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...

Studying wave optics in the light curves of exoplanet microlensing

, Article Monthly Notices of the Royal Astronomical Society ; Volume 431, Issue 2 , 2013 , Pages 1264-1274 ; 00358711 (ISSN) Mehrabi, A ; Rahvar, S ; Sharif University of Technology

2013

Abstract

We study the wave optics features of gravitational microlensing by a binary lens composed of a planet and a parent star. In this system, the source star near the caustic line produces a pair of images in which they can play the role of secondary sources for the observer. This optical system is similar to the Young double-slit experiment. The coherent wavefronts from a source on the lens plane can form a diffraction pattern on the observer plane. This diffraction pattern has two modes from the close- and wide-pair images. From the observational point of view, we study the possibility of detecting this effect through the Square Kilometre Array (SKA) project in the resonance and...

Investigation of Fracture Toughness of Epoxy Resins by Addition of CNT and Rubber Microparticles

, M.Sc. Thesis Sharif University of Technology Mehrabi, Fatemeh (Author) ; Bagheri, Reza (Supervisor)

Abstract

Epoxy resins are relatively brittle and have low resistance to crack propagation. It is common to add rubber particles to improve crack resistance in epoxies, although these particles may deteriorate the strength of the matrix. Different nanomaterials are used to overcome the inherent brittleness of epoxies and to keep the mechanical properties. Among them, carbon nanotubes has been attracted many attentions. Fractue behavior and mechanical properties of two kind of novel nanocomposites, i.e, epoxy/carbon nanotube and epoxy/rubber/carbon nanotube are investigated in current study. Electron microscopy investigations were done to assure the CNTs distribution and fracture mechanisms as well....

Performance Evaluation of Machine Learning and Statistical Approaches for Wildfire Modeling and Prediction

, M.Sc. Thesis Sharif University of Technology Mehrabi, Majid (Author) ; Moghim, Sanaz (Supervisor)

Abstract

Wildfires are complex phenomena with many indeterminate and highly unpredictable driving factors that have remained unresolved. During the last decade, machine learning methods have successfully excelled in wildfire prediction as an alternative to traditional field research methods by elucidating the relationship between historical wildfire events and various important variables. The main purpose of this research is to evaluate the random forest machine learning approach and the logistic regression statistical approach to prepare a wildfire susceptibility map using data related to historical wildfires and effective variables in the Okanogan region in Washington province of the United States...

Post-consumer recycled high density polyethylene/polypropylene blend with improved overall performance through modification by impact polypropylene copolymer: morphology, properties and fracture resistance

, Article Polymer International ; Volume 70, Issue 12 , 2021 , Pages 1701-1716 ; 09598103 (ISSN) Mehrabi Mazidi, M ; Sharifi, H ; Sharif University of Technology

John Wiley and Sons Ltd 2021

Abstract

The effect of an impact polypropylene copolymer (IPC) having excellent stiffness–toughness balance on the microstructure and properties of a blend comprising 80 wt% recycled high density polyethylene (rHDPE) and 20 wt% recycled isotactic polypropylene (rPP) was studied. Morphological observations revealed improved interfacial interactions, a finer dispersion state and a more homogeneous phase morphology upon IPC incorporation into the blend up to 20 wt%. Flexural modulus, flexural strength, tensile strength and tensile ductility were steadily increased with IPC loading, and exhibited 13%, 14%, 35% and 520% improvement at 20 wt% IPC. A monotonic rise in Izod impact energy, accompanied by a...

Cooperative Data Aggregation in Wireless Sensor Networks

, M.Sc. Thesis Sharif University of Technology Mehrabi Koushki, Masoud (Author) ; Movaghar, Ali (Supervisor)

Abstract

Minimizing energy consumption is the most important concern in wireless sensor networks (WSNs). Cooperative multiple-input multiple-output (MIMO) and data aggregation are two promising techniques to conserve energy in network nodes by coordinating their transmissions through cooperative communications along with eliminating the inherent redundancy of raw data for transmissions. In this thesis, with the goal of reducing energy consumption, we present a dynamic clustering framework for combined used of cooperative MIMO and data aggregation in cluster-based WSNs. We derive a new and more general energy model for computing energy consumption of cooperative data aggregation in wireless sensor...

Numerical Fatigue Investigation of Composites Honeycomb Structures Using Four Point Bending Loading Specimen

, M.Sc. Thesis Sharif University of Technology Mehrabi, Hadi (Author) ; Adibnazari, Saeed (Supervisor)

Abstract

In this thesis, design and analyses of honeycomb structures are investigated. Primary goal is to develop an equivalent orthotropic material model that is a good substitute for the actual honeycomb core. By replacing the actual honeycomb structure with the orthotropic model, during the finite element analyses, substantial advantages can be obtained with regard to ease of modeling and model modification, solution time and hardware resources . To figure out the best equivalent model among the approximate analytical models that can be found in the literature, a comparison is made. First sandwich beams with four different honeycomb cores are modeled in detail and these are accepted as reference...

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...

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...

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...

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...

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 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...

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...

Wave Optics Effects in Microlensing of a Binary Lenses

, Ph.D. Dissertation Sharif University of Technology Mehrabi Rahmanpour, Ahmad (Author) ; Rahvar, Sohrab (Supervisor)

Abstract

In this thesis, we investigate two subjects in gravitational microlensing. In first part we study wave optics effect in light curve of a binary system. Gravitational lensing occurs when light deflects in a gravitational field. This deflection produces multi-images from real one. In microlensing regime, images can not be detected separately and gravitational lensing appears as magnifying source’s flux . Microlensing has been studied mostly in geometric optics regime. At larger wavelengths, mostly at radio wavelengths, we expect to see the effects of wave optics in microlensing. Stars at radio wave are faint and to detect them we need a powerful radio telescope. In the near future, SKA (Square...

Numerical Simulation of Magneto Mercury Reciprocating Micropump

, M.Sc. Thesis Sharif University of Technology Mehrabi, Ali (Author) ; Shafii, Mohammad Behshad (Supervisor)

Abstract

In this investigation Magneto Mercury Reciprocating Micrpump (MMRM) the combination of Magneto-Hydrodynamic and Reciprocating micropumps has been analyzed. To achieve the analytical and numerical solution of one-tank and three-tank MMRM, the momentum, continuity, volume fraction and magnetohydrodynamic equations have been presented. The dimensionless analytical solution of one-phase and two-phase three dimensional MHD flow in the condition of using constant current and potential electrical source, has been offered.
The boundary between mercury and air has been tracked via VOF method in OpenFOAM software. VOF equation has been solved by explicit method with variable time step and maximum...

Development of a Conceptual Model for Heat Recovery from Exhaust Gases of Electric Arc Furnace

, M.Sc. Thesis Sharif University of Technology Mehrabi, Mohammad Reza (Author) ; Saboohi, Yadollah (Supervisor)

Abstract

Steel in Iran is mainly produced by EAFs. One of the most fundamental issues in the field of electric arc furnace is to foresight methods to reduce energy consumption and emissions. A model is presented in the present research work that avails itself to analysis of mass and energy recovery simultaneously. The proposed model includes three major elements: scrap pre-heating, sponge iron pre-heating and inert gases pre-heating. An important feature of this approach is to preheat sponge iron. Mathematical model for preheating scrap has been developed on the basis of CONSTEEL technology. Also the model for sponge iron and inert gases preheating has been formulated based on the literature review....

Theoretical and Numerical Simulation of a Solar Collector for Direct Steam Generation

, M.Sc. Thesis Sharif University of Technology Mehrabi, Pouria (Author) ; Morad, Mohammad Reza (Supervisor)

Abstract

Direct steam generation (DSG) process using linear FRESNEL collectors has been developed widely in recent years and is one of the most promising solar technologies for thermal power generation, Industrial processes and domestic usage. In this process water as heat transfer fluid (HTF) is heated through a solar field. Continuous breakthroughs are being achieved on improvement of these collectors. A multi-phase CFD model is developed to calculate the wall temperature of linear Fresnel absorber tubes and fluid properties including temperature, velocity, and pressure. In order to design the collector field and identify the critical condition such as overheating of the absorber tubes, modeling of...

Design and Construction of a Single Axis Stable Platform Using the Model-Based Design Approach

, M.Sc. Thesis Sharif University of Technology Mehrabi, Mohammad Hossein (Author) ; Nobahari, Hadi (Supervisor)

Abstract

The perpuse of this thesis is to design and fabricate a laboratory one degree of freedom stable platform under turbulences by model-based design method. To do this, different parts of the system were first modeled in the Solidworks software and then fabricated with various tools. With proper assembly of electronic and mechanical components, the original body of the system was created. Then, the controller motor with a stable platform which is attached to it was modeled and simulated in MATLAB software. Then, the parameters of the equations were calculated using standard identification tests and TCACS optimization algorithm. One of the challenges of this thesis is the malfunction of the...