Sharif Digital Repository

In the present study, an analytical solution is developed to calculate the interlaminar stresses in long generally cross-ply laminated composite plates subjected to bending. At first, upon the integration of the strain-displacement relations and using the existing patterns in deformation of the long laminate, the general displacement field is extracted and simplified to the final form. Presented solution is based on a combined method containing the equivalent single-layer (ESL) theories beside the Reddy’s layerwise theory. In this method, the equivalent single-layer theories are utilized because of their simplicity and low computational efforts rather than the layerwise theory in evaluation... 

Galaxy clusters are the most massive virialized systems in the universe. Their studies provide crucial grasp on the galaxy formation and evolution, dark matter and its nature, cosmological parameters and large scale structure of the universe. Because of their significant role in cosmology, providing a catalogue of galaxy clusters in a wide range of spatial angle, mass and redshift seems vital. Galaxy cluster detection can be performed by various methods in a broad spectrum of electromagnetic radiation. Optical detection of galaxy clusters is of the most traditional and popular methods. Among optical algorithms, one of the most efficient is called Cluster Red Sequence (CRS) which applies the... 

Flow conditions in a confined geometry play an important role on Mach stem formation processes, especially if the fluid is combustible. The purpose of this research is to investigate the impact of the radius of curvature as well as the upstream flow Mach number on Mach stem formation and further to predict to Mach stem height in 90 degree bends. The wave interaction processes as well as the Mach stem formation are studied for both sudden as well as smooth flow turn. Closed form solutions are determined which reveals the position and the size of Mach stem. Results are compared with experimental and numerical data  

Dynamic modeling and process control, especially the equipment of bioreactors and fermenters, have always faced many challenges due to the complexity and high uncertainty of the kinetics of environmental reactions. Among these, semi-continuous fermentation for bioethanol production is one of the important technologies in biochemical industries. The problem of modeling as well as controlling the use of the main discontinuous and semi-continuous methods of ethanol production is the lack of uniform state conditions and the possibility of aerobic and non-aerobic multiplication conditions in two ways. The main goal of this research is to obtain a new method in modeling bioethanol fermentation and... 

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... 

In this project Mordinate and Eu-1 zeolite were synthesized by hydrothermal method and then bifunctional catalysts including acid-base zeolite and Pt-Al2O3 metal base were mixed and made using a planetary mill. The modified catalysts were detected by various methods such as XRD, SEM, FTIR. The aim of this project is to synthesize and characterize the modified catalysts and to escalate their catalytic properties. Our focus is primarily on the synthesis of zeolite-based catalysts modified with unique features such as having active acid sites, high thermal stability and appropriate selectivity for the purpose of investigating the mechanism and kinetics of the C8 aromatic Compounds... 

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.... 

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... 

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... 

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....