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Control of the Activated Sludge System Using Neural Network Model Predictive Control
, M.Sc. Thesis Sharif University of Technology ; Shaygan Salek, Jalaloddin (Supervisor)
Abstract
Activated sludge systems are widespread biological wastewater treatment systems that have a very complex and nonlinear dynamics with a wide range of time constants and, as a consequence, are difficult to model and control. On the other hand, using neural networks as function approximators has provided a reliable tool for modeling complex dynamic systems like activated sludge. In this study a multi-input multi-output neural network model predictive controller (NNMPC) is developed and tested based on the basic control strategy of a benchmark simulation model (called BSM1) suggested by european co-operation in the field of science and technical research (COST) actions 682/624. The controller...
New Generation of On-purpose Attacks for Evaluating Digital Image Watermarking Methods by Preserving the Image Quality
, Ph.D. Dissertation Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
Up to now, compared with the comprehensive research for developing robust watermarking algorithms, no equal attention has been devoted to the proposition of benchmarks tailored to assess the watermark robustness. In addition, almost all the state of the art benchmarks only integrate a number of common image processing operations like geometrical transformations to remove watermarks. However, the quality of the processed image is often too degraded to permit further commercial exploitation. Moreover, to the best of our knowledge, the design of these tools does not take into account the statistical properties of the images and watermarks in the design of attacks. In spite of the significant...
Improving CPU-GPU System Performance Through Dynamic Management of LLC and NoC
, M.Sc. Thesis Sharif University of Technology ; Sarbazi Azad, Hamid (Supervisor)
Abstract
CPU-GPU Heterogeneous System Architectures (HSA) play an important role in today's computing systems. Because of fast-growing in technology and the necessity of high-performance computing, HSAs are widely used platforms. Integrating the multi-core Central Processing Unit (CPU) with many-core Graphics Processing Unit (GPU) on the same die combines the feature of both processors and providing better performance. The capacity of HSAs to provide high throughput of computing led to the widespread use of these systems. Besides the high performance of HSAs, we also face challenges. These challenges are caused by the use of two processors with different behaviors and requirements on the same die....
Single-Cell RNA-seq Dropout Imputation and Noise Reduction by Machine Learning
, M.Sc. Thesis Sharif University of Technology ; Soleymani Baghshah, Mahdih (Supervisor) ; Sharifi Zarchi, Ali (Supervisor) ; Goodarzi, Hani (Co-Supervisor)
Abstract
Single-cell RNA sequencing (scRNA-seq) technologies have empowered us to study gene expressions at the single-cell resolution. These technologies are developed based on barcoding of single cells and sequencing of transcriptome using next-generation sequencing technologies. Achieving this single-cell resolution is specially important when the target population is complex or heterogeneous, which is the case for most biological samples, including tissue samples and tumor biopsies.Single-cell technologies suffer from high amounts of noise and missing values, generally known as dropouts. This complexity can affect a number of key downstream analyses such as differential expression analysis,...
, M.Sc. Thesis Sharif University of Technology ; Bakhshi, Ali (Supervisor)
Abstract
To verify most of the numerical and analytical developments in the structural and earthquake engineering techniques, experimental methods have been considered by many researchers. For instance, numerical simulations in structural health monitoring, structural control and energy dissipation systems need to be verified and compared with experimental results. Consequently, research organizations spend substantial budgets on assessing and updating these experimental methods. Many of these experimental tests are essentially conducted on the benchmark structures with specific technical characteristics; these properties should not be changed after each experiment. Therefore, the tests on these...
Assessment of cell-centered and cell-vertex finite volume approaches for computation of 2d structural dynamics on arbitrary quadrilateral grids
, Article CMES - Computer Modeling in Engineering and Sciences ; Volume 106, Issue 6 , 2015 , Pages 395-439 ; 15261492 (ISSN) ; Azampour, M. H ; Sharif University of Technology
Tech Science Press
2015
Abstract
In this study, cell-centered (CC) and cell-vertex (CV) finite volume (FV) approaches are applied and assessed for the simulation of two-dimensional structural dynamics on arbitrary quadrilateral grids. For the calculation of boundary nodes displacement in the CC FV approach, three methods are employed. The first method is a simple linear regression of displacement of boundary nodes from the displacement of interior cell centers. In the second method, an extrapolation technique is applied for this purpose and, in the third method; the line boundary cell technique is incorporated into the solution algorithm in an explicit manner. To study the effects of grid irregularity on the results of CC...
Modification of a dynamic monte carlo technique to simplify and accelerate transient analysis with feedback
, Article Nuclear Science and Engineering ; 2021 ; 00295639 (ISSN) ; Salehi, A. A ; Vosoughi, N ; Sharif University of Technology
Taylor and Francis Ltd
2021
Abstract
In this paper, a simpler approach compared to the existing approaches is developed to analyze nuclear reactor dynamics based on the explicit Monte Carlo method. A new population control method is also introduced to prevent neutron population growth and consequent computer memory shortages, which also increases simulation speed. The scheme is applied for time-dependent particle tracking in three-dimensional arbitrary geometries in the presence of feedbacks through a code named MCSP-Explicit. Changes in material density, as well as geometry dimensions, are also considered during simulation. MCSP-Explicit can be run with either continuous or multigroup data libraries, and it is further boosted...
Predictive tri-linear benchmark curve for in-plane behavior of adobe walls
, Article International Journal of Architectural Heritage ; Volume 9, Issue 8 , Nov , 2015 , Pages 986-1004 ; 15583058 (ISSN) ; Bakhshi, A ; Ghannad, M. A ; Yekrangnia, M ; Soumi, F ; Sharif University of Technology
Taylor and Francis Inc
2015
Abstract
In the present study, numerical simulations are conducted to estimate the in-plane response of adobe walls subjected to pseudo-static cyclic loading based on the finite element code ABAQUS. The simplified micro-modeling approach is adopted and an interface model reported in ABAQUS material library is applied as material model for zero-thickness interface elements. The comparison between obtained results and field test data results in good agreement. Parametric studies are carried out to evaluate the effectiveness of independent parameters changes on response of adobe walls. It is noted that mechanical properties of joints and adobe units play an active role on in-plane behavior of walls. A...
Optimal design of truss structures with frequency constraints: a comparative study of DE, IDE, LSHADE, and CMAES algorithms
, Article Engineering with Computers ; 2021 ; 01770667 (ISSN) ; Mesbahi, P ; Moosavian, N ; Daliri, H ; Sharif University of Technology
Springer Science and Business Media Deutschland GmbH
2021
Abstract
The present study examines the performance of three powerful methods including the original differential evolution (DE), the improved differential evolution (IDE), and the winner of the CEC-2014 competition, LSHADE, in addition to the covariance matrix adaptation evolution strategy (CMAES) for size optimization of truss structures under natural frequency constraints. Despite the abundant researches on novel meta-heuristic algorithms in the literature, the application of CMAES, one of the most powerful and reliable optimization algorithms, on the optimal solution of the truss structures has received scant attention. For consistent comparison between these algorithms, four stopping criteria...
A weighting scheme for mining key skeletal joints for human action recognition
, Article Multimedia Tools and Applications ; Volume 78, Issue 22 , 2019 , Pages 31319-31345 ; 13807501 (ISSN) ; Naghsh Nilchi, A. R ; Kasaei, S ; Sharif University of Technology
Springer New York LLC
2019
Abstract
A novel class-dependent joint weighting method is proposed to mine the key skeletal joints for human action recognition. Existing deep learning methods or those based on hand-crafted features may not adequately capture the relevant joints of different actions which are important to recognize the actions. In the proposed method, for each class of human actions, each joint is weighted according to its temporal variations and its inherent ability in extension or flexion. These weights can be used as a prior knowledge in skeletal joints-based methods. Here, a novel human action recognition algorithm is also proposed in order to use these weights in two different ways. First, for each frame of a...
ShEMO: a large-scale validated database for persian speech emotion detection
, Article Language Resources and Evaluation ; 2018 ; 1574020X (ISSN) ; Jamshid Lou, P ; Karami, M ; Sharif University of Technology
Springer Netherlands
2018
Abstract
This paper introduces a large-scale, validated database for Persian called Sharif Emotional Speech Database (ShEMO). The database includes 3000 semi-natural utterances, equivalent to 3 h and 25 min of speech data extracted from online radio plays. The ShEMO covers speech samples of 87 native-Persian speakers for five basic emotions including anger, fear, happiness, sadness and surprise, as well as neutral state. Twelve annotators label the underlying emotional state of utterances and majority voting is used to decide on the final labels. According to the kappa measure, the inter-annotator agreement is 64% which is interpreted as “substantial agreement”. We also present benchmark results...
ShEMO: a large-scale validated database for Persian speech emotion detection
, Article Language Resources and Evaluation ; Volume 53, Issue 1 , 2019 ; 1574020X (ISSN) ; Jamshid Lou, P ; Karami, M ; Sharif University of Technology
Springer Netherlands
2019
Abstract
This paper introduces a large-scale, validated database for Persian called Sharif Emotional Speech Database (ShEMO). The database includes 3000 semi-natural utterances, equivalent to 3 h and 25 min of speech data extracted from online radio plays. The ShEMO covers speech samples of 87 native-Persian speakers for five basic emotions including anger, fear, happiness, sadness and surprise, as well as neutral state. Twelve annotators label the underlying emotional state of utterances and majority voting is used to decide on the final labels. According to the kappa measure, the inter-annotator agreement is 64% which is interpreted as “substantial agreement”. We also present benchmark results...
Offshore wind farm layout optimization using particle swarm optimization
, Article Journal of Ocean Engineering and Marine Energy ; Volume 4, Issue 1 , 2018 , Pages 73-88 ; 21986444 (ISSN) ; Chick, J ; Johanning, L ; Khorasanchi, M ; Sharif University of Technology
Springer International Publishing
2018
Abstract
This article explores the application of a wind farm layout optimization framework using a particle swarm optimizer to three benchmark test cases. The developed framework introduces an increased level of detail characterizing the impact that the wind farm layout can have on the levelized cost of energy by modelling the wind farm’s electrical infrastructure, annual energy production, and cost as functions of the wind farm layout. Using this framework, this paper explores the application of a particle swarm optimizer to the wind farm layout optimization problem considering three different levels of wind farm constraint faced by modern wind farm developers. The particle swarm optimizer is found...
A Lagrangian relaxation for a fuzzy random EPQ Problem with Shortages and Redundancy Allocation: Two Tuned Meta-heuristics
, Article International Journal of Fuzzy Systems ; Volume 20, Issue 2 , 2018 , Pages 515-533 ; 15622479 (ISSN) ; Niaki, S. T. A ; Malekian, M. R ; Wang, Y ; Sharif University of Technology
Springer Berlin Heidelberg
2018
Abstract
This paper develops an economic production quantity model for a multi-product multi-objective inventory control problem with fuzzy-stochastic demand and backorders. In this model, the annual demand is represented by trapezoidal fuzzy random numbers. The centroid defuzzification and the expected value methods are applied to defuzzify and make decisions in a random environment. In the case where the warehouse space is limited, the Lagrangian relaxation procedure is first employed to determine the optimal order and the maximum backorder quantities of the products such that the total inventory cost is minimized. The optimal solution obtained by the proposed approach is compared with that...
A new hybrid algorithm to solve bound-constrained nonlinear optimization problems
, Article Neural Computing and Applications ; Volume 32, Issue 16 , 2020 , Pages 12427-12452 ; Rahman, M. S ; Shaikh, A. A ; Akhavan Niaki, S. T ; Bhunia, A. K ; Sharif University of Technology
Springer
2020
Abstract
The goal of this work is to propose a hybrid algorithm called real-coded self-organizing migrating genetic algorithm by combining real-coded genetic algorithm (RCGA) and self-organizing migrating algorithm (SOMA) for solving bound-constrained nonlinear optimization problems having multimodal continuous functions. In RCGA, exponential ranking selection, whole-arithmetic crossover and non-uniform mutation operations have been used as different operators where as in SOMA, a modification has been done. The performance of the proposed hybrid algorithm has been tested by solving a set of benchmark optimization problems taken from the existing literature. Then, the simulated results have been...
Designing a MapReduce performance model in distributed heterogeneous platforms based on benchmarking approach
, Article Journal of Supercomputing ; Volume 76, Issue 9 , 2020 , Pages 7177-7203 ; Movaghar, A ; Reshadi, M ; Khademzadeh, A ; Sharif University of Technology
Springer
2020
Abstract
MapReduce framework is an effective method for big data parallel processing. Enhancing the performance of MapReduce clusters, along with reducing their job execution time, is a fundamental challenge to this approach. In fact, one is faced with two challenges here: how to maximize the execution overlap between jobs and how to create an optimum job scheduling. Accordingly, one of the most critical challenges to achieving these goals is developing a precise model to estimate the job execution time due to the large number and high volume of the submitted jobs, limited consumable resources, and the need for proper Hadoop configuration. This paper presents a model based on MapReduce phases for...
Medical image magnification based on original and estimated pixel selection models
, Article Journal of Biomedical Physics and Engineering ; Volume 10, Issue 3 , 2020 , Pages 357-366 ; Khosravi, M. R ; Khosravi, B ; Halvaee, P ; Sharif University of Technology
Shiraz University of Medical Sciences
2020
Abstract
Background: The issue of medial image resolution enhancement is one of the most important topics for medical imaging that helps improve the performance of many post-processing aspects like classification and segmentation towards medical diagnosis. Objective: Our aim in this paper is to evaluate different types of pixel selection models in terms of pixel originality in medical image reconstruction problems. A previous investigation showed that selecting far original pixels has highly better performance than using near unoriginal/estimated pixels while magnifying some benchmarks in digital image processing. Material and Methods: In our technical study, we apply two classical inter-polators,...
Estimating the parameters of mixed shifted negative binomial distributions via an EM algorithm
, Article Scientia Iranica ; Volume 26, Issue 1E , 2019 , Pages 571-586 ; 10263098 (ISSN) ; Akhavan Tabatabaei, R ; Salmasi, N ; Modarres, M ; Sharif University of Technology
Sharif University of Technology
2019
Abstract
Discrete Phase-Type (DPH) distributions have one property that is not shared by Continuous Phase-Type (CPH) distributions, i.e., representing a deterministic value as a DPH random variable. This property distinguishes the application of DPH in stochastic modeling of real-life problems, such as stochastic scheduling, in which service time random variables should be compared with a deadline that is usually a constant value. In this paper, we consider a restricted class of DPH distributions, called Mixed Shifted Negative Binomial (MSNB), and show its flexibility in producing a wide range of variances as well as its adequacy in fitting fat-tailed distributions. These properties render MSNB...
Estimating the parameters of mixed shifted negative binomial distributions via an EM algorithm
, Article Scientia Iranica ; Volume 26, Issue 1E , 2019 , Pages 571-586 ; 10263098 (ISSN) ; Akhavan Tabatabaei, R ; Salmasi, N ; Modarres, M ; Sharif University of Technology
Sharif University of Technology
2019
Abstract
Discrete Phase-Type (DPH) distributions have one property that is not shared by Continuous Phase-Type (CPH) distributions, i.e., representing a deterministic value as a DPH random variable. This property distinguishes the application of DPH in stochastic modeling of real-life problems, such as stochastic scheduling, in which service time random variables should be compared with a deadline that is usually a constant value. In this paper, we consider a restricted class of DPH distributions, called Mixed Shifted Negative Binomial (MSNB), and show its flexibility in producing a wide range of variances as well as its adequacy in fitting fat-tailed distributions. These properties render MSNB...
Numerical simulation using a modified solver within OpenFOAM for compressible viscous flows
, Article European Journal of Computational Mechanics ; Volume 28, Issue 6 , 2020 , Pages 541-572 ; Salehi, A. A ; Keshtkar, A ; Shadman, M. M ; Askari, M. H ; Sharif University of Technology
River Publishers
2020
Abstract
In this work, we attempted to develop an Implicit Coupled Density-Based (ICDB) solver using LU-SGS algorithm based on the AUSM+ up scheme in OpenFOAM. Then sonicFoam solver was modified to include viscous dissipation in order to improve its capability to capture shock wave and aerothermal variables. The details of the ICDB solver as well as key implementation details of the viscous dissipation to energy equation were introduced. Finally, two benchmark tests of hypersonic airflow over a flat plate and a 2-D cylinder were simulated to show the accuracy of ICDB solver. To verify and validate the ICDB solver, the obtained results were compared with other published experimental data. It was...