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    Data Mining Application in Customer Relationship Management: Case study in Saipa Yadak Co.

    , M.Sc. Thesis Sharif University of Technology Akbari, Amin (Author) ; Salmasi, Naser (Supervisor)
    Abstract
    One of the most applicable fields in data mining is customer relationship management (CRM). CRM process includes four aspects: Customer identification, Customer attraction, Customer retention, and Customer development. Data mining can be a supportive tool for decision making in each of these CRM aspects. Huge volume of data and information corresponding to CRM that exists in companies' databases, has made sufficient potential for data mining process and discovering hidden knowledge. Importance of concepts like customer needs identification, customer retention, and increasing customer value for companies has made the need to use of data mining techniques more valuable. Saipa Yadak Co., as a... 

    Prediction of Hotel Customers’ Revisit Behavior by Determining the Appropriate Marketing Mix Using Customer Review Analysis

    , M.Sc. Thesis Sharif University of Technology Marandi, Ali Akbar (Author) ; Najmi, Manoochehr (Supervisor) ; Tasavori, Misagh (Supervisor)
    Abstract
    In recent years, the tourism industry has become one of the most influential industries in the income generation of countries and has attracted the attention of researchers. Identifying the important features of the hotel from the users' point of view is one of the areas that have been considered, while the segmentation of hotel customers based on the extracted features has been less in the focus of researchers and the need for more research in this field has been felt by experts.Given that the desire to return to the hotel by travelers has always been one of the factors affecting the financial performance of hotels, the factors affecting it are of great importance. It can be very valuable... 

    Modeling International Air Itinerary Choice

    , Ph.D. Dissertation Sharif University of Technology Rezaei, Ali (Author) ; Nasiri, Habibollah (Supervisor)
    Abstract
    Modelling passengers’ itinerary choice behaviour is valuable to understand the increasingly competitive airline market and predicting air travel demand. Research in the choice behaviour of air travellers has evolved to include an analytical focus on variation in the sensitivities of travellers to factors influencing itinerary choice. That is, some choice studies have moved beyond a focus on assumed representative, mean-level sensitivities toward a goal of representing the distribution of preferences across a sample. An important issue that remains is whether the insight gained in previous studies, which focussed on preferences in mature markets with relatively high per-capita rates of air... 

    Sparse Representation and Dictionary Learning based Methods for Skin lesion Segmentation and Classification

    , Ph.D. Dissertation Sharif University of Technology Moradi Davijani, Nooshin (Author) ; Mahdavi Amiri, Nezamoddin (Supervisor)
    Abstract
    Skin cancer is a common type of cancer in the world. Melanoma is considered as the deadliest form of human skin cancer that causes approximately 75% of deaths associated with this cancer. However, melanoma is curable if diagnosed in an early stage. Due to high visual similarities and diverse characteristics of lesions, it is a challenging task to differentiate between different types of skin lesions. Therefore, it is worthwhile to develop a reliable automatic system increasing the accuracy and efficiency of pathologists. Here, we propose sparse representation and dictionary learning based methods for skin lesion segmentation and classification. First, we review the steps of a computer aided... 

    Lesion Classification in Mammography Images

    , M.Sc. Thesis Sharif University of Technology Bagheri Khaligh, Ali (Author) ; Manzuri Shalmani, Mohammad Taghi (Supervisor)
    Abstract
    Computer-Aided Diagnosis (CAD) systems are widely used for detection of various kinds of abnormalities in mammography images. In this work, mass classification is investigated and its steps are explained in detail, for each step a main method is presented and other methods are also discussed. For mass segmentation a relatively new method based on level set and Morphological Component Analysis (MCA) is used.After this step, various kinds of features such as shape, geometrical, and textural ones are introduced. Moreover, a set of proposed features based on wavelet transformation,for this application are presented. The proposed features can describe margin and texture characterizations of a... 

    Providing Confidentiality of Outsourced Data through Fragmentation

    , M.Sc. Thesis Sharif University of Technology Dodangeh, Peyman (Author) ; Jalili, Rasool (Supervisor)
    Abstract
    Data outsourcing is considered as a promising approach in today computing and connected world. This approach enables organizations to outsource their data to anexternal third party server which is responsible for storing and propagation of outsourced data. Although data outsourcing offers many benefits, especially for those organizations with limited resources and increaseing data volume, but this approach in security aspects like providing confidentiality and privacy about curious external third party or other threats, is faced by serious challenges. In the recent decade many approaches for solving or at least decreasing the potential threats over providing confidentiality of outsourced... 

    Improving Robustness of Deep Neural Networks Against Adversarial Examples in Image

    , M.Sc. Thesis Sharif University of Technology Mahabadi Mohamadi, Mohamad (Author) ; Kasaei, Shohreh (Supervisor)
    Abstract
    Despite widespread applications and high performance of deep neural networks in the fields of computer vision, they have been shown to be vulnerable to adversarial examples. An adversarial example is a perturbated image that the magnitude of its difference with its corresponding natural image is small and yet given such example, the network produces incorrect output. In recent years, many approaches have been proposed to increase the robustness of DNNs against adversarial examples with adversarial training being proposed as the most effective defense measure. Approaches based on adversarial training try to increase the robustness of the network by training on the adversarial examples. One of... 

    Sharing Economy’s Customers Segmentation Based on Participation Motives Case Study: Ride-sharing Platforms in Iran

    , M.Sc. Thesis Sharif University of Technology Yazdanshad, Arian (Author) ; Najmi, Manoochehr (Supervisor)
    Abstract
    Among businesses operating under the sharing economy model, ride-sharing platforms or Internet taxis have attracted a lot of attention and have been able to encourage millions of people to use them in a few years. Meanwhile, what has been the subject of numerous researches in recent years is the motivation of people to use this type of business. Understanding what motivates users to use these businesses is important to them because it helps them allocate their resources optimally by focusing on the benefits, shortcomings, and potential disadvantages of their product, And then by improving the provided service, have more advantages and attractiveness in the eyes of customers. Accordingly, in... 

    Joint Segmentation and Motion Estimation of Cardiac Cine MR Image Sequences

    , Ph.D. Dissertation Sharif University of Technology Eslami, Abouzar (Author) ; Jahed, Mehran (Supervisor)
    Abstract
    In this study a variational framework for joint segmentation and motion estimation is provided for inspecting heart in Cine MRI sequences. In the first work, a functional including Mumford-Shah segmentation and optical flow based dense motion estimation is proposed. However, the motion estimation technique is replaced with warping estimation in the second work to reach in more regular and smooth motion field based on tracking of cardiac boundaries. Both of these functionals are then approximated by using the phase-field method to make them suitable for extracting Euler-Lagrange equations. Numerical solution to the optimization problem, when the time and image spaces are discretized by finite... 

    Test Case Selection in Test-Driven Development

    , Ph.D. Dissertation Sharif University of Technology Mafi, Zohreh (Author) ; Mirian Hosseinabadi, Hassan (Supervisor)
    Abstract
    The large number of unit tests produced in the test-driven development (TDD) method and the iterative execution of these tests extend the regression test execution time in TDD. This study aims to reduce test execution time in TDD. We propose a TDD-based approach that creates traceable code elements and connects them to relevant test cases to support regression test selection during the TDD process. Our proposed hybrid technique combines text and syntax program differences to select related test cases using the nature of TDD. We use a change detection algorithm to detect program changes. Our experience is reported with a tool called RichTest, which implements this technique. To evaluate our...