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neshat--najmeh
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Formal Analysis of Security Protocols using Theorem Proving
, M.Sc. Thesis Sharif University of Technology ; Jalili, Rasool (Supervisor)
Abstract
Security protocols are mostly verified using tools based on model checking approach. These tools are automatic but they can be used for verifying protocols with low complexity and limited number of participants. The other approach that can be used in these cases is theorem proving. Inductive method is a theorem proving approach which is based on induction in mathematics. Inductive method has been applied for verifying several classical and real-world protocols.
The basic concepts in this method are event and trace. Using the concept of event, the network traffic can be modeled through various events occurring in the network. Atrace is a list of events and model a history of the network....
The basic concepts in this method are event and trace. Using the concept of event, the network traffic can be modeled through various events occurring in the network. Atrace is a list of events and model a history of the network....
Predictive Process Control Using a Hierachical Method Based on Regression Analysis and Artificial Neural Networks (case study: Spray Drying in Tile Industry)
, M.Sc. Thesis Sharif University of Technology ; Mahlooji, Hashem (Supervisor)
Abstract
This is the first attempt at process modeling in terms of predictive control using a hierachical method based on regression analysis and artificial neural networks(ANNs).This hierachical use leads to the reliability improvement of neural model of process in prediction (extrapolation and interpolation) of process output. such an outlook makes it possible to predict the proper input settings which achieved a desired process output by designing various senarios for process set up. This approach was applied in Tile industry for spray dring process and in order to indicate the achieved improvement,three models:(i) regression model of process using multiple linear regression,(ii)Neural model of...
Algebraic bound for the phase–frequency response of the commande robuste d'ordre non-entier approximation of fractional differentiators and its applications in control systems analysis
, Article JVC/Journal of Vibration and Control ; 2021 ; 10775463 (ISSN) ; Tavazoei, M. S ; Sharif University of Technology
SAGE Publications Inc
2021
Abstract
This article deals with analyzing the phase–frequency response of commande robuste d'ordre non-entier approximations of fractional-order differentiators. More precisely, an algebraic tight upper bound is derived for the phase of the approximations obtained from the commande robuste d'ordre non-entier method. Then, some applications for this achievement are discussed in the viewpoint of control systems analysis. These applications include usefulness of the obtained upper bound in stability preservation analysis during the commande robuste d'ordre non-entier–based approximation process and applicability of such a bound in finding necessary or sufficient conditions for test of positive...
Algebraic bound for the phase–frequency response of the commande robuste d'ordre non-entier approximation of fractional differentiators and its applications in control systems analysis
, Article JVC/Journal of Vibration and Control ; Volume 28, Issue 9-10 , 2022 , Pages 1074-1085 ; 10775463 (ISSN) ; Tavazoei, M. S ; Sharif University of Technology
SAGE Publications Inc
2022
Abstract
This article deals with analyzing the phase–frequency response of commande robuste d'ordre non-entier approximations of fractional-order differentiators. More precisely, an algebraic tight upper bound is derived for the phase of the approximations obtained from the commande robuste d'ordre non-entier method. Then, some applications for this achievement are discussed in the viewpoint of control systems analysis. These applications include usefulness of the obtained upper bound in stability preservation analysis during the commande robuste d'ordre non-entier–based approximation process and applicability of such a bound in finding necessary or sufficient conditions for test of positive...
An enhanced neural network model for predictive control of granule quality characteristics
, Article Scientia Iranica ; Volume 18, Issue 3 E , 2011 , Pages 722-730 ; 10263098 (ISSN) ; Mahloojifl, H ; Kazemi, A ; Sharif University of Technology
2011
Abstract
An integrated approach is presented for predicting granule particle size using Partial Correlation (PC) analysis and Artificial Neural Networks (ANNs). In this approach, the proposed model is an abstract form from the ANN model, which intends to reduce model complexity via reducing the dimension of the input set and consequently improving the generalization capability of the model. This study involves comparing the capability of the proposed model in predicting granule particle size with those obtained from ANN and Multi Linear Regression models, with respect to some indicators. The numerical results confirm the superiority of the proposed model over the others in the prediction of granule...
Effect of reformer gas blending on homogeneous charge compression ignition combustion of primary reference fuels using multi zone model and semi detailed chemical-kinetic mechanism
, Article Applied Energy ; Volume 179 , 2016 , Pages 463-478 ; 03062619 (ISSN) ; KhoshbakhtiSaraya Saray, R ; Hosseini, V ; Sharif University of Technology
Elsevier Ltd
2016
Abstract
This study mainly aims to investigate the effect of reformer gas (RG) addition on the performance of homogeneous charge compression ignition (HCCI) engines using a multi zone model. The developed model is validated using a wide range of experimental data of a cooperative fuel research engine. Blended fuels of isooctane and n-heptane, known as primary reference fuels, with different octane numbers are used as the main engine fuel. A semi detailed chemical-kinetic mechanism containing 101 species and 594 reactions is used to simulate the combustion of blended fuels. The study is performed with different percentages of RG (0–30%). The results show that RG reduces the rate of some H abstraction...
Investigation of the effect of reformer gas on PRFs HCCI combustion based on exergy analysis
, Article International Journal of Hydrogen Energy ; Volume 41, Issue 7 , 2016 , Pages 4278-4295 ; 03603199 (ISSN) ; Saray, R. K ; Hosseini, V ; Sharif University of Technology
Elsevier Ltd
2016
Abstract
Lack of a direct method to control combustion timing is one of the main disadvantages of homogeneous charge compression ignition (HCCI) engines. Fuel blending, in which two fuels with different auto-ignition characteristics are blended, can be used to control combustion timing. Utilizing different additives is another method for HCCI combustion control. The aim of this research is investigation on the effect of reformer gas addition on the availability terms in HCCI engines fueled with primary reference fuels (PRFs). A multi zone model (MZM) coupled with a semi detailed chemical kinetics mechanism is used for calculation of different terms of exergy analysis. Heat and mass transfer between...
Conditions on Fractional-order LTI Systems to be Negative Imaginary
, M.Sc. Thesis Sharif University of Technology ; Tavazoei, Mohammad Saleh (Supervisor)
Abstract
In this thesis, we derive the analytic condition that linear time invariant fractional order system being positive real. Also, by inspiration of positive real condition, we derive the analytic condition for linear time invariant fractional order system that their imaginary part of frequency response being negative. Intended conditions for single input single output systems are derived in the form of necessary conditions in one way and derived in the form of sufficient conditions in another way. However, intended conditions in multiple input multiple output are just derived in the form of sufficient conditions. Furthermore, an upper band for phase of oustaloup approximation frequency response...
A Survey on Black Hole Physics
, M.Sc. Thesis Sharif University of Technology ; Bahmanabadi, Mahmoud (Supervisor) ; Sheikh-Jabbari, Mohammad Mahdi (Co-Supervisor)
Abstract
Black holes are a general set of solutions of Einstein’s general relativity. Their most important feature is the horizon, which is basically a region that separates the space-time into two causally disconnected regions. Studying the general features of black holes, classifying this family of solutions and studying the dynamics of particles and fields in the background of a given black hole are famous subjects in the field of classical black hole physics which are going to be covered in this thesis. By putting different conditions on the equations, we will get different solutions like Schwarzschild, Reissner-Nordstrom, Kerr, Kerr-Newman and etc, each of them having specific features. Then we...
A comparative study on car ownership modeling by applying fuzzy linear regression and artificial neural network - case study of Iran
, Article Summer Computer Simulation Conference, SCSC 2010 - Proceedings of the 2010 Summer Simulation Multiconference, SummerSim 2010, 12 July 2010 through 14 July 2010 ; Issue 1 BOOK , 2010 , Pages 25-31 ; 9781617387029 (ISBN) ; Rafiee, K ; Zohrevand, A.M ; Neshat, N ; Society for Modeling and Simulation International (SCS) ; Sharif University of Technology
2010
Abstract
This paper models car ownership in Iran based on the data in a period of years 1980 to 2007 by artificial neural network (ANN) and Fuzzy Linear Regression (FLR). The car ownership is mainly affected by purchasing power of the customers, social and demographic factors; the car ownership model has a multi variable form. To explain the effect of these factors, ANN and FLR models are applied. The major reason for applying fuzzy concept and ANN is to overcome the inter-correlation problem associated with the independent variables. In this study, average family size; total population; urban population; urbanization rate; gross national product per capita; gasoline price; total length of road are...
A hierarchical artificial neural network for transport energy demand forecast: Iran case study
, Article Neural Network World ; Volume 20, Issue 6 , 2010 , Pages 761-772 ; 12100552 (ISSN) ; Shakouri, H .G ; Menhaj, M. B ; Mehregan, M. R ; Neshat, N ; Asgharizadeh, E ; Taghizadeh, M. R ; Sharif University of Technology
2010
Abstract
This paper presents a neuro-based approach for annual transport energy demand forecasting by several socio-economic indicators. In order to analyze the influence of economic and social indicators on the transport energy demand, gross domestic product (GDP), population and total number of vehicles are selected. This approach is structured as a hierarchical artificial neural networks (ANNs) model based on the supervised multi-layer perceptron (MLP), trained with the back-propagation (BP) algorithm. This hierarchical ANNs model is designed properly. The input variables are transport energy demand in the last year, GDP, population and total number of vehicles. The output variable is the energy...