Loading...
Search for:
suri--sajad
0.053 seconds
Woman-Headed Household and Household Welfare An Emprical Study for Iran
,
M.Sc. Thesis
Sharif University of Technology
;
Suri, Davood
(Supervisor)
Abstract
This research aimed to investigate the relationship between household poverty and the gender of the head in the Iranian households. The self-reported gender of the head of household (FHH), underestimates the rate of poverty in female- head households (FHH). The self-reported gender of the head of household considers, conventionally, a family as male-head, even if the man of the family is incapable of making money. In much of these families the wife is the sole income holder even though she is not recognized as the head. In this study, a definition for household headship is introduced, which considers head of household the one who provides more than 50% of household income. Using household’s...
Upscaling Compositional Simulation of Gas Injection Process Due to Enhanced Oil Recovery from an Oil Reservoir
, M.Sc. Thesis Sharif University of Technology ; Ghazanfari, Mihammad Hossein (Supervisor)
Abstract
Gas injection is a common method for enhanced oil recovery. Simulating the processes involved in this method requires solving compositional equations, which are computationally expensive, highlighting the need for compositional upscaling. Upscaling methods are categorized into three groups: single-phase, two-phase, and compositional upscaling. To execute reservoir flow models in coarse-scale simulations, all relevant parameters, including rock properties, flow functions, and phase properties of components, must be upscaled. In this study, due to the need for modifying flow equations, access to the source code of a reservoir simulator is necessary. Thus, a black-oil simulator and subsequently...
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...