Sharif Digital Repository

Crop classification is one of the most important applications of remote sensing in agriculture. Knowing what crops are on the farm is invaluable both on a micro and macro scale. For example, this information can be used to design and imple- ment agricultural policies, product management and ensure food security. Also, this information can be used as a prerequisite for implementing other programs at the farm scale, such as monitoring and detecting anomalies during the crop growth cycle. Most of the studies in this field are focused on the optical data of the Sentinel-2 satel- lite, but the optical data are vulnerable to atmospheric conditions, and on the other hand, there is valuable... 

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... 

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... 

In recent years, the spread of neurological disorders worldwide has been increasing, especially in developing countries. Due to the unknown function, complexity, and high importance of the brain, such disorders have been pervasive, severe, prolonged, and impose enormous costs on the individual, the family, and the community. Thus, increasing the knowledge about the brain and its areas in various activities is too vital and can facilitate the diagnosis and treatment of many different and unknown neuro- logical disorders. Different kinds of research have been done to automatically process and find the active and vital areas in various states and brain activities. The problem with most of these... 

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... 

The energy consumed by lighting, heating, ventilating, and air conditioning (LHVAC) systems have been increasing over the last decades. Thus, improving the efficiency of LHVAC systems has gained the attention of industry and academia. This concern has posed challenges for controlling and optimizing LHVAC systems. The traditional methods, such as on/off and PID approaches, usually involve conditions and parameters that may not hold in practice since LHVAC systems are complex, nonlinear, and dynamic. Also, controllers are one of the important components of a method for its efficiency. This research focuses on controlling LHVAC systems. Fuzzy logic controllers one of the best controller for... 

It is believed that the synchronized activity of different brain areas, is the main cause of information binding inside the brain. Tis is definitely one of the most exciting challenges in modelling modern complex systems. Brain disorders such as schizophrenia,Alzheimer’s disease, epilepsy, autism and Parkinson’s disease are associated with abnormal synchronization abilities of neural networks. Functional connections can be assessed indirectly by measuring the electrophysiological criteria of ynchronization.Traditionally, in the study of neurophysiological, synchronizations are assessed by analyzing the coherence of frequency-domain characteristics of time series in standard methods for... 

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... 

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... 

Today with increasing advancement of robotic technology, we witness the increment of robots role in humans’ life. One of the issues always present for robots is routing which may require locating their position. Most of these robots make use of sensors like gyroscope, accelerometer and GPS to estimate their position. But each of these sensors has their own short comings such as drift or being unavailable in certain environments. Fusion of inertial and vision sensor’s data can be used to reduce the impact of these errors. Considering the time consumption of image processing and accumulating error of inertial sensor, this combination can be very useful. This approach is also used in... 

Sensor networks is a set of sensors (nodes) which are communicating with each other, and gather information from different environments, and process them to give us valuable results. Sensors have a small energy source like a small battery which have to be used efficiently. Congestion detection and avoidance, together are of great importance in Wireless Sensor Networks (WSNs) in case of traffic load, data loss, and power consumption. In this work, we propose a new APS layer (application support sub-layer), which is another key standard component of Application layer, offering a well-defined interface and several control services. It functions as a bridge between the network layer and other... 

Disturbances due to sensor runout and mass unbalance are the main sources of harmonic disturbances in active magnetic bearing systems. Existence of this type of the disturbance not only causes harmonic vibrations in the system but also changes the steady-state position of the axis of rotation from the geometric center of the AMB. In this research, an observer-based control method used to estimate and reject this disturbance. Proposed integral observer estimates dc and harmonic content of the sensor runout and also estimates the states of the system at the same time with good precision. Lyapunov method is used to prove asymptotic stability of the proposed observer and demonstrated that sensor... 

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.... 

Image classification is one of the most challenging issues in computer vision. One sort of such classifications is Scene Classification. To perform automatic classification reserchers used many aproches.The general approach used features directly extracted from the image, such as color and texture or features extracted by the SIFT algorithmetc. Another method is based on recognizing object of the Scene (espessially indoor scene). This method is based on finding of a limited number of prespecified objects. In the proposed method, first a window surrounding each objects, (regardless of the type of object) founded. Then the SIFT feature is extracted from that window. All features (corresponding... 

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... 

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... 

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... 

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.


 

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...