Sharif Digital Repository

This paper reports a polarization controllable and angle-insensitive perfect metamaterial absorber (PMA). The proposed PMA consists of periodically arranged asymmetric omega-shaped resonators made of metallic copper. The absorptivity was analyzed considering the microwave C-band from 4 GHz to 8 GHz. The proposed PMA shows an absorption peak with almost 100% absorptivity at 6.2 GHz. Also, wideband negative index of refraction is observed. Further, the absorber is inspected for the different rotation angles of the top metasurface (omega-shaped ring) along the optical axis, and obliquity of incidence angle for both TE and TM polarized waves. Moreover, surface electric field and surface current... 

This paper presents the influence of the severe shot peening process on the fatigue life of the laser-cladded Inconel 718 specimens which can be employed during refurbishment of components enduring high mechanical cyclic loads such as gas turbine components. In order to quantitatively evaluate the destructive effect of laser cladding on the fatigue endurance, fatigue tests are first performed on the as-received and laser-cladded specimens. Then, microstructural analysis by scanning electron microscope (SEM) is carried out to identify the root causes of the drawback of laser cladding. Moreover, by employing a comprehensive laser-cladding FE analysis considering cyclic plastic material... 

Mobility is one of the most challenging issues in mobile ad-hoc networks and has a significant impact on performance of network protocols. Different kinds of mobility models have been proposed to represent the movement pattern of mobile nodes in mobile ad-hoc networks. These models attempt to capture various mobility characteristics existing in real movement of mobile nodes. In this paper, a new framework called Fuzzy Mobility Analyzer has been proposed to evaluate mobility models. At first, our framework categorizes mobility models based on their mobility characteristics into five classes; subsequently it uses mobility metrics to capture the mobility and graph connectivity characteristics... 

Due to reliability and performance considerations, employing multiple software-defined networking (SDN) controllers is known as a promising technique in Wireless Sensor Networks (WSNs). Nevertheless, employing multiple controllers increases the inter-controller synchronization overhead. Therefore, optimal placement of SDN controllers to optimize the performance of a WSN, subject to the maximum number of controllers, determined based on the synchronization overhead, is a challenging research problem. In this paper, we first formulate this research problem as an optimization problem, then to address the optimization problem, we propose the Cuckoo Placement of Controllers (Cuckoo-PC) algorithm.... 

This work concerns the experimental investigation of surfactant alternating CO 2 injection in carbonate rocks. The core samples provided from a low-temperature fractured light oil reservoir, located in southwest Iran. The experiments were designed to observe the effect of CO 2-foam injection on gas mobility and oil recovery at different surfactant concentrations. The core samples were initially saturated with synthetic/field brine, 5,000 ppm, and then flooded with live oil to reach connate water saturation at reservoir condition, 115F and 1,700 psia. The commercial surfactant used was sodium lauryl sulfate as an anionic surfactant. The results of this work, along with field-scale simulation... 

This paper presents a new Compressive Sensing (CS) scheme for detecting network congested links. We focus on decreasing the required number of measurements to detect all congested links in the context of network tomography. We have expanded the LASSO objective function by adding a new term corresponding to the prior knowledge based on the relationship between the congested links and the corresponding link Betweenness Centrality (BC). The accuracy of the proposed model is verified by simulations on two real datasets. The results demonstrate that our model outperformed the state-of-the-art CS based method with significant improvements in terms of F-Score  

In this paper, we study the problem of simulating a DMC channel from another DMC channel. We assume that the input to the channel we are simulating is i.i.d. and that the transmitter and receivers are provided with common randomness at limited rates. We prove bounds for simulating point-to-point, MAC and broadcast channels. As a special case, we recover the achievability part of the result of Cuff for point-to-point channel simulation via a noiseless link and shared randomness  

An experimental investigation of the flow field of pressure swirl atomizers for different pressure drops is performed. Two experimental methods are employed. For low injection pressures, a visual study is conducted while for higher pressures the velocity components and size of the droplets are measured by using Phase Doppler Anemometer. The spray formation, spray cone angle, and breakup length are visually investigated. Velocity and size of the droplets are measured on a plane of measurement along the axis of the spray so that the properties are carried out in a radial direction as a function of both pressure drop and axial distance from the nozzle. Self-similar mean axial velocity profiles... 

This paper presents the scheduling optimisation of cargo trains by hybrid computer simulation (CS) and genetic algorithm. Scheduling cargo trains is based on the timetable of passenger trains that have priority in relation to cargo trains. System modelling is accomplished by Visual SLAM by considering time limitations, queue priority and limited station lines. Time limitations define that a cargo train is permitted to travel from station i to j if scheduled passenger trains have completed the travel from station i to j. Queue priority means that passenger trains have priority over cargo trains. In addition, each station has a limited storage track. In addition, all repair, maintenance,... 

The depth of anesthesia quantification has been one of the most research interests in the field of EEG signal processing and nonlinear dynamical analysis has emerged as a novel method for the study of complex systems in the past few decades. In this investigation we use the concept of nonlinear time series analysis techniques to reconstruct the attractor of anesthesia from EEG signal which have been obtained from different hypnotic states during surgery to give a characterization of the dimensional complexity of EEG by Correlation Dimension estimation. The dimension of the anesthesia strange attractor can be thought of as a measure of the degrees of freedom or the 'complexity' of the... 

Consider an arbitrarily oriented ellipsoidal domain near the interface of an isotropic bimaterial space. It is assumed that a general class of piecewise nonuniform dilatational eigenstrain field is distributed within the ellipsoidal domain. Two theorems relevant to prediction of the nature of the induced displacement field for the interior and exterior points of the ellipsoidal domain are stated and proved. As a resultant the exact analytical expression of the elastic fields are obtained rigorously. In this work a new Eshelby-like tensor, A is introduced. In particular, the closed-form expressions for A associated with the interior points of spherical and cylindrical inclusion are derived.... 

The small-scale effect on the natural frequencies and buckling of pressurized nanotubes is investigated in this study. Based on the firstorder shear deformable shell theory, the nonlocal theory of elasticity is used to account for the small-scale effect and the governing equations of motion are obtained. Applying modal analysis technique and based on Galerkin's method a procedure is proposed to obtain natural frequencies of vibrations. For the case of nanotubes with simply supported boundary conditions, explicit expressions are obtained which establish the dependency of the natural frequencies and buckling loads of the nanotube on the small-scale parameter and natural frequencies obtained by... 

In this paper, several numerical simulations are performed to study the failure of epoxy adhesive joining composite plates. Different geometries for the joint and its edge are considered, and the effects of these geometries on the failure load are investigated. Moreover, the joints are subjected to different types of loading in order to determine the failure load. The failure theories of composite materials are implemented into the finite element software ABAQUS, and the failure propagation in the joint is studied. © 2020, Shiraz University  

A green precipitation method has been used for the synthesis of ultra-small APTMS-mPEG conjugated Mn3O4 nanoparticles. Spherical cores in the uniform size of 4±1 nm were characterized by HRTEM. Zeta potential of −45 mV and the invariant turbidimetry results during the time, confirmed super-stability of the colloids. MRI relaxometry by 1.5 T scanner represented two values of r1= 8.23 s−1mM−1 and r1=7.3 s−1mM−1 for diluted and concentrated samples. The r2/r1 ratio was also decreased from 11.86 to 6.9 by dilution of colloids. Particle aggregation and motional narrowing phenomena led to a dual T1/T2 contrast agent in the Mn ion concentrations of more than 0.2 mM. The optimum concentration of Mn... 

During recent years, active learning has evolved into a popular paradigm for utilizing user's feedback to improve accuracy of learning algorithms. Active learning works by selecting the most informative sample among unlabeled data and querying the label of that point from user. Many different methods such as uncertainty sampling and minimum risk sampling have been utilized to select the most informative sample in active learning. Although many active learning algorithms have been proposed so far, most of them work with binary or multi-class classification problems and therefore can not be applied to problems in which only samples from one class as well as a set of unlabeled data are... 

This study aims to elucidate the impact of salinity on the interactions governing the adsorption of polar aromatic oil compounds onto calcite. To this end, molecular dynamics simulations were employed to assess adsorption of a model polar organic molecule (deprotonated benzoic acid, benzoate) on the calcite surface in NaCl brines of different concentration levels, namely, deionized water (DW), low-salinity water (LS, 5000 ppm), and sea water (SW; 45,000 ppm). Calcite was found to be completely covered by several well-ordered water layers. The top hydration layer is very compact and prevents direct adsorption of benzoates onto the substrate. Instead, Na+ ions form a distinct positively... 

Many reservoir and production engineers face asphaltene precipitation as a major problem during miscible carbon dioxide flooding projects. Experimental studies regarding asphaltene precipitation are therefore employed to assist in selecting appropriate facilities and proper operation schemes. During this study, a series of high pressure, high temperature experiments are designed and performed to analyze asphaltene precipitation behavior of an Iranian light reservoir crude at reservoir conditions due to natural production and miscible CO2 gas injection. For both sets of experiments, two different temperature levels (including reservoir temperature) are selected to investigate the role of... 

In this paper, we address the problem of data description using a Bayesian framework. The goal of data description is to draw a boundary around objects of a certain class of interest to discriminate that class from the rest of the feature space. Data description is also known as one-class learning and has a wide range of applications. The proposed approach uses a Bayesian framework to precisely compute the class boundary and therefore can utilize domain information in form of prior knowledge in the framework. It can also operate in the kernel space and therefore recognize arbitrary boundary shapes. Moreover, the proposed method can utilize unlabeled data in order to improve accuracy of... 

This paper introduces adaptive consensus, a spatio-temporal adaptive method to improve convergence behavior of the current consensus fusion schemes. This is achieved by introducing a time adaptive weighting method for updating each sensor data in each iteration. Adaptive consensus method will improve node convergence rate, average convergence rate and the variance of error over the network. A mathematical formulation of the method according to the adaptive filter theory as well as derivation of the time adaptive weights and convergence conditions are presented. The analytical results are verified by simulation as well. ©2006 IEEE