Sharif Digital Repository

The so-called enriched weight functions (EWFs) are utilized in mesh-free methods (MMs) to solve linear elastic fracture mechanics (LEFM) problems; the following issues are of concern: convergence behavior; sufficiency of EWFs to capture singular fields around the crack-tip; and the preservation of the J-integral path-independency. EWFs prove useful in conjunction with the moving least square reproducing kernel method (MLSRKM); for this purpose, both EWFs and MLSRKM are modified. Since EWFs are not truly representative of the near-tip solution, fully EWFs (FEWFs) are introduced. Finally, some descriptive examples address the aforementioned concerns and the accuracy and efficacy of the... 

This is a theoretical study that extends a classical method of treating the convection heat transfer in complex geometries to gaseous slip flow forced convection in microchannels with H1 thermal boundary condition. Through this line, the momentum and energy equations in cylindrical coordinates are made dimensionless. Afterward, solutions are presented that exactly satisfy the dimensionless differential equations along with the symmetry condition and finiteness of the flow parameter at the origin. The first-order slip boundary conditions are then applied to the solution utilizing the least squares matching method. Though the method is general enough to be applied to almost any arbitrary cross... 

We first establish some necessary and sufficient conditions for solvability of fuzzy LR linear systems. We then propose a concept for an approximate solution when a fuzzy LR linear system lacks a solution. Recently, we have proposed an approximate solution for a fuzzy LR linear system under the condition that a corresponding crisp linear system was solvable. Here, we remove this condition by presenting a more general concept of an approximate solution based on a least squares model. We also develop the conditions for the uniqueness of the approximate solution. To compute an approximate solution, we propose an algorithm based on a quadratic programming model with bound constraints on some... 

This study presents a novel method for fault location of transmission lines by multiple fault current measurements. In contrast to conventional methods, it is proposed to utilise several current measurements, which may be far from the faulted line. The circuit equations of the network are used to express each fault current as a function of fault location. Fault location is then estimated using a least-squares estimation technique. To achieve a robust estimation of fault location, statistical hypotheses-testing is employed for identifying erroneous measurements. The method is applicable to both synchronised and unsynchronised measurements. Moreover, fault location can be estimated regardless... 

Response surfaces express the behavior of responses and can be used for both single and multi-response problems. A common approach to estimate a response surface using experimental results is the ordinary least squares (OLS) method. Since OLS is very sensitive to outliers, some robust approaches have been discussed in the literature. Although there are many methods available in the literature for multiple response optimizations, there are a few studies in model building especially robust models. Assuming correlated responses, in this paper, a robust coefficient estimation method is proposed for multi response problem based on M-estimators. In order to illustrate the performance of the... 

This study describes spectrometric monitored kinetic processes to determine the size of citrate-capped Au nanoparticles (Au NPs) based on aggregation induced by L-cysteine (L-Cys) as a molecular linker. The Au NPs association process is thoroughly dependent on pH, concentration and size of nanoparticles. Size dependency of aggregation inspirits to determine the average diameters of Au NPs. For this aim the procedure is achieved in aqueous medium at pH 7 (phosphate buffer), and multivariate data including kinetic spectra of Au NPs are collected during aggregation process. Subsequently partial least squares (PLS) modeling is carried out analyzing the obtained data. The model is built on the... 

Multivariate curve resolution-particle swarm optimization (MCR-PSO) algorithm is proposed to exploit pure chromatographic and spectroscopic information from multi-component hyphenated chromatographic signals. This new MCR method is based on rotation of mathematically unique PCA solutions into the chemically meaningful MCR solutions. To obtain a proper rotation matrix, an objective function based on non-fulfillment of constraints is defined and is optimized using particle swarm optimization (PSO) algorithm. Initial values of rotation matrix are calculated using local rank analysis and heuristic evolving latent projection (HELP) method. The ability of MCR-PSO in resolving the chromatographic... 

Conventional models of cardiovascular system frequently lack required detail and focus primarily on the overall relationship between pressure, flow and volume. This study proposes a localized and regional model of the cardiovascular system. It utilizes noninvasive blood flow and pressure seed data and temporal cardiac muscle regional activity to predict the operation of the heart under normal and congestive heart failure conditions. The analysis considers specific regions of the heart, namely, base, mid and apex of left ventricle. The proposed method of parameter estimation for hydraulic electric analogy model is recursive least squares algorithm. Based on simulation results and comparison... 

In the present study, a prediction model was derived for the effective angle of shearing resistance (φ′) of soils using a novel hybrid method coupling genetic programming (GP) and orthogonal least squares algorithm (OLS). The proposed nonlinear model relates φ′ to the basic soil physical properties. A comprehensive experimental database of consolidated-drained triaxial tests was used to develop the model. Traditional GP and least square regression analyses were performed to benchmark the GP/OLS model against classical approaches. Validity of the model was verified using a part of laboratory data that were not involved in the calibration process. The statistical measures of correlation... 

A new method for position determination of stationary targets from radio bearings, using triangulation, and based on the partial derivative analysis of bearing error has been proposed. Mathematical derivations have been carried out and a simulation illustrating the effectiveness of the method has been run. It turns out that, the method works best when the noise is excessively high and the traversed path is asymmetric. In such conditions, the method illustrates an error reduction of up to 5% with respect to the Least Square algorithm  

A method for two dimensional position finding of stationary targets whose bearing measurements suffers from indeterminable bias and random noise has been proposed. The algorithm uses convex optimization to minimize an error function which has been calculated based on circular as well as linear loci of error. Taking into account a number of observations, certain modifications have been applied to the initial crude method so as to arrive at a faster, more accurate method. Simulation results of the method illustrate up to 30% increase in accuracy compared with the well-known least square filter  

Conventional models of cardiovascular system (CV) frequently lack required detail. Once utilized to study the heart function, these models focus primarily on the overall relationship between pressure, flow and volume. This study proposes a localized and regional model of the CV system. It utilizes non-invasive blood flow and pressure seed data and temporal cardiac muscle regional activation to predict the operation of the heart. Proposed localized analysis considers specific regions of the heart, namely base, mid and apex sections of the left ventricle. This modular system is based on a hydraulic electric analogy model, estimating desired parameters, namely resistance (R), compliance (C),... 

In this article, we examine Independent Component Analysis (ICA) and the concept of Mutual information (MI) as a quantitative measure of independence from the point of view of analytical chemistry. We compare results obtained by different ICA methods with results obtained by Multivariate Curve Resolution Alternating Least Squares (MCR-ALS). These results have shown that, when non-negativity constraints are applied, values of MI increase considerably and the resolved components cannot anymore be considered to be independent (i.e. they can only be considered to be the " least dependent" components). MI values of profiles resolved by MCR-ALS and ICA did not differ significantly when... 

This paper proposes an enhanced illumination compensation algorithm, which can compensate for the uneven illuminations on human faces and reconstruct face images in normal lighting conditions. To detect the illumination category, based on 65 categories in YaleB database, the images processed using Block-based Histogram Equalization (BHE) is compared with the original face image processed using histogram equalization (HE). Based on the identified illumination category, a quadratic model is used to reconstruct an image that will visually be under normal illumination. In order to avoid the effect of light source intensity on face images, we used HE method. Experimental results show that, by... 

Analytical Jacobian, nonlinear least square and three layer artificial neural network models are employed to predict deformation of mouse embryos under needle injection, based on experimental data captured from literature. The Maximum Absolute Error (MAE), coefficient of determination ( R2), Relative Error of Prediction (REP), Root Mean Square Error of Prediction (RMSEP), NashSutcliffe coefficient of efficiency ( Ef) and accuracy factor ( Af) are used as the basis for comparison of these three models. Analytical Jacobian, nonlinear least square and ANN models have yielded the correlation coefficient of 0.9985, 0.9964 and 0.9998, respectively. The REP between the models predicted values and... 

In this paper, a low order recursive linear prediction method and recursive least square as an adaptive filter (LP-RLS) are introduced to predict the speech and the excitation signals. In real-time packet-based communication systems, one major problem is misrouted or delayed packets which results in degraded perceived voice quality. If packets are not available on time, the packet is known as lost packet. The easiest task of a network terminal receiver is to replace silence for the duration of lost speech segments. In a high quality communication system, to avoid quality reduction due to packet loss, a suitable method and/or algorithm is needed to replace the missing segments of speech. The... 

In real-time packet-based communication systems, one major problem is misrouted or delayed packets which results in degraded perceived voice quality. If packets are not available on time, the packet is known as lost packet. The easiest task of a network terminal receiver is to replace silence for the duration of lost speech segments. In a high quality communication system, to avoid quality reduction due to packet loss, a suitable method and/or algorithm is needed to replace the missing segments of speech. In this paper, we introduce a low order recursive linear prediction method for replacement of lost speech segment. In this method a normalized least mean square (NLMS) as an adaptive filter...