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    Experimental Studies for Construction of a Microbial Fuel Cell (MFC) in Continuous Flow Mode

    , M.Sc. Thesis Sharif University of Technology Sadeghi Haskoo, Mohammad Amin (Author) ; Vossoughi, Manoochehr (Supervisor) ; Aalemzadeh, Iran (Supervisor)
    Abstract
    In this research performance of microbial fuel cells (MFCs) in continuous flow mode was studied. Different anodic chambers were tested and it was found that granular activated carbons (GACs) produced the highest power density (1228 mW/m3) in comparison with multiple anodes (731 mW/m3), single anode (294 mW/m3) and polymeric packings (40 mW/m3). It was also shown that in a plug-anodic chamber (PAC) the power output is reduced by reducing agitation of anodic volume. Adding more GACs to anodic chamber results in power increase, however by increasing occupied volume from 80% to 100% the power increase was negligible in result of cathodic reactions limitations. Feed flowrate was increased from... 

    A Real-Time and Energy-Efficient Decision Making Framework for Computation Offloading in Iot

    , M.Sc. Thesis Sharif University of Technology Heydarian, Mohammad Reza (Author) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    Based on fog computing paradigm, new applications have become feasible through the use of hardware capabilities of smart phones. Many of these applications require a vast amount of computing and real-time execution should be guaranteed. Based on fog computing, in order to solve these problems in is necessary to offload heavy computing to servers with adequate hardware capabilities. On the other side, the offloading process causes time overhead and endangers the real-timeliness of the application. Also, because of the limited battery capacity of the handheld devices, energy consumption is very important and should be minimized.The usual proposed solution for this problem is to refactor the... 

    Stocks Market Trading Strategy Recommendation Using Experts’ Opinion Aggregation

    , M.Sc. Thesis Sharif University of Technology Faryabi, Mohammad Mahdi (Author) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    Investors highly value the ability to predict the behavior of the capital market. Over time, various methods have been introduced to forecast the future of this market and anticipate its movements. A novel approach to achieving this is by developing data-driven decision support systems that can assist investors in making informed trading decisions. The opinions of experts play a crucial role in shaping people's perception of the market, which ultimately affects its final behavior. In this study, we have created a decision support system that can help investors by considering the complexities and meaningful relationships between different aspects of the problem. We have developed frameworks... 

    Investigation of Demand Response to Changing the Household Electricity Meter from Single Stroke Case to Three Stroke Case; Evidence from Tehran Interior Region 2

    , M.Sc. Thesis Sharif University of Technology Sadeghi, Saeed (Author) ; Vesal, Mohammad (Supervisor)
    Abstract
    This study investigates consumers’ response to changing the household electricity meter from single stroke case to three stroke case. Existence of different prices in different hours during the day is the advantage of three stroke electricity meters compared to single stroke ones. Electricity bill data of 19,742 subscribers, in Tehran Interior Region 2, during the period 1387 to 1393, has been used to evaluate this policy. Subscribers who always use only single stroke electricity meters or three stroke ones are considered as the control group; and subscribers who have experienced electricity meter change during the period are considered as the experimental group. Changing electricity meters... 

    Design of Control for Fractional Order Systems with Output Constraints

    , M.Sc. Thesis Sharif University of Technology Sadeghi, Hamed (Author) ; Sharokhi, Mohammad (Supervisor)
    Abstract
    Identifying fractional systems and designing controllers for these systems is one of the leading challenges due to their limitations. Systems can have constraints on output, input, and states. These constraints make it difficult to design a controller. In this project, controller design methods for fractional-order systems with output constraints are investigated. A controller is designed for a strict feedback nonlinear system with unknown dynamics subject to asymmetric and variable output constraints, unknown direction of the controller, and unmeasurable states. To design the controller, the direct and backstepping technique is used and the Lyapunov barrier function is applied for the first... 

    Implementation of Compaction Meter with Controller Design and Simulation

    , M.Sc. Thesis Sharif University of Technology Zajkani, Mohammad Amin (Author) ; Nobakhti, Amin (Supervisor)
    Abstract
    There are a lot of ways to measure the soil compaction but all of them have some deficiencies like low precision, soil destructive, time consuming and etc. The usual ways to measure the compaction in Iran are so traditonal and have the above problems. To solve these problems, modern ways like intelligent compaction is recomonded to decrease the time and cost of compaction. The observor can also control the compaction of all the soil point to prevent any offenses by making the network between the rollers.In new methods the soil compaction is calculated by measuring the roller vibratory and usage of fourier transform from the drum response . To compact the soil more precisely and more quickly,... 

    Predicting Usefulness of Code Review Comments Using Machine Learning Algorithms

    , M.Sc. Thesis Sharif University of Technology Mohammadi, Atefeh (Author) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    The competition for staying in the business world has intensified today with the rise of open-source and commercial software. As long as a software is tailor-made to suit the needs of users, it is so-called alive and can stay in the competition. So the maintenance phase is necessary to make changes to the software to meet the needs of users. To reduce costs associated with this phase, it is necessary to avoid software bugs. One way to avoid software bugs is to use peer code review. Peer code review has been recognized as one of the best software engineering principles of the last 35 years. This principle helps maintain the quality of the code due to changes made to parts of the code that... 

    Investigating the Status of Contractual Risk Sharing in Iran’s Standard-form Contract of Public-private Partnership

    , M.Sc. Thesis Sharif University of Technology Hosseini, Mohammad Taghi (Author) ; Alvanchi, Amin (Supervisor)
    Abstract
    Many public projects in Iran are being developed with the participation of the private sector. Complaints, however, have arisen in both the public and the private sectors in many public-private-partnership (PPP) projects. It is claimed that the current PPP standard-form contract is unable to properly handle project risks. This investigation was set to improve risk responses in the PPP standard-form contract in the country. A comprehensive list of 66 universal PPP project risks was prepared by review of various related international research efforts. The list was refined to 36 risk items for the country in consultation with PPP project experts and assessing two PPP cases. These risks were... 

    Evaluation of Goals and Readiness Assessment to Implement Building Information Modeling (BIM) in IRAN's Water Industry

    , M.Sc. Thesis Sharif University of Technology Jafari, Mohammad Amin (Author) ; Alvanchi, Amin (Supervisor)
    Abstract
    Today, the correct management of construction projects in IRAN's water industry has become a severe concern for its managers. Construction projects of the water industry constitute a considerable part of the country's construction industry. Several significant Issues such as operation management, water industry projects, correct management of resources, crisis management in the water industry, increased productivity and useful life of structures, increasing productivity, and preventing water loss are among the determinative challenges in construction projects in Iran. One of the new methods for the correct management of the life cycle of projects in this area is the use of Building... 

    Representation Learning for Dynamic Graphs

    , M.Sc. Thesis Sharif University of Technology Loghmani, Erfan (Author) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    Representation learning methods on graphs have enabled using machine learning methods on graphs' discrete structure by transferring them to a continuous domain. As graphs' structures are not always static and may evolve through time, dynamic representation learning methods have recently gained scholars' attention. Several methods have been proposed to enable the model to update the embeddings graph changes, or new interactions happen between nodes. These online methods could significantly reduce the learning time by refreshing the model as the changes occur, so we don't need to retrain the model with the complete graph information. Moreover, by using the temporal information of interactions,... 

    Developing BIM Vision and BIM Strategic Plan for Municipalities

    , M.Sc. Thesis Sharif University of Technology Hemmat, Mohammad Amin (Author) ; Alvanchi, Amin (Supervisor)
    Abstract
    The municipality is an administrative, public and non-state institution that falls into the city district of the most countries’ administrative divisions. This institution has relatively autonomy and independent power. Municipalities are trying to apply the best approaches (Such as Building Information Modeling (BIM) as a procedure contributing the project management) to save time and money, as well as to satisfy the citizens in the implementation of civil projects. This study examines and evaluates the readiness of municipalities to modify the construction projects based on BIM. In addition, a pattern for identifying BIM applications, evaluating the organization readiness and the needs of... 

    An Intelligent Triangular Pattern Recognition in Stock Price Charts

    , M.Sc. Thesis Sharif University of Technology Hedayati, Emadeddin (Author) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    Stock price patterns are a technical analysis approach to forecast future trends with tremendous practical benefits. However, the current algorithms solely rely on machine learning techniques and deep neural networks which could be a problem in countries where data sets such as these are not available. We propose an algorithm based on geometry and mathematics for this problem, leading to an O(n^3logn + n^2k) complexity, where k is the number of triangular patterns  

    Predicting Opponent’s Movement in Dota 2

    , M.Sc. Thesis Sharif University of Technology Bashiri, Vahid (Author) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    Video games with respect to an ever Increasing player pool and Industry growth, have attracted a lot of attention in recent years. Dota 2, as one of the most successful games both in casual gamers’ community and E-sport community, is considered as a proper case study, however, most of the research done was limited to predicting games’ outcome. Despite The popularity, the rather unintelligent AI of the game has made quite a frustrating experience for new players. In this research, with a novel approach, hero features are used to predict their future positions. For this purpose, 35 professional games are collected and analyzed and 601 features are extracted. Then, suitable features are... 

    Development of a Deep Learning and Natural Language Processing Based Method in Order to Extract Risky Clauses of Construction Contracts

    , M.Sc. Thesis Sharif University of Technology Kazemi, Mohammad Hossein (Author) ; Alvanchi, Amin (Supervisor)
    Abstract
    One of the most significant factors for the on-time and successful implementation of construction projects is contract management. Proper management of construction contracts and assessment of potential risks in the bidding process and before its signing have a significant impact on preventing or reducing the occurrence of claims and disputes between the contract parties at various stages of the project. In this research, using the latest deep learning (DL) and natural language processing (NLP) state-of-the-art methods, and various deep neural networks (DNN) architectures a model has been developed for extracting Persian contract risk-prone clauses. In addition, this study provides a... 

    Political Tweet Classification with Active Learning

    , M.Sc. Thesis Sharif University of Technology Mirzababaei, Sajad (Author) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    Deep learning algorithms combined with supervision rely heavily on labeled data, posing challenges in the data labeling process. Addressing this issue, researchers in the field of machine learning have focused on developing approaches to reduce the dependency on labeled data and improve the efficiency of data collection for labeling purposes. This thesis investigates the training of a classification model using data collected through a human-in-the-loop system. Notably, this research pioneers the application of active learning techniques to differentiate between political and non-political Persian tweets. The dataset introduced in this study is the sole available collection for this specific... 

    Design and Implementation of an Intelligent Agent for Automatic Configuration of Content Delivery Servers

    , M.Sc. Thesis Sharif University of Technology Lotfi, Hossein (Author) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    Content delivery networks play a significant role in improving the quality of internet services by placing the necessary content closer to users on servers. Currently, over half of internet traffic is delivered through these networks to end users. The efficiency of a content delivery network depends on various parameters, including the type of requested content, workload distribution methods, network topology, routing algorithms, caching policies, network server configurations, and resource allocation (shared or dedicated hardware resources). Additionally, the requests made to a content delivery network vary based on the type of service and even the time of day, making optimization a... 

    Optimal Method for Controller Placement Problem in Sdn Using Machine Learning Techniques

    , M.Sc. Thesis Sharif University of Technology Mirhosseini, Hossein (Author) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    Software-defined networking (SDN) is a network management approach that allows centralized control of the network independently from network hardware. As a network management method, SDN provides many capabilities not traditionally found in existing hardware-based networks. However, one of the significant challenges of SDN is the placement of the controller within the network. In SDN, the central controller must be able to efficiently route all data flows separately to end devices. Therefore, the placement of the controller in the network is crucial. However, controller placement in the network poses a major challenge as it needs to be appropriately and optimally positioned to enhance... 

    Developing Balanced Contractual Model for Hiring Management Contractor in Construction Projects

    , M.Sc. Thesis Sharif University of Technology Ghaffari, Mohammad Amin (Author) ; Alvanchi, Amin (Supervisor)
    Abstract
    In construction projects, when the employer does not have enough knowledge or experience to implement and manage the project, or does not have enough time to implement the project, can hire a Management Contractor with sufficient experience and knowledge in the field of project management. On the other hand, the inability of the Management Contractor to manage the project or contracting with him in inappropriate way, not only causes additional costs for hiring the Management Contractor, but also causes the employer to suffer due to the inappropriate performance of the Management Contractor. Therefore, the utmost care should be taken in choosing the Management Contractor and contracting with... 

    A Reinforcement Learning Framework for Portfolio Management Problem Leveraging Stocks Historical Data And Their Correlation

    , M.Sc. Thesis Sharif University of Technology Taherkhani, Hamed (Author) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    Over the past few years, deep reinforcement learning(DRL) has been given a lot of attention in finance for portfolio management. With the help of experts’ signals and historical price data, we have developed a new reinforcement learning(RL) method. The use of experts’ signals in tandem with DRL has been used before in finance, but we believe this is the first time this method has been used to solve the financial portfolio management problem. As our agent, we used the Proximal Policy Optimization(PPO) algorithm to process the reward and take actions in the environment. Our framework comprises a convolutional network to aggregate signals, a convolutional network for historical price data, and... 

    The Effects of Content-Based Features on Improving Code Review Automation

    , M.Sc. Thesis Sharif University of Technology Sadri, Marzieh (Author) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    In the world of software development, Code Review is one of the most vital processes to ensure code quality and security. The textual content features in code review comments play a significant role in assessing quality and guiding the review process. This research aims to examine the importance and role of these features in identifying anti-social comments and improving code review processes. In this study, we first challenge the concept of toxicity in code review comments, which had previously been accepted as a concept in the field of code review. We focus on enhancing and automating code review processes by accurately and reliably detecting anti-social comments based on relevant...