Sharif Digital Repository

Renewable energy deployment through distributed energy resources is among the central goals of future power systems. Microgrids have proven to be an economically viable soloution for distributed energy resources integration into power system and benefit the customers with uninterrupted power supply. In this context provisional microgrids have been introduced with the main goal of rapid renewable energy sources deployment. Since a considerable portion of renewable enegy resources as well as residential loads are DC and this portion is expected to grow even further, hybrid AC/DC design of provisional microgrids can improve both efficiency and economic benefit by optimal arrangement of AC/DC... 

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,... 

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... 

In this thesis the calculated dose by corePLAN treatment planning software is compared with the calculated dose from combining BEAMnrc and DOSXYZnrc Monte Carlo codes. First Varian Clinic 2100c/d linear accelerator was simulated and modeling parameters such as electron beam energy and its spatial distribution FWHM were tuned in order for PDD and dose profile curves to have an agreement with less than 2% error with the ion chamber dosimetry. In the second section the derived X-ray beams from the accelerator head simulations were used to calculate dose in different organs of a RANDO phantom. The female RANDO phantom was simulated based on its CT data using DOSXYZnrc code. The CT files of the... 

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... 

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... 

This research deals with one of the current issues in the world and in Iran which is called the field of cryptocurrencies. This research has tried to map the situation of cryptocurrencies in the world and then the situation of Iran in this field.In order to understand the situation of Iran in the field of cryptocurrencies, three main questions have been defined. The Questions that first express the nature of Iran's policies and then determine the position of these policies in relation to the conceptual framework, and then it will discover the reason of the adoption of these policies in Iran.Therefore, this research has an exploratory approach and its research method is qualitative. In order... 

This research deals with one of the current issues in the world and in Iran, which is named the field of cryptocurrencies. Domain that is managed decentrally due to the use of blockchain platform. This decentralization has caused different challenges (security problems, disruption of economic governance, etc.) for governments and has created different advantages and disadvantages for each country. This study seeks to investigate how Iran is facing the challenges in the field of cryptocurrencies. In this research, three main questions have been asked to determine the situation of Iran in the field of cryptocurrencies. In the first question, what are the policies of Iran is questioned and then... 

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... 

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... 

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...