Sharif Digital Repository

The behaviour of a dislocation pileup with a finite-strength source is investigated in the presence of various stress gradients within a continuum model where a free-dislocation region exists around the source. Expressions for dislocation density and stress field within the pileup are derived for the situation where there are first and second spatial gradients in applied stress. For a pileup configuration under an applied stress, yielding occurs when the force acting on the leading dislocations at the pileup tips reaches the obstacle strength, and at the same time, it is required that the source be at the threshold stress for dislocation production. A numerical methodology is presented to... 

The continuum theory of dislocations is applied to formulate the problem of a double ended dislocation pileup under quadratic applied stress. Accordingly, a second order stress gradient plasticity model is presented to address the contribution of the first and the second stress gradients in the effect interpretation. The model is employed to predict the initial strengthening and subsequent hardening in curved and straight thin foils under pure bending within the continuum framework. It is shown that the so-called stress gradient plasticity model that ignores the second stress gradient may not give sound interpretations of the size effects. The plastic response of thin foils is affected by... 

For a moving camera recognizing that it has seen a place before now, is one the most important issues in the 3D reconstruction problems. In these problems, the main goal is to create a three-dimensional model from a sequence of 2D captured images during different times. That part of the scene which is rendered by a camera is often modeled by a frustum. Calculating the amount of intersection of two camera view frustums at different times can help to solve this problem. However, there are two major difficulties. First, calculating the intersection of two frustums, in general, is so complicated. And second, there are some uncertainties in the moving camera parameters over time. In this paper,... 

The problem of finding nearest neighbors in a certain distance is well defined in machine learning area. There are well-known and exact solutions for it. However, in real world problems, especially in machine vision area, where we have a moving sensor and we want to know which objects of the scene are in the measurement range of it, two issues are important. First, usually in these problems, the time cost is more important than accuracy. It means they can tolerate some measurements error if they can do the process in real-time. Second, the location of an object can be described in the three-dimensional space and does not require the higher dimensions. According to these issues, we introduced... 

A continuum implementation of stress gradient plasticity is established to analyze passivated thin films under tension. It is verified and evaluated by investigation of the tensile response of passivated Cu films with different thicknesses and grain sizes. The material parameters are fitted to the stress-strain experimental data, while the length scale parameter is directly characterized from the corresponding available discrete dislocation predictions. The numerical solutions give rise to boundary layers near the interface between film and passivation. This prediction is consistent with the formation of dislocation pileups at the film-passivation interface and also is responsible for the... 

The fast growth of battery operated devices has made low power SRAM designs a necessity in recent years. Moreover, embedded SRAM units have become an important block in modern SoCs. The SRAM performance is limited by the cell stability during different operation. By adding extra transistor to the conventional 6T-cell, hold, read and write static noise margin (SNM) can be improved in the sub-threshold SRAM. In this paper we proposed a new 9T-cell SRAM that shows 80% and 50% improvement in read and write SNM respectively in comparison to the conventional 6T-cell SRAM. Using stack transistors in the leakage current path, the new structure shows lower bitline leakage assisting the sense... 

Persian handwritten digit recognition has attracted some interests in the research community by introduction of large Hoda dataset. In this paper, the well-known random forest (RF) and convolutional neural network (CNN) algorithms are investigated for Persian handwritten digit recognition on the Hoda dataset. Using the Hoda dataset as a standard testbed, we have performed some experiments with different preprocessing steps, feature types, and baselines. It is then shown that RFs and CNNs perform competitively with the state-of-the-art methods on this dataset, while CNNs being the fastest if appropriate hardware is available  

Mud filtration happens during an overbalanced drilling operation that causes mud invasion into pores and fractures. The productivity of a formation is significantly affected by the invasion of the mud into the near-wellbore area during the mud loss process. A considerable number of studies have evaluated mud filtration statically; however, a few studies have considered the dynamic behavior of a mud loss process during overbalanced drilling, which results in the inadequate prediction of the mud loss volume and inflicted damage to the formation. In this study, a near-wellbore simulation system (NeWSS) was designed to evaluate the dynamic mud loss behavior using dimensionless parameters and... 

This research addresses the location problem of congested facilities, assuming service interruptions and customer withdrawals. Service interruptions can occur as a result of events such as machine failures, power outages, and communication system disconnections. As long as no interruption occurs, each facility functions as a M/M/1 queuing system. Upon an interruption, the server stops working, and customers receiving service or waiting in line leave the queue before being served. Moreover, customers who visit the facility during the repair avoid entering the facility. The problem is first formulated as a mixed-integer nonlinear programming (MINLP) model, for which two piecewise mixed-integer... 

In this letter, we consider the problem of blind source separation under certain nonlinear mixing conditions using a deep learning approach. Conventionally, the separation of sources within linear mixtures is achieved by applying the independence property of the sources. In the nonlinear regime, however, this property is no longer sufficient. In this letter, we consider nonlinear mixing operators where the non-linearity could be fairly approximated using a Taylor series. Next, for solving the nonlinear BSS problem, we design an end-to-end recurrent neural network (RNN) that learns the inverse of the system, and ultimately separates the sources. For training the RNN, we employ a set of... 

Various challenging pollutants are produced in the environment by organic materials of diverse industries including leather, paint, and textile. Nowadays, it is vital to develop efficient manners regarding the fundamental issues and removing pollutants. Such pollutants can be effectively removed from the environment through heterogeneous catalysts. Recently, a huge deal of interest has been attracted by hydrogel-based metal catalysts as heterogeneous and efficient catalysts. In this regard, silver with its unique features is suitable for environmental remediation. Hence, the present review deals with summarizing the present advances in the synthesis of silver-based hydrogel catalysts, as... 

Despite complex fluctuations, missing data, and maintenance costs of detectors, traffic volume forecasting at intersections is still a challenge. Moreover, most existing forecasting methods consider an isolated intersection instead of multiple adjacent ones. By accurately forecasting the volume of short-term traffic, a low-cost method can be provided to solve the problems of congestion, delay, and breakdown of detectors in the road transport system. This paper outlines a novel hybrid method based on deep learning to estimate short-term traffic volume at three adjacent intersections. The gated recurrent unit (GRU) and long short-term memory (LSTM) bilayer network with wavelet transform (WL)... 

A reaction-diffusion equation on [0, 1]d with the heat conductivity k > 0, a polynomial drift term and an additive noise, fractional in time with H > 1/2, and colored in space, is considered. We have shown the existence, uniqueness and uniform boundedness of solution with respect to k Also we show that if k tends to infinity, then the corresponding solutions of the equation converge to a process satisfying a stochastic ordinary differential equation  

Ring rolling is one of the most significant methods for producing rings with highly precise dimensions and superior qualities such as high strength uniformity, all accomplished without wasting any materials. In this article, we have achieved analytical formulas for calculating the pressure and shear friction over the contact arcs between the rollers and ring in the ring rolling process for the material in general nonlinear hardening property. We have also asserted the best mathematical model to predict friction for rolling processes. The method we use is based on calculating the analytical stress distribution. In other words, by using of Saint-Venan principal the stress components are... 

In this paper, the design of an efficient sparse array, used to reconstruct the image from millimeter-wave signals, is presented. The proposed array takes advantage of the sparsity concept of the image in the spatial Fourier domain to reduce the number of array elements such that the beam pattern of the designed array meets the desired beamwidth and sidelobe level. Simulation and measured results confirm the effectiveness of the proposed design on high-quality reconstruction of the image, while 85% reduction in the number of elements is achieved as well as the reduction in scan time and system complexity  

Real-world image classification, which aims to determine the semantic class of un-labeled images, is a challenging task. In this paper, we focus on two challenges of image classification and propose a method to address both of them simultaneously. The first challenge is that representing images by heterogeneous features, such as color, shape and texture, helps to provide better classification accuracy. The second challenge comes from dissimilarities in the visual appearance of images from the same class (intra class variance) and similarities between images from different classes (inter class relationship). In addition to these two challenges, we should note that the feature space of... 

The goal of this paper is to reduce the antenna count in a millimeter (mm)-wave imaging system by proposing both hardware and software solutions. The concept of image sparsity in the transform domain is utilized to present the compressive sensing (CS) formulation for both mono-static and multistatic imaging at mm-wave frequencies. To reduce the complexity of the imaging system and reconstruction process, we introduce 1.5-D array structure, which is a random sparse array with orthogonal element locations. It is shown that the peak signal-to-noise ratio (PSNR) of the reconstructed image obtained by a 1.5-D array with 65% sparsity is very close to the PSNR of a uniform 2-D array for mono-static... 

In this paper, effect of penicillin addition in enhancing the secretion of glutamic acid by Corynebacterium glutamicum was studied. The proper time of adding penicillin to maximize glutamic acid production was found to drift at repeated trials. In contrast, maximum acid productivity was obtained when penicillin was injected at a proper biomass concentration of about 7.7 gram dry weight per lit (gdw/l). Moreover, rate of consumption of sugar and ammonia through the course of glutamic acid fermentation was monitored. In production phase, these two rates were correlated properly with a ratio of 3.2:1 which is comparable to the theoretical stoichiometric value of 5:1. Therefore, through feeding...