Sharif Digital Repository

Control charts are the most popular Statistical Process Control tools used to monitor process changes. However, they are not capable of identifying the real time of a process change, which is essential for diagnosing assignable causes of the change. Therefore, a number of methods of change-point estimation have been developed. In the literature, relatively little study has been done on multiple changes. In this research, a new method based on Maximum Likelihood Estimator (MLE) is introduced to identify linear drifts and step changes in multivariate multiple linear profiles. Due to the massive increase in the amount and time of the calculations along with the growth of the number of the... 

In the past few decades, regarding the advancement of science and technology, the application of Unmanned Aerial Vehicles (UAVs) are increasingly on the rise. One of these applications is to search and localize ground targets. Among the advantages of drones, removing the manpower to carry out exploration and positioning is one of the most important benefits. This feature can reduce the risk of mission, reduce the burden of the plane and increase the height and range of operations. On the other hand, using a group of intelligent robots to increase speed and accuracy in the mission, is one of the topics that have been discussed in recent years. By merging these two topics and utilizing a... 

In this thesis, at first upstream transient error propagation and amplification phenomenon is introduced. Then, the previous methods to attenuate this phenomenon are presented. To overcome this drawback, a new method that is based on feed-forward and off-take disturbance estimation and lost data reconstruction in wireless communication is presented. In this thesis, an estimation of unknown off-take disturbance at the present time is approximated or in fact predicted using the last data. Also, in the presented method, the lost data is reconstructed using two different methods. At the end, the satisfactory performance of the proposed control method is illustrated by many computer simulations  

Characterizing cellular states in response to various disease conditions is an important issue which is addressed by different methods such as Large-scale gene expression profiling. One of the most important challenges in front of bioinformaticians is the loss of data because expression profiling is still very expensive. It is understood that profiling a group of selected genes could be enough for understanding all of the gene expression profile.In this research, we propose a fast method for estimation of the missing values inlow-rank matrices. We consider the highly correlated expression profiles as a low-rank matrix. Then, we used this new method in a proposed algorithm which will select... 

To provide a safe environment for space equipments and infrastructures in addition to managing the role of hazardous objects that are known as space debris, the presented thesis describes a new robust technique to estimate the dynamic states and inertial parameters of Uncooperative Space Objects (USO) with uncertain dynamics in the cluttered orbits. The prescribed method is especially effective to capture stray objects, capture and servicing of the satellites, rendezvous and collision avoidance maneuvers, space explorations as well as Actrive Debris Removal (ADR) missions. Such missions call for high degree of precision and reliable estimation methods. The proposed estimation architecture... 

In this document, the cooperative estimation of states between two interceptors and one target is expressed in order to evaluate the effect of information sharing in different situations on the estimation performance. Due to the importance of the proper estimation of the target acceleration in advanced navigation rules, the main focus of the document is on a more precise estimation of the absolute states of the target. For this purpose, a filter based on the extended Kalman filter was used as an estimator, and to evaluate the promotion of the estimation performance, the combination of measured data was used in two different ways. Matlab Simulink is the simulation software used. The dynamics... 

In examining protein-protein interaction networks, we often encounter similar and repetitive schemes. Examination of these designs, which often appear in the form of motifs and similar patterns, reveals important information such as the type of protein linkage and many of the internal similarities between these networks. The ability to recognize these similarities plays an important role in identifying the function of genes, recognizing the relationships between diseases, and making drugs. We know that exact algorithms for examining subgraph isomorphism are np-hard and time-consuming and infeasible in large networks; Therefore, in practice, approximate and heuristic algorithms are used and... 

Sensors are one of the most vital instruments in Nuclear Power Plants (NPP), and operators and safety systems monitor various parts of the NPP and control transients by analyzing the values reported by the sensors. Failure to detect malfunctions or anomalies in them would lead to catastrophic consequences. A new approach based on thermo-hydraulic simulation by RELAP5 code and Feed-Forward Neural Networks (FFNN) is given to detect faulty sensors and estimate their correct value which are two main objectives of the current study. This approach consists of two main parts; The first part, Fault Detection Hyper Block (FDHB), responsible for detecting faulty sensors, and the second part,... 

We study the expected value of stopping times in stochastic processes. Since there is no rigorous solution for computing stopping times in many processes, our approach is based on estimation using well-known methods in the Reinforcement Learning literature. The primary method in this research is the temporal difference algorithm. With some modifications, we can study the role of some state features in determining the stopping time. Moreover, without a complicated mathematical analysis, we can find functions closely enough to the goal function.Furthermore, we compare our proposed algorithm to the well-known regression methods and show our algorithm's advantages and disadvantages. The primary...