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    Physical Modeling of Group Pile Response to Liquefaction-Induced Lateral Spreading by Shaking Table Tests

    , M.Sc. Thesis Sharif University of Technology Asefzadeh, Arian (Author) ; Haeri, Mohsen (Supervisor)
    Abstract
    In recent earthquakes piles have been severely damaged due to liquefaction-induced lateral spreading. Liquefaction causes lateral spreading in gently sloped saturated soft granular soils, leading to significant damage in structures and deep foundations. Although in recent years many studies have focused on different aspects of this phenomenon, the complex nature of the dynamic interaction between piles and liquefied soil is not yet fully understood. Thus more studies in this regard is inevitable. The present research focuses on the discussion and analysis of two large scale shaking table tests of 2x2 and 3x3 group piles. A three layer soil profile was used for the model, consisting of one... 

    An Integrated Multi-criteria Decision Making Approach for a Sustainable Supply Chain Network Design

    , M.Sc. Thesis Sharif University of Technology Arian, Ebrahim (Author) ; Shavandi, Hassan (Supervisor)
    Abstract
    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... 

    Characterization of Plasma Etching Process Using Plasmonic Structures

    , M.Sc. Thesis Sharif University of Technology Arian, Kiarash (Author) ; Rashidian, Bizhan (Supervisor)
    Abstract
    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,... 

    Pathwise grid valuation of fixed-income portfolios with applications to risk management

    , Article Heliyon ; Volume 8, Issue 7 , 2022 ; 24058440 (ISSN) Zamani, S ; Chaghazardi, A ; Arian, H ; Sharif University of Technology
    Elsevier Ltd  2022
    Abstract
    Numerical calculation of Value-at-Risk (VaR) for large-scale portfolios poses great challenges to financial institutions. The problem is even more daunting for large fixed-income portfolios as their underlying instruments have exposure to higher dimensions of risk factors. This article provides an efficient algorithm for calculating VaR using a historical grid-based approach with volatility updating and shows its efficiency in computational cost and accuracy. Our VaR computation algorithm is flexible and simple, while one can easily extend it to cover other nonlinear portfolios such as derivative portfolios on equities and FX securities. © 2022  

    Study of the behavior of pile groups during lateral spreading in medium dense sands by large scale shake table test

    , Article International Journal of Civil Engineering ; Vol. 12, Issue. 3 , 2014 , pp. 374-391 ; ISSN: 17350522 Kavand, A ; Haeri, S. M ; Asefzadeh, A ; Rahmani, I ; Ghalandarzadeh, A ; Bakhshi, A ; Sharif University of Technology
    2014
    Abstract
    In this paper, different aspects of the behavior of 2×2 pile groups under liquefaction-induced lateral spreading in a 3-layer soil profile is investigated using large scale 1g shake table test. Different parameters of the response of soil and piles including time-histories of accelerations, pore water pressures, displacements and bending moments are presented and discussed in the paper. In addition, distribution of lateral forces due to lateral spreading on individual piles of the groups is investigated in detail. The results show that total lateral forces on the piles are influenced by the shadow effect as well as the superstructure mass attached to the pile cap. It was also found that... 

    Portfolio Value-at-Risk and expected-shortfall using an efficient simulation approach based on Gaussian Mixture Model

    , Article Mathematics and Computers in Simulation ; Volume 190 , 2021 , Pages 1056-1079 ; 03784754 (ISSN) Seyfi, S. M. S ; Sharifi, A ; Arian, H ; Sharif University of Technology
    Elsevier B.V  2021
    Abstract
    Monte Carlo Approaches for calculating Value-at-Risk (VaR) are powerful tools widely used by financial risk managers across the globe. However, they are time consuming and sometimes inaccurate. In this paper, a fast and accurate Monte Carlo algorithm for calculating VaR and ES based on Gaussian Mixture Models is introduced. Gaussian Mixture Models are able to cluster input data with respect to market's conditions and therefore no correlation matrices are needed for risk computation. Sampling from each cluster with respect to their weights and then calculating the volatility-adjusted stock returns leads to possible scenarios for prices of assets. Our results on a sample of US stocks show that... 

    Customer Churn Prediction in Therapy Policy in Iran

    , M.Sc. Thesis Sharif University of Technology Khosravi, Mahnaz (Author) ; Aslani, Shirin (Supervisor) ; Arian, Hamidreza (Supervisor)
    Abstract
    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... 

    Comparative evaluation of advanced gas turbine cycles with modified blade cooling models [electronic resource]

    , Article Proceedings of the ASME Turbo Expo ; Volume 4, Pages 537-546 , 2006 Tabari, A ; Sharif University of Technology
    2006
    Abstract
    Advanced gas turbine cycles use advanced blade cooling technologies to reach high turbine inlet temperature. Accurate modeling and optimization of these cycles depend on blade cooling model. In this study, different models have been used to simulate gas turbine performance. The first model is the continuous model and the second is stage-by-stage model with alternative methods for calculating coolant, stagnation pressure loss and SPR. Variation of specific heat and enthalpy with temperature are included in both models. The composition of gas stream in turbine is changed step by step due to air cooling. These models are validated by two case study gas turbine results, which show good agreement... 

    Estimation of a Portfolio's Value-at-Risk Using Variational Auto-Encoders

    , M.Sc. Thesis Sharif University of Technology Moghimi, Mehrdad (Author) ; Arian, Hamidreza (Supervisor) ; Talebian, Masoud (Supervisor)
    Abstract
    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... 

    Calculating Value at Risk for Bond Portfolios by Selecting Basic Scenarios in the Historical Simulation Method

    , M.Sc. Thesis Sharif University of Technology Chaghazardi, Ali (Author) ; Zamani, Shiva (Supervisor) ; Arian, Hamid Reza (Supervisor)
    Abstract
    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... 

    Investor Experience in Chabahar Free Zone: Scale Generation

    , M.Sc. Thesis Sharif University of Technology Pourvaziri, Rouhollah (Author) ; Najmi, Manoochehr (Supervisor) ; Arian, Hamidreza (Supervisor)
    Abstract
    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... 

    Portfolio Management: Combining Hierarchical Models with Prior Hierarchical Structure

    , M.Sc. Thesis Sharif University of Technology Shahryarpoor, Farhad (Author) ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
    Abstract
    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... 

    Integrating Supervised and Unsupervised Machine Learning Algorithms for Profit-based Credit Scoring

    , M.Sc. Thesis Sharif University of Technology Mehrabi, Amir (Author) ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
    Abstract
    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... 

    Patch testing in Iranian children with allergic contact dermatitis

    , Article BMC Dermatology ; Volume 16, Issue 1 , 2016 ; 14715945 (ISSN) Mortazavi, H ; Ehsani, A ; Sajjadi, S. S ; Aghazadeh, N ; Arian, E ; Sharif University of Technology
    BioMed Central Ltd  2016
    Abstract
    Background: Allergic contact dermatitis is a common disorder in adults and children alike and appears to be on the increase. The purpose of this study was to determine the sensitization trends in Iranian children with contact dermatitis. Methods: The result of 109 patch tests performed using the 24 allergens of the European Standard Series in patients below 18 years old from September 2007 to March 2009 were recorded and analyzed. The tests were evaluated at 48 and 72 h after performing. Results: The study population consisted of 72 (66.1 %) females and 37 (33.9 %) males. Hands were the most commonly affected anatomic site. In the final evaluation of the tests on day three, 51 (46.8 %)... 

    Optimal Distance Calculation Method for Portfolio Optimization using
    Nested Cluster Optimization

    , M.Sc. Thesis Sharif University of Technology Rafatnezhad, Ramtin (Author) ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
    Abstract
    In the basic model of this thesis, which is called nested cluster optimization, only one distance function is used for clustering to form clusters with similar characteristics, while depending on whether the optimization model is long-only or long-short, different functions can be used. The aim of this thesis is to find the optimal distance function between assets in the simple nested cluster optimization so that during three different and separate strategies, based on three criteria of the lowest risk, the highest Sharpe ratio, and the highest return, the optimal distance function of assets is selected and clustering and finally weighting the portfolio to be done. The optimal distance... 

    Bitcoin Price Prediction based on Artificial Intelligence Models

    , M.Sc. Thesis Sharif University of Technology Shadkam, Mohammad Saeed (Author) ; Arian, Hamid Reza (Supervisor) ; Talebian, Masoud (Supervisor)
    Abstract
    Cryptocurrencies (cryptos), as a new type of money, are considered a medium of exchange, an investment asset, and a hedging tool in today's world. In 2008, bitcoin as the first cryptocurrency was introduced, which has survived through recent years and has gained more and more popularity every day. Cryptos are one of the first applications of blockchain, the technology that many expect to revolutionize the future world in different ways. We aim to investigate what affects the bitcoin price, based on artificial intelligence and, in particular, machine learning. First, we find features impacting bitcoin price via a thorough investigation of the literature. Then, applying machine learning and... 

    Assessment of Risk Arising from Changes in Implied Volatility in Option Portfolios

    , M.Sc. Thesis Sharif University of Technology Moslemi Haghighi, Alireza (Author) ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
    Abstract
    This study delves into the intricate realm of risk evaluation within the domain of specific financial derivatives, notably options. Unlike other financial instruments, like bonds, options are susceptible to broader risks. A distinctive trait characterizing this category of instruments is their non-linear price behavior relative to their pricing parameters. Consequently, evaluating the risk of these securities is notably more intricate when juxtaposed with analogous scenarios involving fixed-income instruments, such as debt securities. A paramount facet in options risk assessment is the inherent uncertainty stemming from first-order fluctuations in the underlying asset’s volatility. The... 

    Customer Churn Prediction in the Iran Insurance Industry

    , M.Sc. Thesis Sharif University of Technology Etemad Hosseini, Amir Hossein (Author) ; Aslani, Shirin (Supervisor) ; Arian, Hamid Reza (Supervisor)
    Abstract
    Insurance companies in Iran operate in a completely competitive and dynamic environment. Because customer acquisition in these companies is significantly more expensive than customer retention, with timely forecasting of churning customers, they can manage their customers more effectively. In this study, in order to predict customer churn in the insurance industry, the data of one of the Iranian insurance companies that has more than two million insurers were used. In order to identify important data and variables, previous studies were reviewed, and on the other hand, the Central Insurance Regulations of the Islamic Republic of Iran, as well as the information of the insurance contracts of... 

    The Predicting Power of Investors’ Sentiment for Cryptocurrency Returns

    , M.Sc. Thesis Sharif University of Technology Hejranfar, Mohammad Reza (Author) ; Arian, Hamid Reza (Supervisor) ; Hagh Panah, Farshad (Co-Supervisor)
    Abstract
    Classical financial literature believes that people's decisions in financial markets are rational and that asset prices remain at their intrinsic value. On the other hand, behavioral finance literature believes that there are limitations in investors' decision-making and the impact of decisions on emotions, and states that investors' emotions directly affect asset prices. The aim of this research is to investigate which of the famous indicators introduced in the literature as a representative of the emotional behavior of investors has a better performance in predicting the returns of cryptocurrencies. For this purpose, in the first step, the information related to the calculation of three... 

    Heterogeneous catalytic ozonation by Nano-MgO is better than sole ozonation for metronidazole degradation, toxicity reduction, and biodegradability improvement

    , Article Desalination and Water Treatment ; Volume 57, Issue 35 , 2016 , Pages 16435-16444 ; 19443994 (ISSN) Kermani, M ; Bahrami Asl, F ; Farzadkia, M ; Esrafili, A ; Salahshour Arian, S ; Khazaei, M ; Dadban Shahamat, Y ; Zeynalzadeh, D ; Sharif University of Technology
    Taylor and Francis Inc  2016
    Abstract
    Abstract: In the current paper, the removal efficiency of metronidazole (MNZ) using a catalytic ozonation process (COP) in the presence of magnesium oxide nanocrystals, as a catalyst, was investigated in deionized water and compared with a sole ozonation process (SOP). The influence of several operational factors on both removal processes was evaluated: solution pH, MgO dosage, initial MNZ concentration, and reaction time. Biodegradability improvement, mineralization rate, oxidation intermediates, and toxicity were also studied for the COP. The results showed that MgO nanocrystals accelerated MNZ removal compared to the SOP. The optimum pH for both SOP and COP was obtained at 10 and optimum...