Sharif Digital Repository

In this paper, we address the problem of recovering degraded images using multivariate Gaussian mixture model (GMM) as a prior. The GMM framework in our method for image restoration is based on the assumption that the accumulation of similar patches in a neighborhood are derived from a multivariate Gaussian probability distribution with a specific covariance and mean. Previous methods of image restoration with GMM have not considered spatial (geometric) distance between patches in clustering. Our conducted experiments show that in the case of constraining Gaussian estimates into a finite-sized windows, the patch clusters are more likely to be derived from the estimated multivariate Gaussian... 

A mathematical model has been developed that is based the dual sorption in the dense layer and pore flow in the porous layer. In the porous layer a resistance model is applied where four mechanisms, i.e., Knudsen, Viscous, Slip, and Surface flows, are superimposed. Steady-state, constant pressure along the membrane and constant physical properties are assumed. Its application to the separation of H 2S/CH 4 gas mixtures as a sour gas in natural gas sweetening by using a PPO hollow fiber module is put forward. The Quasi Newton method is used to determine the parameters of membrane transport model for the case of H 2S/CH 4 separation. The H 2S and CH 4 permeances increased by increasing the... 

Recently, decellularized amniotic membrane-derived hydrogels (DAMHs) have received significant attention for wound care, ocular surface reconstruction, and chondral healing. Despite the advantages of DAMHs for tissue engineering (TE), the loss of structural components during the decellularization process mitigates their mechanical strength and thus limits their practical application. Herein, we present a method for the surface modification of two-dimensional nanosilicates (laponite) as a rheological modifier to tailor the properties of DAMHs. Results show that after introducing nanosilicates, severe aggregation of the nanoparticles occurs, owing to the shielding effect of ions on the surface... 

Recently, decellularized amniotic membranes (dAM) have attracted significant interest as a valuable source for the development of shear-thinning hydrogels and bioinks. However, the inferior rheological behavior and weak mechanical durability restrict the printability of the hydrogels and their stability after three-dimensional (3D) bioprinting. Therefore, a chemical or physical modification with biocompatible components is necessary to improve dAM-derived hydrogels’ properties. The present study proposes a strategy to fabricate printable dAM-derived hydrogels (DAMHs) supplemented with sodium alginate and Laponite nanoplatelets. Rheological experiments determined the key role of Laponite... 

In this paper we address the problem of image interpolation using Gaussian Mixture Models (GMM) as a prior. Previous methods of image restoration with GMM have not considered spatial (geometric) distance between patches in clustering, failing to fully exploit the coherency of nearby patches. The GMM framework in our method for image interpolation is based on the assumption that the accumulation of similar patches in a neighborhood are derived from a multivariate Gaussian probability distribution with a specific covariance and mean. An Expectation Maximization-like (EM-like) algorithm is used in order to determine patches in a cluster and restore them. The results show that our image... 

In this paper, we address the problem of dictionary learning for sparse representation. Considering the regularized form of the dictionary learning problem, we propose a method based on a homotopy approach, in which the regularization parameter is overall decreased along iterations. We estimate the value of the regularization parameter adaptively at each iteration based on the current value of the dictionary and the sparse coefficients, such that it preserves both sparse coefficients and dictionary optimality conditions. This value is, then, gradually decreased for the next iteration to follow a homotopy method. The results show that our method has faster implementation compared to recent... 

In this work, permeation of mixed gases H2S/CH4 through commercial polyphenylene oxide (PPO) hollow fiber and poly (ester urethane) urea (PEUU) flat membranes was studied at pressures of 345–689 kPa, at ambient temperature and at 313.15 K. Various H2S concentrations of about 100–5000 ppm in CH4 binary synthetic gas mixtures as well as a real natural gas sample obtained from a gas refinery containing 0.3360 mol.% H2S (equivalent to 3360 ppm) were tested. It was observed that the permeance of components was affected by the balance between competitive sorption and plasticization effects. Separation factors of H2S/CH4 were in the range of 1.3–2.9, 1.8–3.1 and 2.2–4.3 at pressures of 345, 517 and... 

In this communication, a hybrid model based on Least Square Support Vector Machine (LSSVM) was constructed to predict CO2 corrosion rate. The input parameters of the model are temperature, CO2 partial pressure, flow velocity and pH. The data used for training and testing of the developed model are 612 and 109 data, respectively. In order to benefit LSSVM from Kernel learning, we compared three kernel functions to select the most efficient one. Furthermore, Coupled Simulated Annealing (CSA) optimization technique was adapted to choose the best optimal values of the model parameters. The results elucidate that Gaussian Kernel functions is the desired function which can afford high accuracy for... 

The one-dimensional cutting stock problem has many applications in industries and during the past few years has been one of the centers of attention among the researchers in the field of applied operations research. In this paper, a revised version of Ant Colony Optimization (ACO) technique is presented to solve this problem. This paper is a sequel to the previous ACO algorithm presented by the authors. In this algorithm, according to some probabilistic rules, artificial ants will select cutting patterns and generate a feasible solution. Computational results show the high efficiency and accuracy of the proposed algorithm for solving one- dimensional cutting stock problem