Sharif Digital Repository

Protocol identification and reverse engineering have recently received much attention due to their importance in many communication and security applications. In this field, the main challenges are: protocol identification, clustering unknown protocols, extracting protocol fields, and finding the protocol format based on these fields and their relations. Most of the proposed methods for the first two parts (protocol identification and clustering) use machine learning and AI techniques. For the last part, some bioinformatics techniques like sequence alignment algorithms are used. In this thesis, after reviewing different methods for protocol identification and reverse engineering, some... 

One of the new paradigms in information retrieval is to develop textual Question-Answering systems. Question-Answering (QA) is an advanced IR process at which for a natural language question, the answer is extracted and issued in natural language. The QA systems are divided into two general groups: Open-Domain QA and Restricted-Domain QA.
In this research field, a number of different models and methods are developed in which a document collection is used to retrieve candidate answers and then different methods are deployed to detect and eliminate irrelevant ones from answer set. Most of these methods decide based on expected semantic answer type, which is determined using pre-defined... 

Previous researches has established that retrofitting RC (reinforced concrete) columns with FRP (fiber reinforced polymer) jackets is an effective means of providing external confinement to the column cross section. In an effort to evaluate FRP jacketing technology, this study focused on the confinement effectiveness of FRP jackets for rectangular building-type RC columns. Variables investigated include the following: the type of fibers (AFRP, CFRP), the thickness of the jacket, the shape (rectangular or circular) and aspect ratio of the cross section, and the sharpness of the corners of the rectangular cross sections. The sample structures were designed initially without lateral forces and... 

In a solar central system plant about 40% of energy losses occurs in the heliostat field. Furtheremore, half of the investment costs for construction of the plant is related to the heliostat field. Therefore, an optimal design of the heliostat field is necessary for reduction of levelized cost of energy in solar tower power plants. In this study, in order to optimally design the heliostat field, first energy performance of the helistat field in one year is simulated. Solar power and sun’s position at each moment of the day is determined by mathematical relations. Then, loss factors in the field are modelled and heliostat field layout is designed by an algorithm. Finally, by using PSO... 

Today, due to the scarcity of fossil energy resources, security of energy supply, and increasing environmental concerns, we need to develop new technologies to promote energy-saving and reduce greenhouse gas emissions. One of the suitable options for this purpose is to use the simultaneous production of electric power, cooling, and heating. Meanwhile, trigeneration systems that provide part of their energy needs from the sun, due to the free solar energy source and low environmental impact, can be an ideal technology for clean and safe scattered production. The present study has suggested a trigeneration system of cooling, heating, and power generation based on the organic Rankin cycle and... 

Today, due to increasing electricity consumption and demand, the use of conventional systems such as thermal, hydro and nuclear power plants is not enough to convert energy. Over the past century, scientists have sought to discover new technologies for exploiting different forms of energy and converting them into high-efficiency electrical energy. One of these ways is to use the phenomenon of magnetohydrodynamics (magnetic fluid dynamics) to convert thermal energy directly into electrical energy. Magnetohydrodynamics is a theoretical field that studies the dynamics of fluids with electrical conductivity. Induction magneto-hydrodynamic generators use ionized hot plasma (a quasi-neutral gas of... 

The power generation system of this type of power plants operates on the air flowing through the power plant’s chimney and colliding with the turbine blades within the chimney. When the solar collector warms the nearby air and thus expands the air by absorbing the sunlight, a difference is created in the density. Then, this difference in the density creates the phenomenon of buoyancy, making the air pass to the top of the chimney through the collector.This study simulated and optimized a solar chimney power plant. The simulation and optimization were performed based on the information of Manzanares Solar Chimney Power Plant in Spain (located in 150 km from the south of Madrid). It was... 

The issue under discussion in this paper is to optimize the fuel consumption of the Toyota Prius hybrid car. In order to solve this problem, the ADVISOR design model used by NREL in the Matlab / Simulink environment has been used. Various parts of this model are described. The optimization performed on this issue is based on the emotional controller. This controller works by simulating learning in animals based on encouraging and punishing them. With the introduction of the controller, the model and its inclusion in the fuel consumption control and its implementation have achieved good results. In the initial state and the controller in the model, the fuel consumption was 4.9 liters per 100... 

In this thesis, an attempt has been made to provide a smart and innovative system to optimize fuel consumption in cars by using the combination of engineering sciences, aerospace, and machine learning. Considering the current challenges of societies, the economic importance of saving fuel, as well as recent developments in the fields of machine learning and reinforcement learning, this research tries to improve the performance of cars in order to minimize the air resistance force of car bodies. In this regard, deep neural networks have been used to learn the dynamics of aerodynamic forces and reinforcement learning algorithms, especially DDPG (Deep Deterministic Policy Gradient), have been... 

This research has been surveyed the impact of intermediate skilled and high skilled human labor force on the productivity of manufacturing sectors by the Nelson & Phelps and also Lucas approaches. first model is related to the level of productivity and the second model is related to the growth of it. We has been prepared the needed statistics from the raw figures of iran statistics center. regression analysis has been done on the basis of panel data model by the use of stata software. the results show that not good efficiency to optimize technology factor of Cobb-Douglas model although it shows higher marginal labor productivity of high skilled human labor force. we has proposed some... 

Today’s radio transmitters must be able to send information in several standards. One problem involved in these wide band electronic systems lies in its end part, ie power amplifier. To have a broad band width either switching must be made among several power amplifiers with narrow band width (tuned) or the transistor part of power amplifier must be the same and single and selection be made only among matching networks. In this thesis, a power amplifier with broad band width without requiring a matching network has been designed and laid out. Also considering the low breakdown voltage of the gate oxide of the today’s standard CMOS transistors, it is very difficult to get a high output power... 

Hybrid electric vehicles (HEV) are proving to be one of the most promising innovations in advanced transportation systems to reduce air pollution and fossil fuel consumption. EMS is one of the most vital aspects of the HEV powertrain system. This research aims to design an optimal EMS under the condition of meeting the goals of drivability control, fuel consumption reduction, and battery charge stability. The current EMS is based on the classical rule-based method derived from fuzzy logic, which guides to the suboptimal solution in episodic driving cycles. Previous experiences in implementing Reinforcement Learning (RL) suffer from late convergence, instability in tracking the driving...