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    Conventional and Hyperspectral Imaging Combined with Chemometric Techniques for Rice Authentication

    , M.Sc. Thesis Sharif University of Technology Dehbasteh, Maryam (Author) ; Parastar Shahri, Hadi (Supervisor)
    Abstract
    Fast, non-destructive and reliable methods for food authentication purposes have been deemed important in recent years. The hyperspectral imaging technique (HSI) is a powerful method in this field, allowing the study of different features such as size, color, texture. Comprehensive interpretation is crucial, and utilizing chemometric methods enhances data interpretation. Rice is a vital and strategic food source for nearly half of the world, with Asia, particularly Iran, being a leading producer and exporter. Various types of rice fraud exist, including the mixing of high-quality and low-quality varieties, sold at a high cost. The present project aims to determine the geographical origin and... 

    Discharge coefficient of triangular and asymmetric labyrinth side weirs using the nonlinear PLS method

    , Article Journal of Irrigation and Drainage Engineering ; Volume 142, Issue 11 , 2016 ; 07339437 (ISSN) Parvaneh, A ; Kabiri Samani, A ; Nekooie, M. A ; Sharif University of Technology
    American Society of Civil Engineers (ASCE)  2016
    Abstract
    Side weirs are hydraulic control structures widely used in irrigation and drainage systems as well as wastewater treatment plants. These structures also serve as adjusting/diverting flow structures with a minimum head loss. In the present study, by applying experimental data of more than 400 laboratory tests and using the multivariable nonlinear partial least-squares (PLS) method, three nonlinear equations are proposed for discharge coefficient, CM, of triangular and asymmetric labyrinth side weirs. These equations relate the discharge coefficient to the relevant geometrical and hydraulic dimensionless characteristics of flow. Results indicate that the new proposed equations are more... 

    Application of Gold Nanoparticles for Simultaneous Determination of Polycyclic Aromatic Hydrocarbons in Water Samples with the Aid of Multivariate Chemometric Methods

    , M.Sc. Thesis Sharif University of Technology Rezaiyan, Mahsa (Author) ; Parastar Shahri, Hadi (Supervisor) ; Hormozi Nezhad, Mohammad Reza (Supervisor)
    Abstract
    In this study, a multivariate-based strategy was developed for simultaneous determination of thirteen carcinogenic polycyclic aromatic hydrocarbons (PAHs) in water samples using gold nanoparticles (AuNPs) as solid-phase extraction (SPE) sorbent combined with gas chromatography-flame ionization detector (GC-FID). The extraction technique is based on the strong affinity between citrate capped AuNPs and PAHs. Furthermore, characterization of AuNPs was performed by UV-Vis and TEM techniques. A rotatable central composite design (CCD) combined with multiple linear regression (MLR) was used for designing the extraction procedure and developing models using the GC peak areas of 13 PAHs. Also,... 

    Is Driving More Dangerous in Holidays than Normal Days?Investigating the Effect of Holidays on Road Accidents in Iran

    , M.Sc. Thesis Sharif University of Technology Kushkbaghi, Maryam (Author) ; Vesal, Mohammad (Supervisor)
    Abstract
    Traffic accidents are one of the main causes of death in Iran. Between 2005 to 2019, 20,000 people were killed and 300,000 were injured on average annually. About 65 percent of all traffic fatalities over the past seven years has been on intercity roads. Finding patterns of accidents on specific days, such as holidays, would help the planners prevent traffic accidents. In this study, using police accident data, traffic counts of Road Maintenance and Transportation Organization, and meteorological data of Iran Meteorological Organization during 2011 to 2018, we study the effect of official holidays, and the days before, after and between two holidays on the rate and severity of road accidents... 

    Investigating the Impact of Key Innovation Variables on the Level of Technological Catch up: A Comparison between High and Middle Income Countries

    , M.Sc. Thesis Sharif University of Technology Fakhimi Jamil, Mohammad Amin (Author) ; Miremadi, Iman (Supervisor)
    Abstract
    Today, innovation plays an essential role in the economic growth of countries. By evaluating technological capabilities, different approaches have considered important effects of innovation on the economic ability and superiority of countries either directly or indirectly. In recent years, the Global Innovation Index (GII) has been employed as a common framework in this respect. It consists of five components, including “institutions,” “human capital and research,” “infrastructure,” “market sophistication,” and “business sophistication,” as the inputs, and two components, including the “knowledge and technology outputs” and “creative outputs” as the outputs of innovation. The present study... 

    The Role of E-WOM Social Commerce And Subjective Norms On Online Impulsive Buying

    , M.Sc. Thesis Sharif University of Technology Abbasi Bastami, Asal (Author) ; Khalili Nasr, Arash (Supervisor)
    Abstract
    One challenge in the world of digital business is the impact of opinion leaders on the type of e-commerce shopping. In this research, emotional shopping is specifically investigated, and to examine the effect of opinion leaders, this research that compares the impact of mental norms and word-of-mouth advertising has addressed the word of mouth of the online trading world on emotional shopping. In this study, I applied the S-O-R model (stimulus-organism-response model) to discuss subjective norms and word-of-mouth advertising in the online trading world as stimuli and, according to this model, organisms of satisfaction and trust, hedonic browsing, and utilitarian browsing are examined, and... 

    N-way partial least squares with variable importance in projection combined to GC×GC-TOFMS as a reliable tool for toxicity identification of fresh and weathered crude oils

    , Article Analytical and Bioanalytical Chemistry ; Volume 407, Issue 1 , January , 2015 , Pages 285-295 ; 16182642 (ISSN) Mostafapour, S ; Parastar, H ; Sharif University of Technology
    Springer Verlag  2015
    Abstract
    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... 

    Emotion Recognition from EEG Signals using Tensor based Algorithms

    , M.Sc. Thesis Sharif University of Technology Einizadeh, Aref (Author) ; Hajipour, Sepideh (Supervisor)
    Abstract
    The brain electrical signal (EEG) has been widely used in clinical and academic research, due to its ease of recording, non-invasiveness and precision. One of the applications can be emotion recognition from the brain's electrical signal. Generally, two types of parameters (Valence and Arousal) are used to determine the type of emotion, which, in turn, indicate "positive or negative" and "level of extroversion or excitement" for a specific emotion. The significance of emotion is determined by the effects of this phenomenon on daily tasks, especially in cases where the person is confronted with activities that require careful attention and concentration.In the emotion recognition problem,... 

    Brain Connectivity Analysis Using Multiple Partial Least Square on fMRI Signals

    , M.Sc. Thesis Sharif University of Technology Hosseini Naghavi, Nader (Author) ; Fatemizadeh, Emad (Supervisor)
    Abstract
    Nowadays studying the brain's function in different Mental States like Resting-State or performing cognitive tasks is a very important component of research areas such as Biomedical Engineering, Neuroscience and Cognitive Sciences. The applications of studying the brain's function can be divided into two principal groups. In the first group of applications, the goal is understanding how the brain processes and response to external stimuli (like visual or audio stimuli) and internal states (like emotions). In these kinds of applications, particularly healthy subjects participate since the goal of these studies is finding healthy brain function in different states and stimuli. However, in the... 

    Marketing Agility; the Missing Chain in Impact Model of Innovation Ambidexterity on Marketing Innovation in Turbulent Market

    , M.Sc. Thesis Sharif University of Technology Hosseini Veleshkolaei, Amir Hossein (Author) ; Najmi, Manoochehr (Supervisor) ; Tasavori, Misagh (Supervisor)
    Abstract
    Marketing innovation is an idea that is the focal point of numerous marketing scholars recently. This study investigated relationships among the innovation ambidexterity, marketing innovation, marketing agility, and the moderator effect of market turbulence. Attempts are made to understand ambidexterity and agility notions from marketing perspectives to accelerate marketing innovation and identify measures for all of the mentioned constructs. Main theories which have been used to justify the constructs’ relationships are dynamic capability point of view, resource-based theory, and ambidexterity theory. Structural equation modeling (SEM), utilizing the technique of partial least squares... 

    QSPR studies for predicting gas to acetone and gas to acetonitrile solvation enthalpies using support vector machine

    , Article Journal of Molecular Liquids ; Volume 175 , 2012 , Pages 24-32 ; 01677322 (ISSN) Toubaei, A ; Golmohammadi, H ; Dashtbozorgi, Z ; Acree Jr., W. E ; Sharif Unviersity of Technology
    2012
    Abstract
    Quantitative structure-properties relationship (QSPR) has been applied to modelling and predicting the gas to acetone and gas to acetonitrile solvation enthalpies (ΔH Solv) of organic compounds using partial least squares (PLS), artificial neural network (ANN) and support vector machine (SVM) techniques. Two different datasets were assessed. The first one contained a set of gas to acetone enthalpy of solvation data of 68 different organic compounds while the second one included a total of 69 experimental data points for the enthalpy of solvation in acetonitrile. Genetic algorithm (GA) was used to search the descriptor space and select the descriptors responsible for property. After the... 

    Detection of addition of barley to coffee using near infrared spectroscopy and chemometric techniques

    , Article Talanta ; Volume 99 , 2012 , Pages 175-179 ; 00399140 (ISSN) Ebrahimi Najafabadi, H ; Leardi, R ; Oliveri, P ; Chiara Casolino, M ; Jalali Heravi, M ; Lanteri, S ; Sharif University of Technology
    Elsevier  2012
    Abstract
    The current study presents an application of near infrared spectroscopy for identification and quantification of the fraudulent addition of barley in roasted and ground coffee samples. Nine different types of coffee including pure Arabica, Robusta and mixtures of them at different roasting degrees were blended with four types of barley. The blending degrees were between 2 and 20 wt% of barley. D-optimal design was applied to select 100 and 30 experiments to be used as calibration and test set, respectively. Partial least squares regression (PLS) was employed to build the models aimed at predicting the amounts of barley in coffee samples. In order to obtain simplified models, taking into... 

    Determination of discharge coefficient of triangular labyrinth side weirs with one and two cycles using the nonlinear PLS method

    , Article Sustainable Hydraulics in the Era of Global Change - Proceedings of the 4th European Congress of the International Association of Hydroenvironment engineering and Research, IAHR 2016, 27 July 2016 through 29 July 2016 ; 2016 , Pages 653-657 ; 9781138029774 (ISBN) Nekooie, M. A ; Parvaneh, A ; Kabiri Samani, A ; Sharif University of Technology
    CRC Press/Balkema  2016
    Abstract
    Side weirs are hydraulic control structures widely used in irrigation, drainage networks and waste water treatment plants. These structures can be used for adjusting and diverting of flow with minimum energy loss. In spite of many studies were carried out on rectangular side weirs, the studies on oblique and labyrinth side weirs are scarce. In this study, based on the experimental data from more than 210 laboratory tests and through using the multivariable nonlinear partial least square (PLS) method, two nonlinear equations are presented for discharge coefficient CM of triangular labyrinth side weirs with one and two cycles. The obtained empirical equations relating CM with the relevant... 

    Quality assessment of gasoline using comprehensive two-dimensional gas chromatography combined with unfolded partial least squares: A reliable approach for the detection of gasoline adulteration

    , Article Journal of Separation Science ; Volume 39, Issue 2 , 2016 , Pages 367-374 ; 16159306 (ISSN) Parastar, H ; Mostafapour, S ; Azimi, G ; Sharif University of Technology
    Wiley-VCH Verlag 
    Abstract
    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... 

    Chemometric techniques coupled with NMR for matabolic profiling of lettuce exposed to polycyclic aromatic hydrocarbones

    , Article Analytical Biochemistry ; Volume 611 , 2020 Feizi, N ; Seraj, M ; Tajali, R ; Shavandi, S. R ; Parastar, H ; Sharif University of Technology
    Academic Press Inc  2020
    Abstract
    Treated waste water (TWW) quality varies due to the occurrence of polycyclic aromatic hydrocarbons (PAHs) up to low μg L−1. In this study, a non-targeted metabolomic analysis was performed on lettuce (Lactuca sativa L) exposed to 4 PAHs by irrigation. The plants were watered with different concentrations of contaminants (0–100 μg L−1) for 39 days under controlled conditions and then harvested, extracted and analyzed by nuclear magnetic resonance (NMR). Different chemometric tools based on principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) are proposed for the analysis of the complex data sets generated in the different exposure experiments.... 

    Discrimination of wines based on 2D NMR spectra using learning vector quantization neural networks and partial least squares discriminant analysis

    , Article Analytica Chimica Acta ; Volume 558, Issue 1-2 , 2006 , Pages 144-149 ; 00032670 (ISSN) Masoum, S ; Bouveresse, D. J. R ; Vercauteren, J ; Jalali Heravi, M ; Rutledge, D. N ; Sharif University of Technology
    2006
    Abstract
    The learning vector quantization (LVQ) neural network is a useful tool for pattern recognition. Based on the network weights obtained from the training set, prediction can be made for the unknown objects. In this paper, discrimination of wines based on 2D NMR spectra is performed using LVQ neural networks with orthogonal signal correction (OSC). OSC has been proposed as a data preprocessing method that removes from X information not correlated to Y. Moreover, the partial least squares discriminant analysis (PLS-DA) method has also been used to treat the same data set. It has been found that the OSC-LVQ neural networks method gives slightly better prediction results than OSC-PLS-DA © 2005... 

    Fuzzy C-means clustering for chromatographic fingerprints analysis: A gas chromatography-mass spectrometry case study

    , Article Journal of Chromatography A ; Volume 1438 , 2016 , Pages 236-243 ; 00219673 (ISSN) Parastar, H ; Bazrafshan, A ; Sharif University of Technology
    Elsevier 
    Abstract
    Fuzzy C-means clustering (FCM) is proposed as a promising method for the clustering of chromatographic fingerprints of complex samples, such as essential oils. As an example, secondary metabolites of 14 citrus leaves samples are extracted and analyzed by gas chromatography-mass spectrometry (GC-MS). The obtained chromatographic fingerprints are divided to desired number of chromatographic regions. Owing to the fact that chromatographic problems, such as elution time shift and peak overlap can significantly affect the clustering results, therefore, each chromatographic region is analyzed using multivariate curve resolution-alternating least squares (MCR-ALS) to address these problems. Then,...