Sharif Digital Repository

What determines the function of a protein, after its synthesis by the ribosome, is its unique three dimensional structure. The unique structure of protein is achieved through process of folding which is detrimental to protein function. Although this unique structure is stable in a variety of situations, the protein may undergo conformational change, due to slight changes in physiological conditions, affecting the protein structure and function. In certain conditions, the conformational change brings about misfolding of the protein leading to protein aggregation. The protein aggregation can also result in amyloid formation in which a soluble protein is converted to fibrils with specific... 

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... 

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.... 

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... 

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... 

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... 

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... 

Multimedia applications which exploit the network resources are best provided in broadband networks. Additionally, broadband wireless access systems enable broadband access in places where the wired solutions are not applicable. The IEEE 802.16 standard is designed to provide broadband wireless access and addresses the PHY and MAC layers of wireless metropolitan area networks. This standard has been designed to support quality of service for different applications, and due to their various requirements has considered four classes of service for connections. However, quality of service support mechanisms (such as admission control and packet scheduling), are out of the scope of the standard.... 

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... 

In fact knot theory is working by an elastic string. A knot is A smooth embedding of in . We say that two knots are equivalent if there is an ambient isotopic between them. In knot theory we study equivalent classes of knots. As it seems from its name, a dynamical system is the study of motions, mechanics and dynamics of a system. We will observe some systems and stability of orbits in theme. Then we define templates which contain orbits in themselves. At last, we observe relations between discrete dynamical systems and knot theory. Then for any arbitrary chaotic knot we observe that there exist an universal template that contain a copy of any kind of not. Finally we will study some open... 

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.

 

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... 

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...