Sharif Digital Repository

In this study, a chemometric strategy was developed for analysis of gas chromatographic (GC) and infrared spectroscopic (FT-IR) fingerprints of nine crude oil samples from the main oil wells of Iran to classify them and to find their origins. In this regard, a fractionation method based on saturated, aromatic, resin, and asphaltene (SARA) test was used. Then, these fractions were analyzed by GC-FID and GC–MS. Also, nine crude oil samples were analyzed by FT-IR. The obtained GC fingerprints were aligned using correlation optimized warping (COW) and auto-scaled, and then analyzed using principal component analysis (PCA) and hierarchical cluster analysis (HCA). Evaluation of PCA scores plot... 

In the present contribution, visible-near infrared hyperspectral imaging (Vis-NIR-HSI) combined with a novel chemometric approach based on mean-filed independent component analysis (MF-ICA) followed by multivariate classification techniques is proposed for saffron authentication and adulteration detection. First, MF-ICA was used to exploit pure spatial and spectral profiles of the components. Then, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to find patterns of authentic samples based on their distribution maps. Then, detection of five common plant-derived adulterants of saffron including safflower, saffron style, calendula, rubia and turmeric were... 

In the present contribution, visible and short wavelengths of near infrared hyperspectral imaging (Vis-SWNIR-HSI) combined with different chemometric techniques is proposed as a novel technique for turmeric authentication and multiple adulterants (corn flour, rice flour, starch, wheat flour, and zedoary) detection. In this regard, twenty-three samples of turmeric were collected as whole rhizomes or powdered from seven countries and then their VIS-SWNIR hyperspectral images were obtained in 400–1000 nm using SPECIM IQ HSI device. Two multivariate resolution techniques of multivariate curve resolution-alternating least squares (MCR-ALS) and mean-field independent component analysis (MF-ICA)... 

In this work, a central difference unstructured finite volume lattice Boltzmann method (FVLBM) in an arbitrary Lagrangian–Eulerian (ALE) framework is applied to effectively simulate the compressible viscous flows over moving bodies. Here, the two-dimensional compressible LB equation based on the multispeed Watari model is formulated in the ALE framework on an unstructured body-fitted mesh and the resulting equation is discretized by using the cell-centered finite volume method in which a central averaging scheme is made to calculate the numerical fluxes. A suitable dissipation term is added to the formulation to ensure the stability of the numerical scheme applied. The time integration is... 

This study presents a rapid method for detecting and authenticating intact saffron stigma through its packaging using visible-short wavelength near-infrared (Vis-SWNIR) hyperspectral imaging (HSI) in conjunction with chemometrics. A dataset containing 38 authentic saffron samples was utilized, and HSI images were captured within the spectral range of 400–950 nm. Multivariate curve resolution-alternating least squares (MCR-ALS) was used to obtain pure spatial and spectral profiles of the components. The resolved spatial profiles were then subjected to principal component analysis (PCA) to identify potential patterns in the authentic samples. Binary mixtures of pooled saffron samples and... 

Metabolomics is the science of studying small molecules (metabolites) in biological systems with the aim of getting insight into cells, biofluids and organisms. Chemometric methods are powerful tools to address data problems generated in metabolomic studies and to extract valuable information. This review focuses mainly on a range of chemometric methods used for processing of metabolomics data generated from gas chromatography-mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography-mass spectrometry (GC × GC-MS). Herein, essential skills used for preprocessing of raw data, multivariate resolution, pattern recognition, variable selection and identification of... 

In the present contribution, a new approach based on mutual information (MI) is proposed for exploring the independence of feasible solutions in two component systems. Investigating how independent are different feasible solutions can be a way to bridge the gap between independent component analysis (ICA) and multivariate curve resolution (MCR) approaches and, to the best of our knowledge, has not been investigated before. For this purpose, different chromatographic and hyperspectral imaging (HSI) datasets were simulated, considering different noise levels and different degrees of overlap for two-component systems. Feasible solutions were then calculated by both grid search (GS) and... 

Exploiting Compressive Sensing (CS) in MIMO radars, we can remove the need of the high rate A/D converters and send much less samples to the fusion center. In distributed MIMO radars, the received signal can be modeled as a block sparse signal in a basis. Thus, block CS methods can be used instead of classical CS ones to achieve more accurate target parameter estimation. In this paper a new method of energy allocation to the transmitters is proposed to improve the performance of the block CS-based distributed MIMO radars. This method is based on the minimization of an upper bound of the sensing matrix block-coherence. Simulation results show a significant increase in the accuracy of multiple... 

Multiple-input multiple-output (MIMO) radars offer higher resolution, better target detection, and more accurate target parameter estimation. Due to the sparsity of the targets in space-velocity domain, we can exploit Compressive Sensing (CS) to improve the performance of MIMO radars when the sampling rate is much less than the Nyquist rate. In distributed MIMO radars, block CS methods can be used instead of classical CS ones for more performance improvement, because the received signal in this group of MIMO radars is a block sparse signal in a basis. In this paper, two new methods are proposed to improve the performance of the block CS-based distributed MIMO radars. The first one is a new... 

Neurological diseases have different etiological causes. Contemporary, developing an ef-fective treatment for these diseases is an ongoing challenge. Cell therapy is recognized as one of the promising solutions for the treatment of these diseases. Amongst various types of stem cells, bone marrow-derived mesenchymal stem cells (BM-MSC) are known to be the most widely used stem cells. These cells are endowed with appealing properties such as the ability to differentiate into other cell types, including the muscle, liver, glial, and nerve cells. In this review study, we have systematically evaluated the ability of a variety of chemical compounds used in the last ten years to differentiate... 

We describe a nanocomposite prepared from polydopamine, silver nanoparticles, and polypyrrole (PDA-Ag-PPy) that can be used for the microextraction in packed syringe (MEPS) of tricyclic antidepressants from urine samples. The PDA-Ag-PPy composite was prepared in-situ by the reduction of silver ion - doped PPy during oxidative polymerization of dopamine. The PDA-Ag coatings on the nanoribbon – shaped PPy represent a highly porous, inorganic–organic hybrid nanomaterial that has a wide range of applications. The nanocomposite was characterized by FTIR and scanning electron microscopy. It is shown to be an efficient sorbent for the MEPS of the tricyclic antidepressants amitriptyline, imipramine... 

The main goal in many fields in the empirical sciences is to discover causal relationships among a set of variables from observational data. PC algorithm is one of the promising solutions to learn underlying causal structure by performing a number of conditional independence tests. In this paper, we propose a novel GPU-based parallel algorithm, called cuPC, to execute an order-independent version of PC. The proposed solution has two variants, cuPC-E and cuPC-S, which parallelize PC in two different ways for multivariate normal distribution. Experimental results show the scalability of the proposed algorithms with respect to the number of variables, the number of samples, and different graph... 

Segmentation of a scene to the part made is a challenging work. In this paper a graphical model is used for this task. The methods based on geometrical derivatives such as curvature and normal often haven't good result in segmentation of geometrically-complex architecture and lead to over-segmentation and even failure. Proposed method for segmentation contains two steps. At first region growing based on curvature, normal and color is used for growing region. This segmented cloud is used for unary potential in graphical model. Fully connected graph for Conditional Random Field with Gaussian kernel for pair wise potentials is used for correcting this segmentation. Gaussian kernels are based on... 

A thermo-elastic analysis coupled with a phase change model is employed to evaluate thermal stresses as well as progress of austenite decomposition after hot strip rolling operations. The thermo-mechanical finite element analysis is utilized to assess the distributions of temperature and thermal stresses during cooling while at the same time, a model based on the additivity rule is used to determine the rate of austenite to ferrite decomposition. The proposed model is applicable to multi-pass rolling schedules while the effects of different process parameters including the rolling speed and cooling configuration of the run-out table can be taken into account. In order to verify the... 

A major problem in a multiple output converter structure is the different power flow via its various outputs. This problem leads to unwanted input DC-link voltage. This paper studies full bridge based DC-DC converters with multiple outputs. The effect of power flow variation is studied and a regenerative converter topology which controls the DC-link voltage by space voltage vector modulation technique is proposed. The proposed converter has a fast response to control the DC-link voltage in an acceptable band. Simulation and experimental results are presented to verify the analytical studies. © 2018 IEEE  

Fractional-pixel accuracy Motion Estimation (ME) has been shown to result in higher quality reconstructed image sequences in hybrid video coding systems. However, the higher quality is achieved by notably increased Motion Field (MF) bitrate and more complex computations. In this paper, new half-pixel block matching ME algorithms are proposed to improve the rate-distortion characteristics of low bitrate video communications. The proposed methods tend to decrease the required video bandwidth, while improving the motion compensation quality. The key idea is to put a deeper focus on the search origin of the ME process, based on center-bias characteristics of low bitrate video MFs. To employ the... 

Motion estimation at fractional-pixel accuracy results in higher quality video sequences. However, the higher quality is achieved by more computations and increased required motion field bitrates. In this paper, new half-pixel accuracy block matching-based motion estimation algorithms are proposed to improve the rate-distortion characteristics of low-bitrate video communications. The proposed methods especially tend to decrease the required video bandwidth, with no degradation in quality of reconstructed image sequences. The key idea is to put a deeper focus on the origin (zero motion) based on the center-bias characteristics of low bitrate video motion fields. The experimental results show...