Sharif Digital Repository

As a result of adopting various sample preparation techniques and optical measurement strategies, there are different experimental datasets available for presenting the complex dielectric function of gold. Therefore, evaluating them and selecting the most reliable ones seem essential for the corresponding optical-based designs and applications. The Brendel-Bormann model, one of the most accurate theoretical models for rendering the complex dielectric function of materials, is considered an appropriate criterion for this purpose. Despite the model's computational complexity, MS Excel has been employed as a fast and accessible tool for calculating the model. According to the results, ‘Palik'... 

Call admission control schemes are crucially Important concepts ID researches on cellular mobile networks. One of them is the new thinning scheme. In this study we define a confidence interval for threshold and the numerical results show the performance of the scheme in defined interval. Also we discuss the sensitivity of the scheme (in sample-based sensitivity method) at different thresholds. The results show the better performance in confidence thresholds and sensitivity of scheme into variations of thresholds  

This paper presents an effective hybrid optimal modulation technique for a cascaded H-bridge (CHB) multilevel inverter. The introduced method is generalized optimal pulsewidth modulation, which can be extended to any m-level CHB multilevel inverter operating at any switching frequency. The presented hybrid optimal modulation strategy includes the pattern exchange and optimal modulation techniques. In the optimal modulation technique, the hybrid interior-point algorithm, which is more flexible and efficient than conventional optimization techniques, is applied. The proposed hybrid optimal modulation strategy yields balanced units' output fundamental voltages, and low total harmonic distortion... 

Human mind from system perspective deals with high dimensional complex world as an adaptive Multi-Input Multi-Output complex system. This view is theorized by reductionism theory in philosophy of mind, where the world is represented as logical combination of simpler sub-systems for human so that operate with less energy. On the other hand, Human usually uses linguistic rules to describe and manipulate his expert knowledge about the world; the way that is well modeled by Fuzzy Logic. But how such a symbolic form of knowledge can be encoded and stored in plausible neural circuitry? Based on mentioned postulates, we have proposed an adaptive Neuro-Fuzzy machine in order to model a rule-based... 

In this paper a new probabilistic view to the Visual Secret Sharing (VSS) is presented and as a result, a new VSS scheme is proposed. The proposed scheme is a threshold scheme with perfect black pixel reconstruction. We present the scheme by introducing two sets C0 and C1. We consider an unknown probability distribution on the elements of C0 and C 1. Perfectness provides some linear constraints on the probabilities of C0 and C1 elements. By solving the provided system of linear equations, the probability distributions are specified and we achieve a perfect VSS scheme. ©2008 IEEE  

A pH-responsive drug delivery system based on core shell structure of mesoporous silica nanoparticle (MSN) and chitosan-PEG copolymer was prepared and characterized by Fourier transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), scanning electron microscope (SEM), and high-resolution transmission microscope (HR-TEM) techniques. In order to improve compatibility MSN and drug, mesoporous nanosilica was modified by 3-aminopropyl triethoxysilane. The release of erythromycin (a macrolide antibiotic) as a model drug was investigated in two pHs, 7.4 and 5.5  

In systems with hysteresis behavior like magnetic cores, Piezo actuators, Shape Memory Alloy(SMA), we essentially need an accurate modeling of hysteresis either for design or performance evaluation; also in some control applications accurate system identification is needed. One of the famous methods of Hysteresis modeling is Preisach model. In this numerical method hysteresis is modeled by linear combination of smaller hysteresis loops as an elemental operator and local memory. In this paper we discuss those Radial Base artificial neural networks (RBF) which provides natural settings in accordance with the Preisach model. It is shown that the proposed approach can represent hysteresis... 

Active Learning Method (ALM) is a powerful fuzzy soft computing tool, developed originally in order to promote an engineering realization of human brain. This algorithm, as a macro-level brain imitation, has been inspired by some behavioral specifications of human brain and active learning ability. ALM is an adaptive recursive fuzzy learning algorithm, in which a complex Multi Input, Multi Output system can be represented as a fuzzy combination of several Single-Input, Single-Output systems. SISO systems as associative layer of algorithm capture partial spatial knowledge of sample data space, and enable a granular knowledge resolution tuning mechanism through the learning process. The... 

Human Brain is one of the most wonderful and complex systems which is designed for ever; A huge complex network composed of neurons as tiny biological and chemical processors which are distributed and work together as a super parallel system to do control and vital activities of human body. Brain learning simulation and hardware implementation is one of the most interesting research areas in order to make artificial brain. One of the researches in this area is Active Learning Method in brief ALM. ALM is an adaptive recursive fuzzy learning algorithm based on brain functionality and specification which models a complex Multi Input Multi Output System as a fuzzy combination of Single Input... 

In some systems with hysteresis behavior like Shape Memory Alloy (SMA) actuators and Piezo actuators, we essentially need an accurate modeling of hysteresis either for controller design or performance evaluation. One of the most interesting Hysteresis non-linearity identification methods is Preisach model in which hysteresis is modeled by linear combination of elemental operators. Despite good ability of Preisach modeling to extract main features of system with hysteresis behavior, cause of tough numerical nature of Preisach, it is not convenient to use in real-time control applications. In this paper we present a novel method based on Artificial Neural Network. For evaluation of proposed...