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asadollahi--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...
Rapid and simultaneous determination of tetracycline and cefixime antibiotics by mean of gold nanoparticles-screen printed gold electrode and chemometrics tools
, Article Measurement: Journal of the International Measurement Confederation ; Vol. 47, Issue. 1 , 2014 , pp. 145-149 ; ISSN: 02632241 ; Mani-Varnosfaderani, A ; Sharif University of Technology
2014
Abstract
The screen-printed gold electrode (SPGE) modified with the formation of self-assembly monolayer (SAM) of cysteine (Cys) on gold-nanoparticles (Au nano) was utilized for rapid and simultaneous determination of tetracycline and cefixime antibiotics by square wave voltammetry (SWV). Electrochemical investigation and characterization of the modified electrode was achieved using cyclic voltammetry (CV) and scanning electron microscopy (SEM). A principal component artificial neural network (PCANN) with three layer back-propagation network was utilized for the analysis of the voltammogram data. It is possible to simultaneously determine the tetracycline and cefixime concentrations in the ranges of...
Chemometrics-assisted GC-MS analysis of volatile and semi-volatile constituents of elettaria cardamomum
, Article Food Analytical Methods ; Vol. 7, issue. 9 , 2014 , pp. 1745-1754 ; ISSN: 1936-9751 ; Mani-Varnosfaderani, A ; Sharif University of Technology
2014
Abstract
Multivariate curve resolutions (MCR) along with other chemometric techniques are proposed to improve the analysis of Iranian Elettaria cardamomum (E. cardamom) essential oil with gas chromatography-mass spectrometry (GC-MS). In addition, multivariate curve resolution-alternating least squares (MCR-ALS) is used to obtain pure elution and mass spectral profiles for the components present in each chromatographic segment as well as their relative concentrations. This strategy was also used to overcome the problems of baseline offset, asymmetric peaks, retention time shifts, and overlapped and embedded peaks occurring during GC-MS analysis. The analysis of GC-MS data revealed that 42 components...
Polymeric mixed matrix membranes containing zeolites as a filler for gas separation applications: A review
, Article Journal of Industrial and Engineering Chemistry ; Volume 19, Issue 2 , 2013 , Pages 375-393 ; 1226086X (ISSN) ; Esmaeili, N ; Asadollahi, M ; Sharif University of Technology
2013
Abstract
Polymeric membrane technology has received extensive attention in the field of gas separation, recently. However, the tradeoff between permeability and selectivity is one of the biggest problems faced by pure polymer membranes, which greatly limits their further application in the chemical and petrochemical industries. To enhance gas separation performances, recent works have focused on improving polymeric membranes selectivity and permeability by fabricating mixed matrix membranes (MMMs). Inorganic zeolite materials distributed in the organic polymer matrix enhance the separation performance of the membranes well beyond the intrinsic properties of the polymer matrix. This concept combines...
Permeation of single gases through TEG liquid membranes modified by Na-Y nano-zeolite particles
, Article Separation and Purification Technology ; Volume 76, Issue 2 , 2010 , Pages 120-125 ; 13835866 (ISSN) ; Bastani, D ; Kazemian, H ; Sharif University of Technology
2010
Abstract
In this research, a triethylene glycol (TEG)/nano-zeolite Na-Y liquid membrane was developed in order to investigate the effect of zeolite nanoparticles on separation performance of a liquid membrane. To do this, a high yield nano-zeolite Na-Y was synthesized using mid-synthesis addition method. The synthesized samples were characterized by XRD, FT-IR, and SEM (EDX) instrumental techniques. A supported liquid membrane was prepared by impregnating a porous hydrophilic PVDF support with TEG and nano-zeolite Na-Y. The permeation tests of single gas components of O2, N2 and CO2 were carried out at pressure differences of 0.8 and 1.8 bar. The permeances of the single gases were found to be: CO2 >...
Toward understanding the effects of solution heat treatment, Ag addition, and simultaneous Ag and Cu addition on the microstructure, mechanical properties, and corrosion behavior of the biodegradable Mg–2Zn alloy
, Article Journal of Materials Research and Technology ; Volume 26 , 2023 , Pages 1553-1571 ; 22387854 (ISSN) ; Alizadeh, R ; Sadrnezhaad, K ; Sharif University of Technology
Elsevier Editora Ltda
2023
Abstract
In this study, the effects of adding silver (0.2 and 0.6 wt%) and copper (0.1 wt%) antibacterial elements, on the microstructure, mechanical properties, and degradation behavior of the as-cast Mg–2Zn alloy were investigated. The obtained results indicate that both Ag and Cu showed significant grain refinement effects in the as-cast condition. The MgZn precipitates were formed in the as-cast Mg–2Zn–0.2Ag alloy, which contained a small amount of Ag. Increasing the Ag content to 0.6 wt% resulted in formation of the Mg54Ag17 phase. Simultaneous addition of 0.2 wt% Ag and 0.1 wt% Cu to the Mg–2Zn alloy caused the ternary Mg(Zn,Cu) precipitates to form. Solution-treated Mg–2Zn and Mg–2Zn–0.6Ag...
Numerical Study of Passive Heat Transfer Enhancement Methods in Automobile Radiator
, M.Sc. Thesis Sharif University of Technology ; Mousavi, Ali (Supervisor)
Abstract
In this study, a three dimensional model of water-ethylene glycol based aluminum oxide nanofluid in the laminar flow of an automobile radiator has been numerically studied. The passive heat transfer enhancement method of twisted tape insertion in the flat tubes of radiator is used. The effects of different parameters on heat transfer and pressure drop have been investigated. Simulation results show that utilizing twisted tapes is an effective way of enhancing heat transfer in an automobile radiator. Despite the pressure drop penalty of using twisted tapes, the thermal performance factor which is a proper criteria for evaluating the practical use of the twisted tapes and considers the effect...
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...
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...
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...
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...
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 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...
Enhancement of surface properties and performance of reverse osmosis membranes after surface modification: a review
, Article Desalination ; Volume 420 , 2017 , Pages 330-383 ; 00119164 (ISSN) ; Bastani, D ; Musavi, S. A ; Sharif University of Technology
2017
Abstract
Reverse osmosis (RO) membrane process has become the most promising technology for desalination to produce purified water. Among numerous polymeric materials used to fabricate RO membranes, aromatic polyamide thin film composite (TFC) membranes are dominant in commercial RO membrane processes because of their high salt rejection and water permeability as well as their excellent chemical, thermal, and mechanical stability. However, the major hindrance to the effective application of polyamide TFC RO membranes is membrane fouling. Furthermore, polyamide TFC RO membranes have limited stability to chlorine, which is commonly used as disinfect to control membrane biofouling. These two factors...
Proposing Appropriate Lateral Load Pattern for 3-D Pushover Analysis of Unsymmetric-Plan Building Structures
, M.Sc. Thesis Sharif University of Technology ; Rahimzadeh Rofooei, Fayyaz (Supervisor)
Abstract
Recent studies in the area of damage assessment of structures under severe earthquakes have shown that plan asymmetry of structures have considerable effects on the severity of the induced damages. In these cases, structure enters into its nonlinear behaviour, and both structural and nonstructural elements sustain large forces and deformations. Nowadays, due to the complication of nonlinear dynamic analyses in estimating these forces and deformations in case of seismic ground motion, the use of nonlinear static analysis methods has increased. These procedures expose the structures to monotonically increasing lateral forces with an invariant height-wise distribution until a predetermined...
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...
Numerical investigation of optimization of injection angle effects on fluidic thrust vectoring
, Article Journal of Applied Fluid Mechanics ; Volume 10, Issue 1 , 2017 , Pages 157-167 ; 17353572 (ISSN) ; Taeibe Rahni, M ; Asadollahi Ghohieh, A ; Sharif University of Technology
Isfahan University of Technology
2017
Abstract
A computational investigation was conducted to optimize the fluidic injection angle effects on thrust vectoring. Numerical simulation of fluidic injection for shock vector control, with a convergent-divergent nozzle concept was performed, using URANS approach with Spalart-Allmaras turbulence model. The fluidic injection angles from 60° to 120° were investigated at different aerodynamic and geometric conditions. The current investigation demonstrated that secondary injection angle is an essential parameter in fluidic thrust vectoring. Computational results indicated that, optimizing secondary injection angle would have positive impact on thrust vectoring performance. Furthermore, in most...
Numerical investigation of freestream flow effects on thrust vector control performance
, Article Ain Shams Engineering Journal ; 2018 ; 20904479 (ISSN) ; Taeibe Rahni, M ; Asadollahi Ghohieh, A ; Sharif University of Technology
Ain Shams University
2018
Abstract
The current research attempted to apply a numerical investigation for external freestream-flow influence on thrust-vector control. The freestream-flow Mach numbers varying from 0.05 to 1.1 were studied at different flow conditions. Computational modeling and simulation of a converging diverging nozzle with shock-vector control structure was achieved with utilizing the Unsteady-RANS approach and Spalart-Allmaras turbulence model. The present investigation has shown that, freestream-flow is an essential parameter on performance of shock-vector nozzle. Numerical results demonstrate that, increasing freestream Mach number would reduce the thrust-vectoring effectiveness. Furthermore, optimizing...