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malekzadeh--mahdieh
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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...
Production of silver nanoparticles by electromagnetic levitation gas condensation
, Article Chemical Engineering Journal ; Volume 168, Issue 1 , March , 2011 , Pages 441-445 ; 13858947 (ISSN) ; Halali, M ; Sharif University of Technology
2011
Abstract
Electromagnetic levitation gas condensation (ELGC) method was used to synthesize silver nanoparticles (NPs). Silver droplets were melted and levitated stably at about 1130°C with appropriate flat coils in a 10mm OD silica tube. High purity argon, nitrogen and helium were employed as carrier gases and cooling media. Morphology and particle size of the products were investigated by scanning and transmission electron microscopy (SEM and TEM), X-ray diffraction (XRD), energy dispersive X-ray analysis (EDAX) and dynamic light scattering (DLS). The DLS, SEM and TEM studies demonstrated narrow size distribution of spherical shape silver NPs with mean particle size of about 60, 50 and 30nm...
An Investigation on Production of Silver Nanopowder by Electromagnetic Levitation Melting Method
, M.Sc. Thesis Sharif University of Technology ; Halali, Mohammad (Supervisor)
Abstract
Electromagnetic levitation gas condensation (ELGC) method was used to synthesize silver nanoparticles. Silver droplets were melted and levitated stably at about 1130 °C with appropriate flat coils in a 10 mm OD silica tube. High purity argon, nitrogen and helium were employed as carrier gases and cooling media. Morphology and particle size of the products were investigated by scanning and transmission electron microscopy (SEM and TEM), X-ray diffraction (XRD) energy dispersive X-ray analysis (EDAX) and dynamic light scattering (DLS). The DLS, SEM and TEM studies demonstrated narrow size distribution of spherical shape Ag nanoparticles with particle size of about 60, 45 and 35 nm synthesized...
A Topological and Geometric Approach to Fixed Points Results for Sum of Operators and Applications
, M.Sc. Thesis Sharif University of Technology ; Ranjbar, Ali (Supervisor)
Abstract
In this thesis, we establish a fixed point result of Krasnoselskii type for the sum A+B, where A and B are continuous maps acting on locally convex spaces. We apply such results to obtain strong solutions for some quasi-linear elliptic equations with lack of compactness. We also provide an application to the existence and regularity theory of solutions to a nonlinear integral equation modeled in a Banach space. Finally, we develop a sequentially weak continuity result for a class of operators acting on vector-valued Lebesgue spaces. Such a result is used together with a geometric condition as the main tool to provide an existence theory for nonlinear integral equations in Lp(E)
The Preliminary Design of an Airplane Anti-ice System and Development of laboratory for Its Experimental Tests
, M.Sc. Thesis Sharif University of Technology ; Darbandi, Massoud (Supervisor)
Abstract
Icing is a prominent and consequently a primitive parameter in aeronautic accidents.This has promoted the aerospace and aeronautical companies to work on that very seriously since four decades ago. There are several systems to confront with ice accumulation over the airplane surface; such as pneumatic, weeping, electrical, and heating systems. Of course, each of them has its own advantages and disadvantages. At the first step of our study, we need to determine the criteriaaffecting the customer needs, airplane constraints, and the specified missions. At the second stage, it requires selectinga preferred system and we should have taken our decision based on the facts that a good choice can...
A discretized analytical solution for fully coupled non-linear simulation of heat and mass transfer in poroelastic unsaturated media
, Article International Journal for Numerical and Analytical Methods in Geomechanics ; Volume 33, Issue 13 , 2009 , Pages 1589-1611 ; 03639061 (ISSN) ; Pak, A ; Sharif University of Technology
2009
Abstract
Mathematical simulation of non-isothermal multiphase flow in deformable unsaturated porous media is a complicated issue because of the need to employ multiple partial differential equations, the need to take into account mass and energy transfer between phases and because of the non-linear nature of the governing partial differential equations. In this paper, an analytical solution for analyzing a fully coupled problem is presented for the one-dimensional case where the coefficients of the system of equations are assumed to be constant for the entire domain. A major issue is the non-linearity of the governing equations, which is not considered in the analytical solution. In order to...
Synthesis and Preparation of Nanostructured Ag@SiO2 Core Shells with Different Morphologies and their Antibacterial Properties
, Ph.D. Dissertation Sharif University of Technology ; Halali, Mohammad (Supervisor)
Abstract
In this study, silver nanoparticles (Ag NPs) with different morphologies were synthesize by physical and chemical methods. Spherical silver nanoparticles were synthesized by electro magnetic levitation melting approach, while silver nanoplates and nanorods were prepared by chemical reduction route. Ag NPs were then coated with thin porous silica shell. The dissolution behavior of synthesized Ag@SiO2 was investigated in PBS at 25, 37 and 55 °C. Spherical and triangular Ag@SiO2 were conjugated by Penicillin G molecules. The silver and penicillin contents of the synthesized nano-antibiotics were determined by ICP-OES and TGA analyses. The nanoparticles were characterized by X-ray diffraction...
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...
Development of the Electron and Photon Transport Code for Dose Calculations on GPU and Benchmarking with EGSnrc Simulation for Radiotherapy
, M.Sc. Thesis Sharif University of Technology ; Sohrabpour, Mostafa (Supervisor)
Abstract
Almost half of all cancer patients receive radiation therapy as main or part of the treatment process. Before performing radiation therapy, first it is necessary to determine the patient’s treatment plan and estimate the outcome of it based on the dose distribution. The quality of treatment is dependent on the accuracy of dosimetry calculations that lies in Monte Carlo algorithms. Unfortunately, most of the computation time is long and not suitable for clinical applications. On the other hand, a real treatment planning will be possible if all aspects of radiation therapy should be considered. The radiation source that is obtained from a medical linear accelerator head is one of these...
Mechanism of reaction of molten NiTi with EBM graphite crucible
, Article Materials Science and Technology ; Volume 25, Issue 6 , 2009 , Pages 699-706 ; 02670836 (ISSN) ; Ahmadi, E ; Malekzadeh, M ; Sharif University of Technology
2009
Abstract
Ultra clean NiTi shape memory alloy was produced by electron beam melting of Ni rich vacuum inductionally melted butts together with pure Ti chunks in both condensed and electrographite crucibles. A hollow cathode discharge gun was used for heating up to 1623, 1653 and 1693 K and holding the charge materials under vacuum for 300, 600, 900 and 1200 s. Effects of temperature, time and compactness of the crucible on formation/disappearance of the hard compounds like Ni3Ti, Ti4Ni2O, Ti4Ni 2C, Ti3Ni2OC and TiC were determined by X-ray diffraction, scanning electron microscopy and energy dispersive X-ray analysis. A combination of the experimental results with the kinetic rate equations indicated...
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...
Prediction of The Link Sign Between Nodes in Signed Social Networks
, M.Sc. Thesis Sharif University of Technology ; Rabiee, Hamid Reza (Supervisor)
Abstract
Interactions in social networks consist of positive relations, such as friendship, trust, like, and negative relations, such as antagonism, distrust, dislike. “Signed networks” are utilized to model these networks. These networks are presented by “signed graphs” in which nodes are the people and relations are modeled by sign of edges. One of the challenging problem in signed networks is link sign prediction, i.e., specifying unknown edge sign along with evolution of the network given sign of some edges and further information about remainder of network. Two approaches are used to answer this problem. The first approach is proposing computing models for sign prediction. In this assertion we...
Modeling Effect of Soil behavior on Fatigue Life of Steel Catenary Risers in Touch Down Zone
, M.Sc. Thesis Sharif University of Technology ; Raie, Mohammad (Supervisor)
Abstract
Purpose of this research is an investigation on the effect of soil behavior on fatigue life of steel catenary risers in touch down zone. Steel catenary risers are a part of pipeline installed between the seabed and the offshore platform on the sea level, and its application is to transfer the gas or oil from the seabed to the sea level. Steel catenary risers for their resilience against buckling, easy installation, lower cost comparing other conductors are preferred to other means of conducting oil in recent years. The most challenging issue in the design of this kind of riser is the fatigue problem. The characteristic of the wave loadings we are facing in this environment is cyclic;...