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function range</title> <meta name="description" content="Search results for: membership function range"> <meta name="keywords" content="membership function range"> <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 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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="membership function range"> <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> 11192</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: membership function range</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11192</span> Defuzzification of Periodic Membership Function on Circular Coordinates</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Takashi%20Mitsuishi">Takashi Mitsuishi</a>, <a href="https://publications.waset.org/abstracts/search?q=Koji%20Saigusa"> Koji Saigusa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents circular polar coordinates transformation of periodic fuzzy membership function. The purpose is identification of domain of periodic membership functions in consequent part of IF-THEN rules. The proposed methods are applied to the simple color construct system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=periodic%20membership%20function" title="periodic membership function">periodic membership function</a>, <a href="https://publications.waset.org/abstracts/search?q=polar%20coordinates%20transformation" title=" polar coordinates transformation"> polar coordinates transformation</a>, <a href="https://publications.waset.org/abstracts/search?q=defuzzification" title=" defuzzification"> defuzzification</a>, <a href="https://publications.waset.org/abstracts/search?q=circular%20coordinates" title=" circular coordinates"> circular coordinates</a> </p> <a href="https://publications.waset.org/abstracts/14722/defuzzification-of-periodic-membership-function-on-circular-coordinates" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14722.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">309</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">11191</span> Design of Membership Ranges for Fuzzy Logic Control of Refrigeration Cycle Driven by a Variable Speed Compressor</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Changho%20Han">Changho Han</a>, <a href="https://publications.waset.org/abstracts/search?q=Jaemin%20Lee"> Jaemin Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20Hua"> Li Hua</a>, <a href="https://publications.waset.org/abstracts/search?q=Seokkwon%20Jeong"> Seokkwon Jeong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Design of membership function ranges in fuzzy logic control (FLC) is presented for robust control of a variable speed refrigeration system (VSRS). The criterion values of the membership function ranges can be carried out from the static experimental data, and two different values are offered to compare control performance. Some simulations and real experiments for the VSRS were conducted to verify the validity of the designed membership functions. The experimental results showed good agreement with the simulation results, and the error change rate and its sampling time strongly affected the control performance at transient state of the VSRS. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=variable%20speed%20refrigeration%20system" title="variable speed refrigeration system">variable speed refrigeration system</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic%20control" title=" fuzzy logic control"> fuzzy logic control</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20function%20range" title=" membership function range"> membership function range</a>, <a href="https://publications.waset.org/abstracts/search?q=control%20performance" title=" control performance"> control performance</a> </p> <a href="https://publications.waset.org/abstracts/90707/design-of-membership-ranges-for-fuzzy-logic-control-of-refrigeration-cycle-driven-by-a-variable-speed-compressor" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/90707.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">265</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">11190</span> A Fuzzy Nonlinear Regression Model for Interval Type-2 Fuzzy Sets</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=O.%20Poleshchuk">O. Poleshchuk</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Komarov"> E. Komarov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=interval%20type-2%20fuzzy%20sets" title="interval type-2 fuzzy sets">interval type-2 fuzzy sets</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20regression" title=" fuzzy regression"> fuzzy regression</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20interval" title=" weighted interval"> weighted interval</a> </p> <a href="https://publications.waset.org/abstracts/6138/a-fuzzy-nonlinear-regression-model-for-interval-type-2-fuzzy-sets" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6138.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">373</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">11189</span> Transformation of Periodic Fuzzy Membership Function to Discrete Polygon on Circular Polar Coordinates</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Takashi%20Mitsuishi">Takashi Mitsuishi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fuzzy logic has gained acceptance in the recent years in the fields of social sciences and humanities such as psychology and linguistics because it can manage the fuzziness of words and human subjectivity in a logical manner. However, the major field of application of the fuzzy logic is control engineering as it is a part of the set theory and mathematical logic. Mamdani method, which is the most popular technique for approximate reasoning in the field of fuzzy control, is one of the ways to numerically represent the control afforded by human language and sensitivity and has been applied in various practical control plants. Fuzzy logic has been gradually developing as an artificial intelligence in different applications such as neural networks, expert systems, and operations research. The objects of inference vary for different application fields. Some of these include time, angle, color, symptom and medical condition whose fuzzy membership function is a periodic function. In the defuzzification stage, the domain of the membership function should be unique to obtain uniqueness its defuzzified value. However, if the domain of the periodic membership function is determined as unique, an unintuitive defuzzified value may be obtained as the inference result using the center of gravity method. Therefore, the authors propose a method of circular-polar-coordinates transformation and defuzzification of the periodic membership functions in this study. The transformation to circular polar coordinates simplifies the domain of the periodic membership function. Defuzzified value in circular polar coordinates is an argument. Furthermore, it is required that the argument is calculated from a closed plane figure which is a periodic membership function on the circular polar coordinates. If the closed plane figure is continuous with the continuity of the membership function, a significant amount of computation is required. Therefore, to simplify the practice example and significantly reduce the computational complexity, we have discretized the continuous interval and the membership function in this study. In this study, the following three methods are proposed to decide the argument from the discrete polygon which the continuous plane figure is transformed into. The first method provides an argument of a straight line passing through the origin and through the coordinate of the arithmetic mean of each coordinate of the polygon (physical center of gravity). The second one provides an argument of a straight line passing through the origin and the coordinate of the geometric center of gravity of the polygon. The third one provides an argument of a straight line passing through the origin bisecting the perimeter of the polygon (or the closed continuous plane figure). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=defuzzification" title="defuzzification">defuzzification</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20membership%20function" title=" fuzzy membership function"> fuzzy membership function</a>, <a href="https://publications.waset.org/abstracts/search?q=periodic%20function" title=" periodic function"> periodic function</a>, <a href="https://publications.waset.org/abstracts/search?q=polar%20coordinates%20transformation" title=" polar coordinates transformation"> polar coordinates transformation</a> </p> <a href="https://publications.waset.org/abstracts/67249/transformation-of-periodic-fuzzy-membership-function-to-discrete-polygon-on-circular-polar-coordinates" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/67249.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">363</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">11188</span> Similarity Based Membership of Elements to Uncertain Concept in Information System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Kamel%20El-Sayed">M. Kamel El-Sayed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The process of determining the degree of membership for an element to an uncertain concept has been found in many ways, using equivalence and symmetry relations in information systems. In the case of similarity, these methods did not take into account the degree of symmetry between elements. In this paper, we use a new definition for finding the membership based on the degree of symmetry. We provide an example to clarify the suggested methods and compare it with previous methods. This method opens the door to more accurate decisions in information systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=information%20system" title="information system">information system</a>, <a href="https://publications.waset.org/abstracts/search?q=uncertain%20concept" title=" uncertain concept"> uncertain concept</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20function" title=" membership function"> membership function</a>, <a href="https://publications.waset.org/abstracts/search?q=similarity%20relation" title=" similarity relation"> similarity relation</a>, <a href="https://publications.waset.org/abstracts/search?q=degree%20of%20similarity" title=" degree of similarity"> degree of similarity</a> </p> <a href="https://publications.waset.org/abstracts/88086/similarity-based-membership-of-elements-to-uncertain-concept-in-information-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88086.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">223</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">11187</span> Study on Optimal Control Strategy of PM2.5 in Wuhan, China</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qiuling%20Xie">Qiuling Xie</a>, <a href="https://publications.waset.org/abstracts/search?q=Shanliang%20Zhu"> Shanliang Zhu</a>, <a href="https://publications.waset.org/abstracts/search?q=Zongdi%20Sun"> Zongdi Sun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we analyzed the correlation relationship among PM2.5 from other five Air Quality Indices (AQIs) based on the grey relational degree, and built a multivariate nonlinear regression equation model of PM2.5 and the five monitoring indexes. For the optimal control problem of PM2.5, we took the partial large Cauchy distribution of membership equation as satisfaction function. We established a nonlinear programming model with the goal of maximum performance to price ratio. And the optimal control scheme is given. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=grey%20relational%20degree" title="grey relational degree">grey relational degree</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20linear%20regression" title=" multiple linear regression"> multiple linear regression</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20function" title=" membership function"> membership function</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20programming" title=" nonlinear programming"> nonlinear programming</a> </p> <a href="https://publications.waset.org/abstracts/54538/study-on-optimal-control-strategy-of-pm25-in-wuhan-china" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54538.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">299</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11186</span> Electrical Load Estimation Using Estimated Fuzzy Linear Parameters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bader%20Alkandari">Bader Alkandari</a>, <a href="https://publications.waset.org/abstracts/search?q=Jamal%20Y.%20Madouh"> Jamal Y. Madouh</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20M.%20Alkandari"> Ahmad M. Alkandari</a>, <a href="https://publications.waset.org/abstracts/search?q=Anwar%20A.%20Alnaqi"> Anwar A. Alnaqi </a> </p> <p class="card-text"><strong>Abstract:</strong></p> A new formulation of fuzzy linear estimation problem is presented. It is formulated as a linear programming problem. The objective is to minimize the spread of the data points, taking into consideration the type of the membership function of the fuzzy parameters to satisfy the constraints on each measurement point and to insure that the original membership is included in the estimated membership. Different models are developed for a fuzzy triangular membership. The proposed models are applied to different examples from the area of fuzzy linear regression and finally to different examples for estimating the electrical load on a busbar. It had been found that the proposed technique is more suited for electrical load estimation, since the nature of the load is characterized by the uncertainty and vagueness. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20regression" title="fuzzy regression">fuzzy regression</a>, <a href="https://publications.waset.org/abstracts/search?q=load%20estimation" title=" load estimation"> load estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20linear%20parameters" title=" fuzzy linear parameters"> fuzzy linear parameters</a>, <a href="https://publications.waset.org/abstracts/search?q=electrical%20load%20estimation" title=" electrical load estimation"> electrical load estimation</a> </p> <a href="https://publications.waset.org/abstracts/18341/electrical-load-estimation-using-estimated-fuzzy-linear-parameters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18341.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">540</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">11185</span> A Different Approach to Optimize Fuzzy Membership Functions with Extended FIR Filter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jun-Ho%20Chung">Jun-Ho Chung</a>, <a href="https://publications.waset.org/abstracts/search?q=Sung-Hyun%20Yoo"> Sung-Hyun Yoo</a>, <a href="https://publications.waset.org/abstracts/search?q=In-Hwan%20Choi"> In-Hwan Choi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hyun-Kook%20Lee"> Hyun-Kook Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Moon-Kyu%20Song"> Moon-Kyu Song</a>, <a href="https://publications.waset.org/abstracts/search?q=Choon-Ki%20Ahn"> Choon-Ki Ahn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The extended finite impulse response (EFIR) filter is addressed to optimize membership functions (MFs) of the fuzzy model that has strong nonlinearity. MFs are important parts of the fuzzy logic system (FLS) and, thus optimizing MFs of FLS is one of approaches to improve the performance of output. We employ the EFIR as an alternative optimization option to nonlinear fuzzy model. The performance of EFIR is demonstrated on a fuzzy cruise control via a numerical example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic%20system" title="fuzzy logic system">fuzzy logic system</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20function" title=" membership function"> membership function</a>, <a href="https://publications.waset.org/abstracts/search?q=extended%20FIR%20filter" title=" extended FIR filter"> extended FIR filter</a> </p> <a href="https://publications.waset.org/abstracts/42104/a-different-approach-to-optimize-fuzzy-membership-functions-with-extended-fir-filter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42104.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">723</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">11184</span> Influence of Telkom Membership Card Customer Perceived Value on Retaining PT. Telkom Indonesia's Customer in 2013-2014</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eka%20Yuliana">Eka Yuliana</a>, <a href="https://publications.waset.org/abstracts/search?q=Siska%20Shabrina%20Julyan"> Siska Shabrina Julyan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The competitive environment and high customer’s churn rate in telecommunication industries lead Indonesian telecommunication companies become strive to offer products with more value. Offering product with more value can encourage customers to keep using the companies product. One of way to retain customer is give a membership card to the customers as practiced by PT. Telkom by giving Telkom Membership Card to PT. Telkom loyal customer. This study aims to determine the influence of Telkom Membership Card customer perceived value on retaining PT. Telkom Indonesia’s customer in 2013-2014 by using quantitative method with causal study. Analythical technique used in this study is Structural Equation Modelling (SEM) to test the causal relationship with 216 owner of Telkom Membership Card in Indonesia. This study conclude that: (i) Customer perceived value on Telkom Membership Card is located in fair value zone, (ii) PT. Telkom efforts in order to retain the customers is classified as good, (iii) Customer perceived value is influencing the effort to retain the customer with the probability value less than 0.05 and level of influence 69%. Based on result of this study, PT. Telkom should (i) Improve Telkom Membership Card’s promotion because not all customer of PT. Telkom have the membership card. (iia) Adding Telkom Membership Card’s benefit such as discount at various merchant (iib) Making call center for member of Telkom Membership Card (iii) PT. Telkom should be ensure availability of their service. (iv) PT. Telkom should make a priority to customer who have telkom membership card and offers a better service.For future research should be use different variables. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=customer%20perceived%20value" title="customer perceived value">customer perceived value</a>, <a href="https://publications.waset.org/abstracts/search?q=customer%20retention" title=" customer retention"> customer retention</a>, <a href="https://publications.waset.org/abstracts/search?q=marketing" title=" marketing"> marketing</a>, <a href="https://publications.waset.org/abstracts/search?q=relationship%20marketing" title=" relationship marketing"> relationship marketing</a> </p> <a href="https://publications.waset.org/abstracts/31461/influence-of-telkom-membership-card-customer-perceived-value-on-retaining-pt-telkom-indonesias-customer-in-2013-2014" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31461.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">11183</span> Membership Surface and Arithmetic Operations of Imprecise Matrix</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dhruba%20Das">Dhruba Das</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a method has been developed to construct the membership surfaces of row and column vectors and arithmetic operations of imprecise matrix. A matrix with imprecise elements would be called an imprecise matrix. The membership surface of imprecise vector has been already shown based on Randomness-Impreciseness Consistency Principle. The Randomness- Impreciseness Consistency Principle leads to defining a normal law of impreciseness using two different laws of randomness. In this paper, the author has shown row and column membership surfaces and arithmetic operations of imprecise matrix and demonstrated with the help of numerical example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=imprecise%20number" title="imprecise number">imprecise number</a>, <a href="https://publications.waset.org/abstracts/search?q=imprecise%20vector" title=" imprecise vector"> imprecise vector</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20surface" title=" membership surface"> membership surface</a>, <a href="https://publications.waset.org/abstracts/search?q=imprecise%20matrix" title=" imprecise matrix"> imprecise matrix</a> </p> <a href="https://publications.waset.org/abstracts/33597/membership-surface-and-arithmetic-operations-of-imprecise-matrix" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33597.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">386</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">11182</span> Imprecise Vector: The Case of Subnormality</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dhruba%20Das">Dhruba Das</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this article, the author has put forward the actual mathematical explanation of subnormal imprecise vector. Every subnormal imprecise vector has to be defined with reference to a membership surface. The membership surface of normal imprecise vector has already defined based on Randomness-Impreciseness Consistency Principle. The Randomness- Impreciseness Consistency Principle leads to defining a normal law of impreciseness using two different laws of randomness. A normal imprecise vector is a special case of subnormal imprecise vector. Nothing however is available in the literature about the membership surface when a subnormal imprecise vector is defined. The author has shown here how to construct the membership surface of a subnormal imprecise vector. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=imprecise%20vector" title="imprecise vector">imprecise vector</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20surface" title=" membership surface"> membership surface</a>, <a href="https://publications.waset.org/abstracts/search?q=subnormal%20imprecise%20number" title=" subnormal imprecise number"> subnormal imprecise number</a>, <a href="https://publications.waset.org/abstracts/search?q=subnormal%20imprecise%20vector" title=" subnormal imprecise vector"> subnormal imprecise vector</a> </p> <a href="https://publications.waset.org/abstracts/44144/imprecise-vector-the-case-of-subnormality" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44144.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">320</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">11181</span> A Relative Entropy Regularization Approach for Fuzzy C-Means Clustering Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ouafa%20Amira">Ouafa Amira</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiangshe%20Zhang"> Jiangshe Zhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Clustering is an unsupervised machine learning technique; its aim is to extract the data structures, in which similar data objects are grouped in the same cluster, whereas dissimilar objects are grouped in different clusters. Clustering methods are widely utilized in different fields, such as: image processing, computer vision , and pattern recognition, etc. Fuzzy c-means clustering (fcm) is one of the most well known fuzzy clustering methods. It is based on solving an optimization problem, in which a minimization of a given cost function has been studied. This minimization aims to decrease the dissimilarity inside clusters, where the dissimilarity here is measured by the distances between data objects and cluster centers. The degree of belonging of a data point in a cluster is measured by a membership function which is included in the interval [0, 1]. In fcm clustering, the membership degree is constrained with the condition that the sum of a data object’s memberships in all clusters must be equal to one. This constraint can cause several problems, specially when our data objects are included in a noisy space. Regularization approach took a part in fuzzy c-means clustering technique. This process introduces an additional information in order to solve an ill-posed optimization problem. In this study, we focus on regularization by relative entropy approach, where in our optimization problem we aim to minimize the dissimilarity inside clusters. Finding an appropriate membership degree to each data object is our objective, because an appropriate membership degree leads to an accurate clustering result. Our clustering results in synthetic data sets, gaussian based data sets, and real world data sets show that our proposed model achieves a good accuracy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clustering" title="clustering">clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20c-means" title=" fuzzy c-means"> fuzzy c-means</a>, <a href="https://publications.waset.org/abstracts/search?q=regularization" title=" regularization"> regularization</a>, <a href="https://publications.waset.org/abstracts/search?q=relative%20entropy" title=" relative entropy"> relative entropy</a> </p> <a href="https://publications.waset.org/abstracts/96361/a-relative-entropy-regularization-approach-for-fuzzy-c-means-clustering-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/96361.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">259</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">11180</span> Prediction of Coronary Heart Disease Using Fuzzy Logic</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elda%20Maraj">Elda Maraj</a>, <a href="https://publications.waset.org/abstracts/search?q=Shkelqim%20Kuka"> Shkelqim Kuka</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Coronary heart disease causes many deaths in the world. Unfortunately, this problem will continue to increase in the future. In this paper, a fuzzy logic model to predict coronary heart disease is presented. This model has been developed with seven input variables and one output variable that was implemented for 30 patients in Albania. Here fuzzy logic toolbox of MATLAB is used. Fuzzy model inputs are considered as cholesterol, blood pressure, physical activity, age, BMI, smoking, and diabetes, whereas the output is the disease classification. The fuzzy sets and membership functions are chosen in an appropriate manner. Centroid method is used for defuzzification. The database is taken from University Hospital Center "Mother Teresa" in Tirana, Albania. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=coronary%20heart%20disease" title="coronary heart disease">coronary heart disease</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20logic%20toolbox" title=" fuzzy logic toolbox"> fuzzy logic toolbox</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20function" title=" membership function"> membership function</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction%20model" title=" prediction model"> prediction model</a> </p> <a href="https://publications.waset.org/abstracts/148911/prediction-of-coronary-heart-disease-using-fuzzy-logic" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/148911.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">161</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">11179</span> Psychological Sense of School Membership and Coping Ability as Predictors of Multidimensional Life Satisfaction among School Children</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mary%20Banke%20Iyabo%20Omoniyi">Mary Banke Iyabo Omoniyi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Children in the developing countries have complex social, economic, political and environmental contexts that create a wide range of challenges for school children to surmount as they journey through school from childhood to adolescent. Many of these children have little or no personal resources and social support to confront these challenges. This study employed a descriptive research design of survey type to investigate the psychological sense of school membership and coping skills as they relate to the multidimensional life satisfaction of the school children. The sample consists of 835 school children with the age range of 7-11 years who were randomly selected from twenty schools in Ondo state, Nigeria. The instrument for data collection was a questionnaire consisting of 4 sections A, B, C and D. Section A contained items on the children’s bio-data (Age, School, father’s and mother’s educational qualifications), section B is the Multidimensional Children Life Satisfaction Questionnaire (MCLSQ) with a 20 item Likert type scale. The response format range from Never= 1 to Almost always =4. The (MCLSQ) was designed to provide profile of children satisfaction with important domains of (school, family and friends). Section C is the Psychological Sense of School Membership Questionnaire (PSSMQ) with 18 items having response format ranging from Not at true=1 to completely true=5. While section D is the Self-Report Coping Questionnaire (SRCQ) which has 16 items with response ranging from Never =1 to Always=5. The instrument has a test-retest reliability coefficient of r = 0.87 while the sectional reliabilities for MCLSQ, PSSMQ and SRCQ are 0.86, 0.92 and 0.89 respectively. The results indicated that self-report coping skill was significantly correlated with multidimensional life satisfaction (r=592;p<0.05). However, the correlation between multidimensional life satisfaction and psychological sense of school membership was not significant (r=0.038;p>0.05). The regression analysis indicated that the contribution of mother’s education and father’s education to psychological sense of school member of the children were 0.923, Adjusted R2 is 0.440 and 0.730 and Adjusted R2 is 0.446. The results also indicate that contribution of gender to psychological sense of school for male and female has R= 0.782, Adjusted R2 = 0.478 and R = 0.998, Adjusted R2 i= 0.932 respectively. In conclusion, mother’s education qualification was found to contribute more to children psychological sense of membership and multidimensional life satisfaction than father’s. The girl child was also found to have more sense of belonging to the school setting than boy child. The counselling implications and recommendations among others were geared towards positive emotional gender sensitivity with regards to the male folk. Education stakeholders are also encouraged to make the school environment more conducive and gender friendly. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multidimensional%20life%20satisfaction" title="multidimensional life satisfaction">multidimensional life satisfaction</a>, <a href="https://publications.waset.org/abstracts/search?q=psychological%20sense%20of%20school" title=" psychological sense of school"> psychological sense of school</a>, <a href="https://publications.waset.org/abstracts/search?q=coping%20skills" title=" coping skills"> coping skills</a>, <a href="https://publications.waset.org/abstracts/search?q=counselling%20implications" title=" counselling implications"> counselling implications</a> </p> <a href="https://publications.waset.org/abstracts/68417/psychological-sense-of-school-membership-and-coping-ability-as-predictors-of-multidimensional-life-satisfaction-among-school-children" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68417.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">310</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">11178</span> Multiple Relaxation Times in the Gibbs Ensemble Monte Carlo Simulation of Phase Separation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bina%20Kumari">Bina Kumari</a>, <a href="https://publications.waset.org/abstracts/search?q=Subir%20K.%20Sarkar"> Subir K. Sarkar</a>, <a href="https://publications.waset.org/abstracts/search?q=Pradipta%20Bandyopadhyay"> Pradipta Bandyopadhyay</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The autocorrelation function of the density fluctuation is studied in each of the two phases in a Gibbs Ensemble Monte Carlo (GEMC) simulation of the problem of phase separation for a square well potential with various values of its range. We find that the normalized autocorrelation function is described very well as a linear combination of an exponential function with a time scale τ₂ and a stretched exponential function with a time scale τ₁ and an exponent α. Dependence of (α, τ₁, τ₂) on the parameters of the GEMC algorithm and the range of the square well potential is investigated and interpreted. We also analyse the issue of how to choose the parameters of the GEMC simulation optimally. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autocorrelation%20function" title="autocorrelation function">autocorrelation function</a>, <a href="https://publications.waset.org/abstracts/search?q=density%20fluctuation" title=" density fluctuation"> density fluctuation</a>, <a href="https://publications.waset.org/abstracts/search?q=GEMC" title=" GEMC"> GEMC</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a> </p> <a href="https://publications.waset.org/abstracts/131552/multiple-relaxation-times-in-the-gibbs-ensemble-monte-carlo-simulation-of-phase-separation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131552.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">188</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">11177</span> The Withdrawal of African States from the International Criminal Court</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Allwell%20Uwazuruike">Allwell Uwazuruike</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the withdrawal, in 2016, of 3 African states from the ICC, the discourse took an interesting twist. African states, or at least some of them, had now shown their resolve to part ways with the ICC and, by implication, focus on further enthroning regional control and governance through an improved continental justice system. A range of views has been expressed over the years on the allegations of bias by some African states and the continued membership of the ICC. While there may be a split on the merits of the allegations of bias, academic analysts have generally not opposed African states’ membership of the ICC nor been particularly optimistic about the prospects of an African criminal court. There is also a degree of ambivalence on whether there are positives to be taken from African states’ withdrawal from the ICC. This article examines the recent developments with the ICC and analyses whether these could be viewed from the positive (or, at least, alternative) spectrum of the AU’s spirited march towards regional sovereignty or entirely negatively from the point of view of African Heads-of-State seeking to enthrone an era of authoritarianism and non-accountability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=international%20criminal%20court" title="international criminal court">international criminal court</a>, <a href="https://publications.waset.org/abstracts/search?q=Africa" title=" Africa"> Africa</a>, <a href="https://publications.waset.org/abstracts/search?q=regionalism" title=" regionalism"> regionalism</a>, <a href="https://publications.waset.org/abstracts/search?q=criminal%20justice" title=" criminal justice"> criminal justice</a> </p> <a href="https://publications.waset.org/abstracts/82258/the-withdrawal-of-african-states-from-the-international-criminal-court" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/82258.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">11176</span> A Comparative Assessment of Information Value, Fuzzy Expert System Models for Landslide Susceptibility Mapping of Dharamshala and Surrounding, Himachal Pradesh, India</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kumari%20Sweta">Kumari Sweta</a>, <a href="https://publications.waset.org/abstracts/search?q=Ajanta%20Goswami"> Ajanta Goswami</a>, <a href="https://publications.waset.org/abstracts/search?q=Abhilasha%20Dixit"> Abhilasha Dixit</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bivariate%20statistical%20techniques" title="bivariate statistical techniques">bivariate statistical techniques</a>, <a href="https://publications.waset.org/abstracts/search?q=BG%20and%20TT%20membership%20structure" title=" BG and TT membership structure"> BG and TT membership structure</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20expert%20system" title=" fuzzy expert system"> fuzzy expert system</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20value%20method" title=" information value method"> information value method</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning%20technique" title=" machine learning technique"> machine learning technique</a> </p> <a href="https://publications.waset.org/abstracts/121072/a-comparative-assessment-of-information-value-fuzzy-expert-system-models-for-landslide-susceptibility-mapping-of-dharamshala-and-surrounding-himachal-pradesh-india" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/121072.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">127</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">11175</span> Application of ANN and Fuzzy Logic Algorithms for Runoff and Sediment Yield Modelling of Kal River, India</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahesh%20Kothari">Mahesh Kothari</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20D.%20Gharde"> K. D. Gharde</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The ANN and fuzzy logic (FL) models were developed to predict the runoff and sediment yield for catchment of Kal river, India using 21 years (1991 to 2011) rainfall and other hydrological data (evaporation, temperature and streamflow lag by one and two day) and 7 years data for sediment yield modelling. The ANN model performance improved with increasing the input vectors. The fuzzy logic model was performing with R value more than 0.95 during developmental stage and validation stage. The comparatively FL model found to be performing well to ANN in prediction of runoff and sediment yield for Kal river. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=transferred%20function" title="transferred function">transferred function</a>, <a href="https://publications.waset.org/abstracts/search?q=sigmoid" title=" sigmoid"> sigmoid</a>, <a href="https://publications.waset.org/abstracts/search?q=backpropagation" title=" backpropagation"> backpropagation</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20function" title=" membership function"> membership function</a>, <a href="https://publications.waset.org/abstracts/search?q=defuzzification" title=" defuzzification "> defuzzification </a> </p> <a href="https://publications.waset.org/abstracts/33110/application-of-ann-and-fuzzy-logic-algorithms-for-runoff-and-sediment-yield-modelling-of-kal-river-india" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33110.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">569</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">11174</span> Roles of Aquatic Plants on Erosion Relief of Stream Bed</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jin-Hong%20Kim">Jin-Hong Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Roles of the vegetation to mitigate the erosion of the stream bed or to facilitate the deposition of the fine sediments by the species of the aquatic plants were presented. Field investigation on the estimation of the change of the bed level and the estimation of the flow characteristics were performed. The results showed that Phragmites japonica has the mitigation function of 0.3m-0.4m of the erosion in the range of higher than 1.0m/s of flow velocity at the vegetated region. Phragmites communis has the mitigation function of 0.2m-0.3m of the erosion in the range of higher than 0.7m/s of flow velocity at the vegetated region. Salix gracilistyla has greater role than Phragmites japonica and Phragmites communis to sustain the stable channel. It has the mitigation function of 0.4m-0.5m of the erosion in the range of higher than 1.4m/s of flow velocity. Miscanthus sacchariflorus has a weak role compared with that of Phragmites japonica and Salix gracilistyla, but it has still function for sustaining the stable bed. From these results, the vegetation has effective roles to mitigate the erosion or to facilitate the deposition of the stream bed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=aquatic%20plants" title="aquatic plants">aquatic plants</a>, <a href="https://publications.waset.org/abstracts/search?q=Phragmites%20japonica" title=" Phragmites japonica"> Phragmites japonica</a>, <a href="https://publications.waset.org/abstracts/search?q=Phragmites%20communis" title=" Phragmites communis"> Phragmites communis</a>, <a href="https://publications.waset.org/abstracts/search?q=Salix%20gracilistyla" title=" Salix gracilistyla"> Salix gracilistyla</a> </p> <a href="https://publications.waset.org/abstracts/24518/roles-of-aquatic-plants-on-erosion-relief-of-stream-bed" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24518.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">385</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">11173</span> Integration of Quality Function Deployment and Modular Function Deployment in Product Development</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Naga%20Velamakuri">Naga Velamakuri</a>, <a href="https://publications.waset.org/abstracts/search?q=Jyothi%20K.%20Reddy"> Jyothi K. Reddy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Quality must be designed into a product and not inspected has become the main motto of all the companies globally. Due to the rapidly increasing technology in the past few decades, the nature of demands from the consumers has become more sophisticated. To sustain this global revolution of innovation in production systems, companies have to take steps to accommodate this technology growth. In this process of understanding the customers' expectations, all the firms globally take steps to deliver a perfect output. Most of these techniques also concentrate on the consistent development and optimization of the product to exceed the expectations. Quality Function Deployment(QFD) and Modular Function Deployment(MFD) are such techniques which rely on the voice of the customer and help deliver the needs. In this paper, Quality Function Deployment and Modular Function Deployment techniques which help in converting the quantitative descriptions to qualitative outcomes are discussed. The area of interest would be to understand the scope of each of the techniques and the application range in product development when these are applied together to any problem. The research question would be mainly aimed at comprehending the limitations using modularity in product development. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quality%20function%20deployment" title="quality function deployment">quality function deployment</a>, <a href="https://publications.waset.org/abstracts/search?q=modular%20function%20deployment" title=" modular function deployment"> modular function deployment</a>, <a href="https://publications.waset.org/abstracts/search?q=house%20of%20quality" title=" house of quality"> house of quality</a>, <a href="https://publications.waset.org/abstracts/search?q=methodology" title=" methodology"> methodology</a> </p> <a href="https://publications.waset.org/abstracts/75517/integration-of-quality-function-deployment-and-modular-function-deployment-in-product-development" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75517.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">328</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">11172</span> Multi-Cluster Overlapping K-Means Extension Algorithm (MCOKE)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Said%20Baadel">Said Baadel</a>, <a href="https://publications.waset.org/abstracts/search?q=Fadi%20Thabtah"> Fadi Thabtah</a>, <a href="https://publications.waset.org/abstracts/search?q=Joan%20Lu"> Joan Lu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Clustering involves the partitioning of n objects into k clusters. Many clustering algorithms use hard-partitioning techniques where each object is assigned to one cluster. In this paper, we propose an overlapping algorithm MCOKE which allows objects to belong to one or more clusters. The algorithm is different from fuzzy clustering techniques because objects that overlap are assigned a membership value of 1 (one) as opposed to a fuzzy membership degree. The algorithm is also different from other overlapping algorithms that require a similarity threshold to be defined as a priority which can be difficult to determine by novice users. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title="data mining">data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=k-means" title=" k-means"> k-means</a>, <a href="https://publications.waset.org/abstracts/search?q=MCOKE" title=" MCOKE"> MCOKE</a>, <a href="https://publications.waset.org/abstracts/search?q=overlapping" title=" overlapping"> overlapping</a> </p> <a href="https://publications.waset.org/abstracts/18638/multi-cluster-overlapping-k-means-extension-algorithm-mcoke" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18638.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">575</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">11171</span> A Fuzzy Programming Approach for Solving Intuitionistic Fuzzy Linear Fractional Programming Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sujeet%20Kumar%20Singh">Sujeet Kumar Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Shiv%20Prasad%20Yadav"> Shiv Prasad Yadav</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper develops an approach for solving intuitionistic fuzzy linear fractional programming (IFLFP) problem where the cost of the objective function, the resources, and the technological coefficients are triangular intuitionistic fuzzy numbers. Here, the IFLFP problem is transformed into an equivalent crisp multi-objective linear fractional programming (MOLFP) problem. By using fuzzy mathematical programming approach the transformed MOLFP problem is reduced into a single objective linear programming (LP) problem. The proposed procedure is illustrated through a numerical example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=triangular%20intuitionistic%20fuzzy%20number" title="triangular intuitionistic fuzzy number">triangular intuitionistic fuzzy number</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20programming%20problem" title=" linear programming problem"> linear programming problem</a>, <a href="https://publications.waset.org/abstracts/search?q=multi%20objective%20linear%20programming%20problem" title=" multi objective linear programming problem"> multi objective linear programming problem</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20mathematical%20programming" title=" fuzzy mathematical programming"> fuzzy mathematical programming</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20function" title=" membership function"> membership function</a> </p> <a href="https://publications.waset.org/abstracts/16411/a-fuzzy-programming-approach-for-solving-intuitionistic-fuzzy-linear-fractional-programming-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16411.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">566</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">11170</span> Yang-Lee Edge Singularity of the Infinite-Range Ising Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seung-Yeon%20Kim">Seung-Yeon Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Ising model, consisting magnetic spins, is the simplest system showing phase transitions and critical phenomena at finite temperatures. The Ising model has played a central role in our understanding of phase transitions and critical phenomena. Also, the Ising model explains the gas-liquid phase transitions accurately. However, the Ising model in a nonzero magnetic field has been one of the most intriguing and outstanding unsolved problems. We study analytically the partition function zeros in the complex magnetic-field plane and the Yang-Lee edge singularity of the infinite-range Ising model in an external magnetic field. In addition, we compare the Yang-Lee edge singularity of the infinite-range Ising model with that of the square-lattice Ising model in an external magnetic field. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ising%20ferromagnet" title="Ising ferromagnet">Ising ferromagnet</a>, <a href="https://publications.waset.org/abstracts/search?q=magnetic%20field" title=" magnetic field"> magnetic field</a>, <a href="https://publications.waset.org/abstracts/search?q=partition%20function%20zeros" title=" partition function zeros"> partition function zeros</a>, <a href="https://publications.waset.org/abstracts/search?q=Yang-Lee%20edge%20singularity" title=" Yang-Lee edge singularity"> Yang-Lee edge singularity</a> </p> <a href="https://publications.waset.org/abstracts/20452/yang-lee-edge-singularity-of-the-infinite-range-ising-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20452.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">739</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">11169</span> Volcanoscape Space Configuration Zoning Based on Disaster Mitigation by Utilizing GIS Platform in Mt. Krakatau Indonesia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vega%20Erdiana%20Dwi%20Fransiska">Vega Erdiana Dwi Fransiska</a>, <a href="https://publications.waset.org/abstracts/search?q=Abyan%20Rai%20Fauzan%20Machmudin"> Abyan Rai Fauzan Machmudin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Particularly, space configuration zoning is the very first juncture of a complete space configuration and region planning. Zoning is aimed to define discrete knowledge based on a local wisdom. Ancient predecessor scientifically study the sign of natural disaster towards ethnography approach by operating this knowledge. There are three main functions of space zoning, which are control function, guidance function, and additional function. The control function refers to an instrument for development control and as one of the essentials in controlling land use. Hence, the guidance function indicates as guidance for proposing operational planning and technical development or land usage. Any additional function is useful as a supplementary for region or province planning details. This phase likewise accredits to define boundary in an open space based on geographical appearance. Informant who is categorized as an elder lives in earthquake prone area, to be precise the area is the surrounding of Mount Krakatau. The collected data is one of method for analyzed with thematic model. Later on, it will be verified. In space zoning, long-range distance sensor is applied to determine visualization of the area, which will be zoned before the step of survey to validate the data. The data, which is obtained from long-range distance sensor and site survey, will be overlaid using GIS Platform. Comparing the knowledge based on a local wisdom that is well known by elderly in that area, some of it is relevant to the research, while the others are not. Based on the site survey, the interpretation of a long-range distance sensor, and determining space zoning by considering various aspects resulted in the pattern map of space zoning. This map can be integrated with disaster mitigation affected by volcano eruption. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=elderly" title="elderly">elderly</a>, <a href="https://publications.waset.org/abstracts/search?q=GIS%20platform" title=" GIS platform"> GIS platform</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20wisdom" title=" local wisdom"> local wisdom</a>, <a href="https://publications.waset.org/abstracts/search?q=space%20zoning" title=" space zoning"> space zoning</a> </p> <a href="https://publications.waset.org/abstracts/41085/volcanoscape-space-configuration-zoning-based-on-disaster-mitigation-by-utilizing-gis-platform-in-mt-krakatau-indonesia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41085.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">254</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11168</span> The Implementation of Secton Method for Finding the Root of Interpolation Function</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nur%20Rokhman">Nur Rokhman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A mathematical function gives relationship between the variables composing the function. Interpolation can be viewed as a process of finding mathematical function which goes through some specified points. There are many interpolation methods, namely: Lagrange method, Newton method, Spline method etc. For some specific condition, such as, big amount of interpolation points, the interpolation function can not be written explicitly. This such function consist of computational steps. The solution of equations involving the interpolation function is a problem of solution of non linear equation. Newton method will not work on the interpolation function, for the derivative of the interpolation function cannot be written explicitly. This paper shows the use of Secton method to determine the numerical solution of the function involving the interpolation function. The experiment shows the fact that Secton method works better than Newton method in finding the root of Lagrange interpolation function. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Secton%20method" title="Secton method">Secton method</a>, <a href="https://publications.waset.org/abstracts/search?q=interpolation" title=" interpolation"> interpolation</a>, <a href="https://publications.waset.org/abstracts/search?q=non%20linear%20function" title=" non linear function"> non linear function</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20solution" title=" numerical solution"> numerical solution</a> </p> <a href="https://publications.waset.org/abstracts/1837/the-implementation-of-secton-method-for-finding-the-root-of-interpolation-function" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1837.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">379</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">11167</span> Highly Accurate Target Motion Compensation Using Entropy Function Minimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amin%20Aghatabar%20Roodbary">Amin Aghatabar Roodbary</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Hassan%20Bastani"> Mohammad Hassan Bastani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=automatic%20target%20recognition%20%28ATR%29" title="automatic target recognition (ATR)">automatic target recognition (ATR)</a>, <a href="https://publications.waset.org/abstracts/search?q=high%20resolution%20range%20profile%20%28HRRP%29" title=" high resolution range profile (HRRP)"> high resolution range profile (HRRP)</a>, <a href="https://publications.waset.org/abstracts/search?q=motion%20compensation" title=" motion compensation"> motion compensation</a>, <a href="https://publications.waset.org/abstracts/search?q=stepped%20frequency%20waveform%20technique%20%28SFW%29" title=" stepped frequency waveform technique (SFW)"> stepped frequency waveform technique (SFW)</a>, <a href="https://publications.waset.org/abstracts/search?q=target%20motion%20parameters%20%28TMPs%29" title=" target motion parameters (TMPs)"> target motion parameters (TMPs)</a> </p> <a href="https://publications.waset.org/abstracts/97540/highly-accurate-target-motion-compensation-using-entropy-function-minimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97540.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">152</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">11166</span> Prediction of Phonon Thermal Conductivity of F.C.C. Al by Molecular Dynamics Simulation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Leila%20Momenzadeh">Leila Momenzadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexander%20V.%20Evteev"> Alexander V. Evteev</a>, <a href="https://publications.waset.org/abstracts/search?q=Elena%20V.%20Levchenko"> Elena V. Levchenko</a>, <a href="https://publications.waset.org/abstracts/search?q=Tanvir%20Ahmed"> Tanvir Ahmed</a>, <a href="https://publications.waset.org/abstracts/search?q=Irina%20Belova"> Irina Belova</a>, <a href="https://publications.waset.org/abstracts/search?q=Graeme%20Murch"> Graeme Murch</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, the phonon thermal conductivity of f.c.c. Al is investigated in detail in the temperature range 100 – 900 K within the framework of equilibrium molecular dynamics simulations making use of the Green-Kubo formalism and one of the most reliable embedded-atom method potentials. It is found that the heat current auto-correlation function of the f.c.c. Al model demonstrates a two-stage temporal decay similar to the previously observed for f.c.c Cu model. After the first stage of decay, the heat current auto-correlation function of the f.c.c. Al model demonstrates a peak in the temperature range 100-800 K. The intensity of the peak decreases as the temperature increases. At 900 K, it transforms to a shoulder. To describe the observed two-stage decay of the heat current auto-correlation function of the f.c.c. Al model, we employ decomposition model recently developed for phonon-mediated thermal transport in a monoatomic lattice. We found that the electronic contribution to the total thermal conductivity of f.c.c. Al dominates over the whole studied temperature range. However, the phonon contribution to the total thermal conductivity of f.c.c. Al increases as temperature decreases. It is about 1.05% at 900 K and about 12.5% at 100 K. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=aluminum" title="aluminum">aluminum</a>, <a href="https://publications.waset.org/abstracts/search?q=gGreen-Kubo%20formalism" title=" gGreen-Kubo formalism"> gGreen-Kubo formalism</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20dynamics" title=" molecular dynamics"> molecular dynamics</a>, <a href="https://publications.waset.org/abstracts/search?q=phonon%20thermal%20conductivity" title=" phonon thermal conductivity"> phonon thermal conductivity</a> </p> <a href="https://publications.waset.org/abstracts/19983/prediction-of-phonon-thermal-conductivity-of-fcc-al-by-molecular-dynamics-simulation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19983.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">11165</span> A Methodology of Using Fuzzy Logics and Data Analytics to Estimate the Life Cycle Indicators of Solar Photovoltaics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Thor%20Alexis%20Sazon">Thor Alexis Sazon</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexander%20Guzman-Urbina"> Alexander Guzman-Urbina</a>, <a href="https://publications.waset.org/abstracts/search?q=Yasuhiro%20Fukushima"> Yasuhiro Fukushima</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=solar%20photovoltaic" title="solar photovoltaic">solar photovoltaic</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=inference%20system" title=" inference system"> inference system</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title=" artificial neural networks"> artificial neural networks</a> </p> <a href="https://publications.waset.org/abstracts/114050/a-methodology-of-using-fuzzy-logics-and-data-analytics-to-estimate-the-life-cycle-indicators-of-solar-photovoltaics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/114050.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">164</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">11164</span> Throughput of Point Coordination Function (PCF)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Faisel%20Eltuhami%20Alzaalik">Faisel Eltuhami Alzaalik</a>, <a href="https://publications.waset.org/abstracts/search?q=Omar%20Imhemed%20Alramli"> Omar Imhemed Alramli</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Mohamed%20Elaieb"> Ahmed Mohamed Elaieb</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The IEEE 802.11 defines two modes of MAC, distributed coordination function (DCF) and point coordination function (PCF) mode. The first sub-layer of the MAC is the distributed coordination function (DCF). A contention algorithm is used via DCF to provide access to all traffic. The point coordination function (PCF) is the second sub-layer used to provide contention-free service. PCF is upper DCF and it uses features of DCF to establish guarantee access of its users. Some papers and researches that have been published in this technology were reviewed in this paper, as well as talking briefly about the distributed coordination function (DCF) technology. The simulation of the PCF function have been applied by using a simulation program called network simulator (NS2) and have been found out the throughput of a transmitter system by using this function. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DCF" title="DCF">DCF</a>, <a href="https://publications.waset.org/abstracts/search?q=PCF" title=" PCF"> PCF</a>, <a href="https://publications.waset.org/abstracts/search?q=throughput" title=" throughput"> throughput</a>, <a href="https://publications.waset.org/abstracts/search?q=NS2" title=" NS2"> NS2</a> </p> <a href="https://publications.waset.org/abstracts/2456/throughput-of-point-coordination-function-pcf" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2456.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">577</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">11163</span> A Computational Fluid Dynamics Study of Turbulence Flow and Parameterization of an Aerofoil</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Z.%20M.%20Duwahir">Mohamed Z. M. Duwahir</a>, <a href="https://publications.waset.org/abstracts/search?q=Shian%20Gao"> Shian Gao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The main objective of this project was to introduce and test a new scheme for parameterization of subsonic aerofoil, using a function called Shape Function. Python programming was used to create a user interactive environment for geometry generation of aerofoil using NACA and Shape Function methodologies. Two aerofoils, NACA 0012 and NACA 1412, were generated using this function. Testing the accuracy of the Shape Function scheme was done by Linear Square Fitting using Python and CFD modelling the aerofoil in Fluent. NACA 0012 (symmetrical aerofoil) was better approximated using Shape Function than NACA 1412 (cambered aerofoil). The second part of the project involved comparing two turbulent models, k-ε and Spalart-Allmaras (SA), in Fluent by modelling the aerofoils NACA 0012 and NACA 1412 in conditions of Reynolds number of 3 × 106. It was shown that SA modelling is better for aerodynamic purpose. The experimental coefficient of lift (Cl) and coefficient of drag (Cd) were compared with empirical wind tunnel data for a range of angle of attack (AOA). As a further step, this project involved drawing and meshing 3D wings in Gambit. The 3D wing flow was solved and compared with 2D aerofoil section experimental results and wind tunnel data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CFD%20simulation" title="CFD simulation">CFD simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=shape%20function" title=" shape function"> shape function</a>, <a href="https://publications.waset.org/abstracts/search?q=turbulent%20modelling" title=" turbulent modelling"> turbulent modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=aerofoil" title=" aerofoil"> aerofoil</a> </p> <a href="https://publications.waset.org/abstracts/75069/a-computational-fluid-dynamics-study-of-turbulence-flow-and-parameterization-of-an-aerofoil" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75069.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 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