Linear principal transformation: toward locating features in N-dimensional image space

Projection Functions have been widely used for facial feature extraction and optical/handwritten character recognition due to their simplicity and efficiency. Because these transformations are not one-to-one, they may result in mapping distinct points into one point, and consequently losing detailed information. Here, we solve this problem by defining an N-dimensional space to represent a single image. Then, we propose a one-to-one transformation in this new image space. The proposed method, which we referred to as Linear Principal Transformation (LPT), utilizes Eigen analysis to extract the vector with the highest Eigenvalue. Afterwards, extrema in this vector were analyzed to extract the features of interest. In order to evaluate the proposed method, we performed two sets of experiments on facial feature extraction and optical character recognition in three different data sets. The results show that the proposed algorithm outperforms the observed algorithms in the paper and achieves accuracy from 1.4 % up to 14 %, while it has a comparable time complexity and efficiency.     

Efficient task scheduling for runtime reconfigurable systems

Recent research indicates the promising performance of employing reconfigurable systems to accelerate multimedia and communication applications. Nonetheless, they are yet to be widely adopted. One reason is the lack of efficient operating system support for these platforms. In this paper, we address the problem of runtime task scheduling as a main part of the operating systems. To do so, a new task replacement parameter, called Time-Improvement, is proposed for compiler assisted scheduling algorithms. In contrast with most related approach, we validate our approach using real application workload obtained from an application for multimedia test remotely taken by students. The proposed online task scheduling algorithm outperforms previous algorithms and accelerates task execution from 4% up to 20%.     

Application of artificial neural network for vapor liquid equilibrium calculation of ternary system including ionic liquid: Water, ethanol and 1-butyl-3-methylimidazolium acetate

A feed forward three-layer artificial neural network (ANN) model was developed for VLE prediction of ternary systems including ionic liquid (IL) (water+ethanol+1-butyl-3- methyl-imidazolium acetate), in a relatively wide range of IL mass fractions up to 0.8, with the mole fractions of ethanol on IL-free basis fixed separately at 0.1, 0.2, 0.4, 0.6, 0.8, and 0.98. The output results of the ANN were the mole fraction of ethanol in vapor phase and the equilibrium temperature. The validity of the model was evaluated through a test data set, which were not employed in the training case of the network. The performance of the ANN model for estimating the mole fraction and temperature in the ternary system including IL was compared with the non-random-two-liquid (NRTL) and electrolyte non-random-two-liquid (eNRTL) models. The results of this comparison show that the ANN model has a superior performance in predicting the VLE of ternary systems including ionic liquid.     

An Optimization Model for the Increment in the Yield of Distillation Columns Based on Reverse Engineering in the Petroleum Industry

Abstract

Optimization in the chemical and petroleum industry is gaining increased interest because of its importance in maintaining product quality and enhancing production levels while improving profit margins. In this article, simulation of the atmospheric distillation unit of an existing petroleum refinery is carried out. Optimization was performed on the prepared simulation through the use of a sequential quadratic programming approach (SQP). The objective function consisted of energy minimization and production level maximization. The results obtained from optimization were implemented on the real process and it was demonstrated that the suggested changes increased overhead production levels and maintained product quality. Furthermore, a net economical balance between the increment of overhead products and the energy consumption showed an energy savings in the refinery.     

High-speed GPU implementation of a secret sharing scheme based on cellular automata

The Journal of Supercomputing - Parallel implementation provides a solution for the problem of accelerating cellular automata (CA)-based secret sharing schemes and make them appropriate for bulk...     

Ionic conduction and crystal structure of aluminum doped NASICON-type LiGe<Subscript>2</Subscript>(PO<Subscript>4</Subscript>)<Subscript>3</Subscript> glass-ceramic crystallized at different times and temperatures

In this communication, NASICON-type glass-ceramic (lithium germanium phosphate, LiGe₂(PO₄)₃) was prepared as lithium super ionic conductor using aluminum as dopant for ionic conduction improvement. The solid solution was Li_1?+?xAl_xGe_2-x(PO₄)₃ (x?=?0.5) that Ge⁴⁺ ions were partially substituted by Al³⁺ ions in crystal structure. Initial glasses were converted to glass-ceramics at different times and temperatures for maximum ionic conduction achievement. The crystals were characterized by X-ray Diffraction (XRD), Field Emission Scanning Electron Microscopy (FESEM), Energy-Dispersive X-ray spectroscopy (EDX), Differential Scanning Calorimetry (DSC) and Complex Impedance Spectroscopy (CIS) methods. The maximum lithium ion conductivity for glass-ceramic, 5.32?×?10^?3 S/cm at 26 °C was obtained for specimen crystallized at 850 °C for 8 h with minimum activation energy of 0.286 eV. Increasing the crystallization temperature results in secondary phase formation in grain boundary and increasing in crystallization time results in microcracks formation in specimen. Both phenomena decreased the ionic conductivity.     

Analytical solution of the parabolic and hyperbolic heat transfer equations with constant and transient heat flux conditions on skin tissue

In this article, the parabolic (Pennes bioheat equation) and hyperbolic (thermal wave) bioheat transfer models for constant, periodic and pulse train heat flux boundary conditions are solved analytically by applying the Laplace transform method for skin as a semi-infinite and finite domain. The bioheat transfer analysis with transient heat flux on skin tissue has only been studied by Pennes equation for a semi-infinite domain. For modeling heat transfer in short duration of an initial transient, or when the propagation speed of the thermal wave is finite, there are major differences between the results of parabolic and hyperbolic heat transfer equations. The non-Fourier bioheat transfer equation describes the thermal behavior in the biological tissues better than Fourier equation. The outcome of transient heat flux condition shows that by penetrating into the depths beneath the skin subjected to heat, the amplitude of temperature response decreases significantly. The blood perfusion rate can be predicted using the phase shift between the surface temperature and transient surface heat flux. The thermal damage of the skin is studied by applying both the parabolic and hyperbolic bioheat transfer equations.     

The Static and Dynamic Modeling of a Steam Methane Reforming Hydrogen Plant

Abstract

Actual hydrogen plant data consisting of temperatures and partial pressures of inlet and outlet gases of the reformer were collected over a five-year period. Subsequently a one-dimensional pseudohomogeneous reactor model comprising the Langmuir-Hinshelwood-Hougen-Watson reaction kinetic has been developed. Established intrinsic kinetic parameters from literature were used and the effect of intraparticle gradients was accounted for by incorporation of effectiveness factor. The validated model was used to predict the actual plant conversions and temperature profiles in the reformer tube. The steady-state one-dimensional pseudohomogeneous model was then extended to include the temporal variation of heat and mass transfer phenomena and then the dynamic response of the reformer under sudden disturbances in the feed conditions were studied.     

Clustering Persian viseme using phoneme subspace for developing visual speech application

There are numerous multimedia applications such as talking head, lip reading, lip synchronization, and computer assisted pronunciation training, which entices researchers to bring clustering and analyzing viseme into focus. With respect to the fact that clustering and analyzing visemes are language dependent process, we concentrated our research on Persian language, which indeed has suffered from the lack of such study. To this end, we proposed a novel adopting image-based approach which consists of four main steps including (a) extracting the lip region, (b) obtaining Eigenviseme of each phoneme considering coarticulation effect, (c) mapping each viseme into its subspace and other phonemes’ subspaces in order to create the distance matrix so as to calculate the distance between viseme’s cluster, and finally (d) comparing similarity of each viseme based on the weight value of reconstructed one. In order to indicate the robustness of the proposed algorithm, three sets of experiments were conducted on Persian and English databases in which Consonant/Vowel and Consonant/Vowel/Consonant syllables were examined. The results indicated that the proposed method outperformed the observed state-of-the-art algorithms in feature extraction, and it had a comparable efficiency in generating adequate clusters. Moreover, obtained results reached a milestone in grouping Persian visemes with respect to the perceptual test given by volunteers.     

Analytical Solution of Thermal Wave Models on Skin Tissue Under Arbitrary Periodic Boundary Conditions

Modeling and understanding the heat transfer in biological tissues is important in medical thermal therapeutic applications. The biothermomechanics of skin involves interdisciplinary features, such as bioheat transfer, biomechanics, and burn damage. The hyperbolic thermal wave model of bioheat transfer and the parabolic Pennes bioheat transfer equations with blood perfusion and metabolic heat generation are applied for the skin tissue as a finite and semi-infinite domain when the skin surface temperature is suddenly exposed to a source of an arbitrary periodic temperature. These equations are solved analytically by Laplace transform methods. The thermal wave model results indicate that a non-Fourier model has predicted the thermal behavior correctly, compared to that of previous experiments. The results of the thermal wave model show that when the first thermal wave moves from the first boundary, the temperature profiles for finite and semi-infinite domains of skin become separated for these phenomena; the discrepancy between these profiles is negligible. The accuracy of the obtained results is validated through comparisons with existing numerical results. The results demonstrate that the non-Fourier model is significant in describing the thermal behavior of skin tissue.