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    Deep Learning For Recommender Systems

    , M.Sc. Thesis Sharif University of Technology Abbasi, Omid (Author) ; Soleimani, Mahdieh (Supervisor)
    Abstract
    Collaborative fltering (CF) is one of the best and widely employed approaches in Recommender systems (RS). This approach tries to fnd some latent features for users and items so it would predict user rates with these features. Early CF methods used matrix factorization to learn users and items latent features. But these methods face cold start as well as sparsity problem. Recent years methods employ side information along with rating matrix to learn users and items latent features. On the other hand, deep learning models show great potential for learning effective representations especially when auxiliary information is sparse. Due to this feature of deep learning, we use deep learning to... 

    Using Deep generative Models for Event Sequence Generation in Recommender Systems

    , M.Sc. Thesis Sharif University of Technology Haghipour, Amir Shayan (Author) ; Soleimani, Mahdieh (Supervisor) ; Rabeei, Hamid Reza (Supervisor)
    Abstract
    In a variety of applications, we deal with event sequences which we require to model the time of those. Event sequences modelling is vital in a variety of applications such as electronic commerce, social networks, health information; For instance, in the context of social networks entrance time, the act of like or comment can be regarded as an event sequence. Point processes are the framework for modelling event sequences, in which designer use prior knowledge and different assumptions (which is not necessarily true) to set the functional form of intensity function. That functional form may not be sufficient enough to model event sequences. In this project, we have used a deep nonlinear... 

    Test case prioritization using test case diversification and fault-proneness estimations

    , Article Automated Software Engineering ; Volume 29, Issue 2 , 2022 ; 09288910 (ISSN) Mahdieh, M ; Mirian Hosseinabadi, S. H ; Mahdieh, M ; Sharif University of Technology
    Springer  2022
    Abstract
    Regression testing activities greatly reduce the risk of faulty software release. However, the size of the test suites grows throughout the development process, resulting in time-consuming execution of the test suite and delayed feedback to the software development team. This has urged the need for approaches such as test case prioritization (TCP) and test-suite reduction to reach better results in case of limited resources. In this regard, proposing approaches that use auxiliary sources of data such as bug history can be interesting. We aim to propose an approach for TCP that takes into account test case coverage data, bug history, and test case diversification. To evaluate this approach we... 

    Multi-Modal Distance Metric Learning

    , M.Sc. Thesis Sharif University of Technology Roostaiyan, Mahdi (Author) ; Soleymani, Mahdieh (Supervisor)
    Abstract
    In many real-world applications, data contain multiple input channels (e.g., web pages include text, images and etc). In these cases, supervisory information may also be available in the form of distance constraints such as similar and dissimilar pairs from user feedbacks. Distance metric learning in these environments can be used for different goals such as retrieval and recommendation. In this research, we used from dual-wing harmoniums to combining text and image modals to a unified latent space when similar-dissimilar pairs are available. Euclidean distance of data represented in this latent space used as a distance metric. In this thesis, we extend the dual-wing harmoniums for... 

    Unsupervised Domain Adaptation via Representation Learning

    , M.Sc. Thesis Sharif University of Technology Gheisary, Marzieh (Author) ; Soleymani, Mahdieh (Supervisor)
    Abstract
    The existing learning methods usually assume that training and test data follow the same distribution, while this is not always true. Thus, in many cases the performance of these learning methods on the test data will be severely degraded. We often have sufficient labeled training data from a source domain but wish to learn a classifier which performs well on a target domain with a different distribution and no labeled training data. In this thesis, we study the problem of unsupervised domain adaptation, where no labeled data in the target domain is available. We propose a framework which finds a new representation for both the source and the target domain in which the distance between these... 

    Fabrication and Characterization of Thermoplastic Starch Based Nanocomposite for Bone Scaffold

    , M.Sc. Thesis Sharif University of Technology Mahdieh, Zahra (Author) ; Bagheri, Reza (Supervisor)
    Abstract
    This project aimed to fabricate the bone scaffolds with applying thermoplastic starch-based nano-biocomposites. The starting materials for this scaffold are as follows: thermoplastic starch, ethylene vinyl alcohol as the polymer matrix and nanoforsterite as the ceramic reinforcing phase. Furthermore, vitamin E was used as antioxidant for preserving starch against thermo-mechanical degradations. Likewise, 3D pore structure was developed using azo-dicarbonamide and water in injection moulding process. With blending thermoplastic starch and ethylene vinyl alcohol, some thermoplastic starch’s properties including degradation rate and water absorption were modified. In addition, having... 

    Deep Learning for Multimodal Data

    , M.Sc. Thesis Sharif University of Technology Rastegar, Sarah (Author) ; Soleymani, Mahdieh (Supervisor)
    Abstract
    Recent advances in data recording has lead to different modalities like text, image, audio and video. Images are annotated and audio accompanies video. Because of distinct modality statistical properties, shallow methods have been unsuccessful in finding a shared representation which maintains the most information about different modalities. Recently, deep networks have been used for extracting high-level representations for multimodal data. In previous methods, for each modality, one modality-specific network was learned. Thus, high-level representations for different modalities were extracted. Since these high-level representations have less difference than raw modalities, a shared... 

    Deep Zero-shot Learning

    , M.Sc. Thesis Sharif University of Technology Shojaee, Mohsen (Author) ; Soleymani, Mahdieh (Supervisor)
    Abstract
    In some of object recognition problems, labeled data may not be available for all categories. Zero-shot learning utilizes auxiliary information (also called signatures) describing each category in order to find a classifier that can recognize samples from categories with no labeled instance. On the other hand, with recent advances made by deep neural networks in computer vision, a rich representation can be obtained from images that discriminates different categorizes and therefore obtaining a unsupervised information from images is made possible. However, in the previous works, little attention has been paid to using such unsupervised information for the task of zero-shot learning. In this... 

    Adversarial Networks for Sequence Generation

    , M.Sc. Thesis Sharif University of Technology Montahaei, Ehsan (Author) ; Soleymani, Mahdieh (Supervisor)
    Abstract
    Lots of essential structures can be modeled as sequences and sequences can be utilized to model the structures like molecules, graphs and music notes. On the other hand, generating meaningful and new sequences is an important and practical problem in different applications. Natural language translation and drug discovery are examples of sequence generation problem. However, there are substantial challenges in sequence generation problem. Discrete spaces of the sequence and challenge of the proper objective function can be pointed out.On the other, the baseline methods suffer from issues like exposure bias between training and test time, and the ill-defined objective function. So, the... 

    Improving Sampling Efficiency of Probabilistic Graphical Models

    , M.Sc. Thesis Sharif University of Technology Mahdieh, Mohsen (Author) ; Beigy, Hamid (Supervisor)
    Abstract
    Deep learning methods have become more popular in the past years. These methods use complex network architectures to model rich, hierarchical datasets. Although most of the research has been centered around Discriminative models, however, recently a lot of research is focused on Deep Generative Models. Two of the pioneering models in this field are Generative Adversarial Networks and Variational Auto-Encoders. In addition, knowing the structure of data helps models to search in a narrower hypothesis space. Most of the structure in datasets are models using Probabilistic Graphical Models. Using this structural information, one can achieve better parameter estimations. In the case of... 

    Improving Graph Construction for Semi-supervised Learning in Computer Vision Applications

    , M.Sc. Thesis Sharif University of Technology Mahdieh, Mostafa (Author) ; Rabiee, Hamid Reza (Supervisor)
    Abstract
    Semi-supervised Learning (SSL) is an extremely useful approach in many applications where unlabeled data can be easily obtained. Graph based methods are among the most studied branches in SSL. Since neighborhood graph is a key component in these methods, we focus on methods of graph construction in this project. Graph construction methods based on Euclidean distance have the common problem of creating shortcut edges. Shortcut edges refer to the edges which connect two nearby points that are far apart on the manifold. Specifically, we show both in theory and practice that using geodesic distance for selecting and weighting edges results in more appropriate neighborhood graphs. We propose an... 

    Throughput Analysis of a Cognitive Multi-hop Wireless Network Overlaid on a Cellular Network

    , M.Sc. Thesis Sharif University of Technology Soleimani, Hosein (Author) ; Ashtiani, Farid (Supervisor)
    Abstract
    In this thesis, we evaluate the maximum stable throughput of a cognitive multi-hop IEEE 802.11-based WLAN overlaid on a cellular network. In the considered scenario, the secondary users operate in the downlink or uplink frequency band of primary network and transmit their data in free primary channels using OFDM technique. The activity of primary nodes is modeled independently by ON-OFF alternating states. To model the scenario, each secondary user is modeled with an open queueing network. The queueing network can model the transmission of data as well as the effect of primary users. By writing the traffic equations of the queueing network and applying the stability conditions, we are able... 

    Analysis of the Effect of Frame Aggregation in IEEE 802.11 Standard

    , M.Sc. Thesis Sharif University of Technology Soleimani, Mohammad (Author) ; Ashtiyani, Farid (Supervisor)
    Abstract
    In this thesis the effect of frame aggregation mechanism in maximizing throughput in Wireless Local Area Networks (WLANs) have been investigated. Frame aggregation has become a part of the IEEE 802.11 standard as the amendment IEEE 802.11n. First, we have a quick review on access control layer in IEEE 802.11 standard then illustrate the necessity of frame aggregation. Afterwards, we propose an analytical model for the analysis of an IEEE 802.11n network comprised of an Access Point (AP) and several conventional nodes, all in the coverage area of each other. This analytical model focuses on downlink throughput; therefore only AP uses frame aggregation and the other nodes use basic IEEE 802.11... 

    Throughput analysis of a cognitive multi-hop IEEE 802.11-based WLAN overlaid on a cellular network

    , Article 2011 International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2011, 15 September 2011 through 17 September 2011, Split, Hvar, Dubrovnik ; 2011 , Pages 307-311 ; 9789532900262 (ISBN) Soleimani, H ; Ashtiani, F ; Sharif University of Technology
    2011
    Abstract
    In this paper, we focus on a cognitive network scenario, comprised of a multi-hop IEEE 802.11-based WLAN overlaid on a cellular network. In this scenario, the wireless nodes in a WLAN, i.e., cognitive nodes, use the downlink frequency channels of the cellular network opportunistically, such that at each packet transmission all idle channels have been exploited. In order to evaluate the capability of the considered cognitive network scenario, we propose an open queueing network model such that different packet transmission phases are mapped onto different queueing nodes. We also map different types of collisions, i.e., collision on control signals as well as collision on data transmission due... 

    Synergistic strengthening by severe plastic deformation and post-heat treatment of a low-carbon steel

    , Article Steel Research International ; Volume 89, Issue 6 , 2018 ; 16113683 (ISSN) Soleimani, F ; Kazeminezhad, M ; Sharif University of Technology
    Wiley-VCH Verlag  2018
    Abstract
    Low-carbon steel sheets are severely plastic deformed to strains of up to ≈3.48 and subsequently heat treated by conventional annealing followed by water-quenching. Four temperatures are chosen for the annealing below and over the Ac1 and Ac3 transformation lines. The effects of post-deformation heat treatment are investigated by evaluating the microstructure and mechanical properties, including strength, ductility, work hardening capability, and hardness. A maximum increase of 86% in the strength is obtained through intercritical annealing and quenching of the samples subjected to strain of 1.16. It is interesting that both the elongation and ultimate tensile strength values are higher... 

    A Mathematical Model for Pricing and Container Repositioning in a Competitive Transportation Network

    , M.Sc. Thesis Sharif University of Technology Soleimani, Mahdi (Author) ; Najafi, Mehdi (Supervisor)
    Abstract
    The transportation is one of the important components in the economies of different countries. In the maritime transportation network, the demand is usually not balanced in different routes, and this imbalance results to accumulation of containers in a node. In order to sustain the problem, firms have to reposition empty equipment from a surplus location to a shortage location, which causes the problem of “Empty Repositioning Problem”. In this study, pricing strategies in one transportation market with two locations are considered; while there is ERP problem in issue. The problem is solved by Bertrand game method. The research is divided into two parts of the monopoly network and the duopoly... 

    Development of Cascade Fuzzy Filters in Integrated INS-DVL-GPS Navigation

    , M.Sc. Thesis Sharif University of Technology Soleimani, Rasoul (Author) ; Salarieh, Hassan (Supervisor)
    Abstract
    Navigation is the science of determining the velocity and attitude of a moving object in every given moment. There have been many methods for navigation. Nowadays with the advancement of technology, advanced navigation systems have been developed. Although each of these navigation systems have their pros and cons, in order to improve the overall performance of the system and to solve their problems, these systems are integrated.The goal of this project is to present an integrated cascade method to decrease error and also decrease dependence on GPS. In this project, INS, DVL & GPS are integrated with the cascade method.To achieve this, INS-GPS and INS-DVL integration are first performed. The... 

    Multi-agent programming to enhance resiliency of earthquake-prone old metropolitan areas by transit-oriented development under public-private partnership

    , Article European Journal of Transport and Infrastructure Research ; Volume 21, Issue 1 , 2021 , Pages 19-52 ; 15677141 (ISSN) Soleimani, H ; Poorzahedy, H ; Sharif University of Technology
    TU Delft  2021
    Abstract
    Deteriorated urban areas in large cities have poor living standards, are inaccessible and small-sized, and have unstable building structures. Earthquake hazards may turn such situations into human disasters. In most cases, neither the governments nor the owners of these properties have enough budgets for renovating them. The purpose of this paper is to take advantage of Transit Oriented Development concepts to simultaneously solve two major urban area problems: (a) renovation of deteriorated urban areas and prevention of urban sprawl, and (b) design of transit network and promotion of transit-oriented development to reduce traffic congestion, pollution, and other unwanted outcomes of the... 

    Application of survival model to reveal influential objective and subjective variables to educate old metropolitan area residents in trading lands for housings: case of Tehran

    , Article Journal of Housing and the Built Environment ; 2022 ; 15664910 (ISSN) Soleimani, H ; Poorzahedy, H ; Sharif University of Technology
    Springer Science and Business Media B.V  2022
    Abstract
    Deteriorated land-uses constitute vast portions of the metropolitan areas, being small lots of land, hardly accessible, structurally unstable, and extremely vulnerable to moderate earthquakes. We present the results of a stated preference survey done to support the viability of administering a novel tri-lateral Public–Private Partnership of Build-Operate-Transfer type proposal of Government (G)-Residents (R)-Private Sector Investors (P). In this proposal, the (low income) R in a zone trade their lands for an equivalent value of safe housing built by P next to a newly constructed Bus Rapid Transit line built by G in the same zone, thus a Transit-Oriented Development. P, in return, receives... 

    Microstructure Modification and Electrical Conductivity Development in PA6/PS Blend using PANI Coated CNT

    , M.Sc. Thesis Sharif University of Technology Soleimani, Elahe (Author) ; Bagheri, Reza (Supervisor)
    Abstract
    In this research, a nanocomposite blend of polyamide 6/polystyrene containing polyaniline-coated carbon nanotubes was fabricated via melt blending method, aiming to achieve electrical conductivity in the range of static dissipation. The effect of weight percentage of nanofillers and surface modification of carbon nanotubes with polyaniline on the electrical properties and microstructure of the nanocomposite was investigated. To promote compatibility between the immiscible polyamide 6 and polystyrene polymers, PS-g-MA compatibilizer was utilized, and its effect on the morphology of the nanocomposite blend was examined. Additionally, the influence of weight percentage of nanofillers and the...