Sharif Digital Repository

Weighting elements to achieve radiation patterns with desired characteristics is a classical work in phased array antennas. These characteristics can be low sidelobe level, narrow beamwidth, high directivity, pattern nulling in special angle and etc. For each of these characteristics, different methods have been introduced. Most of methods have been presented for uniform arrays, however there are lots of methods to obtain a desired pattern for antennas with non-uniform element distances. The problem with these methods is complexity or not very good results. In this paper, fast and easy methods based on Least Square Error that leads to good results are presented. In addition, weighting of... 

The potentials of partial least squares regression (PLSR) and multivariate curve resolution alternating least squares (MCR-ALS) are evaluated for the simultaneous determination of diclofenac (DCF), naproxen (NAP), mefenamic acid (MEF) and carbamazepine (CBZ) as target analytes and gemfibrozil (GEM) as an interference in synthetic and real environmental samples. The analysis of first-order UV-Vis spectra is performed using PLSR with different variable selection methods, which include variable importance in projection (VIP), recursive weighted partial least squares (rPLS), regression coefficient (RV) and uninformative variable elimination (UVE), and using MCR-ALS with correlation constraint... 

There are, to date, few general answers to fundamental questions related to the interactions of nanoparticles (NPs) with living cells. Studies reported in the literature have delivered only limited principles about the nano-bio interface and thus the biological behavior of NPs is yet far from being completely understood. Combining computational tools with experimental approaches in this regard helps to precisely probe the nano-bio interface and allows the development of predictive and descriptive relationships between the structure and the activity of nanomaterials. In the present contribution, a nano-quantitative structure-activity relationship (nano-QSAR) model has been statistically... 

Recently, there has been a growing interest in estimation of sparse channels as they are observed in underwater acoustic and ultrawideband channels. In this paper we present a new Bayesian sparse channel estimation (SCE) algorithm that, unlike traditional SCE methods, exploits noise statistical information to improve the estimates. The proposed method uses approximate maximum a posteriori probability (MAP) to detect the non-zero channel tap locations while least square estimation is used to determine the values of the channel taps. Computer simulations shows that the proposed algorithm outperforms the existing algorithms in terms of normalized mean squared error (NMSE) and approaches... 

In this study, N-way partial least squares (NPLS) is proposed to correlate comprehensive two-dimensional gas chromatography-time of flight mass spectrometry (GC×GCTOFMS) data of different aromatic oil fractions (fresh and weathered) to their toxicity values. Before NPLS modeling, since drift and wander of baseline interfere with information of sought analytes in GC×GC-TOFMS data, a novel method called two-dimensional asymmetric least squares is thus developed for comprehensive correction of the baseline contributions in both chromatographic dimensions. The algorithmis termed comprehensive because it functions to correct the entire chromatogram in both dimensions and it preserves the... 

The problem of estimating a sparse channel, i.e. a channel with a few non-zero taps, appears in many fields of communication including acoustic underwater or wireless transmissions. In this paper, we have developed an algorithm based on Iterative Alternating Minimization technique which iteratively detects the location and the value of the channel taps. In fact, at each iteration we use an approximate Maximum A posteriori Probability (MAP) scheme for detection of the taps, while a least square method is used for estimating the values of the taps at each iteration. For approximate MAP detection, we have proposed three different methods leading to three variants for our algorithm. Finally, we... 

An extension to conventional Hidden Markov Model (HMM)-based speech enhancement method is developed. An algebraic method is proposed to estimate gain of speech and noise in order to improve the quality of the estimated speech. Different pronunciations and intonations may affect speech gain. Besides, gain of noise may vary remarkably from one environment to the other one. This may lead in a mismatch between energy contour of trained models and energy contour of noisy speech signal. In this work, speech gain and noise gain are estimated based on an algebraic method simultaneously in order to match gain of noisy speech and noisy model. To carry out this procedure an extension of least square... 

Load pay back effect is the excess of load as a result of load curtailment, observed in direct load control programs related to thermostatically controlled appliances. In this paper, according to a stochastic difference equation, the load profile of an aggregation of customers without control will be attained. Then the assumption to consider load pay back as linear will be examined through simulations. Afterwards, based on a data structure gained from performing load curtailments at each interval, least-square method will be used to fit load pay back factors for each interval. It is notable that there are some significant differences between the results attained in this paper and what was... 

The present contribution is devoted to develop multivariate analytical figures of merit (AFOMs) as a new metric for evaluation of quantitative measurements using comprehensive two-dimensional gas chromatography–mass spectrometry (GC × GC–MS). In this regard, new definition of sensitivity (SEN) is extended to GC × GC–MS data and then, other multivariate AFOMs including analytical SEN (γ), selectivity (SEL) and limit of detection (LOD) are calculated. Also, two frequently used second- and third-order calibration algorithms of multivariate curve resolution-alternating least squares (MCR-ALS) as representative of multi-set methods and parallel factor analysis (PARAFAC) as representative of... 

In this article, two adaptive model predictive controllers (AMPC) are applied to regulate the blood glucose in type 1 diabetic patients. The first controller is constructed based on a linear model, while the second one is designed by using a nonlinear Hammerstein model. The adaptive version of these control schemes is considered to make them more robust against model mismatches and external disturbances. The least squares method with forgetting factor is used to update the model parameters. For simulation study, two well-known mathematical models namely, Puckett and Hovorka which describe the dynamical behavior of patient's body have been selected. The performances and robustness of the... 

Adopting the Navier slip conditions, we analyze the fully developed electroosmotic flow in hydrophobic microducts of general cross section under the Debye-Hückel approximation. The method of analysis includes series solutions which their coefficients are obtained by applying the wall boundary conditions using the least-squares matching method. Although the procedure is general enough to be applied to almost any arbitrary cross section, eight microgeometries including trapezoidal, double-trapezoidal, isosceles triangular, rhombic, elliptical, semi-elliptical, rectangular, and isotropically etched profiles are selected for presentation. We find that the flow rate is a linear increasing... 

This paper considers Pressure Oscillation (PO) experiments for which we find the minimum experiment time that guarantees user-imposed parameter variance upper bounds and honours actuator limits. The parameters permeability and porosity are estimated with a classical least-squares estimation method for which an expression of the covariance matrix of the estimates is calculated. This expression is used to tackle the optimization problem. We study the Dynamic Darcy Cell experiment set-up (Heller et al., 2002) and focus on data generation using square wave actuator signals, which, as we shall prove, deliver shorter experiment times than sinusoidal ones. Parameter identification is achieved using... 

Semi-analytical solutions are obtained for the electrical potential, electroosmotic velocity, ionic conductance, and surface physicochemical properties associated with long pH-regulated nanochannels of arbitrary but constant cross-sectional area. The effects of electric double layer overlap, multiple ionic species, and surface association/dissociation reactions are all taken into account, assuming low surface potentials. The method of analysis includes series solutions which the pertinent coefficients are obtained by applying the wall boundary conditions using either of the least-squares or point matching techniques. Although the procedure is general enough to be applied to almost any... 

Estimation of physical parameters of a parametrically excited gyroscope is studied in this paper. This estimation is possible by reading the input and output data of the gyroscope. Because of different faults in the manufacturing process and tolerances, physical parameters of a gyroscope are not exactly same as the expected values of the manufacturer. Moreover, changing of temperature, humidity, external acceleration, etc. can change the physical parameters of the gyro. Thus, the physical parameters of gyroscope are not fixed values and may deviate from the desired designed values. The physical parameters of gyroscope determine the optimal region for working of gyroscope. Thus, if the... 

This study proposes a novel non-invasive method for estimating the utility harmonic impedance. Since the major concern about non-invasive methods is the dependency of the accuracy of the results on background harmonic fluctuations, proper measured samples are selected using a three-point data selection technique to increase the method accuracy. Then, a new non-invasive method for the evaluation of the utility harmonic impedance at a point of common coupling (PCC) based on fuzzy logic is presented. In the proposed method, fuzzy logic is applied to the constrained recursive least squares algorithm (CRLS) by designing a set of fuzzy if-then rules. Due to the changes in the quantities at a... 

We report the design, fabrication and error analysis of a sun sensor array composed of six photodiodes. The sensor estimates the direction of the sun using a linear least squares method. The performance of the sensor is deteriorated by three major sources: fabrication errors, scattered environmental light, and inexact modeling of photodiodes. Using a calibration procedure and modeling the uniform component of the environmental light, we mitigate the first two errors and significantly reduce root mean squared error from 2.63° to 0.83°. For a Field of View (FOV) of 110°, the maximum estimation error also drops from 3.8° to 1.6°. Through exact mathematical modeling of photodiodes, we... 

As the ordinary least squares (OLS) method is very sensitive to outliers as well as to correlated responses, a robust coefficient estimation method is proposed in this paper for multi-response surfaces in multistage processes based on M-estimators. In this approach, experimental designs are used in which the intermediate response variables may act as covariates in the next stages. The performances of both the ordinary multivariate OLS and the proposed robust multi-response surface approach are analyzed and compared through extensive simulation experiments. Sum of the squared errors in estimating the regression coefficients reveals the efficiency of the proposed robust approach. © 2017 Taylor... 

The main goal of the current study is developing an advanced and robust numerical tool for accurate capturing heat front propagation. In some applications such as impermeable medium, Heat transfer in the surrounding domain of fracture acts just as a conduction process but the heat transfer through the fractures appears as a convection process. From a mathematical point of view, a parabolic partial differential equation (PDE) should be solved in the surrounding domain whereas a hyperbolic PDE should be solved in the domain of fractures. In fact, they have completely different treatments and this is one of the complicated problems in this area. In this paper, the presence of fractures and... 

Operational modal analysis based on power spectral density transmissibility functions (PSDT) is a powerful tool to identify the modal parameters with low sensitivity to excitations. The rotor systems may have the asymmetric damping or stiffness matrices which can lead to increase the difficulties of the identification procedure. In this paper, a new method is proposed to identify the modal parameters of the asymmetric rotary systems by the operational modal analysis based on the power spectral density transmissibility functions. For pole extraction from the PSDT function, a proper parametric identification method such as the Poly-reference Least Squares Complex Frequency-domain method... 

As the ordinary least squares (OLS) method is very sensitive to outliers as well as to correlated responses, a robust coefficient estimation method is proposed in this paper for multi-response surfaces in multistage processes based on M-estimators. In this approach, experimental designs are used in which the intermediate response variables may act as covariates in the next stages. The performances of both the ordinary multivariate OLS and the proposed robust multi-response surface approach are analyzed and compared through extensive simulation experiments. Sum of the squared errors in estimating the regression coefficients reveals the efficiency of the proposed robust approach. © 2018 Taylor...