Sharif Digital Repository

The Weibull distribution plays an important role in failure distribution modeling of reliability research. While there are three parameters in the general form of this distribution, for simplicity, one of its parameters is usually omitted and as a result, the others are estimated easily. However, due to its more flexibility, when the general form of the Weibull distribution is of interest, the estimation procedure is not an easy task anymore. For example, in the maximum likelihood estimation method, the likelihood function that is formed for a three-parameter Weibull distribution is very hard to maximize. In this paper, a new hybrid methodology based on a variable neighborhood search and a... 

This paper introduces a novel approach for tuning the parameters of the adaptive network-based fuzzy inference system (ANFIS). In the commonly used training methods, the antecedent and consequent parameters of ANFIS are trained by gradient-based algorithms and recursive least square method, respectively. In this study, a new swarm-based meta-heuristic optimization algorithm, so-called "Cat Swarm Optimization", is used in order to train the antecedent part parameters and gradient descent algorithm is applied for training the consequent part parameters. Experimental results for prediction of Mackey-Glass model and identification of two nonlinear dynamic systems reveal that the performance of... 

Segmentation of the human airway tree from volumetric computed tomography images is an important stage for many clinical applications such as virtual bronchoscopy. The main challenges of previously developed methods are to deal with two problems namely, leaking into the surrounding lung parenchyma during segmentation and the need to manually adjust the parameters. To overcome these problems, a multi-seeded fuzzy based region growing approach in conjuction with the spatial information of voxels is proposed. Comparison with a commonly used region growing segmentation algorithm shows that the proposed method retrieves more accurate results by achieving the specificity and sensitivity of 98.81%... 

In this study, ensemble Kalman filter (EnKF) is first applied to estimate absolute and relative permeabilities jointly under three-phase flow condition in the porous media. By assimilating historical data, absolute permeability field is adjusted progressively towards its reference. However, assimilation process does not improve the estimation of all relative permeability parameters, and some of them are poorly estimated at the end of assimilation. To improve the estimation of the relative permeability curves, we propose a new hybrid approach in which the estimation process of the absolute and relative permeabilities is separated. In this approach, gridblock permeabilities are again estimated... 

One of the problems in Bayesian inference is the prior selection. We can categorize different methods for selecting prior into two main groups: informative and non-informative. Here, we have considered an informative method called filters random filed and minimax entropy (FRAME). Despite of its theoretical interest, that method introduces a huge amount of computational burden, which makes it very unsuitable for real-time applications. The main critical point of the method is its parameter estimation part, which plays a major role in its very low speed. In this paper, we have introduced a fast method for parameter estimation to fasten the FRAME approach. Although the kernel of our approach is... 

The use of human hand gestures as a natural interface tool has motivated researchers to conduct research in the modeling, analyzing and recognition of various hand movements. In particular, human computer intelligent interaction has been a focus for research in vision-based gesture recognition. In this work, we introduce a 3D hand model reconstruction method which offers flexible and elaborate representation of hand gestures. We used 20 landmarked points on tips and joints of the fingers and calculated the 3D coordinates of these points through a stereo vision system. Our results show that such reconstruction provides a precise 3D hand model only to be influenced by intrinsic and extrinsic... 

The huge availability of data in the last decade has raised the opportunity for the better use of data in decision-making processes. The idea of using the existing data to achieve a more coherent reality solution has led to a branch of optimization called data-driven optimization. On the one hand, the presence of uncertain variables in these datasets makes it crucial to design robust optimization methods in this area. On the other hand, in many real-world problems, the closed-form of the objective function is not available and a meta-model based framework is necessary. Motivated by the above points, in this paper a Gaussian process is used in a Bayesian optimization framework to design a... 

In this paper a nonlinear control method based on Lyapunov stability theorem is proposed to design an adaptive controller for synchronizing two different chaotic systems. It is assumed that the unknown parameters of the drive and the response chaotic systems are time varying. It is shown that the proposed scheme can identify the system parameters if the system parameters are time invariant and the richness conditions is satisfied. To demonstrate the effectiveness of the proposed technique it has been applied to Lorenz-Chen dynamic systems, as drive-response systems. Simulation results indicate that the proposed adaptive controller has a high performance in synchronizing two chaotic systems.... 

In most approaches to adaptive robust control design for manipulators, a constant upper bound is considered for unmodeled dynamics. However, experiments show that the nature of the control input affects the magnitude of the unmodeled dynamics. For example, in an almost rigid manipulator where the mechanical flexibilities are considered as unmodeled dynamics, high frequency components of the input torque which are resulted form non-smooth control laws, can themselves excite system flexibilities. In this paper, we consider different characterizations of the unmodeled dynamics to take into account the effect of control input signal on the unmodeled dynamics. Simulation results illustrate the... 

In this study, adaptive observer-based synchronization of chaotic systems is considered. The master and slaves systems have different dynamics and it is assumed that the master system parameters are unknown while its states are available. First, it is assumed that the slave system parameters are known but its states are not completely available. It is shown that an observer for the slave system can be designed and applied for the purpose of synchronization. Based on a Lyapunov function, an adaptive law for master parameters estimation and a control law for the synchronization goal are extracted. Stability of the entire system including the observer dynamics has been proved. Further, it is... 

Laser Powder Deposition technique is an advanced production method with many applications. Despite this fact, reliable and accurate control schemes have not yet fully developed for this method. This article presents method for in time identification of the process for modeling and adaptation of proper control strategy. ARMAX structure is chosen for system model. Recursive least square method and Kalman Filter methods are adopted for system identification, and their performance are compared. Experimental data was used for system identification, and proper filtering schemes are devised here for noise elimination and increased estimation results. It was concluded that although both methods... 

An integrated guidance and control (IGC) is designed in this study for a surface-to-air missile considering burned or broken fin as a fault. The IGC model in the pitch plane is developed with various uncertainties in the presence of fin failure. The considered fault may cause a change in the vehicle’s shape that leads to a change in aerodynamic coefficients and consequently in the model. To identify the new model, aerodynamic coefficients are estimated using an estimator and the result is sent to the controller. Then, an adaptive robust controller is designed using the combination of backstepping and sliding mode scheme to compensate fin failure and changes in the dynamic. The simulation... 

Proper modeling of the human arm dynamic, as it interacts with telemanipulation and haptic systems, is important in enhancing the transparency of these systems. In this article, we introduced an adaptive identifier to estimate the impedance characteristic of a human operator as it interacts with a single translational degree of freedom mechanism. The five parameter model, including an extra spring and damper for a better approximation of the dynamic behavior of human arm, has been used. Since the impedance characteristic of human arm differs from one individual to another, it is important to estimate these parameters for each individual and update the controller to enhance the transparency... 

The acoustical system of car was analyzed using finite element method (FEM) and identification of the system. The acoustical model of a vehicle was proposed and by using FEM modal analysis, acoustic modal analysis, structural modal analysis, and coupling modal analysis was performed successfully. The influence of the acoustic system on the driver ears to understand these effects were also shown. The methods and results can be applied to a vehicle design procedure for conformability of the human being when riding  

Sound in the interior cabin of cars has been of the great importance nowadays. The automotive industry has long been fiercely competitive with different vendors attempting to produce vehicles with better performance, handling and fuel efficiency. The competition of the automotive industries today is directed on the reduction of noise in the cars cabin. This paper proposes a new method for noise studies in the cabin, which frequencies of excitation are lower than 200 Hz. The topics, which are covered in the paper, include the computation of the structural and acoustic mode shapes, resonant frequencies of the passenger compartment, coupling between structure and acoustic effects, and forced... 

In many sensor fusion algorithms, the vision based RANdom Sample Consensus (RANSAC) method is used for estimating motion parameters for autonomous robots. Usually such algorithms estimate both translation and rotation parameters together which makes them inefficient solutions for merely rotation estimation purposes. This paper presents a novel 3-point RANSAC algorithm for estimating only the rotation parameters between two camera frames which can be utilized as a high rate source of information for a camera-IMU sensor fusion system. The main advantage of our proposed approach is that it performs less computations and requires fewer iterations for achieving the best result. Despite many... 

The fabrication of complex-shaped parts out of Co-Cr-Mo alloy and 316L stainless steel by three-dimensional printing (3DP) is studied using two grades of each alloy with average particle size of 20 and 75 nm, respectively. To produce sound specimens, the proper 3DP processing parameters were determined. The sintering behavior of the powders is characterized by dilatometric analysis and by batch sintering in argon atmosphere at 1280°C for 2h. The 3DP process has successfully produced complex-shaped biomedical parts with total porosity of 12-25% and homogenous pore structure, which is suitable for tissue growth into the pores  

The gravity currents on the inclined boundaries are formed when the inflow fluid has a density difference with the ambient fluid and a tangential component of gravity becomes the driving force. If the density difference arises from the suspension of particles, the currents are known as particle-driven density currents, in which the local density of the gravity current depends on the concentration of particles. A low Reynolds k-ε turbulence model is used to simulate three dimensional turbidity currents. Also a laboratory apparatus was built to study the 3D flow resulting from the release of particle laden density currents on a sloping surface in a channel of freshwater via a sluice gate and... 

This article presents the results of 2D and 3D simulations of a bubble column reactor at steady state conditions and low gas flow rates. The simulations have been done based on a two-fluid model with a k - ε model used for turbulence modeling. The experimental data have been obtained by differential pressure transducer. For analyzing of hydrodynamic parameters such as hold up and velocity profiles of phases, a system consists of water tank and air aerated from bottom is set up. The simulations have been done based on two different approaches which are mixture and eulerian approaches. Despite the fact that these approaches lead to similar results, the convergence and stability of eulerian... 

In this work, a modified free-volume (FV) model based on the UNIQUAC-Nonrandom factor (UNIQUAC-NRF) model developed by Haghtalab and Asadollahi was proposed. While the combinatorial part of the proposed model for activity coefficient takes the same form as that of the entropic free-volume (entropic-FV) model, the residual part is similar to that of the UNIQUAC-NRF model. The proposed model, i.e., the FV-UNIQUAC-NRF model overcomes the main shortcoming of the original UNIQUAC-NRF model in predicting the lower critical solution temperature (LCST) for polymer solutions. The appearance of the LCST is believed to be attributed to the existence of the free volume differences between polymer and...