Sharif Digital Repository

In the present project, a stringed cavity, specifically the body of the Persian Setar, was studied using computational simulation. This study was carried out via acoustic approaches, based on structural and sound wave interactions. At first, the effects of different structural components were considered, separately. Based on vibrational modal analysis, dynamic characteristics of the elastic structure was investigated in terms of calculated vibrational normal modes. Then, the details of the whole structure was analyzed and the effects of these details on the quality of the produced sounds were investigated by applying some specific changes. The eigenmodes of Setar’s sound board and body, and... 

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... 

This research is conducted aiming to analyze the Customer Knowledge Management and Customer Interaction Management in CRM in Iran Insurance Industry. Cheng and Yang Model was utilized for analyzing the two aforementioned parameters. The current research is descriptive and survey was conducted for data gathering. The research population involves 80 employees working in Technical and Marketing segments of the 5 insurance companies (Iran, Asia, Alborz, Dana, Parsian). The dependent parameter is Customer Interaction Management and the independent parameter is Customer Knowledge Management. The data collected from conducting the survey is analyzed by LISREL software and with Structural Equation... 

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.... 

Deep learning is one of the most powerful branches of machine learning, demonstrating exceptional performance in tasks such as image and speech recognition with the help of neural networks. However, deep learning networks are highly vulnerable to small and intentional changes in input data, known as adversarial perturbations. These perturbations, despite having a significant impact on the model's output, are usually imperceptible to humans and can pose serious security challenges in sensitive areas such as autonomous vehicles and medical diagnostics. To counter these perturbations, extensive research has been conducted, most of which has utilized a single deep learning network to create a... 

The Dye-sensitizers loading on TiO2 is decreasing the electron excitation energy and therefore improving the photocatalytic performance from the increasing the sensitivity under visible light irradiation.in this project CoPCTS , Mordant dye and N3(Ruthenium 535) used as dye-sensitizers. Also The addition of VIII group metals on TiO2 is improving the photocatalytic activity that increasing the photocatalytic reaction rate because of the intermediation role of them for moving the conduction band electrons to electron acceptors and increasing the pair electron-holes long-life that in this case Pt loading used as a VIII group metal. In this project Titanium Isopropoxide as a precursore and...