Sharif Digital Repository

Reinforcement learning is a successful model of learning that has received a lot of attention in recent years and has had significant achievements. However, methods based on reinforcement require a lot of data. Therefore, it is important to find ideas to keep learning at a high level despite the lack of data. Many of these ideas are known as statistical regularity. In this thesis, we study methods to enhance the learning rate, including methods for sharing neural network weights between value function and policy networks. In this thesis we will try to gain a more general understanding of the regularization in reinforcement learning and increase the learning rate by implementing these methods... 

Loosening and gap opening at the bone-implant interface depends on several physiological and mechanical factors such as bone remodeling, stress concentration, and variation in load transfer pathway. Since fracture of orthopedic material at the interface is one of the major failure mode of total joint implants, this study focused on the micromechanical behavior of the interface. Using a two-dimensional FE model, with pure compressive, tensile, and shearing forces applied on bone or cement, ratio of the stress at the interface to the applied stress has been calculated. Stress distribution was considered as a function of porosity,angle of bead contact to surface, as well as size of bead for two... 

The quality assessment of image and video data has became an important and challenging problem in the fields of image/video processing. Oftentimes, the images/videos files are designed to be viewed by a human observer. Further, the number and size of such files
are growing everyday. Thus, computer-assisted monitoring of the quality has emerged as the only possible solution for this challenge. In this thesis, we shall first review the existing techniques for no-reference(blind) quality assessment of image and video data. Next, we propose some new approaches for the no-reference quality assessment of image and video data in-the-wild. In the case of images, our contributions consist of two... 

Single nucleotide polymorphs, There are changes caused by a mutation in a nucleotide in the Dena sequence. Mononucleotide polymorphisms are the most common type of genetic variation. Some of these changes have little or no effect on cells, while others cause significant changes in the expression of cell genes that can lead to disease or resistance to certain diseases. Because of the importance of these changes and their effect on cell function, the relationships between these changes are also important. Over the past decade, thousands of single disease-related mononucleotide polymorphisms have been identified in genome-related studies. Studies in this field have shown that the expression of... 

In the past few years, many research works on the controllable integration of metal nanoparticles and metal-organic frameworks were done, since the obtained composite material shows a synergism effect in catalysis and photocatalysis, drug delivery applications, gas, and energy storage, as well as sensing. For the first time, in this study, we employed template-assisted growth to synthesize Au-HKUST-1 Nanocomposite. XRD analysis entirely confirms that employing this strategy in synthesizing Au-HKUST-1 was wholly successful, and the plasmonic properties of this nanostructure were studied via UV-visible spectroscopy. In the course of synthesis, gold nanoparticles with 70nm diameter were... 

Our bodies are made from billions of individual cells and DNA is the control central of each cell. In addition to linear DNAs, there are circular DNAs in nature. Circular DNAs cause new topological structures such as knots and catenanes. These topological structures form during biological proccesses such as replication. For example during replication, two daughter circular DNAs may link together and form catenanes. Anzymes named topoisomerases can simplify the topology of circular DNAs. Type 2 topoisomerases is used for simplification of catenanes. These anzymes do it with breaking a double-strand DNA and passing through another one. In comparison with DNAs, topoisomerases are very small and... 

Nowadays, video streaming over peer-to-peer networks has become an interesting field to deliver video in large scale networks. As multi-channel live video streaming networks increase,distributing video with high quality among channels faces many challenges. The most significant challenges cause from frequent channel churns, unbalanced channel resources, network heterogeneity and diversity of users’ bandwidths. They include: nodes’ unstability, low users participations, large startup and playback delays, low video quality received by users and lack of resources in unpopular channels.In order to solve the above problems, we have proposed several solutions such as: 1- using distribution groups... 

The fast growth of social networks and their wide range of applications have made the anal-ysis of them an interesting field of research. The growth of concern in modeling large social networksand investigation of their structural features leads studies towards community detec-tion in such networks. In recent years, a great amount of effort has been done for introducing community detection algorithms, many of which are based on optimization of a global cri-terion which needs network’s topology. However, because of big size of most of the social networks , accessing their global information tends to be impossible. Hence, local commu-nity detection algorithms have been introduced. In this... 

Semi-supervised Learning (SSL) is an extremely useful approach in many applications where unlabeled data can be easily obtained. Graph based methods are among the most studied branches in SSL. Since neighborhood graph is a key component in these methods, we focus on methods of graph construction in this project. Graph construction methods based on Euclidean distance have the common problem of creating shortcut edges. Shortcut edges refer to the edges which connect two nearby points that are far apart on the manifold. Specifically, we show both in theory and practice that using geodesic distance for selecting and weighting edges results in more appropriate neighborhood graphs. We propose an... 

At first the killing vector fields will be investigated. Conditions are introduced for the hypersurface of a Riemannian manifold with a killing vector field to be equipped with the same killing vector field. Then 2-killing vector field is studied and its relation with killing vector fields and monotone vector fields is presented. After that conformal vector fields are discussed and conditions are introduced in order that the Riemannian manifold equipped with a conformal vector field, isisometric to n-dimensional sphere with constant curvature. Finally we will present the conditions which conformal vector field is a 2-killing vector field. Then we will present the results in which the... 

During the last decade, there have been a great number of researches on complex networks.Data aggregation is the first step in the analysis of these networks. However, due to the large scale of them, almost never is there complete information about a network’s different aspects. Therefore, analysis of a complex network is usually done based on the incomplete data. Al-though a good sampling approach in a way that the achieved sample is a good representative of the whole network has its own challenges, analysis of incomplete data causes a significant alternation in the estimation results. Consequently, one of the first problems emerging after sampling is the possibility of predicting the... 

A great deal of information are continuously generated by users in different contexts such as social networks and online service providers in terms of temporal marked events. These events indicate that what happened to who by when and where.Modeling such events and predicting future ones has interesting applications in different domains such as item recommendation in online service providers and trending topic prediction in online social networks. However, complex longitudinal dependencies among such events makes the prediction task challenging. Moreover, nonstationarity of generative model of events and large size of events, makes the modeling and learning the models challenging.In this... 

Nowadays many of us spend a big part of our daily times on social media.One of the most important research problems in social media analysis is how to engage users. The trace of user activity over these websites is a valuable resource for user understanding and engagement, but this data is very huge and unstructured. An approach to deal with this problem is user behavior modeling. In this process, first a behavioral model is considered for users, then using the activity data and the behavioral model, some parameters are learned. Finally, using the learned parameters, a user profile is constructed for each user. This profile can be used for user engagement and many other applications....