Sharif Digital Repository

Control of line of sight (LOS) orientation is a fundamental prerequisite for virtually all dynamic applications in which an optical sensor is used to obtain images. In this research, a 3 DOF parallel mechanism is utilized to build a stable platform for high precision satellite photography. The platform may be designed based on the Stewart platform concept. The stability is obtained by controlling the roll, pitch and yaw of the mechanism. To apply linear control techniques and to use roll-pitch and yaw rates and also their absolute values, an active stable platform is designed. Line Of Sight (LOS) is a position vector from origin of a topocentric-horizontal system to the satellite of... 

Cerebrovascular Attack has been ranked the second or third of top 10 death causes in Taiwan. It has caused about 13,000 deaths every year since 1986. Once Cerebrovascular Attack (CVA) occurs, it not only leads to the huge cost of medical care, but even death. All developed countries in the world put CVA prevention and treatment in high priority. However, it is necessary to build a detective model to enhance the accurate diagnosis of CVA. From this detective model, CVA classification rules were extracted and used to improve the diagnosis and detection of CVA. This study acquired 2449 valid samples from this CVA prevention and treatment program, and adopted three classification algorithms,... 

Weed management is the important issue in agriculture. Using herbicides is one of the strategies to control weed. But using huge amount of herbicides are destructive for environment. Smart spraying system is an impressive solution for this problem. This system detects weeds and sprays just them instead of spraying overall field. In this thesis a new method for plant detection is presented by using Lab color space. We determine the type of plants (broadleaf/grass) to spray specific herbicides onto specific type of plant. One feature of grass plants (the parallel edges of leaf) is used to detect grass plants. A convolutional neural network with four layers and fuzzy logic are used to separate... 

Learning disability (LD) is a neurological condition that interferes with an individual’s ability to store, process, or produce information. There are different types of learning disabilities affecting reading, writing, speaking, spelling, etc. Based on a study conducted by National Center for Learning Disabilities, 2.4 million American public school students are diagnosed with learning disability. They attend school in order to learn and be successful while they do not know their learning process is different from their peers. LD diagnosis in children is especially important as such cases must be identified early enough in order to provide them with proper education.This project targets LD... 

Nuclear magnetic resonance is a spectroscopic method which is used to investigate characteristics of molecules with hydrogen and carbon chains. In this thesis we used, NMR spectrum extracted from 19 types of amino acids for investigating on feature generation for protein sequences. We processed NMR spectra based on Hydrogen and Carbon atoms in structure of the amino acids and after preprocessing we extracted features for each amino acid from the spectra. After that, we tried to cluster the amino acids with Fuzzy Clustering Method (FCM) then we generated feature vectors by extracting special descriptor for amino acids in sequence of proteins. In addition to NMR, we used the features of... 

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... 

Brain-inspired methods are now widely used to process the data generated by the brain with the aim of improving our understanding of how the brain functions and produces the remarkable intelligence exhibited by humans, which is the source of all realizations, perception and actions. Therefore brain-computer interface (BCI) is one of the most challenging scientific problems which focuses scientists attention, in most cases these systems are based on EEG signals recorded from the surface of the scalp because this method of the brain activity monitoring is noninvasive, easy to use and quit inexpensive. Brain computer interface (BCI) systems analyse the EEG signals and translate person’s... 

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... 

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... 

In this project we have worked on the new architecture of the auction based resource scheduling, from the bidders point of view. The performance of different bidding strategies for the resources which participate in reverse auction system has been investigated; our main parameter for evaluating different bidding strategies is the amount of the profit gained by resources which follow such strategies. The main historical bidding strategies are created based on two famous predictors ES and AUTO-REGRESSION. In addition a game theory approach has been proposed. We have shown that our bidding algorithm (based on the sequential game model) reaches to an equilibrium point if all the bidders follow... 

The growth of intelligent attacks has prompted the designers to envision the intrusion detection as a built-in process in operating systems. This thesis investigates a novel anomaly-based intrusion detection mechanism which utilizes the manner of interactions between users and kernel processes to bring functionality to this notion. In fact, this mechanism is inspired by homeostatic behavior of an organism. Homeostatic is the property of an open system or a closed system, particularly a living organism, which regulates its internal environment to maintain a stable, constant condition. Such a developed mechanism can provide the computer system with a high level of protection from artificial... 

According to increasing energy demand in Iran and the world, the role of natural gas as a relatively clean and cost-effective source has received more attention. Given the high share of the residential sector in the country's natural gas consumption, providing a model for forecasting the demand of this sector is of great importance for policy makers and decision makers in this field. In the present study, we employ three popular methods of machine learning, support vector regression, artificial neural network and decision tree to predict the consumption of natural gas in the residential sector in Tehran according to meteorological parameters (including temperature, precipitation and wind... 

Energy storage systems are expected to play an important role in future renewable-based power systems. Recently, lithium-ion batteries have been attracting considerable attention as alternative energy storage systems due to their advantages. In this study, viability of battery storage systems as large-scale energy storage systems is studied in the context of a residential energy hub. A stochastic optimization problem is proposed for energy management of the energy hub where wind generation and demand are considered uncertain. In order to account for the degradation costs of the battery storage system, a data-driven State-of-health prediction model is developed based on the relevance vector... 

Economics is the science of using scarce resources, which helps to identify the optimal use of economic resources. Enhancement of productivity leads more efficient use of resources in economics sectors. Identification of ways and means of improving productivity is an important policy issue which requires an analysis of the effects of determinants of productivity. In the present research work, Total Factor Productivity (TFP) has been econometrically estimated; based on production function theory. Application of this concept indicates that the elasticities of total value-added (i.e. GDP minus oil rents) with respect to physical capital and labor are 0.8 and 0.2 respectively. It is further... 

This thesis introduces a new method for identification and forecasting of future states of nuclear power plants (NPPs) parameters. The proposed method consists of four steps. First, the type of transients is recognized by the modular identifier which has been developed using the latest advances of error back propagation (EBP) learning algorithm. In second step, for more robustness of modular identifier against noisy input data, auto-regressive integrated moving average (ARIMA) method is used. A hybrid network is then used to forecast the selected parameters of the identified transient. ARIMA model is used to estimate the linear component of the selected parameters. The neural network... 

There is a class of small vertical take-off and landing flying vehicles that only have a dual coaxial engine on top and move based on the thrust vector control method. In this project in order to have better insight about the physical mechanism we are dealing with, a conceptual design of a prototype vehicle is first carried out. It is then followed by extraction of two and three dimensional dynamic models of the vehicle. By computer simulation and a simple dynamic analysis, the equations are verified and the movement of the aircraft is discussed for different flight phases  

Reliability modeling, analysis and computation of a Thrust Vector Control System (TVC) is investigated. In this respect, first the TVC subsystems including the jet vanes (JVs), sensors and actuators,... are identified and their pertinent Reliability Block Diagram (RBD) is depicted. Subsequently static reliability of a jet vane is calculated considering both structural and thermal loadings via related verified limit state functions. In addition, a sensitivity analysis is performed that identifies the key JVs design parameters from a reliability point of view. Next, knowing the structural and thermal reliability of the JVs, static reliability of the total TVC system is computed via utility of... 

In this thesis, maneuverability enhancement of a given twin engine fighter aircraft with integrated thrust-vector and conventional aerodynamic control surfaces havebeen studied. For this purpose a nonlinear 6DOF simulation program base on a near exact mathematical model has been prepared for the aircraft, and then a thrust vectoring system for producing moments about three body axes, like that used in F/A-18, has been added to the simulation. The control method that is employed to control the aircraft in simulation environment is based on Nonlinear Dynamic Inversion (NDI). Finally the Velocity Vector Roll (VVR) maneuver has been considered as an example tostudymaneuverability enhacement. It... 

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... 

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...