Sharif Digital Repository

Several efforts have been performed to improve LBM defects related to its computational performance. In this work, a new algorithm has been introduced to reduce memory consumption. In the past, most LBM developers have not paid enough attention to retain LBM simplicity in their modified version, while it has been one of the main concerns in developing of the present algorithm. Note, there is also a deficiency in our new algorithm. Besides the memory reduction, because of high memory call back from the main memory, some computational efficiency reduction occurs. To overcome this difficulty, an optimization approach has been introduced, which has recovered this efficiency to the original... 

We describe several return code schemes for secure vote submission in electronic voting systems. We consider a unified treatment where a return code is generated as a multiparty computation of a secure MAC tag applied on an encrypted message submitted by a voter. Our proposals enjoy a great level of flexibility with respect to various usability, security, and performance tradeoffs. © 2017, Springer International Publishing AG  

In this paper, an analytical performance model for adaptive wormhole routing in the hypercube-based optical transpose interconnection system (OTIS-hypercube) is proposed and validated. Using this model, the performance merits of the OTIS-hypercube are discussed. We also compare the performance of the OTIS-hypercube with that of equivalent hypercube network under different implementation constraints. Compared to pure simulation results, the presented model can serve as a more appropriate and compact method to display the performance characteristics of OTIS-hypercube networks. © 2007 Elsevier Inc. All rights reserved  

Coupled continuous quadratic knapsack problems (CCK) are introduced in the present study. The solution of a CCK problem is equivalent to the projection of an arbitrary point onto the volume constrained Gibbs N-simplex, which has a wide range of applications in computational science and engineering. Three algorithms have been developed in the present study to solve large scale CCK problems. According to the numerical experiments of this study, the computational costs of presented algorithms scale linearly with the problem size, when it is sufficiently large. Moreover, they show competitive or even superior computational performance compared to the advanced QP solvers. The ease of... 

Fracture network modeling is a crucial step in development of hydrocarbon resources. For proposing development plan and design of stimulation operations fracture network should be known. This paper proposes a new improved simulated annealing algorithm for the problem of fracture network modeling. This algorithm improves computation performance without degrading solution quality so much by incorporating a method for estimation of the initial value of temperature-like parameter, using an adaptive Markov chain length (inner iterations) and suggesting a new fast and adaptive annealing schedule. Masihi et al. (2007) proposed an objective function for fracture network modeling based on mechanism... 

To perform active structural health monitoring, guided Lamb waves for damage detection have recently gained extensive attention. Many algorithms are used for damage detection with guided waves and among them, the delay-and-sum method is the most commonly used algorithm because of its robustness and simplicity. However, delay-and-sum images tend to have poor accuracy with a large spot size and a high noise floor, especially in the presence of multiple damages. To overcome these problems, another method that is based on sparse reconstruction can be used. Although the images produced by the sparse reconstruction method are superior to the conventional delay-and-sum method, it has the challenges... 

This paper presents a synthesis strategy for impact force localization and identification of framed structures in time-domain using a two-step wavelet-based fitness evaluation scheme in conjunction with genetic and water cycle algorithms. For this purpose, a straightforward approach is developed for sensitivity analysis of accelerations and spatial signal connecting the peak values. The proposed scheme is capable of using diverse scales of wavelet functions at considerably small sampling rates. A decimal genetic algorithm (GA) coding system and a recently developed water cycle algorithm (WCA) are improved to be used for impact localization and identification, respectively. The fitness... 

In this paper, numerical and experimental investigation of the performance and internal flow field characteristics of the twinentry radial inflow turbine under full and partial admission conditions are presented. The turbine is tested on a turbocharger test facility, which was developed for small and medium size turbochargers. The flow pattern in the volute and impeller of a twin-entry turbine is analyzed using fully three-dimensional viscous program. The computational performance results are compared with the experimental results, and good agreement is found. The flow field at the outlet of the turbine is investigated using a five-hole pressure probe. The tests are performed for both full... 

In this paper, a numerical and experimental investigation of the performance and internal flow field characteristics of the twin-entry radial inflow turbine under full and partial admission conditions are presented. The turbine is tested on a turbocharger test facility which was developed for small and medium size turbochargers. The flow pattern in the volute and impeller of a twin-entry turbine is analyzed using a fully three-dimensional viscous program. The computational performance results are compared with the experimental results, and good agreement is found. The flow field at the outlet of the turbine is investigated using a five-hole pressure probe. Numerical and experimental results... 

In this paper, Stochastic Activity Networks (SANs) are exploited to model and evaluate the power consumption and performance of virtualized servers in cloud computing. The proposed SAN models the physical servers in three different power consumption and provisioning delay modes, switching the status of the servers according to the workload of the corresponding cluster if required. The Dynamic Voltage and Frequency Scaling (DVFS) technique is considered in the proposed model for dynamically controlling the supply voltage and clock frequency of CPUs. Thus, Virtual Machines (VMs) on top a physical server can be divided into several power consumption and processing speed groups. According to the... 

This paper presents a mathematical model using Stochastic Activity Networks (SANs) to model a grid resource, and compute the throughput of a resource in servicing grid tasks, wherein the failure–repair behavior of the processors inside the resource is taken into account. The proposed SAN models the structural behavior of a grid resource and evaluates the combined performance and availability measure of the resource. Afterwards, the curve fitting technique is used to find a suitable function fitted to the throughput of a resource for grid tasks. Having this function and the size of each grid job based on its tasks, an algorithm is proposed to compute the makespan of each available resource to... 

Long and continuous running of software can cause software aging-induced errors and failures. Cloud data centers suffer from these kinds of failures when Virtual Machine Monitors (VMMs), which control the execution of Virtual Machines (VMs), age. Software rejuvenation is a proactive fault management technique that can prevent the occurrence of future failures by terminating VMMs, cleaning up their internal states, and restarting them. However, the appropriate time and type of VMM rejuvenation can affect performance, availability, and power consumption of a system. In this paper, an analytical model is proposed based on Stochastic Activity Networks for performance evaluation of... 

In this paper, dynamic programming alignment is replaced by a particle swarm optimization (PSO) procedure in time warping problem. The basic PSO is a very slow process to be applied to speech recognition application. In order to achieve a higher performance, by inspiring of PSO optimization methodology, we introduced a PSO Inspired Time warping Algorithm (PTW) that significantly increase the computational performance of time warping in alignments of long length massive data sets. As a main enhancement, a pruning strategy with an add-in controlling threshold is defined in PTW that causes a considerable reduction in recognition time, while maintaining the system accuracy comparing to DTW. ©... 

This paper presents numerical and experimental investigation of the performance and internal flow field characteristics of twin-entry radial inflow turbines at full and extreme partial admission conditions. The turbine is tested on a turbocharger test facility, which was developed for small and medium size turbochargers. Experimental results show that the lowest efficiency corresponds to extreme conditions. Therefore, flow field analyzing is employed to consider these conditions. The flow pattern in the volute and impeller of a twin-entry turbine is analyzed using an in-house fully three-dimensional viscous flow solver. The computational performance results are compared with the experimental... 

The main scope of this study is to analyse muscle-driven forward dynamics simulation of stair locomotion to understand the functional differences of individual muscles during the movement. A static optimization was employed to minimize a performance criterion based on the muscle energy consumption to resolve muscle redundancy during forward dynamics simulation. The proposed method was employed to simulate a musculoskeletal system with ten degrees of freedom in the sagittal plane and containing 18 Hill-type musculotendon actuators per leg. Simulation results illustrated that simulated joint kinematics closely tracked experimental quantities with root-mean-squared errors less than 1°. In...