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    Providing a Method for Developing Oil & Gas Project’s Time Schedule Automatically, based on Artificial Intelligence and Soft Computing

    , M.Sc. Thesis Sharif University of Technology Akbari, Zohreh (Author) ; Habibi, Moslem (Supervisor)
    Abstract
    The project schedule is used as a key tool for managers to measure the progress of the project and prevent the deviation of the project from achieving its goals.Project scheduling started with manual methods. After a while, due to the increase in the size of projects and their complexity, the efficiency of traditional methods decreased. After the advances in computer sciences, scientists and experts had moved towards intelligentization and automation.During the past three decades, despite the attention of both academic and industrial fields towards automatic planning and scheduling of projects, Most of the researches focused on construction projects, and unfortunately, a few attentions have... 

    Investigating the Effect of Knowledge Sharing Factors in Determining the Size of Agile Teams

    , M.Sc. Thesis Sharif University of Technology Vahid Chirani, Hanieh (Author) ; Habibi, Moslem (Supervisor)
    Abstract
    Today, knowledge is the most important resource in software development. The success of software development relies on the exchange of knowledge between software developers working in different agile teams. The purpose of this research is to determine the size of agile teams according to knowledge sharing factors. Knowledge sharing factors between work teams have been extracted by searching articles; Then, all these factors, which are classified into five main categories: individual, organizational, technological, cultural, and geographical, were investigated and separated according to the working conditions in Iran, and finally, the important factors were identified by the evaluation of... 

    A Stock Portfolio Management Algorithm Based on Fundamental Market Data for Tehran’s Stock Exchange – Case Study on Mining & Metal Industries

    , M.Sc. Thesis Sharif University of Technology Zarei, Mohammad (Author) ; Habibi, Moslem (Supervisor)
    Abstract
    The aim of this research is to develop and implement a deep reinforcement learning algorithm for portfolio management in the Tehran stock market, which is considered an emerging market with distinct patterns compared to the stock markets of developed countries. In this study, in addition to the market price data extensively used in previous research, we leverage fundamental ratio data extracted from company financial reports, which have received less attention. Furthermore, the research scope is limited to stocks in the mining and metal industries to enable the utilization of specific industry features, such as susceptibility to global prices of a key commodity. The portfolio management... 

    A Quantitative Model for Measuring Business and IT Alignment Based on Process-Oriented IT KPIs

    , M.Sc. Thesis Sharif University of Technology Biaram, Mohammad Amin (Author) ; Habibi, Moslem (Supervisor) ; Bozorgi Amiri, Ali (Co-Supervisor)
    Abstract
    In recent years with the growth and development of emerging technologies, one of the main challenges in various organizations is the issue of Business-IT Alignment programs at different levels of strategic, tactical, and operational. Many managers and experts in the field of information technology recognize the importance of this issue because of its broad effects on the development and maturity of the organization. However, they face various difficulties in creating actionable plans to achieve high levels of alignment. The main problem is the inability to measure the alignment degree index. This index is affected by various sub-indicators in various fields of business and information... 

    A Machine Learning-Based Hierarchical Risk Parity Approach for Portfolio Asset Allocation on the Tehran Stock Exchange

    , M.Sc. Thesis Sharif University of Technology Aghaee Dabaghan Fard, Sina (Author) ; Habibi, Moslem (Supervisor) ; Fazli, Mohammad Amin (Co-Supervisor)
    Abstract
    The process of portfolio construction and optimization can be broken down into three main steps: selecting appropriate assets, allocating capital, and monitoring and adjusting the portfolio. This study focuses on evaluating the performance of the Hierarchical Risk Parity (HRP) method for capital allocation in investment portfolios, specifically in Iran’s capital market. The aim is to enhance the method's effectiveness by implementing alternative correlation calculation approaches, such as Wavelet and Chatterjee correlations. The study utilizes three different portfolios containing assets from the Tehran Stock Exchange, the US stock market, and the cryptocurrency market. The primary objective... 

    Extraction and Analysis of Product Aspects of Online Stores Based on Customers' Reviews Using Machine Learning Techniques

    , M.Sc. Thesis Sharif University of Technology Kazemi Foroushani, Amir Hossein (Author) ; Habibi, Moslem (Supervisor) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    Today, with the popularity of online shopping, many business owners are interested in launching online stores. Recording opinions and using the opinions of customers and buyers of products provides the possibility of listening to the opinions of customers in the design and improvement of products. On the other hand, other users and those who intend to buy a specific product, after paying attention to the features and aspects of the product they want, refer to the section of customer views and opinions. The user also reads these comments among thousands of different sentences and words written with different opinions and suggests; It gets confusing and many users won't be able to make the...