Sharif Digital Repository

In past few centuries , dams have been always a crucial part of human life . Using dams for agriculture and supplying water for people , has made them a valuable asset for countries . So evaluating dam safety and dam breach properties is so important. This issue is a geotechnical , structural and hydrological matter. Safety of earth dams could be threatened due to dam body breach caused by overtopping or pipping, during heavy floods, strong ground motions or any structural damage or defection. As in previous studies , calculating the final geometrical breach properties and time of failure was the main goal , we tried to connect this characteristics and find the relation of time and breach... 

The aim of the present thesis is to develop a novel heuristic filter by utilizing Firefly Optimization Algorithm for state estimation of nonlinear, non-Gaussian systems. The proposed filter formulates the estimation problem as a dynamic, stochastic one. The swarm intelligence of the fireflies enables the filter to find and track the best estimation. To estimate the states of a system, the model of the system is required. Hence, an 8-DoF quadrotor with slung payload system, as a case study, is modeled by the tensor method. In this case, as a highly nonlinear system, in order not to rely on extra sensors for monitoring swing-angle, the estimation of payload states is needed. In this regard,... 

Reactive crystallization or precipitation is an important industrial process. Many chemicals and biochemicals such as catalysts and pigments are produced by precipitation. Because of the advantages of impinging jets in chemical engineering processes, the main aim of this research was to investigate the application of this method in precipitation and to study the effects of different operating and design parameters on the product’s quality and properties. Two chemical models of barium sulfate and copper oxalate were used as main products. Each of these chemicals was produced by a liquid-liquid reaction of two aqueous solutions, which were fed to an impinging-jets reactor. Effects of... 

Growing concerns towards social and environmental issues besides economic in supply chain causes that the sustainable supply chain become one of the most important concepts in a supply chain. Likewise, a supply chain network design which is profound influence on long-run economic, environmental, and social decisions is one of the key and strategic topics in a supply chain. In this study, we represent an integrated approach for a three-layer sustainable supply chain network design with routing and different transportation modes, the objectives of which are minimizing total costs, a minimizing 〖CO〗_2 emissions of transportation, and maximizing total values of social purchasing. In this... 

plasma characterization has become an essential tool for characterization of etching process in fabrication of nano-electronic devices. The existing methods, such as Langmuir probe and interferometry, have shown drawbacks including disturbing the plasma and sensitivity to mechanical and thermal stability of the measuring systems. In recent years, due to the scale down of microelectronic devices and increase of their sensitivity to disturbance in the plasma etching process, a demand for measuring methods offering less disturbance has arisen. Plasmonic structures, owing to their unprecedented field enhancement and confinement, have been extensively studied. Their sub-wavelength dimensions,... 

The six-vertex model is one of the lattice models of two dimensional statistical physics. In this model, like other models in statistical physics, the probability of occurrence of any configuration is proportional to the product of some local weights.The partition function of the model is the sum of products of local weights over all of the allowable configurations. The partition function has important physical interpretations and computing it is regarded as the first step toward the understanding of the model. In this thesis, we give a survey on different methods of calculating the partition functions. The important point is the generality of these methods such as employing Yang-Baxter... 

Using customer relationship management systems has led to the formation of databases containing businesses customer information. Increased competition in the markets, limited resources and high costs of attracting new customers compared to retaining existing customers have made customer retention an inevitable subject for business owners. Meanwhile, insurance companies, which due to their long history have suitable databases of product information and their customers, have resorted to using their databases to manage the relationship with their customers. In this research, while predicting customers churn in health insurance, as one of the most widely used products of domestic insurance... 

Optimizing optical tweezers and achieving powerful traps has always been a challenging topic for researchers , since the trap stiffness increases with increasing laser power which may damage specimens , especially biological ones and cells . In this thesis , we introduce a special geometry and structure of particles that , have the possibility to increase the stiffness (strength) of the optical trap and cause the magnetic response of particles at optical frequencies . Special geometries such as a combination of dielectric particles with magnetic nanoparticles that emphasize the role of the laser magnetic field and lead to changes in the electrical and magnetic properties at the laser... 

One of the most crucial aspects of financial risk management is risk measurement. Advanced AI-based solutions can provide the proper tools for assessing global markets, given the complexity of the global economy and the violation of typical modeling assumptions. A new strategy for quantifying stock portfolio risk based on one of the machine learning models known as Variational Autoencoders is provided in this dissertation. The suggested method is a generative model that can learn the stocks' dependency structure without relying on assumptions about stock return covariance and produce various market scenarios using cross-sectional stock return data with a higher signal-to-noise ratio. We... 

I investigate methods of integrating prior hierarchical structure into hierarchical portfolio optimization methods. My contributions to the literature are forming a prior hierarchical structure based on investors' priorities and generating a unique representative distance matrix, which can be used as an input to other portfolio optimization methods too. In addition, I use SIC and GICs industry classifications as priory information for S&P500 companies and use them as a complementary input to the Hierarchical Risk Parity model and Hierarchical Equal Risk Contribution and compare the resultant portfolios' performance with (López de Prado, 2019)’s method of integrating prior information and... 

In this study, we combined supervised and unsupervised machine learning algorithms, included the benefits of true identification of good borrowers and costs of false identification of bad borrowers, and then proposed a model for predicting the default of loan applicants with a profit-based approach. The results show that our proposed model has the best performance in profit measure in comparison with individual supervised models. In fact, we first divided the data into two train sets and one test set. We have constructed our model by training unsupervised models on the first train set and supervised models on the second train set. The results of implementing the model on the Australian and... 

Free economic zones in Iran have been established with the goal of developing infrastructure, improving living conditions, fostering economic growth, attracting capital and increasing income, productive job creation, regulating job and goods market, maintaining active presence in international and regional markets, manufacturing and exporting of goods and providing public services. Yet many free economic zones have fallen short of these goals. Considering the government's inability to fund the development of the free economic zones with its limited financial capacity and shortcomings in terms of management system, it is imperative to the development of these regions that private sector... 

In many methods of calculating Value-at-Risk (VaR), we need to calculate the value of the portfolio several times for different scenarios. Because an explicit formula is not available to calculate the value of some fixed income assets, calculating VaR for portfolios containing these assets imposes a heavy computational burden. In this study, we introduce a new method for calculating VaR for such portfolios. In this method, some of the existing scenarios are selected as basic scenarios and the value of the portfolio is calculated only for each of them. Next, using the calculated values, the portfolio values for other scenarios are estimated by interpolation (or extrapolation). Finally, by... 

differential equations. These methods have extensive applications in the financial domain, including in risk hedging and derivative pricing. One of the main advantages of using deep learning methods in this area is their high capability to solve high-dimensional problems. Despite the introduction of these new methods, some of them have not performed well in certain problems. In this research, efforts have been made to improve the efficiency of these methods by enhancing the neural network architecture and modifying the learning process