Loading...
Search for: hejazi--mohammad-amin
0.161 seconds

    Multi-Agent Machine Learning in Self-Organizing Systems

    , M.Sc. Thesis Sharif University of Technology Hejazi Hosseini, Ehsan (Author) ; Nobakhti, Amin (Supervisor) ; Bagheri Shouraki, Saeed (Supervisor)
    Abstract
    This paper develops a novel insight and procedure that includes a variety of algorithms for finding the best solution in a structured multi-agent system with internal communications and a global purpose. In other words, it finds the optimal communication structure among agents and the optimal policy in this structure. First, a unique reinforcement learning algorithm is proposed to find the optimal policy of each agent in a fixed structure with non-linear function approximation like artificial neural networks (ANN) and eligibility traces. Secondly, a mechanism is presented to perform self-organization based on the information of the learned policy. Finally, an algorithm that can discover an... 

    Cosmic Inflation with Serrated Effective Potentials and Primordial Black Holes

    , M.Sc. Thesis Sharif University of Technology Hejazi, Mohammad Amin (Author) ; Abolhasani, Ali Akbar (Supervisor)
    Abstract
    A variety of early universe models predict the formation of primordial black holes. Primordial black holes can be a candidate for a fraction or total dark matter in the universe. Moreover, mergers of these black holes can produce gravitational waves. After re-entering the horizon, having a sufficiently large amplitude, the initial fluctuations of cosmic matter can collapse to primordial black holes. This thesis studies an inflationary potential that can amplify the power spectrum of curvature perturbations up to several orders of magnitude via imposing some features on the potential. This power amplification on small scales can lead to the formation of primordial black holes. For simplicity,... 

    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... 

    Determining Product Portfolio of Petrochemical Plants Using Multi Objective Decision Making Tools (Case study: Jam Petrochemical Plant)

    , M.Sc. Thesis Sharif University of Technology Hejazi Bakhsh, Mahboubeh (Author) ; Akbari Jokar, Mohammad Reza (Supervisor)
    Abstract
    Decision making for planning a petrochemical plant is a difficult task, particularly when decisions are required to be made under constraints and different objectives. Final purpose of current research is to develop a reliable model for selecting limited petrochimal products among all potential alternatives under different constraints, considering two desired objective functions; Maximizing economic gain and minimizing safety risk. The powerful tool of multi objective decision making has been used for solving the proposed model. The developed model has been applied to Jam Petrochemical Company as a case study and the acquired results found to be successful.

     

    Thermal-hydraulic Analysis of Dry Storage Cask of the Spent Nuclear Fuel and Construction of a Prototype Experimental Setup for its Simulation

    , M.Sc. Thesis Sharif University of Technology Hejazi, Mohammad Ali (Author) ; Outokesh, Mohammad (Supervisor) ; Mousavian, Khalil (Supervisor) ; Rezaeian, Mahdi (Co-Supervisor)
    Abstract
    Storage of the spent nuclear fuels is one of the topics of interest in recent years and many researches have been conducted in this field in order to design storage casks for spent nuclear fuels. In this study, thermal-hydraulic analysis of a dry storage cask for Bushehr Nuclear Power Plant spent nuclear fuels is carried out. Geometry of the analyzed cask is taken from a Russian transportation cask TK-13. Drawing of the geometry is achieved with SolidWorks and it’s meshing is completed in Gambit. 3 different cases were considered for cask’s geometry and design: cask without spacers inside, cask with spacers inside, and cask with spacers inside and fins on the outside surface of the cask.... 

    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... 

    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... 

    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... 

    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... 

    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... 

    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... 

    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,... 

    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,... 

    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... 

    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... 

    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... 

    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... 

    Workflow Ensemble Scheduling in Edge-Based Infrastructures using Game Theory

    , M.Sc. Thesis Sharif University of Technology Parto, Hossein (Author) ; Fazli, Mohammad Amin (Supervisor)
    Abstract
    With the expansion of the Internet of Things and the significant increase in latencysensitive applications, cloud computing is facing serious challenges. In order to solve the challenges of cloud computing and respond to the needs of delay-sensitive applications, the concept of edge computing is proposed. In edge-based infrastructures, computing resources are located near the network edge and end devices. These infrastructures can better serve latency and security sensitive applications that require low processing and high interaction with end devices. However, achieving the benefits of edge-based infrastructure requires optimal resource management. One of the effective steps for optimal use... 

    Improving Data Efficiency in Predictive Reinforcement Learning in Non-stationary Environments

    , M.Sc. Thesis Sharif University of Technology Rimaz, Mohammad Sadra (Author) ; Nobakhti, Amin (Supervisor)
    Abstract
    One type of non-stationary environment studied in reinforcement learning involves environments where only one model from a limited set is valid at each time step. The weighted mixture policy method in these environments uses predictions of future model changes to increase cumulative rewards. This method creates a new policy by combining the weighted optimal policy of the current model with that of the future model, after receiving a prediction and before the model change. Obtaining the optimal policy for models is a time-consuming process requiring a large amount of data. This thesis examines existing reinforcement learning methods in non-stationary environments. It demonstrates that the...