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hierarchical-structures
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Hybrid Multilayer Evolutionary Algorithms and Its Applications in Optimization
, M.Sc. Thesis Sharif University of Technology ; Bagheri Shouraki, Saeed (Supervisor)
Abstract
Evolutionary algorithms have gradually established a strong foothold as powerful search methods and have been widely applied to solve problems in many disciplines. By the way the performance of these algorithms in hierarchical applications is not satisfying. In order to improve the performance and applicability, numerous sophisticated mechanisms have been introduced and integrated into EAs. In this thesis we have tried to implement a multilayer evolutionary algorithm in order to overcome the problem. The practical results show this improvement any various aspects.
Simulation of the Self-organized Critical Models on the
Human’s Brain Network
,
M.Sc. Thesis
Sharif University of Technology
;
Moghimi Araghi, Saman
(Supervisor)
Abstract
Self-organized critical phenomena are interesting phenomena which are ubiquitous in nature. Examples include mountain ranges , coastlines and also activities in the hu-man's brain. In these processes, without fine-tuning of any external parameter such as the temperature, the system exhibits critical behavior. In other words, the dynamics of the system, drives it towards an state in which long range correlations in space and scaling behaviors can be seen.The first successful model which could characterize such systems was BTW model, introduced by Bak , Tang and Wiesenfeld in 1987. This model, later named Abelian sandpile model, was very simple and because of this simplicity, a large amount of...
Portfolio Management: Combining Hierarchical Models with Prior Hierarchical Structure
, M.Sc. Thesis Sharif University of Technology ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
Abstract
I investigate methods of integrating prior hierarchical structure into hierarchical portfolio optimization methods. My contributions to the literature are forming a prior hierarchical structure based on investors' priorities and generating a unique representative distance matrix, which can be used as an input to other portfolio optimization methods too. In addition, I use SIC and GICs industry classifications as priory information for S&P500 companies and use them as a complementary input to the Hierarchical Risk Parity model and Hierarchical Equal Risk Contribution and compare the resultant portfolios' performance with (López de Prado, 2019)’s method of integrating prior information and...
Multi-Scale Numerical Modeling of Two Phase Flow over Flexible Surface Micro-Structures
, Ph.D. Dissertation Sharif University of Technology ; Javadi, Khodayar (Supervisor)
Abstract
The present thesis investigates the micro-droplet dynamics in an inclined channel covered with flexible structures. For this purpose, the DPD (dissipative particle dynamics) method is used to study the behavior of particles present in the flow, including the droplet, the fluid around the droplet, and polymeric structures. This model leads to a more accurate representation of flow hydrodynamics and indicates the way for exploring and understanding complex fluid properties in real flows. The first part of the thesis deals with the dynamics of rising bubbles attached to a vertical wall under different wettability conditions. Even though bubbles rising freely in a liquid have extensively been...
Image Categorization Using Deep Learning
, M.Sc. Thesis Sharif University of Technology ; Jafari Siavoshani, Mahdi (Supervisor) ; Rabiee, Hamid Reza (Co-Advisor)
Abstract
The representation of data influences the explanation factors of data variations. Thus,the success of learner algorithms depends on the data representation. Our main contribution in this thesis is learning of high level and abstract representation using deep structure. One of the fundamental examples of representation learning is the AutoEncoders. The auto-encoder is a rigid framework that doesn’t consider explanation factors in terms of statistical concepts. So, the auto-encoders can be re-interpreted by seeing the decoder as the statistical model of interest. The role of encoder is a mechanism for inference in the model described by the decoder. Our purpose is to design such model with...
Two-level Robust Control of Large-scale Systems
,
Ph.D. Dissertation
Sharif University of Technology
;
Sadati, Naser
(Supervisor)
Abstract
In this thesis, two-level optimal control of uncertain and non-uncertain large-scale systems is presented. In the proposed two-level approach, using a decomposition/coordination framework, the large-scale system is first decomposed into several interactive subsystems, at the first-level, where a smaller optimization problem is solved at each subsystem. At the second-level, a substitution type prediction method, as a coordination strategy, is used to predict the interaction between subsystems. The coordinator mainly evaluates the next update for the coordination parameters and continues to exchange information with the first-level, so that the overall optimum solution is obtained. It is shown...
A graph-theoretic approach toward autonomous skill acquisition in reinforcement learning
, Article Evolving Systems ; Volume 9, Issue 3 , 2018 , Pages 227-244 ; 18686478 (ISSN) ; Taghizadeh, N ; Beigy, H ; Sharif University of Technology
Springer Verlag
2018
Abstract
Hierarchical reinforcement learning facilitates learning in large and complex domains by exploiting subtasks and creating hierarchical structures using these subtasks. Subtasks are usually defined through finding subgoals of the problem. Providing mechanisms for autonomous subgoal discovery and skill acquisition is a challenging issue in reinforcement learning. Among the proposed algorithms, a few of them are successful both in performance and also efficiency in terms of the running time of the algorithm. In this paper, we study four methods for subgoal discovery which are based on graph partitioning. The idea behind the methods proposed in this paper is that if we partition the transition...
A lightweight hierarchical authentication scheme for internet of things
, Article Journal of Ambient Intelligence and Humanized Computing ; 2018 , Pages 1-13 ; 18685137 (ISSN) ; Bayat, M ; Zahednejad, B ; Payandeh, A ; Aref, M. R ; Sharif University of Technology
Springer Verlag
2018
Abstract
The Internet of Things (IoT) technology enables numerous things with different processing power and storage capacity to communicate and share data with each other. Considering the constrained devices of the IoT network in terms of processing and storage, designing a lightweight authentication scheme is quite important. So in this paper, we propose a lightweight authentication scheme based on Chebyshev Chaotic Maps. In the proposed scheme we apply a hierarchical structure to define different access controls for various entities. We then provide a formal analysis via the BAN logic to show the security of our scheme. Moreover, we compare our proposed scheme with previous ones in terms of...
A lightweight hierarchical authentication scheme for internet of things
, Article Journal of Ambient Intelligence and Humanized Computing ; Volume 10, Issue 7 , 2019 , Pages 2607-2619 ; 18685137 (ISSN) ; Bayat, M ; Zahednejad, B ; Payandeh, A ; Aref, M. R ; Sharif University of Technology
Springer Verlag
2019
Abstract
The Internet of Things (IoT) technology enables numerous things with different processing power and storage capacity to communicate and share data with each other. Considering the constrained devices of the IoT network in terms of processing and storage, designing a lightweight authentication scheme is quite important. So in this paper, we propose a lightweight authentication scheme based on Chebyshev Chaotic Maps. In the proposed scheme we apply a hierarchical structure to define different access controls for various entities. We then provide a formal analysis via the BAN logic to show the security of our scheme. Moreover, we compare our proposed scheme with previous ones in terms of...
Detection of Apnea Bradycardia from ECG Signals of Preterm Infants Using Layered Hidden Markov Model
, Article Annals of Biomedical Engineering ; Volume 49, Issue 9 , 2021 , Pages 2159-2169 ; 00906964 (ISSN) ; Shamsollahi, M. B ; Fatemizadeh, E ; Beuchée, A ; Hernández, A. I ; Montazeri Ghahjaverestan, N ; Sharif University of Technology
Springer
2021
Abstract
Apnea-bradycardia (AB) is a common complication in prematurely born infants, which is associated with reduced survival and neurodevelopmental outcomes. Thus, early detection or predication of AB episodes is critical for initiating preventive interventions. To develop automatic real-time operating systems for early detection of AB, recent advances in signal processing can be employed. Hidden Markov Models (HMM) are probabilistic models with the ability of learning different dynamics of the real time-series such as clinical recordings. In this study, a hierarchy of HMMs named as layered HMM was presented to detect AB episodes from pre-processed single-channel Electrocardiography (ECG). For...
Three-dimensional bioprinting of functional skeletal muscle tissue using gelatin methacryloyl-alginate bioinks
, Article Micromachines ; Volume 10, Issue 10 , 2019 ; 2072666X (ISSN) ; Çelebi Saltik, B ; Barros, N ; Nasiri, R ; Banton, E ; Shamloo, A ; Ashammakhi, N ; Dokmeci, M. R ; Ahadian, S ; Sharif University of Technology
MDPI AG
2019
Abstract
Skeletal muscle tissue engineering aims to fabricate tissue constructs to replace or restore diseased or injured skeletal muscle tissues in the body. Several biomaterials and microscale technologies have been used in muscle tissue engineering. However, it is still challenging to mimic the function and structure of the native muscle tissues. Three-dimensional (3D) bioprinting is a powerful tool to mimic the hierarchical structure of native tissues. Here, 3D bioprinting was used to fabricate tissue constructs using gelatin methacryloyl (GelMA)-alginate bioinks. Mechanical and rheological properties of GelMA-alginate hydrogels were characterized. C2C12 myoblasts at the density 8 × 106 cells/mL...
Photoelectrochemical water-splitting using CuO-Based electrodes for hydrogen production: a review
, Article Advanced Materials ; Volume 33, Issue 33 , 2021 ; 09359648 (ISSN) ; Hosseini Hosseinabad, S. M ; Masudy Panah, S ; Seza, A ; Jalali, M ; Fallah Arani, H ; Dabir, F ; Gholipour, S ; Abdi, Y ; Bagheri Hariri, M ; Riahi Noori, N ; Lim, Y. F ; Hagfeldt, A ; Saliba, M ; Sharif University of Technology
John Wiley and Sons Inc
2021
Abstract
The cost-effective, robust, and efficient electrocatalysts for photoelectrochemical (PEC) water-splitting has been extensively studied over the past decade to address a solution for the energy crisis. The interesting physicochemical properties of CuO have introduced this promising photocathodic material among the few photocatalysts with a narrow bandgap. This photocatalyst has a high activity for the PEC hydrogen evolution reaction (HER) under simulated sunlight irradiation. Here, the recent advancements of CuO-based photoelectrodes, including undoped CuO, doped CuO, and CuO composites, in the PEC water-splitting field, are comprehensively studied. Moreover, the synthesis methods,...
Graphic: Graph-based hierarchical clustering for single-molecule localization microscopy
, Article 18th IEEE International Symposium on Biomedical Imaging, ISBI 2021, 13 April 2021 through 16 April 2021 ; Volume 2021-April , 2021 , Pages 1892-1896 ; 19457928 (ISSN); 9781665412469 (ISBN) ; Aziznejad, S ; Unser, M ; Sage, D ; Sharif University of Technology
IEEE Computer Society
2021
Abstract
We propose a novel method for the clustering of point-cloud data that originate from single-molecule localization microscopy (SMLM). Our scheme has the ability to infer a hierarchical structure from the data. It takes a particular relevance when quantitatively analyzing the biological particles of interest at different scales. It assumes a prior neither on the shape of particles nor on the background noise. Our multiscale clustering pipeline is built upon graph theory. At each scale, we first construct a weighted graph that represents the SMLM data. Next, we find clusters using spectral clustering. We then use the output of this clustering algorithm to build the graph in the next scale; in...
Tunable microwave absorption features in bi-layer absorber based on mesoporous CuS micro-particle with 3D hierarchical structure and nanosphere like NiCo2O4
, Article Ceramics International ; Volume 48, Issue 7 , 2022 , Pages 9146-9156 ; 02728842 (ISSN) ; Dai, F ; Mouldi, A ; Bouallegue, B ; Akhtar, M. N ; Sharif University of Technology
Elsevier Ltd
2022
Abstract
There has been a growing demand for materials with superior absorption capabilities, such as strong absorbing capacity, thin thickness, and light weight, to solve challenges related to EM radiation pollution. While the majority of the research is focused on optimizing material compositions, component microstructure and absorber structure are also critical factors for improving microwave absorption performance. In this research, we show how the microstructure of components and absorber design may increase dissipation features. Solvothermal and hydrothermal methods were utilized for synthesizing mesoporous CuS micro-particles with a 3D hierarchical structure as a dielectric component and...
Micromechanics and constitutive modeling of connective soft tissues
, Article Journal of the Mechanical Behavior of Biomedical Materials ; Volume 60 , 2016 , Pages 157-176 ; 17516161 (ISSN) ; Ahmadian, M. T ; Firozbakhsh, K ; Aghdam, M. M ; Sharif University of Technology
Elsevier Ltd
Abstract
In this paper, a micromechanical model for connective soft tissues based on the available histological evidences is developed. The proposed model constituents i.e. collagen fibers and ground matrix are considered as hyperelastic materials. The matrix material is assumed to be isotropic Neo-Hookean while the collagen fibers are considered to be transversely isotropic hyperelastic. In order to take into account the effects of tissue structure in lower scales on the macroscopic behavior of tissue, a strain energy density function (SEDF) is developed for collagen fibers based on tissue hierarchical structure. Macroscopic response and properties of tissue are obtained using the numerical...
A novel superhydrophilic/superoleophobic nanocomposite PDMS-NH2/PFONa-SiO2 coated-mesh for the highly efficient and durable separation of oil and water
, Article Surface and Coatings Technology ; Volume 394 , 2020 ; Siavash Moakhar, R ; Dolati, A ; Sharif University of Technology
Elsevier B.V
2020
Abstract
A surface to separate oil–water mixtures is a global concern and highly needed particularly in oil industries. The present study was conducted to create a novel superhydrophilic/superoleophobic nanocomposite coating on the stainless-steel mesh for the aim of oil/water separation. Different hydrophilic resins along with PFOA as oleophobic agent with 15 flours in its chemical structure and various oxide nanoparticles containing SiO2 and TiO2 at different concentrations were studied to achieve superhydrophilic/superoleophobic surface. The fabricated nanocomposites were fully characterized via field-emission scanning microscopy (FESEM), atomic force microscopy (AFM) and Fourier-transform...
Preparation and characterization of superhydrophobic and highly oleophobic FEVE-SiO2 nanocomposite coatings
, Article Progress in Organic Coatings ; Volume 138 , 2020 ; Dolati, A ; Sharif University of Technology
Elsevier B.V
2020
Abstract
Here, an excellent superhydrophobic and highly oleophobic nanocomposite coating composed of fluoroethylene-vinyl ether (FEVE) resin as a matrix for modified SiO2 nanoparticles was synthesized on a stainless-steel wire mesh substrate via a facile sol-gel method. The surface morphology, microstructure, composition, and roughness of the coatings were investigated by field emission scanning electron microscopy (FESEM) equipped with energy-dispersive spectroscopy (EDS) and atomic force microscopy (AFM). The most efficient coating with superhydrophobicity and high oleophobicity feature indicates the water and oil repellency with contact angles (CAs) of 152° and 141°, respectively, with the high...
Influence of new superhydrophobic micro-structures on delaying ice formation
, Article Colloids and Surfaces A: Physicochemical and Engineering Aspects ; Volume 595 , 2020 ; Taeibi Rahni, M ; Javadi, K ; Davoudian, S. H ; Miller, R ; Sharif University of Technology
Elsevier B.V
2020
Abstract
Drop motion on different types of new proposed micro-structure surfaces has been numerically investigated to find the optimum structure in view point of ice formation delaying. The droplet automatically moves on the inclined surfaces due to gravity forces. To validate the numerical algorithm, three different bench mark problems have been considered. The results indicate that the present algorithm is trustable for the presented numerical simulations. Then the validated numerical approach has been used to simulate droplet motion on nine proposed superhydrophobic surfaces in the same conditions. Comparison the drop motion on different micro-structure surfaces at different time indicate that...
Highly concurrent latency-tolerant register files for GPUs
, Article ACM Transactions on Computer Systems ; Volume 37, Issue 1-4 , 2021 ; 07342071 (ISSN) ; Mirhosseini, A ; Hajiabadi, A ; Ehsani, S. B ; Falahati, H ; Sarbazi Azad, H ; Drumond, M ; Falsafi, B ; Ausavarungnirun, R ; Mutlu, O ; Sharif University of Technology
Association for Computing Machinery
2021
Abstract
Graphics Processing Units (GPUs) employ large register files to accommodate all active threads and accelerate context switching. Unfortunately, register files are a scalability bottleneck for future GPUs due to long access latency, high power consumption, and large silicon area provisioning. Prior work proposes hierarchical register file to reduce the register file power consumption by caching registers in a smaller register file cache. Unfortunately, this approach does not improve register access latency due to the low hit rate in the register file cache. In this article, we propose the Latency-Tolerant Register File (LTRF) architecture to achieve low latency in a two-level hierarchical...
Flexible polymeric tail for micro robot drag reduction bioinspired by the nature microorganisms
, Article Physics of Fluids ; Volume 34, Issue 11 , 2022 ; 10706631 (ISSN) ; Javadi, K ; Sharif University of Technology
American Institute of Physics Inc
2022
Abstract
In nature, most microorganisms have flexible micro/nanostructure tails, which help them create propulsion, reduce drag, or search for food. Previous studies investigated these flexible structures mostly from the propulsion creation perspective. However, the drag reduction and the underlying physical mechanisms of such tails are less known. This scientific gap is more significant when multi-polymeric/hierarchical structures are used. To fill the gap, we use the dissipative particle dynamics (DPD) method as a powerful fluid-polymer interaction technique to study the flexible tails' influences on drag reduction. Note that the flow regime for these microorganisms is in the range of laminar low...