Sharif Digital Repository

Precipitation of strontium sulfate (or SrSO4) has already been distinguished as one of the most costly and critical problems which may occur in process industries and oilfield operations. Costs due to scaling and remedial actions that need to be taken afterward are generally high owing to low solubility of SrSO4 in aqueous solutions. Therefore, a thorough understanding of the SrSO4 thermodynamic behavior under various operating conditions is vital to predict or even avoid the overall damage caused by scaling. The primary aim of this work is to develop a model based on Least Squares Support Vector Machine (LSSVM) and Coupled Simulated Annealing (CSA) referred to as CSA-LSSVM to predict... 

Deposition of barium sulfate (or BaSO4) has already been recognized as a devastating problem facing process industries and oilfield operations, mainly owing to its low solubility in aqueous solutions. Predicting and also preventing the overall damage caused by BaSO4 precipitation requires a profound knowledge of its solubility under different thermodynamic conditions. The main aim of this study is to develop a solubility prediction model based on a hybrid of least squares support vector nachines (LSSVM) and coupled simulated annealing (CSA) aiming to predict the solubility of barium sulfate over wide ranges of temperature, pressure and ionic compositions. Results indicate that predictions of... 

Early diagnosis of any disease at a lower cost is preferable. Automatic medical diagnosis classification tools reduce financial burden on health care systems. In medical diagnosis, patterns consist of observable symptoms and the results of diagnostic tests, which have various associated costs and risks. In this paper, we have experimented and suggested an automated pattern classification method for classifying four diseases into two classes. In the literature on machine learning or data mining, regression and classification problems are typically viewed as two distinct problems differentiated by continuous or categorical dependent variables. There are endeavors to use regression methods to... 

The existing methods in attitude control of satellites are based on using the estimate of satellite attitude, which is usually generated by using multiple vector measurements. In this paper we propose an output feedback controller that directly uses a single vector measurement and does not use an attitude estimator. The output feedback gain is computed by solving a generalized Riccati differential equation (GRDE). The existence of a solution to the GRDE depends on a uniform controllability condition  

In analyzing the lifetime properties of a coherent system, the concept of "signature" is a useful tool. Let T be the lifetime of a coherent system having n iid components. The signature of the system is a probability vector s=(s1, s2,., sn), such that s i=P(T=Xi:n), where, Xi:n, i=1, 2,., n denote the ordered lifetimes of the components. In this note, we assume that the system is working at time t>0. We consider the conditional signature of the system as a vector in which the ith element is defined as pi(t)=P(T=Xi: n|T>t) and investigate its properties as a function of time  

Precipitation and scaling of calcium sulfate have been known as major problems facing process industries and oilfield operations. Most scale prediction models are based on aqueous thermodynamics and solubility behavior of salts in aqueous electrolyte solutions. There is yet a huge interest in developing reliable, simple, and accurate solubility prediction models. In this study, a comprehensive model based on least-squares support vector machine (LS-SVM) is presented, which is mainly devoted to calcium sulfate dihydrate (or gypsum) solubility in aqueous solutions of mixed electrolytes covering wide temperature ranges. In this respect, an aggregate of 880 experimental data were gathered from... 

The main purpose of this article is to generalize a recent result about isometries of Lipschitz spaces. Botelho, Fleming and Jamison [2] described surjective linear isometries between vector-valued Lipschitz spaces under certain conditions. In this article, we extend the main result of [2] by removing the quasi-sub-reflexivity condition from Banach spaces  

Although exemplar based approaches have shown good accuracy in classification problems, some limitations are observed in the accuracy of exemplar based automatic speech recognition (ASR) applications. The main limitation of these algorithms is their high computational complexity which makes them difficult to extend to ASR applications. In this paper, an N-best class selector is introduced based on sparse representation (SR) and a tree search strategy. In this approach, the classification is fulfilled in three steps. At first, the set of similar training samples for the specific test sample is selected by k-dimensional (KD) tree search algorithm. Then, an SR based N-best class selector is... 

The presence of the desired signal (DS) in the training snapshots makes the adaptive beamformer sensitive to any steering vector mismatch and dramatically reduces the convergence rate. The objective of the present study is to propose a new adaptive beamformer which is robust against direction-of-arrival (DOA) mismatch and its convergence rate is not sensitive to the presence of the DS. This method is applicable to the arrays with specific structure such as the linear array. Our approach is based on the DS elimination from the training snapshots and the sub-array beamforming technique. To accomplish this goal, a blocking matrix which converts the primary data to the DS-free data is... 

Estimation of the viscosity of naturally occurring petroleum gases is essential to provide more accurate analysis of gas reservoir engineering problems. In this study, a new soft computing approach, namely, least square support vector machine (LSSVM) modeling, optimized with a coupled simulated annealing technique was applied for estimation of the natural gas viscosities at different temperature and pressure conditions. This model was developed based on 2485 viscosity data sets of 22 gas mixtures. The model predictions showed an average absolute relative error of 0.26% and a correlation coefficient of 0.99. The results of the proposed model were also compared with the well-known predictive... 

In this paper, we study the discriminative modeling of Spoken Language Understanding (SLU) using Conditional Random Fields (CRF) and Statistical Machine Translation (SMT) alignment models. Previous discriminative approaches to SLU have been dependent on n-gram features. Other previous works have used SMT alignment models to predict the output labels. We have used SMT alignment models to align the abstract labels and trained CRF to predict the labels. We show that the state transition features improve the performance. Furthermore, we have compared the proposed method with two baseline approaches; Hidden Vector States (HVS) and baseline-CRF. The results show that for the F-measure the proposed... 

Similarity measure is an important key in image registration. Most traditional intensity-based similarity measures (e.g. sum-of-squared-differences, correlation coefficient, mutual information and correlation ratio) assume a stationary image and pixel-by-pixel independence. These similarity measures ignore the correlation among pixel intensities; hence, a perfect image registration cannot be achieved especially in the presence of spatially varying intensity distortions and outlier objects that appear in one image but not in the other. It is supposed here that non-stationary intensity distortion (such as bias field) has a sparse representation in the transformation domain. Based on this... 

In this paper, we introduce a method of threshold secret sharing scheme in which secret reconstruction is based on celebrated Babai lattice algorithm. In order to supply secure public channels for transmitting shares to parties, we need to ensure that there is no quantum threats to these channels. One solution for this problem can be utilization of lattice cryptosystems for these channels which requires designing lattice based secret sharing schemes. We indicate that our scheme is asymptotically correct. Moreover, we analyze the security of our scheme by giving a quantitative proof of security from the view point of information theory  

Liver-shape analysis and quantification is still an open research subject. Quantitative assessment of the liver is of clinical importance in various procedures such as diagnosis, treatment planning, and monitoring. Liver-shape classification is of clinical importance for corresponding intra-subject and inter-subject studies. In this research, we propose a novel technique for the liver-shape classification based on Spherical Harmonics (SH) coefficients. The proposed liver-shape classification algorithm consists of the following steps: (a) Preprocessing, including mesh generation and simplification, point-set matching, and surface to template alignment; (b) Liver-shape parameterization,... 

We present an attempt to improve the performance of multi-class image segmentation systems based on a multilevel description of segments. The multi-class image segmentation system used in this paper marks the segments in an image, describes the segments via multilevel feature vectors and passes the vectors to a multi-class object classifier. The focus of this paper is on the segment description section. We first propose a robust, scale-invariant texture feature set, named directional differences (DDs). This feature is designed by investigating the flaws of conventional texture features. The advantages of DDs are justified both analytically and experimentally. We have conducted several... 

The presence of the desired signal (DS) in the training snapshots makes the adaptive beamformer sensitive to any steering vector mismatch and dramatically reduces the convergence rate. Even the performance of the most of the existing robust adaptive beamformers is degraded when the signal-to-noise ratio (SNR) is increased. In this study, a high converging rate robust adaptive beamformer is proposed. This method is a promoted eigenspace-based beamformer. In this paper, a new signal-plus-interferences (SPI) covariance matrix estimator is proposed. The subspace of the ideal SPI covariance matrices is exploited and the estimated covariance matrix is projected into this subspace. This projection... 

This paper provides an understanding of counter-flow fluidic thrust vectoring, in the presence of the secondary air vacuum, applied to the exhaust nozzle of a micro-jet engine. An analytical and numerical study is performed here on a divergent collar surface adjacent to the cylindrical exhaust duct system. The vectoring angle is controlled by manipulating the momentum flux through a vacuum gap that is located on a circle concentric to the main nozzle. Three dimensional numerical simulations are conducted by utilizing a computational fluid dynamics model with two-equation standard k-ε turbulence model to study the pressure and velocity distribution of internal flow and nozzle geometry.... 

Accurate knowledge of pure hydrocarbon and natural gas viscosity is essential for reliable reservoir characterization and simulation as well as economic design of natural gas processing and transport units. The most trustable sources of pure hydrocarbon and natural gas viscosity values are laboratory experiments. When there is no available experimental data for the required composition, pressure, and temperature conditions, the use of predictive methods becomes important. In this communication, a novel approach was proposed to develop for prediction of viscosity of pure hydrocarbons as well as gas mixtures containing heavy hydrocarbon components and impurities such as carbon dioxide,... 

In this paper, we develop the machinery of real interference alignment. This machinery is extremely powerful in achieving the sum degrees of freedom (DoF) of single antenna systems. The scheme of real interference alignment is based on designing single-layer and multilayer constellations used for modulating information messages at the transmitters. We show that constellations can be aligned in a similar fashion as that of vectors in multiple antenna systems and space can be broken up into fractional dimensions. The performance analysis of the signaling scheme makes use of a recent result in the field of Diophantine approximation, which states that the convergence part of the... 

In oil and gas fields, it is a common practice to flow liquid and gas mixtures through choke valves. In general, different types of primary valves are employed to control pressure and flow rate when the producing well directs the natural gas to the processing equipment. In this case, the valve normally is affected by elevated levels of flow (or velocity) as well as solid materials suspended in the gas phase (e.g., fine sand and other debris). Both surface and subsurface chokes may be installed to regulate flow rates and to protect the porous medium and surface facilities from unusual pressure instabilities.In this study a reliable, novel, computer based predictive model using Least-Squares...