Sharif Digital Repository

The functional network of the human brain is altered in many neurological and psychiatric disorders. Characterizing brain activity in terms of functionally segregated regions does not reveal anything about the communication among different brain regions and how such inter-communication could influence neural activity in each local region. The aim of this project is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the simulated, realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral... 

Graph partitioning, or graph clustering, is an essential researa problem in many areas. In this thesis, we focus on the partitioning problem of unweighted undirected graph, that is, graphs for which the weight of all edges is 1. We will investigate spectral methods for solving the graph partitioning and we compare them. In addition to theoretical analysis,We also implement some of spectral algorithms in matlab and apply them on standard graph data sets. Finally, the experimental
results obtained are offering  

Complex directed networks are widely used in representing, modeling and summarizing various homo and heterogeneous real networks such as protein-protein interactions, social and twitting networks, brain connectomes, chipsets mapping and marketing. While working on undirected networks in the hope for detecting communities or any other static and dynamic structures, has been on agenda of many physician and computer scientists, dealing with directed ones seems more challengeable for quick advances. Availability of theoretical basis especially symmetric adjacency matrix recommends modeling with undirected graphs but we believe that directed graphs are more general and practical to model real... 

Perceptual memory used in novel vs familiar discrimination is not only vital for the evaluation of environmental variations but also essential for learning, perception, and correcting behavioral policies. On the other hand, value-based memory which allows for discrimination of valuable objects among equally familiar ones also drives behavioral interactions and decision making. Although many studies have been conducted to address the neuronal association regarding each separately, the neural correspondence between perceptual and value-based memory is not scrutinized adequately. To this end, the differential neural activation in two macaque monkeys to unrewarded novel vs familiar fractals (>100... 

Content-based spam filtering problem is defined as classifying input emails into spam and legitimate emails. so it is considered as an application of supervised-learning. The supervised learning methods often require a large training set of labelled emails to attain good accuracy and the users should label huge amount of emails. In reality, it is not reasonable to expect users to do this. To address this issue and reduce number of labelling request from user active learning techniques can be used. The goal of active Learning algorithms is to achieve appropriate accuracy by using fewer amounts of labelled data in comparison with supervised-learning methods.In this thesis two active learning... 

Autism spectrum disorders (ASD) have been defined as developmental disorders characterized by abnormalities in social interaction, communication skills, and behavioral flexibility. Over the past decades, studies using various genetic, neurobiological, cognitive and behavioral approaches have sought a single explanation for the heterogeneous manifestations of ASD, but no consensus on the etiology of ASD has emerged. Further studies aim to clarify the mechanism of disease.
Functional Magnetic Resonance Imaging (fMRI) is a new way of imaging which evaluates activity of brain by measuring magnetic difference caused by oscillation in blood oxygen level. fMRI has been widely used in recent...