Sharif Digital Repository

The classification of different tumor types is of great importance in cancer diagnosis and drug discovery. However, most previous cancer classification studies are clinical based and have limited diagnostic ability. Cancer classification using gene expression data is known to contain the keys for addressing the fundamental problems relating to cancer diagnosis. The recent advent of DNA microarray technique has made simultaneous monitoring of thousands of gene expressions possible. With this abundance of gene expression data, researchers have started to explore the possibilities of cancer classification using gene expression data and quite a number of Pattern Recognition approaches have been... 

Ambient Intelligence (AmI) is an environment in which devices are embedded and connected to each other with a communication network, working in concert to predict users’ wishes according to the context of the environment (devices and people) to help them with their everyday activities. An ambient intelligent environment should be context-aware. One of the most complicated problems in context-aware computations is recognition of the activities in which users of the environment are engaged. These activities could be recognized by means of the information hidden in communication networks of the devices, especially different sensors embedded in the environment to ease up the process. Most of... 

The accessibility of broadband Internet to home users has pushed video broadcasting applications up, in the list of most favorite applications in todays Internet. Such applications involve delivering the data which generated in a single sender to a set of users which are scattered around the world. While it was formerly believed that the IP-Multicasting is the mean to provide this kind of services, the trend has altered to the use of Application Layer Multicasting techniques due to their deployment simplicty. Since their advent, Peer to Peer applications has mitigated many problems previously unsolved in the field of communication. File sharing, distributed file systems, distributed data... 

In this project we investigate Brouwer’s homeomorphisms in the plane. A Brouwer’s homeomorphisms is an orientation-preserving and fixed-point-free homeomorphism in the plane. For this purpose we prove Brouwer and scoenflies Theorem in the plane. we prove that bounded connected sets in the Plane that are open or closed and meets an infinite number of it’s iterates under Brouwer homeomorphisms must meets all of them.

 

The improvments in computer networks and video compression techniques have motivated the network engineers to broadcast video over the Internet. Recently, Peer-to-Peer networks have been considered as a suitable way for video streaming. P2P networks are distributed and there’s no central management mechanism in them. In addition, video has a time-sensitive nature. Therefore, these networks are vulnerable to security attacks. Denial of Service attacks, attacks on the membership management mechanism, attacks on neighbors selection mechanism, selfish nodes and content pollution attacks are common attack on Peer-to-Peer Video Streaming networks. In a content pollution attack, one or several... 

Simultaneous triangulation of matrices is a subject with a rich literature. There are many well known theorems available, such as McCoy theorem or Burnsides. In the nite dimensional case since the all the topologies on vector spaces are the same, there is a little bit diculty and most of the arguments are from linear algebra. In this thesis we study the simultaneous triangulation of sub algebras of K(X),with X a innite dimensional Banach space. We will give a denition of simultaneous triangulation which is independent of the notion of Basis and totally relies on Invariant subspaces. This denition coincides with the denition of simultaneous triangulation in nite dimensional case. Then we will... 

The IEEE 802.16 is an emerging standard that provides broadband wireless access in metropolitan area networks. The standard facilitates desirable capabilities including mesh topologies and multimedia communications for users.In IEEE 802.16 based mesh networks, there is no explicit uplink and downlink subframes in the physical frame structure and the uplink and downlink traffic scheduling is done within a single time frame. A frame is divided into two subframes: the control subframe and the data subframe. The control subframe is used to carry control messages and the data subframe is used for forwarding data packets to the users.In the mesh mode, two scheduling mechanisms, called centralized... 

Information Technology In the recent years, Peer-to-Peer Networking and Applications has received significant attention from both the Internet users and research area. One of the most successful Applications of P2P networks is streaming the video which is applicable in Internet TV. On the other hand, Complex networks describe a wide range of networked systems in technology, nature and society, such as Internet, WWW networks, P2P networks, biological networks and social interactions.In this thesis we focus on mesh-pull based streaming networks and our goal is to propose a complex network model for such a P2PIPTV topology. To reach to this aim we consider the microscopic processes on each node... 

Error concealment is one of the effective ways to alleviate the effect of packet loss in video communication over error-prone environments. In order to estimate lost macro-blocks, we have employed Bayesian estimation as an efficient and robust framework. Gaussian process regression has been used as the modeling approach through this framework. Considering luminance component as Gaussian process,a minimum mean squared error estimation of the lost macro-block is obtained. This estimator, as a function of the existing data, is only determined by the covariance matrix defined over them. Therefore,the main step in Gaussian process regression, is construction of the convenient covariance matrix... 

Entrance of secular science to Muslim societies has made them face a duality. That is because, on the one hand, they like to preserve their religious values; and on the other, prevalence of secular ideas prevents people from being committed to such values. Therefore, some Islamic scholars proposed religious science as opposed to Western secular science as a remedy to this crisis In case of religious science, explanatory model has the highest position, but disagreement over how to combine experimental and religious characteristics has led to different models in this area. One of the explanatory models of religious knowledge is that of Doctor Mehdi Golshani which has received due attention at... 

In this research, we have used machine learning methods to approach the problem of human activity recognition. As the process of labeling the data in this problem is so costly and time consuming, and regarding the copious available unlabeled data, semi supervised methods have a high performance in this problem. In recent years, graph based methods have became very populaer among semi supervised learning methods. However, constructing a graph on the data which presents their structure in a proper manner has remained a main challenge in these methods. One of the causes of this problem is the existance of the shortcut edges. In this report, we will first introduce a method to solve the problem... 

In this research, we introduce a semi-supervised manifold regularization framework for hu- man pose estimation. Here we aim the three major challenges in discriminative human pose estimation. We utilize the unlabeled data to reduce the need to labeled data and compen- sate for the complexities in the input space. We model the underlying manifold by a nearest neighbor graph. Due to depth ambiguity which is the main challenge in this problem, the true underlying manifold of the data bends and gets too close to itself is some areas which results in poor graph construction. To solve this problem, we argue that the optimal graph is a subgraph of the k-nearest neighbor graph and employ an... 

Mobile Ad hoc networks or MANETs consist of autonomous selfish nodes, which usually have a limited source of energy and choose their own transmission power independently. Nodes are mobile; hence the network topology changes continuously in time, therefore a topology control protocol is required to preserve the network connectivity and to adjust the transmission range of the nodes. Also in the absence of any infrastructure in the network, since the energy source of each node is limited and nodes are not eager to consume it for others, in order to stimulate the selfish nodes to cooperate to provide network services (such as relaying data packets) , we need to exert an incentive mechanism in... 

Communication among people over the emerging networks has been the focus of attention in different branches of science during last decades. Online Social Networks (OSNs), with more than hundreds of millions of users are powerful means for directing information within and across societies. Thus, studying various aspects of OSNs is an important issue for researchers. Due to large number of users and friendship relationships among them, gathering complete information from an OSN is not feasible. On the other hand, hiding users information and crawlers limitations are challenges for gathering complete data. A Common solution for this problem is Sampling from OSNs. Sampling from OSNs (and... 

In this thesis, we have discussed image classification by sparse representation. Sparse representation is used in two different ways for image classification. The first goal of sparse representation is to make an efficient classifier, that can learn the subspace, in which the data lies. In this field we have surveyed various methods. We also proposed a method, called ”Locality Preserving Dictionary Learning” that works approximately better than state of the art similar methods, specially when training data is limited. We have reported the result of lassification on four datasets including MNIST, USPS, COIL2 and ISOLET. Another use of sparse representation, is to extract local features from... 

Compressive Sensing (CS) is a new paradigm in signal processing and information theory, which proposes to sample and compress sparse signals simultaneously and has drawn much attention in recent years. Many signals in lots of applications have a sparse representation in some bases, so CS is used as an efficient way of data compression in many applications such as image processing and medical applications in the last couple of years. Since some of the distributed information in complex networks are compressible too, CS can be used in order to gather the distribted information on the nodes or links efficiently. Traffic analysis and performance monitoring in computer networks, topology... 

Image retrieval, simply put, is the process of finding images in a predefined set , that are similar to an image specified by the user. In particular, the user inputs an image as query, and expects to see images similar to the query. Our purpose is to retrieve the images, by means of visual features, without any use of latent information such as tags and annotations.Afer the first round of retrieval, the answers can become more accurate, by means of user feedbacks. In this state, using active learning methods may be usefull. By using active data selection, we hope to achieve the answer faster. Learning based on manifold assumption, is another means which may be used in image retrieval.... 

Microbial Electrolysis is a new method for producing Biohydrogen from oxidation of organic materials by microorganisms. Generally, this process is depended on two different kinds of energy source containing Organic Material Oxidation by bacteria and Electricity. In this specific study, landfill leachate, extracted from ARADKOOH Tehran Iran was used as a carbon source and effective parameters in Microbial Electrolysis Cell were scrutinized for increasing the hydrogen production and efficiency of COD removal in wastewater. Two H-type rectors with 300 ml of volume in each side were used during the experiments. Various amount of voltages started with 0.4 (V), were tested in the system and it was... 

Many real-world communication systems such as Internet, online social networks, and brain networks can be modeled as a complex network of interacting dynamical nodes. These networks have non-trivial topological features, i.e., features that do not occur in simple networks such as lattices or random networks. The tremendous growth of Internet and its applications in recent years has resulted in creation of large-scale complex networks involving tens or hundreds of millions of nodes and links. Thus, it may be impossible or costly to obtain a complete picture of these large networks, and sampling methods are essential for practical estimation of network properties. Therefore, in this thesis, we... 

Visual tracking is a classic problem, but is continuously an active area of research, in computer vision. Given a bounding box defining the object of interest (target) in the first frame of a video sequence, the goal of a general tracker is to determine the ob-ject’s bounding box in subsequent frames. Utilizing sparse representation, we propose a robust tracking algorithm to handle challenges such as illumination variation, pose change, and occlusion. Object appearance is modeled using a dictionary composed of target patch images contained in previous frames. In each frame, the target is found from a set of candidates via a likelihood measure that is proportional to the sum of the...