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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="weighting coefficient"> <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> 2407</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: weighting coefficient</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2407</span> Performance Evaluation of Refinement Method for Wideband Two-Beams Formation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=C.%20Bunsanit">C. Bunsanit</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the refinement method for two beams formation of wideband smart antenna. The refinement method for weighting coefficients is based on Fully Spatial Signal Processing by taking Inverse Discrete Fourier Transform (IDFT), and its simulation results are presented using MATLAB. The radiation pattern is created by multiplying the incoming signal with real weights and then summing them together. These real weighting coefficients are computed by IDFT method; however, the range of weight values is relatively wide. Therefore, for reducing this range, the refinement method is used. The radiation pattern concerns with five input parameters to control. These parameters are maximum weighting coefficient, wideband signal, direction of mainbeam, beamwidth, and maximum of minor lobe level. Comparison of the obtained simulation results between using refinement method and taking only IDFT shows that the refinement method works well for wideband two beams formation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fully%20spatial%20signal%20processing" title="fully spatial signal processing">fully spatial signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=beam%20forming" title=" beam forming"> beam forming</a>, <a href="https://publications.waset.org/abstracts/search?q=refinement%20method" title=" refinement method"> refinement method</a>, <a href="https://publications.waset.org/abstracts/search?q=smart%20antenna" title=" smart antenna"> smart antenna</a>, <a href="https://publications.waset.org/abstracts/search?q=weighting%20coefficient" title=" weighting coefficient"> weighting coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=wideband" title=" wideband"> wideband</a> </p> <a href="https://publications.waset.org/abstracts/58916/performance-evaluation-of-refinement-method-for-wideband-two-beams-formation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58916.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">226</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">2406</span> Feature Weighting Comparison Based on Clustering Centers in the Detection of Diabetic Retinopathy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kemal%20Polat">Kemal Polat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title="machine learning">machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20weighting" title=" data weighting"> data weighting</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a> </p> <a href="https://publications.waset.org/abstracts/51496/feature-weighting-comparison-based-on-clustering-centers-in-the-detection-of-diabetic-retinopathy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51496.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">325</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">2405</span> 1/Sigma Term Weighting Scheme for Sentiment Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hanan%20Alshaher">Hanan Alshaher</a>, <a href="https://publications.waset.org/abstracts/search?q=Jinsheng%20Xu"> Jinsheng Xu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Large amounts of data on the web can provide valuable information. For example, product reviews help business owners measure customer satisfaction. Sentiment analysis classifies texts into two polarities: positive and negative. This paper examines movie reviews and tweets using a new term weighting scheme, called one-over-sigma (1/sigma), on benchmark datasets for sentiment classification. The proposed method aims to improve the performance of sentiment classification. The results show that 1/sigma is more accurate than the popular term weighting schemes. In order to verify if the entropy reflects the discriminating power of terms, we report a comparison of entropy values for different term weighting schemes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=1%2Fsigma" title="1/sigma">1/sigma</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20processing" title=" natural language processing"> natural language processing</a>, <a href="https://publications.waset.org/abstracts/search?q=sentiment%20analysis" title=" sentiment analysis"> sentiment analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=term%20weighting%20scheme" title=" term weighting scheme"> term weighting scheme</a>, <a href="https://publications.waset.org/abstracts/search?q=text%20classification" title=" text classification"> text classification</a> </p> <a href="https://publications.waset.org/abstracts/134006/1sigma-term-weighting-scheme-for-sentiment-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/134006.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">2404</span> Nullity of t-Tupple Graphs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khidir%20R.%20Sharaf">Khidir R. Sharaf</a>, <a href="https://publications.waset.org/abstracts/search?q=Didar%20A.%20Ali"> Didar A. Ali</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The nullity η (G) of a graph is the occurrence of zero as an eigenvalue in its spectra. A zero-sum weighting of a graph G is real valued function, say f from vertices of G to the set of real numbers, provided that for each vertex of G the summation of the weights f (w) over all neighborhood w of v is zero for each v in G.A high zero-sum weighting of G is one that uses maximum number of non-zero independent variables. If G is graph with an end vertex, and if H is an induced sub-graph of G obtained by deleting this vertex together with the vertex adjacent to it, then, η(G)= η(H). In this paper, a high zero-sum weighting technique and the end vertex procedure are applied to evaluate the nullity of t-tupple and generalized t-tupple graphs are derived and determined for some special types of graphs. Also, we introduce and prove some important results about the t-tupple coalescence, Cartesian and Kronecker products of nut graphs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=graph%20theory" title="graph theory">graph theory</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20spectra" title=" graph spectra"> graph spectra</a>, <a href="https://publications.waset.org/abstracts/search?q=nullity%20of%20graphs" title=" nullity of graphs"> nullity of graphs</a>, <a href="https://publications.waset.org/abstracts/search?q=statistic" title=" statistic"> statistic</a> </p> <a href="https://publications.waset.org/abstracts/4759/nullity-of-t-tupple-graphs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4759.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">239</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">2403</span> Intelligent Recognition of Diabetes Disease via FCM Based Attribute Weighting</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kemal%20Polat">Kemal Polat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20C-means%20clustering" title="fuzzy C-means clustering">fuzzy C-means clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20C-means%20clustering%20based%20attribute%20weighting" title=" fuzzy C-means clustering based attribute weighting"> fuzzy C-means clustering based attribute weighting</a>, <a href="https://publications.waset.org/abstracts/search?q=Pima%20Indians%20diabetes" title=" Pima Indians diabetes"> Pima Indians diabetes</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM" title=" SVM"> SVM</a> </p> <a href="https://publications.waset.org/abstracts/46171/intelligent-recognition-of-diabetes-disease-via-fcm-based-attribute-weighting" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46171.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">413</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">2402</span> Enhancing Spatial Interpolation: A Multi-Layer Inverse Distance Weighting Model for Complex Regression and Classification Tasks in Spatial Data Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yakin%20Hajlaoui">Yakin Hajlaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=Richard%20Labib"> Richard Labib</a>, <a href="https://publications.waset.org/abstracts/search?q=Jean-Fran%C3%A7ois%20Plante"> Jean-François Plante</a>, <a href="https://publications.waset.org/abstracts/search?q=Michel%20Gamache"> Michel Gamache</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study introduces the Multi-Layer Inverse Distance Weighting Model (ML-IDW), inspired by the mathematical formulation of both multi-layer neural networks (ML-NNs) and Inverse Distance Weighting model (IDW). ML-IDW leverages ML-NNs' processing capabilities, characterized by compositions of learnable non-linear functions applied to input features, and incorporates IDW's ability to learn anisotropic spatial dependencies, presenting a promising solution for nonlinear spatial interpolation and learning from complex spatial data. it employ gradient descent and backpropagation to train ML-IDW, comparing its performance against conventional spatial interpolation models such as Kriging and standard IDW on regression and classification tasks using simulated spatial datasets of varying complexity. the results highlight the efficacy of ML-IDW, particularly in handling complex spatial datasets, exhibiting lower mean square error in regression and higher F1 score in classification. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deep%20learning" title="deep learning">deep learning</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-layer%20neural%20networks" title=" multi-layer neural networks"> multi-layer neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=gradient%20descent" title=" gradient descent"> gradient descent</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial%20interpolation" title=" spatial interpolation"> spatial interpolation</a>, <a href="https://publications.waset.org/abstracts/search?q=inverse%20distance%20weighting" title=" inverse distance weighting"> inverse distance weighting</a> </p> <a href="https://publications.waset.org/abstracts/185810/enhancing-spatial-interpolation-a-multi-layer-inverse-distance-weighting-model-for-complex-regression-and-classification-tasks-in-spatial-data-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185810.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">52</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">2401</span> Vendor Selection and Supply Quotas Determination by Using Revised Weighting Method and Multi-Objective Programming Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tunjo%20Peri%C4%8D">Tunjo Perič</a>, <a href="https://publications.waset.org/abstracts/search?q=Marin%20Fatovi%C4%87"> Marin Fatović</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper a new methodology for vendor selection and supply quotas determination (VSSQD) is proposed. The problem of VSSQD is solved by the model that combines revised weighting method for determining the objective function coefficients, and a multiple objective linear programming (MOLP) method based on the cooperative game theory for VSSQD. The criteria used for VSSQD are: (1) purchase costs and (2) product quality supplied by individual vendors. The proposed methodology is tested on the example of flour purchase for a bakery with two decision makers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cooperative%20game%20theory" title="cooperative game theory">cooperative game theory</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20objective%20linear%20programming" title=" multiple objective linear programming"> multiple objective linear programming</a>, <a href="https://publications.waset.org/abstracts/search?q=revised%20weighting%20method" title=" revised weighting method"> revised weighting method</a>, <a href="https://publications.waset.org/abstracts/search?q=vendor%20selection" title=" vendor selection"> vendor selection</a> </p> <a href="https://publications.waset.org/abstracts/31124/vendor-selection-and-supply-quotas-determination-by-using-revised-weighting-method-and-multi-objective-programming-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31124.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">358</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">2400</span> Setting Uncertainty Conditions Using Singular Values for Repetitive Control in State Feedback</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20A.%20Alsubaie">Muhammad A. Alsubaie</a>, <a href="https://publications.waset.org/abstracts/search?q=Mubarak%20K.%20H.%20Alhajri"> Mubarak K. H. Alhajri</a>, <a href="https://publications.waset.org/abstracts/search?q=Tarek%20S.%20Altowaim"> Tarek S. Altowaim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A repetitive controller designed to accommodate periodic disturbances via state feedback is discussed. Periodic disturbances can be represented by a time delay model in a positive feedback loop acting on system output. A direct use of the small gain theorem solves the periodic disturbances problem via 1) isolating the delay model, 2) finding the overall system representation around the delay model and 3) designing a feedback controller that assures overall system stability and tracking error convergence. This paper addresses uncertainty conditions for the repetitive controller designed in state feedback in either past error feedforward or current error feedback using singular values. The uncertainty investigation is based on the overall system found and the stability condition associated with it; depending on the scheme used, to set an upper/lower limit weighting parameter. This creates a region that should not be exceeded in selecting the weighting parameter which in turns assures performance improvement against system uncertainty. Repetitive control problem can be described in lifted form. This allows the usage of singular values principle in setting the range for the weighting parameter selection. The Simulation results obtained show a tracking error convergence against dynamic system perturbation if the weighting parameter chosen is within the range obtained. Simulation results also show the advantage of weighting parameter usage compared to the case where it is omitted. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=model%20mismatch" title="model mismatch">model mismatch</a>, <a href="https://publications.waset.org/abstracts/search?q=repetitive%20control" title=" repetitive control"> repetitive control</a>, <a href="https://publications.waset.org/abstracts/search?q=singular%20values" title=" singular values"> singular values</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20feedback" title=" state feedback"> state feedback</a> </p> <a href="https://publications.waset.org/abstracts/99234/setting-uncertainty-conditions-using-singular-values-for-repetitive-control-in-state-feedback" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99234.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">155</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">2399</span> A Decision Support System to Detect the Lumbar Disc Disease on the Basis of Clinical MRI </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yavuz%20Unal">Yavuz Unal</a>, <a href="https://publications.waset.org/abstracts/search?q=Kemal%20Polat"> Kemal Polat</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Erdinc%20Kocer"> H. Erdinc Kocer</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=lumbar%20disc%20abnormality" title="lumbar disc abnormality">lumbar disc abnormality</a>, <a href="https://publications.waset.org/abstracts/search?q=lumbar%20MRI" title=" lumbar MRI"> lumbar MRI</a>, <a href="https://publications.waset.org/abstracts/search?q=lumbar%20spine" title=" lumbar spine"> lumbar spine</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20models" title=" hybrid models"> hybrid models</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20features" title=" hybrid features"> hybrid features</a>, <a href="https://publications.waset.org/abstracts/search?q=k-means%20clustering%20based%20feature%20weighting" title=" k-means clustering based feature weighting"> k-means clustering based feature weighting</a> </p> <a href="https://publications.waset.org/abstracts/24486/a-decision-support-system-to-detect-the-lumbar-disc-disease-on-the-basis-of-clinical-mri" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24486.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">2398</span> Multiobjective Economic Dispatch Using Optimal Weighting Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mandeep%20Kaur">Mandeep Kaur</a>, <a href="https://publications.waset.org/abstracts/search?q=Fatehgarh%20Sahib"> Fatehgarh Sahib</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of economic load dispatch is to allocate the required load demand between the available generation units such that the cost of operation is minimized. It is an optimization problem to find the most economical schedule of the generating units while satisfying load demand and operational constraints. The multiobjective optimization problem in which the engineer’s goal is to maximize or minimize not a single objective function but several objective functions simultaneously. The purpose of multiobjective problems in the mathematical programming framework is to optimize the different objective functions. Many approaches and methods have been proposed in recent years to solve multiobjective optimization problems. Weighting method has been applied to convert multiobjective optimization problems into scalar optimization. MATLAB 7.10 has been used to write the code for the complete algorithm with the help of genetic algorithm (GA). The validity of the proposed method has been demonstrated on a three-unit power system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=economic%20load%20dispatch" title="economic load dispatch">economic load dispatch</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=generating%20units" title=" generating units"> generating units</a>, <a href="https://publications.waset.org/abstracts/search?q=multiobjective%20optimization" title=" multiobjective optimization"> multiobjective optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=weighting%20method" title=" weighting method"> weighting method</a> </p> <a href="https://publications.waset.org/abstracts/117420/multiobjective-economic-dispatch-using-optimal-weighting-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/117420.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">150</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">2397</span> Prioritization in a Maintenance, Repair and Overhaul (MRO) System Based on Fuzzy Logic at Iran Khodro (IKCO)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Izadi%20Banafsheh">Izadi Banafsheh</a>, <a href="https://publications.waset.org/abstracts/search?q=Sedaghat%20Reza"> Sedaghat Reza</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Maintenance, Repair, and Overhaul (MRO) of machinery are a key recent issue concerning the automotive industry. It has always been a debated question what order or priority should be adopted for the MRO of machinery. This study attempts to examine several criteria including process sensitivity, average time between machine failures, average duration of repair, availability of parts, availability of maintenance personnel and workload through a literature review and experts survey so as to determine the condition of the machine. According to the mentioned criteria, the machinery were ranked in four modes below: A) Need for inspection, B) Need for minor repair, C) Need for part replacement, and D) Need for major repair. The Fuzzy AHP was employed to determine the weighting of criteria. At the end, the obtained weights were ranked through the AHP for each criterion, three groups were specified: shaving machines, assembly and painting in four modes. The statistical population comprises the elite in the Iranian automotive industry at IKCO covering operation managers, CEOs and maintenance professionals who are highly specialized in MRO and perfectly knowledgeable in how the machinery function. The information required for this study were collected from both desk research and field review, which eventually led to construction of a questionnaire handed out to the sample respondents in order to collect information on the subject matter. The results of the AHP for weighting the criteria revealed that the availability of maintenance personnel was the top priority at coefficient of 0.206, while the process sensitivity took the last priority at coefficient of 0.066. Furthermore, the results of TOPSIS for prioritizing the IKCO machinery suggested that at the mode where there is need for inspection, the assembly machines took the top priority while paining machines took the third priority. As for the mode where there is need for minor repairs, the assembly machines took the top priority while the third priority belonged to the shaving machines. As for the mode where there is need for parts replacement, the assembly machines took the top priority while the third belonged to the paining machinery. Finally, as for the mode where there is need for major repair, the assembly machines took the top priority while the third belonged to the paining machinery. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=maintenance" title="maintenance">maintenance</a>, <a href="https://publications.waset.org/abstracts/search?q=repair" title=" repair"> repair</a>, <a href="https://publications.waset.org/abstracts/search?q=overhaul" title=" overhaul"> overhaul</a>, <a href="https://publications.waset.org/abstracts/search?q=MRO" title=" MRO"> MRO</a>, <a href="https://publications.waset.org/abstracts/search?q=prioritization%20of%20machinery" title=" prioritization of machinery"> prioritization of machinery</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic" title=" fuzzy logic"> fuzzy logic</a>, <a href="https://publications.waset.org/abstracts/search?q=AHP" title=" AHP"> AHP</a>, <a href="https://publications.waset.org/abstracts/search?q=TOPSIS" title=" TOPSIS"> TOPSIS</a> </p> <a href="https://publications.waset.org/abstracts/35379/prioritization-in-a-maintenance-repair-and-overhaul-mro-system-based-on-fuzzy-logic-at-iran-khodro-ikco" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35379.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">286</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">2396</span> Analysis of Rural Roads in Developing Countries Using Principal Component Analysis and Simple Average Technique in the Development of a Road Safety Performance Index</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Tufail">Muhammad Tufail</a>, <a href="https://publications.waset.org/abstracts/search?q=Jawad%20Hussain"> Jawad Hussain</a>, <a href="https://publications.waset.org/abstracts/search?q=Hammad%20Hussain"> Hammad Hussain</a>, <a href="https://publications.waset.org/abstracts/search?q=Imran%20Hafeez"> Imran Hafeez</a>, <a href="https://publications.waset.org/abstracts/search?q=Naveed%20Ahmad"> Naveed Ahmad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Road safety performance index is a composite index which combines various indicators of road safety into single number. Development of a road safety performance index using appropriate safety performance indicators is essential to enhance road safety. However, a road safety performance index in developing countries has not been given as much priority as needed. The primary objective of this research is to develop a general Road Safety Performance Index (RSPI) for developing countries based on the facility as well as behavior of road user. The secondary objectives include finding the critical inputs in the RSPI and finding the better method of making the index. In this study, the RSPI is developed by selecting four main safety performance indicators i.e., protective system (seat belt, helmet etc.), road (road width, signalized intersections, number of lanes, speed limit), number of pedestrians, and number of vehicles. Data on these four safety performance indicators were collected using observation survey on a 20 km road section of the National Highway N-125 road Taxila, Pakistan. For the development of this composite index, two methods are used: a) Principal Component Analysis (PCA) and b) Equal Weighting (EW) method. PCA is used for extraction, weighting, and linear aggregation of indicators to obtain a single value. An individual index score was calculated for each road section by multiplication of weights and standardized values of each safety performance indicator. However, Simple Average technique was used for weighting and linear aggregation of indicators to develop a RSPI. The road sections are ranked according to RSPI scores using both methods. The two weighting methods are compared, and the PCA method is found to be much more reliable than the Simple Average Technique. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=indicators" title="indicators">indicators</a>, <a href="https://publications.waset.org/abstracts/search?q=aggregation" title=" aggregation"> aggregation</a>, <a href="https://publications.waset.org/abstracts/search?q=principle%20component%20analysis" title=" principle component analysis"> principle component analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=weighting" title=" weighting"> weighting</a>, <a href="https://publications.waset.org/abstracts/search?q=index%20score" title=" index score"> index score</a> </p> <a href="https://publications.waset.org/abstracts/132175/analysis-of-rural-roads-in-developing-countries-using-principal-component-analysis-and-simple-average-technique-in-the-development-of-a-road-safety-performance-index" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132175.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">157</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">2395</span> On Coverage Probability of Confidence Intervals for the Normal Mean with Known Coefficient of Variation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Suparat%20Niwitpong">Suparat Niwitpong</a>, <a href="https://publications.waset.org/abstracts/search?q=Sa-aat%20Niwitpong"> Sa-aat Niwitpong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Statistical inference of normal mean with known coefficient of variation has been investigated recently. This phenomenon occurs normally in environment and agriculture experiments when the scientist knows the coefficient of variation of their experiments. In this paper, we constructed new confidence intervals for the normal population mean with known coefficient of variation. We also derived analytic expressions for the coverage probability of each confidence interval. To confirm our theoretical results, Monte Carlo simulation will be used to assess the performance of these intervals based on their coverage probabilities. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=confidence%20interval" title="confidence interval">confidence interval</a>, <a href="https://publications.waset.org/abstracts/search?q=coverage%20probability" title=" coverage probability"> coverage probability</a>, <a href="https://publications.waset.org/abstracts/search?q=expected%20length" title=" expected length"> expected length</a>, <a href="https://publications.waset.org/abstracts/search?q=known%0D%0Acoefficient%20of%20variation" title=" known coefficient of variation"> known coefficient of variation</a> </p> <a href="https://publications.waset.org/abstracts/11176/on-coverage-probability-of-confidence-intervals-for-the-normal-mean-with-known-coefficient-of-variation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11176.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">2394</span> Investigation of the Turbulent Cavitating Flows from the Viewpoint of the Lift Coefficient</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ping-Ben%20Liu">Ping-Ben Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Chien-Chou%20Tseng"> Chien-Chou Tseng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The objective of this study is to investigate the relationship between the lift coefficient and dynamic behaviors of cavitating flow around a two-dimensional Clark Y hydrofoil at 8° angle of attack, cavitation number of 0.8, and Reynolds number of 7.10⁵. The flow field is investigated numerically by using a vapor transfer equation and a modified turbulence model which applies the filter and local density correction. The results including time-averaged lift/drag coefficient and shedding frequency agree well with experimental observations, which confirmed the reliability of this simulation. According to the variation of lift coefficient, the cycle which consists of growth and shedding of cavitation can be divided into three stages, and the lift coefficient at each stage behaves similarly due to the formation and shedding of the cavity around the trailing edge. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Computational%20Fluid%20Dynamics" title="Computational Fluid Dynamics">Computational Fluid Dynamics</a>, <a href="https://publications.waset.org/abstracts/search?q=cavitation" title=" cavitation"> cavitation</a>, <a href="https://publications.waset.org/abstracts/search?q=turbulence" title=" turbulence"> turbulence</a>, <a href="https://publications.waset.org/abstracts/search?q=lift%20coefficient" title=" lift coefficient"> lift coefficient</a> </p> <a href="https://publications.waset.org/abstracts/70047/investigation-of-the-turbulent-cavitating-flows-from-the-viewpoint-of-the-lift-coefficient" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70047.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">350</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">2393</span> Simplified Stress Gradient Method for Stress-Intensity Factor Determination </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jeries%20J.%20Abou-Hanna">Jeries J. Abou-Hanna</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Several techniques exist for determining stress-intensity factors in linear elastic fracture mechanics analysis. These techniques are based on analytical, numerical, and empirical approaches that have been well documented in literature and engineering handbooks. However, not all techniques share the same merit. In addition to overly-conservative results, the numerical methods that require extensive computational effort, and those requiring copious user parameters hinder practicing engineers from efficiently evaluating stress-intensity factors. This paper investigates the prospects of reducing the complexity and required variables to determine stress-intensity factors through the utilization of the stress gradient and a weighting function. The heart of this work resides in the understanding that fracture emanating from stress concentration locations cannot be explained by a single maximum stress value approach, but requires use of a critical volume in which the crack exists. In order to understand the effectiveness of this technique, this study investigated components of different notch geometry and varying levels of stress gradients. Two forms of weighting functions were employed to determine stress-intensity factors and results were compared to analytical exact methods. The results indicated that the “exponential” weighting function was superior to the “absolute” weighting function. An error band +/- 10% was met for cases ranging from a steep stress gradient in a sharp v-notch to the less severe stress transitions of a large circular notch. The incorporation of the proposed method has shown to be a worthwhile consideration. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fracture%20mechanics" title="fracture mechanics">fracture mechanics</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=stress%20intensity%20factor" title=" stress intensity factor"> stress intensity factor</a>, <a href="https://publications.waset.org/abstracts/search?q=stress%20gradient" title=" stress gradient"> stress gradient</a> </p> <a href="https://publications.waset.org/abstracts/110572/simplified-stress-gradient-method-for-stress-intensity-factor-determination" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110572.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">135</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">2392</span> Evaluating the Permeability Coefficient of Sandy Soil for Grouting to Reinforce Soft Soil in Binh Duong, Vietnam</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Trung%20Le%20Thanh">Trung Le Thanh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Soil permeability coefficient is an important parameter that affects the effectiveness of mortar restoration work to reinforce soft soil. Currently, there are many methods to determine the permeability coefficient of ground through laboratory and field experiments. However, the value of the permeability coefficient is determined very differently depending on the geology in general and the sand base in particular. This article presents how to determine the permeability coefficient of sand foundation in Phu My Ward, Tan Uyen City, Binh Duong. The author analyzes and evaluates the advantages and disadvantages of assessment methods based on the data and results obtained, and on that basis recommends a suitable method for determining the permeability coefficient for sand foundations. The research results serve the evaluation of the effectiveness of grouting to reinforce soft ground in general, and grouting of bored piles in particular. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=permeability%20coefficient" title="permeability coefficient">permeability coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=soft%20soil" title=" soft soil"> soft soil</a>, <a href="https://publications.waset.org/abstracts/search?q=shaft%20grouting" title=" shaft grouting"> shaft grouting</a>, <a href="https://publications.waset.org/abstracts/search?q=post%20grouting" title=" post grouting"> post grouting</a>, <a href="https://publications.waset.org/abstracts/search?q=jet%20grouting" title=" jet grouting"> jet grouting</a> </p> <a href="https://publications.waset.org/abstracts/173939/evaluating-the-permeability-coefficient-of-sandy-soil-for-grouting-to-reinforce-soft-soil-in-binh-duong-vietnam" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/173939.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">74</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">2391</span> Optimal Tuning of Linear Quadratic Regulator Controller Using a Particle Swarm Optimization for Two-Rotor Aerodynamical System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ayad%20Al-Mahturi">Ayad Al-Mahturi</a>, <a href="https://publications.waset.org/abstracts/search?q=Herman%20Wahid"> Herman Wahid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an optimal state feedback controller based on Linear Quadratic Regulator (LQR) for a two-rotor aero-dynamical system (TRAS). TRAS is a highly nonlinear multi-input multi-output (MIMO) system with two degrees of freedom and cross coupling. There are two parameters that define the behavior of LQR controller: state weighting matrix and control weighting matrix. The two parameters influence the performance of LQR. Particle Swarm Optimization (PSO) is proposed to optimally tune weighting matrices of LQR. The major concern of using LQR controller is to stabilize the TRAS by making the beam move quickly and accurately for tracking a trajectory or to reach a desired altitude. The simulation results were carried out in MATLAB/Simulink. The system is decoupled into two single-input single-output (SISO) systems. Comparing the performance of the optimized proportional, integral and derivative (PID) controller provided by INTECO, results depict that LQR controller gives a better performance in terms of both transient and steady state responses when PSO is performed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=LQR%20controller" title="LQR controller">LQR controller</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20control" title=" optimal control"> optimal control</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimization%20%28PSO%29" title=" particle swarm optimization (PSO)"> particle swarm optimization (PSO)</a>, <a href="https://publications.waset.org/abstracts/search?q=two%20rotor%20aero-dynamical%20system%20%28TRAS%29" title=" two rotor aero-dynamical system (TRAS)"> two rotor aero-dynamical system (TRAS)</a> </p> <a href="https://publications.waset.org/abstracts/65313/optimal-tuning-of-linear-quadratic-regulator-controller-using-a-particle-swarm-optimization-for-two-rotor-aerodynamical-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65313.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">322</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">2390</span> Predicting Trapezoidal Weir Discharge Coefficient Using Evolutionary Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20Roushanger">K. Roushanger</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Soleymanzadeh"> A. Soleymanzadeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Weirs are structures often used in irrigation techniques, sewer networks and flood protection. However, the hydraulic behavior of this type of weir is complex and difficult to predict accurately. An accurate flow prediction over a weir mainly depends on the proper estimation of discharge coefficient. In this study, the Genetic Expression Programming (GEP) approach was used for predicting trapezoidal and rectangular sharp-crested side weirs discharge coefficient. Three different performance indexes are used as comparing criteria for the evaluation of the model’s performances. The obtained results approved capability of GEP in prediction of trapezoidal and rectangular side weirs discharge coefficient. The results also revealed the influence of downstream Froude number for trapezoidal weir and upstream Froude number for rectangular weir in prediction of the discharge coefficient for both of side weirs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=discharge%20coefficient" title="discharge coefficient">discharge coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20expression%20programming" title=" genetic expression programming"> genetic expression programming</a>, <a href="https://publications.waset.org/abstracts/search?q=trapezoidal%20weir" title=" trapezoidal weir"> trapezoidal weir</a> </p> <a href="https://publications.waset.org/abstracts/61052/predicting-trapezoidal-weir-discharge-coefficient-using-evolutionary-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61052.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">387</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">2389</span> Hybrid Weighted Multiple Attribute Decision Making Handover Method for Heterogeneous Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohanad%20Alhabo">Mohanad Alhabo</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20Zhang"> Li Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Naveed%20Nawaz"> Naveed Nawaz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Small cell deployment in 5G networks is a promising technology to enhance capacity and coverage. However, unplanned deployment may cause high interference levels and high number of unnecessary handovers, which in turn will result in an increase in the signalling overhead. To guarantee service continuity, minimize unnecessary handovers, and reduce signalling overhead in heterogeneous networks, it is essential to properly model the handover decision problem. In this paper, we model the handover decision according to Multiple Attribute Decision Making (MADM) method, specifically Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). In this paper, we propose a hybrid TOPSIS method to control the handover in heterogeneous network. The proposed method adopts a hybrid weighting, which is a combination of entropy and standard deviation. A hybrid weighting control parameter is introduced to balance the impact of the standard deviation and entropy weighting on the network selection process and the overall performance. Our proposed method shows better performance, in terms of the number of frequent handovers and the mean user throughput, compared to the existing methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=handover" title="handover">handover</a>, <a href="https://publications.waset.org/abstracts/search?q=HetNets" title=" HetNets"> HetNets</a>, <a href="https://publications.waset.org/abstracts/search?q=interference" title=" interference"> interference</a>, <a href="https://publications.waset.org/abstracts/search?q=MADM" title=" MADM"> MADM</a>, <a href="https://publications.waset.org/abstracts/search?q=small%20cells" title=" small cells"> small cells</a>, <a href="https://publications.waset.org/abstracts/search?q=TOPSIS" title=" TOPSIS"> TOPSIS</a>, <a href="https://publications.waset.org/abstracts/search?q=weight" title=" weight"> weight</a> </p> <a href="https://publications.waset.org/abstracts/129187/hybrid-weighted-multiple-attribute-decision-making-handover-method-for-heterogeneous-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/129187.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">149</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">2388</span> Bag of Words Representation Based on Weighting Useful Visual Words</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fatma%20Abdedayem">Fatma Abdedayem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The most effective and efficient methods in image categorization are almost based on bag-of-words (BOW) which presents image by a histogram of occurrence of visual words. In this paper, we propose a novel extension to this method. Firstly, we extract features in multi-scales by applying a color local descriptor named opponent-SIFT. Secondly, in order to represent image we use Spatial Pyramid Representation (SPR) and an extension to the BOW method which based on weighting visual words. Typically, the visual words are weighted during histogram assignment by computing the ratio of their occurrences in the image to the occurrences in the background. Finally, according to classical BOW retrieval framework, only a few words of the vocabulary is useful for image representation. Therefore, we select the useful weighted visual words that respect the threshold value. Experimentally, the algorithm is tested by using different image classes of PASCAL VOC 2007 and is compared against the classical bag-of-visual-words algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=BOW" title="BOW">BOW</a>, <a href="https://publications.waset.org/abstracts/search?q=useful%20visual%20words" title=" useful visual words"> useful visual words</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20visual%20words" title=" weighted visual words"> weighted visual words</a>, <a href="https://publications.waset.org/abstracts/search?q=bag%20of%20visual%20words" title=" bag of visual words"> bag of visual words</a> </p> <a href="https://publications.waset.org/abstracts/14009/bag-of-words-representation-based-on-weighting-useful-visual-words" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14009.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">436</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">2387</span> Numerical Study of Flow around Flat Tube between Parallel Walls</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamidreza%20Bayat">Hamidreza Bayat</a>, <a href="https://publications.waset.org/abstracts/search?q=Arash%20Mirabdolah%20Lavasani"> Arash Mirabdolah Lavasani</a>, <a href="https://publications.waset.org/abstracts/search?q=Meysam%20Bolhasani"> Meysam Bolhasani</a>, <a href="https://publications.waset.org/abstracts/search?q=Sajad%20Moosavi"> Sajad Moosavi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Flow around a flat tube is studied numerically. Reynolds number is defined base on equivalent circular tube and it is varied in range of 100 to 300. Equations are solved by using finite volume method and results are presented in form of drag and lift coefficient. Results show that drag coefficient of flat tube is up to 66% lower than circular tube with equivalent diameter. In addition, by increasing l/D from 1 to 2, the drag coefficient of flat tube is decreased about 14-27%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=laminar%20flow" title="laminar flow">laminar flow</a>, <a href="https://publications.waset.org/abstracts/search?q=flat-tube" title=" flat-tube"> flat-tube</a>, <a href="https://publications.waset.org/abstracts/search?q=drag%20coefficient" title=" drag coefficient"> drag coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=cross-flow" title=" cross-flow"> cross-flow</a>, <a href="https://publications.waset.org/abstracts/search?q=heat%20exchanger" title=" heat exchanger"> heat exchanger</a> </p> <a href="https://publications.waset.org/abstracts/14593/numerical-study-of-flow-around-flat-tube-between-parallel-walls" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14593.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">503</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">2386</span> Determinants of Probability Weighting and Probability Neglect: An Experimental Study of the Role of Emotions, Risk Perception, and Personality in Flood Insurance Demand</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Peter%20J.%20Robinson">Peter J. Robinson</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20J.%20Wouter%20Botzen"> W. J. Wouter Botzen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Individuals often over-weight low probabilities and under-weight moderate to high probabilities, however very low probabilities are either significantly over-weighted or neglected. Little is known about factors affecting probability weighting in Prospect Theory related to emotions specific to risk (anticipatory and anticipated emotions), the threshold of concern, as well as personality traits like locus of control. This study provides these insights by examining factors that influence probability weighting in the context of flood insurance demand in an economic experiment. In particular, we focus on determinants of flood probability neglect to provide recommendations for improved risk management. In addition, results obtained using real incentives and no performance-based payments are compared in the experiment with high experimental outcomes. Based on data collected from 1’041 Dutch homeowners, we find that: flood probability neglect is related to anticipated regret, worry and the threshold of concern. Moreover, locus of control and regret affect probabilistic pessimism. Nevertheless, we do not observe strong evidence that incentives influence flood probability neglect nor probability weighting. The results show that low, moderate and high flood probabilities are under-weighted, which is related to framing in the flooding context and the degree of realism respondents attach to high probability property damages. We suggest several policies to overcome psychological factors related to under-weighting flood probabilities to improve flood preparations. These include policies that promote better risk communication to enhance insurance decisions for individuals with a high threshold of concern, and education and information provision to change the behaviour of internal locus of control types as well as people who see insurance as an investment. Multi-year flood insurance may also prevent short-sighted behaviour of people who have a tendency to regret paying for insurance. Moreover, bundling low-probability/high-impact risks with more immediate risks may achieve an overall covered risk which is less likely to be judged as falling below thresholds of concern. These measures could aid the development of a flood insurance market in the Netherlands for which we find to be demand. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=flood%20insurance%20demand" title="flood insurance demand">flood insurance demand</a>, <a href="https://publications.waset.org/abstracts/search?q=prospect%20theory" title=" prospect theory"> prospect theory</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20perceptions" title=" risk perceptions"> risk perceptions</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20preferences" title=" risk preferences"> risk preferences</a> </p> <a href="https://publications.waset.org/abstracts/88728/determinants-of-probability-weighting-and-probability-neglect-an-experimental-study-of-the-role-of-emotions-risk-perception-and-personality-in-flood-insurance-demand" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88728.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">274</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">2385</span> The Design Optimization for Sound Absorption Material of Multi-Layer Structure</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Un-Hwan%20Park">Un-Hwan Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Jun-Hyeok%20Heo"> Jun-Hyeok Heo</a>, <a href="https://publications.waset.org/abstracts/search?q=In-Sung%20Lee"> In-Sung Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Tae-Hyeon%20Oh"> Tae-Hyeon Oh</a>, <a href="https://publications.waset.org/abstracts/search?q=Dae-Kyu%20Park"> Dae-Kyu Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sound absorbing material is used as automotive interior material. Sound absorption coefficient should be predicted to design it. But it is difficult to predict sound absorbing coefficient because it is comprised of several material layers. So, its targets are achieved through many experimental tunings. It causes a lot of cost and time. In this paper, we propose the process to estimate the sound absorption coefficient with multi-layer structure. In order to estimate the coefficient, physical properties of each material are used. These properties also use predicted values by Foam-X software using the sound absorption coefficient data measured by impedance tube. Since there are many physical properties and the measurement equipment is expensive, the values predicted by software are used. Through the measurement of the sound absorption coefficient of each material, its physical properties are calculated inversely. The properties of each material are used to calculate the sound absorption coefficient of the multi-layer material. Since the absorption coefficient of multi-layer can be calculated, optimization design is possible through simulation. Then, we will compare and analyze the calculated sound absorption coefficient with the data measured by scaled reverberation chamber and impedance tubes for a prototype. If this method is used when developing automotive interior materials with multi-layer structure, the development effort can be reduced because it can be optimized by simulation. So, cost and time can be saved. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sound%20absorption%20material" title="sound absorption material">sound absorption material</a>, <a href="https://publications.waset.org/abstracts/search?q=sound%20impedance%20tube" title=" sound impedance tube"> sound impedance tube</a>, <a href="https://publications.waset.org/abstracts/search?q=sound%20absorption%20coefficient" title=" sound absorption coefficient"> sound absorption coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization%20design" title=" optimization design"> optimization design</a> </p> <a href="https://publications.waset.org/abstracts/82871/the-design-optimization-for-sound-absorption-material-of-multi-layer-structure" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/82871.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">2384</span> Evaluating and Reducing Aircraft Technical Delays and Cancellations Impact on Reliability Operational: Case Study of Airline Operator</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adel%20A.%20Ghobbar">Adel A. Ghobbar</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20Bakkar"> Ahmad Bakkar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Although special care is given to maintenance, aircraft systems fail, and these failures cause delays and cancellations. The occurrence of Delays and Cancellations affects operators and manufacturers negatively. To reduce technical delays and cancellations, one should be able to determine the important systems causing them. The goal of this research is to find a method to define the most expensive delays and cancellations systems for Airline operators. A predictive model was introduced to forecast the failure and their impact after carrying out research that identifies relevant information to tackle the problems faced while answering the questions of this paper. Data were obtained from the manufacturers’ services reliability team database. Subsequently, delays and cancellations evaluation methods were identified. No cost estimation methods were used due to their complexity. The model was developed, and it takes into account the frequency of delays and cancellations and uses weighting factors to give an indication of the severity of their duration. The weighting factors are based on customer experience. The data Analysis approach has shown that delays and cancellations events are not seasonal and do not follow any specific trends. The use of weighting factor does have an influence on the shortlist over short periods (Monthly) but not the analyzed period of three years. Landing gear and the navigation system are among the top 3 factors causing delays and cancellations for all three aircraft types. The results did confirm that the cooperation between certain operators and manufacture reduce the impact of delays and cancellations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reliability" title="reliability">reliability</a>, <a href="https://publications.waset.org/abstracts/search?q=availability" title=" availability"> availability</a>, <a href="https://publications.waset.org/abstracts/search?q=delays%20%26%20cancellations" title=" delays & cancellations"> delays & cancellations</a>, <a href="https://publications.waset.org/abstracts/search?q=aircraft%20maintenance" title=" aircraft maintenance"> aircraft maintenance</a> </p> <a href="https://publications.waset.org/abstracts/108908/evaluating-and-reducing-aircraft-technical-delays-and-cancellations-impact-on-reliability-operational-case-study-of-airline-operator" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/108908.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">132</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">2383</span> A Study on the Determinants of Earnings Response Coefficient in an Emerging Market</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bita%20Mashayekhi">Bita Mashayekhi</a>, <a href="https://publications.waset.org/abstracts/search?q=Zeynab%20Lotfi%20Aghel"> Zeynab Lotfi Aghel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The determinants of Earnings Response Coefficient (ERC), including firm size, earnings growth, and earnings persistence are studied in this research. These determinants are supposed to be moderator variables that affect ERC and Return Response Coefficient. The research sample contains 82 Iranian listed companies in Tehran Stock Exchange (TSE) from 2001 to 2012. Gathered data have been processed by EVIEWS Software. Results show a significant positive relation between firm size and ERC, and also between earnings growth and ERC; however, there is no significant relation between earnings persistence and ERC. Also, the results show that ERC will be increased by firm size and earnings growth, but there is no relation between earnings persistence and ERC. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=earnings%20response%20coefficient%20%28ERC%29" title="earnings response coefficient (ERC)">earnings response coefficient (ERC)</a>, <a href="https://publications.waset.org/abstracts/search?q=return%20response%20coefficient%20%28RRC%29" title=" return response coefficient (RRC)"> return response coefficient (RRC)</a>, <a href="https://publications.waset.org/abstracts/search?q=firm%20size" title=" firm size"> firm size</a>, <a href="https://publications.waset.org/abstracts/search?q=earnings%20growth" title=" earnings growth"> earnings growth</a>, <a href="https://publications.waset.org/abstracts/search?q=earnings%20persistence" title=" earnings persistence"> earnings persistence</a> </p> <a href="https://publications.waset.org/abstracts/54086/a-study-on-the-determinants-of-earnings-response-coefficient-in-an-emerging-market" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54086.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">332</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">2382</span> Training a Neural Network Using Input Dropout with Aggressive Reweighting (IDAR) on Datasets with Many Useless Features</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Stylianos%20Kampakis">Stylianos Kampakis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a new algorithm for neural networks called “Input Dropout with Aggressive Re-weighting” (IDAR) aimed specifically at datasets with many useless features. IDAR combines two techniques (dropout of input neurons and aggressive re weighting) in order to eliminate the influence of noisy features. The technique can be seen as a generalization of dropout. The algorithm is tested on two different benchmark data sets: a noisy version of the iris dataset and the MADELON data set. Its performance is compared against three other popular techniques for dealing with useless features: L2 regularization, LASSO and random forests. The results demonstrate that IDAR can be an effective technique for handling data sets with many useless features. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=neural%20networks" title="neural networks">neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20selection" title=" feature selection"> feature selection</a>, <a href="https://publications.waset.org/abstracts/search?q=regularization" title=" regularization"> regularization</a>, <a href="https://publications.waset.org/abstracts/search?q=aggressive%20reweighting" title=" aggressive reweighting"> aggressive reweighting</a> </p> <a href="https://publications.waset.org/abstracts/20362/training-a-neural-network-using-input-dropout-with-aggressive-reweighting-idar-on-datasets-with-many-useless-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20362.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">455</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">2381</span> Documents Emotions Classification Model Based on TF-IDF Weighting Measure</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amr%20Mansour%20Mohsen">Amr Mansour Mohsen</a>, <a href="https://publications.waset.org/abstracts/search?q=Hesham%20Ahmed%20Hassan"> Hesham Ahmed Hassan</a>, <a href="https://publications.waset.org/abstracts/search?q=Amira%20M.%20Idrees"> Amira M. Idrees</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=emotion%20detection" title="emotion detection">emotion detection</a>, <a href="https://publications.waset.org/abstracts/search?q=TF-IDF" title=" TF-IDF"> TF-IDF</a>, <a href="https://publications.waset.org/abstracts/search?q=WEKA%20tool" title=" WEKA tool"> WEKA tool</a>, <a href="https://publications.waset.org/abstracts/search?q=classification%20algorithms" title=" classification algorithms"> classification algorithms</a> </p> <a href="https://publications.waset.org/abstracts/41563/documents-emotions-classification-model-based-on-tf-idf-weighting-measure" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41563.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">484</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">2380</span> Parameter Interactions in the Cumulative Prospect Theory: Fitting the Binary Choice Experiment Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elzbieta%20Babula">Elzbieta Babula</a>, <a href="https://publications.waset.org/abstracts/search?q=Juhyun%20Park"> Juhyun Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Tversky and Kahneman’s cumulative prospect theory assumes symmetric probability cumulation with regard to the reference point within decision weights. Theoretically, this model should be invariant under the change of the direction of probability cumulation. In the present study, this phenomenon is being investigated by creating a reference model that allows verifying the parameter interactions in the cumulative prospect theory specifications. The simultaneous parametric fitting of utility and weighting functions is applied to binary choice data from the experiment. The results show that the flexibility of the probability weighting function is a crucial characteristic allowing to prevent parameter interactions while estimating cumulative prospect theory. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=binary%20choice%20experiment" title="binary choice experiment">binary choice experiment</a>, <a href="https://publications.waset.org/abstracts/search?q=cumulative%20prospect%20theory" title=" cumulative prospect theory"> cumulative prospect theory</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20weights" title=" decision weights"> decision weights</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20interactions" title=" parameter interactions"> parameter interactions</a> </p> <a href="https://publications.waset.org/abstracts/139527/parameter-interactions-in-the-cumulative-prospect-theory-fitting-the-binary-choice-experiment-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/139527.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">2379</span> Multidisciplinary and Multilevel Design Methodology of Unmanned Aerial Vehicles using Enhanced Collaborative Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pedro%20F.%20Albuquerque">Pedro F. Albuquerque</a>, <a href="https://publications.waset.org/abstracts/search?q=Pedro%20V.%20Gamboa"> Pedro V. Gamboa</a>, <a href="https://publications.waset.org/abstracts/search?q=Miguel%20A.%20Silvestre"> Miguel A. Silvestre</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present work describes the implementation of the Enhanced Collaborative Optimization (ECO) multilevel architecture with a gradient-based optimization algorithm with the aim of performing a multidisciplinary design optimization of a generic unmanned aerial vehicle with morphing technologies. The concepts of weighting coefficient and a dynamic compatibility parameter are presented for the ECO architecture. A routine that calculates the aircraft performance for the user defined mission profile and vehicle’s performance requirements has been implemented using low fidelity models for the aerodynamics, stability, propulsion, weight, balance and flight performance. A benchmarking case study for evaluating the advantage of using a variable span wing within the optimization methodology developed is presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multidisciplinary" title="multidisciplinary">multidisciplinary</a>, <a href="https://publications.waset.org/abstracts/search?q=multilevel" title=" multilevel"> multilevel</a>, <a href="https://publications.waset.org/abstracts/search?q=morphing" title=" morphing"> morphing</a>, <a href="https://publications.waset.org/abstracts/search?q=enhanced%20collaborative%20optimization" title=" enhanced collaborative optimization"> enhanced collaborative optimization</a> </p> <a href="https://publications.waset.org/abstracts/18259/multidisciplinary-and-multilevel-design-methodology-of-unmanned-aerial-vehicles-using-enhanced-collaborative-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18259.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">929</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">2378</span> Effect of Drag Coefficient Models concerning Global Air-Sea Momentum Flux in Broad Wind Range including Extreme Wind Speeds</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Takeshi%20Takemoto">Takeshi Takemoto</a>, <a href="https://publications.waset.org/abstracts/search?q=Naoya%20Suzuki"> Naoya Suzuki</a>, <a href="https://publications.waset.org/abstracts/search?q=Naohisa%20Takagaki"> Naohisa Takagaki</a>, <a href="https://publications.waset.org/abstracts/search?q=Satoru%20Komori"> Satoru Komori</a>, <a href="https://publications.waset.org/abstracts/search?q=Masako%20Terui"> Masako Terui</a>, <a href="https://publications.waset.org/abstracts/search?q=George%20Truscott"> George Truscott</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Drag coefficient is an important parameter in order to correctly estimate the air-sea momentum flux. However, The parameterization of the drag coefficient hasn’t been established due to the variation in the field data. Instead, a number of drag coefficient model formulae have been proposed, even though almost all these models haven’t discussed the extreme wind speed range. With regards to such models, it is unclear how the drag coefficient changes in the extreme wind speed range as the wind speed increased. In this study, we investigated the effect of the drag coefficient models concerning the air-sea momentum flux in the extreme wind range on a global scale, comparing two different drag coefficient models. Interestingly, one model didn’t discuss the extreme wind speed range while the other model considered it. We found that the difference of the models in the annual global air-sea momentum flux was small because the occurrence frequency of strong wind was approximately 1% with a wind speed of 20m/s or more. However, we also discovered that the difference of the models was shown in the middle latitude where the annual mean air-sea momentum flux was large and the occurrence frequency of strong wind was high. In addition, the estimated data showed that the difference of the models in the drag coefficient was large in the extreme wind speed range and that the largest difference became 23% with a wind speed of 35m/s or more. These results clearly show that the difference of the two models concerning the drag coefficient has a significant impact on the estimation of a regional air-sea momentum flux in an extreme wind speed range such as that seen in a tropical cyclone environment. Furthermore, we estimated each air-sea momentum flux using several kinds of drag coefficient models. We will also provide data from an observation tower and result from CFD (Computational Fluid Dynamics) concerning the influence of wind flow at and around the place. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=air-sea%20interaction" title="air-sea interaction">air-sea interaction</a>, <a href="https://publications.waset.org/abstracts/search?q=drag%20coefficient" title=" drag coefficient"> drag coefficient</a>, <a href="https://publications.waset.org/abstracts/search?q=air-sea%20momentum%20flux" title=" air-sea momentum flux"> air-sea momentum flux</a>, <a href="https://publications.waset.org/abstracts/search?q=CFD%20%28Computational%20Fluid%20Dynamics%29" title=" CFD (Computational Fluid Dynamics)"> CFD (Computational Fluid Dynamics)</a> </p> <a href="https://publications.waset.org/abstracts/41397/effect-of-drag-coefficient-models-concerning-global-air-sea-momentum-flux-in-broad-wind-range-including-extreme-wind-speeds" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41397.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">371</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=weighting%20coefficient&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=weighting%20coefficient&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=weighting%20coefficient&page=4">4</a></li> <li class="page-item"><a class="page-link" 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