Search for: hierarchical-structures
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    Simulation of the Self-organized Critical Models on the
    Human’s Brain Network

    , M.Sc. Thesis Sharif University of Technology Shokouhi, Fatemeh (Author) ; Moghimi Araghi, Saman (Supervisor)
    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 Shahryarpoor, Farhad (Author) ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
    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... 

    Two-level Robust Control of Large-scale Systems

    , Ph.D. Dissertation Sharif University of Technology Rahmani, Mehdi (Author) ; Sadati, Naser (Supervisor)
    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... 

    Image Categorization Using Deep Learning

    , M.Sc. Thesis Sharif University of Technology Behfar, Sajad (Author) ; Jafari Siavoshani, Mahdi (Supervisor) ; Rabiee, Hamid Reza (Co-Advisor)
    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... 

    Hybrid Multilayer Evolutionary Algorithms and Its Applications in Optimization

    , M.Sc. Thesis Sharif University of Technology Babaeizadeh, Mohammad (Author) ; Bagheri Shouraki, Saeed (Supervisor)
    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.


    Enforcing access control policies over data stored on untrusted server

    , Article 2017 14th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology, ISCISC 2017, 6 September 2017 through 7 September 2017 ; 2018 , Pages 54-57 ; 9781538665602 (ISBN) Soltani, N ; Jalili, R ; Sharif University of Technology
    One of the security issues in data outsourcing scenario is the enforcement of data owner's access control policies. This includes some challenges; namely, the number of keys required to access authorized resources, efficient policy updating, write access control enforcement, user and data owner overhead, and preserving confidentiality of data and policies. Most of the existing solutions address only some of the challenges, while they impose high overhead on both the data owner and users. Though, policy management in the Role-Based Access Control (RBAC) model is easier and more efficient due to the existence of role hierarchical structure and role inheritance; most of the existing solutions... 

    Photoelectrochemical water-splitting using CuO-Based electrodes for hydrogen production: a review

    , Article Advanced Materials ; Volume 33, Issue 33 , 2021 ; 09359648 (ISSN) Siavash Moakhar, R ; 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
    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,... 

    Three-dimensional bioprinting of functional skeletal muscle tissue using gelatin methacryloyl-alginate bioinks

    , Article Micromachines ; Volume 10, Issue 10 , 2019 ; 2072666X (ISSN) Seyedmahmoud, R ; 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
    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... 

    FTS: An efficient tree structure based tool for searching in large data sets

    , Article ICIME 2010 - 2010 2nd IEEE International Conference on Information Management and Engineering, 16 April 2010 through 18 April 2010 ; Volume 2 , April , 2010 , Pages 294-298 ; 9781424452644 (ISBN) Saejdi Badashian, A ; Najafpour, M ; Mahdavi, M ; Ashurzad Delcheh, M ; Khalkhali, I ; Sharif University of Technology
    This paper addresses the issue of finding and accessing desired items when a large amount of data items are concerned, by proposing some concepts based on Tree Search Structure -a hierarchical structure for information retrieval. The proposed concepts are applicable to several environments such as File Managers on PCs, help tree views, site maps, taxonomies, and cell phones. A software tool, FTS (File Tree Search), that is developed to utilize the proposed concepts is also presented  

    Highly concurrent latency-tolerant register files for GPUs

    , Article ACM Transactions on Computer Systems ; Volume 37, Issue 1-4 , 2021 ; 07342071 (ISSN) Sadrosadati, M ; 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
    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... 

    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) Sadoughi, A ; Shamsollahi, M. B ; Fatemizadeh, E ; Beuchée, A ; Hernández, A. I ; Montazeri Ghahjaverestan, N ; Sharif University of Technology
    Springer  2021
    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... 

    A bio-inspired modular hierarchical structure to plan the sit-to-stand transfer under varying environmental conditions

    , Article Neurocomputing ; Volume 118 , 2013 , Pages 311-321 ; 09252312 (ISSN) Sadeghi, M ; Emadi Andani, M ; Parnianpour, M ; Fattah, A ; Sharif University of Technology
    Human motion planning studies are of considerable importance in producing human-like trajectories for various industrial or clinical applications (e.g. assistive robots). In this case, the capability of Central Nervous System (CNS) in generating a large repertoire of actions can be inspirational to develop more efficient motion planning approaches. Here, inspired by structural and functional modularity in the CNS, a novel modular and hierarchical model is developed to plan the sit-to-stand (STS) transfer under varying environmental conditions. In this model, the planning process is distributed among several functionally simple modules. The cooperation of modules enables the model to plan the... 

    A mixture of modular structures to describe human motor planning level: A new perspective based on motor decomposition

    , Article 2011 18th Iranian Conference of Biomedical Engineering, ICBME 2011 ; 2011 , Pages 199-204 ; 9781467310055 (ISBN) Sadeghi, M ; Andani, M. E ; Fattah, A ; Parnianpour, M ; Sharif University of Technology
    A modular hierarchical structure is developed to describe human movement planning level. The modular feature of the proposed model enables it to generalize planning a task. The movements are planned based on decomposing a task into its corresponding subtasks (motion phases). There is a module responsible for one condition. The final plan is constructed using soft computing of the plans proposed by different modules. Each module estimates the kinematics of the joints at the end of each subtask; we call them kinematic estimator modules (KEMs). A timing module estimates the duration of motion and a gating module determines the responsibility of each KEM under different conditions. To evaluate... 

    Two-level robust optimal control of large-scale nonlinear systems

    , Article IEEE Systems Journal ; Volume 9, Issue 1 , 2015 , Pages 242-251 ; 19328184 (ISSN) Sadati, N ; Rahmani, M ; Saif, M ; Sharif University of Technology
    Finding an optimal control strategy for a nonlinear uncertain system is a challenging problem in the area of nonlinear controller design. In this paper, a two-level control algorithm is developed for robust optimal control of large-scale nonlinear systems. For this purpose, using a decomposition/coordination framework, the large-scale nonlinear system is first decomposed into several smaller subsystems, at the first level, where a closed-form solution as a feedback of states and interactions is obtained to optimize each subsystem. At the second level, a substitution-type prediction method, as a coordination strategy, is used to compensate the nonlinear terms of the system and to predict the... 

    Robust optimal control for large-scale systems with state delay

    , Article Transactions of the Institute of Measurement and Control ; Vol. 36, Issue. 4 , June , 2014 , pp. 551-558 ; ISSN: 01423312 Rahmani, M ; Sadati, N ; Sharif University of Technology
    Optimal control of large-scale uncertain dynamic systems with time delays in states is considered in this paper. For this purpose, a two-level strategy is proposed to decompose the large-scale system into several interconnected subsystems at the first level. Then optimal control inputs are obtained by minimization of convex performance indices in presence of uncertainties, in the form of states and interactions feedback. The solution is achieved by bounded data uncertainty problems, where the uncertainties are only needed to be bounded and it is not required to satisfy the so-called 'matching conditions'. At the second level, a simple substitution-type interaction prediction method is used... 

    Two-level optimal load-frequency control for multi-area power systems

    , Article International Journal of Electrical Power and Energy Systems ; Volume 53, Issue 1 , December , 2013 , Pages 540-547 ; 01420615 (ISSN) Rahmani, M ; Sadati, N ; Sharif University of Technology
    In large-scale power systems, classical centralized control approaches may fail due to geographically distribution of information and decentralized controllers result in sub-optimal solution for load-frequency control (LFC) problems. In this paper, a two-level structure is presented to obtain optimal solution for LFC problems and also reduce the computational complexity of centralized controllers. In this approach, an interconnected multi-area power system is decomposed into several sub-systems (areas) at the first-level. Then an optimization problem in each area is solved separately, with respect to its local information and interaction signals coming from other areas. At the second-level,... 

    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) Pourya, M ; Aziznejad, S ; Unser, M ; Sage, D ; Sharif University of Technology
    IEEE Computer Society  2021
    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... 

    Searching for galactic hidden gas through interstellar scintillation: the OSER project

    , Article Proceedings of Science, 18 August 2008 through 22 August 2008, Stockholm ; 2008 ; 18248039 (ISSN) Moniez, M ; Ansari, R ; Habibi, F ; Sharif University of Technology
    Considering the results of baryonic compact massive objects searches through microlensing [1], cool molecular hydrogen (H2 - He) clouds should now be seriously considered as a possible major component of the Galactic hidden matter. It has been suggested that a hierarchical structure of cold H 2 could fill the Galactic thick disk [8] or halo [3], providing a solution for the Galactic hidden matter problem. This gas should form transparent "clumpuscules" of ∼ 10 AU size, with a column density of 1024-25cm-2, and a surface filling factor smaller than 1%. The OSER project (Optical Scintillation by Extraterrestrial Refractors) is proposed to search for scintillation of extra-galactic sources... 

    Towards a knowledge based approach to style driven architecture design

    , Article Procedia Computer Science, 5 March 2015 through 6 March 2015 ; Volume 62 , 2015 , Pages 236-244 ; 18770509 (ISSN) Moaven, S ; Habibi, J ; Alidoosti, R ; Parvizi Mosaed, A ; Bahrami, M ; Sharif University of Technology
    Nowadays, knowledge is the key to success in all software engineering processes. This valuable knowledge, obtained through analysis, design, development, and maintenance processes of the system, should be saved and reused in designing and developing current and similar systems. Using pre-existing knowledge is a practical approach which reduces design complexity, improves software architecture design and manages software quality. In this paper, we describe an approach to create architecture design knowledge using a hierarchical structure of architectural styles based on quality attributes. Knowledge is most importance asset of our approach that reuses similar domains, correlates architectures... 

    A graph-theoretic approach toward autonomous skill acquisition in reinforcement learning

    , Article Evolving Systems ; Volume 9, Issue 3 , 2018 , Pages 227-244 ; 18686478 (ISSN) Kazemitabar, S. J ; Taghizadeh, N ; Beigy, H ; Sharif University of Technology
    Springer Verlag  2018
    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...