Sharif Digital Repository

In the present study, we examine the behavior of institutional investors in response to fluctuations in the Iranian stock market. Specifically, we examine the question of whether, in significant market fluctuations, institutional investors engage in grievous trading behavior and follow market trends or move in the opposite direction of the market and provide liquidity. For this purpose, we examine the relationship between the percentage of ownership of institutional shareholders and the stock price return and the trading volume of companies in severe market fluctuations. Also, we obtain the relationship between the percentage of ownership of institutional shareholders and stock price returns... 

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... 

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... 

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.... 

Cancer is the leading cause of death worldwide, and colorectal cancer is the second leading cause of death in women and the third in men. On the other hand, colon polyps can cause colorectal cancer. Therefore, early detection of polyps is of great importance. In recent years, many methods have been proposed for polyp detection using deep learning with high accuracy, but most of them have problems with speed, accuracy, or interpretability. Speed is important because colonoscopy should be performed as quickly and promptly as possible, and in many cases, it is not possible to repeat the colonoscopy. In addition, many of them only address the issue of polyp detection, while from a medical point... 

One of the main sources of genetic variations are structural variations, including the widespread Copy Number Variations (CNVs). CNVs include two types, copy of genetic material (duplication) and loss of part of genetic sequence (deletion) and typically range from one kilobase pairs (Kbp) to several megabase pairs (Mbp) in size. Most of the copy number variations are occured in in healthy people; however, these variants can also contribute to numerous diseases through several genetic mechanisms (e.g. change gene dosage through insertions, duplications or deletions). The CNV study can provide greater insight into the etiology of disease phenotypes. Nowadays, with the huge amount of investment... 

The main goal of this thesis is to classify minimal translation surfaces of three-dimensional Euclidean space. In pursuing that, a method will be introduced that constructs explicit examples. A translation surface is the sum of two regular curves α and β. A minimal surface is a surface, with zero mean curvature. Will be shown that besides the know examples (plane and surfaces of Scherk type) any minimal translation surfaces can be described Ψ(s, t) = α(s)+α(t) , where α is the unit speed curve and its curvature κα is a positive solution of (y ′ ) 2 + y 4 + c3y 2 + c 2 1 y −2 + c1c2 = 0 and its torsion is τ (s) = c1/κ(s) 2 . the above coefficients and their relations will be described  

A decade after discovery of graphene, the unique properties and characteristics of two-dimensional materials, particularly an emerging family of carbides and nitrides (MXenes), have attracted the attention of researchers. MXenes are two-dimensional structures of two or more layers of transition metals, with interstitial carbon and/or nitrogen atoms, with exceptional properties such as high specific surface area, excellent elastic modulus, metallic conductivity, and various termination groups. These properties can be altered by various factors, including chemical composition and synthesis processes, and any changes in these factors significantly affect the properties of MXene sheets. In this... 

Multiple object tracking refers to the detection and following of target object classes in video sequences. In this task, all objects belonging to the target classes in the video are detected simultaneously in each frame, and a unique ID is assigned to each of them throughout the video. In recent years, the use of graph neural networks for solving this problem has received significant attention because these models are suitable tools for discovering and improving the relationships between objects in the scene, which can greatly assist in better object pairing. However, there are various challenges to using graph neural networks, the most important of which is the limitation of input graph... 

With the advancement of technologies related to electroencephalography signals, brain and computer interfaces, the program has received much attention. This report deals with one of the new and important issues in this field, i.e. converting thought into text. In this research, the letters, words, and sentences that a person thinks or utters in his mind are decoded and converted into text based on electroencephalography signals. There is still no credible and credible information in neuroscience about whether the same patterns of neuronal activity occur in the brain when thinking about similar letters or words. However, the remarkable growth and development of deep neural networks has made... 

In the new era of machine vision, action recognition in videos remains a pivotal and essential challenge. With advancements in processing capabilities and the rise of digital data, multimodal networks like CLIP (Contrastive Language-Image Pre-training) have emerged, adeptly bridging the connection between visual and linguistic data. While these networks are tailor-made for images and associated texts, they falter when confronted with motion data in videos. In this research, we propose a novel dual-stream architecture aiming to augment action recognition in videos, astutely blending the encoding prowess of the VideoMAE model with the representational strength of the CLIP model. Our design... 

During the last decade, the study of various aspects of social networks has received in- creasing attention. Communication and information propagation among network mem- bers are important issues in social networking. The diffusion process is a fundamental mechanism by which information, behaviors, or new ideas spread over the network. This process starts from a small group of nodes and continues until the majority of members are affected. Although it is possible to observe the times when nodes become infected, de- termining who infected each node is often difficult to ascertain. Analyzing and modeling the diffusion process has various applications in marketing, politics, and social studies. Most... 

Red phosphorus, due to its unique chemical properties, and glycidol, with its reactive functional groups, provide an effective combination for synthesizing new copolymers with potential applications in biological fields, particularly in enzyme stabilization. In this study, a novel copolymer was synthesized using red phosphorus and glycidol through an anionic ring-opening mechanism. The synthesis process was confirmed using various analytical techniques, including FTIR, NMR, and thermal analyses, which demonstrated the successful incorporation of functional groups and an average phosphorus content of 40% in the copolymer. In the next step, modification of this copolymer by linking it to the... 

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...