Sharif Digital Repository

With the rapid development of the economy, more people have started investing in the stock market. Predicting price changes can reduce the risk of investing in stocks. Technical data such as price and volume in the stock market is usually used to predict stock prices, and less often other types of data such as market data or fundamental data are used. In this study, we want to determine what impact each of the available data types has on stock prices. For example, data of buy and sell for per capita, capital inflows and outflows for small and large natural and legal investors, information related to the stocks themselves, indicators, fundamental data such as earnings per share (EPS) and... 

In this work, we aim to find a way to identify and forecast transients in nuclear power plants with the aid of semi-supervised machine learning algorithm. Forecasting and identifying transients in nuclear power plants at the early stages of formation are essential for safety considerations and precautionary measures. The use of machine learning algorithms provides an intelligent control mechanism that, along with the main operator of the power plant, raises the transient detection and identification rate. Our algorithm of choice is to change the way data is presented, which is a semi-supervised learning approach. The algorithm consists of two methods: quantum dynamics clustering... 

The ultimate goal of this study is to evaluate the condition of concrete structures using computer vision methods and using powerful tools such as machine learning methods based on visual information. This assessment is performed by detecting damage in these structures. With the aging of structures such as dams, bridges and tall buildings, structural health monitoring is an important task in ensuring their safety and stability. Therefore, rapid assessment of the health of structures and diagnosis of damage after destructive events is of great value in terms of providing resilience of structures. Visual inspection of structures by experts is one of the basic methods of evaluating structures.... 

Increasing the popularity of smartphones and the great ovation of users of mobile apps has turned the app stores to massive software repositories. Therefore, using these repositories can be useful for improving the quality of the program. Since the bridge between users and developers of mobile apps is the comments that users write in the app store, special attention to these comments from developers can make a dramatic improvement in final quality of mobile apps. Hence, in recent years, numerous studies have been conducted around the topic of opinion mining, whose intention was to extract and exert important information from user’s reviews. One of the shortcomings of these studies is the... 

In this thesis, we review some methods related to model-free discrete reinforcement learning and their corresponding algorithms. Our main goal is to present existing methods in an integrated and formal setup, without compromising their mathematical accuracy or comprehensibility. We have done our best to fix the inconsistencies existing in notations and definitions appearing in different areas of the vast literature. We discuss dynamic programming methods, including policy iteration and value iteration and temporal difference methods as well as policy-based methods such as policy gradient, advantage actor-critic, TRPO, and PPO. Among value-based methods, we discuss Q-learning and C51 where we... 

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... 

Gamma ray spectroscopy has a special place in the industrial applications of nuclear radiation. Currently, the most common device for gamma ray detection and spectroscopy is the sodium iodide scintillation detector. Long life and high efficiency and reasonable price of these detectors are the reasons for the development of the use of these detectors in industries and laboratories. But these detectors in the classification of energy sensitive detectors are considered as detectors with low resolution. The presence of broad peaks in the gamma ray spectrum of this detector increases the possibility of interference of peaks related to different energies and makes it difficult to identify the... 

For several years, self-organizing networks have been introduced by 3GPP to reduce the costs of mobile operators. Self-organizing networks, by introducing a kind of intelligence to the mobile network, will cause optimal performance and, as a result, reduce the operating costs of operators. Improving network coverage and increasing user data rates are always among the priorities of operators to increase profits and customer satisfaction. Coverage and capacity optimization is one of the most important functions introduced in self-organized networks. In this study, in addition to the coverage and capacity optimization function, the load balance optimization and the contradictory interaction of... 

Direct Torque Control (DTC) is one of the vector methods to control Permanent Magnet Synchronous Machines (PMSM). In order to achieve an appropriate control in vector control methods, an accurate estimation of flux is indispensable. Flux estimation should be fulfilled in a wide speed range without considerable dependence on motor parameters. Prevalent flux estimation methods are based on integration of stator voltage which is not feasible in low speed, or performed based on assumption of decoupled equations on d and q axis which is not precise for applications with fast dynamic. Different flux estimation methods are investigated in this thesis with the aim of improving the flux estimation in... 

Common induction motors are controlled with the stator voltage and so all the power passes throw the converter. In the Brushless Doubly-fed Induction Motor (BDFM) a converter with smaller size and lower cost can be used. Also its brushless operation and cage rotor are advantages in comparison with doubly-fed induction motors with rotor excitation. Direct Torque Control is a method to control induction motors. Its advantages include fast responses to flux and torque commands, not requiring to know machine parameters except winding resistors, and easy implementation. In this thesis application of this method to control the BDFM is studied. At the first, electromagnetic mechanism and coupling... 

Machining chatter is unstable and destructive vibrations that leads to damages to the surface of workpiece and reduces the tool life. These damages have significant effects on surface quality and material removal rate. Many studies have been done on chatter modeling and control in various machining processes. On the other hand, recently, ultrasonic vibrations have been used in many manufacturing processes including cutting to enhance the quality of products. Therefore, it is important to investigate the effect of ultrasonic vibrations on the stability of cutting process. Although a number of advantages such as improved surface roughness of workpiece and reduced machining forces have been... 

Using superconducting synchronous machine leads to many advantages such as increasing overall efficiency, decreasing mass and valume of peropulsion system, eliminating some restrictions in hydrodynamic design , etc. The goal of this thesis is design of 200 kW, with 250 rpm superconducting synchronous motor for small ship propulsion drive application. The low speed motor can be directly coupled to the propeller whitch eliminates bulky and inefficient gearbox. After comparison of different structures of superconducting synchronous machines, finally rotating superconducting field with stationary copper armature winding is selected as the most approporiate structure for our application.
For... 

Cryptocurrencies are not only regarded as a trustworthy method of financial transaction validated by a decentralized cryptographic system as opposed to a centralized authority, but also as one of the most popular and lucrative forms of trade and investing. Predicting the price of a cryptocurrency is a challenging topic in time-series research. Its intricacy is due to the volatility and large swings of cryptocurrencies' price. The emergence of brand-new cryptocurrencies, which might present a profitable trading opportunity but lack sufficient historical data for technical analysis, prompted us to develop a trading strategy that could be applied universally. The forecast of the next timestep's... 

Ability to differentiate induced pluripotent stem cells to cardiomycocytes has attracted attentions,considering crucial role of the heart in the human body and great potential applications of these cells like disease modeling, new treatment methods and basic research. We are able to analyze the performance of beating cells through recording extracellular field potentials of cardiomyocytes using multi-electrode array (MEA) technology. This analysis is an essential step to use cardiac cells in any future development and experiment. Currently, the electrophysiology experts analyze recorded extracellular field potentials of induced cardiomyocytes by observing all the episodes of each record.... 

In recent years, studying of biological tissues by mass spectrometry imaging (MSI) has been considered due to its selectivity in identifying different compounds in biological tissues, no need for sample preparation, and the possibility of creating the distribution map of these compounds. The complexity of biological tissues due to their heterogeneity, the large volume of data generated, and the effects of competition of other species for ionization in MSI experiments have doubled the importance of using chemometrics to interpret these data. The aim of this work is to quantitatively study Chlordcone as a carcinogenic pesticide and to extract its spatial distribution pattern in mouse liver... 

Ever increasing demand for higher data rate in wireless communication in the face of limited or underutilized spectral resources has motivated the introduction of cognitive radio for dynamic access to spectrum. In dynamic spectrum access a new type of users called secondary users measure the spectrum to see if it is occupied by licensed users (primary users or PU). When channel is empty secondary users can use it to transmit signal. This approach is called spectrum sensing. Hidden PU problem can severely defect detection ability of non-cooperativ spectrum sensing systems. Cooperative spectrum sensing (CSS) uses spatial diversity of spectrum sensors to tackle this problem. There are two kinds... 

In this project an optimized and robust orientation estimation method using IMU and magnetic sensors is presented. Magnetic distortion effects in orientation estimation is also one of the main purposes. Proposed sensor fusion algorithm is based on a complementary filter which provides a quaternion estimation as the algebraic solution of a system from inertial/magnetic observations. To develop the basic sensor fusion algorithm some procedures including a simple calculation to deal better with non-gravitational accelerations, decrease the effect of magnetometer in the presence of distortions and online gyroscope bias estimation is added. Also, a method for classification the different types of... 

Today, titanium and its alloys are the most widely used metals in manufacturing of biomedical implants. But unfortunately, most of bulk (nonporous) titanium alloys implants are facing problems such as stress shielding. If titanium is produced in such a way that has sufficient amount of porosity on the surface and inside of the sample, it provides sufficient space for connection and proliferation of new bone tissues and transmission of body fluids. However, machining of porous titanium causes pore closing. Due to the importance of recognizing the machining mechanism of materials such as porous titanium for manufacturing of implants, in this study micromachining of porous titanium with the... 

In recent decades, electricity generation using renewable energy sources especially wind has gained considerable attention worldwide. Various generating systems have been proposed for wind turbines to convert wind mechanical power into electrical power. Up to 70% of the installed wind turbines incorporate Doubly-Fed Induction Generator (DFIG) and a fractionally rated power converter. Other schemes still have technological and economic penalties such as high cost of active materials, complexity of machine manufacturing and control systems and large and expensive converter, which limit their spread in wind power plants. Among these, Brushless Doubly-Fed Induction Generator (BDFIG) has... 

The Brushless Doubly-Fed Machine (BDFM) is a machine which incorporates the robustness of the squirrel cage induction machine and the speed and power factor control of a synchronous machine. All of these advantages are obtainable from a relatively low rating power electronic converter (e.g. 30% of the machine’s rating). The stator of a BDFM is furnished with two balanced three phase windings of conventional design (power and control winding). These windings differ in pole number and are often excited at different frequencies. Hence, there is no direct magnetic coupling between them. The power winding is connected to a constant-voltage, constant-frequency source and the control winding is...