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    A Feedback-based Process of Corporate Structur Design

    , M.Sc. Thesis Sharif University of Technology Ghazanfari, Hossein (Author) ; Modarres, Abdolhamid (Supervisor)
    Abstract
    Designing the structure of organization is one of the most important issues confronting all managers, especially those in large corporations. Structure design process consists of making several trade-offs about parameters that are affected with various contingency factors. This leads manages to confusion so some of them have no plans for progressing this process. Referring to organization theory and design, one sees a large number of models of organizational structure design. But there is not any means to compare them with each other. In this research, next the introduction of a conceptual feed-back model of organizational structure design process, three well-known processes in the last... 

    Simulation of Freight Grouping and Moving in Railroad Networks for Evaluating Freight Transportation Strategies

    , M.Sc. Thesis Sharif University of Technology Moeinaddini, Amin (Author) ; Shafahi, Yousef (Supervisor)
    Abstract
    Importance role of railway in transporting freight attract researchers and operators of railroad to consider using the new technology and methods to making this mode of transportation more efficient. Most railways network use one prevalent method to move freight wagons from origin to destination. In this method, freight wagons on its route from their origin to their destination passing through different type of stations. Some of these stations are origin or destination. Some of station use to just refueling, passing or crossing freight trains. Third types of stations are classification stations. In these stations its passible freight wagons are reclassified. In other word freight wagons... 

    An Efficient Algorithm for Group Recommender Systems based on Centrality of Users

    , M.Sc. Thesis Sharif University of Technology Fathian Rad, Fahimeh (Author) ; Movaghar, Ali (Supervisor)
    Abstract
    The significant increase in data volume makes it difficult to choose from a variety of options. Recommender systems help people choose their priorities in a limited time and facilitate the selection process for users. These systems predict users 'interest in the future by examining users' information and their preferences. Recently, with the significant increase in the number of users, studies in this field have changed so that groups of people with similar priorities are correctly identified and a list of recommendations is provided for each group. Identifying groups and presenting a suggestion list each require high computational cost and are often inefficient. The centrality of nodes will...