Sharif Digital Repository

In this paper, we introduce a new Multi-Objective Genetic Algorithm (MOGA) for mapping a given set of intellectual property onto a Network-on-Chip architecture such that for a specific application total communication cost and energy consumption become optimized while bandwidth constraints are satisfied. As the main theoretical contribution, we first introduce a generic queuing model to estimate performance and an experimental energy consumption model during the design phase, with acceptable accuracy. Then, an efficient genetic algorithm employs these models to propose a Pareto optimal front for an application and an arbitrary topology. Experimental results show that the proposed algorithm is... 

Linear programming problems with trapezoidal fuzzy variables (FVLP) have recently attracted some interest. Some methods have been developed for solving these problems by introducing and solving certain auxiliary problems. Here, we apply a linear ranking function to order trapezoidal fuzzy numbers. Then, we establish the dual problem of the linear programming problem with trapezoidal fuzzy variables and hence deduce some duality results. In particular, we prove that the auxiliary problem is indeed the dual of the FVLP problem. Having established the dual problem, the results will then follow as natural extensions of duality results for linear programming problems with crisp data. Finally,... 

We explore some duality properties in fuzzy number linear programming problems. By use of a linear ranking function we introduce the dual of fuzzy number linear programming primal problems. We then present several duality results. © 2006 Elsevier Inc. All rights reserved  

Recently, fuzzy variable linear programming problems have attracted some interests. We introduce the dual of fuzzy variable linear programming problem, and then deduce some important duality results. COPYRIGHT © ENFORMATIKA  

Deep Neural Networks (DNNs) are very resource-demanding at inference time. Hence, one needs to be able to offload the model execution on the cloud as a solution. The problem is that we should use the same model on both resource-constrained devices and cloud sides. On the other hand, adversarial robustness is one of the main issues in many real-world applications, such as autonomous driving, where one desires model stability under imperceptible but adversarial input perturbations. However, adversarial training (AT) requires access to the actual model architecture and weights during the training. In our setup, two different deep models (suitable for each side) are broken into several blocks.... 

In this research, we will use an accelerator for MD simulations, called Atomic Approximation Method, which leads to more efficient simulations without harming the physical properties in simulations. The main idea of this method is to define a virtual material with lower number of atoms, which has the same physical properties as the original material. To demonstrate the validity of the proposed technique the modal analysis results are compared with the ones of the conventional molecular dynamics method. It is shown that this method accelerates conventional MD simulations significantly. Copyright © 2006 by ASME  

In this study, the impacts of salinity, ion type, and aging process were investigated on coalescence and spreading of crude oil interfaces (including an oil droplet and an oil film) under gravity, through drop rest time measurement techniques, aided by an image analysis system. Three different salt solutions of NaCl, Na2SO4, and MgCl2 were studied at different ionic strengths, ranged from 1% to 150% of Persian Gulf seawater ionic strength. According to the results, aging the oil droplet in the brine increased the interfacial rigidity. Addition of a gas phase - by thinning the surface oil film - almost doubled both rest time and spreading time values. In the aged mode, the presence of salt in... 

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... 

The trade-off between the fuel consumption and drag coefficient makes the investigations of drag reduction of utmost importance. In this paper, the rear-end shape optimization of Ahmed body is performed. Before changing the geometry, to identify the suitable simulation method and validate it, the standard Ahmed body is simulated using k − ω shear stress transport (SST) and k-epsilon turbulence models. The slant angle, rear box angle, and rear box length as variables were optimized simultaneously. Optimizations conducted by genetic algorithm (GA) and particle swarm optimization (PSO) methods indicate a 26.3% decrease in the drag coefficient. To ensure the validity of the results, a... 

The trade-off between the fuel consumption and drag coefficient makes the investigations of drag reduction of utmost importance. In this paper, the rear-end shape optimization of Ahmed body is performed. Before changing the geometry, to identify the suitable simulation method and validate it, the standard Ahmed body is simulated using k − ω shear stress transport (SST) and k-epsilon turbulence models. The slant angle, rear box angle, and rear box length as variables were optimized simultaneously. Optimizations conducted by genetic algorithm (GA) and particle swarm optimization (PSO) methods indicate a 26.3% decrease in the drag coefficient. To ensure the validity of the results, a... 

The trade-off between the fuel consumption and drag coefficient makes the investigations of drag reduction of utmost importance. In this paper, the rear-end shape optimization of Ahmed body is performed. Before changing the geometry, to identify the suitable simulation method and validate it, the standard Ahmed body is simulated using k − ω shear stress transport (SST) and k-epsilon turbulence models. The slant angle, rear box angle, and rear box length as variables were optimized simultaneously. Optimizations conducted by genetic algorithm (GA) and particle swarm optimization (PSO) methods indicate a 26.3% decrease in the drag coefficient. To ensure the validity of the results, a... 

In this paper the effect of emittance on the relevant issues of the synchrotron radiation sources, optics and beamline design for two values of emittance, ex=3.278 and 0.937 nm.rad, suggested for the Iranian Light Source Facility lattice design, have been discussed. The effect of spot size and divergence of the electron beam, and strength of the bending magnet field, have been considered in the calculations. The results show that reducing of emittance, increases the brilliance of the undulator by factor 5, and decrease the foot print on the optical elements and spot size of photon beam on the sample by a factor of about 2  

Adaptation of Penicillium simplicissimum with different heavy metals present in a spent hydrocracking catalyst, as well as one-step, two-step, and spent medium bioleaching of the spent catalyst by the adapted fungus, was examined in batch cultures. Adaptation experiments with the single metal ions Ni, Mo, Fe, and W showed that the fungus could tolerate up to 1500. mg/L Ni, 8000. mg/L Mo, 3000. mg/L Fe, and 8000. mg/L W. In the presence of multi-metals, the fungus was able to tolerate up to 300. mg/L Ni, 200. mg/L Mo, 150. mg/L Fe and 2500. mg/L W. A total of 3% (w/v) spent catalyst generally gave the maximum extraction yields in the two-step bioleaching process (100% of W, 100% of Fe, 92.7%... 

Statistically based experimental designs were applied to screen and optimize the bioleaching of spent hydrocracking catalyst by Penicillium simplicissimum. Eleven factors were examined for their significance on bioleaching using a Plackett-Burman factorial design. Four significant variables (pulp density, sucrose, NaNO3, and yeast extract concentrations) were selected for the optimization studies. The combined effect of these variables on metal bioleaching was studied using a central composite design (CCD). Second-order polynomials were established to identify the relationship between the recovery percent of the metals and the four significant variables. The optimal values of the variables... 

The quantity of spent hydroprocessing catalysts discarded as solid wastes in the petroleum refining industries has increased remarkably due to a steady increase in the processing of heavier feedstock. The adaptation of Penecillum Simplicissimum BBRC1-20019 with different heavy metals present in spent hydrocracking catalysts was studied. Adaptation experiments with single metals showed that the fungus could tolerate ≤ 1500 mg/L Ni, 8000 mg/L Mo, 3000 mg/L Fe, and 8000 mg/L W. In the presence of a mixture of these metals, the fungus tolerated ≤ 300 mg/L Ni, 200 mg/L Mo, 150 mg/L Fe, and 2500 mg/L W. The presence of multi-metals acted cumulatively to enhance the toxic effect in the growth of... 

This study was designed to compare one-step, two-step and spent medium bioleaching of spent catalyst by adapted Penecillum simplicissimum in batch cultures. Penecillum simplicissimum which was adapted to heavy metal ions Ni, Mo, Fe, and W grew in the presence of up to 5 %w/v of spent catalyst in the medium. The main lixiviant in bioleaching was gluconic acid which was produced mainly in present and absence of spent catalyst. A total of 3 %w/v spent catalyst generally gave maximum extraction yields in two-step bioleaching process, which the amounts of leached metals were 100 % of W, 100 % of Fe, 92.7 % of Mo, 66.43 % of Ni, and 25 % of Al. The red pigment produced by fungus could also... 

Analysis of the multispectral remotely sensed images of the areas destroyed by an earthquake is proved to be a helpful tool for destruction assessments. The performance of such methods is highly dependant on the preprocess that registers the two shots before and after an event. In this paper, we propose a new fast and reliable change detection method for remotely sensed images and analyze its performance. The experimental results show the efficiency of the proposed algorithm. Copyright © 2006 Hindawi Publishing Corporation. All right reserved  

This paper presents a novel algorithm for matching image interest points. Potential interest points are identified by searching for local peaks in Difference-of-Gaussian (DoG) images. We refine and assign rotation, scale and location for each keypoint by using the SIFT algorithm. Pseudo log-polar sampling grid is then applied to properly scaled image patches around each keypoint, and a weighted adaptive lifting scheme transform is designed for each ring of the log-polar grid. The designed adaptive transform for a ring in the reference keypoint and the general non-adaptive transform are applied to the corresponding ring in a test keypoint. Similarity measure is calculated by comparing the... 

This paper presents a new algorithm for detecting user-selected objects in a sequence of images based on a new weighted adaptive lifting scheme transform. In our algorithm, we first select a set of coefficients as object features in the wavelet transform domain and then build an adaptive transform considering the selected features. The goal of the designed adaptive transform is to "vanish" the selected features as much as possible in the transform domain. After applying both non-adaptive and adaptive transforms to a given test image, the corresponding transform domain coefficients are compared for detecting the object of interest. We have verified our claim with experimental results on 1-D... 

This paper presents a new adaptive lifting scheme transform for detecting user-selected objects in a sequence of images. In our algorithm, we first select a set of object features in the wavelet transform domain and then build an adaptive transform by using the selected features. The adaptive transform is constructed based on adaptive prediction in a lifting scheme procedure. Adaptive prediction is performed such that, the large coefficients in the high-pass component of the non-adaptive transform vanishes in the high-pass component of the adaptive transform. Finally, both the non-adaptive and adaptive transforms are applied to a given test image and the transform domain coefficients are...