Sharif Digital Repository

Briefly, the accomplishment of movies is based on their sales at the box office or gaining an achievement at the film festivals. Utilizing AI calculations and machine learning algorithms, various models have been proposed for the prediction of these achievements in the literature such as predicting the success of movies using regression models or the success of movies using discrete decision models is anticipated, and in another study the effect of social media data on sales investigated. The methods which are used to tackle these problems can be referred to as machine learning algorithms including neural networks, regression models, discrete decision-making models, public and experts... 

Control of complex networks is the main topic in this study. In this thesis, we consider the methods to steer the dynamics of a network from an initial state to the desired final state. To achieve this goal, one needs to inject appropriate control signals from some of the network nodes, known as driver nodes. We consider the quadratic sum of control signals as a cost function, to control the dynamics of the network. By minimising the cost function, we obtain the control signals as well as driver nodes for a linear time-invariant system. As an example, we provide the results of an energy minimization strategy to control the second order Kuramoto and Rössler dynamics in Erdos-Renyi and... 

Chlorophyll-a, as an important component in evaluating water resources, has a significant impact on the status of water resources. This component is dependent on various quality parameters, such as phosphorus concentration, nitrogen concentration, turbidity, suspended solid concentration, temperature, pH, and dissolved oxygen concentration in water. To evaluate the quality status of surface water, it is necessary to estimate the exact concentration of chlorophyll-a in different temporal and spatial ranges. The objective of this study is to simulate and predict the concentration of chlorophyll-a in different temporal and spatial ranges using a combined application of machine learning models,... 

Increasing in social communication via electronic ways has been made social network analysis of these communications more important each day. One of the most important aspects in social network analysis is community detection in such networks. There are many different ways to extract communities from social graph structure which in some of them the content of communication between actors has been noticed in community extraction algorithm. In this thesis after a short survey over advantages and disadvantages of existing methods for community detection, a new method for extracting communities from social networks has been suggested which in addition to streaming property of data it spot the... 

One of the most efficient techniques deployed for end-stage renal disease remedy is kidney transplantation, but in this case, we commonly encounter with the problem of gap between the demand of patients and supply of donors. In the majority of models has been proposed until now, either kidney exchange technique in a pool of incompatible pairs or kidney allocation system from deceased donors to waiting list is recommended. In this research, in order to enhance kidney transplantation plans, first, a hybrid conceptual model is proposed. Then, its mathematical model is discussed, in which some of the transplantations are selected from kidney allocation system before injecting to the pool of... 

The standard model of Cosmology (SM), based on Einstein’s theory of general relativity (GR), is the best model in describing the cosmic-scale observations. In galactic scales, however, galactic dynamics show a discrepancy between the observed luminous mass and the predicted value from the theory. Two approaches are suggested to eliminate this inconsistency: assuming the existence of dark matter within the context of GR, or modifying the theory of gravity in galactic scales, like MOND or MOG. In this thesis, we study the spherical collapse and the formation of shell galaxies in MOG, in comparison with SM. We introduce the action and the field equations of MOG and the equation of motion of a... 

Strongly Rayleigh measures are an important class of negatively dependent (repulsive) probability measures. These measures are defined via a geometric condition, called “real stability”, on their generating polynomials, and have interesting probabilistic properties. On one important property of negatively dependent measures is their rigid dependence structure. In other words, the it is impossible for these measures to have strong overall dependencies. In this thesis, we study two manifestations if this phenomenon: (1) paving property and (2) tail triviality. Informally, the paving property states that it is possible to partition the set of the components of every strongly Rayleigh random... 

In this thesis, consider three important questions in the Iranian Wholesale Electricity Market (IWEM) and answer its. The first one is whether the bidding behavior of the firms in the IWEM has been ex-post optimal? The results of the research show that, on average, the firm’s bidding behavior didn’t optimal in the IWEM, and therefore the bidding strategy of them could be improved. This issue is importance from the regulatory viewpoint in terms of assessing market efficiency and market power of firms, as well as from the firm’s point of view to improve the bidding strategy and increase its profits. The second issue is the assessment of the firm’s ability to exercise unilateral market power by... 

Multi-part rotating parts are used in various industries with very high revolutions. Therefore, the method of assembling each part and keeping the axis of rotation of each part close to the axis passing through two supports (bearings) is important. In this research, three main steps are followed, the development of the differential equations governing the multi-part rotating system and the calculation of the range of oscillations created at the critical points, and then the calculation of the optimal assembly angles with the aim of reducing the introduced oscillations, and finally the discussion of crossing the speeds A crisis is being investigated. The method of obtaining the system of... 

MQTT (Message Queuing Telemetry Transport) is one of the essential and widely used protocols in the Internet of Things (IoT) networks. It operates at the application layer (Layer 7) for data transmission. As IoT applications using this protocol for communication have grown, securing such systems against security attacks has become a significant challenge. One of the important attacks implementable by IoT networks is Distributed Denial of Service (DDoS) attacks. In this thesis, we initially provide a general overview of IoT security and demonstrate how DDoS attacks disrupt the availability feature in these networks. We then examine known types of DDoS attacks to gain a better understanding of... 

There are several methods for measuring thin film thickness, however, for the analysis of liquid film motors [1] we need a method which is capable of measuring the thickness using a single image of the film. In this work, we use the colors that appear on thin films, such as soup bubbles, which is a result of light interference to calculate the thickness of the layer  

One of the most elusive problems in quantum mechanics is the transition between classical and quantum physics. This problem can be traced back to the Schrodinger's cat. A key element that lies at the center of this problem is the lack of a clear understanding and characterization of macroscopic quantum states. Our understanding of Macroscopic Quantumness relies on states such as the Greenberger-Horne-Zeilinger(GHZ) or the NOON state. Here we take a first principle approach to this problem. We start from coherence as the key quantity that captures the notion of quantumness and demand the quantumness to be collective and macroscopic. To this end, we introduce macroscopic coherence which is the... 

With confidence in the recorded observations, the RLS method no longer estimates the recorded measurements by sensors, i.e. the displacement and speed of the floors, and only estimates the parameters. In contrast, in the EKF method, in addition to estimating the structure's parameters, a more precise estimation of the observations recorded by the sensors has been done by accepting the noise in the recorded observations. These methods, which are based on the Bayesian updating, investigate the two primary sources of uncertainty in a problem: a) measurement noise or observation noise, and b) process noise, which includes modeling errors. In these methodologies, the unknown system parameters,... 

Knee arthritis is a painful disease from which millions of people around the world are suffering. One of the main causes of osteoarthritis and joint damage that starts from a young age, is that bones around the knee are not in a straight line. As a result, this situation causes additional pressure to the knee. This should be corrected with surgery. There are two procedures for this operation, a conventional method and a customized method. In conventional method, surgical planning is based on 2d X-ray images and plates are formed and fixed approximately at the desired location. This method is not precise enough and may cause problems for the patient. A new developing method, is that all the... 

Entanglement is one of the key resources of quantum information science which makes identification of entangled states essential to a wide range of quantum technologies and phenomena.This problem is however both computationally and experimentally challenging.Here we use autoencoder neural networks to find semi-optimal measurements for detection of entangled states. We show that it is possible to find high-performance entanglement detectors with as few as three measurements. Also, with the complete information of the state, we develop a neural network that can identify all two-qubits entangled states almost perfectly.This result paves the way for automatic development of efficient... 

The vortex tube is a simple device that injects compressed gas (air) tangentially into the vortex chamber through one or more injection nozzles. After entering, the flow becomes rotational and an axial cold flow goes towards the cold outlet and a peripheral hot flow goes towards the hot outlet. Besides all the different applications of the vortex tube, the main application of this device is cooling. Here, the goal is to optimize the geometry and physical conditions to improve the performance, which is done by using a commercial software and numerical analysis of a vortex tube to understand the flow physics and optimization. In this research, we use experimental and numerical data for... 

Quantum Information Processing (QIP) is one of the active areas of research in both theoretical and experimental physics. Any experimental technique that is used for a scalable implementation of QIP must satisfy DiVincenzo’s criteria [17]. Nuclear Magnetic Resonance (NMR) satisfies many of these conditions, but it is not scalable and cannot initialize the qubits to pure state [28]. NMR can be a great platform for studying the fundamentals of QIP. In this project, for a two­qubit system, we prepare pseudo pure states from the initial mixed states by using unitary operations and implement CNOT gates. According to the results of our experiments, we can apply all the gates with high fidelity....