Sharif Digital Repository

In many medical applications, it is necessary to precisely control a robot to achieve exact positioning. In such cases, some components of robot which had been considered rigid should be modeled with visco-elastic elements to present more exact model of robot, and hence controllers designed under the assumption of rigidity may not accurately control them, especially when time-delay and disturbances have been appeared in the closed-loop system. In this study, we present a new control approach to force such robots to have rigid and exact motions, while they have visco-elastic components. Time-delay in the feedback path defects transient state response, while disturbances change the steady... 

In this paper we will address two major problems in mammogram analysis for breast cancer in MR-images. The first is classification between normal and abnormal cases and then, discrimination between benign and malignant in cancerous cases. Our proposed method extracts textural and statistical descriptive features that are fed to a learning engine based on the use of Support Vector Machine learning framework to categorize them. The obtained results show excellent accuracy in both classification problems, that proves the appropriate combination of our features and selecting powerful classifier i.e. Support Vector Machine leads us to a brilliant outcome  

In this study, we have proposed a novel approach to investigate the features of four subbands of 2-D wavelet transform in magnetic resonance images (MRIs) for normal and abnormal brains which defected by Multiple Sclerosis (MS). Concurrently, another method extracts different kinds of features in spatial domain. Totally, 116 features have been extracted. Before applying the algorithm, we have to use a registration method because of variety in size of brain images. All extracted features have been passed over the Principal Component Analysis (PCA) and have been pushed to an Artificial Neural Network (ANN) that is a feed-forward type. According to changing in position of defected parts of... 

The paper presents an effective algorithm to analyze MR-images in order to recognize Alzheimer's Disease (AD) which appeared in patient's brain. The features of interest are categorized in Features of the Spatial Domain (FSD's) and Features of the Frequency Domain (FFD's) which are based on the first four statistic moments of the wavelet transform. Extracted features have been classified by a multi-layer perceptron Artificial Neural Network (ANN). Before ANN, the number of features is reduced from 44 to 12 to optimize and eliminate any correlation between them. The contribution of this paper is to demonstrate that by using the wavelet transform number of features needed for AD diagnosis has... 

In this paper, we propose two different types of circuit models for Fano-shape guided-mode resonance (GMR) in waveguide gratings. Both the models constitute a resonant tank circuit together with a direct non-resonant channel between the incident and scattered light. One neglects the frequency dependence of the direct non-resonant channel and is only more accurate in the immediate vicinity of the Fano-type resonance. The other accounts for the frequency dependence of the direct non-resonant channel and thus remains accurate within a wider range of frequencies. The former being referred to as the narrow-band model is extremely accurate, insofar as the isolated GMR is of interest within a... 

In this paper, we propose two different types of circuit models for Fano-shape guided mode resonance (GMR) in waveguide gratings. Both models constitute a resonant tank circuit together with a direct non-resonant channel between the incident and the scattered light. One neglects the frequency dependence of the direct non-resonant channel and is only more accurate in the immediate vicinity of the Fano type resonance. The other accounts for the frequency dependence of the direct non-resonant channel and thus remains accurate within a wider range of frequencies. The former being referred to as the narrow-band model is extremely accurate insofar as the isolated GMR is of interest within a narrow... 

In this paper, we propose two different types of circuit models for Fano-shape guided mode resonance (GMR) in waveguide gratings. Both models constitute a resonant tank circuit together with a direct non-resonant channel between the incident and the scattered light. One neglects the frequency dependence of the direct non-resonant channel and is only more accurate in the immediate vicinity of the Fano type resonance. The other accounts for the frequency dependence of the direct non-resonant channel and thus remains accurate within a wider range of frequencies. The former being referred to as the narrow-band model is extremely accurate insofar as the isolated GMR is of interest within a narrow... 

We propose a range-free localization framework in which a network of randomly deployed acoustic sensors can passively use natural acoustic phenomena within its environment to localize itself. We introduce a novel approach for registration of sensors observations which takes advantage of a clustering technique on triplets of associated observations. A Bayesian filtering method is employed to incrementally improve system state estimation as more observations become available. To the best of our knowledge this is the first work done on range-free passive acoustic localization. Simulation experiments of the proposed algorithms are presented. © 2008 IEEE  

Numerical approximation based on different forms of the governing partial differential equation can lead to significantly different results for two-phase flow in porous media. Selecting the proper primary variables is a critical step in efficiently modeling the highly nonlinear problem of multiphase subsurface flow. A comparison of various forms of numerical approximations for two-phase flow equations is performed in this work. Three forms of equations including the pressure-based, mixed pressure-saturation and modified pressure-saturation are examined. Each of these three highly nonlinear formulations is approximated using finite difference method and is linearized using both Picard and... 

The properties of Functionally Graded Materials (FGM) are characterized by gradual variation of volume fraction of their constituents or phases over the thickness direction. They are normally ceramic in one side and metal in the other side. This kind of material has been employed as thermal barrier and also as coatings in many applications including turbine blades. Thermal stress behavior of FGMs is normally studied by simulating the material as a composite laminate where the properties ofeach layer are found by averaging the properties and volume fraction of FGM constituents through the thickness of the layer. However, it should be mentioned that the grains of FGM constituents are usually... 

The electrodeposition of nickel was studied using electrochemical techniques in different electrolytes and various agents. The voltammetry analysis clearly showed that the electrodeposition of nickel was a diffusion-controlled process associated with a typical nucleation process. The current transients represented instantaneous nucleation with a typical three-dimensional (3D) growth mechanism. Scharifker's equations were derived for instantaneous and progressive nucleation of the 3D growth of the spherical centers under diffusion-controlled condition. The number of nucleation sites increased with the increment in overpotential and Ni 2+ concentration. Atomic force microscopy was used to...