Sharif Digital Repository

In this study, optical technology is considered as SA issues' solution with the potential ability to increase the speed, overcome memory-limitation, reduce power consumption, and increase output accuracy. So we examine the effect of bio-data encoding and the creation of input images on the pattern-recognition error-rate at the output of optical Vander-lugt correlator. Moreover, we present a genetic algorithm-based coding approach, named as GAC, to minimize output noises of cross-correlating data. As a case study, we adopt the proposed coding approach within a correlation-based optical architecture for counting k-mers in a DNA string. As verified by the simulations on Salmonella whole-genome,... 

In this study, optical technology is considered as SA issues' solution with the potential ability to increase the speed, overcome memory-limitation, reduce power consumption, and increase output accuracy. So we examine the effect of bio-data encoding and the creation of input images on the pattern-recognition error-rate at the output of optical Vander-lugt correlator. Moreover, we present a genetic algorithm-based coding approach, named as GAC, to minimize output noises of cross-correlating data. As a case study, we adopt the proposed coding approach within a correlation-based optical architecture for counting k-mers in a DNA string. As verified by the simulations on Salmonella whole-genome,... 

Economic design of a control chart involves determining its basic parameters such that a cost function is minimized. This design when statistical performance measures are also considered is referred to as the economic-statistical design. In this paper, a simplex-based Nelder-Mead algorithm is used in combination with a particle swarm meta-heuristic procedure to solve both the economic and economic-statistical designs of a MEWMA control chart. The application results on extensive simulation experiments show that the particle swarm can lead the Nelder-Mead algorithm to better results. Furthermore, a comparative study is performed on the performances of three different algorithms of the... 

In this paper the performance characteristics of a turbocharger twin-entry radial inflow gas turbine with asymmetrical volute and rotor tip diameter of 73.6 mm in steady state and under full and partial admission conditions are investigated. The employed method is based on one dimensional performance prediction which is developed for partial admission conditions. Furthermore, this method is developed for the asymmetrical volute of the turbine considering the flow specifications. Experimental investigation of the research was carried out on special test facilities under full and partial admission conditions for a wide range of speeds. A comparison of experimental and modeling results shows... 

To mitigate environmental pollution and food contamination caused by inappropriate and excessive herbicide usage, most potent herbicides should be screened to control rice weeds. A research trial was executed for assessing the comparative efficacy of different herbicides to control rice field weeds and to evaluate the toxicity on rice under normal (distilled water) as well as different salinity levels (4 and 8 dS m-1). The study was designed to select the most potent herbicide and its appropriate dose for weed control of rice crop in coastal areas. Fourteen herbicidal treatments were included weed free crop, Pretilachlor (0.25, 0.50, 0.375 and 0.75 kg a.i. ha-1), Propanil + Thiobencarb (0.6... 

The current study is aimed at comparison of adsorption behaviors of silica-supported Cu nanoparticles (Si-N-Cu) and micrometric copper powder (Mi-Cu) for uptake of iodine vapor. The Si-N-Cu was synthesized by the decomposition of aqueous Cu(NO3)2 solution at supercritical condition, followed by reduction of the sample by H 2-N2 mixture. The Si-N-Cu sample with 29.4 nm Cu particles adsorbed 95% of I2 at partial pressure 10-5 bar in 1 h, while the 1 μm Mi-Cu adsorbed 51% of iodine in 6 h, indicating higher yield and faster kinetics of the nanometric sample. Theoretical analysis revealed the existence of a strong thermodynamic size effect in the Cu-I2 reaction system, so that molar |ΔG| for 2... 

This paper introduces a new procedure to forecast the future O/D demand. It is a hybrid of logit and Fratar model. The hybrid model has the long run, policy sensitive, characteristic of a logit model, calibrated at sector-level with little/no zero O/D cells. This feature, joint with a Fratar-type operation at zonal level within a sector, gives a better performance to this model than either of the two types of the models alone. The performance of the hybrid model is contrasted with a neural network model, and shows encouraging results in a real case  

In CHES 2008 a generic side-channel distinguisher, Mutual Information, has been introduced to be independent of the relation between measurements and leakages as well as between leakages and data processed. Assuming a Gaussian model for the side-channel leakages, correlation power analysis (CPA) is capable of revealing the secrets efficiently. The goal of this paper is to compare mutual information analysis (MIA) and CPA when leakage of the target device fits into a Gaussian assumption. We first theoretically examine why MIA can reveal the correct key guess amongst other hypotheses, and then compare it with CPA proofs. As our theoretical comparison confirms and shown recently in ACNS 2009... 

In this study, we have experimentally investigated the electrical properties of graphene and its derivatives (Exfoliated graphene, CVD synthesized graphene, graphene oxide and hydrogenated graphene oxide) under uniaxial strain. We have used gauge factor as a common representation of the sensitivity of the strain sensors and found that the hydrogenated graphene oxide shows significantly higher responsivity comparing to other samples under study. Reproducibility, reliability and lack of hysteresis in the responses of the graphene based samples make them a good candidate to be used in the strain sensors. © 2018  

A comparative study on the uptake properties of alginate microcapsules containing Cyanex 302 extractant, Lewatite TP 214 chelating resin, and Amberlite 200CT strongly acidic ion exchanger has been conducted using Ag+ as the target ion. The study resulted in an analytical formula, as well as three phenomenological breakthrough formulas that are also applicable in other fixed-bed operations. It also demonstrated a close similarity of the uptake properties of alginate microcapsules (MCs) and the chelating resins. Advantages of MCs over chelating resins include ease of preparation, ability to immobilize different extractants, and, most remarkably, an enormous distribution factor (Kd ≈ 106... 

An astigmatism compensated isosceles triangular ring resonator is designed and tested for a subjoule class Nd:YAG laser, considering the thermal lensing effects. The ABCD approach is used and the laser rod is considered as a lens like media whose optical power is induced by dissipated heat in the rod. The beam spot size, divergence angle, and some other parameters were studied for both sagittal and tangential planes and a minimal astigmatic configuration is designed applying dynamic stability condition. It is shown practically that the designed resonator emits a circular TEM00 Gaussian beam (using an aperture). Comparative studies were also done considering a linear resonator especially for... 

Three different controllers, i.e., active controller, nonlinear controller, and active sliding mode controller are designed and examined for the synchronization of pairs of three different chaotic systems, i.e., Chen, Lü, and Lorenz. The synchronizing methods are then compared from various point of views including synchronizing error variance, convergence time, control effort, maximum and minimum values of the control signal. Our results indicate that the nonlinear controller synchronizes pairs of the different chaotic systems generally better than two other controllers according to the defined criteria. © 2006 Elsevier B.V. All rights reserved  

By manipulating the phase map of a wavefront of light using a spatial light modulator, the scattered light can be sharply focused on a specific target. Several iterative optimization algorithms for obtaining the optimum phase map have been explored. However, there has not been a comparative study on the performance of these algorithms. In this paper, six optimization algorithms for wavefront shaping including continuous sequential, partitioning algorithm, transmission matrix estimation method, particle swarm optimization, genetic algorithm (GA), and simulated annealing (SA) are discussed and compared based on their efficiency when introduced with various measurement noise levels  

Determination of different facies in an underground reservoir with the aid of various applicable neural network methods can improve the reservoir modeling. Accordingly facies identification from well logs and cores data information is considered as the most prominent recent tasks of geological engineering. The aim of this study is to analyze and compare the five artificial neural networks (ANN) approaches with identification of various structures in a rock facies and evaluate their capability in contrast to the labor intensive conventional method. The selected networks considered are Backpropagation Neural Networks (BPNN), Radial Basis Function (RBF), Probabilistic Neural Networks (PNN),... 

In this paper, a high performance procedure for estimating of hydrodynamic coefficients in Autonomous Underwater Vehicles (AUV's) is proposed. In modeling of an AUV, experimental data should be verified and validated using appropriate techniques. Due to implementation complexity in calculating methods, computation of hydrodynamic parameters is challenging. This paper presents analytical approaches for estimating an AUV's hydrodynamic coefficients. Nonlinear Kalman Filter (KF) algorithms are implemented to estimate unknown augmented states (coefficients). A comparative study is conducted which shows the superior performance of Unscented Kalman Filter (UKF) in comparison with Extended Kalman... 

Determination of different facies in an underground reservoir with the aid of various applicable neural network methods can improve the reservoir modeling. Accordingly facies identification from well logs and cores data information is considered as the most prominent recent tasks of geological engineering. The aim of this study is to analyze and compare the five artificial neural networks (ANN) approaches with identification of various structures in a rock facies and evaluate their capability in contrast to the labor intensive conventional method. The selected networks considered are Backpropagation Neural Networks (BPNN), Radial Basis Function (RBF), Probabilistic Neural Networks (PNN),... 

In the present work, the interaction of hydrogen molecules with defective graphene structures doped by transition metal (TM) atoms is investigated by using first principles density functional theory (DFT). Defective graphene structures include Stone-Wales (SW), 585 and 555-777 and transition metals include early TMs, i.e. scandium (Sc), titanium (Ti) and vanadium (V). It is found that in comparison with the pristine graphene, presence of defects significantly enhances the metal binding. Among three defects, 585 divacancy leads to the strongest binding between graphene and metal. Hydrogen adsorption is then evaluated by sequential addition of hydrogen molecules to the system. The results... 

Decimal multiplication is a frequent operation with inherent complexity in implementation. Commercial and financial applications require working with decimal numbers while it has been shown that if we convert decimal number to binary ones, this will negatively influence the preciseness required for these applications. Existing research works on parallel decimal multipliers have mainly focused on latency and area as two major factors to be improved. However, energy/power consumption is another prominent issue in today's digital systems. While the energy consumption of parallel decimal multipliers has not been addressed in previous works, in this paper we present a comparative study of... 

An information system network (ISN) can be modeled as a stochastic-flow network (SFN). There are several algorithms to evaluate reliability of an SFN in terms of Minimal Cuts (MCs). The existing algorithms commonly first find all the upper boundary points (called d-MCs) in an SFN, and then determine the reliability of the network using some approaches such as inclusion-exclusion method, sum of disjoint products, etc. However, most of the algorithms have been compared via complexity results or through one or two benchmark networks. Thus, comparing those algorithms through random test problems can be desired. Here, the authors first state a simple improved algorithm. Then, by generating a... 

In this work, a comparative study of hybrid solar cells based on P3HT and TiO2 nanofibers was accomplished. Electrospinning, a low cost production method for large area nanofibrous films, was employed to fabricate the organic-inorganic hybrid solar cells based on poly (3-hexylthiophene) and TiO2 nanofibers. The performance of the hybrid solar cells was analyzed for four density levels of TiO2 nanofibers which resulted in the average power conversion efficiency of about 0.0134% under AM 1.5 simulated illuminations (100 mWcm-2). It is found that the higher densities of TiO2 lead to more interface area and generating exciton, so the power conversion efficiency will be increased till the active...