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مقاله
1 - Buckling Analyses of Rectangular Plates Composed of Functionally Graded Materials by the New Version of DQ Method Subjected to Non-Uniform Distributed In-Plane LoadingJournal of Solid Mechanics , شماره 1 , سال 1 , زمستان 2009In this paper, the new version of differential quadrature method (DQM), for calculation of the buckling coefficient of rectangular plates is considered. At first the differential equations governing plates have been calculated. Later based on the new version of differen چکیده کاملIn this paper, the new version of differential quadrature method (DQM), for calculation of the buckling coefficient of rectangular plates is considered. At first the differential equations governing plates have been calculated. Later based on the new version of differential quadrature method, the existing derivatives in equation are converted to the amounts of function in the grid points inside the region. Having done that, the equation will be converted to an eigen value problem and the buckling coefficient is obtained. Solving this problem requires two kinds of loading: (1) unaxial half-cosine distributed compressive load and (2) uni-axial linearly varied compressive load. Having considered the answering in this case and the analysis of the effect of number of grid points on the solution of the problem, the accuracy of answering is considered, and also the effect of power law index over the buckling coefficient is investigated. Finally, if the case is an isotropic type, the results will be compared with the existing literature. پرونده مقاله -
مقاله
2 - Sentimental Categorization of Persian News Headlines using Three Machine Learning Techniques Versus Human CategorizationJournal of Advances in Computer Research , شماره 5 , سال 10 , پاییز 2019The aim of this paper is to elaborate on an attempt to classify Persian news headlines using machine learning techniques rather than human-based analysis. Three major techniques namely Naïve Bayes, Maximum Entropy and Support Vector Machine were introduced and appl چکیده کاملThe aim of this paper is to elaborate on an attempt to classify Persian news headlines using machine learning techniques rather than human-based analysis. Three major techniques namely Naïve Bayes, Maximum Entropy and Support Vector Machine were introduced and applied to Persian news headlines. Results were compared with each other as well as the human analysis. It is concluded that these techniques outperform human analysis and one technique (Naïve Bayes) is superior to all the techniques mentioned. It can be concluded from this study that the inclusion of discourse analysis is necessary in order to attain better results since the whole is not necessarily the sum of the parts. It means that what you see in the headline does not necessarily reflect what is mentioned in the news itself. So it is recommended that in future studies, elements from discourse analysis be introduced into these algorithms so that better results can be achieved. پرونده مقاله