Sharif Digital Repository

Two-dimensional (2D) nanomaterials are ultrathin nanomaterials with a high degree of anisotropy and chemical functionality. Research on 2D nanomaterials is still in its infancy, with the majority of research focusing on elucidating unique material characteristics and few reports focusing on biomedical applications of 2D nanomaterials. Here we report the properties and application of 2Dnanomaterials in field of bio technology while used main material in our project is graphene oxide for investigating its antibacterial properties. Because the properties of graphene oxide (GO)-based materials strongly depend on the lateral size and size distribution of GO nanosheets; therefore, GO and its... 

This thesis investigates the scheduling of television advertisements, which is critical for optimizing the efficiency and profitability of marketing campaigns for TV networks. Since its inception in the 1930s, television has been a cornerstone of advertising, enabling businesses to reach broad and diverse audiences. The evolution of TV advertising strategies, particularly with the rise of digital media competition, underscores the importance of effective advertisement scheduling to maintain relevance and effectiveness. To address this challenge, a comprehensive mixed-integer linear programming (MILP) model was developed. This model incorporates various hypotheses to manage real-world... 

A probabilistic approach to modeling the seismic damage incurred by structural and nonstructural components is developed in this study. For this purpose, Bayesian linear regression is employed to characterize the epistemic uncertainty in the model. In this approach, regressors are constructed based on the mechanics of damage. In turn, the probability distributions of the model parameters and the model error are quantified by Bayesian regression using real-life data from laboratory experiments and/or post-earthquake inspections of damaged components. The study presents the stepwise procedure of collecting the observations, quantifying the repair costs, developing model forms, performing model... 

DeepFake is a type of forgery that uses deep learning algorithms to make changes to audio and video content that the audience is unable to detect. Nowadays, due to the threats posed by the use of DeepFake to move people's faces in video, researchers' attention has been drawn to designing methods to detect this type of forgery. Detection methods are usually classified into two types. The first case is the extraction of features to detect forgery distortions, for example, the extraction of facial orientations to detect inconsistencies. The second case is the use of deep learning networks for feature extraction and classification, of which the EfficientNet network is an example. Despite the...