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saleh-kaleybar--saber
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Total 114 records
Combinatorial Optimization with Reinforcement Learning
, M.Sc. Thesis Sharif University of Technology ; Saleh Kaleybar, Saber (Supervisor)
Abstract
One of the key subjects in the area of mathematical optimization is a class of problems known as combinatorial optimization. We can find the optimal solution of continuous optimization problems feasible in time. But, in combinatorial optimization, we aim to obtain the optimal solution of the problem over a finite set. These problems are NP-hard and no polynomial-time solution has been proposed for this class of problems so far. Thus, in practical scenarios, we often use heuristic methods for solving NP-hard problems. There are lots of heuristic methods and choosing the best one in different situations might be challenging. In recent years, with the advances in deep neural networks,...
Decoding Graph based Linear Codes Using Deep Neural Networks
, M.Sc. Thesis Sharif University of Technology ; Amini, Arash (Supervisor) ; Saleh Kaleybar, Saber (Supervisor)
Abstract
One of the most important goals we pursue in telecommunications science is to send and receive information from telecommunication channels. By designing a powerful telecommunication system consisting of a transmitter and a receiver, we achieve this goal. Speed of data transmission, accuracy of received information and speed of data extraction are some of the criteria by which the performance of a telecommunication system can be evaluated. No telecommunication channel is free of noise. For this reason, additional information is added to the original information in the transmitter, which can still be extracted if the original information is noisy. This process is called coding. Following...
Deep Learning Based Blind Recognition of Channel Code Parameters
,
M.Sc. Thesis
Sharif University of Technology
;
Saleh Kaleybar, Saber
(Supervisor)
;
Hashemi, Matin
(Co-Supervisor)
Abstract
In the communication systems, the raw signals of information are mainly encoded so as to prevent the detrimental effects of channel noises and distortions. After some processes, this encoded signal is passed through the channel. At the receiver side, the received signal has to be decoded to extract the information signal. In order to decode the received signal, the receiver require prior knowledge about the encoder parameters. The traditional approach is to send the encoder parameters along with the encoded signals. However, this transmission overhead might occupy a considerable amount of bandwidth since the type of coding may alter several times in a fraction of a second based on the...
Distributed Algorithm Design for Function Computation with Limited Computational Resources
, M.Sc. Thesis Sharif University of Technology ; Saleh Kaleybar, Saber (Supervisor)
Abstract
In some applications of distributed systems, agents use weak communication models instead of sending and receiving messages to each other. Beeping, Stone-age, and Population protocols are examples of weak communication models. For example, population protocols are currently used in a variety of areas, such as biological systems (like molecular programming).In this model, the agents are initialized based on their own values. These agents then wake up according to their local clocks and interact with other agents randomly. During these interactions and updating states repeatedly, the agents converge to their final states, which is the expected outcome of the problem.We consider the problem of...
Learning of Causal Structures with Deep Reinforcement Learning
, M.Sc. Thesis Sharif University of Technology ; Saleh Kaleybar, Saber (Supervisor) ; Hashemi, Matin (Co-Supervisor)
Abstract
We study the problem of experiment design to learn causal structures from interventional data. We consider an active learning setting in which the experimenter decides to intervene on one of the variables in the system in each step and uses the results of the intervention to recover further causal relationships among the variables. The goal is to fully identify the causal structures with minimum number of interventions. We present the first deep reinforcement learning based solution for the problem of experiment design. In the proposed method, we embed input graphs to vectors using a graph neural network and feed them to another neural network which outputs a variable for performing...
Efficient Acceleration of Large-scale Graph Algorithms
, M.Sc. Thesis Sharif University of Technology ; Saleh Kaleybar, Saber (Supervisor) ; Hashemi, Matin (Supervisor)
Abstract
Given a social network modeled as a weighted graph G, the influence maximization problem seeks k vertices to become initially influenced, to maximize the expected number of influenced nodes under a particular diffusion model. The influence maximization problem has been proven to be NP-hard, and most proposed solutions to the problem are approximate greedy algorithms, which can guarantee a tunable approximation ratio for their results with respect to the optimal solution. The state-of-the-art algorithms are based on Reverse Influence Sampling (RIS) technique, which can offer both computational efficiency and non-trivial (1-1/e-ϵ)-approximation ratio guarantee for any ϵ>0. RIS-based...
New methods for Opportunistic Spectrum Access in Multi-user Cognitive Radio Networks
, M.Sc. Thesis Sharif University of Technology ; Pakravan, Mohammad Reza (Supervisor)
Abstract
In this dissertation, we design channel access strategies for opportunistic spectrum access in cognitive radio networks. It is assumed that the secondary transmitter and receiver hop across spectrum opportunities synchronously. This synchronization between the transmitter and the receiver can be separated in two phases: In the first phase, two Secondary Users (SUs) meet each other for the first time in a spectrum opportunity and exchange control messages. In the second phase, two SUs hop across available channels to transfer data. Rendezvous algorithm can facilitate the first meeting of two SUs. For the first phase, we propose a blind rendezvous algorithm and study its features. We show that...
Experiment Design for Causal Discovery Based on the Observational/Interventional Data
, Ph.D. Dissertation Sharif University of Technology ; Tabandeh, Mahmoud (Supervisor) ; Saleh Kalibar, Saber (Supervisor)
Abstract
In numerous scientific disciplines, analyzing a system often fails to reveal significant relationships between its various variables. However, in certain instances, changes in one variable can influence the behavior of one or more other variables. Systems where such underlying causal relationships exist are referred to as causal systems. The process of inferring the structure of these systems is known as causal learning. In causal learning, given observed samples from a system and under certain assumptions, the joint distribution of the variables can determine the equivalence class of their corresponding graphical model. Once the equivalence class is identified, interventions are employed to...
Efficient vision transformer for accurate traffic sign detection
, Article 2023 13th International Conference on Computer and Knowledge Engineering, ICCKE 2023 ; 2023 , Pages 36-41 ; 979-835033015-1 (ISBN) ; Khaloo, H ; Naghipour, A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2023
Abstract
This research paper addresses the challenges associated with traffic sign detection in self-driving vehicles and driver assistance systems. The development of reliable and highly accurate algorithms is crucial for the widespread adoption of traffic sign recognition and detection (TSRD) in diverse real-life scenarios. However, this task is complicated by suboptimal traffic images affected by factors such as camera movement, adverse weather conditions, and inadequate lighting. This study specifically focuses on traffic sign detection methods and introduces the application of the Transformer model, particularly the Vision Transformer variants, to tackle this task. The Transformer's attention...
Capturing local and global features in medical images by using ensemble cnn-transformer
, Article 2023 13th International Conference on Computer and Knowledge Engineering, ICCKE 2023 ; 2023 , Pages 30-35 ; 979-835033015-1 (ISBN) ; Saadat, H ; Khaloo, H ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2023
Abstract
This paper introduces a groundbreaking classification model called the Controllable Ensemble Transformer and CNN (CETC) for the analysis of medical images. The CETC model combines the powerful capabilities of convolutional neural networks (CNNs) and transformers to effectively capture both high and low frequency features present in medical images. The model architecture comprises three main components: a transformer classification block (TCB), a transposed-convolutional decoder block (TDB), and a convolutional encoder block (CEB). The CEB is responsible for capturing multi-local features at different scales and draws upon components from VGGNet, ResNet, and MobileNet as backbones. By...
Achievable Delay Margin by Using PID Fractional-Order Controllers
, M.Sc. Thesis Sharif University of Technology ; Tavazoei, Mohammad Saleh (Supervisor)
Abstract
This paper concerns the delay margin achievable using fractional order Proportional_Integral_Derivative controllers for linear time- invariant systems subject to variable, unknown time delays. The basic issue under investigation addresses the question: What is the largest range of time delay so that there exists a single fractional order Proportional_Integral_Derivative controller to stabilize the delay plants within the entire range? Delay margin is a fundamental measure of robust stabilization against uncertain time delays and poses a fundamental, longstanding problem that remains open except in simple, isolated cases. In this research, we develop explicit expressions of the exact delay...
Workspace analysis of a cable-suspended robot with active/passive cables
, Article Proceedings of the ASME Design Engineering Technical Conference ; Volume 6 A , August , 2013 ; 9780791855935 (ISBN) ; Zohoor, H ; Sharif University of Technology
American Society of Mechanical Engineers
2013
Abstract
Cable-driven parallel robots have several outstanding characteristics that make them unique in many robotic applications. Since cables can only pull, one of the most important issues associated with these robots is obtaining their workspace. In this paper a spatial translational cable-driven robot with active/passive cables is considered and its workspace is investigated from several points of views. First the moment resisting capability of the robot is discussed and the effects of some robot's parameters on the workspace are studied. Then, both force-feasibility and moment-resisting capability of the robot are considered to find the region where the end-effector may exert the required...
Kinematic and Dynamic Analysis and Workspace Optimization of a 3DoF Cable-Based Parallel Robot
, M.Sc. Thesis Sharif University of Technology ; Zohoor, Hassan (Supervisor)
Abstract
Cable-driven robots are referred to as parallel robots actuated with cables. In fact,in such robots rigid links are replaced by cables, which may be extended to desired lengths without making mechanism much heavy. This robot possesses a number of unique properties that makes it suitable for many industrial applications. The main factor which makes cable robots analysis different from other parallel robots is the incapability of cables to push objects. Hence, obtaining the workspace of a cable robot is one of the most important subjects associated with this type of robot.The goal of this thesis is to design a spatial translational cable driven robot, which may be used for object handling. For...
Planning of Energy Storage Systems with the Main Goal of Managing the Output Power of Wind Farms
, M.Sc. Thesis Sharif University of Technology ; Ehsan , Mehdi (Supervisor)
Abstract
Uncertain fuel prices and also global climate changes are accompanied by some state initiatives such as renewable portfolio standards (RPS). This has caused a fast growth in the amount of renewable energy installed worldwide especially wind energy over last decades. However, the intrinsic characteristics of wind farms output power, i.e. intermittency and volatility of wind speed along with being non-dispatchable in output generation of wind turbine raises many new technical and financial challenges for power system operators and planners. Up to these issues, large level of wind power penetration causes a growing concern in wind energy curtailment issue which the wind farm’s operator may be...
Strengthening RC Slabs under Various Loads and Boundary Conditions Using FRP Composites
, M.Sc. Thesis Sharif University of Technology ; Khaloo, Ali Reza (Supervisor)
Abstract
In recent decades the use of FRP materials for strengthening structures has been developed extensively, thanks to their high strength, sufficient stiffness, high durablity, and ease of use. A great deal of research has been conducted on strengthening reinforced concrete beams and columns with FRP composites. By contrast, not many researches are performed on slabs, especially two-way slabs. In these few researches, the loading and boundary conditions are limited to simplest ones. Therefore, in this thesis, the focus of attention is on strengthening reinforced concrete slabs under various loads and boundary conditions using FRP composites.
In this thesis, first, FRP composites and their...
In this thesis, first, FRP composites and their...
Data Sharing Aware Scheduling for Reducing Memory Accesses in GPGPUs
, M.Sc. Thesis Sharif University of Technology ; Hesabi, Shahin (Supervisor)
Abstract
Access to global memory is one of the bottlenecks in performance and energy in GPUs. Graphical processors uses multi-thread in streaming multiprocessors to reduce memory access latency. However, due to the high number of concurrent memory requests, the memory bandwidth of low level memorties and the interconnection network are quickly saturated. Recent research suggests that adjacent thread blocks share a significant amount of data blocks. If the adjacent thread blocks are assigned to specific streaming multiprocessor, shared data block can be rused by these thread blocks. However the thread block scheduler assigns adjacent thread blocks to different streaming multiprocessors that increase...
PLC Implementation of Fractional Order Controllers
, M.Sc. Thesis Sharif University of Technology ; Tavazoei, Mohammad Saleh (Supervisor)
Abstract
In this thesis, various fractional order controllers (FOCs), e.g., FO-PID, FO-TID, CRONE and FO-Lead/Lag, are implemented using PLC. For this purpose first, several methods are used to approximate the differentiator and integral operators. Based on these methods, the equivalent rational transfer functions of the fractional order controllers are obtained. Then, using STEP7 software, the FOCs are implemented in Siemens PLC. Moreover, to facilitate the use of the implemented FOCs in the industry and to take full advantage of the controllers, WinCC software as an interface between human and machine (HMI) is used. The WinCC software enables the operator to access the PLC through a computer (PC)...
Study on Solution Existence in Tuning Fractional Order PD and PI Controllers
, M.Sc. Thesis Sharif University of Technology ; Tavazoei, Mohammad Saleh (Supervisor)
Abstract
In this study, some of robust and exact tuning methods for fractional order PD and PI controllers are investigated in order to extract their solution existence conditions. Using aforementioned methods needs solving a set of nonlinear equations to obtain desired controller parameters which satisfy the control objectives. Hence, one of the aims of this study is to find necessary and sufficient condition on tuning specifications which guarantee the applicability of the aforementioned methods. The achievable performance region of the methods is obtained through the extracted necessary and sufficient conditions. The other aim of this work is to investigate the uniqueness of the methods...
Evaluating the Performance of Quantitative Trading Strategies in the Gold Coin futures Maket of Iran Merchantile Exchange
, M.Sc. Thesis Sharif University of Technology ; Bahramgiri, Mohsen (Supervisor)
Abstract
Along with the development of electronic exchanges, accessibility to various data streams, increasing computing power, decreasing trading costs, and growing competition in financial investment industry, quantitative trading strategies or quantitative trading rules have developed rapidly in the recent decades. These strategies try to forecast the future price movements of risky assets from the historical market information in algorithmic ways or statistical ways and thus challenge the Efficient Market Hypothesis.
The increasing attention to these strategies and lack of related empirical studies in the financial markets of Iran, motivate the research in this area. Furthermore, despite its...
The increasing attention to these strategies and lack of related empirical studies in the financial markets of Iran, motivate the research in this area. Furthermore, despite its...
Development of a zero emission integrated system for co-production of electricity and methanol through renewable hydrogen and CO 2 capture
, Article International Journal of Greenhouse Gas Control ; Volume 7 , 2012 , Pages 145-152 ; 17505836 (ISSN) ; Azar, K. M ; Saber, M ; Sharif University of Technology
2012
Abstract
In order to decrease CO 2 emission into the atmosphere and develop renewable energy sources for carbon capture, an integrated system is considered for co-production of electricity and methanol. In this research, methanol synthesis unit through captured CO 2 from fossil fuel power plant and produced H 2 from water electrolysis unit by wind renewable energy is developed. An oxy-fuel combustion carbon capture method is considered in large scale Matiant power plant based on utilization of oxygen from water electrolysis unit. Technical and economical analysis of the proposed system shows that when the price of natural gas is 7.8US$/GJ, the total CO 2 avoided cost is 93US$/(tonne of CO 2) and...