Sharif Digital Repository

In this paper, an efficient dynamic simulation algorithm is developed for an Unmanned Underwater Vehicle (UUV) with a N degrees of freedom manipulator. In addition to the effects of mobile base, the various hydrodynamic forces exerted on these systems in an underwater environment are also incorporated into the simulation. The effects modeled in this work are added mass, viscous drag, fluid acceleration, and buoyancy forces. Also the dynamics of thrusters are developed, and an appropriate mapping matrix dependent on the position and orientation of the thrusters on the vehicle, is used to calculate resultant forces and moments of the thrusters on the center of gravity of the vehicle. It should... 

The inhibition effects of 3.5 bis (2-pyridil) 4-amino 1,2,4 triazole (NBTA) and 1-10 phenantrolin (PHEN), on corrosion of mild steel in acid solutions, (sulphuric acid and hydrochloric acid) were studied. The Tafel polarisation and ac impedance techniques were employed. Results obtained reveal that both compounds are relatively good inhibitors. The inhibition efficiencies of NBTA are higher in hydrochloric acid than in sulphuric acid. This has been attributed to the synergistic effect of chloride ions present in hydrochloric acid. The mechanism of inhibition of PHEN is believed to be owing to the formation of insoluble chelates between the organic molecules and atom/ion on the metal surface.... 

The seismic risk framework of building structures has been presented to reduce earthquake-induced adverse consequences. In this context, probabilistic analysis of engineering demand parameters (EDPs) is always associated with many uncertainties and high computational demand for use in practical applications. This study has been presented to efficiently estimate the distribution of EDPs in probabilistic seismic risk assessment of irregular steel moment-resisting frames (SMRFs). For this purpose, the incorporation of the consistent fish-bone (CFB) model and the endurance time (ET) analysis method has been used. The proposed method (i.e., CFB-ET) has a substantial impact on reducing the... 

Although medical advancements have successfully helped a lot of couples with their infertility by assisted reproductive technologies (ART), sperm selection, a crucial stage in ART, has remained challenging. Therefore, we aimed to investigate novel sperm separation methods, specifically microfluidic systems, as they do sperm selection based on sperm and/or the female reproductive tract (FRT) features without inflicting any damage to the selected sperm during the process. In this review, after an exhaustive studying of FRT features, which can implement by microfluidics devices, the focus was centered on sperm selection and investigation devices. During this study, we tried not to only point to... 

In clustering spatial data, we are given a set of points in Rn and the objective is to find the clusters (representing spatial objects) in the set of points. Finding clusters with different shapes, sizes, and densities in data with noise and potentially outliers is a challenging task. This problem is especially studied in machine learning community and has lots of applications. We present a novel clustering technique, which can solve mentioned issues considerably. In the proposed algorithm, we let the structure of the data set itself find the clusters, this is done by having points actively send and receive feedbacks to each other. The idea of the proposed method is to transform the input... 

In this paper, a new highly convergent, efficient, and fast response control technique entitled as fuzzy-Padé control method is introduced. It provides a simple methodology to exploit the heuristic knowledge in controlling a system. Fuzzy-Padé controllers originate from a unification of heuristic knowledge expressed as the rule base, and Padé approximants. In this method, fuzzy singleton rules are used to generate the rule base. Accordingly, unknown parameters in the Padé approximant are determined using these rules. The fuzzy-Padé controllers possess certain advantages over fuzzy controllers, and they can be applied in situations where fuzzy controllers previously failed. To demonstrate the... 

One of the main causes of death the world over are cardiovascular diseases, of which coronary artery disease (CAD) is a major type. This disease occurs when the diameter narrowing of one of the left anterior descending, left circumflex, or right coronary arteries is equal to or greater than 50 percent. Angiography is the principal diagnostic modality for the stenosis of heart vessels; however, because of its complications and costs, researchers are looking for alternative methods such as data mining. This study conducts data mining algorithms on the Z-Alizadeh Sani dataset which has been collected from 303 random visitors to Tehran's Shaheed Rajaei Cardiovascular, Medical and Research... 

We theoretically demonstrate the tunabiltiy of terahertz random lasers composed of high temperature superconductor YBCO and ruby layers as active medium. The considered system is a one-dimensional disordered medium made of ruby grain and YBCO. Finite-difference time domain method is used to calculate the emission spectrum and spatial distribution of electric field at different temperatures. Our numerical results reveal that the superconductor based random lasers exhibit large temperature tunability in the terahertz domain. The emission spectrum is significantly temperature dependent, the number of lasing modes and their intensities increase with decreasing temperature. Also, we make some... 

We propose that spectral intensity of superconductor based random lasers can be made tunable by changing temperature. The two fluid model and wavelength dependent dispersion formula have been employed to describe the optical response of the superconducting materials. Random laser characteristics have been calculated using the one dimensional FDTD method. Our simulation results reveal that the emission spectrum can be manipulated through the ambient temperature of the system. It is observed that transition from metal phase to pure superconducting phase leads to the enhancement of the laser emission. Furthermore, spatial distribution of the fields in one dimensional disordered media is very... 

The vulnerability of microprocessors to soft errors is increasing due to continuous shrinking in fabrication process. Recent studies show that 1-5% of the SEUs (single event upset) can cause MBUs (multiple bit upsets). The probability of MBU generation due to SEU is increasing because of the reduction in minimum energy required to flip a memory bit in modern technologies. Register file is the most sensitive component in a microprocessor. In this paper, we present an innovative way to protect registers in a 64-bit register file for a RISC processor using extended Hamming (8, 4) code (SEC-DED code) and narrow-width values. A narrow-width value can be represented by half number of bits of the... 

Voluminous amount of videos in today’s world has made the subject of objective (or semi-objective) classification of videos to be very popular. Among the various descriptors used for video classification, SIFT and LIFT can lead to highly accurate classifiers. But, SIFT descriptor does not consider video motion and LIFT is time-consuming. In this paper, a robust descriptor for semi-supervised classification based on video content is proposed. It holds the benefits of LIFT and SIFT descriptors and overcomes their shortcomings to some extent. For extracting this descriptor, the SIFT descriptor is first used and the motion of the extracted keypoints are then employed to improve the accuracy of... 

This paper presents a new approach for fuel burn up evaluation and radioactive inventory calculation used in Tehran Research Reactor. The approach is essentially based upon the utilization of a program written by C# which integrates the cell and core calculation codes, i.e., WIMSD-4 and CITVAP, respectively. Calculation of fuel burn up and radioactive inventories has been done for 26 core configuration of Tehran Research Reactor with HEU fuel element. The present inventory and fuel enrichment of each fuel element have been calculated  

During the past years, various principal component analysis algorithms have been developed. In this paper, a new approach for local nonlinear principal component analysis is proposed which is applied to capture voice conversion (VC). A new structure of autoassociative neural network is designed which not only performs data partitioning but also extracts nonlinear principal components of the clusters. Performance of the proposed method is evaluated by means of two experiments that illustrate its efficiency; at first, performance of the network is described by means of an artificial dataset and then, the developed method is applied to perform VC  

The ability of wearable cameras to continuously capture the first person viewpoint with minimal user interaction, has made them very attractive in many application domains. Wearable technology today is available and useful but not widely used and accepted due to various challenges mainly privacy concerns. In this paper, we introduce a novel efficient privacy-aware framework for wearable cameras that can protect all sensitive subjects such as people, objects (e.g, display screens, license plates and credit cards) and locations (e.g, bathrooms and bedrooms). It uses the contextual information obtained from the wearable's sensors and recorded images to identify the potential sensitive subjects... 

This paper investigates free torsional vibration behavior of a nonlinear nano-cone, based on the nonlocal strain gradient elasticity theory. The nano-cone is made of homogeneous and isotropic materials. Moreover, the cross-sectional area of the nano-cone varies in the longitudinal direction by a nonlinear function. Governing equation and boundary conditions are derived using Hamilton’s principle. These equations are solved by employing the generalized differential quadrature method (GDQM). The effects of some parameters, such as cross-sectional area change and small-scale parameter, are investigated. Results show that the cross-sectional area change has a significant effect on the torsional... 

Advances in the manufacturing of miniaturized low-power embedded systems are paving the way for ultra-lightweight wearable cameras that can visually log the minute details of people's daily lives. This survey highlights the possible applications of wearable cameras, from industrial to personal, and outlines the main challenges in realizing their full potential. © 2017 IEEE  

TiO2 nanoparticles were prepared by the sol - gel process using 2-hydroxylethy- lammonium formate as an ionic liquid. Nanoparticles were crystallized at various temperatures (300-700°C). The products were characterized using X-ray diffraction (XRD), nitrogen adsorption - desorption isotherms and scanning electron microscopy (SEM) techniques. It was found that the resulting TiO2 nanoparticles had good thermal stability either to resist collapse or the anatase-to-rutile phase transformation during heat treatment. The photocatalytic activity of the nanocrystalline TiO2 was evaluated by the degradation of Acid Blue 92 (AB92) which is commonly used as a textile dye. The results showed that the... 

In the last decades, much attention has been paid to the design of multi-speaker voice conversion. In this work, a new method for voice conversion (VC) using nonlinear principal component analysis (NLPCA) is presented. The principal components are extracted and transformed by a feed-forward neural network which is trained by combination of Genetic Algorithm (GA) and Back-Propagation (BP). Common pre- and post-processing approaches are applied to increase the quality of the synthesized speech. The results indicate that the proposed method can be considered as a step towards multi-speaker Voice conversion. © 2007 IEEE  

In this paper, a new constructive auto-associative neural network performing nonlinear principal component analysis is presented. The developed constructive neural network maps the data nonlinearly into its principal components and preserves the order of principal components at the same time. The weights of the neural network are trained by a combination of Back Propagation (BP) and Genetic Algorithm (GA) which accelerates the training process by preventing local minima. The performance of the proposed method was evaluated by means of two different experiments that illustrated its efficiency. ©2007 IEEE  

In most image retrieval systems, images include various high-level semantics, called tags or annotations. Virtually all the state-of-the-art image annotation methods that handle imbalanced labeling are search-based techniques which are time-consuming. In this paper, a novel coupled dictionary learning approach is proposed to learn a limited number of visual prototypes and their corresponding semantics simultaneously. This approach leads to a real-time image annotation procedure. Another contribution of this paper is that utilizes a marginalized loss function instead of the squared loss function that is inappropriate for image annotation with imbalanced labels. We have employed a marginalized...