Sharif Digital Repository

In the current work, the results of full-scale laboratory testing of 114.3 and 168.3 mm in diameter steel gas distribution pipes buried at different depths and in two different soil types under a reverse fault offset of 0.6 m are presented and discussed in terms of longitudinal strain distribution, pipe deformation, and cross-section distortion. Results show that the pipe deformation and accordingly its failure mode, and soil failure planes change with increasing burial depth. It was also found that severe cross-section distortion occurs at about 2.3 times the strain limit for onset of wrinkling suggested by various guidelines. © 2018, © 2018 Taylor & Francis Group, LLC  

In the current work, the results of full-scale laboratory testing of 114.3 and 168.3 mm in diameter steel gas distribution pipes buried at different depths and in two different soil types under a reverse fault offset of 0.6 m are presented and discussed in terms of longitudinal strain distribution, pipe deformation, and cross-section distortion. Results show that the pipe deformation and accordingly its failure mode, and soil failure planes change with increasing burial depth. It was also found that severe cross-section distortion occurs at about 2.3 times the strain limit for onset of wrinkling suggested by various guidelines. © 2017 Taylor & Francis Group, LLC  

Permanent ground displacement (PGD) caused by surface faulting is considered as one of the most significant hazards affecting buried pipelines. Pipelines crossing reverse-slip faults are subjected to compressive actions (stresses and strains) which can result in buckling of the pipe. In current work, the results obtained from the full-scale laboratory testing and finite element analyses of 4″ (114.3 mm) and 6″ (168.3 mm) steel gas pipes (without internal pressure) buried inside a split box and subjected to a reverse faulting of 0.6 m (pure dip-slip) are presented. These pipes are commonly used in gas distribution lines and networks. The experimental setup, procedure and instrumentation as... 

Mean field independent component analysis (MF-ICA) along with other chemometric techniques was proposed for obtaining more information from multi-component gas chromatographic-mass spectrometric (GC-MS) signals of essential oils (mandarin and lemon as examples). Using these techniques, some fundamental problems during the GC-MS analysis of essential oils such as varying baseline, presence of different types of noise and co-elution have been solved. The parameters affecting MF-ICA algorithm were screened using a 25 factorial design. The optimum conditions for MF-ICA algorithm were followed by deconvolution of complex GC-MS peak clusters. The number of independent components (ICs) (chemical... 

Gas chromatography-mass spectrometry (GC-MS) combined with Chemometric resolution techniques were proposed as a method for the analysis of volatile components of Iranian damask rose oil. The essential oil of damask rose was extracted using hydrodistillation method and analyzed with GC-MS in optimized conditions. A total of 70 components were identified using similarity searches between mass spectra and MS database. This number was extended to 95 components with concentrations higher than 0.01% accounting for 94.75% of the total relative content using Chemometric techniques. For the first time in this work, an approach based upon subspace comparison is used for determination of the chemical... 

Essential oils (EOs) are valuable natural products that are popular nowadays in the world due to their effects on the health conditions of human beings and their role in preventing and curing diseases. In addition, EOs have a broad range of applications in foods, perfumes, cosmetics and human nutrition. Among different techniques for analysis of EOs, gas chromatography-mass spectrometry (GC-MS) is the most important one in recent years. However, there are some fundamental problems in GC-MS analysis including baseline drift, spectral background, noise, low S/N (signal to noise) ratio, changes in the peak shapes and co-elution. Multivariate curve resolution (MCR) approaches cope with ongoing... 

Multivariate curve resolution based on the minimization of an objective function (MCR-FMIN) defined directly from the non-fulfillment of constraints was applied for the first time as a deconvolution method to separate co-eluted gas chromatographic-mass spectrometric (GC-MS) signals. Simulated and real (standard real mixture and limon oil) GC-MS data were used to evaluate the feasibility of this method. The MCR-FMIN solutions have been obtained based on the rotation of principal component analysis (PCA) solutions using the non-linear optimization algorithms. Calculation of the initial values of R rotation matrix using model free analysis methods such as fixed-size moving window-evolving... 

A novel method for extraction and analysis of volatile compounds of Artemisia haussknechtii Boiss., using simultaneous hydro-distillation and static headspace liquid microextraction followed by gas chromatography-mass spectrometry (SHD-SHLPME-GCMS) is developed. SHLPME parameters including nature of extracting solvent, headspace volume and design, extraction time, sample weight and microdrop volume were optimized. Comparison of hydro-distillation gas chromatography-mass spectrometry and HD-SHLPME-GCMS showed that the latter method is fast, simple, inexpensive and effective for the analysis of volatile compounds of aromatic plants. By using this method, 56 compounds were extracted and... 

In this paper, a new graph product, called Edge Graph Product (EGP) is proposed by replacing each edge in the multiplicand graph by a copy of the multiplier graph via two candidate nodes. The edge product, unlike other products already proposed, results in a graph whose number of edges is numerical product of the number of the edges in the multiplicand and multiplier graphs, and the number of vertices is not equal to the numerical product of the number of vertices in the multiplicand and multiplier graphs. After formal definition of the new product, some basic properties of the product operator are studied. We then address Hamiltonian, Eulerian and routing properties of the new product, and... 

In this paper, the problem of power allocation and optimal decoding order of users for the uplink channel of a multirate direct-sequence code-division multiple-access system with linear successive interference cancellation (IC) is addressed. First, the closed-form expressions of the required received powers at the base station for providing all users with their demanded rates and signal to interference-plus-noise ratios (SINRs) are derived. Then, it is shown that, unlike the case when the IC is perfect, in this case, optimum ordering of users at the receiver, which minimizes the total transmitted power, is a function of both their requested SINRs and path gains. Finally, in searching for the... 

In this paper, we will address the issue of power distribution and decoding order in the uplink side of a multirate code division multiple access (CDMA) system based on linear successive interference cancellation (SIC). First, the closed form expressions for the required received powers at the base station, in order to achieve the users bit rate and Quality of Service (QoS) requirements, will be derived. Then, we will investigate the problem of optimal decoding order of the users under imperfect interference cancellation condition and will show that optimum decoding order of users, unlike the case of perfect SIC, is a function of their requested SINR values in addition to their path gains.... 

In this paper, we will address the issue of power distribution and decoding order in the uplink side of a multirate code division multiple access (CDMA) system based on linear successive interference cancellation (SIC). First, the closed form expressions for the required received powers at the base station, in order to achieve the users bit rate and Quality of Service (QoS) requirements, will be derived. Then, we will investigate the problem of optimal decoding order of the users under imperfect interference cancellation condition and will show that optimum decoding order of users, unlike the case of perfect SIC, is a function of their requested SINR values in addition to their path gains.... 

Volatile components of saffron from different regions of Iran were extracted by ultrasonic-assisted solvent extraction (USE) and were analyzed by gas chromatography-mass spectrometry (GC-MS). Self-modeling curve resolution (SMCR) was proposed for resolving the co-eluted GC-MS peak clusters into pure chromatograms and mass spectra. Multivariate curve resolution-objective function minimization (MCR-FMIN) and multivariate curve resolution-alternating least square (MCR-ALS) were successfully used for this purpose. The accuracy of the qualitative and quantitative results was improved considerably using SMCR techniques. Comparison of the results of saffron from different regions of Iran showed... 

The volatile components of Iranian saffron were extracted using ultrasonic solvent extraction (USE) technique and then were separated and detected by gas chromatography-mass spectrometry (GC-MS). Variables affecting the extraction procedure were screened by using a 25-1 fractional factorial design and among them; sample amount, solvent volume, solvent ratio and extraction time were optimized by applying a rotatable central composite design (CCD). The optimum values of factors were: 2.38 g sample, 29.04 mL solvent, 69.23% MeOH solvent ratio and 71.8 min for the extraction time. Forty constituents were identified for Iranian saffron by GC-MS representing 90% of the total peak area. The major... 

The gas chromatography retention indices of 100 different components of essential oils, on three columns with stationary phases of different polarities, were used to develop robust quantitative structure-retention relationship (QSRR) models. Two linear models with only one variable, i.e. solvation entropy, were developed, which explain 95 and 94% of variances of the test set for dimethyl silicone and dimethyl silicone with 5% phenyl group columns, respectively. These models are extremely simple and easy to interpret, but they show higher errors compared with more robust models such as partial least square (PLS) and ridge regressions. For the third column (polyethylene glycol (PEG)), 24... 

This contribution focuses on the use of ladder particle swarm optimisation (LPSO) on modelling of oxadiazole- and triazolesubstituted naphthyridines as human immunodeficiency virus-1 integrase inhibitors. Artificial neural network (ANN) and Monte Carlo cross-validation techniques were combined with LPSO to develop a quantitative structure-activity relationship model. The techniques of LPSO, ANN and sample set partitioning based on joint x-y distances were applied as feature selection, mapping and model evaluation, respectively. The variables selected by LPSO were used as inputs of Bayesian regularisation ANN. The statistical parameters of correlation of deterministic, R2, and... 

Achieving high rates of detection in low rates of embedding is still a challenging problem in many steganalysis systems. The newly proposed steganalysis system based on sparse representation classifier has shown remarkable detection rates in low embedding rate. In this paper, we propose a new steganalysis system based on double sparse representation classifier. We compare our proposed method with other steganalysis systems which use different classifier (including nearest neighbor, support vector machine, ensemble support vector machine and sparse representation). In all of our experiments, input features to the classifier are fixed and the ability of classifier is examined. Also we provide...