Sharif Digital Repository

An improved wavelet-based 2-D ECG data compression method is presented which employs a double stage compression. In the first stage the set partitioning in hierarchical trees (SPIHT) algorithm is used to compress the 2-D data array formed by cutting and beat-aligning the heartbeat data sequence. In the second stage vector quantization is applied to the residual image obtained from the previous stage. The 2-D approach utilizes both inter-beat and inter-sample redundancies in the ECG signal The proposed algorithm is applied to several records in the MIT-BIH arrhythmia database. Results show lower Percent Root mean square Difference (PRD) than 1-D methods and several 2-D methods for the same... 

Up to now, different methods have been developed for estimation of buildup factor (BF). However, either expensive estimation or time-consuming estimation are major restrictions/challenges of these methods. In this study a new technique utilizing combination of Monte Carlo method and the Bayesian regularization (BR) learning algorithm of multilayer feed-forward neural network (FFNN) is employed for estimation of BFs. First, the BFs of the different elements (i.e. Al, Cu, and Fe) at different energies and different mean free paths (MFPs) are modeled by the MCNP code. The results show that the calculated BFs by MCNP code are in good agreement with the reported values of American nuclear society... 

Up to now, different methods have been developed for estimation of buildup factor (BF). However, either expensive estimation or time-consuming estimation are major restrictions/challenges of these methods. In this study a new technique utilizing combination of Monte Carlo method and the Bayesian regularization (BR) learning algorithm of multilayer feed-forward neural network (FFNN) is employed for estimation of BFs. First, the BFs of the different elements (i.e. Al, Cu, and Fe) at different energies and different mean free paths (MFPs) are modeled by the MCNP code. The results show that the calculated BFs by MCNP code are in good agreement with the reported values of American nuclear society... 

This paper present a simple watermarking approach based on the rotation of low frequency components of image blocks. The rotation process is performed with less distortion by projection of the samples on specific lines according to message bit. To have optimal detection Maximum Likelihood criteria has been used. Thus, by computing the distribution of rotated noisy samples the optimum decoder is presented and its performance is analytically investigated. The privilege of this proposed algorithm is its inherent robustness against gain attack as well as its simplicity. Experimental results confirm the validity of the analytical derivations and also high robustness against common attacks. ©... 

In this paper, a new scaling based information hiding approach with high robustness against noise and gain attack is presented. The host signal is assumed to be stationary Gaussian with first-order autoregressive model. For data embedding, the host signal is divided into two parts, and just one patch is manipulated while the other one is kept unchanged for parameter estimation. A maximum likelihood (ML) decoder is proposed which uses the ratio of samples for decoding the watermarked data. Due to the decorrelating property of the proposed decoder, it is very efficient for watermarking highly correlated signals for which the decoding process is not straightforward. By calculating the... 

Denoising of corrupted images has been a classical problem in image processing. In this paper we propose a new approach for image noise reduction using wavelet transform. In this method an improved version of thresholding neural networks (TNN) is used to find the optimum threshold values in the sense of minimum mean square error (MMSE). Based on these optimum thresholds a novel cycle-spinning based method is used to reduce image artifacts. In this method, we utilize two thresholding schemes as the thresholding operator of cycle-spinning. A neighbor dependent thresholding scheme is employed as its first shrinkage step and a simple wavelet thresholding with the optimum derived threshold values... 

In assembly level programming we need to know the mnemonic of each assembly instruction. But it is not so easy to remember mnemonics of all instructions, while the instruction set of Pentium processor includes 280 instructions. In this paper we introduce a new programming approach to assembly level programming in which most important assembly instructions (about 100 instructions) can be substituted for simple equivalents. These equivalent instructions are based on simple familiar operators and make a large simplification in assembly programming. This new language has a free format structure and hence is called Free Format Assembly Language. Evaluating the performance of this language using a... 

In this paper, a novel scaling based information hiding approach robust against noise and gain attack is presented. The host signal is assumed to be stationary Gaussian modeled with a first-order autoregressive process. For data embedding, the host signal is divided into two parts. One part is manipulated while the other part is kept unchanged for parameter estimation. The decoding scheme using the ratio of samples is suitable for highly correlated signals in which the decoding process is difficult. By calculating the distribution of the ratio, the performance of the maximum likelihood decoder is analytically studied. The proposed algorithm is applied to several artificial Gaussian... 

In this paper we propose a new method for image noise reduction based on wavelet transform. In this method we: introduce an improved version of thresholding neural networks. (TNN) by utilizing a new class of smooth nonlinear thresholding functions as the activation function. Using this approach we will find the best thresholds in the sense of minimum mean square error (MMSE). Then using, TNN with obtained thresholds, we employ a cycle-spinningbased technique to reduce image artifacts. Experimental results indicate that the proposed method outperforms several other established wavelet denoising techniques, in terms of Peak-Signal-to-Noise-Ratio (PSNR) and visual quality. © 2007 IEEE  

In this paper, a new multiplicative image watermarking system is presented. As human visual system is less sensitive to the image edges, watermarking is applied in the contourlet domain, which represents image edges sparsely. In the presented scheme, watermark data is embedded in the most energetic directional subband. By modeling General Gaussian Distribution (GGD) for the contourlet coefficients, the distribution of watermarked noisy coefficients is analytically calculated. At the receiver, based on the Maximum Likelihood (ML) decision rule, the optimal detector is proposed. Experimental results show the imperceptibility and high robustness of the proposed method against Additive White... 

Prediction of the amino acids that have a catalytic effect on the enzymes is a major stage in appointing the activity of the enzymes and classification. The biological activity of a protein usually depends on the existence of a small number of amino acids. Recently, many algorithms have been proposed in the literature for finding these amino acids which are complex and time consuming. In this paper, we will introduce a new method for predicting the active sites that will use the spatial coordinates and the type of amino acids that contain the active sites. In order to increase the speed we use an approximate graph isomorphism algorithm. Furthermore, this algorithm allows us to find several... 

In this paper, a new blind scaling based watermarking approach is presented. The host signal is assumed to be stationary Gaussian with first-order autoregressive model. Partitioning the host signal into two separate parts, the data is embedded in one part and the other is kept unchanged for blind parameter estimation. Driving the distribution of the decision variable we have suggested a maximum likelihood decoding algorithm which is independent of the host signal distribution and can be applied for any transform domains. The proposed algorithm is applied to both artificial Gaussian autoregressive signals as well as various test images. Experimental results confirm the independence of the... 

Trapping a single aerosol using optical tweezers could be of great importance for environmental sciences. Though a single nanoparticle as small as 10 nm is successfully trapped in aqueous media using optical tweezers, due to spherical aberration only large clusters of nanoparticles were stably trapped in air. In this paper we provide our theoretical and experimental results on optimized trapping of aerosols as small as 400 nm in radius by the introduction of an extra spherical aberration source in order to minimize the total spherical aberration of the system. Our method allows for trapping of high refractive index particles such as polystyrene beads in air. It also provides considerably... 

Optical tweezers have proven to be indispensable micromanipulation tools especially in aqueous solutions. Because of the significantly larger spherical aberration induced by the refractive index mismatch, trapping aerosols has always been cumbersome if not impossible. We introduce a simple but very efficient method for optimized aerosol trapping at a desired depth. We show that a wise selection of the immersion medium and the mechanical tube length not only enables trapping of objects that are known to be untrappable but also provides a way to tune the trappable depth range  

In this paper, a new multiplicative semi-blind image-adaptive watermarking system has been presented, which exploits human visual model for adapting the watermark data to local properties of the host image. To have a better robustness, the proposed algorithm is implemented on the low-frequency coefficients of the wavelet transform. Moreover, regarding invisibility of the algorithm, the strength factor which controls the watermark power is optimally selected. To extract the watermark data, the Maximum Likelihood (ML) estimator is used. Experimental results confirm the imperceptibility of the proposed method and its high robustness against various attacks such as JPEG compression, noise... 

The challenge of finding an optimized and reliable path dates back to emersion of mobile robots. Several approaches have been developed that have partially answered this need. Satisfying results in previous implementations has led to an increased utilization of sampling-based motion planning algorithms in recent years, especially in high degrees of freedom (DOF), fast evolving environments. Another advantage of these algorithms is their probabilistic completeness that guarantees delivery of a path in sufficient time, if one exists. On the other hand, sampling based motion planners leave no comment on safety of the planned path. This paper suggests biasing the Rapidly-exploring Random Trees... 

This paper presents the most frequently used maintenance concerns and challenges in distribution utilities of Iran. A questionnaire is devised and distributed among the maintenance experts in more than 30 distribution utilities all over Iran and their responses have been taken under consideration in this paper. The aim is to get the most out of the successful maintenance experiences within the utilities, to find the solutions on the current common challenges on the distribution system maintenance policies, and eventually to enlighten the way on the transition to the more efficient maintenance approaches such as reliability-centered maintenance (RCM) in distribution systems  

This paper presents the most frequently used maintenance concerns and challenges in distribution utilities of Iran. A questionnaire is devised and distributed among the maintenance experts in more than 30 distribution utilities all over Iran and their responses have been taken under consideration in this paper. The aim is to get the most out of the successful maintenance experiences within the utilities, to find the solutions on the current common challenges on the distribution system maintenance policies, and eventually to enlighten the way on the transition to the more efficient maintenance approaches such as reliability-centered maintenance (RCM) in distribution systems  

Polylactic acid (PLA) scaffolds produced by the fused deposition modeling (FDM) method have biocompatibility, close Young's modulus to that of bone, and the ability to make complex shapes. However, PLA has some drawbacks like brittleness, inappropriate mechanical strength and hydrophobicity, and a low degradation rate. In this study, polyethylene glycol (PEG) (5 and 10 wt%) by solving method and titanium (Ti) particles (5 wt%) by two different methods were mixed with PLA to address the mentioned problems. Extruded filaments were investigated by X-ray diffraction (XRD), differential scanning calorimetry (DSC), and fourier transform infrared (FTIR). Surface morphology of the produced filaments... 

3D hydrogel environment with both unique properties of nanofibrous structure and electrical character can provide a promising scaffold for skeletal muscle tissue engineering approaches. Herein, the poly acrylic acid (PAA)-based hydrogel was engineered to conductive one by aniline polymerization in the form of nanofibers. The poly aniline (PANi) nanofibers were made by the optimized chemical reactions between the surface carboxylate groups of based hydrogel and protonated aniline monomers. We found that the strong bonding which was created between PANi and camphor sulphonic acid (CSA) as a doping agent supporting the stable electrical property of composite hydrogel after incubation in cell...