Sharif Digital Repository

This letter proposes a dictionary learning algorithm for solving the grid mismatch problem in direction of arrival (DOA) estimation from both the array sensor data and from the sign of the array sensor data. Discretization of the grid in the sparsity-based DOA estimation algorithms is a problem, which leads to a bias error. To compensate this bias error, a dictionary learning technique is suggested, which is based on minimizing a suitable cost function. We also propose an algorithm for the estimation of DOA from the sign of the measurements. It extends the iterative method with adaptive thresholding algorithm to the 1-b compressed sensing framework. Simulation results show the effectiveness... 

With the increasing volume of data, the best approach for learning from this data is to exploit an online learning algorithm. Online ensemble methods take advantage of an ensemble of classifiers to predict labels of data. Prediction with expert advice is a well-studied problem in the online ensemble learning literature. The weighted majority and the randomized weighted majority (RWM) algorithms are two well-known solutions to this problem, aiming to converge to the best expert. Since among some expert, the best one does not necessarily have the minimum error in all regions of data space, defining specific regions and converging to the best expert in each of these regions will lead to a... 

For a moving camera recognizing that it has seen a place before now, is one the most important issues in the 3D reconstruction problems. In these problems, the main goal is to create a three-dimensional model from a sequence of 2D captured images during different times. That part of the scene which is rendered by a camera is often modeled by a frustum. Calculating the amount of intersection of two camera view frustums at different times can help to solve this problem. However, there are two major difficulties. First, calculating the intersection of two frustums, in general, is so complicated. And second, there are some uncertainties in the moving camera parameters over time. In this paper,... 

The problem of finding nearest neighbors in a certain distance is well defined in machine learning area. There are well-known and exact solutions for it. However, in real world problems, especially in machine vision area, where we have a moving sensor and we want to know which objects of the scene are in the measurement range of it, two issues are important. First, usually in these problems, the time cost is more important than accuracy. It means they can tolerate some measurements error if they can do the process in real-time. Second, the location of an object can be described in the three-dimensional space and does not require the higher dimensions. According to these issues, we introduced... 

This letter investigates the problem of threedimensional (3-D) target localization in multiple-input multipleoutput (MIMO) radars with distributed antennas, using hybrid timedelay (TD) and angle of arrival (AOA) measurements. We propose a closed-form positioning method based on weighted least squares (WLS) estimation. The proposed estimator is shown theoretically to achieve the Cramer-Rao lower bound (CRLB) under mild noise conditions. Numerical simulations also verify the theoretical developments. IEEE  

In this survey, firstly, a silicon wafer-based microchip, possessing a 50-cm microchannel with the dimensions of 120 and 60 μm, was manufactured by chemical etching technique. Subsequently, the inner surface of the microchannel was coated with a primary layer of gold nanoparticles synthesized by galvanic displacement. Then a self-assembled monolayer of 3-mercaptopropyltriethoxysilane was immobilized on the first layer. Eventually, a polydimethylsiloxane film with a thickness of 16 ± 1 μm was formed on the walls of the microchannel by means of sol-gel method. Field emission scanning electron microscopy and atomic force microscopy were extensively employed to investigate the status of both... 

In this letter, the problem of target localization from bistatic range (BR) measurements in distributed multiple-input multiple-output radar systems is investigated. By introducing nuisance parameters, a pseudolinear set of BR equations is established. Then, a closed-form localization algorithm is developed, based on this pseudolinear set of equations and multistage weighted least squares estimation. This solution is shown analytically to attain the Cramer-Rao lower bound under the small Gaussian noise assumption. Simulations are included to support the theoretical studies. Unlike the existing studies where the variance of BR measurements is assumed to be independent of the corresponding... 

In this study, the authors propose an algorithm to reduce the effect of antenna location uncertainty for locating moving targets in multiple-input multiple-output (MIMO) radar systems. The proposed method is a closed-form solution which employs the measurements of multiple independent targets to alleviate the antenna location uncertainties. The authors establish a pseudo-linear set of equations by using the range and the range-rate auxiliary parameters, which allows the problem to be solved using a two-stage weighted least squares estimator. The proposed method is shown analytically and confirmed by simulations to attain the Cramer-Rao lower bound under small error conditions. The... 

Numerical calculation of Value-at-Risk (VaR) for large-scale portfolios poses great challenges to financial institutions. The problem is even more daunting for large fixed-income portfolios as their underlying instruments have exposure to higher dimensions of risk factors. This article provides an efficient algorithm for calculating VaR using a historical grid-based approach with volatility updating and shows its efficiency in computational cost and accuracy. Our VaR computation algorithm is flexible and simple, while one can easily extend it to cover other nonlinear portfolios such as derivative portfolios on equities and FX securities. © 2022  

The behavior of a Jeffcott rotor with lateral-torsional coupling is investigated in the presence of internal and external damping and eccentricity. The governing equations are derived based on the Lagrange method. Also, the Laplace method and linearization is used to solve the governing equations for free vibrations analysis. For a rotor with unbalance, the instability occurs when the real part of eigenvalues has positive values, and at the same time, it is the intersection point between the lines of natural frequencies. The instability speed increases with increasing the external damping, yet dependent on the internal damping and unbalance. Also, it is demonstrated that the rotor critical... 

The behavior of a Jeffcott rotor with lateral-torsional coupling is investigated in the presence of internal and external damping and eccentricity. The governing equations are derived based on the Lagrange method. Also, the Laplace method and linearization is used to solve the governing equations for free vibrations analysis. For a rotor with unbalance, the instability occurs when the real part of eigenvalues has positive values, and at the same time, it is the intersection point between the lines of natural frequencies. The instability speed increases with increasing the external damping, yet dependent on the internal damping and unbalance. Also, it is demonstrated that the rotor critical... 

The main objective of this paper is to investigate the stability and stabilization problem of fuzzy large-scale systems in which the system is composed of a number of Takagi-Sugeno fuzzy subsystems with interconnection. Instead of fuzzy parallel distributed compensation (PDC) design, nonlinear state feedback controllers are used in stabilization of the overall large-scale system. Based on Lyapunov stability theory, linear matrix inequalities (LMIs) conditions are derived for asymptotic and exponential stability. Two numerical examples are given to confirm the analytical results and illustrate the effectiveness of the proposed strategy  

An investigation of the possible performance improvements of thin walled composite beams through the use of the variable stiffness concept with curvilinear fiber is presented. The beams are constructed from a single-cell closed cross section and a number of non-classical effects such as material anisotropy, transverse shear, warping inhibition and nonuniform torsional model are considered in the beam model. The governing equations were derived by means of the extended Hamilton's principle. Also the extended Galerkin's method is used to solve governing equations. Composite beams subjected to different loading with given geometry and material properties are optimized for maximum failure load.... 

In the present study the effect of nanodiamond (ND) on the adsorption capacity of Drug has been investigated. Thermal oxidation nanodiamond (OND) was used as adsorbents for Methotrexate adsorption. The surface properties of NDs were studied by Fourier transform infrared spectroscopy and zeta potential. It was determined that thermal oxidation changed the surface properties of ND, including increase the amount of carboxylic acid groups and decreasing the zeta potential of ND by increasing the thermal oxidation time. The adsorption experiments showed that untreated ND (UND) has large adsorption capacity and fast adsorption kinetic for methotrexate (MTX). These results suggest that the... 

Multigeneration systems (MGSs) driven by renewable sources are proved as cutting-edge technologies for multiple productions purposes to curb greenhouse gas emissions. With this regard, a novel geothermal-based MGS is proposed to produce multiple commodities of cooling, heating, power, and hydrogen, simultaneously, using liquefied natural gas (LNG) as cold energy recovery. The system is composed of an organic Rankine cycle (ORC), an ejector refrigeration cycle (ERC), an LNG power generation system, and a proton exchange membrane (PEM) electrolyzer system. To demonstrate the feasibility of the proposed MGS, energy, exergy, and exergoeconomic analysis are employed as the most effective tools... 

This paper presents a scalp electroencephalogram (EEG) rhythmic pattern detection scheme based on neural networks. Rhythmic discharges detection is applicable to the majority of seizures seen in newborns, and is listed as detecting 90% of all the seizures. In this approach some features based on various methods are extracted and compared by a modified multilayer neural network in order to find rhythmic discharges. Statistical performance comparison with seizure detection schemes of Gotman et al. and Liu et al. is performed. © 2006 IEEE  

A millimeter wave H-plane duplexer using E-plane filters has been designed. T-junction is used for connecting the channel filters compensated by cylindrical post and analyzed by integral contour method. Moreover the junction discontinuity effects have been taken into account. The combination of filters and compensated T-junction allows for low-cost manufacturing. The E-plane filters are analyzed separately, by mode matching method. The scattering parameters of the combination of filters and T-junction are obtained. The diameter and position of the compensating rod and length of T arms are optimized to achieve desired performance. This procedure saves time and memory in computations. The 38... 

Persian handwritten digit recognition has attracted some interests in the research community by introduction of large Hoda dataset. In this paper, the well-known random forest (RF) and convolutional neural network (CNN) algorithms are investigated for Persian handwritten digit recognition on the Hoda dataset. Using the Hoda dataset as a standard testbed, we have performed some experiments with different preprocessing steps, feature types, and baselines. It is then shown that RFs and CNNs perform competitively with the state-of-the-art methods on this dataset, while CNNs being the fastest if appropriate hardware is available  

Mud filtration happens during an overbalanced drilling operation that causes mud invasion into pores and fractures. The productivity of a formation is significantly affected by the invasion of the mud into the near-wellbore area during the mud loss process. A considerable number of studies have evaluated mud filtration statically; however, a few studies have considered the dynamic behavior of a mud loss process during overbalanced drilling, which results in the inadequate prediction of the mud loss volume and inflicted damage to the formation. In this study, a near-wellbore simulation system (NeWSS) was designed to evaluate the dynamic mud loss behavior using dimensionless parameters and... 

In this letter, we consider the problem of blind source separation under certain nonlinear mixing conditions using a deep learning approach. Conventionally, the separation of sources within linear mixtures is achieved by applying the independence property of the sources. In the nonlinear regime, however, this property is no longer sufficient. In this letter, we consider nonlinear mixing operators where the non-linearity could be fairly approximated using a Taylor series. Next, for solving the nonlinear BSS problem, we design an end-to-end recurrent neural network (RNN) that learns the inverse of the system, and ultimately separates the sources. For training the RNN, we employ a set of...