AMIRKABIR
Year:2008 | Volume:18 | Issue:67-A (TOPICS IN: GROUPS OF ENGINEERING, ELECTRONIC, BIOMEDICAL, COMPUTER)|Papers Count:13

In this paper statistical assessment of target parameters, in polarimetric remote sensing radars, such as scattering mechanism and Entropy are extracted and simulated. For this objective eigenvector analysis technique by target decomposition method (TDM) used for calculating eigenvector as well as probability of them from their coherency or covariance matrix. In addition, a simulation scheme developed for calculating Entropy and Scattering mechanism for spheroid targets and rough surfaces. In this work, drop size distribution (DSD) is considered for stochastic process of spheroid rain droplet. Results for different distributions presented and compared with radar data set from German Aerospace center (DLR).

Adaptive filtering is an indispensable tool in a large number of signal processing applications. In this paper, a new adaptive filtering algorithm named fast affine projection algorithm based on matching pursuits (MP) is presented. In this algorithm, one of the filter coefficients is suitably selected and updated iteratively. Another characteristic of the proposed algorithm is employing one or more MP-iterations at each time instant, in order to fulfill a suitable tradeoff between convergence rate and computational complexity. The Performance of the proposed algorithm is fully studied through the energy conservation analysis used in adaptive filters and a general expression for the steady-state mean square error is derived. The simulation results highlight better the out-performance of the proposed algorithm in terms of both convergence rate and steady-state mean square error.

In this paper, an efficient method is proposed for load estimation of distribution networks with limited real-time data based on principal component analysis. The principal components of load variables are first detected off-line from historical data. Next, the interrelations between the load variables are developed using a new concept that we call Inverse PCA (IPCA) method; this leads to some proper models devised so that the distribution network becomes observable. Finally, through incorporation of a certain finite set of real time data measurements, the loads of all network nodes in real-time are estimated with a desired degree of accuracy via the IPCA method. A case study on a real network is considered in the paper to highlight better the merit of the proposed method. The experimental results easily show that the proposed method outperforms the previously cited techniques.

In this paper, the main aim is to introduce a regular procedure to select the location of arresters (voltage limiters) in a way to optimally confine the risk of flashovers in a given high voltage network. Mathematically, simulation optimization is used to create an acceptable meta model from a real model which, on its own, is created to represent a real high voltage network in a transient analyzer program, The proposed meta model is a three layer perceptron neural network which is learned to estimate the risk function with arrester locations as inputs and network risk of flashover as output. Genetic algorithm is then invoked to locate the best position of arresters. The proposed method is then accomplished to set the location of 5 identical arresters in Iranian South East 400 kV network and the results are shown to be acceptable by simulating the real model of this network.

Shear stress is known to play a central role in restenosis formation and is sensitive to stent geometry. This article presents 2D and 3D computational fluid dynamics models to analyze steady blood flow in a stented human coronary artery. In 3D simulations, .stents are assumed with real structure and modeled using the commercial software package (Gambit, V2.0). The blood flow was modeled as an incompressible Newtonian viscous fluid resulting in the Navier-Stokes equations. Rigid geometric boundary conditions were assumed for all simulations. The governing equations were solved using the commercial finite volume code (Fluent, V6.0.12). The results have shown that the wall shear stress between stent struts was sensitive to strut spacing, profile of strut, number of strut and curvature. In 3D models, the wall shear stress distributions for different types of stents were calculated and critical regions were investigated. By application of a flow divider, the wall shear stress in stented segment increases markedly.

In this study, nano particles of non-stoichiometric hydroxyapatite (HAp) were wet chemically prepared in optimized conditions. Phase transformation, morphology and particle size of resultant powders were examined by XRD and SEM. Results revealed that in semi-crystalline nano particles obtained by wet chemical synthesis, there is no obvious change in morphology and particle size by thermal treatment up to 600oC, while the homogeneity has increased and a great enhancement in crystallinity has been observed. In temperatures more than 900oC, a phase transformation to beta-tricalcium phosphate occurs due to non-stoichiometry of HAp structure. Simultaneously, the particles are partially sintered and grain boundaries can be recognized in a vivid micro-structure.

Microparticulate form of biodegradable polymers containing drugs is a promising approach toward new controlled release drug delivery systems, and a perfect alternative for daily painful injection of protein drugs. One major challenge in developing such systems is increasing efficiency of fabrication processes and retaining stability and effectiveness of encapsulated proteins and drugs. In this study capabilities of double emulsion (W/O/W)-solvent evaporation method for encapsulation of attenuated avian influenza virus (H9N2) in poly (lactic-co-glycolic acid) 50:50 were investigated and, the protein in vitro release profiles were determined. Some basic salts such as MgCO3 co-encapsulated with protein were used to increase stability and release of the protein. Additives such as NaCL and urea were added to second water phase to ensure and increase loading of the protein. The microspheres were all spherical with almost smooth surface and some small pores. Release profiles reveal that MgCO3 increased the amount of released protein but did not have a significant effect on release rate.

Nowadays, the main difficulties encountered in cryosurgery are the exact position of freezing contour, the depth and extent of tissue freezing, and temperature distribution in tissue. In this study, for the first time, superficial cryosurgery treatment has been modeled by finite element method using macros. In this modeling, the tissue is treated as nonideal materials freezing over a temperature range, and the thermophysical properties of which are temperature dependent. The enthalpy method is applied to solve this highly nonlinear problem. After solving this problem for superficial cryoprobe, good agreement was seen in penetration depth of freezing in tissue and the extent of freezing on tissue between our results and the results of other studies. This problem was solved for a new probe by applying cooling and heating loads simultaneously. According to calculated results, for the new probe, the depth of freezing and the quantity of freezing degrease to 1mmand 20%, respectively.

In this paper, a new method for quantification of rigidity in elbow joint of Parkinsonian patients is introduced. One of the most known syndromes in Parkinson's disease is increased passive stiffness in muscles, which leads to rigidity in joints. Clinical evaluation of stiffness in wrist and/or elbow, commonly used by clinicians, is based on Unified Parkinson's Disease Rating System (UPDRS). Subjective nature of this method may influence the accuracy and precision of evaluations. Hence, introducing an objective standard method based on quantitative measurements may be helpful. A test rig was designed and fabricated to measure range of motion and viscous and elastic components of passive stiffness in elbow joint. Measurements were done for 41 patients and 11 controls. Measures were extracted using Matlab-Rl4 software and statistical analyses were done by Spss-13. Relation between each computed measure and the level of illness were analyzed. Results showed a better correlation between viscous component of-stiffness and UPDRS score compared to the elastic component. Results of this research may help to introduce a standard objective method for evaluation of Parkinson's disease.

A single reference image is used for detecting the face area in gray scale images. The algorithm uses Gabor transform as a powerful tool for feature extraction. Zero-crossing of Gabor transform is used for constructing the binary feature vectors and Hamming distance is used for measuring the similarity between feature vectors. Our developed method uses a pyramidal structure for finding the face images with different sizes. The algorithm has considerable robustness to the cluttered backgrounds and non-uniform illumination. More than 11,000 face images have been tested. The results show a very high detection rate for non occluded face images with low facial expression. The algorithm can also be used for correcting the head rotation angle in input images. The algorithm can also be used for correcting the head rotation angle in input images. The proposed method is suitable for the cases that contain one face image.