Sharif Digital Repository

Due to financial resources constraints, the country's oil industry, especially the upstream oil sector accounting for most of the country's foreign exchange and budget revenues, has not been developed. Thanks to the international sanctions against our country, the conventional financing methods are difficult to use anymore. According to the the current circumstances, the alternative sources of funding using modern approaches are necessary. Moreover, small capital is one of the alternative sources with the high potential for the high level of the liquidity in the society. This study, investigates the financial tools regarding capital market to attract small capital in order to finance... 

Additive manufacturing (AM) has gained significant attention in recent years as a novel approach to fabricate three-dimensional parts. Its advantages, including high speed, low-cost production for small-scale batches, and greater design freedom, have made it a competitive alternative to traditional manufacturing methods. However, the application of AM for components subjected to fretting fatigue requires careful evaluation. Fretting fatigue is a major cause of failure in turbines, particularly at the contact interface between turbine blade roots and disk. In this study, the influence of AM and post-processing treatments on the fretting fatigue life of Ti-6Al-4V alloy was investigated. Five... 

The need to estimate a positive definite or positive semi-definite solution to an overdetermined linear system of equations with multiple right hand side vectors arises in several process control contexts. A similar problem is encountered in certain contexts related to statistics and control theory with the unknown matrix being positive semi-definite. The coefficient and the right hand side matrices are respectively named data and target matrices. A number of optimization methods were proposed for solving such problems, in which the data matrix is unrealistically assumed to be error free. Here, considering error in measured data and target matrices, we present new approachs to solve two... 

Purpose of this study is the assignment of the optimal monetary policy rule with attention to housing price with base of setting and to estimating a Dynamic Stochastic General Equilibrium modeling (DSGE). This study has two steps. In the first step we set a model with base of Households, firms, government, and monetary sector behavior and with attention to important variables like outcome, consumption, and investment, the model will be caliber and by simulation it will be evaluated. In the second step we determine optimal monetary rule and the model simulate again with this monetary rule. The comparison between two simulation for verity of shocks shows us that the optimal monetary policy... 

One of the most important problems in machine learning is investigating the performance of the learning algorithms, and especially deep neural networks, on adversarial examples, which are generated by imperceptibly perturbing input images, so that cause the model make a wrong prediction. Not only this line of research is important for making deep neural networks dependable, but also can help with understanding the fundamental limitations of deep neural networks, and the nature of their operation, which can in turn provide researchers with valuable insights into artificial intelligence. In this research work, we have tried to approach the topic with a mainly theoretical mindset. The method we... 

Existing face forgery detection methods mainly focus on certain features of images, such as features related to image noise, local textures or frequency statistics of images for forgery detection. This makes the extracted representations and the final decision depend on the data in the database and makes it difficult to detect forgery with unknown manipulation methods. Solving this challenge, which is called the generalization challenge in artificial intelligence literature, has become the main goal of researchers in this field. In this thesis, the focus is on extracting effective features for success in forgery detection and preventing the performance of the forgery detection network from... 

In recent years, deep learning has experienced rapid and remarkable advancements, demonstrating exceptional performance in various applications such as computer vision, natural language processing, and autonomous vehicles. These models are continually evolving and expanding, yet they harbor inherent vulnerabilities that prevent complete trust in their reliability. One of the most critical issues is their susceptibility to adversarial attacks, where a clean image is subtly manipulated to create an adversarial example. Adversarial examples, generated by adding imperceptible perturbations to input data, can easily mislead deep learning models into making highly confident yet incorrect... 

Wind energy technologies guarantee low pollution and operational costs. Using a DFIG and a fractionally rated power electronics converter gives variable speed operation with a low cost drive train. As energy policy organizations have allocated a considerable quota of wind energy generation to offshore wind farms, the absence of slip rings and brushes in the brushless DFIG (BDFIG) is an advantage for offshore wind turbines where maintenance is vital and expensive. With increasing wind power penetration in power systems, grid code requirements are an important consideration for the ride-through capability of wind farms through voltage dips, particularly for multi- MW wind turbine generators....