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An Approach to Align Business Process with Business Strategies
, M.Sc. Thesis Sharif University of Technology ; Najafi, Mehdi (Supervisor)
Abstract
Todays, organizations are in a competitive global environment. Therefore, strategic planning followed by strategy implementation is critical for business success more than ever. The ability of organizations to implement strategies is important and useful for the organization’s success in the market and gives them a competitive advantage. Implementation is the process of turning strategies and plans into action in order to accomplish strategic objectives and goals. This research suggests an approach to align business processes with organizational strategies. This approach intends on managing processes based on using resources to achieve goals. The proposed model consists of three cycles which...
Persian sentiment analysis of an online store independent of pre-processing using convolutional neural network with fastText embeddings
, Article PeerJ Computer Science ; Volume 7 , 2021 , Pages 1-22 ; 23765992 (ISSN) ; Yazdinejad, M ; Guo, Y ; Sharif University of Technology
PeerJ Inc
2021
Abstract
Sentiment analysis plays a key role in companies, especially stores, and increasing the accuracy in determining customers’ opinions about products assists to maintain their competitive conditions. We intend to analyze the users’ opinions on the website of the most immense online store in Iran; Digikala. However, the Persian language is unstructured which makes the pre-processing stage very difficult and it is the main problem of sentiment analysis in Persian. What exacerbates this problem is the lack of available libraries for Persian pre-processing, while most libraries focus on English. To tackle this, approximately 3 million reviews were gathered in Persian from the Digikala website using...
Adversarial Attack to Deep Learning Networks via Imperceptible Sparse Perturbation
, M.Sc. Thesis Sharif University of Technology ; Ghaemmaghami, Shahrokh (Supervisor) ; Marvasti, Farokh (Supervisor) ; Amini, Sajad (Co-Supervisor)
Abstract
Nowadays, methods based on deep learning networks are the most effective artificial in telligence methods. Although they have achieved success in various fields (such as machine vision and object recognition), practical and experimental cases show the fragility of deep learning networks against perturbations and unwanted changes of the input pattern. All these perturbations must be in a way that the main class of the perturbed input pattern can be rec ognized by human, but the network makes a mistake in recognizing its correct class. This thesis seeks a more accurate evaluation by designing adversarial attacks such that the main class of the adversarial pattern is detectable by human...
Dynamic response of metal foam FG porous cylindrical micro-shells due to moving loads with strain gradient size-dependency
, Article European Physical Journal Plus ; Volume 134, Issue 5 , 2019 ; 21905444 (ISSN) ; Forsat, M ; Barati, M. R ; Abdella, G. M ; Mohasel Afshari, B ; Hamouda, A. M. S ; Rabby, S ; Sharif University of Technology
Springer Verlag
2019
Abstract
The dynamic characteristics of functionally graded (FG) metal foam cylindrical micro-scale shells in contact with a moving load will be analyzed thorough this paper accounting for strain-gradient size-dependency. In the material structure of a metal foam, pores can diffuse uniformly or non-uniformly. Based upon Laplace transform, the dynamical governing equations of the first-order micro-shell model can be established in a new domain. In order to go back into the time domain, an inverse Laplace transform will be required. Thus, on can express the time response or dynamic deflection of the micro-shell under moving load. In the presented results, it is easy to see the prominence of...