search?q=Saghar%20Heidari"> Saghar Heidari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we studied the pricing problem of American options under a regime-switching model with the possibility of a non-optimal exercise policy (early or late exercise time) which is called an irrational strategy. For this, we consider a Markovmodulated model for the dynamic of the underlying asset as an alternative model to the classical Balck-Scholes-Merton model (BSM) and an intensity-based model for the irrational strategy, to provide more realistic results for American option prices under the irrational behavior in real financial markets. Applying a partial differential equation (PDE) approach, the pricing problem of American options under regime-switching models can be formulated as coupled PDEs. To solve the resulting systems of PDEs in this model, we apply a finite element method as the numerical solving procedure to the resulting variational inequality. Under some appropriate assumptions, we establish the stability of the method and compare its accuracy to some recent works to illustrate the suitability of the proposed model and the accuracy of the applied numerical method for the pricing problem of American options under the regime-switching model with irrational behaviors. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=irrational%20exercise%20strategy" title="irrational exercise strategy">irrational exercise strategy</a>, <a href="https://publications.waset.org/abstracts/search?q=rationality%20parameter" title=" rationality parameter"> rationality parameter</a>, <a href="https://publications.waset.org/abstracts/search?q=regime-switching%20model" title=" regime-switching model"> regime-switching model</a>, <a href="https://publications.waset.org/abstracts/search?q=American%20option" title=" American option"> American option</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20element%20method" title=" finite element method"> finite element method</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20inequality" title=" variational inequality"> variational inequality</a> </p> <a href="https://publications.waset.org/abstracts/160801/numerical-pricing-of-financial-options-under-irrational-exercise-times-and-regime-switching-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160801.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">73</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18943</span> A Deep Learning Based Method for Faster 3D Structural Topology Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arya%20Prakash%20Padhi">Arya Prakash Padhi</a>, <a href="https://publications.waset.org/abstracts/search?q=Anupam%20Chakrabarti"> Anupam Chakrabarti</a>, <a href="https://publications.waset.org/abstracts/search?q=Rajib%20Chowdhury"> Rajib Chowdhury</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Topology or layout optimization often gives better performing economic structures and is very helpful in the conceptual design phase. But traditionally it is being done in finite element-based optimization schemes which, although gives a good result, is very time-consuming especially in 3D structures. Among other alternatives machine learning, especially deep learning-based methods, have a very good potential in resolving this computational issue. Here convolutional neural network (3D-CNN) based variational auto encoder (VAE) is trained using a dataset generated from commercially available topology optimization code ABAQUS Tosca using solid isotropic material with penalization (SIMP) method for compliance minimization. The encoded data in latent space is then fed to a 3D generative adversarial network (3D-GAN) to generate the outcome in 64x64x64 size. Here the network consists of 3D volumetric CNN with rectified linear unit (ReLU) activation in between and sigmoid activation in the end. The proposed network is seen to provide almost optimal results with significantly reduced computational time, as there is no iteration involved. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=3D%20generative%20adversarial%20network" title="3D generative adversarial network">3D generative adversarial network</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20topology%20optimization" title=" structural topology optimization"> structural topology optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20auto%20encoder" title=" variational auto encoder"> variational auto encoder</a> </p> <a href="https://publications.waset.org/abstracts/110331/a-deep-learning-based-method-for-faster-3d-structural-topology-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110331.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">174</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18942</span> Large Amplitude Free Vibration of a Very Sag Marine Cable</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=O.%20Punjarat">O. Punjarat</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Chucheepsakul"> S. Chucheepsakul</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Phanyasahachart"> T. Phanyasahachart</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper focuses on a variational formulation of large amplitude free vibration behavior of a very sag marine cable. In the static equilibrium state, the marine cable has a very large sag configuration. In the motion state, the marine cable is assumed to vibrate in in-plane motion with large amplitude from the static equilibrium position. The total virtual work-energy of the marine cable at the dynamic state is formulated which involves the virtual strain energy due to axial deformation, the virtual work done by effective weight, and the inertia forces. The equations of motion for the large amplitude free vibration of marine cable are obtained by taking into account the difference between the Euler’s equation in the static state and the displaced state. Based on the Galerkin finite element procedure, the linear and nonlinear stiffness matrices, and mass matrices of the marine cable are obtained and the eigenvalue problem is solved. The natural frequency spectrum and the large amplitude free vibration behavior of marine cable are presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=axial%20deformation" title="axial deformation">axial deformation</a>, <a href="https://publications.waset.org/abstracts/search?q=free%20vibration" title=" free vibration"> free vibration</a>, <a href="https://publications.waset.org/abstracts/search?q=Galerkin%20finite%20element%20method" title=" Galerkin finite element method"> Galerkin finite element method</a>, <a href="https://publications.waset.org/abstracts/search?q=large%20amplitude" title=" large amplitude"> large amplitude</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20method" title=" variational method"> variational method</a> </p> <a href="https://publications.waset.org/abstracts/114132/large-amplitude-free-vibration-of-a-very-sag-marine-cable" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/114132.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">254</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18941</span> Anisotropic Approach for Discontinuity Preserving in Optical Flow Estimation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pushpendra%20Kumar">Pushpendra Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Sanjeev%20Kumar"> Sanjeev Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Balasubramanian"> R. Balasubramanian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Estimation of optical flow from a sequence of images using variational methods is one of the most successful approach. Discontinuity between different motions is one of the challenging problem in flow estimation. In this paper, we design a new anisotropic diffusion operator, which is able to provide smooth flow over a region and efficiently preserve discontinuity in optical flow. This operator is designed on the basis of intensity differences of the pixels and isotropic operator using exponential function. The combination of these are used to control the propagation of flow. Experimental results on the different datasets verify the robustness and accuracy of the algorithm and also validate the effect of anisotropic operator in the discontinuity preserving. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optical%20flow" title="optical flow">optical flow</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20methods" title=" variational methods"> variational methods</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20vision" title=" computer vision"> computer vision</a>, <a href="https://publications.waset.org/abstracts/search?q=anisotropic%20operator" title=" anisotropic operator"> anisotropic operator</a> </p> <a href="https://publications.waset.org/abstracts/20827/anisotropic-approach-for-discontinuity-preserving-in-optical-flow-estimation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20827.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">873</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18940</span> Specification and Unification of All Fundamental Forces Exist in Universe in the Theoretical Perspective – The Universal Mechanics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Surendra%20Mund">Surendra Mund</a> </p> <p class="card-text"><strong>Abstract:</strong></p> At the beginning, the physical entity force was defined mathematically by Sir Isaac Newton in his Principia Mathematica as F ⃗=(dp ⃗)/dt in form of his second law of motion. Newton also defines his Universal law of Gravitational force exist in same outstanding book, but at the end of 20th century and beginning of 21st century, we have tried a lot to specify and unify four or five Fundamental forces or Interaction exist in universe, but we failed every time. Usually, Gravity creates problems in this unification every single time, but in my previous papers and presentations, I defined and derived Field and force equations for Gravitational like Interactions for each and every kind of central systems. This force is named as Variational Force by me, and this force is generated by variation in the scalar field density around the body. In this particular paper, at first, I am specifying which type of Interactions are Fundamental in Universal sense (or in all type of central systems or bodies predicted by my N-time Inflationary Model of Universe) and then unify them in Universal framework (defined and derived by me as Universal Mechanics in a separate paper) as well. This will also be valid in Universal dynamical sense which includes inflations and deflations of universe, central system relativity, Universal relativity, ϕ-ψ transformation and transformation of spin, physical perception principle, Generalized Fundamental Dynamical Law and many other important Generalized Principles of Generalized Quantum Mechanics (GQM) and Central System Theory (CST). So, In this article, at first, I am Generalizing some Fundamental Principles, and then Unifying Variational Forces (General form of Gravitation like Interactions) and Flow Generated Force (General form of EM like Interactions), and then Unify all Fundamental Forces by specifying Weak and Strong Interactions in form of more basic terms - Variational, Flow Generated and Transformational Interactions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Central%20System%20Force" title="Central System Force">Central System Force</a>, <a href="https://publications.waset.org/abstracts/search?q=Disturbance%20Force" title=" Disturbance Force"> Disturbance Force</a>, <a href="https://publications.waset.org/abstracts/search?q=Flow%20Generated%20Forces" title=" Flow Generated Forces"> Flow Generated Forces</a>, <a href="https://publications.waset.org/abstracts/search?q=Generalized%20Nuclear%20Force" title=" Generalized Nuclear Force"> Generalized Nuclear Force</a>, <a href="https://publications.waset.org/abstracts/search?q=Generalized%20Weak%20Interactions" title=" Generalized Weak Interactions"> Generalized Weak Interactions</a>, <a href="https://publications.waset.org/abstracts/search?q=Generalized%20EM-Like%20Interactions" title=" Generalized EM-Like Interactions"> Generalized EM-Like Interactions</a>, <a href="https://publications.waset.org/abstracts/search?q=Imbalance%20Force" title=" Imbalance Force"> Imbalance Force</a>, <a href="https://publications.waset.org/abstracts/search?q=Spin%20Generated%20Forces" title=" Spin Generated Forces"> Spin Generated Forces</a>, <a href="https://publications.waset.org/abstracts/search?q=Transformation%20Generated%20Force" title=" Transformation Generated Force"> Transformation Generated Force</a>, <a href="https://publications.waset.org/abstracts/search?q=Unified%20Force" title=" Unified Force"> Unified Force</a>, <a href="https://publications.waset.org/abstracts/search?q=Universal%20Mechanics" title=" Universal Mechanics"> Universal Mechanics</a>, <a href="https://publications.waset.org/abstracts/search?q=Uniform%20And%20Non-Uniform%20Variational%20Interactions" title=" Uniform And Non-Uniform Variational Interactions"> Uniform And Non-Uniform Variational Interactions</a>, <a href="https://publications.waset.org/abstracts/search?q=Variational%20Interactions" title=" Variational Interactions"> Variational Interactions</a> </p> <a href="https://publications.waset.org/abstracts/169765/specification-and-unification-of-all-fundamental-forces-exist-in-universe-in-the-theoretical-perspective-the-universal-mechanics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/169765.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">50</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18939</span> Variational Explanation Generator: Generating Explanation for Natural Language Inference Using Variational Auto-Encoder</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhen%20Cheng">Zhen Cheng</a>, <a href="https://publications.waset.org/abstracts/search?q=Xinyu%20Dai"> Xinyu Dai</a>, <a href="https://publications.waset.org/abstracts/search?q=Shujian%20Huang"> Shujian Huang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiajun%20Chen"> Jiajun Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recently, explanatory natural language inference has attracted much attention for the interpretability of logic relationship prediction, which is also known as explanation generation for Natural Language Inference (NLI). Existing explanation generators based on discriminative Encoder-Decoder architecture have achieved noticeable results. However, we find that these discriminative generators usually generate explanations with correct evidence but incorrect logic semantic. It is due to that logic information is implicitly encoded in the premise-hypothesis pairs and difficult to model. Actually, logic information identically exists between premise-hypothesis pair and explanation. And it is easy to extract logic information that is explicitly contained in the target explanation. Hence we assume that there exists a latent space of logic information while generating explanations. Specifically, we propose a generative model called Variational Explanation Generator (VariationalEG) with a latent variable to model this space. Training with the guide of explicit logic information in target explanations, latent variable in VariationalEG could capture the implicit logic information in premise-hypothesis pairs effectively. Additionally, to tackle the problem of posterior collapse while training VariaztionalEG, we propose a simple yet effective approach called Logic Supervision on the latent variable to force it to encode logic information. Experiments on explanation generation benchmark—explanation-Stanford Natural Language Inference (e-SNLI) demonstrate that the proposed VariationalEG achieves significant improvement compared to previous studies and yields a state-of-the-art result. Furthermore, we perform the analysis of generated explanations to demonstrate the effect of the latent variable. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20inference" title="natural language inference">natural language inference</a>, <a href="https://publications.waset.org/abstracts/search?q=explanation%20generation" title=" explanation generation"> explanation generation</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20auto-encoder" title=" variational auto-encoder"> variational auto-encoder</a>, <a href="https://publications.waset.org/abstracts/search?q=generative%20model" title=" generative model"> generative model</a> </p> <a href="https://publications.waset.org/abstracts/126633/variational-explanation-generator-generating-explanation-for-natural-language-inference-using-variational-auto-encoder" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/126633.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">151</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18938</span> Self-Action Effects of a Non-Gaussian Laser Beam Through Plasma </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sandeep%20Kumar">Sandeep Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Naveen%20Gupta"> Naveen Gupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The propagation of the Non-Gaussian laser beam results in strong self-focusing as compare to the Gaussian laser beam, which helps to achieve a prerequisite of the plasma-based electron, Terahertz generation, and higher harmonic generations. The theoretical investigation on the evolution of non-Gaussian laser beam through the collisional plasma with ramped density has been presented. The non-uniform irradiance over the cross-section of the laser beam results in redistribution of the carriers that modifies the optical response of the plasma in such a way that the plasma behaves like a converging lens to the laser beam. The formulation is based on finding a semi-analytical solution of the nonlinear Schrodinger wave equation (NLSE) with the help of variational theory. It has been observed that the decentred parameter ‘q’ of laser and wavenumber of ripples of medium contribute to providing the required conditions for the improvement of self-focusing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=non-Gaussian%20beam" title="non-Gaussian beam">non-Gaussian beam</a>, <a href="https://publications.waset.org/abstracts/search?q=collisional%20plasma" title=" collisional plasma"> collisional plasma</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20theory" title=" variational theory"> variational theory</a>, <a href="https://publications.waset.org/abstracts/search?q=self-focusing" title=" self-focusing"> self-focusing</a> </p> <a href="https://publications.waset.org/abstracts/124754/self-action-effects-of-a-non-gaussian-laser-beam-through-plasma" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/124754.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">195</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18937</span> F-VarNet: Fast Variational Network for MRI Reconstruction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Omer%20Cahana">Omer Cahana</a>, <a href="https://publications.waset.org/abstracts/search?q=Maya%20Herman"> Maya Herman</a>, <a href="https://publications.waset.org/abstracts/search?q=Ofer%20Levi"> Ofer Levi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Magnetic resonance imaging (MRI) is a long medical scan that stems from a long acquisition time. This length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach, such as compress sensing (CS) or parallel imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. In order to achieve that, two properties have to exist: i) the signal must be sparse under a known transform domain, ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm needs to be applied to recover the signal. While the rapid advance in the deep learning (DL) field, which has demonstrated tremendous successes in various computer vision task’s, the field of MRI reconstruction is still in an early stage. In this paper, we present an extension of the state-of-the-art model in MRI reconstruction -VarNet. We utilize VarNet by using dilated convolution in different scales, which extends the receptive field to capture more contextual information. Moreover, we simplified the sensitivity map estimation (SME), for it holds many unnecessary layers for this task. Those improvements have shown significant decreases in computation costs as well as higher accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=MRI" title="MRI">MRI</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title=" deep learning"> deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20network" title=" variational network"> variational network</a>, <a href="https://publications.waset.org/abstracts/search?q=computer%20vision" title=" computer vision"> computer vision</a>, <a href="https://publications.waset.org/abstracts/search?q=compress%20sensing" title=" compress sensing"> compress sensing</a> </p> <a href="https://publications.waset.org/abstracts/145519/f-varnet-fast-variational-network-for-mri-reconstruction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145519.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">162</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18936</span> Solving Optimal Control of Semilinear Elliptic Variational Inequalities Obstacle Problems using Smoothing Functions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=El%20Hassene%20Osmani">El Hassene Osmani</a>, <a href="https://publications.waset.org/abstracts/search?q=Mounir%20Haddou"> Mounir Haddou</a>, <a href="https://publications.waset.org/abstracts/search?q=Naceurdine%20Bensalem"> Naceurdine Bensalem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we investigate optimal control problems governed by semilinear elliptic variational inequalities involving constraints on the state, and more precisely, the obstacle problem. We present a relaxed formulation for the problem using smoothing functions. Since we adopt a numerical point of view, we first relax the feasible domain of the problem, then using both mathematical programming methods and penalization methods, we get optimality conditions with smooth Lagrange multipliers. Some numerical experiments using IPOPT algorithm (Interior Point Optimizer) are presented to verify the efficiency of our approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=complementarity%20problem" title="complementarity problem">complementarity problem</a>, <a href="https://publications.waset.org/abstracts/search?q=IPOPT" title=" IPOPT"> IPOPT</a>, <a href="https://publications.waset.org/abstracts/search?q=Lagrange%20multipliers" title=" Lagrange multipliers"> Lagrange multipliers</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%20programming" title=" mathematical programming"> mathematical programming</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20control" title=" optimal control"> optimal control</a>, <a href="https://publications.waset.org/abstracts/search?q=smoothing%20methods" title=" smoothing methods"> smoothing methods</a>, <a href="https://publications.waset.org/abstracts/search?q=variationally%20inequalities" title=" variationally inequalities"> variationally inequalities</a> </p> <a href="https://publications.waset.org/abstracts/132882/solving-optimal-control-of-semilinear-elliptic-variational-inequalities-obstacle-problems-using-smoothing-functions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132882.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">173</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18935</span> Homogenization of a Non-Linear Problem with a Thermal Barrier</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hassan%20Samadi">Hassan Samadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mustapha%20El%20Jarroudi"> Mustapha El Jarroudi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, we consider the homogenization of a non-linear problem in periodic medium with two periodic connected media exchanging a heat flux throughout their common interface. The interfacial exchange coefficient λ is assumed to tend to zero or to infinity following a rate λ=λ(ε) when the size ε of the basic cell tends to zero. Three homogenized problems are determined according to some critical value depending of λ and ε. Our method is based on Γ-Convergence techniques. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=variational%20methods" title="variational methods">variational methods</a>, <a href="https://publications.waset.org/abstracts/search?q=epiconvergence" title=" epiconvergence"> epiconvergence</a>, <a href="https://publications.waset.org/abstracts/search?q=homogenization" title=" homogenization"> homogenization</a>, <a href="https://publications.waset.org/abstracts/search?q=convergence%20technique" title=" convergence technique"> convergence technique</a> </p> <a href="https://publications.waset.org/abstracts/29054/homogenization-of-a-non-linear-problem-with-a-thermal-barrier" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29054.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">525</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18934</span> A Parallel Approach for 3D-Variational Data Assimilation on GPUs in Ocean Circulation Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rossella%20Arcucci">Rossella Arcucci</a>, <a href="https://publications.waset.org/abstracts/search?q=Luisa%20D%27Amore"> Luisa D'Amore</a>, <a href="https://publications.waset.org/abstracts/search?q=Simone%20Celestino"> Simone Celestino</a>, <a href="https://publications.waset.org/abstracts/search?q=Giuseppe%20Scotti"> Giuseppe Scotti</a>, <a href="https://publications.waset.org/abstracts/search?q=Giuliano%20Laccetti"> Giuliano Laccetti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work is the first dowel in a rather wide research activity in collaboration with Euro Mediterranean Center for Climate Changes, aimed at introducing scalable approaches in Ocean Circulation Models. We discuss designing and implementation of a parallel algorithm for solving the Variational Data Assimilation (DA) problem on Graphics Processing Units (GPUs). The algorithm is based on the fully scalable 3DVar DA model, previously proposed by the authors, which uses a Domain Decomposition approach (we refer to this model as the DD-DA model). We proceed with an incremental porting process consisting of 3 distinct stages: requirements and source code analysis, incremental development of CUDA kernels, testing and optimization. Experiments confirm the theoretic performance analysis based on the so-called scale up factor demonstrating that the DD-DA model can be suitably mapped on GPU architectures. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20assimilation" title="data assimilation">data assimilation</a>, <a href="https://publications.waset.org/abstracts/search?q=GPU%20architectures" title=" GPU architectures"> GPU architectures</a>, <a href="https://publications.waset.org/abstracts/search?q=ocean%20models" title=" ocean models"> ocean models</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20algorithm" title=" parallel algorithm"> parallel algorithm</a> </p> <a href="https://publications.waset.org/abstracts/29397/a-parallel-approach-for-3d-variational-data-assimilation-on-gpus-in-ocean-circulation-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29397.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">412</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18933</span> Pricing European Continuous-Installment Options under Regime-Switching Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saghar%20Heidari">Saghar Heidari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we study the valuation problem of European continuous-installment options under Markov-modulated models with a partial differential equation approach. Due to the opportunity for continuing or stopping to pay installments, the valuation problem under regime-switching models can be formulated as coupled partial differential equations (CPDE) with free boundary features. To value the installment options, we express the truncated CPDE as a linear complementarity problem (LCP), then a finite element method is proposed to solve the resulted variational inequality. Under some appropriate assumptions, we establish the stability of the method and illustrate some numerical results to examine the rate of convergence and accuracy of the proposed method for the pricing problem under the regime-switching model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=continuous-installment%20option" title="continuous-installment option">continuous-installment option</a>, <a href="https://publications.waset.org/abstracts/search?q=European%20option" title=" European option"> European option</a>, <a href="https://publications.waset.org/abstracts/search?q=regime-switching%20model" title=" regime-switching model"> regime-switching model</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20element%20method" title=" finite element method"> finite element method</a> </p> <a href="https://publications.waset.org/abstracts/130909/pricing-european-continuous-installment-options-under-regime-switching-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/130909.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">137</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18932</span> Effects of Two Cross Focused Intense Laser Beams On THz Generation in Rippled Plasma</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sandeep%20Kumar">Sandeep Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Naveen%20Gupta"> Naveen Gupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Terahertz (THz) generation has been investigated by beating two cosh-Gaussian laser beams of the same amplitude but different wavenumbers and frequencies through rippled collisionless plasma. The ponderomotive force is operative which is induced due to the intensity gradient of the laser beam over the cross-section area of the wavefront. The electrons evacuate towards a low-intensity regime, which modifies the dielectric function of the medium and results in cross focusing of cosh-Gaussian laser beams. The evolution of spot size of laser beams has been studied by solving nonlinear Schrodinger wave equation (NLSE) with variational technique. The laser beams impart oscillations to electrons which are enhanced with ripple density. The nonlinear oscillatory motion of electrons gives rise to a nonlinear current density driving THz radiation. It has been observed that the periodicity of the ripple density helps to enhance the THz radiation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=rippled%20collisionless%20plasma" title="rippled collisionless plasma">rippled collisionless plasma</a>, <a href="https://publications.waset.org/abstracts/search?q=cosh-gaussian%20laser%20beam" title=" cosh-gaussian laser beam"> cosh-gaussian laser beam</a>, <a href="https://publications.waset.org/abstracts/search?q=ponderomotive%20force" title=" ponderomotive force"> ponderomotive force</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20technique" title=" variational technique"> variational technique</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20current%20density" title=" nonlinear current density"> nonlinear current density</a> </p> <a href="https://publications.waset.org/abstracts/139951/effects-of-two-cross-focused-intense-laser-beams-on-thz-generation-in-rippled-plasma" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/139951.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">201</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18931</span> Deep Reinforcement Learning Model Using Parameterised Quantum Circuits</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lokes%20Parvatha%20Kumaran%20S.">Lokes Parvatha Kumaran S.</a>, <a href="https://publications.waset.org/abstracts/search?q=Sakthi%20Jay%20Mahenthar%20C."> Sakthi Jay Mahenthar C.</a>, <a href="https://publications.waset.org/abstracts/search?q=Sathyaprakash%20P."> Sathyaprakash P.</a>, <a href="https://publications.waset.org/abstracts/search?q=Jayakumar%20V."> Jayakumar V.</a>, <a href="https://publications.waset.org/abstracts/search?q=Shobanadevi%20A."> Shobanadevi A.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the evolution of technology, the need to solve complex computational problems like machine learning and deep learning has shot up. But even the most powerful classical supercomputers find it difficult to execute these tasks. With the recent development of quantum computing, researchers and tech-giants strive for new quantum circuits for machine learning tasks, as present works on Quantum Machine Learning (QML) ensure less memory consumption and reduced model parameters. But it is strenuous to simulate classical deep learning models on existing quantum computing platforms due to the inflexibility of deep quantum circuits. As a consequence, it is essential to design viable quantum algorithms for QML for noisy intermediate-scale quantum (NISQ) devices. The proposed work aims to explore Variational Quantum Circuits (VQC) for Deep Reinforcement Learning by remodeling the experience replay and target network into a representation of VQC. In addition, to reduce the number of model parameters, quantum information encoding schemes are used to achieve better results than the classical neural networks. VQCs are employed to approximate the deep Q-value function for decision-making and policy-selection reinforcement learning with experience replay and the target network. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quantum%20computing" title="quantum computing">quantum computing</a>, <a href="https://publications.waset.org/abstracts/search?q=quantum%20machine%20learning" title=" quantum machine learning"> quantum machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=variational%20quantum%20circuit" title=" variational quantum circuit"> variational quantum circuit</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20reinforcement%20learning" title=" deep reinforcement learning"> deep reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=quantum%20information%20encoding%20scheme" title=" quantum information encoding scheme"> quantum information encoding scheme</a> </p> <a href="https://publications.waset.org/abstracts/152629/deep-reinforcement-learning-model-using-parameterised-quantum-circuits" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152629.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">134</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=variational%20method&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=variational%20method&page=3">3</a></li> <li class="page-item"><a class="page-link" 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