Sharif Digital Repository

In recent years, hardware Trojans (HTs) have become one of the main challenging concerns within the chain of manufacturing digital integrated circuit chips. Because of their diversity in chips, HTs are difficult to detect and locate. This thesis attempted to propose a new improved method for detection and localization of HTs based on the real-time logical values of nodes. The algorithm extracts the nodes with special attributes. At the next stage, the nodes with the greatest similarity in terms of logical value are selected as targets. Depending on the size of the circuit, the extraction continues until a sufficient number of similar nodes has been selected. The logical relationship between... 

Today, with the spread of various videos especially sports video and availability of them, the need for automated methods for search and retrieval of concepts from videos is strongly felt. On the other hand, summarizing video in order to making significant parts of them available is very important. One of the broadest scope that researchers have provided methods for extracting semantic concepts, is soccer videos. Often to extract high-level events, we need a definition and use of intermediate concepts. In this thesis "replay", "audio highlights" and "view type" are used to extract important events in the game. Here, two new methods are introduced for replay detection and view type... 

Gene regulatory network consists of a set of genes; interacting with each other via their protein products. Such interations lead to the regulation of the genes’ production rate. A breakdown in the regulatory process, may lead to some kinds of diseases. Therefore, understanding the gene regulatory process, is beneficial for both diagnosis and treatment. In this thesis, gene regulatory networks are modeled by the means of dynamic Bayesian networks. We have used sampling based methods, in order to learn the network structure. As these methos have a very high computational cost; we have used a correlation test to prune the search space. This way, an undirected network skeleton is obtained; for... 

Image registration is the process of matching two or more images captured at different times, angles or even sensors. Image registration is finding a transformation between two images. Image registration has many applications in different fields of Image Processing and machine vision. In the field of remote sensing, image registration can be used for environmental monitoring, generating graphical maps and gathering data for geogeraphical information systems, also in the field of medical image processing it can be used to detect tumor growth. Generally whenever there is need to extract information from many images; image registration is considered as an important pre-processing step.... 

Price prediction in financial markets is an exciting problem for a vast majority of groups and people; however, investment portfolio managers and owners are always looking for holistic predic-tion approaches and tools having high functional accurate metrics. Strictly speaking, players in fi-nancial markets are always in search of methods and toolboxes since they need to overcome the un-certainty of their buy, sell, or hold decisions in order to reduce the investment risk. In this research, we have tried to deal with the stock price prediction problem as an asset pricing problem and find a novel approach to push forward the state-of-the-art of the problem based on the fundamental pric-ing... 

Human face-to-face communication is an ideal model for designing a multimodal/media human-computer interface (HCI). Recent advances in image analysis and pattern recognition open up the possibility of automatic detection and classification of emotional and conversational facial signals. Automating facial expression analysis could bring facial expressions into man-machine interaction as a new modality and make the interaction tighter and more efficient. In this research an accurate real-time sequence-based system for representation, recognition and analysis of low-intensity facial expressions and facial action uints (FAUs) is presented. The feature extraction is done using facial feature... 

A Mobile Ad hoc NETwork (MANET) is a set of wireless mobile nodes that form a self configured network. MANETs do not have infrastructure and are not currently deployed on large scales. So research in this area is simulation based. Mobility model in a mobile ad hoc network explains the movement pattern of mobile users and is designed to describe the change of their location, velocity and acceleration over time. One of the challenges in this field is the definition of a common mobility model that provides an accurate and realistic movement description of mobile nodes. In this thesis we want to study the mobility pattern of vehicles on Kish Island and compare it with different kinds of... 

Sensor Localization is a crucial part of many location‐dependent applications that utilize wireless sensor networks (WSNs). Several approaches, including range‐based and range‐free, have been proposed to calculate the position of randomly deployed sensor nodes. With specific hardware, the range‐based schemes typically achieve high accuracy based on either node‐to-node distances or angles. On the other hand, the range‐free mechanisms support less positioning accuracy with less expense. The proposed scheme is based on range‐free localization, which utilizes the received signal strength (RSS) from the anchor nodes. In this work, genetic fuzzy and neuro-fuzzy systems are used to yield more... 

In this research we explain a new method for detection of infraction behavior of drivers in highways. There are different approaches to find and register such abnormal and illegal behaviors, such as a camera-based monitoring system and Radar-based infraction detectors. But none of them can recognize and register the weave through traffic or spiral motions of vehicles, because the radar-based systems do not have adequate latitudinal–resolution while their longitudinal-accuracy is moderate. Moreover, the locations of radars are fixed and, the drivers adapt the velocity of their vehicles based on the position of the known radars. Consequently, these systems are inherently not suitable for our... 

Wireless networks with the shared media require Medium Access Control (MAC) protocol that provides contention resolution mechanism. The design of MAC protocol is a challenging issue because of limited energy source and high propagation delay in UnderWater Acoustic Sensor Networks (UWASNs). The most important goal of the MAC design for underwater sensor networks is to resolve data packet collision efficiently with respect to energy consumption. So, selection of MAC protocol is an important task because it has significant impact on the system efficiency. A suitable MAC protocol must consider some factors such as fairness, energy consumption, latency and throughput based on various... 

Content-Based Image Retrieval has been an active research area in recent years, due to the vast amount of digital media available via the Internet. In this work we formulate contentbased image retrieval as machine learning problem using the relevance feedback technique and propose a learning algorithm adapted to specific properties of image retrieval. After studying specific properties of image retrieval as a machine learning problem, we propose a Bayesian framework for image retrieval based on one-class learning and test it on different image datasets. The proposed method is a kernel based approach and can also utilize domain knowledge in the form of prior knowledge in constructing a model... 

This thesis presents several methods time-frequency based approach for classifying the vibration signals of rotatery machine. It uses the features extracted from the time-frequency distribution (TFD) of the vibration signal segments. Results of applying the method to a database of real signals reveal that, for the given classification task, the selected features consistently exhibit a high degree of discrimination between the vibration signals collected from healthy and fault machine. A comparison between the performances of the features extracted from several TFDs shows that the STFT slightly outperforms other reduced interference TFDs.


 

Widespread use of the interconnected devices has caused an increase in the number of online services and the Internet of Things applications. Some of the protocols used in networking equipment does not have the ability to manage the high volume of traffic, scalability and mobility. Existing networks with traditional protocols are rigid and the process of policy-making on network is slow. Manging the huge number of data flows is a complex and time-consuming task. To respond to such problems, in this study a Software defined architecture is proposed as an alternative to traditional network architecture. In this type of networks, administrators have overview on network controllers and network... 

One of the major problems encountered in artificial intelligence is environment interaction. A sensible way for around-interaction is to collect information from sensors and make proper reactions. Generally, in the real world, an intelligent agent needs to know its pose. There are several ways to know the pose of an agent. One of them is based on the fusion of the output of an inertial sensor with the information retrieved from a camera. This leads to enhance the estimation of the pose of an agent. In this research different solutions for this problem are compared. Studies are done with the goal of attitude detection for vehicles and mini-robots, moving on planar surface. For this end, we... 

Visual Question Answering (VQA) deep-learning systems tend to capture superficial statistical correlations in the training data because of strong language priors and fail to generalize to test data with a significantly different question-answer(QA) distribution. To address this issue, we introduce a Visually Directed Question Encoder to replace the commonly used RNNs in base models. our method uses visual features alongside word embeddings of question words to encode each word. As a result, the model is forced to look at the visual information relevant to each word and it no longer produces answers based on just the question itself. We evaluate our approach on the VQA generalization task... 

Throughout history, forming an optimal asset portfolio has been the primary goal of capital owners and managers of investment funds in any economic activity. Achieving this goal is equivalent to trying to minimize the risk caused by the inevitable fluctuations in the capital market and maximizing the overall investment return during the expected period. Investors can operate in various financial markets where there are different stocks and asset classes in each of these markets. The main goal of investors is to identify profitable stocks and form an optimal asset portfolio based on them.Based on this, during the past decades, many studies have been conducted to form and optimize the stock... 

In drilling oil well with respect to depth of several thousand meters, knowing the physical conditions of down-hole well such as temperature, pressure and stress have particular importance in prevention of possible injuries such as breaking the drill bit or increasing temperature. If these data can transfer from down-hole to bore-hole of the well, the operators can prevent from critical conditions such as intertangle of the drill-string. Currently, because of this lack of information, there are irreparable damages in oil industry annually. Based on researches, because of down-hole conditions of the well, these data can’t transfer with electromagnetic telemetry. Currently one of the data... 

Drilling in oil industry, is an expensive process in produce and extract oil from well. Any mistake in drilling may cause many drawbacks for industry owners. Phisic’s quantities information at downhole like tempreture, pressure and force on bit synchronously can inform user from torrid conditions and prevent undesired events by actions like evoke bit from downhole or change at rotation velocity in drilling and finally stop operations. With attention to a lot of problems in data transport from long distance more than one kilometer from downhole, scientists believe that one of the methods to do this process is converting data gathered at the bottom hole to acoustic waves and transmit them to... 

Congestion in Wireless Sensor Networks (WSNs) leads to both packet loss and excessive energy consumption. That is why congestion has to be controlled during the life of a WSN. One of the go well protocols that has tried to tackle congestion in WSNs is PCCP. PCCP utilizes a cross-layer optimization, imposes a hop-by-hop approach and achieves efficient congestion control; however it has got its own shortcomings. Here we have carried out a survey on congestion problem and have proposed a solution called Modified PCCP to elevate the performance of PCCP by making some changes in the scheduler which is designed in the cross layer. Using this model the congestion is controlled and the PCCP protocol... 

Localization of electrical activity in the brain is one of the major problems in cognitive science and neuroscience. Indeed, Source localization is the inverse processing procedure on brain signals to estimate the location and position of resources in the human brain. Current technics for neurological imaging is included fMRI، PET، MEG and ERP. These methods is not appropriated to answer the question that when does each of different components of the brain begin their activity. The EEG signals could be useful to eliminate some of limitations of above methods. The problem with EEG signals collected from the skull is that they don’t refer directly to the location of active neurons. The...