Sharif Digital Repository

The absorption characteristics of zirconium nitride (ZrN)-based metamaterial absorber of fractal geometry are studied. The proposed absorber is comprised of fractal metasurface at the top having subwavelength-sized periodic pattern of specially designed ZrN circular nano-discs arranged over silicon dioxide (SiO2) substrate. A tri-layer graphene, owing to its exhibiting better tunability, is introduced at the interface of metasurface and substrate. The bottom side of SiO2 is coated with silver nanolayer to block transmission. The absorptivity essentially depends on the kind of fractal design used in metasurface to configure the absorber. The obtained results exhibit the absorption... 

We consider the problem of corrupted radar super-resolution, a generalization of compressed radar super-resolution in which one aims to recover the continuous-valued delay-Doppler pairs of moving objects from a collection of corrupted and noisy measurements. The received signal in this type consists of contributions from objects, outlier and noise. While this problem is ill-posed in general, tractable recovery is possible when both the number of objects and corrupted measurements are limited. In this brief, we propose an atomic norm optimization in order to find the delay-Doppler pairs and the outlier signal. The objective function of our optimization problem encourages both sparsity in the... 

Edit distance is one of the most fundamental problems in combinatorial optimization to measure the similarity between strings. Ulam distance is a special case of edit distance where no character is allowed to appear more than once in a string. Recent developments have been very fruitful for obtaining fast and parallel algorithms for both edit distance and Ulam distance. In this work, we present an almost optimal MPC (massively parallel computation) algorithm for Ulam distance and improve MPC algorithms for edit distance. Our algorithm for Ulam distance is almost optimal in the sense that (1) the approximation factor of our algorithm is $1+epsilon$1+ϵ, (2) the round complexity of our... 

Dynamic analysis of problems with complex geometries requires utilization of numerical methods. To completely capture the effects of seismic wave propagation in a system, one must consider the structure or irregularity within its encompassing half-space. Correct consideration of half-space in a numerical model is important specially when it comes to cases where the half-space contains semi-infinite irregularities. In this study, a generalized numerical methodology is presented for dynamic analysis of a half-space with semi-infinite irregularities. The methodology is first verified through comparison with analytical solution of known problems. Then the method is employed to solve the dynamic... 

In recent years, extensive research in the field of Deep Learning (DL) has led to the development of a wide array of machine learning algorithms dedicated to solving complex tasks such as image classification or speech recognition. Due to their unprecedented ability to explore large volumes of data and extract meaningful hidden structures, DL models have naturally drawn attention from various fields in science. Analytical chemistry, in particular, has successfully benefited from the application of DL tools for extracting qualitative and quantitative information from high-dimensional and complex chemical measurements. This report provides introductory reading for understanding DL machinery... 

In this article, a novel cooperative secondary voltage/frequency control considering time-varying delays and noises in fading channels is presented for an autonomous alternating current (AC) voltage sourced-based converter (VSC)-based microgrid (MG), including inverter-interfaced distributed generations (DGs). Fading phenomenon makes complex random fluctuations on the voltage and frequency of every DG received from its neighbor DGs. In multi-agent cooperative systems, in addition to the total additive noise and time-variant delay, a multiplicative complex random variable is considered to model the main received signal and its replicas due to multipath propagation. The proposed... 

Cloud Manufacturing (CM) as a successful manufacturing business model and a major driver of Industry 4.0 has attracted a lot of attention in recent years. CM idea aims to streamline the on-demand provisioning of manufacturing resources and capabilities as services, providing end-users with flexible and scalable services accessible through global networks. This idea created many opportunities and challenges. One of the critical challenges is resource allocation, which determines who interacts with whom and how in the CM platform. The type of the platform is a determining factor for the selection of the appropriate resource allocation. To analyze the impact of the allocation on the utilities,... 

Accumulative roll bonded (ARBed) AA1050 and Al-2 vol% SiCp (AMC) samples were anodized in an H2SO4 electrolyte to improve corrosion resistance. The SEM images revealed that the anodic oxide's morphology is significantly dependent on the microstructure of the ARBed bare samples, owing to high internal energy that accelerates Al consumption during anodizing process. Potentiodynamic polarization measurements and EIS evaluation showed that anodic oxide improves the corrosion resistance of both ARBed AA and AMC samples; however, the electrochemical behavior of the processed samples changed due to the formation of a complex oxide structure comprising of twisted pore channels and attack routes. ©... 

This article presents a novel identification approach which can deal with nonlinear and time-varying characteristics of complex dynamic systems, especially an aerial vehicle in the entire flight envelope. A set of local sub-models are first developed at different operating points of the system, and subsequently a self-organizing multi-model ensemble is introduced to aggregate the outputs of the local models as a single model. The number of employed local models in the proposed multi-model ensemble is optimized using a novel self-organizing approach. Also, wavelet neural networks, which combine both the universal approximation property of neural networks and the wavelet decomposition... 

Human infertility is a multifactorial disease that affects 8%–12% of reproductive-aged couples worldwide. However, the genetic causes of human infertility are still poorly understood. Synaptonemal complex (SC) is a conserved tripartite structure that holds homologous chromosomes together and plays an indispensable role in the meiotic progression. Here, we identified three homozygous mutations in the SC coding gene C14orf39/SIX6OS1 in infertile individuals from different ethnic populations by whole-exome sequencing (WES). These mutations include a frameshift mutation (c.204_205del [p.His68Glnfs∗2]) from a consanguineous Pakistani family with two males suffering from non-obstructive... 

This paper presents fly-ability, trim-ability, stability, and control ability of a mono-wing aerial vehicle as an under-actuated multi-body system. A nonlinear mathematical model of this vehicle with translational and rotational movements is developed. Based on early simulations, a conceptual prototype of the mono-wing is initially designed and constructed. A comprehensive nonlinear simulation is then performed by modeling aerodynamic forces and moments using the Blade Element Momentum (BEM) theory. Modeling and simulation are validated against experimental data to satisfy research needs. Twenty-three efficient dynamic parameters of the mono-wing are studied in ninety-seven simulation... 

In Iranian Sign Language (ISL), alongside the movement of fingers/arms, the dynamic movement of lips is also essential to perform/recognize a sign completely and correctly. In a follow up of our previous studies in empowering the RASA social robot to interact with individuals with hearing problems via sign language, we have proposed two automated lip-reading systems based on DNN architectures, a CNN-LSTM and a 3D-CNN, on the robotic system to recognize OuluVS2 database words. In the first network, CNN was used to extract static features, and LSTM was used to model temporal dynamics. In the second one, a 3D-CNN network was used to extract appropriate visual and temporal features from the... 

This article focuses on analyzing the aliasing artifact in millimeter-wave imaging systems, with a special focus on multistatic arrays. The current framework to analyze the behavior of multistatic structures is based on the effective aperture concept. Based on this framework, an equivalent monostatic array, approximating the position of each transmitter-receiver pair by its midpoint, is used to quantify the response and efficiency of the system. Although this framework helps to simplify the study of the complex characteristics of multistatic arrays, it suffers from vital deficiencies. Especially, it fails to describe the aliasing artifacts, seen in the image of some sparse multistatic... 

In this letter, an efficient method for solving the multi-target localization problem in distributed MIMO radars is proposed. The proposed method attempts to simultaneously carry out the localization and data association tasks by formulating a mixed-integer optimization problem, which is approximated as a convex problem that can be efficiently solved with a polynomial complexity. Numerical simulations substantiate the efficacy of the proposed method. © 1997-2012 IEEE  

Autoregressive models are among the most successful neural network methods for estimating a distribution from a set of samples. However, these models, such as other neural methods, need large data sets to provide good estimations. We believe that knowing structural information about the data can improve their performance on small data sets. Masked autoencoder for distribution estimation (MADE) is a well-structured density estimator, which alters a simple autoencoder by setting a set of masks on its connections to satisfy the autoregressive condition. Nevertheless, this model does not benefit from extra information that we might know about the structure of the data. This information can... 

In [20] Kraj´ıˇcek and Pudl´ak discovered connections between problems in computational complexity and the lengths of first-order proofs of finite consistency statements. Later Pudl´ak [25] studied more statements that connect provability with computational complexity and conjectured that they are true. All these conjectures are at least as strong as P ̸= NP [23, 25, 24]. One of the problems concerning these conjectures is to find out how tightly they are connected with statements about computational complexity classes. Results of this kind had been proved in [20, 22]. In this paper, we generalize and strengthen these results. Another question that we address concerns the dependence between... 

In this work, a colorimetric sensor array has been designed for the identification and discrimination of thiometon (TM) and phosalone (PS) as organophosphate pesticides and prothioconazole (PC) as a triazole pesticide. For this purpose, two different plasmonic nanoparticles including unmodified gold nanoparticles (AuNPs) and unmodified silver nanoparticles (AgNPs) were used as sensing elements. The principle of the proposed strategy relied on the aggregation AuNPs and AgNPs through the cross-reactive interaction between the target pesticides and plasmonic nanoparticles. Therefore, these aggregation-induced UV–Vis spectra changes were utilized to discriminate the target pesticides with the... 

Capacitance-Resistive Model (CRM), as a fast yet efficient proxy model, suffers from some limitations in modeling relatively complex reservoirs. Some current improvements on this proxy made it a more powerful simulator with updating parameters over time. However, the model's intrinsic uncertainty arisen from simplifying fluid-flow modeling by some limited number of constant parameters is not addressed yet. In this study, this structural limitation of CRM has been addressed by introducing a time-correlated model error, including stochastic and non-stochastic parameters, embedded into this proxy's formulation. The error term's non-stochastic parameters have been tuned to be used in forecasting... 

Hand pose estimation is one of the most attractive research areas for image processing. Among the human body parts, hands are particularly important for human–machine interactions. The advent of commercial depth cameras along with the rapid growth of deep learning has made great progress in all image processing fields, especially in hand pose estimation. In this study, using depth data, we introduce two hybrid deep neural networks to estimate 3D hand poses with fewer computations and higher accuracy compared with their counterparts. Due to the fact that the dimensions of data are reduced while passing through successive layers of networks, which causes data to be lost, we use the concept of... 

A hydroelastic hybrid model is developed to simulate the fluid-structure interaction in water entry problems using the partitioned approach. The interactions between a flat plate and the water are modeled by a hydroelastic model using explicit and implicit couplings. Both couplings are unstable due to numerical instability associated with the fluid added mass. To overcome the instability, an extended Wagner's model is combined with the hydroelastic model, and a hybrid model is developed. The extended Wagner's model is the extension of the classical Wagner's model that is used to estimate the fluid inertial, damping, and restoring forces of a flexible plate within the potential flow theory....