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    Temperature and composition effect on CO2 miscibility by interfacial tension measurement

    , Article Journal of Chemical and Engineering Data ; Volume 58, Issue 5 , March , 2013 , Pages 1168-1175 ; 00219568 (ISSN) Zolghadr, A ; Escrochi, M ; Ayatollahi, S ; Sharif University of Technology
    2013
    Abstract
    Crude oil reservoirs have different temperatures, compositions, and pressures, therefore oil recovery performance by CO2 injection varies from one case to another. Furthermore, it is predicted that lower interfacial tension between injected CO2 and reservoir fluid results in more oil recovery. In this study, we investigate the effect of temperature on the equilibrium interfacial tension between CO2 and three different oil fluids at different pressures. Also minimum miscible pressure (MMP) is measured by the vanishing interfacial tension (VIT) technique to determine the temperature effect on the CO2 miscible gas injection. The results on different pure and mixtures of hydrocarbon fluids show... 

    A New Data Gathering Technique in Delay Tolarant Mobile Ad Hoc Networks

    , M.Sc. Thesis Sharif University of Technology Zolghadr, Mahdi (Author) ; Sarbazi Azad, Hamid (Supervisor)
    Abstract
    Delay Tolerant Networks are a variation of Mobile Ad Hoc Networks, in which low density of nodes in the network area results in global disconnectivity among the nodes. In these networks, communication of data throughout the networks takes place by the means of mobility; nodes store data packets and carry them around the network and forward them to other nodes they encounter along the way. In these situations, a proper selection of data to be exchanged between nodes has a great impact on the quality of data distribution in the whole networks. There is a common assumption among most of the techniques presented in category of Delay Tolerant Networks. They assume the probability of more than two... 

    Modeling and Forecasting the U.S. Presidential Elections Using Learning Algorithms

    , M.Sc. Thesis Sharif University of Technology Zolghadr, Mohammad (Author) ; Akhavan Niaki, Taghi (Supervisor)
    Abstract
    In this project, we intend to use intelligent and learning algorithms to forecast the U.S. presidential elections. First, we considered some economic and political variables in our model. Then by using stepwise regression, we found the most significant variables. After that, we used three data mining techniques on these data. In the next step, we used support vector regression and neural networks to predict the elections. Then we compared these two algorithms with each other. Eventually, we realized how strong and accurate these methods are to predict the U.S. presidential elections. We have, also, proved that using data mining techniques is beneficial to make models more accurate  

    Investigating the effects of temperature, pressure, and paraffin groups on the N2 miscibility in hydrocarbon liquids using the interfacial tension measurement method

    , Article Industrial and Engineering Chemistry Research ; Volume 52, Issue 29 , 2013 , Pages 9851-9857 ; 08885885 (ISSN) Zolghadr, A ; Riazi, M ; Escrochi, M ; Ayatollahi, S ; Sharif University of Technology
    2013
    Abstract
    In this study, interfacial tension measurement (IFT) is utilized to assess the impact of temperature, pressure, and paraffin type on a nitrogen injection process as an efficient enhanced oil recovery method. The pure and equilibrium densities of oil in contact with nitrogen are examined to find IFT behavior and gas solubility in oil. The minimum miscible pressure (MMP) of different systems has been measured using the vanishing interfacial tension technique. The experimental results show that IFT decreases linearly with pressure, with two different slopes. The results indicate that IFT values decrease linearly with temperature at different pressure conditions. The obtained IFT values for... 

    Pressure and temperature functionality of paraffin-carbon dioxide interfacial tension using genetic programming and dimension analysis (GPDA) method

    , Article Journal of Natural Gas Science and Engineering ; Volume 20 , September , 2014 , Pages 407-413 ; ISSN: 18755100 Khadem, S. A ; Jahromi, I. R ; Zolghadr, A ; Ayatollahi, S ; Sharif University of Technology
    2014
    Abstract
    A precise semi-empirical correlation for the calculation of interfacial tension (IFT) between the carbon dioxide and paraffin group to be used in an enhanced oil recovery process and the chemical industry is introduced. Genetic programming and dimension analysis (GPDA) are combined to create a correlation for the calculation of the equilibrium interfacial tension of the carbon dioxide and paraffin group, based on the explicit functionality of the pressure and temperature. The parameters of the correlation consist of critical temperature, critical pressure, density of paraffin at normal temperature, and diffusion coefficients. The pool of experimental data for developing the correlation... 

    Modeling and forecasting US presidential election using learning algorithms

    , Article Journal of Industrial Engineering International ; Volume 14, Issue 3 , 2018 , Pages 491-500 ; 17355702 (ISSN) Zolghadr, M ; Akhavan Niaki, S. A ; Akhavan Niaki, S. T ; Sharif University of Technology
    SpringerOpen  2018
    Abstract
    The primary objective of this research is to obtain an accurate forecasting model for the US presidential election. To identify a reliable model, artificial neural networks (ANN) and support vector regression (SVR) models are compared based on some specified performance measures. Moreover, six independent variables such as GDP, unemployment rate, the president’s approval rate, and others are considered in a stepwise regression to identify significant variables. The president’s approval rate is identified as the most significant variable, based on which eight other variables are identified and considered in the model development. Preprocessing methods are applied to prepare the data for the... 

    Modeling and forecasting US presidential election using learning algorithms

    , Article Journal of Industrial Engineering International ; 2017 , Pages 1-10 ; 17355702 (ISSN) Zolghadr, M ; Akhavan Niaki, S. A ; Niaki, S. T. A ; Sharif University of Technology
    2017
    Abstract
    The primary objective of this research is to obtain an accurate forecasting model for the US presidential election. To identify a reliable model, artificial neural networks (ANN) and support vector regression (SVR) models are compared based on some specified performance measures. Moreover, six independent variables such as GDP, unemployment rate, the president’s approval rate, and others are considered in a stepwise regression to identify significant variables. The president’s approval rate is identified as the most significant variable, based on which eight other variables are identified and considered in the model development. Preprocessing methods are applied to prepare the data for the... 

    Evaluation of interfacial mass transfer coefficient as a function of temperature and pressure in carbon dioxide/normal alkane systems

    , Article Heat and Mass Transfer/Waerme- und Stoffuebertragung ; Volume 51, Issue 4 , April , 2015 , Pages 477-485 ; 09477411 (ISSN) Nikkhou, F ; Keshavarz, P ; Ayatollahi, S ; Raoofi Jahromi, I ; Zolghadr, A ; Sharif University of Technology
    Springer Verlag  2015
    Abstract
    CO2 gas injection is known as one of the most popular enhanced oil recovery techniques for light and medium oil reservoirs, therefore providing an acceptable mass transfer mechanism for CO2–oil systems seems necessary. In this study, interfacial mass transfer coefficient has been evaluated for CO2–normal heptane and CO2–normal hexadecane systems using equilibrium and dynamic interfacial tension data, which have been measured using the pendant drop method. Interface mass transfer coefficient has been calculated as a function of temperature and pressure in the range of 313–393 K and 1.7–8.6 MPa, respectively. The results showed that the interfacial resistance is a parameter that can control... 

    Experimental determination of equilibrium interfacial tension for nitrogen-crude oil during the gas injection process: The role of temperature, pressure, and composition

    , Article Journal of Chemical and Engineering Data ; Vol. 59, issue. 11 , September , 2014 , p. 3461-3469 ; ISSN: 00219568 Hemmati-Sarapardeh, A ; Ayatollahi, S ; Zolghadr, A ; Ghazanfari, M. H ; Masihi, M ; Sharif University of Technology
    2014
    Abstract
    Nitrogen has emerged as a competitive gas injection alternative for gas-based enhanced oil recovery processes in the past two decades. The injection of nitrogen into the reservoirs has improved the oil recovery efficiency in various oil reservoirs from heavy to volatile oils. As it is known, interfacial tension (IFT) plays a key role in any enhanced oil recovery process, particularly gas injection processes; therefore, its accurate determination is crucial for the design of any gas injection process especially at reservoir condition. In this study, an axisymmetric drop shape analysis (ADSA) was utilized to measure the equilibrium IFTs between crude oil and N2 at different temperature levels... 

    Asphaltene deposition during CO 2 injection and pressure depletion: A visual study

    , Article Energy and Fuels ; Volume 26, Issue 2 , December , 2012 , Pages 1412-1419 ; 08870624 (ISSN) Zanganeh, P ; Ayatollahi, S ; Alamdari, A ; Zolghadr, A ; Dashti, H ; Kord, S ; Sharif University of Technology
    2012
    Abstract
    Carbon dioxide miscible flooding has become a popular method for Enhanced Oil Recovery (EOR) because it not only efficiently enhances oil recovery but also considerably reduces green house gas emissions. However, it can significantly cause asphaltene deposition, which leads to serious production problems such as wettability alteration, plugging of the reservoir formation, blocking the transportation pipelines, etc. It is crucial to investigate the effects of different factors on asphaltene deposition. A novel experimental setup was prepared to employ a high-pressure visual cell for investigation of asphaltene deposition on a model rock under typical reservoir conditions. The evolution of... 

    Porous Carrageenan-g-polyacrylamide/bentonite superabsorbent composites: swelling and dye adsorption behavior

    , Article Journal of Polymer Research ; Volume 23, Issue 3 , 2016 , Pages 1-10 ; 10229760 (ISSN) Pourjavadi, A ; Bassampour, Z ; Ghasemzadeh, H ; Nazari, M ; Zolghadr, L ; Hosseini, S. H ; Sharif University of Technology
    Springer Netherlands  2016
    Abstract
    A novel superabsorbent composite based on kappa-Carrageenan (κC) was prepared by graft copolymerization of acrylamide (AAm) onto κC in the presence of bentonite powder using methylenebisacrylamide (MBA) as a crosslinking agent, ammonium persulfate (APS) as an initiator, and sodium carbonate as a pore-forming agent. The swelling behavior in distilled water and in solutions with different pH values was investigated. The results indicated that with increasing carrageenan/bentonite weight ratio, the swelling capacity is increased but the gel content is decreased. The swelling rate of the hydrogels was improved by introducing sodium carbonate as pore-forming agent. The prepared superadsorbent... 

    On the protonated forms of alkyl-bonded polycyclic aromatic heterocycles: Structure prediction and characterization using density functional theory

    , Article Journal of Physics and Chemistry of Solids ; Volume 175 , 2023 ; 00223697 (ISSN) Esmaeilbeig, M. A ; Khorram, M ; Koleini, M. M ; Ayatollahi, S ; Zolghadr, A. R ; Sharif University of Technology
    Elsevier Ltd  2023
    Abstract
    When alkyl chains with electron-donating properties are bonded to heterocyclic rings in polycyclic aromatic hydrocarbons, a certain class of molecules is formed. These molecules become protonated in some industries as a result of their intimate contact with the acidic aqueous phase. However, little attention has been paid to the protonation of these molecules. The purpose of this article was to use computational methods to predict and characterize the final protonated states of these molecules. This study considered three distinct types of these molecules. DFT method was used to determine the most likely proton-accepting sites for the molecules, followed by optimization of their protonated... 

    MBBR and MBR Reactor Configuration for Better Performance

    , M.Sc. Thesis Sharif University of Technology (Author) ; Borgheei, Mahdi (Supervisor)
    Abstract
    Membrane bioreactors (MBRs) which are commonly understood as the combination of membrane filtration and biological treatment using activated sludge have several advantages, but membrane fouling reduces the membrane efficiency, permeability and lifetime. An alternative is replacing a moving bed biofilm reactor (MBBR) with the activated sludge system which may reduce the effect of membrane fouling. The sludge produced in MBBRs has poor settling characteristics, therefore, their efficiency is limited by the sedimentation tank performance and they require a larger settling surface. The combination of moving bed biofilm reactors and membrane bioreactors can compensate for the drawbacks of both of... 

    Forecasting the effects of a Canada-US currency union on output and prices: A counterfactual analysis

    , Article Journal of Forecasting ; Volume 32, Issue 7 , 2013 , Pages 639-653 ; 02776693 (ISSN) Mahdi Barakchian, S ; Sharif University of Technology
    2013
    Abstract
    This paper is a counterfactual analysis investigating the consequences of the formation of a currency union for Canada and the USA: whether outputs increase and prices decrease if these countries form a currency union. We use a two-country cointegrated model to conduct the counterfactual analysis, where the conditional forecasts are generated based on the Gaussian assumption. To deal with structural breaks and model uncertainty, conditional forecasts are generated from different models/estimation windows and the model-averaging technique is used to combine the forecasts. We also examine the robustness of our results to parameter uncertainty using the wild bootstrap method. The results show... 

    Evaluation of Non-linear Combination Method (Neural Network) For Value-at-Risk Forecasting in Market

    , M.Sc. Thesis Sharif University of Technology Rashnavadi, Leila (Author) ; Barakchian, Mahdi (Supervisor)
    Abstract
    Value at risk of an asset, is the asset’s expected maximum loss for a certain period of time and at a specified confidence level. Value-at-Risk can be calculated in the bank with its inter-nal method or standardized method. when a method have more violation number then bank need to keep more daily capital requirements. under the Basel 2 agreement if the violation of method more than 10 times in year, the Bank uses the standardized method.
    There are trade off Between daily capital charge and violations. Therefore, existing methods for calculating the value at risk, usually lead to much daily capital charge or many violations. Studies show with combination of different methods to calculate... 

    Using Complex Network Metrics for Evaluating the Influence of Conference and Journal Papers in Computer Science

    , M.Sc. Thesis Sharif University of Technology Habibi, Fatemeh (Author) ; Jalili, Mahdi (Supervisor)
    Abstract
    Journals and conferences in computer science are the major venue for publishing new achievement in the field. It is an expert opinion that a number of top conferences in computer science are even more important than journals. In this work we aim at studying this in terms of citation analysis. To this end, we took 100 top journals and 63 top conferences and extracted their citation graph through Scopus dataset. We then constructed the citation graph in which the nodes were the journals and conferences and the links corresponded to the citations of the papers. We used various measures to rank the nodes in the graph. The ranking methods included Prestige, PageRank, Eigenfactor, HITS and SALSA.... 

    Design and Implementation of a VLSI Architecture for Time and Frequency Synchronization in the LTE

    , M.Sc. Thesis Sharif University of Technology Golnari, Amene (Author) ; Shabany, Mahdi (Supervisor)
    Abstract
    The long term evolution (LTE) standard is introduced and developed by the 3rd generation partnership project (3GPP) based on orthogonal frequency division multiplexing (OFDM). OFDM systems, in spite of having many advantages such high performance in bandwidth usage, are very sensitive to inter carrier interference (ICI) as a drawback. In order to prevent ICI, the frequency offset, mainly caused by the miss-match between oscillators' frequency and also between the sampling frequency of the transmitter and the receiver, should be estimated and compensated. Frequency synchronization is a part of the tasks of a synchronizer. In this thesis, main tasks of a synchronizer are illustrated and... 

    A New Approach in Value-at-Risk (VaR) Estimation by Forecast Combination Methods

    , M.Sc. Thesis Sharif University of Technology Seraj, Mostafa (Author) ; Barakchian, Mahdi (Supervisor)
    Abstract
    Value-at-Risk (VaR) is the most commontool for risk management. This tool is used to measure market risk and also used as a basis in determining financial standards for international financial institutions. VaR is the maximum loss of the asset portfolio at the specified confidence level and certain time horizon. Many parametric, nonparametric and semi parametric methods have been invented for VaR estimation. Each one of these methods has its advantages and disadvantages and different methods may perform better in differnet situations.When estimating VaR, we can choose one of these methods or we can combine the VaRs estimated by different methods. There are few researches conducted on VaR... 

    EEG Brain Functional Network Analysis in Cortex Level

    , M.Sc. Thesis Sharif University of Technology Pedrood, Bahman (Author) ; Jalili, Mahdi (Supervisor)
    Abstract
    Complex networks science have received tremendous attention in recent years and the brain is one of the systems to which graph theoretical tools have been applied. Alzheimer’s disease (AD) is a neurodegenerative disease affecting many of elderly population. AD changes the anatomy of the brain, which subsequently results in changes in its functions. These changes have been frequently reported in signals recorded from the brain (such as MEG, fMRI and EEG). Among these neuroimaging techniques EEG is one of the most aproprate methods for extracting functional connectivites according to high temporal resolution. In this thesis, we aimed at analyzing the properties of EEG-based functional networks... 

    Learning Improvement in Phase Oscillator Models

    , M.Sc. Thesis Sharif University of Technology Aghighi, Meysam (Author) ; Jalili, Mahdi (Supervisor)
    Abstract
    In the recent years, the problem of modeling a cognitive task using phase oscillators has been receiving a significant attention. In this view, single neurons are no longer elementary computational units. Rather, coherent oscillating groups of neurons are seen as nodes of networks performing cognitive tasks. From this assumption, we develop a model of stimulus-response learning and recognition. The most significant part of our work is defining learning methods for natural frequencies and coupling weights in a coupled phase oscillator network under Kuramoto conditions. In this thesis, we improved the previous models by not only emphasizing on the frequency of the oscillators but also taking...