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akhondzadeh--shamseddin
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Persian Aspect-based Sentiment Analysis using Unsupervised Learning Methods
, M.Sc. Thesis Sharif University of Technology ; Ghasem-Sani, Gholamreza (Supervisor)
Abstract
Sentiment analysis, is a subfield of natural language processing that aims at opinion mining to analyze thoughts, orientation and evaluation of users within some texts. Different organizations in multiple social domains, use this approach as a tool to asses their strengths and shortcomings. In sentiment analysis, the goal is to use machine learning techniques with the purpose of specifying users’ positive or negative orientation about a product or merchandise. The solution to this problem includes two main steps: extracting aspects and determining users’ positive or negative sentiments in respect to the aspects. Two main challenges of sentiment analysis in Farsi, are lack of comprehensive...
An efficient enrichment strategy for modeling stress singularities in isotropic composite materials with X-FEM technique
, Article Engineering Fracture Mechanics ; Volume 169 , 2017 , Pages 201-225 ; 00137944 (ISSN) ; Khoei, A. R ; Broumand, P ; Sharif University of Technology
Elsevier Ltd
2017
Abstract
An efficient enrichment strategy is presented for modeling stress singularities in multi-material problems and crack-tips terminating at a bi-material interface within the X-FEM framework. The eigen-function expansion method is employed to evaluate eigen-values and asymptotic fields around singular points. The generalized stress intensity factors are defined on the basis of direct and interaction integral techniques. Numerical examples are solved for different types of eigen-values, and the convergence study is performed to investigate the accuracy of the proposed enrichment strategy. The results indicate that the proposed method has superior accuracy, higher convergence rate and lower...
Numerical Simulation of Stress Singularities and Crack Propagation Path in Composite Materials Using X-FEM Method
, M.Sc. Thesis Sharif University of Technology ; Khoei, Amir Reza (Supervisor)
Abstract
In the present study, in order to investigate the nature of stress singularities in isotropic multimaterial wedges and junctions, determination of the singularity order and analytical asymptotic fields in the vicinity of singular points using the eigen-function expansion method are explained. Next, an efficient approach is proposed to model stress singularities within the X-FEM framework. In this approach, the Airy stress function coefficients are employed in conjunction with the standard singular enrichment functions to obtain modified singular enrichments. Performance and accuracy of the proposed method is shown via computation of the energy norm error and the convergence rates are...
Neural network prediction of mechanical properties of porous NiTi shape memory alloy
, Article Powder Metallurgy ; Volume 54, Issue 3 , Nov , 2011 , Pages 450-454 ; 00325899 (ISSN) ; Hafizpour, H. R ; Sadrnezhaad, S. K ; Akhondzadeh, A ; Abbasi Gharacheh, M ; Sharif University of Technology
2011
Abstract
A multilayer back propagation learning algorithm was used as an artificial neural network tool to predict the mechanical properties of porous NiTi shape memory alloys fabricated by press/sintering of the mixed powders. Effects of green porosity, sintering time and the ratio of the average Ti to Ni particle sizes on properties of the product were investigated. Hardness and tensile strength of the compacts were determined by hardness Rockwell B method and shear punch test. Three-fourths of 36 pairs of experimental data were used for training the network within the toolbox of the MATLAB software. Porosity, sintering time and particle size ratios were defined as the input variables of the model....