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    Improving data protection in BSS based secure communication: mixing matrix design

    , Article Wireless Networks ; Volume 27, Issue 7 , 2021 , Pages 4747-4758 ; 10220038 (ISSN) Aslani, M. R ; Shamsollahi, M. B ; Nouri, A ; Sharif University of Technology
    Springer  2021
    Abstract
    Abstract: In this paper, a secure and efficient Blind Source Separation (BSS) based cryptosystem is presented. The use of BSS in audio and image cryptography in wireless networks has attracted more attention. A BSS based cryptosystem consists of three main parts: secret data, secret keys, and mixing matrix. In this paper, we propose a new design to create a proper mixing matrix in BSS based cryptosystem. We offer a mathematical criterion to select mixing matrix elements before encryption. The proposed criterion gives a simple way to attach the secret sources to keys, which makes source separation very hard for the adversary. Versus, we show that using the random mixing matrix can lead to... 

    fMRI functional connectivity analysis via kernel graph in Alzheimer’s disease

    , Article Signal, Image and Video Processing ; Volume 15, Issue 4 , 2021 , Pages 715-723 ; 18631703 (ISSN) Ahmadi, H ; Fatemizadeh, E ; Motie Nasrabadi, A ; Sharif University of Technology
    Springer Science and Business Media Deutschland GmbH  2021
    Abstract
    Functional magnetic resonance imaging (fMRI) is an imaging tool that is used to analyze the brain’s functions. Brain functional connectivity analysis based on fMRI signals often calculated correlations among time series in different areas of the brain. For FC analysis most prior research works generate the brain graphs based on linear correlations, however, the nonlinear behavior of the brain can lower the accuracy of such graphs. Usually, the Pearson correlation coefficient is used which has limitations in revealing nonlinear relationships. One of the proper methods for nonlinear analysis is the Kernel trick. This method maps the data into a high dimensional space and calculates the linear... 

    fMRI functional connectivity analysis via kernel graph in Alzheimer’s disease

    , Article Signal, Image and Video Processing ; Volume 15, Issue 4 , 2021 , Pages 715-723 ; 18631703 (ISSN) Ahmadi, H ; Fatemizadeh, E ; Motie-Nasrabadi, A ; Sharif University of Technology
    Springer Science and Business Media Deutschland GmbH  2021
    Abstract
    Functional magnetic resonance imaging (fMRI) is an imaging tool that is used to analyze the brain’s functions. Brain functional connectivity analysis based on fMRI signals often calculated correlations among time series in different areas of the brain. For FC analysis most prior research works generate the brain graphs based on linear correlations, however, the nonlinear behavior of the brain can lower the accuracy of such graphs. Usually, the Pearson correlation coefficient is used which has limitations in revealing nonlinear relationships. One of the proper methods for nonlinear analysis is the Kernel trick. This method maps the data into a high dimensional space and calculates the linear... 

    fMRI functional connectivity analysis via kernel graph in Alzheimer’s disease

    , Article Signal, Image and Video Processing ; 2020 Ahmadi, H ; Fatemizadeh, E ; Motie-Nasrabadi, A ; Sharif University of Technology
    Springer Science and Business Media Deutschland GmbH  2020
    Abstract
    Functional magnetic resonance imaging (fMRI) is an imaging tool that is used to analyze the brain’s functions. Brain functional connectivity analysis based on fMRI signals often calculated correlations among time series in different areas of the brain. For FC analysis most prior research works generate the brain graphs based on linear correlations, however, the nonlinear behavior of the brain can lower the accuracy of such graphs. Usually, the Pearson correlation coefficient is used which has limitations in revealing nonlinear relationships. One of the proper methods for nonlinear analysis is the Kernel trick. This method maps the data into a high dimensional space and calculates the linear... 

    Prediction of the pressure drop for CuO/(Ethylene glycol-water) nanofluid flows in the car radiator by means of Artificial Neural Networks analysis integrated with genetic algorithm

    , Article Physica A: Statistical Mechanics and its Applications ; Volume 546 , 2020 Ahmadi, M. H ; Ghazvini, M ; Maddah, H ; Kahani, M ; Pourfarhang, S ; Pourfarhang, A ; Zeinali Herisg, S ; Sharif University of Technology
    Elsevier B.V  2020
    Abstract
    In this investigation, neural networks were used to predict pressure drop of CuO-based nanofluid in a car radiator. For this purpose, the neural network with the multilayer perceptron structure was used to formulate a model for estimating the pressure drop In this way, different concentrations of copper oxide-based nanofluid were prepared. The base fluid was the mixture of ethylene glycol and pure water (60:40 wt%) which usually used as the cooling fluid in automotive industries. The prepared nanofluid samples were used in a car radiator and the pressure drop of nanofluid flows in the system at different Reynolds were measured. The main purpose of this study was developing the optimized... 

    A new deep convolutional neural network design with efficient learning capability: Application to CT image synthesis from MRI

    , Article Medical Physics ; Volume 47, Issue 10 , 2020 , Pages 5158-5171 Bahrami, A ; Karimian, A ; Fatemizadeh, E ; Arabi, H ; Zaidi, H ; Sharif University of Technology
    John Wiley and Sons Ltd  2020
    Abstract
    Purpose: Despite the proven utility of multiparametric magnetic resonance imaging (MRI) in radiation therapy, MRI-guided radiation treatment planning is limited by the fact that MRI does not directly provide the electron density map required for absorbed dose calculation. In this work, a new deep convolutional neural network model with efficient learning capability, suitable for applications where the number of training subjects is limited, is proposed to generate accurate synthetic computed tomography (sCT) images from MRI. Methods: This efficient convolutional neural network (eCNN) is built upon a combination of the SegNet architecture (a 13-layer encoder-decoder structure similar to the... 

    Developing group contribution models for the estimation of Atmospheric Lifetime and Minimum Ignition Energy

    , Article Chemical Engineering Science ; Volume 226 , 2020 Eini, S ; Jhamb, S ; Sharifzadeh, M ; Rashtchian, D ; Kontogeorgis, G. M ; Sharif University of Technology
    Elsevier Ltd  2020
    Abstract
    The Atmospheric Lifetime (ALT) of a compound represents the potential for the atmospheric accumulation of chemicals. Chemicals with a long lifetime are more resistant to natural decomposition and remain in the environment for a longer period. Minimum Ignition Energy (MIE) is one of the most important properties when evaluating hazardous chemicals. Despite the significance of these environment and safety-related properties, currently, there are no group contribution (GC) models that enable their predictive modeling. The present research aims at filling this gap. To this end, experimental data were collected from literature and the GC model parameters were estimated using the weighted... 

    Adaptive neuro-fuzzy algorithm applied to predict and control multi-phase flow rates through wellhead chokes

    , Article Flow Measurement and Instrumentation ; Volume 76 , 2020 Ghorbani, H ; Wood, D. A ; Mohamadian, N ; Rashidi, S ; Davoodi, S ; Soleimanian, A ; Kiani Shahvand, A ; Mehrad, M ; Sharif University of Technology
    Elsevier Ltd  2020
    Abstract
    A Takagi-Sugeno adaptive neuro-fuzzy inference system (TSFIS) model is developed and applied to a dataset of wellhead flow-test data for the Resalat oil field located offshore southern Iran, the objective is to assist in the prediction and control of multi-phase flow rates of oil and gas through the wellhead chokes. For this purpose, 182 test data points (Appendix 1) related to the Resalat field are evaluated. In order to predict production flow rate (QL) expressed as stock-tank barrels per day (STB/D), this dataset includes four selected input variables: upstream pressure (Pwh); wellhead choke sizes (D64); gas to liquid ratio (GLR); and, base solids and water including some water-soluble... 

    Blood pressure estimation using photoplethysmogram signal and its morphological features

    , Article IEEE Sensors Journal ; Volume 20, Issue 8 , 2020 , Pages 4300-4310 Hasanzadeh, N ; Ahmadi, M. M ; Mohammadzade, H ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Abstract
    In this paper, we present a machine learning model to estimate the blood pressure (BP) of a person using only his photoplethysmogram (PPG) signal. We propose algorithms to better detect some critical points of the PPG signal, such as systolic and diastolic peaks, dicrotic notch and inflection point. These algorithms are applicable to different PPG signal morphologies and improve the precision of feature extraction. We show that the logarithm of dicrotic notch reflection index, the ratio of low-to high-frequency components of heart rate (HR) variability signal, and the product of HR multiplied by the modified Normalized Pulse Volume (mNPV) are the key features in accurately estimating the BP... 

    Interaction of lake-groundwater levels using cross-correlation analysis: A case study of Lake Urmia Basin, Iran

    , Article Science of the Total Environment ; 2020 , Volume 729 Javadzadeh, H ; Ataie Ashtiani, B ; Hosseini, S. M ; Simmons, C. T ; Sharif University of Technology
    Elsevier B.V  2020
    Abstract
    Lake Urmia (LU) is the second largest hypersaline lake in the world. Lake Urmia's water level has dropped drastically from 1277.85 m to 1270.08 m a.s.l (equal to 7.77 m) during the last 20 years, equivalent to a loss of 70% of the lake area. The likelihood of lake-groundwater connection on the basin-scale is uncertain and understudied because of lack of basic data and precise information required for physically-based modeling. In this study, cross-correlation analysis is applied on a various time-frames of water level of the lake and groundwater levels (2001–2018) recorded in 797 observation wells across 17 adjacent aquifers. This provides insightful information on the lake-groundwater... 

    Introducing a response-based duration metric and its correlation with structural damages

    , Article Bulletin of Earthquake Engineering ; Volume 17, Issue 11 , 2019 , Pages 5987-6008 ; 1570761X (ISSN) Mashayekhi, M ; Harati, M ; Ashoori Barmchi, M ; Estekanchi, H. E ; Sharif University of Technology
    Springer Netherlands  2019
    Abstract
    This study proposes a response-based parameter for strong motion duration which is computed for structures and is the total time they are nonlinear during an earthquake. Correlation between structural response and duration for structures, subjected to a set of spectrum matched ground motions, is employed to examine the efficiency of the proposed method. The spectral matching procedure ensures that the influence of amplitude and frequency content of motions on structural response variability is significantly removed. Four concrete building type systems are studied and correlation coefficients of structural response with the proposed duration definition are examined. Comparison of the proposed... 

    Feasibility of imperialist competitive algorithm to predict the surface settlement induced by tunneling

    , Article Engineering with Computers ; Volume 35, Issue 3 , 2019 , Pages 917-923 ; 01770667 (ISSN) Tashayo, B ; Behzadafshar, K ; Soltani Tehrani, M ; Afkhami Banayem, H ; Hashemi, M. H ; Taghavi Nezhad, S. S ; Sharif University of Technology
    Springer London  2019
    Abstract
    Surface settlement is considered as an adverse effect induced by tunneling in the civil projects. This paper proposes the use of the imperialist competitive algorithm (ICA) for predicting the maximum surface settlement (MMS) resulting from the tunneling. For this work, three forms of equations, i.e., linear, quadratic and power are developed and their weights are then optimized/updated with the ICA. The requirement datasets were collected from the line No. 2 of Karaj urban railway, in Iran. In the ICA models, vertical to horizontal stress ratio, cohesion and Young’s modulus, as the effective parameters on the MSS, are adopted as the inputs. The statistical performance parameters such as root... 

    Activated carbon/metal-organic framework nanocomposite: Preparation and photocatalytic dye degradation mathematical modeling from wastewater by least squares support vector machine

    , Article Journal of Environmental Management ; Volume 233 , 2019 , Pages 660-672 ; 03014797 (ISSN) Mahmoodi, N. M ; Abdi, J ; Taghizadeh, M ; Taghizadeh, A ; Hayati, B ; Shekarchi, A. A ; Vossoughi, M ; Sharif University of Technology
    Academic Press  2019
    Abstract
    Herein, Kiwi peel activated carbon (AC), Materials Institute Lavoisier (MIL-88B (Fe), and AC/MIL-88B (Fe) composite were synthesized and used as catalysts to degrade Reactive Red 198. The material properties were analyzed by the FTIR, BET-BJH, XRD, FESEM, EDX, TGA, and UV–Vis/DRS. The BET surface area of AC, MIL-88B (Fe) and AC/MIL-88B (Fe) was 1113.3, 150.7, and 199.4 m2/g, respectively. The band gap values (Eg) estimated by Tauc plot method, were obtained 5.06, 4.19 and 3.79 eV for AC, MIL-88B (Fe) and AC/MIL-88B (Fe), respectively. The results indicated that the AC/MIL-88B (Fe) composite had higher photocatalytic activity (99%) than that of pure AC (79%) and MIL-88B (Fe) catalysts (87%).... 

    Kinetic studies of Bisphenol A in aqueous solutions by enzymatic treatment

    , Article International Journal of Environmental Science and Technology ; Volume 16, Issue 2 , 2019 , Pages 821-832 ; 17351472 (ISSN) Ghobadi Nejad, Z ; Borghei, S. M ; Yaghmaei, S ; Sharif University of Technology
    Center for Environmental and Energy Research and Studies  2019
    Abstract
    Bisphenol A (BPA), which is a major component in the production of various consumer products, is one of the most significant endocrine-disrupting chemicals. In this research, the biocatalytic elimination of Bisphenol A using laccase produced by Phanerochaete chrysosporium was examined and optimized. The response surface methodology was used to study the effect of independent variables such as pH, temperature, initial laccase activity, initial Bisphenol A concentration, and the interactive effects of each variable on the removal of Bisphenol A and residual enzyme activity. Based on response surface plots, the maximum Bisphenol A removal (93%) was detected at a pH value of 8, temperature... 

    Methylene blue removal using modified celery (Apium graveolens) as a low-cost biosorbent in batch mode: Kinetic, equilibrium, and thermodynamic studies

    , Article Journal of Molecular Structure ; Volume 1173 , 2018 , Pages 541-551 ; 00222860 (ISSN) Mohebali, S ; Bastani, D ; Shayesteh, H ; Sharif University of Technology
    Elsevier B.V  2018
    Abstract
    Celery residue modified with H2SO4 was utilized as a low-cost adsorbent for elimination of methylene blue cationic dye from aqueous solution in batch adsorption process. The adsorbent was characterized by Fourier transform infrared (FTIR) spectroscopy and Scanning Electron Microscopy (SEM). The efficacy of dye removal of the modified celery residue (MCR) was verifying by changing adsorbent dose, contact time, pH, initial dye concentration, and temperature. The isotherm models analysis shows that the experimental data can be better demonstrated by Freundlich isotherm model. In order to evaluate the best fit isotherm, three error analysis methods (χ2, ARE and MPSD) as well as correlation... 

    Adaptive neuro-fuzzy inference system approach in bandwidth and mutual coupling analyses of a novel UWB MIMO antenna with notch bands applicable for massive MIMOs

    , Article AEU - International Journal of Electronics and Communications ; Volume 94 , 2018 , Pages 407-417 ; 14348411 (ISSN) Abbasi Layegh, M ; Ghobadi, C ; Nourinia, J ; Samoodi, Y ; Najafi Mashhadi, S ; Sharif University of Technology
    Elsevier GmbH  2018
    Abstract
    A novel UWB MIMO antenna with band-notched characteristic operating in the frequency range between 3.1 GHz and 10.6 GHz is presented. The designed MIMO antenna has two ports and the size of 32×14 mm2 which is fabricated on an FR-4 printed-circuit-board. The feeding system of the proposed antenna is a microstrip line. The two antennas are positioned face to face but laid reversely upon the substrate in order to have a good isolation, less cross polarization, high gain and good envelope correlation coefficient. S-parameters describe the input-output relationship between ports (or terminals) in a MIMO antenna. The effects of the strip feed line width on the variations in reflection coefficient... 

    Feasibility of imperialist competitive algorithm to predict the surface settlement induced by tunneling

    , Article Engineering with Computers ; 2018 ; 01770667 (ISSN) Tashayo, B ; Behzadafshar, K ; Soltani Tehrani, M ; Afkhami Banayem, H ; Hashemi, M. H ; Taghavi Nezhad, S. S ; Sharif University of Technology
    Springer London  2018
    Abstract
    Surface settlement is considered as an adverse effect induced by tunneling in the civil projects. This paper proposes the use of the imperialist competitive algorithm (ICA) for predicting the maximum surface settlement (MMS) resulting from the tunneling. For this work, three forms of equations, i.e., linear, quadratic and power are developed and their weights are then optimized/updated with the ICA. The requirement datasets were collected from the line No. 2 of Karaj urban railway, in Iran. In the ICA models, vertical to horizontal stress ratio, cohesion and Young’s modulus, as the effective parameters on the MSS, are adopted as the inputs. The statistical performance parameters such as root... 

    ECG-derived respiration estimation from single-lead ECG using gaussian process and phase space reconstruction methods

    , Article Biomedical Signal Processing and Control ; Volume 45 , 2018 , Pages 80-90 ; 17468094 (ISSN) Janbakhshi, P ; Shamsollahi, M. B ; Sharif University of Technology
    Elsevier Ltd  2018
    Abstract
    Respiratory activity influences electrocardiographic measurements (ECG) in various ways. Therefore, extraction of respiratory information from ECG, namely ECG-derived respiratory (EDR), can be used as a promising noninvasive method to monitor respiration activity. In this paper, an automatic EDR extraction system using single-lead ECG is proposed. Respiration effects on ECG are categorized into two different models: additive and multiplicative based models. After selection of a proper model for each subject using a proposed criterion, gaussian process (GP) and phase space reconstruction area (PSRArea) are introduced as new methods of EDR extraction for additive and multiplicative models,... 

    Correlation between trunk-pelvis inter-segmental coordination parameters during walking and disability level in chronic low back pain patients

    , Article Journal of Biomedical Physics and Engineering ; Volume 8, Issue 2 , 2018 , Pages 193-202 ; 22517200 (ISSN) Ebrahimi, S ; Kamali, F ; Razeghi, M ; Haghpanah, A ; Sharif University of Technology
    Shiraz University of Medical Sciences  2018
    Abstract
    Background: Chronic low back pain (CLBP) disability has been particularly frustrating because its treatment has been a great therapeutic challenge. Disability has been suggested to depend on different factors that should be found and considered in the medical management. The inter-segmental coordination is often impaired in CLBP subjects; however, to the best of our knowledge, there is no evidence about the relationship between the existence of coordination problems and disability in CLBP patients. Objective: To evaluate the correlation between sagittal plane trunk-pelvis intersegmental coordination parameters during walking and disability level in CLBP patients. Methods: Kinematic data were... 

    Kinetic studies of Bisphenol A in aqueous solutions by enzymatic treatment

    , Article International Journal of Environmental Science and Technology ; Volume 16, Issue 2 , Febraury , 2018 , Pages 821–832 ; 17351472 (ISSN) Ghobadi Nejad, Z ; Borghei, S. M ; Yaghmaei, S ; Sharif University of Technology
    Center for Environmental and Energy Research and Studies  2018
    Abstract
    Bisphenol A (BPA), which is a major component in the production of various consumer products, is one of the most significant endocrine-disrupting chemicals. In this research, the biocatalytic elimination of Bisphenol A using laccase produced by Phanerochaete chrysosporium was examined and optimized. The response surface methodology was used to study the effect of independent variables such as pH, temperature, initial laccase activity, initial Bisphenol A concentration, and the interactive effects of each variable on the removal of Bisphenol A and residual enzyme activity. Based on response surface plots, the maximum Bisphenol A removal (93%) was detected at a pH value of 8, temperature 40...