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method</title> <meta name="description" content="Search results for: bar model method"> <meta name="keywords" content="bar model 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="bar model 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> 31450</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: bar model method</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">31450</span> Reflection on Using Bar Model Method in Learning and Teaching Primary Mathematics: A Hong Kong Case Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chui%20Ka%20Shing">Chui Ka Shing</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This case study research attempts to examine the use of the Bar Model Method approach in learning and teaching mathematics in a primary school in Hong Kong. The objectives of the study are to find out to what extent (a) the Bar Model Method approach enhances the construction of students’ mathematics concepts, and (b) the school-based mathematics curriculum development with adopting the Bar Model Method approach. This case study illuminates the effectiveness of using the Bar Model Method to solve mathematics problems from Primary 1 to Primary 6. Some effective pedagogies and assessments were developed to strengthen the use of the Bar Model Method across year levels. Suggestions including school-based curriculum development for using Bar Model Method and further study were discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bar%20model%20method" title="bar model method">bar model method</a>, <a href="https://publications.waset.org/abstracts/search?q=curriculum%20development" title=" curriculum development"> curriculum development</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematics%20education" title=" mathematics education"> mathematics education</a>, <a href="https://publications.waset.org/abstracts/search?q=problem%20solving" title=" problem solving"> problem solving</a> </p> <a href="https://publications.waset.org/abstracts/138064/reflection-on-using-bar-model-method-in-learning-and-teaching-primary-mathematics-a-hong-kong-case-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/138064.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">219</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">31449</span> A Comparison of Smoothing Spline Method and Penalized Spline Regression Method Based on Nonparametric Regression Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Autcha%20Araveeporn">Autcha Araveeporn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a study about a nonparametric regression model consisting of a smoothing spline method and a penalized spline regression method. We also compare the techniques used for estimation and prediction of nonparametric regression model. We tried both methods with crude oil prices in dollars per barrel and the Stock Exchange of Thailand (SET) index. According to the results, it is concluded that smoothing spline method performs better than that of penalized spline regression method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nonparametric%20regression%20model" title="nonparametric regression model">nonparametric regression model</a>, <a href="https://publications.waset.org/abstracts/search?q=penalized%20spline%20regression%20method" title=" penalized spline regression method"> penalized spline regression method</a>, <a href="https://publications.waset.org/abstracts/search?q=smoothing%20spline%20method" title=" smoothing spline method"> smoothing spline method</a>, <a href="https://publications.waset.org/abstracts/search?q=Stock%20Exchange%20of%20Thailand%20%28SET%29" title=" Stock Exchange of Thailand (SET)"> Stock Exchange of Thailand (SET)</a> </p> <a href="https://publications.waset.org/abstracts/2974/a-comparison-of-smoothing-spline-method-and-penalized-spline-regression-method-based-on-nonparametric-regression-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2974.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">439</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">31448</span> Seat Assignment Model for Student Admissions Process at Saudi Higher Education Institutions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Salem%20Alzahrani">Mohammed Salem Alzahrani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, student admission process is studied to optimize the assignment of vacant seats with three main objectives. Utilizing all vacant seats, satisfying all program of study admission requirements and maintaining fairness among all candidates are the three main objectives of the optimization model. Seat Assignment Method (SAM) is used to build the model and solve the optimization problem with help of Northwest Coroner Method and Least Cost Method. A closed formula is derived for applying the priority of assigning seat to candidate based on SAM. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=admission%20process%20model" title="admission process model">admission process model</a>, <a href="https://publications.waset.org/abstracts/search?q=assignment%20problem" title=" assignment problem"> assignment problem</a>, <a href="https://publications.waset.org/abstracts/search?q=Hungarian%20Method" title=" Hungarian Method"> Hungarian Method</a>, <a href="https://publications.waset.org/abstracts/search?q=Least%20Cost%20Method" title=" Least Cost Method"> Least Cost Method</a>, <a href="https://publications.waset.org/abstracts/search?q=Northwest%20Corner%20Method" title=" Northwest Corner Method"> Northwest Corner Method</a>, <a href="https://publications.waset.org/abstracts/search?q=SAM" title=" SAM"> SAM</a> </p> <a href="https://publications.waset.org/abstracts/13925/seat-assignment-model-for-student-admissions-process-at-saudi-higher-education-institutions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13925.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">498</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">31447</span> Method of Parameter Calibration for Error Term in Stochastic User Equilibrium Traffic Assignment Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xiang%20Zhang">Xiang Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=David%20Rey"> David Rey</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Travis%20Waller"> S. Travis Waller</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Stochastic User Equilibrium (SUE) model is a widely used traffic assignment model in transportation planning, which is regarded more advanced than Deterministic User Equilibrium (DUE) model. However, a problem exists that the performance of the SUE model depends on its error term parameter. The objective of this paper is to propose a systematic method of determining the appropriate error term parameter value for the SUE model. First, the significance of the parameter is explored through a numerical example. Second, the parameter calibration method is developed based on the Logit-based route choice model. The calibration process is realized through multiple nonlinear regression, using sequential quadratic programming combined with least square method. Finally, case analysis is conducted to demonstrate the application of the calibration process and validate the better performance of the SUE model calibrated by the proposed method compared to the SUE models under other parameter values and the DUE model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=parameter%20calibration" title="parameter calibration">parameter calibration</a>, <a href="https://publications.waset.org/abstracts/search?q=sequential%20quadratic%20programming" title=" sequential quadratic programming"> sequential quadratic programming</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20user%20equilibrium" title=" stochastic user equilibrium"> stochastic user equilibrium</a>, <a href="https://publications.waset.org/abstracts/search?q=traffic%20assignment" title=" traffic assignment"> traffic assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=transportation%20planning" title=" transportation planning"> transportation planning</a> </p> <a href="https://publications.waset.org/abstracts/17091/method-of-parameter-calibration-for-error-term-in-stochastic-user-equilibrium-traffic-assignment-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17091.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">299</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">31446</span> QoS-CBMG: A Model for e-Commerce Customer Behavior</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hoda%20Ghavamipoor">Hoda Ghavamipoor</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Alireza%20Hashemi%20Golpayegani"> S. Alireza Hashemi Golpayegani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=customer%20behavior%20model" title="customer behavior model">customer behavior model</a>, <a href="https://publications.waset.org/abstracts/search?q=electronic%20commerce" title=" electronic commerce"> electronic commerce</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20of%20service" title=" quality of service"> quality of service</a>, <a href="https://publications.waset.org/abstracts/search?q=customer%20behavior%20model%20graph" title=" customer behavior model graph"> customer behavior model graph</a>, <a href="https://publications.waset.org/abstracts/search?q=process%20mining" title=" process mining"> process mining</a> </p> <a href="https://publications.waset.org/abstracts/41945/qos-cbmg-a-model-for-e-commerce-customer-behavior" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41945.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">416</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">31445</span> The Use of Stochastic Gradient Boosting Method for Multi-Model Combination of Rainfall-Runoff Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Phanida%20Phukoetphim">Phanida Phukoetphim</a>, <a href="https://publications.waset.org/abstracts/search?q=Asaad%20Y.%20Shamseldin"> Asaad Y. Shamseldin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, the novel Stochastic Gradient Boosting (SGB) combination method is addressed for producing daily river flows from four different rain-runoff models of Ohinemuri catchment, New Zealand. The selected rainfall-runoff models are two empirical black-box models: linear perturbation model and linear varying gain factor model, two conceptual models: soil moisture accounting and routing model and Nedbør-Afrstrømnings model. In this study, the simple average combination method and the weighted average combination method were used as a benchmark for comparing the results of the novel SGB combination method. The models and combination results are evaluated using statistical and graphical criteria. Overall results of this study show that the use of combination technique can certainly improve the simulated river flows of four selected models for Ohinemuri catchment, New Zealand. The results also indicate that the novel SGB combination method is capable of accurate prediction when used in a combination method of the simulated river flows in New Zealand. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multi-model%20combination" title="multi-model combination">multi-model combination</a>, <a href="https://publications.waset.org/abstracts/search?q=rainfall-runoff%20modeling" title=" rainfall-runoff modeling"> rainfall-runoff modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20gradient%20boosting" title=" stochastic gradient boosting"> stochastic gradient boosting</a>, <a href="https://publications.waset.org/abstracts/search?q=bioinformatics" title=" bioinformatics"> bioinformatics</a> </p> <a href="https://publications.waset.org/abstracts/3455/the-use-of-stochastic-gradient-boosting-method-for-multi-model-combination-of-rainfall-runoff-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3455.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">339</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">31444</span> A Dynamical Study of Fractional Order Obesity Model by a Combined Legendre Wavelet Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hakiki%20Kheira">Hakiki Kheira</a>, <a href="https://publications.waset.org/abstracts/search?q=Belhamiti%20Omar"> Belhamiti Omar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose a new compartmental fractional order model for the simulation of epidemic obesity dynamics. Using the Legendre wavelet method combined with the decoupling and quasi-linearization technique, we demonstrate the validity and applicability of our model. We also present some fractional differential illustrative examples to demonstrate the applicability and efficiency of the method. The fractional derivative is described in the Caputo sense. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Caputo%20derivative" title="Caputo derivative">Caputo derivative</a>, <a href="https://publications.waset.org/abstracts/search?q=epidemiology" title=" epidemiology"> epidemiology</a>, <a href="https://publications.waset.org/abstracts/search?q=Legendre%20wavelet%20method" title=" Legendre wavelet method"> Legendre wavelet method</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity "> obesity </a> </p> <a href="https://publications.waset.org/abstracts/42731/a-dynamical-study-of-fractional-order-obesity-model-by-a-combined-legendre-wavelet-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42731.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">420</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">31443</span> Feasibility of Simulating External Vehicle Aerodynamics Using Spalart-Allmaras Turbulence Model with Adjoint Method in OpenFOAM and Fluent</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arpit%20Panwar">Arpit Panwar</a>, <a href="https://publications.waset.org/abstracts/search?q=Arvind%20Deshpande"> Arvind Deshpande</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study of external vehicle aerodynamics using Spalart-Allmaras turbulence model with adjoint method was conducted. The accessibility and ease of working with the Fluent module of ANSYS and OpenFOAM were considered. The objective of the study was to understand and analyze the possibility of bringing high-level aerodynamic simulation to the average consumer vehicle. A form-factor of BMW M6 vehicle was designed in Solidworks, which was analyzed in OpenFOAM and Fluent. The turbulence model being a single equation provides much faster convergence rate when clubbed with the adjoint method. Fluent being commercial software still does not allow us to solve Spalart-Allmaras turbulence model using the adjoint method. Hence, the turbulence model was solved using the SIMPLE method in Fluent. OpenFOAM being an open source provide flexibility in simulation but is not user-friendly. It supports solving the defined turbulence model with the adjoint method. The result generated from the simulation gives us acceptable values of drag, when validated with the result of percentage error in drag values for a notch-back vehicle model on an extensive simulation produced at 6th ANSA and μETA conference, Greece. The success of this approach will allow us to bring more aerodynamic vehicle body design to all segments of the automobile and not limiting it to just the high-end sports cars. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Spalart-Allmaras%20turbulence%20model" title="Spalart-Allmaras turbulence model">Spalart-Allmaras turbulence model</a>, <a href="https://publications.waset.org/abstracts/search?q=OpenFOAM" title=" OpenFOAM"> OpenFOAM</a>, <a href="https://publications.waset.org/abstracts/search?q=adjoint%20method" title=" adjoint method"> adjoint method</a>, <a href="https://publications.waset.org/abstracts/search?q=SIMPLE%20method" title=" SIMPLE method"> SIMPLE method</a>, <a href="https://publications.waset.org/abstracts/search?q=vehicle%20aerodynamic%20design" title=" vehicle aerodynamic design"> vehicle aerodynamic design</a> </p> <a href="https://publications.waset.org/abstracts/88883/feasibility-of-simulating-external-vehicle-aerodynamics-using-spalart-allmaras-turbulence-model-with-adjoint-method-in-openfoam-and-fluent" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88883.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">200</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">31442</span> A Mathematical Equation to Calculate Stock Price of Different Growth Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Weiping%20Liu">Weiping Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an equation to calculate stock prices of different growth model. This equation is mathematically derived by using discounted cash flow method. It has the advantages of being very easy to use and very accurate. It can still be used even when the first stage is lengthy. This equation is more generalized because it can be used for all the three popular stock price models. It can be programmed into financial calculator or electronic spreadsheets. In addition, it can be extended to a multistage model. It is more versatile and efficient than the traditional methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=stock%20price" title="stock price">stock price</a>, <a href="https://publications.waset.org/abstracts/search?q=multistage%20model" title=" multistage model"> multistage model</a>, <a href="https://publications.waset.org/abstracts/search?q=different%20growth%20model" title=" different growth model"> different growth model</a>, <a href="https://publications.waset.org/abstracts/search?q=discounted%20cash%20flow%20method" title=" discounted cash flow method"> discounted cash flow method</a> </p> <a href="https://publications.waset.org/abstracts/12664/a-mathematical-equation-to-calculate-stock-price-of-different-growth-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12664.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">406</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">31441</span> Model Order Reduction for Frequency Response and Effect of Order of Method for Matching Condition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aref%20Ghafouri">Aref Ghafouri</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20javad%20Mollakazemi"> Mohammad javad Mollakazemi</a>, <a href="https://publications.waset.org/abstracts/search?q=Farhad%20Asadi"> Farhad Asadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, model order reduction method is used for approximation in linear and nonlinearity aspects in some experimental data. This method can be used for obtaining offline reduced model for approximation of experimental data and can produce and follow the data and order of system and also it can match to experimental data in some frequency ratios. In this study, the method is compared in different experimental data and influence of choosing of order of the model reduction for obtaining the best and sufficient matching condition for following the data is investigated in format of imaginary and reality part of the frequency response curve and finally the effect and important parameter of number of order reduction in nonlinear experimental data is explained further. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=frequency%20response" title="frequency response">frequency response</a>, <a href="https://publications.waset.org/abstracts/search?q=order%20of%20model%20reduction" title=" order of model reduction"> order of model reduction</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency%20matching%20condition" title=" frequency matching condition"> frequency matching condition</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20experimental%20data" title=" nonlinear experimental data"> nonlinear experimental data</a> </p> <a href="https://publications.waset.org/abstracts/17631/model-order-reduction-for-frequency-response-and-effect-of-order-of-method-for-matching-condition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17631.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">402</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">31440</span> On the Application and Comparison of Two Geostatistics Methods in the Parameterisation Step to Calibrate Groundwater Model: Grid-Based Pilot Point and Head-Zonation Based Pilot Point Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dua%20K.%20S.%20Y.%20Klaas">Dua K. S. Y. Klaas</a>, <a href="https://publications.waset.org/abstracts/search?q=Monzur%20A.%20Imteaz"> Monzur A. Imteaz</a>, <a href="https://publications.waset.org/abstracts/search?q=Ika%20Sudiayem"> Ika Sudiayem</a>, <a href="https://publications.waset.org/abstracts/search?q=Elkan%20M.%20E.%20Klaas"> Elkan M. E. Klaas</a>, <a href="https://publications.waset.org/abstracts/search?q=Eldav%20C.%20M.%20Klaas"> Eldav C. M. Klaas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Properly selecting the most suitable and effective geostatistics method in the parameterization step of groundwater modeling is critical to attain a satisfactory model. In this paper, two geostatistics methods, i.e., Grid-Based Pilot Point (GB-PP) and Head-Zonation Based Pilot Point (HZB-PP) methods, were applied in an eogenetic karst catchment and compared using as model performances and computation time the criteria. Overall, the results show that appropriate selection of method is substantial in the parameterization of physically-based groundwater models, as it influences both the accuracy and simulation times. It was found that GB-PP method performed comparably superior to HZB-PP method. However, reflecting its model performances, HZB-PP method is promising for further application in groundwater modeling. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=groundwater%20model" title="groundwater model">groundwater model</a>, <a href="https://publications.waset.org/abstracts/search?q=geostatistics" title=" geostatistics"> geostatistics</a>, <a href="https://publications.waset.org/abstracts/search?q=pilot%20point" title=" pilot point"> pilot point</a>, <a href="https://publications.waset.org/abstracts/search?q=parameterization%20step" title=" parameterization step"> parameterization step</a> </p> <a href="https://publications.waset.org/abstracts/98227/on-the-application-and-comparison-of-two-geostatistics-methods-in-the-parameterisation-step-to-calibrate-groundwater-model-grid-based-pilot-point-and-head-zonation-based-pilot-point-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98227.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">166</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">31439</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">31438</span> Forecasting Unemployment Rate in Selected European Countries Using Smoothing Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ksenija%20Dumi%C4%8Di%C4%87">Ksenija Dumičić</a>, <a href="https://publications.waset.org/abstracts/search?q=Anita%20%C4%8Ceh%20%C4%8Casni"> Anita Čeh Časni</a>, <a href="https://publications.waset.org/abstracts/search?q=Berislav%20%C5%BDmuk"> Berislav Žmuk</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this paper is to select the most accurate forecasting method for predicting the future values of the unemployment rate in selected European countries. In order to do so, several forecasting techniques adequate for forecasting time series with trend component, were selected, namely: double exponential smoothing (also known as Holt`s method) and Holt-Winters` method which accounts for trend and seasonality. The results of the empirical analysis showed that the optimal model for forecasting unemployment rate in Greece was Holt-Winters` additive method. In the case of Spain, according to MAPE, the optimal model was double exponential smoothing model. Furthermore, for Croatia and Italy the best forecasting model for unemployment rate was Holt-Winters` multiplicative model, whereas in the case of Portugal the best model to forecast unemployment rate was Double exponential smoothing model. Our findings are in line with European Commission unemployment rate estimates. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=European%20Union%20countries" title="European Union countries">European Union countries</a>, <a href="https://publications.waset.org/abstracts/search?q=exponential%20smoothing%20methods" title=" exponential smoothing methods"> exponential smoothing methods</a>, <a href="https://publications.waset.org/abstracts/search?q=forecast%20accuracy%20unemployment%20rate" title=" forecast accuracy unemployment rate"> forecast accuracy unemployment rate</a> </p> <a href="https://publications.waset.org/abstracts/18328/forecasting-unemployment-rate-in-selected-european-countries-using-smoothing-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18328.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">369</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">31437</span> Computing Customer Lifetime Value in E-Commerce Websites with Regard to Returned Orders and Payment Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Morteza%20Giti">Morteza Giti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As online shopping is becoming increasingly popular, computing customer lifetime value for better knowing the customers is also gaining more importance. Two distinct factors that can affect the value of a customer in the context of online shopping is the number of returned orders and payment method. Returned orders are those which have been shipped but not collected by the customer and are returned to the store. Payment method refers to the way that customers choose to pay for the price of the order which are usually two: Pre-pay and Cash-on-delivery. In this paper, a novel model called RFMSP is presented to calculated the customer lifetime value, taking these two parameters into account. The RFMSP model is based on the common RFM model while adding two extra parameter. The S represents the order status and the P indicates the payment method. As a case study for this model, the purchase history of customers in an online shop is used to compute the customer lifetime value over a period of twenty months. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=RFMSP%20model" title="RFMSP model">RFMSP model</a>, <a href="https://publications.waset.org/abstracts/search?q=AHP" title=" AHP"> AHP</a>, <a href="https://publications.waset.org/abstracts/search?q=customer%20lifetime%20value" title=" customer lifetime value"> customer lifetime value</a>, <a href="https://publications.waset.org/abstracts/search?q=k-means%20clustering" title=" k-means clustering"> k-means clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=e-commerce" title=" e-commerce"> e-commerce</a> </p> <a href="https://publications.waset.org/abstracts/30396/computing-customer-lifetime-value-in-e-commerce-websites-with-regard-to-returned-orders-and-payment-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30396.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">319</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">31436</span> An Improved Prediction Model of Ozone Concentration Time Series Based on Chaotic Approach </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nor%20Zila%20Abd%20Hamid">Nor Zila Abd Hamid</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohd%20Salmi%20M.%20Noorani"> Mohd Salmi M. Noorani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chaotic%20approach" title="chaotic approach">chaotic approach</a>, <a href="https://publications.waset.org/abstracts/search?q=phase%20space" title=" phase space"> phase space</a>, <a href="https://publications.waset.org/abstracts/search?q=Cao%20method" title=" Cao method"> Cao method</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20linear%20approximation%20method" title=" local linear approximation method"> local linear approximation method</a> </p> <a href="https://publications.waset.org/abstracts/2015/an-improved-prediction-model-of-ozone-concentration-time-series-based-on-chaotic-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2015.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">331</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">31435</span> Lee-Carter Mortality Forecasting Method with Dynamic Normal Inverse Gaussian Mortality Index </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Funda%20Kul">Funda Kul</a>, <a href="https://publications.waset.org/abstracts/search?q=%C4%B0smail%20G%C3%BCr"> İsmail Gür</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mortality" title="mortality">mortality</a>, <a href="https://publications.waset.org/abstracts/search?q=forecasting" title=" forecasting"> forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=lee-carter%20model" title=" lee-carter model"> lee-carter model</a>, <a href="https://publications.waset.org/abstracts/search?q=normal%20inverse%20gaussian%20distribution" title=" normal inverse gaussian distribution"> normal inverse gaussian distribution</a> </p> <a href="https://publications.waset.org/abstracts/39750/lee-carter-mortality-forecasting-method-with-dynamic-normal-inverse-gaussian-mortality-index" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39750.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">360</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">31434</span> WiFi Data Offloading: Bundling Method in a Canvas Business Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Majid%20Mokhtarnia">Majid Mokhtarnia</a>, <a href="https://publications.waset.org/abstracts/search?q=Alireza%20Amini"> Alireza Amini</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Mobile operators deal with increasing in the data traffic as a critical issue. As a result, a vital responsibility of the operators is to deal with such a trend in order to create added values. This paper addresses a bundling method in a Canvas business model in a WiFi Data Offloading (WDO) strategy by which some elements of the model may be affected. In the proposed method, it is supposed to sell a number of data packages for subscribers in which there are some packages with a free given volume of data-offloaded WiFi complimentary. The paper on hands analyses this method in the views of attractiveness and profitability. The results demonstrate that the quality of implementation of the WDO strongly affects the final result and helps the decision maker to make the best one. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bundling" title="bundling">bundling</a>, <a href="https://publications.waset.org/abstracts/search?q=canvas%20business%20model" title=" canvas business model"> canvas business model</a>, <a href="https://publications.waset.org/abstracts/search?q=telecommunication" title=" telecommunication"> telecommunication</a>, <a href="https://publications.waset.org/abstracts/search?q=WiFi%20data%20offloading" title=" WiFi data offloading"> WiFi data offloading</a> </p> <a href="https://publications.waset.org/abstracts/96950/wifi-data-offloading-bundling-method-in-a-canvas-business-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/96950.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">200</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">31433</span> Performance of the Strong Stability Method in the Univariate Classical Risk Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Safia%20Hocine">Safia Hocine</a>, <a href="https://publications.waset.org/abstracts/search?q=Zina%20Benouaret"> Zina Benouaret</a>, <a href="https://publications.waset.org/abstracts/search?q=Djamil%20A%C2%A8%C4%B1ssani"> Djamil A¨ıssani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we study the performance of the strong stability method of the univariate classical risk model. We interest to the stability bounds established using two approaches. The first based on the strong stability method developed for a general Markov chains. The second approach based on the regenerative processes theory . By adopting an algorithmic procedure, we study the performance of the stability method in the case of exponential distribution claim amounts. After presenting numerically and graphically the stability bounds, an interpretation and comparison of the results have been done. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Marcov%20chain" title="Marcov chain">Marcov chain</a>, <a href="https://publications.waset.org/abstracts/search?q=regenerative%20process" title=" regenerative process"> regenerative process</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20model" title=" risk model"> risk model</a>, <a href="https://publications.waset.org/abstracts/search?q=ruin%20probability" title=" ruin probability"> ruin probability</a>, <a href="https://publications.waset.org/abstracts/search?q=strong%20stability" title=" strong stability"> strong stability</a> </p> <a href="https://publications.waset.org/abstracts/89002/performance-of-the-strong-stability-method-in-the-univariate-classical-risk-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/89002.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">324</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">31432</span> Investigated Optimization of Davidson Path Loss Model for Digital Terrestrial Television (DTTV) Propagation in Urban Area</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pitak%20Keawbunsong">Pitak Keawbunsong</a>, <a href="https://publications.waset.org/abstracts/search?q=Sathaporn%20Promwong"> Sathaporn Promwong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an investigation on the efficiency of the optimized Davison path loss model in order to look for a suitable path loss model to design and planning DTTV propagation for small and medium urban areas in southern Thailand. Hadyai City in Songkla Province is chosen as the case study to collect the analytical data on the electric field strength. The optimization is conducted through the least square method while the efficiency index is through the statistical value of relative error (RE). The result of the least square method is the offset and slop of the frequency to be used in the optimized process. The statistical result shows that RE of the old Davidson model is at the least when being compared with the optimized Davison and the Hata models. Thus, the old Davison path loss model is the most accurate that further becomes the most optimized for the plan on the propagation network design. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DTTV%20propagation" title="DTTV propagation">DTTV propagation</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20loss%20model" title=" path loss model"> path loss model</a>, <a href="https://publications.waset.org/abstracts/search?q=Davidson%20model" title=" Davidson model"> Davidson model</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20square%20method" title=" least square method"> least square method</a> </p> <a href="https://publications.waset.org/abstracts/43812/investigated-optimization-of-davidson-path-loss-model-for-digital-terrestrial-television-dttv-propagation-in-urban-area" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43812.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">338</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">31431</span> Identification of Wiener Model Using Iterative Schemes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vikram%20Saini">Vikram Saini</a>, <a href="https://publications.waset.org/abstracts/search?q=Lillie%20Dewan"> Lillie Dewan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hard%20non-linearity" title="hard non-linearity">hard non-linearity</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20square" title=" least square"> least square</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20estimation" title=" parameter estimation"> parameter estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20approximation%20gradient" title=" stochastic approximation gradient"> stochastic approximation gradient</a>, <a href="https://publications.waset.org/abstracts/search?q=Wiener%20model" title=" Wiener model"> Wiener model</a> </p> <a href="https://publications.waset.org/abstracts/70632/identification-of-wiener-model-using-iterative-schemes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70632.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">405</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">31430</span> 3D Liver Segmentation from CT Images Using a Level Set Method Based on a Shape and Intensity Distribution Prior</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nuseiba%20M.%20Altarawneh">Nuseiba M. Altarawneh</a>, <a href="https://publications.waset.org/abstracts/search?q=Suhuai%20Luo"> Suhuai Luo</a>, <a href="https://publications.waset.org/abstracts/search?q=Brian%20Regan"> Brian Regan</a>, <a href="https://publications.waset.org/abstracts/search?q=Guijin%20Tang"> Guijin Tang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Liver segmentation from medical images poses more challenges than analogous segmentations of other organs. This contribution introduces a liver segmentation method from a series of computer tomography images. Overall, we present a novel method for segmenting liver by coupling density matching with shape priors. Density matching signifies a tracking method which operates via maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated image region and a model photometric distribution. Density matching controls the direction of the evolution process and slows down the evolving contour in regions with weak edges. The shape prior improves the robustness of density matching and discourages the evolving contour from exceeding liver’s boundaries at regions with weak boundaries. The model is implemented using a modified distance regularized level set (DRLS) model. The experimental results show that the method achieves a satisfactory result. By comparing with the original DRLS model, it is evident that the proposed model herein is more effective in addressing the over segmentation problem. Finally, we gauge our performance of our model against matrices comprising of accuracy, sensitivity and specificity. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bhattacharyya%20distance" title="Bhattacharyya distance">Bhattacharyya distance</a>, <a href="https://publications.waset.org/abstracts/search?q=distance%20regularized%20level%20set%20%28DRLS%29%20model" title=" distance regularized level set (DRLS) model"> distance regularized level set (DRLS) model</a>, <a href="https://publications.waset.org/abstracts/search?q=liver%20segmentation" title=" liver segmentation"> liver segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=level%20set%20method" title=" level set method"> level set method</a> </p> <a href="https://publications.waset.org/abstracts/35588/3d-liver-segmentation-from-ct-images-using-a-level-set-method-based-on-a-shape-and-intensity-distribution-prior" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35588.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">313</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">31429</span> Model Averaging for Poisson Regression</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhou%20Jianhong">Zhou Jianhong </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Model averaging is a desirable approach to deal with model uncertainty, which, however, has rarely been explored for Poisson regression. In this paper, we propose a model averaging procedure based on an unbiased estimator of the expected Kullback-Leibler distance for the Poisson regression. Simulation study shows that the proposed model average estimator outperforms some other commonly used model selection and model average estimators in some situations. Our proposed methods are further applied to a real data example and the advantage of this method is demonstrated again. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=model%20averaging" title="model averaging">model averaging</a>, <a href="https://publications.waset.org/abstracts/search?q=poission%20regression" title=" poission regression"> poission regression</a>, <a href="https://publications.waset.org/abstracts/search?q=Kullback-Leibler%20distance" title=" Kullback-Leibler distance"> Kullback-Leibler distance</a>, <a href="https://publications.waset.org/abstracts/search?q=statistics" title=" statistics"> statistics</a> </p> <a href="https://publications.waset.org/abstracts/5501/model-averaging-for-poisson-regression" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5501.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">520</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">31428</span> An Elbow Biomechanical Model and Its Coefficients Adjustment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jie%20Bai">Jie Bai</a>, <a href="https://publications.waset.org/abstracts/search?q=Yongsheng%20Gao"> Yongsheng Gao</a>, <a href="https://publications.waset.org/abstracts/search?q=Shengxin%20Wang"> Shengxin Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jie%20Zhao"> Jie Zhao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Through the establishment of the elbow biomechanical model, it can provide theoretical guide for rehabilitation therapy on the upper limb of the human body. A biomechanical model of the elbow joint can be built by the connection of muscle force model and elbow dynamics. But there are many undetermined coefficients in the model like the optimal joint angle and optimal muscle force which are usually specified as the experimental parameters of other workers. Because of the individual differences, there is a certain deviation of the final result. To this end, the RMS value of the deviation between the actual angle and calculated angle is considered. A set of coefficients which lead to the minimum RMS value will be chosen to be the optimal parameters. The direct search method and the conjugacy search method are used to get the optimal parameters, thus the model can be more accurate and mode adaptability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=elbow%20biomechanical%20model" title="elbow biomechanical model">elbow biomechanical model</a>, <a href="https://publications.waset.org/abstracts/search?q=RMS" title=" RMS"> RMS</a>, <a href="https://publications.waset.org/abstracts/search?q=direct%20search" title=" direct search"> direct search</a>, <a href="https://publications.waset.org/abstracts/search?q=conjugacy%20search" title=" conjugacy search"> conjugacy search</a> </p> <a href="https://publications.waset.org/abstracts/7188/an-elbow-biomechanical-model-and-its-coefficients-adjustment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7188.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">548</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">31427</span> Model Averaging in a Multiplicative Heteroscedastic Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alan%20Wan">Alan Wan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=heteroscedasticity-robust" title="heteroscedasticity-robust">heteroscedasticity-robust</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20averaging" title=" model averaging"> model averaging</a>, <a href="https://publications.waset.org/abstracts/search?q=multiplicative%20heteroscedasticity" title=" multiplicative heteroscedasticity"> multiplicative heteroscedasticity</a>, <a href="https://publications.waset.org/abstracts/search?q=plug-in" title=" plug-in"> plug-in</a>, <a href="https://publications.waset.org/abstracts/search?q=squared%20prediction%20risk" title=" squared prediction risk"> squared prediction risk</a> </p> <a href="https://publications.waset.org/abstracts/68733/model-averaging-in-a-multiplicative-heteroscedastic-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68733.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">384</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">31426</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">31425</span> Model Predictive Control with Unscented Kalman Filter for Nonlinear Implicit Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Takashi%20Shimizu">Takashi Shimizu</a>, <a href="https://publications.waset.org/abstracts/search?q=Tomoaki%20Hashimoto"> Tomoaki Hashimoto</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A class of implicit systems is known as a more generalized class of systems than a class of explicit systems. To establish a control method for such a generalized class of systems, we adopt model predictive control method which is a kind of optimal feedback control with a performance index that has a moving initial time and terminal time. However, model predictive control method is inapplicable to systems whose all state variables are not exactly known. In other words, model predictive control method is inapplicable to systems with limited measurable states. In fact, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. It is also usual that output signals are disturbed by process and sensor noises. Hence, it is important to establish a state estimation method for nonlinear implicit systems with taking the process noise and sensor noise into consideration. To this purpose, we apply the model predictive control method and unscented Kalman filter for solving the optimization and estimation problems of nonlinear implicit systems, respectively. The objective of this study is to establish a model predictive control with unscented Kalman filter for nonlinear implicit systems. <p class="card-text"><strong>Keywords:</strong> <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=nonlinear%20systems" title=" nonlinear systems"> nonlinear systems</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20estimation" title=" state estimation"> state estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a> </p> <a href="https://publications.waset.org/abstracts/97739/model-predictive-control-with-unscented-kalman-filter-for-nonlinear-implicit-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97739.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">202</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">31424</span> Applying the Crystal Model to Different Nuclear Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Amar">A. Amar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The angular distributions of the nuclear systems under consideration have been analyzed in the framework of the optical model (OM), where the real part was taken in the crystal model form. A crystal model (CM) has been applied to deuteron elastically scattered by ⁶,⁷Li and ⁹Be. A crystal model (CM) + distorted-wave Born approximation (DWBA) + dynamic polarization potential (DPP) potential has been applied to deuteron elastically scattered by ⁶,⁷Li and 9Be. Also, a crystal model has been applied to ⁶Li elastically scattered by ¹⁶O and ²⁸Sn in addition to the ⁷Li+⁷Li system and the ¹²C(alpha,⁸Be) ⁸Be reaction. The continuum-discretized coupled-channels (CDCC) method has been applied to the ⁷Li+⁷Li system and agreement between the crystal model and the continuum-discretized coupled-channels (CDCC) method has been observed. In general, the models succeeded in reproducing the differential cross sections at the full angular range and for all the energies under consideration. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optical%20model%20%28OM%29" title="optical model (OM)">optical model (OM)</a>, <a href="https://publications.waset.org/abstracts/search?q=crystal%20model%20%28CM%29" title=" crystal model (CM)"> crystal model (CM)</a>, <a href="https://publications.waset.org/abstracts/search?q=distorted-wave%20born%20approximation%20%28DWBA%29" title=" distorted-wave born approximation (DWBA)"> distorted-wave born approximation (DWBA)</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20polarization%20potential%20%28DPP%29" title=" dynamic polarization potential (DPP)"> dynamic polarization potential (DPP)</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20continuum-discretized%20coupled-channels%20%28CDCC%29%20method" title=" the continuum-discretized coupled-channels (CDCC) method"> the continuum-discretized coupled-channels (CDCC) method</a>, <a href="https://publications.waset.org/abstracts/search?q=and%20deuteron%20elastically%20scattered%20by%20%E2%81%B6" title=" and deuteron elastically scattered by ⁶"> and deuteron elastically scattered by ⁶</a>, <a href="https://publications.waset.org/abstracts/search?q=%E2%81%B7Li%20and%20%E2%81%B9Be" title="⁷Li and ⁹Be">⁷Li and ⁹Be</a> </p> <a href="https://publications.waset.org/abstracts/177307/applying-the-crystal-model-to-different-nuclear-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/177307.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">79</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">31423</span> The Evaluation Model for the Quality of Software Based on Open Source Code</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Li%20Donghong">Li Donghong</a>, <a href="https://publications.waset.org/abstracts/search?q=Peng%20Fuyang"> Peng Fuyang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yang%20Guanghua"> Yang Guanghua</a>, <a href="https://publications.waset.org/abstracts/search?q=Su%20Xiaoyan"> Su Xiaoyan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Using open source code is a popular method of software development. How to evaluate the quality of software becomes more important. This paper introduces an evaluation model. The model evaluates the quality from four dimensions: technology, production, management, and development. Each dimension includes many indicators. The weight of indicator can be modified according to the purpose of evaluation. The paper also introduces a method of using the model. The evaluating result can provide good advice for evaluating or purchasing the software. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=evaluation%20model" title="evaluation model">evaluation model</a>, <a href="https://publications.waset.org/abstracts/search?q=software%20quality" title=" software quality"> software quality</a>, <a href="https://publications.waset.org/abstracts/search?q=open%20source%20code" title=" open source code"> open source code</a>, <a href="https://publications.waset.org/abstracts/search?q=evaluation%20indicator" title=" evaluation indicator"> evaluation indicator</a> </p> <a href="https://publications.waset.org/abstracts/55793/the-evaluation-model-for-the-quality-of-software-based-on-open-source-code" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55793.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">389</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">31422</span> Bubble Point Pressures of CO2+Ethyl Palmitate by a Cubic Equation of State and the Wong-Sandler Mixing Rule</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20Sedghamiz">M. A. Sedghamiz</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Raeissi"> S. Raeissi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study presents three different approaches to estimate bubble point pressures for the binary system of CO2 and ethyl palmitate fatty acid ethyl ester. The first method involves the Peng-Robinson (PR) Equation of State (EoS) with the conventional mixing rule of Van der Waals. The second approach involves the PR EOS together with the Wong Sandler (WS) mixing rule, coupled with the Uniquac Ge model. In order to model the bubble point pressures with this approach, the volume and area parameter for ethyl palmitate were estimated by the Hansen group contribution method. The last method involved the Peng-Robinson, combined with the Wong-Sandler Method, but using NRTL as the GE model. Results using the Van der Waals mixing rule clearly indicated that this method has the largest errors among all three methods, with errors in the range of 3.96–6.22 %. The Pr-Ws-Uniquac method exhibited small errors, with average absolute deviations between 0.95 to 1.97 percent. The Pr-Ws-Nrtl method led to the least errors where average absolute deviations ranged between 0.65-1.7%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bubble%20pressure" title="bubble pressure">bubble pressure</a>, <a href="https://publications.waset.org/abstracts/search?q=Gibbs%20excess%20energy%20model" title=" Gibbs excess energy model"> Gibbs excess energy model</a>, <a href="https://publications.waset.org/abstracts/search?q=mixing%20rule" title=" mixing rule"> mixing rule</a>, <a href="https://publications.waset.org/abstracts/search?q=CO2%20solubility" title=" CO2 solubility"> CO2 solubility</a>, <a href="https://publications.waset.org/abstracts/search?q=ethyl%20palmitate" title=" ethyl palmitate"> ethyl palmitate</a> </p> <a href="https://publications.waset.org/abstracts/2308/bubble-point-pressures-of-co2ethyl-palmitate-by-a-cubic-equation-of-state-and-the-wong-sandler-mixing-rule" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2308.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">474</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">31421</span> A Prediction Method for Large-Size Event Occurrences in the Sandpile Model </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Channgam">S. Channgam</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Sae-Tang"> A. Sae-Tang</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Termsaithong"> T. Termsaithong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this research, the occurrences of large size events in various system sizes of the Bak-Tang-Wiesenfeld sandpile model are considered. The system sizes (square lattice) of model considered here are 25×25, 50×50, 75×75 and 100×100. The cross-correlation between the ratio of sites containing 3 grain time series and the large size event time series for these 4 system sizes are also analyzed. Moreover, a prediction method of the large-size event for the 50×50 system size is also introduced. Lastly, it can be shown that this prediction method provides a slightly higher efficiency than random predictions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bak-Tang-Wiesenfeld%20sandpile%20model" title="Bak-Tang-Wiesenfeld sandpile model">Bak-Tang-Wiesenfeld sandpile model</a>, <a href="https://publications.waset.org/abstracts/search?q=cross-correlation" title=" cross-correlation"> cross-correlation</a>, <a href="https://publications.waset.org/abstracts/search?q=avalanches" title=" avalanches"> avalanches</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction%20method" title=" prediction method"> prediction method</a> </p> <a href="https://publications.waset.org/abstracts/43151/a-prediction-method-for-large-size-event-occurrences-in-the-sandpile-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43151.pdf" target="_blank" class="btn btn-primary 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