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smoothing problem</title> <meta name="description" content="Search results for: resource smoothing problem"> <meta name="keywords" content="resource smoothing problem"> <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="resource smoothing problem"> <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> 9548</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: resource smoothing problem</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">9548</span> Upon One Smoothing Problem in Project Management</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dimitri%20Golenko-Ginzburg">Dimitri Golenko-Ginzburg</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A CPM network project with deterministic activity durations, in which activities require homogenous resources with fixed capacities, is considered. The problem is to determine the optimal schedule of starting times for all network activities within their maximal allowable limits (in order not to exceed the network's critical time) to minimize the maximum required resources for the project at any point in time. In case when a non-critical activity may start only at discrete moments with the pregiven time span, the problem becomes NP-complete and an optimal solution may be obtained via a look-over algorithm. For the case when a look-over requires much computational time an approximate algorithm is suggested. The algorithm's performance ratio, i.e., the relative accuracy error, is determined. Experimentation has been undertaken to verify the suggested algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=resource%20smoothing%20problem" title="resource smoothing problem">resource smoothing problem</a>, <a href="https://publications.waset.org/abstracts/search?q=CPM%20network" title=" CPM network"> CPM network</a>, <a href="https://publications.waset.org/abstracts/search?q=lookover%20algorithm" title=" lookover algorithm"> lookover algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=lexicographical%20order" title=" lexicographical order"> lexicographical order</a>, <a href="https://publications.waset.org/abstracts/search?q=approximate%20algorithm" title=" approximate algorithm"> approximate algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=accuracy%20estimate" title=" accuracy estimate"> accuracy estimate</a> </p> <a href="https://publications.waset.org/abstracts/15779/upon-one-smoothing-problem-in-project-management" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15779.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">302</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">9547</span> Solving Optimal Control of Semilinear Elliptic Variational Inequalities Obstacle Problems using Smoothing Functions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=El%20Hassene%20Osmani">El Hassene Osmani</a>, <a href="https://publications.waset.org/abstracts/search?q=Mounir%20Haddou"> Mounir Haddou</a>, <a href="https://publications.waset.org/abstracts/search?q=Naceurdine%20Bensalem"> Naceurdine Bensalem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we investigate optimal control problems governed by semilinear elliptic variational inequalities involving constraints on the state, and more precisely, the obstacle problem. We present a relaxed formulation for the problem using smoothing functions. Since we adopt a numerical point of view, we first relax the feasible domain of the problem, then using both mathematical programming methods and penalization methods, we get optimality conditions with smooth Lagrange multipliers. Some numerical experiments using IPOPT algorithm (Interior Point Optimizer) are presented to verify the efficiency of our approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=complementarity%20problem" title="complementarity problem">complementarity problem</a>, <a href="https://publications.waset.org/abstracts/search?q=IPOPT" title=" IPOPT"> IPOPT</a>, <a href="https://publications.waset.org/abstracts/search?q=Lagrange%20multipliers" title=" Lagrange multipliers"> Lagrange multipliers</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%20programming" title=" mathematical programming"> mathematical programming</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20control" title=" optimal control"> optimal control</a>, <a href="https://publications.waset.org/abstracts/search?q=smoothing%20methods" title=" smoothing methods"> smoothing methods</a>, <a href="https://publications.waset.org/abstracts/search?q=variationally%20inequalities" title=" variationally inequalities"> variationally inequalities</a> </p> <a href="https://publications.waset.org/abstracts/132882/solving-optimal-control-of-semilinear-elliptic-variational-inequalities-obstacle-problems-using-smoothing-functions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132882.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">173</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">9546</span> The Hyperbolic Smoothing Approach for Automatic Calibration of Rainfall-Runoff Models </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adilson%20Elias%20Xavier">Adilson Elias Xavier</a>, <a href="https://publications.waset.org/abstracts/search?q=Otto%20Corr%C3%AAa%20Rotunno%20Filho"> Otto Corrêa Rotunno Filho</a>, <a href="https://publications.waset.org/abstracts/search?q=Paulo%20Canedo%20De%20Magalh%C3%A3es"> Paulo Canedo De Magalhães</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper addresses the issue of automatic parameter estimation in conceptual rainfall-runoff (CRR) models. Due to threshold structures commonly occurring in CRR models, the associated mathematical optimization problems have the significant characteristic of being strongly non-differentiable. In order to face this enormous task, the resolution method proposed adopts a smoothing strategy using a special C∞ differentiable class function. The final estimation solution is obtained by solving a sequence of differentiable subproblems which gradually approach the original conceptual problem. The use of this technique, called Hyperbolic Smoothing Method (HSM), makes possible the application of the most powerful minimization algorithms, and also allows for the main difficulties presented by the original CRR problem to be overcome. A set of computational experiments is presented for the purpose of illustrating both the reliability and the efficiency of the proposed approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=rainfall-runoff%20models" title="rainfall-runoff models">rainfall-runoff models</a>, <a href="https://publications.waset.org/abstracts/search?q=automatic%20calibration" title=" automatic calibration"> automatic calibration</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperbolic%20smoothing%20method" title=" hyperbolic smoothing method"> hyperbolic smoothing method</a> </p> <a href="https://publications.waset.org/abstracts/123935/the-hyperbolic-smoothing-approach-for-automatic-calibration-of-rainfall-runoff-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/123935.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">9545</span> Estimation of Train Operation Using an Exponential Smoothing Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Taiyo%20Matsumura">Taiyo Matsumura</a>, <a href="https://publications.waset.org/abstracts/search?q=Kuninori%20Takahashi"> Kuninori Takahashi</a>, <a href="https://publications.waset.org/abstracts/search?q=Takashi%20Ono"> Takashi Ono</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this research is to improve the convenience of waiting for trains at level crossings and stations and to prevent accidents resulting from forcible entry into level crossings, by providing level crossing users and passengers with information that tells them when the next train will pass through or arrive. For this paper, we proposed methods for estimating operation by means of an average value method, variable response smoothing method, and exponential smoothing method, on the basis of open data, which has low accuracy, but for which performance schedules are distributed in real time. We then examined the accuracy of the estimations. The results showed that the application of an exponential smoothing method is valid. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=exponential%20smoothing%20method" title="exponential smoothing method">exponential smoothing method</a>, <a href="https://publications.waset.org/abstracts/search?q=open%20data" title=" open data"> open data</a>, <a href="https://publications.waset.org/abstracts/search?q=operation%20estimation" title=" operation estimation"> operation estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=train%20schedule" title=" train schedule"> train schedule</a> </p> <a href="https://publications.waset.org/abstracts/78572/estimation-of-train-operation-using-an-exponential-smoothing-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78572.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">388</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">9544</span> Using “Eckel” Model to Measure Income Smoothing Practices: The Case of French Companies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Feddaoui%20Amina">Feddaoui Amina</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Income smoothing represents an attempt on the part of the company's management to reduce variations in earnings through the manipulation of the accounting principles. In this study, we aimed to measure income smoothing practices in a sample of 30 French joint stock companies during the period (2007-2009), we used Dummy variables method and “ECKEL” model to measure income smoothing practices and Binomial test accourding to SPSS program, to confirm or refute our hypothesis. This study concluded that there are no significant statistical indicators of income smoothing practices in the sample studied of French companies during the period (2007-2009), so the income series in the same sample studied of is characterized by stability and non-volatility without any intervention of management through accounting manipulation. However, this type of accounting manipulation should be taken into account and efforts should be made by control bodies to apply Eckel model and generalize its use at the global level. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=income" title="income">income</a>, <a href="https://publications.waset.org/abstracts/search?q=smoothing" title=" smoothing"> smoothing</a>, <a href="https://publications.waset.org/abstracts/search?q=%27Eckel%27" title=" 'Eckel'"> 'Eckel'</a>, <a href="https://publications.waset.org/abstracts/search?q=French%20companies" title=" French companies"> French companies</a> </p> <a href="https://publications.waset.org/abstracts/90241/using-eckel-model-to-measure-income-smoothing-practices-the-case-of-french-companies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/90241.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">9543</span> Accounting and Auditing Standards Influence on Income Smoothing Perspective in Islamic Financial Institutions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fatma%20Ezzahra%20Kateb">Fatma Ezzahra Kateb</a>, <a href="https://publications.waset.org/abstracts/search?q=Neila%20Boulila%20Taktak"> Neila Boulila Taktak</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Kabir%20Hassan"> Mohamed Kabir Hassan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We examine the impact of Islamic accounting and auditing standards issued by the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) on the income smoothing perspective of Islamic financial institutions located in the Middle East and North Africa region between 2013 and 2018. Based on General Least square regression for panel data, we find a significant and positive relationship between intentional income smoothing and earning persistence and cash flow predictability in all models. However, we discovered that AAOIFI accounting standards (FAS) had a negative and significant effect on intentional income smoothing and earning persistence. As a result, the income smoothing efficiency is lower for IFIs that use FASs than IFIs that use IFRSs. Our findings emphasize the need for specific standards to enhance the relevance of financial reports disclosed by Islamic financial institutions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AAOIFI" title="AAOIFI">AAOIFI</a>, <a href="https://publications.waset.org/abstracts/search?q=financial%20reporting%20quality" title=" financial reporting quality"> financial reporting quality</a>, <a href="https://publications.waset.org/abstracts/search?q=income%20smoothing%20perspective" title=" income smoothing perspective"> income smoothing perspective</a>, <a href="https://publications.waset.org/abstracts/search?q=MENA%20countries" title=" MENA countries"> MENA countries</a> </p> <a href="https://publications.waset.org/abstracts/157853/accounting-and-auditing-standards-influence-on-income-smoothing-perspective-in-islamic-financial-institutions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157853.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">94</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">9542</span> A Comparison of Smoothing Spline Method and Penalized Spline Regression Method Based on Nonparametric Regression Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Autcha%20Araveeporn">Autcha Araveeporn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a study about a nonparametric regression model consisting of a smoothing spline method and a penalized spline regression method. We also compare the techniques used for estimation and prediction of nonparametric regression model. We tried both methods with crude oil prices in dollars per barrel and the Stock Exchange of Thailand (SET) index. According to the results, it is concluded that smoothing spline method performs better than that of penalized spline regression method. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nonparametric%20regression%20model" title="nonparametric regression model">nonparametric regression model</a>, <a href="https://publications.waset.org/abstracts/search?q=penalized%20spline%20regression%20method" title=" penalized spline regression method"> penalized spline regression method</a>, <a href="https://publications.waset.org/abstracts/search?q=smoothing%20spline%20method" title=" smoothing spline method"> smoothing spline method</a>, <a href="https://publications.waset.org/abstracts/search?q=Stock%20Exchange%20of%20Thailand%20%28SET%29" title=" Stock Exchange of Thailand (SET)"> Stock Exchange of Thailand (SET)</a> </p> <a href="https://publications.waset.org/abstracts/2974/a-comparison-of-smoothing-spline-method-and-penalized-spline-regression-method-based-on-nonparametric-regression-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2974.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">440</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">9541</span> Dividends Smoothing in an Era of Unclaimed Dividends: A Panel Data Analysis in Nigeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Apedzan%20Emmanuel%20Kighir">Apedzan Emmanuel Kighir</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research investigates dividends smoothing among non-financial companies trading on the Nigerian Stock Exchange in an era of unclaimed dividends from 2004 to 2013. There has been a raging controversy among Regulatory Authorities, Company Executives, Registrars of Companies, Shareholders and the general public regarding the increasing incidence of unclaimed dividends in Nigeria. The objective of this study is to find out if corporate earnings management through dividends smoothing is implicated in unclaimed dividends among Nigerian non-financial firms. The research used panel data and employed Generalized Method of Moment as method of analysis. The research finds evidence of dividends-smoothing in this era of unclaimed dividends in Nigeria. The research concludes that dividends-smoothing is a trigger and red flag for unclaimed dividends, an output of earnings management. If earnings management and hence unclaimed dividends in Nigeria is allowed to continue, it will lead to great consequences to the investors and corporate policy of government. It is believed that the research will assist investors and government in making informed decisions regarding dividends policy in Nigeria. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dividends%20smoothing" title="dividends smoothing">dividends smoothing</a>, <a href="https://publications.waset.org/abstracts/search?q=non%20financial%20companies" title=" non financial companies"> non financial companies</a>, <a href="https://publications.waset.org/abstracts/search?q=Nigerian%20stock%20exchange" title=" Nigerian stock exchange"> Nigerian stock exchange</a>, <a href="https://publications.waset.org/abstracts/search?q=unclaimed%20dividends" title=" unclaimed dividends"> unclaimed dividends</a>, <a href="https://publications.waset.org/abstracts/search?q=corporate%20earnings%20management" title=" corporate earnings management"> corporate earnings management</a> </p> <a href="https://publications.waset.org/abstracts/41198/dividends-smoothing-in-an-era-of-unclaimed-dividends-a-panel-data-analysis-in-nigeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41198.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">280</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">9540</span> Binarized-Weight Bilateral Filter for Low Computational Cost Image Smoothing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yu%20Zhang">Yu Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Kohei%20Inoue"> Kohei Inoue</a>, <a href="https://publications.waset.org/abstracts/search?q=Kiichi%20Urahama"> Kiichi Urahama</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose a simplified bilateral filter with binarized coefficients for accelerating it. Its computational cost is further decreased by sampling pixels. This computationally low cost filter is useful for smoothing or denoising images by using mobile devices with limited computational power. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bilateral%20filter" title="bilateral filter">bilateral filter</a>, <a href="https://publications.waset.org/abstracts/search?q=binarized-weight%20bilateral%20filter" title=" binarized-weight bilateral filter"> binarized-weight bilateral filter</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20smoothing" title=" image smoothing"> image smoothing</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20denoising" title=" image denoising"> image denoising</a>, <a href="https://publications.waset.org/abstracts/search?q=pixel%20sampling" title=" pixel sampling"> pixel sampling</a> </p> <a href="https://publications.waset.org/abstracts/8980/binarized-weight-bilateral-filter-for-low-computational-cost-image-smoothing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8980.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">469</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">9539</span> Multi-Objective Multi-Mode Resource-Constrained Project Scheduling Problem by Preemptive Fuzzy Goal Programming</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Busaba%20Phurksaphanrat">Busaba Phurksaphanrat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research proposes a pre-emptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of make-span. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, pre-emptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multi-mode%20resource%20constrained%20project%20scheduling%20problem" title="multi-mode resource constrained project scheduling problem">multi-mode resource constrained project scheduling problem</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20set" title=" fuzzy set"> fuzzy set</a>, <a href="https://publications.waset.org/abstracts/search?q=goal%20programming" title=" goal programming"> goal programming</a>, <a href="https://publications.waset.org/abstracts/search?q=pre-emptive%20fuzzy%20goal%20programming" title=" pre-emptive fuzzy goal programming"> pre-emptive fuzzy goal programming</a> </p> <a href="https://publications.waset.org/abstracts/5799/multi-objective-multi-mode-resource-constrained-project-scheduling-problem-by-preemptive-fuzzy-goal-programming" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5799.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">435</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">9538</span> Forecasting Unemployment Rate in Selected European Countries Using Smoothing Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ksenija%20Dumi%C4%8Di%C4%87">Ksenija Dumičić</a>, <a href="https://publications.waset.org/abstracts/search?q=Anita%20%C4%8Ceh%20%C4%8Casni"> Anita Čeh Časni</a>, <a href="https://publications.waset.org/abstracts/search?q=Berislav%20%C5%BDmuk"> Berislav Žmuk</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this paper is to select the most accurate forecasting method for predicting the future values of the unemployment rate in selected European countries. In order to do so, several forecasting techniques adequate for forecasting time series with trend component, were selected, namely: double exponential smoothing (also known as Holt`s method) and Holt-Winters` method which accounts for trend and seasonality. The results of the empirical analysis showed that the optimal model for forecasting unemployment rate in Greece was Holt-Winters` additive method. In the case of Spain, according to MAPE, the optimal model was double exponential smoothing model. Furthermore, for Croatia and Italy the best forecasting model for unemployment rate was Holt-Winters` multiplicative model, whereas in the case of Portugal the best model to forecast unemployment rate was Double exponential smoothing model. Our findings are in line with European Commission unemployment rate estimates. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=European%20Union%20countries" title="European Union countries">European Union countries</a>, <a href="https://publications.waset.org/abstracts/search?q=exponential%20smoothing%20methods" title=" exponential smoothing methods"> exponential smoothing methods</a>, <a href="https://publications.waset.org/abstracts/search?q=forecast%20accuracy%20unemployment%20rate" title=" forecast accuracy unemployment rate"> forecast accuracy unemployment rate</a> </p> <a href="https://publications.waset.org/abstracts/18328/forecasting-unemployment-rate-in-selected-european-countries-using-smoothing-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18328.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">369</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">9537</span> Forecasting Model for Rainfall in Thailand: Case Study Nakhon Ratchasima Province</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20Sopipan">N. Sopipan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we study of rainfall time series of weather stations in Nakhon Ratchasima province in Thailand using various statistical methods enabled to analyse the behaviour of rainfall in the study areas. Time-series analysis is an important tool in modelling and forecasting rainfall. ARIMA and Holt-Winter models based on exponential smoothing were built. All the models proved to be adequate. Therefore, could give information that can help decision makers establish strategies for proper planning of agriculture, drainage system and other water resource applications in Nakhon Ratchasima province. We found the best perform for forecasting is ARIMA(1,0,1)(1,0,1)12. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ARIMA%20Models" title="ARIMA Models">ARIMA Models</a>, <a href="https://publications.waset.org/abstracts/search?q=exponential%20smoothing" title=" exponential smoothing"> exponential smoothing</a>, <a href="https://publications.waset.org/abstracts/search?q=Holt-Winter%20model" title=" Holt-Winter model"> Holt-Winter model</a> </p> <a href="https://publications.waset.org/abstracts/14834/forecasting-model-for-rainfall-in-thailand-case-study-nakhon-ratchasima-province" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14834.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">300</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">9536</span> Forecasting Cancers Cases in Algeria Using Double Exponential Smoothing Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Messis%20A.">Messis A.</a>, <a href="https://publications.waset.org/abstracts/search?q=Adjebli%20A."> Adjebli A.</a>, <a href="https://publications.waset.org/abstracts/search?q=Ayeche%20R."> Ayeche R.</a>, <a href="https://publications.waset.org/abstracts/search?q=Talbi%20M."> Talbi M.</a>, <a href="https://publications.waset.org/abstracts/search?q=Tighilet%20K."> Tighilet K.</a>, <a href="https://publications.waset.org/abstracts/search?q=Louardiane%20M."> Louardiane M.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cancers are the second cause of death worldwide. Prevalence and incidence of cancers is getting increased by aging and population growth. This study aims to predict and modeling the evolution of breast, Colorectal, Lung, Bladder and Prostate cancers over the period of 2014-2019. In this study, data were analyzed using time series analysis with double exponential smoothing method to forecast the future pattern. To describe and fit the appropriate models, Minitab statistical software version 17 was used. Between 2014 and 2019, the overall trend in the raw number of new cancer cases registered has been increasing over time; the change in observations over time has been increasing. Our forecast model is validated since we have good prediction for the period 2020 and data not available for 2021 and 2022. Time series analysis showed that the double exponential smoothing is an efficient tool to model the future data on the raw number of new cancer cases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cancer" title="cancer">cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series" title=" time series"> time series</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction" title=" prediction"> prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=double%20exponential%20smoothing" title=" double exponential smoothing"> double exponential smoothing</a> </p> <a href="https://publications.waset.org/abstracts/164142/forecasting-cancers-cases-in-algeria-using-double-exponential-smoothing-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164142.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">88</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">9535</span> Statistical and Land Planning Study of Tourist Arrivals in Greece during 2005-2016</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dimitra%20Alexiou">Dimitra Alexiou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> During the last 10 years, in spite of the economic crisis, the number of tourists arriving in Greece has increased, particularly during the tourist season from April to October. In this paper, the number of annual tourist arrivals is studied to explore their preferences with regard to the month of travel, the selected destinations, as well the amount of money spent. The collected data are processed with statistical methods, yielding numerical and graphical results. From the computation of statistical parameters and the forecasting with exponential smoothing, useful conclusions are arrived at that can be used by the Greek tourism authorities, as well as by tourist organizations, for planning purposes for the coming years. The results of this paper and the computed forecast can also be used for decision making by private tourist enterprises that are investing in Greece. With regard to the statistical methods, the method of Simple Exponential Smoothing of time series of data is employed. The search for a best forecast for 2017 and 2018 provides the value of the smoothing coefficient. For all statistical computations and graphics Microsoft Excel is used. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=tourism" title="tourism">tourism</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20methods" title=" statistical methods"> statistical methods</a>, <a href="https://publications.waset.org/abstracts/search?q=exponential%20smoothing" title=" exponential smoothing"> exponential smoothing</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20spatial%20planning" title=" land spatial planning"> land spatial planning</a>, <a href="https://publications.waset.org/abstracts/search?q=economy" title=" economy"> economy</a> </p> <a href="https://publications.waset.org/abstracts/85537/statistical-and-land-planning-study-of-tourist-arrivals-in-greece-during-2005-2016" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/85537.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">9534</span> Orthogonal Regression for Nonparametric Estimation of Errors-In-Variables Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anastasiia%20Yu.%20Timofeeva">Anastasiia Yu. Timofeeva</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=grade%20point%20average" title="grade point average">grade point average</a>, <a href="https://publications.waset.org/abstracts/search?q=orthogonal%20regression" title=" orthogonal regression"> orthogonal regression</a>, <a href="https://publications.waset.org/abstracts/search?q=penalized%20regression%20spline" title=" penalized regression spline"> penalized regression spline</a>, <a href="https://publications.waset.org/abstracts/search?q=locally%20weighted%20regression" title=" locally weighted regression"> locally weighted regression</a> </p> <a href="https://publications.waset.org/abstracts/11927/orthogonal-regression-for-nonparametric-estimation-of-errors-in-variables-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11927.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">416</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">9533</span> Quantile Smoothing Splines: Application on Productivity of Enterprises</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Semra%20Turkan">Semra Turkan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we have examined the factors that affect the productivity of Turkey’s Top 500 Industrial Enterprises in 2014. The labor productivity of enterprises is taken as an indicator of productivity of industrial enterprises. When the relationships between some financial ratios and labor productivity, it is seen that there is a nonparametric relationship between labor productivity and return on sales. In addition, the distribution of labor productivity of enterprises is right-skewed. If the dependent distribution is skewed, the quantile regression is more suitable for this data. Hence, the nonparametric relationship between labor productivity and return on sales by quantile smoothing splines. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quantile%20regression" title="quantile regression">quantile regression</a>, <a href="https://publications.waset.org/abstracts/search?q=smoothing%20spline" title=" smoothing spline"> smoothing spline</a>, <a href="https://publications.waset.org/abstracts/search?q=labor%20productivity" title=" labor productivity"> labor productivity</a>, <a href="https://publications.waset.org/abstracts/search?q=financial%20ratios" title=" financial ratios"> financial ratios</a> </p> <a href="https://publications.waset.org/abstracts/60552/quantile-smoothing-splines-application-on-productivity-of-enterprises" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/60552.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">302</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">9532</span> Analysis of Fault Tolerance on Grid Computing in Real Time Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Parampal%20Kaur">Parampal Kaur</a>, <a href="https://publications.waset.org/abstracts/search?q=Deepak%20Aggarwal"> Deepak Aggarwal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the computational Grid, fault tolerance is an imperative issue to be considered during job scheduling. Due to the widespread use of resources, systems are highly prone to errors and failures. Hence, fault tolerance plays a key role in the grid to avoid the problem of unreliability. Scheduling the task to the appropriate resource is a vital requirement in computational Grid. The fittest resource scheduling algorithm searches for the appropriate resource based on the job requirements, in contrary to the general scheduling algorithms where jobs are scheduled to the resources with best performance factor. The proposed method is to improve the fault tolerance of the fittest resource scheduling algorithm by scheduling the job in coordination with job replication when the resource has low reliability. Based on the reliability index of the resource, the resource is identified as critical. The tasks are scheduled based on the criticality of the resources. Results show that the execution time of the tasks is comparatively reduced with the proposed algorithm using real-time approach rather than a simulator. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computational%20grid" title="computational grid">computational grid</a>, <a href="https://publications.waset.org/abstracts/search?q=fault%20tolerance" title=" fault tolerance"> fault tolerance</a>, <a href="https://publications.waset.org/abstracts/search?q=task%20replication" title=" task replication"> task replication</a>, <a href="https://publications.waset.org/abstracts/search?q=job%20scheduling" title=" job scheduling"> job scheduling</a> </p> <a href="https://publications.waset.org/abstracts/1956/analysis-of-fault-tolerance-on-grid-computing-in-real-time-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1956.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">9531</span> Comparison of Receiver Operating Characteristic Curve Smoothing Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=D.%20Sigirli">D. Sigirli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Receiver Operating Characteristic (ROC) curve is a commonly used statistical tool for evaluating the diagnostic performance of screening and diagnostic test with continuous or ordinal scale results which aims to predict the presence or absence probability of a condition, usually a disease. When the test results were measured as numeric values, sensitivity and specificity can be computed across all possible threshold values which discriminate the subjects as diseased and non-diseased. There are infinite numbers of possible decision thresholds along the continuum of the test results. The ROC curve presents the trade-off between sensitivity and the 1-specificity as the threshold changes. The empirical ROC curve which is a non-parametric estimator of the ROC curve is robust and it represents data accurately. However, especially for small sample sizes, it has a problem of variability and as it is a step function there can be different false positive rates for a true positive rate value and vice versa. Besides, the estimated ROC curve being in a jagged form, since the true ROC curve is a smooth curve, it underestimates the true ROC curve. Since the true ROC curve is assumed to be smooth, several smoothing methods have been explored to smooth a ROC curve. These include using kernel estimates, using log-concave densities, to fit parameters for the specified density function to the data with the maximum-likelihood fitting of univariate distributions or to create a probability distribution by fitting the specified distribution to the data nd using smooth versions of the empirical distribution functions. In the present paper, we aimed to propose a smooth ROC curve estimation based on the boundary corrected kernel function and to compare the performances of ROC curve smoothing methods for the diagnostic test results coming from different distributions in different sample sizes. We performed simulation study to compare the performances of different methods for different scenarios with 1000 repetitions. It is seen that the performance of the proposed method was typically better than that of the empirical ROC curve and only slightly worse compared to the binormal model when in fact the underlying samples were generated from the normal distribution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=empirical%20estimator" title="empirical estimator">empirical estimator</a>, <a href="https://publications.waset.org/abstracts/search?q=kernel%20function" title=" kernel function"> kernel function</a>, <a href="https://publications.waset.org/abstracts/search?q=smoothing" title=" smoothing"> smoothing</a>, <a href="https://publications.waset.org/abstracts/search?q=receiver%20operating%20characteristic%20curve" title=" receiver operating characteristic curve"> receiver operating characteristic curve</a> </p> <a href="https://publications.waset.org/abstracts/103835/comparison-of-receiver-operating-characteristic-curve-smoothing-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/103835.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">9530</span> Cryptographic Resource Allocation Algorithm Based on Deep Reinforcement Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xu%20Jie">Xu Jie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As a key network security method, cryptographic services must fully cope with problems such as the wide variety of cryptographic algorithms, high concurrency requirements, random job crossovers, and instantaneous surges in workloads. Its complexity and dynamics also make it difficult for traditional static security policies to cope with the ever-changing situation. Cyber Threats and Environment. Traditional resource scheduling algorithms are inadequate when facing complex decision-making problems in dynamic environments. A network cryptographic resource allocation algorithm based on reinforcement learning is proposed, aiming to optimize task energy consumption, migration cost, and fitness of differentiated services (including user, data, and task security) by modeling the multi-job collaborative cryptographic service scheduling problem as a multi-objective optimized job flow scheduling problem and using a multi-agent reinforcement learning method, efficient scheduling and optimal configuration of cryptographic service resources are achieved. By introducing reinforcement learning, resource allocation strategies can be adjusted in real-time in a dynamic environment, improving resource utilization and achieving load balancing. Experimental results show that this algorithm has significant advantages in path planning length, system delay and network load balancing and effectively solves the problem of complex resource scheduling in cryptographic services. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title="cloud computing">cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=cryptography%20on-demand%20service" title=" cryptography on-demand service"> cryptography on-demand service</a>, <a href="https://publications.waset.org/abstracts/search?q=reinforcement%20learning" title=" reinforcement learning"> reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=workflow%20scheduling" title=" workflow scheduling"> workflow scheduling</a> </p> <a href="https://publications.waset.org/abstracts/193329/cryptographic-resource-allocation-algorithm-based-on-deep-reinforcement-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/193329.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">15</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">9529</span> Cross-Layer Design of Event-Triggered Adaptive OFDMA Resource Allocation Protocols with Application to Vehicle Clusters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shaban%20Guma">Shaban Guma</a>, <a href="https://publications.waset.org/abstracts/search?q=Naim%20Bajcinca"> Naim Bajcinca</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose an event-triggered algorithm for the solution of a distributed optimization problem by means of the projected subgradient method. Thereby, we invoke an OFDMA resource allocation scheme by applying an event-triggered sensitivity analysis at the access point. The optimal resource assignment of the subcarriers to the involved wireless nodes is carried out by considering the sensitivity analysis of the overall objective function as defined by the control of vehicle clusters with respect to the information exchange between the nodes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=consensus" title="consensus">consensus</a>, <a href="https://publications.waset.org/abstracts/search?q=cross-layer" title=" cross-layer"> cross-layer</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed" title=" distributed"> distributed</a>, <a href="https://publications.waset.org/abstracts/search?q=event-triggered" title=" event-triggered"> event-triggered</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-vehicle" title=" multi-vehicle"> multi-vehicle</a>, <a href="https://publications.waset.org/abstracts/search?q=protocol" title=" protocol"> protocol</a>, <a href="https://publications.waset.org/abstracts/search?q=resource" title=" resource"> resource</a>, <a href="https://publications.waset.org/abstracts/search?q=OFDMA" title=" OFDMA"> OFDMA</a>, <a href="https://publications.waset.org/abstracts/search?q=wireless" title=" wireless"> wireless</a> </p> <a href="https://publications.waset.org/abstracts/52766/cross-layer-design-of-event-triggered-adaptive-ofdma-resource-allocation-protocols-with-application-to-vehicle-clusters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52766.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">331</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">9528</span> Application of Rapidly Exploring Random Tree Star-Smart and G2 Quintic Pythagorean Hodograph Curves to the UAV Path Planning Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Luiz%20G.%20V%C3%A9ras">Luiz G. Véras</a>, <a href="https://publications.waset.org/abstracts/search?q=Felipe%20L.%20Medeiros"> Felipe L. Medeiros</a>, <a href="https://publications.waset.org/abstracts/search?q=Lamartine%20F.%20Guimar%C3%A3es"> Lamartine F. Guimarães</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work approaches the automatic planning of paths for Unmanned Aerial Vehicles (UAVs) through the application of the Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm. RRT*-Smart is a sampling process of positions of a navigation environment through a tree-type graph. The algorithm consists of randomly expanding a tree from an initial position (root node) until one of its branches reaches the final position of the path to be planned. The algorithm ensures the planning of the shortest path, considering the number of iterations tending to infinity. When a new node is inserted into the tree, each neighbor node of the new node is connected to it, if and only if the extension of the path between the root node and that neighbor node, with this new connection, is less than the current extension of the path between those two nodes. RRT*-smart uses an intelligent sampling strategy to plan less extensive routes by spending a smaller number of iterations. This strategy is based on the creation of samples/nodes near to the convex vertices of the navigation environment obstacles. The planned paths are smoothed through the application of the method called quintic pythagorean hodograph curves. The smoothing process converts a route into a dynamically-viable one based on the kinematic constraints of the vehicle. This smoothing method models the hodograph components of a curve with polynomials that obey the Pythagorean Theorem. Its advantage is that the obtained structure allows computation of the curve length in an exact way, without the need for quadratural techniques for the resolution of integrals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=path%20planning" title="path planning">path planning</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20smoothing" title=" path smoothing"> path smoothing</a>, <a href="https://publications.waset.org/abstracts/search?q=Pythagorean%20hodograph%20curve" title=" Pythagorean hodograph curve"> Pythagorean hodograph curve</a>, <a href="https://publications.waset.org/abstracts/search?q=RRT%2A-Smart" title=" RRT*-Smart"> RRT*-Smart</a> </p> <a href="https://publications.waset.org/abstracts/92814/application-of-rapidly-exploring-random-tree-star-smart-and-g2-quintic-pythagorean-hodograph-curves-to-the-uav-path-planning-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/92814.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">167</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">9527</span> Overview of Time, Resource and Cost Planning Techniques in Construction Management Research</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Gupta">R. Gupta</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Jain"> P. Jain</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Das"> S. Das</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One way to approach construction scheduling optimization problem is to focus on the individual aspects of planning, which can be broadly classified as time scheduling, crew and resource management, and cost control. During the last four decades, construction planning has seen a lot of research, but to date, no paper had attempted to summarize the literature available under important heads. This paper addresses each of aspects separately, and presents the findings of an in-depth literature of the various planning techniques. For techniques dealing with time scheduling, the authors have adopted a rough chronological documentation. For crew and resource management, classification has been done on the basis of the different steps involved in the resource planning process. For cost control, techniques dealing with both estimation of costs and the subsequent optimization of costs have been dealt with separately. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=construction%20planning%20techniques" title="construction planning techniques">construction planning techniques</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20scheduling" title=" time scheduling"> time scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=resource%20planning" title=" resource planning"> resource planning</a>, <a href="https://publications.waset.org/abstracts/search?q=cost%20control" title=" cost control"> cost control</a> </p> <a href="https://publications.waset.org/abstracts/24164/overview-of-time-resource-and-cost-planning-techniques-in-construction-management-research" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24164.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">487</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">9526</span> Introduction to Multi-Agent Deep Deterministic Policy Gradient</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xu%20Jie">Xu Jie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As a key network security method, cryptographic services must fully cope with problems such as the wide variety of cryptographic algorithms, high concurrency requirements, random job crossovers, and instantaneous surges in workloads. Its complexity and dynamics also make it difficult for traditional static security policies to cope with the ever-changing situation. Cyber Threats and Environment. Traditional resource scheduling algorithms are inadequate when facing complex decisionmaking problems in dynamic environments. A network cryptographic resource allocation algorithm based on reinforcement learning is proposed, aiming to optimize task energy consumption, migration cost, and fitness of differentiated services (including user, data, and task security). By modeling the multi-job collaborative cryptographic service scheduling problem as a multiobjective optimized job flow scheduling problem, and using a multi-agent reinforcement learning method, efficient scheduling and optimal configuration of cryptographic service resources are achieved. By introducing reinforcement learning, resource allocation strategies can be adjusted in real time in a dynamic environment, improving resource utilization and achieving load balancing. Experimental results show that this algorithm has significant advantages in path planning length, system delay and network load balancing, and effectively solves the problem of complex resource scheduling in cryptographic services. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multi-agent%20reinforcement%20learning" title="multi-agent reinforcement learning">multi-agent reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=non-stationary%20dynamics" title=" non-stationary dynamics"> non-stationary dynamics</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-agent%20systems" title=" multi-agent systems"> multi-agent systems</a>, <a href="https://publications.waset.org/abstracts/search?q=cooperative%20and%20competitive%20agents" title=" cooperative and competitive agents"> cooperative and competitive agents</a> </p> <a href="https://publications.waset.org/abstracts/191046/introduction-to-multi-agent-deep-deterministic-policy-gradient" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191046.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">24</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">9525</span> A QoE-driven Cross-layer Resource Allocation Scheme for High Traffic Service over Open Wireless Network Downlink</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Liya%20Shan">Liya Shan</a>, <a href="https://publications.waset.org/abstracts/search?q=Qing%20Liao"> Qing Liao</a>, <a href="https://publications.waset.org/abstracts/search?q=Qinyue%20Hu"> Qinyue Hu</a>, <a href="https://publications.waset.org/abstracts/search?q=Shantao%20Jiang"> Shantao Jiang</a>, <a href="https://publications.waset.org/abstracts/search?q=Tao%20Wang"> Tao Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a Quality of Experience (QoE)-driven cross-layer resource allocation scheme for high traffic service over Open Wireless Network (OWN) downlink is proposed, and the related problem about the users in the whole cell including the users in overlap region of different cells has been solved.A method, in which assess models of the BestEffort service and the no-reference assess algorithm for video service are adopted, to calculate the Mean Opinion Score (MOS) value for high traffic service has been introduced. The cross-layer architecture considers the parameters in application layer, media access control layer and physical layer jointly. Based on this architecture and the MOS value, the Binary Constrained Particle Swarm Optimization (B_CPSO) algorithm is used to solve the cross-layer resource allocation problem. In addition,simulationresults show that the proposed scheme significantly outperforms other schemes in terms of maximizing average users’ MOS value for the whole system as well as maintaining fairness among users. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=high%20traffic%20service" title="high traffic service">high traffic service</a>, <a href="https://publications.waset.org/abstracts/search?q=cross-layer%20resource%20allocation" title=" cross-layer resource allocation"> cross-layer resource allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=QoE" title=" QoE"> QoE</a>, <a href="https://publications.waset.org/abstracts/search?q=B_CPSO" title=" B_CPSO"> B_CPSO</a>, <a href="https://publications.waset.org/abstracts/search?q=OWN" title=" OWN"> OWN</a> </p> <a href="https://publications.waset.org/abstracts/20749/a-qoe-driven-cross-layer-resource-allocation-scheme-for-high-traffic-service-over-open-wireless-network-downlink" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20749.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">541</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">9524</span> Resource Management Framework in Cloud Computing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gagandeep%20Kaur">Gagandeep Kaur</a>, <a href="https://publications.waset.org/abstracts/search?q=Sonal%20Chawla"> Sonal Chawla</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In a Cloud Computing environment, resource provisioning, resource allocation and resource scheduling is the most complex issues these days. Cloud User expects the best resource utilization and Cloud Provider expects revenue maximization by considering budget and time constraints. In this research paper, Resource Management Framework has been proposed to allocate the resources to Cloud Users and Cloud Providers in Cloud environment. The main aim of the proposed work is to provide the resources and services to Cloud Providers and Cloud Users in an efficient and effective manner. The proposed framework has been simulated and tested using the CloudSim simulator tool. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title="cloud computing">cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=resource%20allocation" title=" resource allocation"> resource allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=auction" title=" auction"> auction</a>, <a href="https://publications.waset.org/abstracts/search?q=provisioning" title=" provisioning"> provisioning</a> </p> <a href="https://publications.waset.org/abstracts/145409/resource-management-framework-in-cloud-computing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145409.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">9523</span> Distributed System Computing Resource Scheduling Algorithm Based on Deep Reinforcement Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yitao%20Lei">Yitao Lei</a>, <a href="https://publications.waset.org/abstracts/search?q=Xingxiang%20Zhai"> Xingxiang Zhai</a>, <a href="https://publications.waset.org/abstracts/search?q=Burra%20Venkata%20Durga%20Kumar"> Burra Venkata Durga Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=resource%20scheduling" title="resource scheduling">resource scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20reinforcement%20learning" title=" deep reinforcement learning"> deep reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20system" title=" distributed system"> distributed system</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title=" artificial intelligence"> artificial intelligence</a> </p> <a href="https://publications.waset.org/abstracts/152538/distributed-system-computing-resource-scheduling-algorithm-based-on-deep-reinforcement-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152538.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">111</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">9522</span> Resource Constrained Time-Cost Trade-Off Analysis in Construction Project Planning and Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sangwon%20Han">Sangwon Han</a>, <a href="https://publications.waset.org/abstracts/search?q=Chengquan%20Jin"> Chengquan Jin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Time-cost trade-off (TCTO) is one of the most significant part of construction project management. Despite the significance, current TCTO analysis, based on the Critical Path Method, does not consider resource constraint, and accordingly sometimes generates an impractical and/or infeasible schedule planning in terms of resource availability. Therefore, resource constraint needs to be considered when doing TCTO analysis. In this research, genetic algorithms (GA) based optimization model is created in order to find the optimal schedule. This model is utilized to compare four distinct scenarios (i.e., 1) initial CPM, 2) TCTO without considering resource constraint, 3) resource allocation after TCTO, and 4) TCTO with considering resource constraint) in terms of duration, cost, and resource utilization. The comparison results identify that ‘TCTO with considering resource constraint’ generates the optimal schedule with the respect of duration, cost, and resource. This verifies the need for consideration of resource constraint when doing TCTO analysis. It is expected that the proposed model will produce more feasible and optimal schedule. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=time-cost%20trade-off" title="time-cost trade-off">time-cost trade-off</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithms" title=" genetic algorithms"> genetic algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=critical%20path" title=" critical path"> critical path</a>, <a href="https://publications.waset.org/abstracts/search?q=resource%20availability" title=" resource availability"> resource availability</a> </p> <a href="https://publications.waset.org/abstracts/91630/resource-constrained-time-cost-trade-off-analysis-in-construction-project-planning-and-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/91630.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">187</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">9521</span> Grey Prediction of Atmospheric Pollutants in Shanghai Based on GM(1,1) Model Group</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Diqin%20Qi">Diqin Qi</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiaming%20Li"> Jiaming Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Siman%20Li"> Siman Li</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Based on the use of the three-point smoothing method for selectively processing original data columns, this paper establishes a group of grey GM(1,1) models to predict the concentration ranges of four major air pollutants in Shanghai from 2023 to 2024. The results indicate that PM₁₀, SO₂, and NO₂ maintain the national Grade I standards, while the concentration of PM₂.₅ has decreased but still remains within the national Grade II standards. Combining the forecast results, recommendations are provided for the Shanghai municipal government's efforts in air pollution prevention and control. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=atmospheric%20pollutant%20prediction" title="atmospheric pollutant prediction">atmospheric pollutant prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=Grey%20GM%281" title=" Grey GM(1"> Grey GM(1</a>, <a href="https://publications.waset.org/abstracts/search?q=1%29" title=" 1)"> 1)</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20group" title=" model group"> model group</a>, <a href="https://publications.waset.org/abstracts/search?q=three-point%20smoothing%20method" title=" three-point smoothing method"> three-point smoothing method</a> </p> <a href="https://publications.waset.org/abstracts/185942/grey-prediction-of-atmospheric-pollutants-in-shanghai-based-on-gm11-model-group" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185942.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">35</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">9520</span> An Improved VM Allocation Algorithm by Utilizing Combined Resource Allocation Mechanism and Released Resources in Cloud Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Md%20Habibul%20Ansary">Md Habibul Ansary</a>, <a href="https://publications.waset.org/abstracts/search?q=Chandan%20Garai"> Chandan Garai</a>, <a href="https://publications.waset.org/abstracts/search?q=Ranjan%20Dasgupta"> Ranjan Dasgupta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Utilization of resources is always a great challenge for any allocation problem, particularly when resource availability is dynamic in nature. In this work VM allocation mechanism has been augmented by providing resources in a combined manner. This approach has some inherent advantages in terms of reduction of wait state for the pending jobs of some users and better utilization of unused resources from the service providers’ point of view. Moreover the algorithm takes care of released resources from the finished jobs as soon as those become available. The proposed algorithm has been explained by suitable example to make the work complete. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bid%20ratio" title="Bid ratio">Bid ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud%20service" title=" cloud service"> cloud service</a>, <a href="https://publications.waset.org/abstracts/search?q=virtualization" title=" virtualization"> virtualization</a>, <a href="https://publications.waset.org/abstracts/search?q=VM%20allocation%20problem" title=" VM allocation problem"> VM allocation problem</a> </p> <a href="https://publications.waset.org/abstracts/34024/an-improved-vm-allocation-algorithm-by-utilizing-combined-resource-allocation-mechanism-and-released-resources-in-cloud-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34024.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">396</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">9519</span> Markov-Chain-Based Optimal Filtering and Smoothing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Garry%20A.%20Einicke">Garry A. Einicke</a>, <a href="https://publications.waset.org/abstracts/search?q=Langford%20B.%20White"> Langford B. White</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes an optimum filter and smoother for recovering a Markov process message from noisy measurements. The developments follow from an equivalence between a state space model and a hidden Markov chain. The ensuing filter and smoother employ transition probability matrices and approximate probability distribution vectors. The properties of the optimum solutions are retained, namely, the estimates are unbiased and minimize the variance of the output estimation error, provided that the assumed parameter set are correct. Methods for estimating unknown parameters from noisy measurements are discussed. Signal recovery examples are described in which performance benefits are demonstrated at an increased calculation cost. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimal%20filtering" title="optimal filtering">optimal filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=smoothing" title=" smoothing"> smoothing</a>, <a href="https://publications.waset.org/abstracts/search?q=Markov%20chains" title=" Markov chains"> Markov chains</a> </p> <a href="https://publications.waset.org/abstracts/20256/markov-chain-based-optimal-filtering-and-smoothing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20256.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">317</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span 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