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    Reservoir Characterization and Parameter Estimation Using Ensemble Kalman Filter

    , M.Sc. Thesis Sharif University of Technology Ebrahimkhani, Mohammad Javad (Author) ; Pishvaei, Mahmood Reza (Supervisor) ; Bozorgmehri Boozarjmehri, Ramin (Supervisor)
    Management decisions, enhanced oil recovery, and reservoir development plans in petroleum industries are based on predictions by reservoir simulation. Due to uncertainties in model parameters or engineering assumptions, the simulation results are not accurate, while they are correct. For more accurate estimation of unknown production quantities, it is required to characterize the unknown parameters and its uncertainty. By using static data alone the result of characterization is unreliable and unsure, therefore dynamic data use practically. In reservoir engineering literature, this is called “History Matching”.The ensemble Kalman filter is an optimal recursive data processing algorithm based... 

    1H NMR based metabolic profiling in Crohn's disease by random forest methodology

    , Article Magnetic Resonance in Chemistry ; Vol. 52, issue. 7 , July , 2014 , p. 370-376 Fathi, F ; Majari-Kasmaee, L ; Mani-Varnosfaderani, A ; Kyani, A ; Rostami-Nejad, M ; Sohrabzadeh, K ; Naderi, N ; Zali, M. R ; Rezaei-Tavirani, M ; Tafazzoli, M ; Arefi-Oskouie, A ; Sharif University of Technology
    The present study was designed to search for metabolic biomarkers and their correlation with serum zinc in Crohn's disease patients. Crohn's disease (CD) is a form of inflammatory bowel disease that may affect any part of the gastrointestinal tract and can be difficult to diagnose using the clinical tests. Thus, introduction of a novel diagnostic method would be a major step towards CD treatment.Proton nuclear magnetic resonance spectroscopy ( 1H NMR) was employed for metabolic profiling to find out which metabolites in the serum have meaningful significance in the diagnosis of CD. CD and healthy subjects were correctly classified using random forest methodology. The classification model for... 

    Attenuated asymmetry of functional connectivity in schizophrenia: A high-resolution EEG study

    , Article Psychophysiology ; Volume 47, Issue 4 , Jul , 2010 , Pages 706-716 ; 00485772 (ISSN) Jalili, M ; Meuli, R ; Do, K. Q ; Hasler, M ; Crow, T. J ; Knyazeva, M. G ; Sharif University of Technology
    The interhemispheric asymmetries that originate from connectivity-related structuring of the cortex are compromised in schizophrenia (SZ). Under the assumption that such abnormalities affect functional connectivity, we analyzed its correlate - EEG synchronization - in SZ patients and matched controls. We applied multivariate synchronization measures based on Laplacian EEG and tuned to various spatial scales. Compared to the controls who had rightward asymmetry at a local level (EEG power), rightward anterior and leftward posterior asymmetries at an intraregional level (1st and 2nd order S-estimator), and rightward global asymmetry (hemispheric S-estimator), SZ patients showed generally... 

    Wavelet packet decomposition of a new filter -based on underlying neural activity- for ERP classification

    , Article 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07, Lyon, 23 August 2007 through 26 August 2007 ; 2007 , Pages 1876-1879 ; 05891019 (ISSN) ; 1424407885 (ISBN); 9781424407880 (ISBN) Raiesdana, S ; Shamsollahi, M. B ; Hashemi, M. R ; Rezazadeh, I ; Sharif University of Technology
    This paper introduces a wavelet packet algorithm based on a new wavelet like filter created by a neural mass model in place of wavelet. The hypothesis is that the performance of an ERP based BCI system can be improved by choosing an optimal wavelet derived from underlying mechanism of ERPs. The wavelet packet transform has been chosen for its generalization in comparison to wavelet. We compared the performance of proposed algorithm with existing standard wavelets as Db4, Bior4.4 and Coif3 in wavelet packet platform. The results showed a lowest cross validation error for the new filter in classification of two different kinds of ERP datasets via a SVM classifier. © 2007 IEEE  

    Re-construction of the shut-down PM10 monitoring stations for the reliable assessment of PM10 in Berlin using fuzzy modelling and data transformation

    , Article Environmental Monitoring and Assessment ; Volume 189, Issue 3 , 2017 ; 01676369 (ISSN) Taheri Shahraiyni, H ; Sodoudi, S ; Kerschbaumer, A ; Cubasch, U ; Sharif University of Technology
    Springer International Publishing  2017
    A dense monitoring network is vital for the reliable assessment of PM10 in different parts of an urban area. In this study, a new idea is employed for the re-construction of the 20 shut-down PM10 monitoring stations of Berlin. It endeavours to find the non-linear relationship between the hourly PM10 concentration of both the still operating and the shut-down PM10 monitoring stations by using a fuzzy modelling technique, called modified active learning method (MALM). In addition, the simulations were performed by using not only raw PM10 databases but also log-transformed PM10 databases for skewness reduction. According to the results of hourly PM10 simulation (root mean square error about... 

    The power of environmental observatories for advancing multidisciplinary research, outreach, and decision support: the case of the minnesota river basin

    , Article Water Resources Research ; Volume 55, Issue 4 , 2019 , Pages 3576-3592 ; 00431397 (ISSN) Gran, K. B ; Dolph, C ; Baker, A ; Bevis, M ; Cho, S. J ; Czuba, J. A ; Dalzell, B ; Danesh Yazdi, M ; Hansen, A. T ; Kelly, S ; Lang, Z ; Schwenk, J ; Belmont, P ; Finlay, J. C ; Kumar, P ; Rabotyagov, S ; Roehrig, G ; Wilcock, P ; Foufoula Georgiou, E ; Sharif University of Technology
    Blackwell Publishing Ltd  2019
    Observatory-scale data collection efforts allow unprecedented opportunities for integrative, multidisciplinary investigations in large, complex watersheds, which can affect management decisions and policy. Through the National Science Foundation-funded REACH (REsilience under Accelerated CHange) project, in collaboration with the Intensively Managed Landscapes-Critical Zone Observatory, we have collected a series of multidisciplinary data sets throughout the Minnesota River Basin in south-central Minnesota, USA, a 43,400-km2 tributary to the Upper Mississippi River. Postglacial incision within the Minnesota River valley created an erosional landscape highly responsive to hydrologic change,... 

    Multifractal detrended fluctuation analysis of continuous neural time series in primate visual cortex

    , Article Journal of Neuroscience Methods ; Volume 312 , 2019 , Pages 84-92 ; 01650270 (ISSN) Fayyaz, Z ; Bahadorian, M ; Doostmohammadi, J ; Davoodnia, V ; Khodadadian, S ; Lashgari, R ; Sharif University of Technology
    Elsevier B.V  2019
    Background: Local field potential (LFP) recordings have become an important tool to study the activity of populations of neurons. The functional activity of LFPs is usually compared with the activity of neighboring single spike neurons with sampling rates much higher than those of the continuous field potential channel (5 kHz). However, comparison of these signals generated with the lower sampling rate technique is important. New method: In this study, we provide an analysis of extracellular field potential time series using the sophisticated nonlinear multifractal detrended fluctuation analysis (MF-DFA). Using the MF-DFA, we demonstrate that the integral of the singularity spectrum is a... 

    A heuristic method for finding the optimal number of clusters with application In medical data

    , Article 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08, Vancouver, BC, 20 August 2008 through 25 August 2008 ; 2008 , Pages 4684-4687 ; 9781424418152 (ISBN) Bayati, H ; Davoudi, H ; Fatemizadeh, E ; Sharif University of Technology
    IEEE Computer Society  2008
    In this paper, a heuristic method for determining the optimal number of clusters is proposed. Four clustering algorithms, namely K-means, Growing Neural Gas, Simulated Annealing based technique, and Fuzzy C-means in conjunction with three well known cluster validity indices, namely Davies-Bouldin index, Calinski-Harabasz index, Maulik-Bandyopadhyay index, in addition to the proposed index are used. Our simulations evaluate capability of mentioned indices in some artificial and medical datasets. © 2008 IEEE  

    Validation of the revised stressful life event questionnaire using a hybrid model of genetic algorithm and artificial neural networks

    , Article Computational and Mathematical Methods in Medicine ; Volume 2013 , 2013 ; 1748670X (ISSN) Sali, R ; Roohafza, H ; Sadeghi, M ; Andalib, E ; Shavandi, H ; Sarrafzadegan, N ; Sharif University of Technology
    Objectives. Stressors have a serious role in precipitating mental and somatic disorders and are an interesting subject for many clinical and community-based studies. Hence, the proper and accurate measurement of them is very important. We revised the stressful life event (SLE) questionnaire by adding weights to the events in order to measure and determine a cut point. Methods. A total of 4569 adults aged between 18 and 85 years completed the SLE questionnaire and the general health questionnaire-12 (GHQ-12). A hybrid model of genetic algorithm (GA) and artificial neural networks (ANNs) was applied to extract the relation between the stressful life events (evaluated by a 6-point Likert scale)... 

    Optimization of dispersive liquid-liquid microextraction and improvement of detection limit of methyl tert-butyl ether in water with the aid of chemometrics

    , Article Journal of Chromatography A ; Volume 1217, Issue 45 , November , 2010 , Pages 7017-7023 ; 00219673 (ISSN) Karimi, M ; Sereshti, H ; Samadi, S ; Parastar, H ; Sharif University of Technology
    Dispersive liquid-liquid microextraction (DLLME) coupled with gas chromatography-mass spectrometry-selective ion monitoring (GC-MS-SIM) was applied to the determination of methyl tert-butyl ether (MTBE) in water samples. The effect of main parameters affecting the extraction efficiency was studied simultaneously. From selected parameters, volume of extraction solvent, volume of dispersive solvent, and salt concentration were optimized by means of experimental design. The statistical parameters of the derived model were R 2=0.9987 and F=17.83. The optimal conditions were 42.0μL for extraction solvent, 0.30mL for disperser solvent and 5% (w/v) for sodium chloride. The calibration linear range... 

    Towards obtaining more information from gas chromatography-mass spectrometric data of essential oils: An overview of mean field independent component analysis

    , Article Journal of Chromatography A ; Volume 1217, Issue 29 , 2010 , Pages 4850-4861 ; 00219673 (ISSN) Jalali Heravi, M ; Parastar, H ; Sereshti, H ; Sharif University of Technology
    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...