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    All-optical recurrent neural network with reconfigurable activation function

    , Article IEEE Journal of Selected Topics in Quantum Electronics ; 2022 , Pages 1-1 ; 1077260X (ISSN) Ebrahimi Dehghanpour, A ; Koohi, S ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2022
    Abstract
    Optical Neural Networks (ONNs) can be promising alternatives for conventional electrical neural networks as they offer ultra-fast data processing with low energy consumption. However, lack of suitable nonlinearity is standing in their road of achieving this goal. While this problem can be circumvented in feed-forward neural networks, the performance of the recurrent neural networks (RNNs) depends heavily on their nonlinearity. In this paper, we first propose and numerically demonstrate a novel reconfigurable optical activation function, named ROA, based on adding or subtracting the outputs of two saturable absorbers (SAs). RAO can provide both bounded and unbounded outputs by facilitating an... 

    Orthogonal nonnegative matrix factorization problems for clustering: A new formulation and a competitive algorithm

    , Article Annals of Operations Research ; 2022 ; 02545330 (ISSN) Dehghanpour, J ; Mahdavi Amiri, N ; Sharif University of Technology
    Springer  2022
    Abstract
    Orthogonal Nonnegative Matrix Factorization (ONMF) with orthogonality constraints on a matrix has been found to provide better clustering results over existing clustering problems. Because of the orthogonality constraint, this optimization problem is difficult to solve. Many of the existing constraint-preserving methods deal directly with the constraints using different techniques such as matrix decomposition or computing exponential matrices. Here, we propose an alternative formulation of the ONMF problem which converts the orthogonality constraints into non-convex constraints. To handle the non-convex constraints, a penalty function is applied. The penalized problem is a smooth nonlinear... 

    All-Optical recurrent neural network with reconfigurable activation function

    , Article IEEE Journal of Selected Topics in Quantum Electronics ; Volume 29, Issue 2 , 2023 ; 1077260X (ISSN) Dehghanpour, A. E ; Koohi, S ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2023
    Abstract
    Optical Neural Networks (ONNs) can be promising alternatives for conventional electrical neural networks as they offer ultra-fast data processing with low energy consumption. However, lack of suitable nonlinearity is standing in their way of achieving this goal. While this problem can be circumvented in feed-forward neural networks, the performance of the recurrent neural networks (RNNs) depends heavily on their nonlinearity. In this paper, we first propose and numerically demonstrate a novel reconfigurable optical activation function, named ROA, based on adding or subtracting the outputs of two saturable absorbers (SAs). RAO can provide both bounded and unbounded outputs by facilitating an... 

    A competitive optimization approach for data clustering and orthogonal non-negative matrix factorization

    , Article 4OR ; 2020 Dehghanpour Sahron, J ; Mahdavi Amiri, N ; Sharif University of Technology
    Springer Science and Business Media Deutschland GmbH  2020
    Abstract
    Partitioning a given data-set into subsets based on similarity among the data is called clustering. Clustering is a major task in data mining and machine learning having many applications such as text retrieval, pattern recognition, and web mining. Here, we briefly review some clustering related problems (k-means, normalized k-cut, orthogonal non-negative matrix factorization, ONMF, and isoperimetry) and describe their connections. We formulate the relaxed mean version of the isoperimetry problem as an optimization problem with non-negative orthogonal constraints. We first make use of a gradient-based optimization algorithm to solve this kind of a problem, and then apply a post-processing... 

    A competitive optimization approach for data clustering and orthogonal non-negative matrix factorization

    , Article 4OR ; Volume 19, Issue 4 , 2021 , Pages 473-499 ; 16194500 (ISSN) Dehghanpour Sahron, J ; Mahdavi Amiri, N ; Sharif University of Technology
    Springer Science and Business Media Deutschland GmbH  2021
    Abstract
    Partitioning a given data-set into subsets based on similarity among the data is called clustering. Clustering is a major task in data mining and machine learning having many applications such as text retrieval, pattern recognition, and web mining. Here, we briefly review some clustering related problems (k-means, normalized k-cut, orthogonal non-negative matrix factorization, ONMF, and isoperimetry) and describe their connections. We formulate the relaxed mean version of the isoperimetry problem as an optimization problem with non-negative orthogonal constraints. We first make use of a gradient-based optimization algorithm to solve this kind of a problem, and then apply a post-processing... 

    Effect of severe plastic deformation on evolution of intermetallic layer and mechanical properties of cold roll bonded Al-Steel bilayer sheets

    , Article Journal of Materials Research and Technology ; Volume 9, Issue 5 , 2020 , Pages 11497-11508 Dehghanpour Baruj, H ; Shadkam, A ; Kazeminezhad, M ; Sharif University of Technology
    Elsevier Editora Ltda  2020
    Abstract
    In this study, evolution of intermetallic layer of the cold roll bonded bilayer of Aluminum-Steel sheets, during severe plastic deformation (SPD) followed by annealing has been investigated. The effect of such evolution on mechanical properties has been discussed. For this purpose, Constrained Groove Pressing (CGP) was used as a SPD process. Field emission scanning electron microscope equipped with energy dispersive spectroscopy and optical microscopy were used for examination of intermetallic compounds morphology and composition. Meanwhile, tensile properties of the bilayer sheets were evaluated. According to microstructural observations, continuous intermetallic layer was formed during... 

    Graph Isoperimetry Problem Using Optimization Methods

    , M.Sc. Thesis Sharif University of Technology Dehghanpour Sohroun, Jafar (Author) ; Daneshgar, Amir (Supervisor)
    Abstract
    In this thesis, we study the mean graph isoperimetry problem using an optimization approach. The k-th isoperimetric constant of a graph is defined as the minimum of an objective function (p-norm of the vector consisting of normalized flow) over k-subpartitions of vertices. We note that the normalized cut problem can be formulated as a semidefinite programming problem and utilizing the relaxation methods for semidefinite programs, the problem can be solved in approximately polynomial time. Finally, we model the isoperimetry problem as an optimization problem with orthogonality constraints and utilizing Wen and Yin’s efficient method for finding local minima of the problem, we extract a... 

    , M.Sc. Thesis Sharif University of Technology Dehghanpour Baruj, Hamed (Author) ; Kazeminezhad, Mohsen (Supervisor)
    Abstract
    Demand to structural and industrial materials with unique properties lead to produce unorthodox combination of metals. One of the most useful combinations is composites of Aluminum-Steel and this composites is mostly used as a sheet. Due to differences in melting point of two metals, preferred method for welding of this two metals is Cold Roll Bonding. For enhance of mechanical properties of this two metals, preferred methods is Severe Plastic Deformation. By the way, in SPD methods, two method was established for sheets. Accumulative Roll Bonding and Constrained Groove Pressing but ARB method produce multi-layer composites so preferred method to produce bilayer sheets is CGP. In this study,... 

    Designing an Optical Processing Unit for Non-Linear Operations in Deep Neural Networks

    , M.Sc. Thesis Sharif University of Technology Ebrahimi Dehghanpour, Aida (Author) ; Koohi, Somayyeh (Supervisor)
    Abstract
    Abstract: In this thesis, we tackled the problem of nonlinear activation function in optical artificial neural networks, and in particular in convolutional and recurrent neural networks. In the end, we propose an all-optical recurrent neural network in free-space optics for the first time. Artificial neural networks are a branch of artificial intelligence, which can be adopted to solve a wide variety of problems. While very powerful, these networks can be very power hungry and slow when it comes to solving very complicated problems. Optical versions of these networks bring the promise of solving both of these issues and provide a fast and power efficient platform for these networks. However,... 

    Design and Analysis of Optimization Algorithms for Solving Nonlinear Optimization Pproblems with Orthogonal Constraints and Certain Applications

    , Ph.D. Dissertation Sharif University of Technology Dehghanpour, Jafar (Author) ; Mahdavi Amiri, Nezamoddin (Supervisor)
    Abstract
    Orthogonal Nonnegative Matrix Factorization (ONMF) with orthogonality constraints on a matrix has been found to provide better clustering results over existing clustering problems . Because of the orthogonality constraint , this optimization problem is difficult to solve . Many of the existing constraint-preserving methods deal directly with the constraints using different techniques such as matrix decomposition or computing exponential matrices . Here , we propose an alternative formulation of the ONMF problem which converts the orthogonality constraints into non-convex constraints . To handle the non-convex constraints , a penalty function is applied . The penalized problem is a... 

    Investigation of Effects of Successive Liquefaction Occurrence on Piles Located in Level Ground With an Inclined Base Layer with Using Stone Cloumns – a Physical 1g Shake Table and Laminar Shear Box Model

    , M.Sc. Thesis Sharif University of Technology Dehghanpour Farashah, Ali (Author) ; Haeri, Mohsen (Supervisor)
    Abstract
    Lateral spreading is defined as finite lateral displacement of mildly sloping grounds or those ending in free faces induced by liquefaction. The phenomenon of lateral spreading caused by liquefaction in coastal areas and mildly sloping grounds has caused significant damage to deep foundations of engineering structures such as bridge and buildings in severe earthquakes. Since earthquake is unavoidable, therefore, it is necessary to provide appropriate solution to reduce the effects of liquefaction induced lateral spreading. Despite conducting various laboratory and field studies by previous researchers, there is still no comprehensive approach to evaluate the effects of lateral spreading on... 

    Finite Element Model Updating in Time Domain Using Water Cycle Algorithm

    , M.Sc. Thesis Sharif University of Technology Dehghanpour, Fatemeh (Author) ; Rahimzadeh Rofooei, Fayaz (Supervisor) ; Mahdavi, Hossein (Co-Supervisor)
    Abstract
    Due to inevitable uncertain sources in modeling, operational and environmental conditions, finite element model and structure’s response to a same load pattern differs drastically. To reduce this difference and make the model’s response close to the real structure, finite element model updating procedure is essential. Updated model can be used for structural assessment, damage identification, remaining service life estimation, and structural control. Model updating methods are categorized into two groups in term of information domain used for model updating; time-domain methods and frequency-domain approaches. Time-domain methods have a preference because of the main drawbacks of frequency... 

    Exploiting Locality Properties of Nodes for Improving Search Efficiency in P2P Networks

    , M.Sc. Thesis Sharif University of Technology Hariri, Negar (Author) ; Habibi, Jafar (Supervisor)
    Abstract
    The Use of peer-to-peer architectures instead of traditional client-server architecture can be beneficial in many aspects such as increasing scalability of the systems, enhancing fault tolerance in critical situations, extending the system resources and various other advantages. Nowadays, many applications are based on peer-to-peer architectures and as a result, a large portion of the internet traffic is produced by these applications. This has been a motivation to many researchers to focus on reducing the amount of this traffic while satisfying the content distribution demands. One of the main problems that can result in generating large amount of traffic and also long response times for... 

    Automatic Extraction of Semantic Web Service Composition Patterns

    , M.Sc. Thesis Sharif University of Technology Ghoroghi, Camellia (Author) ; Habibi, Jafar (Supervisor)
    Abstract
    In today’s competitive world، web services have become more and more prevalent and their efficient discovery and composition in order to create novel functionalities is essential for variety of applications. Due to the large number of available services، the discovery of services is a difficult and time consuming task. Existing approaches in web services discovery and composition attempt to use simple web services while ignoring the use of once composed services. Reusing frequently used composite services can considerably increase performance of the entire system. Moreover، the advent of semantic web، as an effective solution of representing information interpretable by machines and none... 

    An Engineering Approach to Software Modeling Language Development

    , Ph.D. Dissertation Sharif University of Technology Kamandi, Ali (Author) ; Habibi, Jafar (Supervisor)
    Abstract
    Nowadays, the essentiality of appropriate modeling languages has become evident, and with the introduction of new concepts such as domain-specific languages, the need for systematic research on designing and engineering new modeling languages has increased significantly. Several modeling languages have been developed and employed over the years, but the area of modeling languages still suffers from the lack of a proper framework: There is a strong need for an engineering framework that specifies the detailed steps of language development, the input and output artifacts of each step, the techniques applicable to each step, and quantifiable methods for quality measurement. From a unified point... 

    Distributed Data Mining in Peer-to-Peer Systems

    , Ph.D. Dissertation Sharif University of Technology Mashayekhi, Hoda (Author) ; Habibi, Jafar (Supervisor)
    Abstract
    Peer-to-peer (P2P) computing is a popular distributed computing paradigm for many applications which in-volve exchange of information among a large number of peers. In such applications, large amount of data is distributed among multiple dispersed sources. Therefore, data analysis is challenging due to processing, storage and transmission costs. Moreover, the data rarely remains static and frequent data changes, quickly out date previously extracted data mining models. Distributed data mining deals with the problem of data analysis in environments with distributed data and computing resources. In this dissertation, we explore distributed data mining in different structures of P2P systems. In... 

    An Architecture Description Language for Software Product Line

    , M.Sc. Thesis Sharif University of Technology Tanhaei, Mohammad (Author) ; Habibi, Jafar (Supervisor)
    Abstract
    Software Product Line is known as a process of developing family of the software together. The methods of building a software product line is trying to capture commonality and variety of this family of software and form a product line based on them. Commonality of this family of the software allows us reuse in every aspect of the development of software. Nowadays, software architecture as a one of the most important aspect of software engineering, plays major role in specifying the tasks and clearing the relationship between people. It can divide large and complex system to some sub-system and overcome complexity of the system. Software architecture forms a basis for communication among... 

    Designing a Model-Based Process and Architecture for Partial Automation of Software Development

    , M.Sc. Thesis Sharif University of Technology Jalal, Ali (Author) ; Habibi, Jafar (Supervisor)
    Abstract
    Automation of the software development process is the software engineers' final goal, but with the current facilities and knowledge in software engineering, it is not possible to automatically generate the whole software. Usually all the software in a specific domain contain common behaviors, which by careful exploration of these common behaviors and automation of code generation in these sections, the cost and time of projects' execution can be reduced. According to Model Driven Development (MDD), the first step in software development is creating appropriate models. For creating models, metamodel is required; therefore, we need to create a specific motamodel for the chosen domain or use... 

    Towards a Mechanism to Design Software Product Line Architecture Based on Heterogeneous Styles

    , M.Sc. Thesis Sharif University of Technology Amirjan, Elahe (Author) ; Habibi, Jafar (Supervisor)
    Abstract
    One of approaches in software architecture design is using architecture styles or patterns. This approach is a suitable way for satisfying functional and nonfunctional requirements and also is cost effective. It is shown that this approach improves effectively quality of software systems. Whereas, choosing a suitability architecture style for complex designs depends on many factors and often one style cannot meet all the requirements, therefore, use of heterogeneous styles can be useful. Also, in software product line architecture design, we must combine different kinds of architectural styles to cover the problem domain and achieve better performance. Correct and accurate choice of... 

    Model Selection for Complex Network Generation

    , M.Sc. Thesis Sharif University of Technology Motallebi, Sadegh (Author) ; Habibi, Jafar (Supervisor)
    Abstract
    Nowadays, there exist many real networks with distinctive features in comparison with random networks. Social networks, collaboration networks, citation networks, protein networks and communication networks are some example of complex network classes. Nowadays these networks are widespread and have many applications and the study of complex networks is an important research area. In many applications, the “synthetic networks generation” is one of the first levels of complex networks analysis. This level has many applications such as simulation and extrapolation. Many generative models are proposed for complex network modeling in recent years. By the use of these models, synthetic networks...