Sharif Digital Repository

The performances of gas chromatography with mass spectrometry and of comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry are examined through the comparison of Daphnia magna metabolic profiles. Gas chromatography with mass spectrometry and comprehensive two-dimensional gas chromatography with mass spectrometry were used to compare the concentration changes of metabolites under saline conditions. In this regard, a chemometric strategy based on wavelet compression and multivariate curve resolution–alternating least squares is used to compare the performances of gas chromatography with mass spectrometry and comprehensive two-dimensional gas chromatography with... 

Comprehensive two-dimensional gas chromatography and flame ionization detection combined with unfolded-partial least squares is proposed as a simple, fast and reliable method to assess the quality of gasoline and to detect its potential adulterants. The data for the calibration set are first baseline corrected using a two-dimensional asymmetric least squares algorithm. The number of significant partial least squares components to build the model is determined using the minimum value of root-mean square error of leave-one out cross validation, which was 4. In this regard, blends of gasoline with kerosene, white spirit and paint thinner as frequently used adulterants are used to make... 

The atmosphere effect before shower maximum is dominantly: an environment for development of Extensive Air Shower(EAS) events, but after that, the absorbtion effect of the atmosphere will be dominant. The shower maximum for about 100 TeV is near 500 gr/cm2 (∼5200m a.s.l), and most of EAS arrays in this energy range are at heights below the shower maximum height, specially for higher zenith angle EAS events, so we need to more concentration on the absorbtion effect specially in this energy range and our site. Therefore for this investigation we logged 476,675 true EAS events by an array of particle water Cherenkov detectors. We calculated the local coordinates (θ, φ) of each EAS event by... 

The present study aims to estimate nitrogen (N) content in tomato (Solanum lycopersicum L.) plant leaves using optimal hyperspectral imaging data by means of computational intelligence [artificial neural networks and the differential evolution algorithm (ANN-DE), partial least squares regression (PLSR), and convolutional neural network (CNN) regression] to detect potential plant stress to nutrients at early stages. First, pots containing control and treated tomato plants were prepared; three treatments (categories or classes) consisted in the application of an overdose of 30%, 60%, and 90% nitrogen fertilizer, called N-30%, N-60%, N-90%, respectively. Tomato plant leaves were then randomly... 

A multi-residue method using gas chromatography coupled with flame ionisation detector has been developed for simultaneous determination of 10 pesticides in milk. The methodology involved a sample clean-up procedure using ‘quick, easy, cheap, effective, rugged and safe’ followed by a preconcentration step based on dispersive liquid–liquid microextraction. In this regard, acetonitrile was added to the milk sample with specific pH and ionic strength, and the mixture was rigorously shaken. The extracts were centrifuged; then, the organic phase (acetonitrile) was transferred to a test tube and was mixed with deionised water. The mixture was sonicated and chloroform was added as an acceptor phase... 

The performance of several regression methods is investigated to estimate the distribution of engineering demand parameters conditioned on intensity measures (EDP|IM) for small record sets. In particular, the performance of the multivariate ordinary least squares (OLS), a simultaneous mean-variance regression (MVR) done by a penalized weighted least-square loss function, and a mean-covariance/variance regression based on expectation maximization method (EM) are assessed. The efficiency of the introduced methods is compared with FEMA-P58 methodology. Performance assessment of EM and MVR methods shows that the overall increase in efficiency is about 25–45% for maximum inter-story drift ratios,... 

The performance of several regression methods is investigated to estimate the distribution of engineering demand parameters conditioned on intensity measures (EDP|IM) for small record sets. In particular, the performance of the multivariate ordinary least squares (OLS), a simultaneous mean-variance regression (MVR) done by a penalized weighted least-square loss function, and a mean-covariance/variance regression based on expectation maximization method (EM) are assessed. The efficiency of the introduced methods is compared with FEMA-P58 methodology. Performance assessment of EM and MVR methods shows that the overall increase in efficiency is about 25–45% for maximum inter-story drift ratios,... 

A multi-residue method using gas chromatography coupled with flame ionisation detector has been developed for simultaneous determination of 10 pesticides in milk. The methodology involved a sample clean-up procedure using ‘quick, easy, cheap, effective, rugged and safe’ followed by a preconcentration step based on dispersive liquid–liquid microextraction. In this regard, acetonitrile was added to the milk sample with specific pH and ionic strength, and the mixture was rigorously shaken. The extracts were centrifuged; then, the organic phase (acetonitrile) was transferred to a test tube and was mixed with deionised water. The mixture was sonicated and chloroform was added as an acceptor phase... 

As the ordinary least squares (OLS) method is very sensitive to outliers as well as to correlated responses, a robust coefficient estimation method is proposed in this paper for multi-response surfaces in multistage processes based on M-estimators. In this approach, experimental designs are used in which the intermediate response variables may act as covariates in the next stages. The performances of both the ordinary multivariate OLS and the proposed robust multi-response surface approach are analyzed and compared through extensive simulation experiments. Sum of the squared errors in estimating the regression coefficients reveals the efficiency of the proposed robust approach. © 2017 Taylor... 

As the ordinary least squares (OLS) method is very sensitive to outliers as well as to correlated responses, a robust coefficient estimation method is proposed in this paper for multi-response surfaces in multistage processes based on M-estimators. In this approach, experimental designs are used in which the intermediate response variables may act as covariates in the next stages. The performances of both the ordinary multivariate OLS and the proposed robust multi-response surface approach are analyzed and compared through extensive simulation experiments. Sum of the squared errors in estimating the regression coefficients reveals the efficiency of the proposed robust approach. © 2018 Taylor... 

Recently, there has been a growing interest in estimation of sparse channels as they are observed in underwater acoustic and ultrawideband channels. In this paper we present a new Bayesian sparse channel estimation (SCE) algorithm that, unlike traditional SCE methods, exploits noise statistical information to improve the estimates. The proposed method uses approximate maximum a posteriori probability (MAP) to detect the non-zero channel tap locations while least square estimation is used to determine the values of the channel taps. Computer simulations shows that the proposed algorithm outperforms the existing algorithms in terms of normalized mean squared error (NMSE) and approaches... 

In this study, N-way partial least squares (NPLS) is proposed to correlate comprehensive two-dimensional gas chromatography-time of flight mass spectrometry (GC×GCTOFMS) data of different aromatic oil fractions (fresh and weathered) to their toxicity values. Before NPLS modeling, since drift and wander of baseline interfere with information of sought analytes in GC×GC-TOFMS data, a novel method called two-dimensional asymmetric least squares is thus developed for comprehensive correction of the baseline contributions in both chromatographic dimensions. The algorithmis termed comprehensive because it functions to correct the entire chromatogram in both dimensions and it preserves the... 

Chromatographic fingerprinting is an effective methodology for authentication and quality control of herbal products. In the presented study, a chemometric strategy based on multivariate curve resolution-alternating least squares (MCR-ALS) and multivariate pattern recognition methods was used to establish a gas chromatography-mass spectrometry (GC-MS) fingerprint of saffron. For this purpose, the volatile metabolites of 17 Iranian saffron samples, collected from different geographical regions, were determined using the combined method of ultrasound-assisted solvent extraction (UASE) and dispersive liquid-liquid microextraction (DLLME), coupled with GC-MS. The resolved elution profiles and... 

In this paper we consider the problem of improving unknown node localization by using differential received signal strength (DRSS). Many existing localization approaches, especially those using the least squares methods, either ignore nonlinear constraint among model parameters or utilize them inefficiently. In this paper, we develop four DRSS-based localization methods by utilizing different combinations of covariance and weight matrices. Each method constructs a two-stage procedure. During the first stage, an initial coarse position estimate is obtained. The second stage results the refined localization by accounting for nonlinear dependency among estimator variables. The proper choice... 

The aim of this study was to determine whether specific three-dimensional aortic shape features, extracted via statistical shape analysis (SSA), correlate with the development of thoracic ascending aortic dissection (TAAD) risk and associated aortic hemodynamics. Thirty-one patients followed prospectively with ascending thoracic aortic aneurysm (ATAA), who either did (12 patients) or did not (19 patients) develop TAAD, were included in the study, with aortic arch geometries extracted from computed tomographic angiography (CTA) imaging. Arch geometries were analyzed with SSA, and unsupervised and supervised (linked to dissection outcome) shape features were extracted with principal component... 

Estimation of physical parameters of a parametrically excited gyroscope is studied in this paper. This estimation is possible by reading the input and output data of the gyroscope. Because of different faults in the manufacturing process and tolerances, physical parameters of a gyroscope are not exactly same as the expected values of the manufacturer. Moreover, changing of temperature, humidity, external acceleration, etc. can change the physical parameters of the gyro. Thus, the physical parameters of gyroscope are not fixed values and may deviate from the desired designed values. The physical parameters of gyroscope determine the optimal region for working of gyroscope. Thus, if the... 

In the present work, the spray characteristics of bio-ethanol and its blends have been experimentally and theoretically investigated. To have a comprehensive study, the effects of ambient condition and injection pressure on the spray of different blends have been considered. Macroscopic and microscopic characteristics of spray such as tip penetration length, cone angle, projected area, volume, Sauter Mean Diameter (SMD), and Ohnesorge number are investigated precisely. Besides, air entrainment and atomization analyses have been carried out to improve mixture formation process. Using curve fitting and least squares method, theoretical correlations have been suggested in such a way to predict...