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bazargani-gilani--mahdieh
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Total 83 records
Investigation of Internal Rotation About C-N Bond in 4- (phenylacetyl) morpholine by Dynamic Nuclear Magnetic Resonance Spectroscopy
, M.Sc. Thesis Sharif University of Technology ; Tafazzoli, Mohsen (Supervisor)
Abstract
In this project, 13 C nuclear magnetic shielding constants and also hindered internal rotation about C-N bond in compound 4 -(phenylacetyle) morpholine are investigated The Factorial Design method was used to obtain the best solution for chemical shift computations and comparison made out in two levels (HF and B 3 LYP). Consequently the (B 3 LYP) method own better data. 13 C NMR Spectra were taken at variable temperature ,and then with simulation of bandshape broadening pattern at coalescence region ,rate constants of exchange were obtained for all temperatures. For simulation of line-shape broadening Spinworks software was used, that with two interfaces made possible simulation with two...
Taxing Policies to Manage Demand And Supply of Automobiles to Reduce Air Pollution
, M.Sc. Thesis Sharif University of Technology ; Pourzahedi, Hossein (Supervisor)
Abstract
One effective way to reduce air pollution created by automobiles is to tax/toll the unfavorable characteristics of the automobiles. This study is an extension of the current literature on taxing visible and measurable aspects of automobile ownership and use, namely engine size, age, fuel used, and technology level. A three sided model, comprising the operator (government), consumers, and automobile producers, has been constructed to control emission by proper taxation. Engine size tax is one-time, age-tax is yearly, and fuel use is usage-based. The model has been built and experimented based on a sample population and the results have been shown to be in the direction of the management...
Spatial variation input effects on seismic response of arch dams
, Article Scientia Iranica ; Volume 19, Issue 4 , August , 2012 , Pages 997-1004 ; 10263098 (ISSN) ; Ghaemian, M
Elsevier
2012
Abstract
In the present paper, the seismic response of an arch dam subjected to spatial variation of ground motions along the interface with its foundations is investigated. Recorded ground accelerations at the dam foundation interface of an arch dam were used for the purpose of this investigation. Topographic amplification between various points of the interface was studied by obtaining ratios of the response spectral displacement and spectral pseudo acceleration. Time shift and amplification between stations show the nonuniform nature of ground motions for large structures like dams. Recorded ground accelerations were interpolated for different nodes of the finite element model. The seismic...
Micro-Mechanical Analysis of Matrix Shear Deformation Effect on Energy Release Rate of Fiber/Matrix Interface Debond in Unidirectional Fiber-Reinforced Plastic Composites
, M.Sc. Thesis Sharif University of Technology ; Hosseini Kordkheili, Ali (Supervisor)
Abstract
The present thesis deals with the effect of matrix shear deformation on energy released due to debonding at fiber/matrix interface during fiber pull out test, which is modeled using two concentric cylinders representing fiber and matrix. Tensile on fiber causes a shear stress at the interface. When this stress exceeds the tensile strength of the interface, debonding occurs at the interface and grows as a crack along the interface. This debonding causes a relative axial displacement between fiber and matrix along the debonded interface, which varies along the debond crack. How fiber/matrix relative displacement changes along the debond region is not known. Thus, the fiber/matrix interface is...
Test case prioritization using test case diversification and fault-proneness estimations
, Article Automated Software Engineering ; Volume 29, Issue 2 , 2022 ; 09288910 (ISSN) ; 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...
Seismic responses of arch dams due to non-uniform ground motions
, Article Scientia Iranica ; Volume 19, Issue 6 , December , 2012 , Pages 1431-1436 ; 10263098 (ISSN) ; Sohrabi Gilani, M ; Sharif University of Technology
2012
Abstract
In the present paper, spatially variation input effects on seismic responses of arch dams have been studied. Recorded ground accelerations at the dam foundation interface of Pacoima dam during January 13, 2001 were used for the purpose of this investigation. A numerical finite element model was developed for dynamic analysis of the dam reservoir system. The modified version of NSAD-DRI finite element program was used for the analysis and the ground acceleration time histories were interpolated at all dam foundation interface nodal points. Total and pseudo static displacements as well as developed stresses due to uniform and non uniform excitations are obtained. The results reveal that...
Dynamic Responses of Arch Dams Subjected to Multiple Support Excitations
, Ph.D. Dissertation Sharif University of Technology ; Ghaemian, Mohsen (Supervisor)
Abstract
Large structures such as dams, long span bridges and piping systems because of an extended interface with the ground as support and the earthquake wave propagation in foundation are subjected to the non-uniform excitations. In such cases, the standard dynamic analysis in which a uniform earthquake is used as an input data is not true and can lead to unrealistic results. In the present study, seismic responses of arch dams subjected to spatial variation of ground motions is investigated and compared with the standard methods. For this purpose the governing equations are implemented into the NSAD-DRI (comprehensive software for Nonlinear Seismic Analysis of Dams) and the seismic responses of...
Multi-Modal Distance Metric Learning
, M.Sc. Thesis Sharif University of Technology ; 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 ; 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 ; 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 ; 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 ; 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...
Deep Learning For Recommender Systems
, M.Sc. Thesis Sharif University of Technology ; 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...
Adversarial Networks for Sequence Generation
, M.Sc. Thesis Sharif University of Technology ; 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 ; 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...
Stability analysis of arch dam abutments due to seismic loading
, Article Scientia Iranica ; Volume 24, Issue 2 , 2017 , Pages 467-475 ; 10263098 (ISSN) ; Sohrabi Gilani, M ; Ghaemian, M ; Sharif University of Technology
Sharif University of Technology
2017
Abstract
Abutments of concrete arch dams are usually crossed by several joints, which may create some rock wedges. Abutment stability analysis and controlling the probable wedge movements is one of the main concerns in the design procedure of arch dams that should be investigated. For decades, the quasi-static method, due to its simple approach, has been used by most of dam designers. In this study, the dynamic method is presented and the obtained time history of sliding safety factors is compared with the quasi-static results. For this purpose, all three components of Kobe (1979) and Imperial Valley (1940) earthquakes are applied to the wedge, simultaneously, and the magnitude and direction of wedge...
Improving Graph Construction for Semi-supervised Learning in Computer Vision Applications
, M.Sc. Thesis Sharif University of Technology ; 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...
The effect of non-uniformity in ground motions on the seismic response of arch dams
, Article SN Applied Sciences ; Volume 3, Issue 3 , 2021 ; 25233971 (ISSN) ; Sohrabi Gilani, M ; Ghaemian, M ; Sharif University of Technology
Springer Nature
2021
Abstract
Recorded ground accelerations at various locations of Karun III Dam during November 20, 2007, were recorded by an array of accelerometers located on the dam. In terms of amplitude and phase, these accelerations show non-uniformities in different elevations. In this paper, the effect of these non-uniform ground motions on the seismic response of the dam taking dam-reservoir-foundation interaction into account is investigated. The EACD-3D-2008 finite element program and ABAQUS Software are used for carrying out the seismic analyses. For this purpose, time histories of the earthquake accelerations are interpolated at nodal points located on the dam foundation interface. The analysis has been...
Thermal analysis of RCC dams during construction considering different ambient boundary conditions at the upstream and downstream faces
, Article Journal of Civil Structural Health Monitoring ; Volume 12, Issue 3 , 2022 , Pages 487-500 ; 21905452 (ISSN) ; Sohrabi Gilani, M ; Ghaemian, M ; Sharif University of Technology
Springer Science and Business Media Deutschland GmbH
2022
Abstract
Thermal analysis of Roller Compacted Concrete (RCC) dams is generally carried out considering identical ambient boundary conditions at upstream and downstream faces. For the case of Shahri-Kor Dam (an RCC dam with a height of 57 m), recorded thermal data depicts a considerable difference between upstream and downstream ambient temperatures, especially during cold months. This paper investigates how taking this difference into account can affect the thermal response of the dam. For this purpose, two thermal analyses are carried out with and without consideration of these different ambient boundary conditions (DABC). Consequently, the computed temperatures at representative points are compared...
Adaptation for Evolving Domains
, M.Sc. Thesis Sharif University of Technology ; Soleymani Baghshah, Mahdieh (Supervisor)
Abstract
Until now many domain adaptation methods have been proposed. A major limitation of almost all of these methods is their assumption that all test data belong to a single stationary target distribution and a large amount of unlabeled data is available for modeling this target distribution. In fact, in many real world applications, such as classifying scene image with gradually changing lighting and spam email identification, data arrives sequentially and the data distribution is continuously evolving. In this thesis, we tackle the problem of adaptation to a continuously evolving target domain that has been recently introduced and propose the Evolving Domain Adaptation (EDA) method to classify...