Sharif Digital Repository

Thrust vector control as a method toward increasing of the aircrafts’ maneuverability and expanding the flight envelope into poor aerodynamic conditions, is considered a major field of academic and industrial appeal. Older methods based upon an approach of utilizing a mechanical instrument, impose quite a large amount of cost onto the design, prototyping and operation of the aircraft, even though they lead to improve in maneuverability. Having taken these setbacks into account, to simplify the manufacturing process and to reduce the thrust losses due to mechanical control of the thrust vector, the direction of research was set toward realizing and employing the flow control procedures. In... 

This thesis analyzes the behavior of inflation in the Iranian economy by introducing a micro-founded model of monetary policy. The model predicts a direct relationship between inflation and oil export revenues in the oil dependent economy of Iran. This theory driven claim is verified empirically, and test results tend to confirm a meaningful relationship between inflation and Oil export data in Iran. Based on results attained from the micro-founded model, an augmented SVAR model is proposed for estimating underlying inflation in the Iranian economy. The proposed model is found to render better results than the conventional models used for estimating underlying inflation. Moreover it is... 

Existing Intrusion Detection Systems (IDSs) are not designed to deal with all categories of processing environments. This thesis focuses on IDSs for the Grid computing environment, and concentrates on feature selection and performance. An existing framework, Globus, is used as the basis for the consideration and development of the research issue in Grid computing. The system is based on two engine designs: (a) Signature and (b) Support Vector Machine; SVM has been selected for pattern discovery in traffic analysis. We found that the performance of the system greatly depends on the efficiency of the underlying framework and the number of Intrusion Detection System instances. We demonstrate... 

Human face detection is an important research area with several applications such as human computer interface (HCI), face recognition, surveillance systems, security systems, and content-based image retrieval (CBIR). Face detection problem can be stated as “determining whether there are human faces in the image” and if there are “returning the location of each human face in the image” regardless of its position, size, scale, orientation, and lighting condition. In this thesis, we have proposed a new face detection method which combines the AdaBoost algorithm with skin color information and support vector machine (SVM). First, a cascade classifier based on AdaBoost is used to detect faces in... 

One of the obvious features of financial markets is the spread of crisis across the markets, which is called contagion and realized in forms of return and volatility spillover. Using the daily data on the stock price from December 2006 through June 2010, this study aims to examine the presence and significance of these spillovers between Tehran and Dubai Stock Exchange, by a FIVECM technique. The FIVECM provides long-run equilibrium relationships between the returns in the markets and short-run dynamics of involved endogenous variables. Furthermore, it takes into account presence of fractionality in the time series’ integration. Our analytical framework, models the spillover effects in... 

Recently many works has been focused on Automatic Security Systems. Car type and color recognition systems are needed in vehicle based access control systems in buildings, outdoor sites and even housing estates. Another usage of car type and color recognition is when a certain model of car is being investigated in highways and streets. In this thesis two independent systems are designed; one for car type recognition and another for car color recognition. They both require to know the license plate location, so we proposed a license plate detection system. In the license plate detection system, first the plate candidates are extracted from image by gradient and morphological operations, then... 

Error concealment is one of the effective ways to alleviate the effect of packet loss in video communication over error-prone environments. In order to estimate lost macro-blocks, we have employed Bayesian estimation as an efficient and robust framework. Gaussian process regression has been used as the modeling approach through this framework. Considering luminance component as Gaussian process,a minimum mean squared error estimation of the lost macro-block is obtained. This estimator, as a function of the existing data, is only determined by the covariance matrix defined over them. Therefore,the main step in Gaussian process regression, is construction of the convenient covariance matrix... 

Nowadays, simulation science supports a wide range of researches. This science is in a constant improvement process. Simulation is a process to fulfill the real world problems by means of experiments which resemble to the real world situation so much. One of the preconditions in statistical simulation is to produce the random number and variables based on the presumed attributes and parameters. In this research, at first, a simple and fast responding algorithm to generate correlated uniformly distributed tri-dimensional vectors is proposed. In this algorithm by producing three groups of random numbers, we can produce tri-dimensional vectors of correlated uniformly distributed based on... 

In this study, the effect of oil price shocks on stock markets is examined for Iran and Norway as two oil-exporting countries. To do this, an unrestricted Vector Auto-regression model is applied based on monthly data from April 2001 to March 2011. The variables used in the model are Brent oil price shocks, interest rate, consumer price index and stock returns. To find the relationship between oil price shocks and stock markets and determine the effects of oil shocks on stock markets, impulse-response analysis and variance decomposition are employed. To compare the effects of positive and negative oil price shocks, a Chi-square test is used. The proposed model is applied on different types of... 

Islanding detection methods are divided into three main groups as remote, active and passive. Although passive schemes have larger Non Detection Zones (NDZ) relative to other schemes, they are more used in utilities due to their low costs and less PQ problems than in other schemes. Passive Schemes are based on the measurements of passive system parameters. These parameters are measured at the point of common coupling (PCC). A new approach in passive techniques is the use of data-mining to classify the system parameters which affect the islanding detection. Therefore, by finding an efficient and robust data-mining algorithm, the inherent problem of passive schemes, which is their relatively... 

Spoken language understanding unit is one of the most important parts of a spoken dialogue system. The input of this system is the output of speech recognition unit. The main function of this unit is to extract the semantic information from the input utterances. There are two main types of approaches to do this task: rule-based approaches, and data-driven approaches. Today data-driven approaches are of more interest because they are more flexible and robust compared to the rule-based approaches. The main drawback of these methods is that they need a large amount of fully annotated or in some cases Treebank data. Preparing such data is time consuming and expensive. The goal of this thesis is... 

The purpose of this project is estimating the two-or three-dimensional human condition using existing data(images or video). Human pose estimation can be used in applications، including the detection of human behavior، animation،human computer interaction، physical therapy and، etc . We use sparse representation method to estimating human pose In this project .Sparse representation methods in recent years has been used in many fields and probably in pose estimation can achieve good results with this method  

Temporal relation classification is one of the contemporary demanding tasks in natural language processing. This task can be used in various applications such as question answering, summarization, and language specific information retrieval. Temporal relation classification methods can be categorized into three main groups of supervised, semi-supervised, and unsupervised (based on the type of the training data that they need). In this thesis, we have two main goals: first, improving accuracy of temporal relation learning, and second, decreasing supervision of algorithm as much as possible. For achieving these goals, three main steps are proposed. In the first step, we propose an improved... 

The subgradient method is one of the most favoriate methods to solve discrete optimization problems. The Easy Implementation and flexibility enbles us to solve a vast types of complicated combinatorial optimization problems. However, the algorithm can be improved by adjusting its parameters and steps.In present research, we present a heuristic structure to modify and improve the algorithm. Then, the proposed algorithm has tested on special classes of discrete optimization problems such as Generealized Assignment and Uncapacitated Warehouse location problems. The results show that the proposed algorithm can improve the efficiency of the classic form of subgradient method.The three main... 

In this study it is attempted to investigate the impact of macroeconomic variables on the determination stock price in Iran.In this study it is used quarterly time series data of stock price and also macroeconomic variables including Growth of Consumer Price Index(Inflation), Iran Crude Oil Price, Exchange Rate, Gold Price, Liquidity, Money Supply and Gross Domestic Product for a period of 10 years (1381:1-1390:4). Data is obtained from monthly and quarterly reports, available on the website of the Central Bank of Iran and Tehran Stock Exchange Organization. In the analysis of the collected data, It is applied unit root tests, test for co integration, and utilize a Vector Auto Regressive... 

The news headlines should represent the main and the most important topics of their stories. The task of selecting an appropriate headline for news stories is mainly done by journalists. The goal of this project has been the design and implementation of a system to automate this task, that is generating headlines for news. This task has been done for Persian news stories. There are various methods for automatic headline generation in English and some other languages, but no work has been done for Persian, yet. Thus, we have adopted some of the ideas from those methods, and do the remaining by our initiation. Our proposed method consists of three main parts: keyword extraction, most important... 

Text classification accompanied by high precision has become a challenging issue in computational linguistics and natural language processing science. Proper data set accessibility, utilizing the best method and prominent linguistics features has been always regarded as the basic concern of this process. The following study relying on Bijan Khan Corpus is tried to represent keywords vectors of different documents using tf_idf. These vectors are regarded as an input for latent topic models algorithms including probabilistic latent semantic analysis. The output of this algorithm will be the documents feature vectors which will be later used in order to train different classifiers like K... 

Transformer are one of the most important equipment in transmission and distribution network. Transformer unplanned outage have severe impacts on the continuity of power system operation and is also an irreparable economic harm to power network operators. To improve the reliability of transformers and to achieve an optimum operation cost, online condition monitoring is inevitbale. Information about the quality of the transformer insulation system is known as the best parameter to be monitored in transformer. Since partiale discharge (PD) signals are initiated long before the beginning of a severe damage, monitoring and its evaluation can be employed to warn the operator. Data mining on the... 

One of the important tools that we frequently use in life is the map. In every day movements we can use the maps in order to navigate and find our way. We also utilize the maps to find out more about our surrounding world. GIS is the key technology which can help us reach these goals. In GIS generally there are 2 methods for representing geographic data, these methods are Raster and Vector data representation. In this thesis our purpose is to find another way for representing GIS data by using vector format. In this new representation we can access to information which are not accessible in regular maps. So we generate a new flexible platform for GIS data. Thus in order to represent new...