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function</title> <meta name="description" content="Search results for: error function"> <meta name="keywords" content="error function"> <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 navbar-toggler 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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="error function"> <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> 6609</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: error function</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6609</span> Bayesian Estimation under Different Loss Functions Using Gamma Prior for the Case of Exponential Distribution</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Md.%20Rashidul%20Hasan">Md. Rashidul Hasan</a>, <a href="https://publications.waset.org/abstracts/search?q=Atikur%20Rahman%20Baizid"> Atikur Rahman Baizid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Bayesian estimation approach is a non-classical estimation technique in statistical inference and is very useful in real world situation. The aim of this paper is to study the Bayes estimators of the parameter of exponential distribution under different loss functions and then compared among them as well as with the classical estimator named maximum likelihood estimator (MLE). In our real life, we always try to minimize the loss and we also want to gather some prior information (distribution) about the problem to solve it accurately. Here the gamma prior is used as the prior distribution of exponential distribution for finding the Bayes estimator. In our study, we also used different symmetric and asymmetric loss functions such as squared error loss function, quadratic loss function, modified linear exponential (MLINEX) loss function and non-linear exponential (NLINEX) loss function. Finally, mean square error (MSE) of the estimators are obtained and then presented graphically. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayes%20estimator" title="Bayes estimator">Bayes estimator</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20likelihood%20estimator%20%28MLE%29" title=" maximum likelihood estimator (MLE)"> maximum likelihood estimator (MLE)</a>, <a href="https://publications.waset.org/abstracts/search?q=modified%20linear%20exponential%20%28MLINEX%29%20loss%20function" title=" modified linear exponential (MLINEX) loss function"> modified linear exponential (MLINEX) loss function</a>, <a href="https://publications.waset.org/abstracts/search?q=Squared%20Error%20%28SE%29%20loss%20function" title=" Squared Error (SE) loss function"> Squared Error (SE) loss function</a>, <a href="https://publications.waset.org/abstracts/search?q=non-linear%20exponential%20%28NLINEX%29%20loss%20function" title=" non-linear exponential (NLINEX) loss function"> non-linear exponential (NLINEX) loss function</a> </p> <a href="https://publications.waset.org/abstracts/53902/bayesian-estimation-under-different-loss-functions-using-gamma-prior-for-the-case-of-exponential-distribution" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53902.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">6608</span> Weighted G2 Multi-Degree Reduction of Bezier Curves</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Salisu%20ibrahim">Salisu ibrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdalla%20Rababah"> Abdalla Rababah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this research, we use Weighted G2-Multi-degree reduction of Bezier curve of degree n to a Bezier curve of degree m, m < n. The degree reduction of Bezier curves is used to represent a given Bezier curve of n by a Bezier curve of degree m, m < n. Exact degree reduction is not possible, and degree reduction is approximate process in nature. We derive a weighted degree reducing method that is geometrically continuous at the end points. Different norms will be considered, several error minimizations will be given. The proposed methods produce error function that are less than the errors of existing methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bezier%20curves" title="Bezier curves">Bezier curves</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20degree%20reduction" title=" multiple degree reduction"> multiple degree reduction</a>, <a href="https://publications.waset.org/abstracts/search?q=geometric%20continuity" title=" geometric continuity"> geometric continuity</a>, <a href="https://publications.waset.org/abstracts/search?q=error%20function" title=" error function"> error function</a> </p> <a href="https://publications.waset.org/abstracts/18669/weighted-g2-multi-degree-reduction-of-bezier-curves" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18669.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">481</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">6607</span> An Alternative Richards’ Growth Model Based on Hyperbolic Sine Function</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samuel%20Oluwafemi%20Oyamakin">Samuel Oluwafemi Oyamakin</a>, <a href="https://publications.waset.org/abstracts/search?q=Angela%20Unna%20Chukwu"> Angela Unna Chukwu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Richrads growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richards growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richards growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richards nonlinear growth models better than the classical Richards growth model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=height" title="height">height</a>, <a href="https://publications.waset.org/abstracts/search?q=diameter%20at%20breast%20height" title=" diameter at breast height"> diameter at breast height</a>, <a href="https://publications.waset.org/abstracts/search?q=DBH" title=" DBH"> DBH</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperbolic%20sine%20function" title=" hyperbolic sine function"> hyperbolic sine function</a>, <a href="https://publications.waset.org/abstracts/search?q=Pinus%20caribaea" title=" Pinus caribaea"> Pinus caribaea</a>, <a href="https://publications.waset.org/abstracts/search?q=Richards%27%20growth%20model" title=" Richards' growth model"> Richards' growth model</a> </p> <a href="https://publications.waset.org/abstracts/66329/an-alternative-richards-growth-model-based-on-hyperbolic-sine-function" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66329.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">392</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">6606</span> The Linear Combination of Kernels in the Estimation of the Cumulative Distribution Functions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdel-Razzaq%20Mugdadi">Abdel-Razzaq Mugdadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ruqayyah%20Sani"> Ruqayyah Sani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Kernel Distribution Function Estimator (KDFE) method is the most popular method for nonparametric estimation of the cumulative distribution function. The kernel and the bandwidth are the most important components of this estimator. In this investigation, we replace the kernel in the KDFE with a linear combination of kernels to obtain a new estimator based on the linear combination of kernels, the mean integrated squared error (MISE), asymptotic mean integrated squared error (AMISE) and the asymptotically optimal bandwidth for the new estimator are derived. We propose a new data-based method to select the bandwidth for the new estimator. The new technique is based on the Plug-in technique in density estimation. We evaluate the new estimator and the new technique using simulations and real-life data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=estimation" title="estimation">estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=bandwidth" title=" bandwidth"> bandwidth</a>, <a href="https://publications.waset.org/abstracts/search?q=mean%20square%20error" title=" mean square error"> mean square error</a>, <a href="https://publications.waset.org/abstracts/search?q=cumulative%20distribution%20function" title=" cumulative distribution function"> cumulative distribution function</a> </p> <a href="https://publications.waset.org/abstracts/28571/the-linear-combination-of-kernels-in-the-estimation-of-the-cumulative-distribution-functions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28571.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">581</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">6605</span> On Differential Growth Equation to Stochastic Growth Model Using Hyperbolic Sine Function in Height/Diameter Modeling of Pines</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20O.%20Oyamakin">S. O. Oyamakin</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20U.%20Chukwu"> A. U. Chukwu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Richard's growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richard's growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richard's growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richard's nonlinear growth models better than the classical Richard's growth model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=height" title="height">height</a>, <a href="https://publications.waset.org/abstracts/search?q=Dbh" title=" Dbh"> Dbh</a>, <a href="https://publications.waset.org/abstracts/search?q=forest" title=" forest"> forest</a>, <a href="https://publications.waset.org/abstracts/search?q=Pinus%20caribaea" title=" Pinus caribaea"> Pinus caribaea</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperbolic" title=" hyperbolic"> hyperbolic</a>, <a href="https://publications.waset.org/abstracts/search?q=Richard%27s" title=" Richard's"> Richard's</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic" title=" stochastic"> stochastic</a> </p> <a href="https://publications.waset.org/abstracts/17738/on-differential-growth-equation-to-stochastic-growth-model-using-hyperbolic-sine-function-in-heightdiameter-modeling-of-pines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17738.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">480</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">6604</span> High Accuracy Analytic Approximation for Special Functions Applied to Bessel Functions J₀(x) and Its Zeros</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fernando%20Maass">Fernando Maass</a>, <a href="https://publications.waset.org/abstracts/search?q=Pablo%20Martin"> Pablo Martin</a>, <a href="https://publications.waset.org/abstracts/search?q=Jorge%20Olivares"> Jorge Olivares</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Bessel function J₀(x) is very important in Electrodynamics and Physics, as well as its zeros. In this work, a method to obtain high accuracy approximation is presented through an application to that function. In most of the applications of this function, the values of the zeros are very important. In this work, analytic approximations for this function have been obtained valid for all positive values of the variable x, which have high accuracy for the function as well as for the zeros. The approximation is determined by the simultaneous used of the power series and asymptotic expansion. The structure of the approximation is a combination of two rational functions with elementary functions as trigonometric and fractional powers. Here us in Pade method, rational functions are used, but now there combined with elementary functions us fractional powers hyperbolic or trigonometric functions, and others. The reason of this is that now power series of the exact function are used, but together with the asymptotic expansion, which usually includes fractional powers trigonometric functions and other type of elementary functions. The approximation must be a bridge between both expansions, and this can not be accomplished using only with rational functions. In the simplest approximation using 4 parameters the maximum absolute error is less than 0.006 at x ∼ 4.9. In this case also the maximum relative error for the zeros is less than 0.003 which is for the second zero, but that value decreases rapidly for the other zeros. The same kind of behaviour happens for the relative error of the maximum and minimum of the functions. Approximations with higher accuracy and more parameters will be also shown. All the approximations are valid for any positive value of x, and they can be calculated easily. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analytic%20approximations" title="analytic approximations">analytic approximations</a>, <a href="https://publications.waset.org/abstracts/search?q=asymptotic%20approximations" title=" asymptotic approximations"> asymptotic approximations</a>, <a href="https://publications.waset.org/abstracts/search?q=Bessel%20functions" title=" Bessel functions"> Bessel functions</a>, <a href="https://publications.waset.org/abstracts/search?q=quasirational%20approximations" title=" quasirational approximations"> quasirational approximations</a> </p> <a href="https://publications.waset.org/abstracts/92867/high-accuracy-analytic-approximation-for-special-functions-applied-to-bessel-functions-j0x-and-its-zeros" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/92867.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">251</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">6603</span> A Compressor Map Optimizing Tool for Prediction of Compressor Off-Design Performance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhongzhi%20Hu">Zhongzhi Hu</a>, <a href="https://publications.waset.org/abstracts/search?q=Jie%20Shen"> Jie Shen</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiqiang%20Wang"> Jiqiang Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A high precision aeroengine model is needed when developing the engine control system. Compared with other main components, the axial compressor is the most challenging component to simulate. In this paper, a compressor map optimizing tool based on the introduction of a modifiable β function is developed for FWorks (FADEC Works). Three parameters (d density, f fitting coefficient, k₀ slope of the line β=0) are introduced to the β function to make it modifiable. The comparison of the traditional β function and the modifiable β function is carried out for a certain type of compressor. The interpolation errors show that both methods meet the modeling requirements, while the modifiable β function can predict compressor performance more accurately for some areas of the compressor map where the users are interested in. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=beta%20function" title="beta function">beta function</a>, <a href="https://publications.waset.org/abstracts/search?q=compressor%20map" title=" compressor map"> compressor map</a>, <a href="https://publications.waset.org/abstracts/search?q=interpolation%20error" title=" interpolation error"> interpolation error</a>, <a href="https://publications.waset.org/abstracts/search?q=map%20optimization%20tool" title=" map optimization tool"> map optimization tool</a> </p> <a href="https://publications.waset.org/abstracts/72730/a-compressor-map-optimizing-tool-for-prediction-of-compressor-off-design-performance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72730.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">267</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">6602</span> Effects of Manufacture and Assembly Errors on the Output Error of Globoidal Cam Mechanisms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shuting%20Ji">Shuting Ji</a>, <a href="https://publications.waset.org/abstracts/search?q=Yueming%20Zhang"> Yueming Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jing%20Zhao"> Jing Zhao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The output error of the globoidal cam mechanism can be considered as a relevant indicator of mechanism performance, because it determines kinematic and dynamical behavior of mechanical transmission. Based on the differential geometry and the rigid body transformations, the mathematical model of surface geometry of the globoidal cam is established. Then we present the analytical expression of the output error (including the transmission error and the displacement error along the output axis) by considering different manufacture and assembly errors. The effects of the center distance error, the perpendicular error between input and output axes and the rotational angle error of the globoidal cam on the output error are systematically analyzed. A globoidal cam mechanism which is widely used in automatic tool changer of CNC machines is applied for illustration. Our results show that the perpendicular error and the rotational angle error have little effects on the transmission error but have great effects on the displacement error along the output axis. This study plays an important role in the design, manufacture and assembly of the globoidal cam mechanism. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=globoidal%20cam%20mechanism" title="globoidal cam mechanism">globoidal cam mechanism</a>, <a href="https://publications.waset.org/abstracts/search?q=manufacture%20error" title=" manufacture error"> manufacture error</a>, <a href="https://publications.waset.org/abstracts/search?q=transmission%20error" title=" transmission error"> transmission error</a>, <a href="https://publications.waset.org/abstracts/search?q=automatic%20tool%20changer" title=" automatic tool changer"> automatic tool changer</a> </p> <a href="https://publications.waset.org/abstracts/33472/effects-of-manufacture-and-assembly-errors-on-the-output-error-of-globoidal-cam-mechanisms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33472.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">574</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">6601</span> Structural Damage Detection Using Modal Data Employing Teaching Learning Based Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Subhajit%20Das">Subhajit Das</a>, <a href="https://publications.waset.org/abstracts/search?q=Nirjhar%20Dhang"> Nirjhar Dhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Structural damage detection is a challenging work in the field of structural health monitoring (SHM). The damage detection methods mainly focused on the determination of the location and severity of the damage. Model updating is a well known method to locate and quantify the damage. In this method, an error function is defined in terms of difference between the signal measured from ‘experiment’ and signal obtained from undamaged finite element model. This error function is minimised with a proper algorithm, and the finite element model is updated accordingly to match the measured response. Thus, the damage location and severity can be identified from the updated model. In this paper, an error function is defined in terms of modal data viz. frequencies and modal assurance criteria (MAC). MAC is derived from Eigen vectors. This error function is minimized by teaching-learning-based optimization (TLBO) algorithm, and the finite element model is updated accordingly to locate and quantify the damage. Damage is introduced in the model by reduction of stiffness of the structural member. The ‘experimental’ data is simulated by the finite element modelling. The error due to experimental measurement is introduced in the synthetic ‘experimental’ data by adding random noise, which follows Gaussian distribution. The efficiency and robustness of this method are explained through three examples e.g., one truss, one beam and one frame problem. The result shows that TLBO algorithm is efficient to detect the damage location as well as the severity of damage using modal data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=damage%20detection" title="damage detection">damage detection</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20element%20model%20updating" title=" finite element model updating"> finite element model updating</a>, <a href="https://publications.waset.org/abstracts/search?q=modal%20assurance%20criteria" title=" modal assurance criteria"> modal assurance criteria</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20health%20monitoring" title=" structural health monitoring"> structural health monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=teaching%20learning%20based%20optimization" title=" teaching learning based optimization"> teaching learning based optimization</a> </p> <a href="https://publications.waset.org/abstracts/77962/structural-damage-detection-using-modal-data-employing-teaching-learning-based-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77962.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">215</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">6600</span> Error Estimation for the Reconstruction Algorithm with Fan Beam Geometry</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nirmal%20Yadav">Nirmal Yadav</a>, <a href="https://publications.waset.org/abstracts/search?q=Tanuja%20Srivastava"> Tanuja Srivastava</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Shannon theory is an exact method to recover a band limited signals from its sampled values in discrete implementation, using sinc interpolators. But sinc based results are not much satisfactory for band-limited calculations so that convolution with window function, having compact support, has been introduced. Convolution Backprojection algorithm with window function is an approximation algorithm. In this paper, the error has been calculated, arises due to this approximation nature of reconstruction algorithm. This result will be defined for fan beam projection data which is more faster than parallel beam projection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computed%20tomography" title="computed tomography">computed tomography</a>, <a href="https://publications.waset.org/abstracts/search?q=convolution%20backprojection" title=" convolution backprojection"> convolution backprojection</a>, <a href="https://publications.waset.org/abstracts/search?q=radon%20transform" title=" radon transform"> radon transform</a>, <a href="https://publications.waset.org/abstracts/search?q=fan%20beam" title=" fan beam"> fan beam</a> </p> <a href="https://publications.waset.org/abstracts/25009/error-estimation-for-the-reconstruction-algorithm-with-fan-beam-geometry" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25009.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">492</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">6599</span> Forecast Based on an Empirical Probability Function with an Adjusted Error Using Propagation of Error</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Oscar%20Javier%20Herrera">Oscar Javier Herrera</a>, <a href="https://publications.waset.org/abstracts/search?q=Manuel%20Angel%20Camacho"> Manuel Angel Camacho</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper addresses a cutting edge method of business demand forecasting, based on an empirical probability function when the historical behavior of the data is random. Additionally, it presents error determination based on the numerical method technique ‘propagation of errors’. The methodology was conducted characterization and process diagnostics demand planning as part of the production management, then new ways to predict its value through techniques of probability and to calculate their mistake investigated, it was tools used numerical methods. All this based on the behavior of the data. This analysis was determined considering the specific business circumstances of a company in the sector of communications, located in the city of Bogota, Colombia. In conclusion, using this application it was possible to obtain the adequate stock of the products required by the company to provide its services, helping the company reduce its service time, increase the client satisfaction rate, reduce stock which has not been in rotation for a long time, code its inventory, and plan reorder points for the replenishment of stock. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=demand%20forecasting" title="demand forecasting">demand forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=empirical%20distribution" title=" empirical distribution"> empirical distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=propagation%20of%20error" title=" propagation of error"> propagation of error</a>, <a href="https://publications.waset.org/abstracts/search?q=Bogota" title=" Bogota"> Bogota</a> </p> <a href="https://publications.waset.org/abstracts/25604/forecast-based-on-an-empirical-probability-function-with-an-adjusted-error-using-propagation-of-error" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25604.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">630</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">6598</span> On the Cluster of the Families of Hybrid Polynomial Kernels in Kernel Density Estimation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Benson%20Ade%20Eniola%20Afere">Benson Ade Eniola Afere</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Over the years, kernel density estimation has been extensively studied within the context of nonparametric density estimation. The fundamental components of kernel density estimation are the kernel function and the bandwidth. While the mathematical exploration of the kernel component has been relatively limited, its selection and development remain crucial. The Mean Integrated Squared Error (MISE), serving as a measure of discrepancy, provides a robust framework for assessing the effectiveness of any kernel function. A kernel function with a lower MISE is generally considered to perform better than one with a higher MISE. Hence, the primary aim of this article is to create kernels that exhibit significantly reduced MISE when compared to existing classical kernels. Consequently, this article introduces a cluster of hybrid polynomial kernel families. The construction of these proposed kernel functions is carried out heuristically by combining two kernels from the classical polynomial kernel family using probability axioms. We delve into the analysis of error propagation within these kernels. To assess their performance, simulation experiments, and real-life datasets are employed. The obtained results demonstrate that the proposed hybrid kernels surpass their classical kernel counterparts in terms of performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classical%20polynomial%20kernels" title="classical polynomial kernels">classical polynomial kernels</a>, <a href="https://publications.waset.org/abstracts/search?q=cluster%20of%20families" title=" cluster of families"> cluster of families</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20error" title=" global error"> global error</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20Kernels" title=" hybrid Kernels"> hybrid Kernels</a>, <a href="https://publications.waset.org/abstracts/search?q=Kernel%20density%20estimation" title=" Kernel density estimation"> Kernel density estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20simulation" title=" Monte Carlo simulation"> Monte Carlo simulation</a> </p> <a href="https://publications.waset.org/abstracts/171468/on-the-cluster-of-the-families-of-hybrid-polynomial-kernels-in-kernel-density-estimation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/171468.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">93</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">6597</span> A Hybrid Data-Handler Module Based Approach for Prioritization in Quality Function Deployment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20Venu">P. Venu</a>, <a href="https://publications.waset.org/abstracts/search?q=Joeju%20M.%20Issac"> Joeju M. Issac</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Quality Function Deployment (QFD) is a systematic technique that creates a platform where the customer responses can be positively converted to design attributes. The accuracy of a QFD process heavily depends on the data that it is handling which is captured from customers or QFD team members. Customized computer programs that perform Quality Function Deployment within a stipulated time have been used by various companies across the globe. These programs heavily rely on storage and retrieval of the data on a common database. This database must act as a perfect source with minimum missing values or error values in order perform actual prioritization. This paper introduces a missing/error data handler module which uses Genetic Algorithm and Fuzzy numbers. The prioritization of customer requirements of sesame oil is illustrated and a comparison is made between proposed data handler module-based deployment and manual deployment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hybrid%20data%20handler" title="hybrid data handler">hybrid data handler</a>, <a href="https://publications.waset.org/abstracts/search?q=QFD" title=" QFD"> QFD</a>, <a href="https://publications.waset.org/abstracts/search?q=prioritization" title=" prioritization"> prioritization</a>, <a href="https://publications.waset.org/abstracts/search?q=module-based%20deployment" title=" module-based deployment"> module-based deployment</a> </p> <a href="https://publications.waset.org/abstracts/1831/a-hybrid-data-handler-module-based-approach-for-prioritization-in-quality-function-deployment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1831.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">297</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">6596</span> High Accuracy Analytic Approximations for Modified Bessel Functions I₀(x)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pablo%20Martin">Pablo Martin</a>, <a href="https://publications.waset.org/abstracts/search?q=Jorge%20Olivares"> Jorge Olivares</a>, <a href="https://publications.waset.org/abstracts/search?q=Fernando%20Maass"> Fernando Maass</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A method to obtain analytic approximations for special function of interest in engineering and physics is described here. Each approximate function will be valid for every positive value of the variable and accuracy will be high and increasing with the number of parameters to determine. The general technique will be shown through an application to the modified Bessel function of order zero, I₀(x). The form and the calculation of the parameters are performed with the simultaneous use of the power series and asymptotic expansion. As in Padé method rational functions are used, but now they are combined with other elementary functions as; fractional powers, hyperbolic, trigonometric and exponential functions, and others. The elementary function is determined, considering that the approximate function should be a bridge between the power series and the asymptotic expansion. In the case of the I₀(x) function two analytic approximations have been already determined. The simplest one is (1+x²/4)⁻¹/⁴(1+0.24273x²) cosh(x)/(1+0.43023x²). The parameters of I₀(x) were determined using the leading term of the asymptotic expansion and two coefficients of the power series, and the maximum relative error is 0.05. In a second case, two terms of the asymptotic expansion were used and 4 of the power series and the maximum relative error is 0.001 at x≈9.5. Approximations with much higher accuracy will be also shown. In conclusion a new technique is described to obtain analytic approximations to some functions of interest in sciences, such that they have a high accuracy, they are valid for every positive value of the variable, they can be integrated and differentiated as the usual, functions, and furthermore they can be calculated easily even with a regular pocket calculator. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analytic%20approximations" title="analytic approximations">analytic approximations</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical-physics%20applications" title=" mathematical-physics applications"> mathematical-physics applications</a>, <a href="https://publications.waset.org/abstracts/search?q=quasi-rational%20functions" title=" quasi-rational functions"> quasi-rational functions</a>, <a href="https://publications.waset.org/abstracts/search?q=special%20functions" title=" special functions"> special functions</a> </p> <a href="https://publications.waset.org/abstracts/77484/high-accuracy-analytic-approximations-for-modified-bessel-functions-i0x" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77484.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">251</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">6595</span> Energy Consumption Modeling for Strawberry Greenhouse Crop by Adaptive Nero Fuzzy Inference System Technique: A Case Study in Iran</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Azar%20Khodabakhshi">Azar Khodabakhshi</a>, <a href="https://publications.waset.org/abstracts/search?q=Elham%20Bolandnazar"> Elham Bolandnazar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Agriculture as the most important food manufacturing sector is not only the energy consumer, but also is known as energy supplier. Using energy is considered as a helpful parameter for analyzing and evaluating the agricultural sustainability. In this study, the pattern of energy consumption of strawberry greenhouses of Jiroft in Kerman province of Iran was surveyed. The total input energy required in the strawberries production was calculated as 113314.71 MJ /ha. Electricity with 38.34% contribution of the total energy was considered as the most energy consumer in strawberry production. In this study, Neuro Fuzzy networks was used for function modeling in the production of strawberries. Results showed that the best model for predicting the strawberries function had a correlation coefficient, root mean square error (RMSE) and mean absolute percentage error (MAPE) equal to 0.9849, 0.0154 kg/ha and 0.11% respectively. Regards to these results, it can be said that Neuro Fuzzy method can be well predicted and modeled the strawberry crop function. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=crop%20yield" title="crop yield">crop yield</a>, <a href="https://publications.waset.org/abstracts/search?q=energy" title=" energy"> energy</a>, <a href="https://publications.waset.org/abstracts/search?q=neuro-fuzzy%20method" title=" neuro-fuzzy method"> neuro-fuzzy method</a>, <a href="https://publications.waset.org/abstracts/search?q=strawberry" title=" strawberry"> strawberry</a> </p> <a href="https://publications.waset.org/abstracts/70034/energy-consumption-modeling-for-strawberry-greenhouse-crop-by-adaptive-nero-fuzzy-inference-system-technique-a-case-study-in-iran" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70034.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">380</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">6594</span> Experimenting with Error Performance of Systems Employing Pulse Shaping Filters on a Software-Defined-Radio Platform</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chia-Yu%20Yao">Chia-Yu Yao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents experimental results on testing the symbol-error-rate (SER) performance of quadrature amplitude modulation (QAM) systems employing symmetric pulse-shaping square-root (SR) filters designed by minimizing the roughness function and by minimizing the peak-to-average power ratio (PAR). The device used in the experiments is the 'bladeRF' software-defined-radio platform. PAR is a well-known measurement, whereas the roughness function is a concept for measuring the jitter-induced interference. The experimental results show that the system employing minimum-roughness pulse-shaping SR filters outperforms the system employing minimum-PAR pulse-shaping SR filters in the sense of SER performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pulse-shaping%20filters" title="pulse-shaping filters">pulse-shaping filters</a>, <a href="https://publications.waset.org/abstracts/search?q=FIR%20filters" title=" FIR filters"> FIR filters</a>, <a href="https://publications.waset.org/abstracts/search?q=jittering" title=" jittering"> jittering</a>, <a href="https://publications.waset.org/abstracts/search?q=QAM" title=" QAM"> QAM</a> </p> <a href="https://publications.waset.org/abstracts/51420/experimenting-with-error-performance-of-systems-employing-pulse-shaping-filters-on-a-software-defined-radio-platform" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51420.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">341</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">6593</span> Relevancy Measures of Errors in Displacements of Finite Elements Analysis Results</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20B.%20Bolkhir">A. B. Bolkhir</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Elshafie"> A. Elshafie</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20K.%20Yousif"> T. K. Yousif</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper highlights the methods of error estimation in finite element analysis (FEA) results. It indicates that the modeling error could be eliminated by performing finite element analysis with successively finer meshes or by extrapolating response predictions from an orderly sequence of relatively low degree of freedom analysis results. In addition, the paper eliminates the round-off error by running the code at a higher precision. The paper provides application in finite element analysis results. It draws a conclusion based on results of application of methods of error estimation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=finite%20element%20analysis%20%28FEA%29" title="finite element analysis (FEA)">finite element analysis (FEA)</a>, <a href="https://publications.waset.org/abstracts/search?q=discretization%20error" title=" discretization error"> discretization error</a>, <a href="https://publications.waset.org/abstracts/search?q=round-off%20error" title=" round-off error"> round-off error</a>, <a href="https://publications.waset.org/abstracts/search?q=mesh%20refinement" title=" mesh refinement"> mesh refinement</a>, <a href="https://publications.waset.org/abstracts/search?q=richardson%20extrapolation" title=" richardson extrapolation"> richardson extrapolation</a>, <a href="https://publications.waset.org/abstracts/search?q=monotonic%20convergence" title=" monotonic convergence"> monotonic convergence</a> </p> <a href="https://publications.waset.org/abstracts/37639/relevancy-measures-of-errors-in-displacements-of-finite-elements-analysis-results" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37639.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">495</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">6592</span> Prediction of Terrorist Activities in Nigeria using Bayesian Neural Network with Heterogeneous Transfer Functions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tayo%20P.%20Ogundunmade">Tayo P. Ogundunmade</a>, <a href="https://publications.waset.org/abstracts/search?q=Adedayo%20A.%20Adepoju"> Adedayo A. Adepoju</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=activation%20functions" title="activation functions">activation functions</a>, <a href="https://publications.waset.org/abstracts/search?q=Bayesian%20neural%20network" title=" Bayesian neural network"> Bayesian neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=mean%20square%20error" title=" mean square error"> mean square error</a>, <a href="https://publications.waset.org/abstracts/search?q=test%20error" title=" test error"> test error</a>, <a href="https://publications.waset.org/abstracts/search?q=terrorism" title=" terrorism"> terrorism</a> </p> <a href="https://publications.waset.org/abstracts/147074/prediction-of-terrorist-activities-in-nigeria-using-bayesian-neural-network-with-heterogeneous-transfer-functions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147074.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">165</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">6591</span> Estimation of Fuel Cost Function Characteristics Using Cuckoo Search</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20R.%20Al-Rashidi">M. R. Al-Rashidi</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20M.%20El-Naggar"> K. M. El-Naggar</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20F.%20Al-Hajri"> M. F. Al-Hajri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The fuel cost function describes the electric power generation-cost relationship in thermal plants, hence, it sheds light on economical aspects of power industry. Different models have been proposed to describe this relationship with the quadratic function model being the most popular one. Parameters of second order fuel cost function are estimated in this paper using cuckoo search algorithm. It is a new population based meta-heuristic optimization technique that has been used in this study primarily as an accurate estimation tool. Its main features are flexibility, simplicity, and effectiveness when compared to other estimation techniques. The parameter estimation problem is formulated as an optimization one with the goal being minimizing the error associated with the estimated parameters. A case study is considered in this paper to illustrate cuckoo search promising potential as a valuable estimation and optimization technique. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cuckoo%20search" title="cuckoo search">cuckoo search</a>, <a href="https://publications.waset.org/abstracts/search?q=parameters%20estimation" title=" parameters estimation"> parameters estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=fuel%20cost%20function" title=" fuel cost function"> fuel cost function</a>, <a href="https://publications.waset.org/abstracts/search?q=economic%20dispatch" title=" economic dispatch"> economic dispatch</a> </p> <a href="https://publications.waset.org/abstracts/25377/estimation-of-fuel-cost-function-characteristics-using-cuckoo-search" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25377.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">581</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">6590</span> Calibration of the Radical Installation Limit Error of the Accelerometer in the Gravity Gradient Instrument</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Danni%20Cong">Danni Cong</a>, <a href="https://publications.waset.org/abstracts/search?q=Meiping%20Wu"> Meiping Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaofeng%20He"> Xiaofeng He</a>, <a href="https://publications.waset.org/abstracts/search?q=Junxiang%20Lian"> Junxiang Lian</a>, <a href="https://publications.waset.org/abstracts/search?q=Juliang%20Cao"> Juliang Cao</a>, <a href="https://publications.waset.org/abstracts/search?q=Shaokuncai"> Shaokuncai</a>, <a href="https://publications.waset.org/abstracts/search?q=Hao%20Qin"> Hao Qin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Gravity gradient instrument (GGI) is the core of the gravity gradiometer, so the structural error of the sensor has a great impact on the measurement results. In order not to affect the aimed measurement accuracy, limit error is required in the installation of the accelerometer. In this paper, based on the established measuring principle model, the radial installation limit error is calibrated, which is taken as an example to provide a method to calculate the other limit error of the installation under the premise of ensuring the accuracy of the measurement result. This method provides the idea for deriving the limit error of the geometry structure of the sensor, laying the foundation for the mechanical precision design and physical design. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gravity%20gradient%20sensor" title="gravity gradient sensor">gravity gradient sensor</a>, <a href="https://publications.waset.org/abstracts/search?q=radial%20installation%20limit%20error" title=" radial installation limit error"> radial installation limit error</a>, <a href="https://publications.waset.org/abstracts/search?q=accelerometer" title=" accelerometer"> accelerometer</a>, <a href="https://publications.waset.org/abstracts/search?q=uniaxial%20rotational%20modulation" title=" uniaxial rotational modulation"> uniaxial rotational modulation</a> </p> <a href="https://publications.waset.org/abstracts/75475/calibration-of-the-radical-installation-limit-error-of-the-accelerometer-in-the-gravity-gradient-instrument" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75475.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">422</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">6589</span> Function Approximation with Radial Basis Function Neural Networks via FIR Filter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kyu%20Chul%20Lee">Kyu Chul Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Sung%20Hyun%20Yoo"> Sung Hyun Yoo</a>, <a href="https://publications.waset.org/abstracts/search?q=Choon%20Ki%20Ahn"> Choon Ki Ahn</a>, <a href="https://publications.waset.org/abstracts/search?q=Myo%20Taeg%20Lim"> Myo Taeg Lim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended Kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore, the number of centers will be considered since it affects the performance of approximation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extended%20Kalman%20filter" title="extended Kalman filter">extended Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=classification%20problem" title=" classification problem"> classification problem</a>, <a href="https://publications.waset.org/abstracts/search?q=radial%20basis%20function%20networks%20%28RBFN%29" title=" radial basis function networks (RBFN)"> radial basis function networks (RBFN)</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20impulse%20response%20%28FIR%29%20filter" title=" finite impulse response (FIR) filter"> finite impulse response (FIR) filter</a> </p> <a href="https://publications.waset.org/abstracts/13851/function-approximation-with-radial-basis-function-neural-networks-via-fir-filter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13851.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">456</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">6588</span> High Capacity Reversible Watermarking through Interpolated Error Shifting</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hae-Yeoun%20Lee">Hae-Yeoun Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Reversible watermarking that not only protects the copyright but also preserve the original quality of the digital content have been intensively studied. In particular, the demand for reversible watermarking has increased. In this paper, we propose a reversible watermarking scheme based on interpolation-error shifting and error precompensation. The intensity of a pixel is interpolated from the intensities of neighbouring pixels, and the difference histogram between the interpolated and the original intensities is obtained and modified to embed the watermark message. By restoring the difference histogram, the embedded watermark is extracted and the original image is recovered by compensating for the interpolation error. The overflow and underflow are prevented by error precompensation. To show the performance of the method, the proposed algorithm is compared with other methods using various test images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reversible%20watermarking" title="reversible watermarking">reversible watermarking</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20capacity" title=" high capacity"> high capacity</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20quality" title=" high quality"> high quality</a>, <a href="https://publications.waset.org/abstracts/search?q=interpolated%20error%20shifting" title=" interpolated error shifting"> interpolated error shifting</a>, <a href="https://publications.waset.org/abstracts/search?q=error%20precompensation" title=" error precompensation"> error precompensation</a> </p> <a href="https://publications.waset.org/abstracts/7023/high-capacity-reversible-watermarking-through-interpolated-error-shifting" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7023.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">6587</span> Tests for Zero Inflation in Count Data with Measurement Error in Covariates</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Man-Yu%20Wong">Man-Yu Wong</a>, <a href="https://publications.waset.org/abstracts/search?q=Siyu%20Zhou"> Siyu Zhou</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhiqiang%20Cao"> Zhiqiang Cao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In quality of life, health service utilization is an important determinant of medical resource expenditures on Colorectal cancer (CRC) care, a better understanding of the increased utilization of health services is essential for optimizing the allocation of healthcare resources to services and thus for enhancing the service quality, especially for high expenditure on CRC care like Hong Kong region. In assessing the association between the health-related quality of life (HRQOL) and health service utilization in patients with colorectal neoplasm, count data models can be used, which account for over dispersion or extra zero counts. In our data, the HRQOL evaluation is a self-reported measure obtained from a questionnaire completed by the patients, misreports and variations in the data are inevitable. Besides, there are more zero counts from the observed number of clinical consultations (observed frequency of zero counts = 206) than those from a Poisson distribution with mean equal to 1.33 (expected frequency of zero counts = 156). This suggests that excess of zero counts may exist. Therefore, we study tests for detecting zero-inflation in models with measurement error in covariates. Method: Under classical measurement error model, the approximate likelihood function for zero-inflation Poisson regression model can be obtained, then Approximate Maximum Likelihood Estimation(AMLE) can be derived accordingly, which is consistent and asymptotically normally distributed. By calculating score function and Fisher information based on AMLE, a score test is proposed to detect zero-inflation effect in ZIP model with measurement error. The proposed test follows asymptotically standard normal distribution under H0, and it is consistent with the test proposed for zero-inflation effect when there is no measurement error. Results: Simulation results show that empirical power of our proposed test is the highest among existing tests for zero-inflation in ZIP model with measurement error. In real data analysis, with or without considering measurement error in covariates, existing tests, and our proposed test all imply H0 should be rejected with P-value less than 0.001, i.e., zero-inflation effect is very significant, ZIP model is superior to Poisson model for analyzing this data. However, if measurement error in covariates is not considered, only one covariate is significant; if measurement error in covariates is considered, only another covariate is significant. Moreover, the direction of coefficient estimations for these two covariates is different in ZIP regression model with or without considering measurement error. Conclusion: In our study, compared to Poisson model, ZIP model should be chosen when assessing the association between condition-specific HRQOL and health service utilization in patients with colorectal neoplasm. and models taking measurement error into account will result in statistically more reliable and precise information. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=count%20data" title="count data">count data</a>, <a href="https://publications.waset.org/abstracts/search?q=measurement%20error" title=" measurement error"> measurement error</a>, <a href="https://publications.waset.org/abstracts/search?q=score%20test" title=" score test"> score test</a>, <a href="https://publications.waset.org/abstracts/search?q=zero%20inflation" title=" zero inflation"> zero inflation</a> </p> <a href="https://publications.waset.org/abstracts/70280/tests-for-zero-inflation-in-count-data-with-measurement-error-in-covariates" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70280.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">288</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">6586</span> Grating Scale Thermal Expansion Error Compensation for Large Machine Tools Based on Multiple Temperature Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wenlong%20Feng">Wenlong Feng</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhenchun%20Du"> Zhenchun Du</a>, <a href="https://publications.waset.org/abstracts/search?q=Jianguo%20Yang"> Jianguo Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To decrease the grating scale thermal expansion error, a novel method which based on multiple temperature detections is proposed. Several temperature sensors are installed on the grating scale and the temperatures of these sensors are recorded. The temperatures of every point on the grating scale are calculated by interpolating between adjacent sensors. According to the thermal expansion principle, the grating scale thermal expansion error model can be established by doing the integral for the variations of position and temperature. A novel compensation method is proposed in this paper. By applying the established error model, the grating scale thermal expansion error is decreased by 90% compared with no compensation. The residual positioning error of the grating scale is less than 15um/10m and the accuracy of the machine tool is significant improved. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=thermal%20expansion%20error%20of%20grating%20scale" title="thermal expansion error of grating scale">thermal expansion error of grating scale</a>, <a href="https://publications.waset.org/abstracts/search?q=error%20compensation" title=" error compensation"> error compensation</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20tools" title=" machine tools"> machine tools</a>, <a href="https://publications.waset.org/abstracts/search?q=integral%20method" title=" integral method"> integral method</a> </p> <a href="https://publications.waset.org/abstracts/34355/grating-scale-thermal-expansion-error-compensation-for-large-machine-tools-based-on-multiple-temperature-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34355.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">365</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">6585</span> Life Prediction Method of Lithium-Ion Battery Based on Grey Support Vector Machines</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xiaogang%20Li">Xiaogang Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Jieqiong%20Miao"> Jieqiong Miao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Grey%20prediction%20model" title="Grey prediction model">Grey prediction model</a>, <a href="https://publications.waset.org/abstracts/search?q=trigonometric%20functions" title=" trigonometric functions"> trigonometric functions</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machines" title=" support vector machines"> support vector machines</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithms" title=" genetic algorithms"> genetic algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=root%20mean%20square%20error" title=" root mean square error"> root mean square error</a> </p> <a href="https://publications.waset.org/abstracts/29370/life-prediction-method-of-lithium-ion-battery-based-on-grey-support-vector-machines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/29370.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">461</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">6584</span> Using Derivative Free Method to Improve the Error Estimation of Numerical Quadrature</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chin-Yun%20Chen">Chin-Yun Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Numerical integration is an essential tool for deriving different physical quantities in engineering and science. The effectiveness of a numerical integrator depends on different factors, where the crucial one is the error estimation. This work presents an error estimator that combines a derivative free method to improve the performance of verified numerical quadrature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=numerical%20quadrature" title="numerical quadrature">numerical quadrature</a>, <a href="https://publications.waset.org/abstracts/search?q=error%20estimation" title=" error estimation"> error estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=derivative%20free%20method" title=" derivative free method"> derivative free method</a>, <a href="https://publications.waset.org/abstracts/search?q=interval%20computation" title=" interval computation "> interval computation </a> </p> <a href="https://publications.waset.org/abstracts/17210/using-derivative-free-method-to-improve-the-error-estimation-of-numerical-quadrature" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17210.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">463</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">6583</span> Medical Error: Concept and Description According to Brazilian Physicians</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vitor%20S.%20Mendonca">Vitor S. Mendonca</a>, <a href="https://publications.waset.org/abstracts/search?q=Maria%20Luisa%20S.%20Schmidt"> Maria Luisa S. Schmidt</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Brazilian medical profession is viewed as being error-free, so healthcare professionals who commit an error are condemned there. Medical errors occur frequently in the Brazilian healthcare system, so identifying better options for handling this issue has become of interest primarily for physicians. The purpose of this study is to better understand the tensions involved in the fear of making an error due to the harm and risk this would represent for those involved. A qualitative study was performed by means of the narratives of the lived experiences of ten acting physicians in the State of Sao Paulo. The concept and characterization of errors were discussed, together with the fear of making an error, the near misses or error in itself, how to deal with errors and what to do to avoid them. The analysis indicates an excessive pressure in the medical profession for error-free practices, with a well-established physician-patient relationship to facilitate the management of medical errors. The error occurs, but a lack of information and discussion often leads to its concealment due to fear or possible judgment by society or peers. The establishment of programs that encourage appropriate medical conduct in the event of an error requires coherent answers for humanization in Brazilian medical science. It is necessary to improve the discussion about medical errors and disseminate models of communication and notification of errors in Brazil. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=medical%20error" title="medical error">medical error</a>, <a href="https://publications.waset.org/abstracts/search?q=narrative" title=" narrative"> narrative</a>, <a href="https://publications.waset.org/abstracts/search?q=physician-patient%20relationship" title=" physician-patient relationship"> physician-patient relationship</a>, <a href="https://publications.waset.org/abstracts/search?q=qualitative%20research" title=" qualitative research"> qualitative research</a> </p> <a href="https://publications.waset.org/abstracts/102416/medical-error-concept-and-description-according-to-brazilian-physicians" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/102416.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">178</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">6582</span> Co-Integration and Error Correction Mechanism of Supply Response of Sugarcane in Pakistan (1980-2012)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Himayatullah%20Khan">Himayatullah Khan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study estimates supply response function of sugarcane in Pakistan from 1980-81 to 2012-13. The study uses co-integration approach and error correction mechanism. Sugarcane production, area and price series were tested for unit root using Augmented Dickey Fuller (ADF). The study found that these series were stationary at their first differenced level. Using the Augmented Engle-Granger test and Cointegrating Regression Durbin-Watson (CRDW) test, the study found that “production and price” and “area and price” were co-integrated suggesting that the two sets of time series had long-run or equilibrium relationship. The results of the error correction models for the two sets of series showed that there was disequilibrium in the short run there may be disequilibrium. The Engle-Granger residual may be thought of as the equilibrium error which can be used to tie the short-run behavior of the dependent variable to its long-run value. The Granger-Causality test results showed that log of price granger caused both the long of production and log of area whereas, the log of production and log of area Granger caused each other. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=co-integration" title="co-integration">co-integration</a>, <a href="https://publications.waset.org/abstracts/search?q=error%20correction%20mechanism" title=" error correction mechanism"> error correction mechanism</a>, <a href="https://publications.waset.org/abstracts/search?q=Granger-causality" title=" Granger-causality"> Granger-causality</a>, <a href="https://publications.waset.org/abstracts/search?q=sugarcane" title=" sugarcane"> sugarcane</a>, <a href="https://publications.waset.org/abstracts/search?q=supply%20response" title=" supply response "> supply response </a> </p> <a href="https://publications.waset.org/abstracts/14689/co-integration-and-error-correction-mechanism-of-supply-response-of-sugarcane-in-pakistan-1980-2012" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14689.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">435</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">6581</span> Lookup Table Reduction and Its Error Analysis of Hall Sensor-Based Rotation Angle Measurement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Young-San%20Shin">Young-San Shin</a>, <a href="https://publications.waset.org/abstracts/search?q=Seongsoo%20Lee"> Seongsoo Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Hall sensor is widely used to measure rotation angle. When the Hall voltage is measured for linear displacement, it is converted to angular displacement using arctangent function, which requires a large lookup table. In this paper, a lookup table reduction technique is presented for angle measurement. When the input of the lookup table is small within a certain threshold, the change of the outputs with respect to the change of the inputs is relatively small. Thus, several inputs can share same output, which significantly reduce the lookup table size. Its error analysis was also performed, and the threshold was determined so as to maintain the error less than 1°. When the Hall voltage has 11-bit resolution, the lookup table size is reduced from 1,024 samples to 279 samples. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hall%20sensor" title="hall sensor">hall sensor</a>, <a href="https://publications.waset.org/abstracts/search?q=angle%20measurement" title=" angle measurement"> angle measurement</a>, <a href="https://publications.waset.org/abstracts/search?q=lookup%20table" title=" lookup table"> lookup table</a>, <a href="https://publications.waset.org/abstracts/search?q=arctangent" title=" arctangent"> arctangent</a> </p> <a href="https://publications.waset.org/abstracts/60862/lookup-table-reduction-and-its-error-analysis-of-hall-sensor-based-rotation-angle-measurement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60862.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">336</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">6580</span> Variation of Refractive Errors among Right and Left Eyes in Jos, Plateau State, Nigeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=F.%20B.%20Masok">F. B. Masok</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20S%20Songdeg"> S. S Songdeg</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20R.%20Dawam"> R. R. Dawam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Vision is an important process for learning and communication as man depends greatly on vision to sense his environment. Prevalence and variation of refractive errors conducted between December 2010 and May 2011 in Jos, revealed that 735 (77.50%) out 950 subjects examined for refractive error had various refractive errors. Myopia was observed in 373 (49.79%) of the subjects, the error in the right eyes was 263 (55.60%) while the error in the left was 210(44.39%). The mean myopic error was found to be -1.54± 3.32. Hyperopia was observed in 385 (40.53%) of the sampled population comprising 203(52.73%) of the right eyes and 182(47.27%). The mean hyperopic error was found to be +1.74± 3.13. Astigmatism accounted for 359 (38.84%) of the subjects, out of which 193(53.76%) were in the right eyes while 168(46.79%) were in the left eyes. Presbyopia was found in 404(42.53%) of the subjects, of this figure, 164(40.59%) were in the right eyes while 240(59.41%) were in left eyes. The number of right eyes and left eyes with refractive errors was observed in some age groups to increase with age and later had its peak within 60 – 69 age groups. This pattern of refractive errors could be attributed to exposure to various forms of light particularly the ultraviolet rays (e.g rays from television and computer screen). There was no remarkable differences between the mean Myopic error and mean Hyperopic error in the right eyes and in the left eyes which suggest the right eye and the left eye are similar. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=left%20eye" title="left eye">left eye</a>, <a href="https://publications.waset.org/abstracts/search?q=refractive%20errors" title=" refractive errors"> refractive errors</a>, <a href="https://publications.waset.org/abstracts/search?q=right%20eye" title=" right eye"> right eye</a>, <a href="https://publications.waset.org/abstracts/search?q=variation" title=" variation"> variation</a> </p> <a href="https://publications.waset.org/abstracts/30588/variation-of-refractive-errors-among-right-and-left-eyes-in-jos-plateau-state-nigeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30588.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> <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=error%20function&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=error%20function&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=error%20function&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=error%20function&page=5">5</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=error%20function&page=6">6</a></li> <li class="page-item"><a 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