The Detection of False Data Injection Attacks in Large-Scale Residential Energy Grids

, M.Sc. Thesis Sharif University of Technology Babaei Ghazvini, Hamid Reza (Author) ; Haeri, Mohammad (Supervisor)

Abstract

This dissertation investigates the detection of false data injection attacks in largescale residential energy grids. A typical multi-micro-grid framework is investigated by considering the geographical dispersion of equivalent models, wherein each microgrid is assumed as an agent and managed by a local aggregator. Furthermore, a fully distributed Nash equilibrium seeking algorithm in the partial-decision information scenario is proposed, where each microgrid estimates the actions of all the microgrids by relying only on the information exchanged with some neighbors over a communication network. To effectively reduce unnecessary signal transmission among the agents, an adaptive algorithm,...

Byzantine agents' detection in distributed nash equilibrium seeking algorithms using an adaptive event-triggered scheme

, Article IEEE Systems Journal ; Volume 17, Issue 3 , 2023 , Pages 4407-4418 ; 19328184 (ISSN) Babaei Ghazvini, H. R ; Haeri, M ; Sharif University of Technology

Institute of Electrical and Electronics Engineers Inc 2023

Abstract

In this article, a resilient, adaptive event-triggered distributed Nash equilibrium seeking algorithm is investigated for a class of multimicrogrid systems. Since the strategy of each microgrid affects others' costs through total generation cost, such interaction among microgrids is modeled as a noncooperative game. To reduce unnecessary signal transmission among the aggregators, an adaptive algorithm, where threshold parameters are adjusted based on the behavior of the estimated signals in the last two iterations, is proposed. It is observed that when false data is injected into an agent, its estimated signals begin to diverge from the equilibrium point, and as a result, the threshold value...

Molecular Dynamic Simulation of Metal and Ceramic Nanopowder Compaction Process and Investigation on Effective Factors

, M.Sc. Thesis Sharif University of Technology Babaei, Mahnoosh (Author) ; Khoei, Amir Reza (Supervisor)

Abstract

In present research forming process of nanopowders, which is a part of powder metallurgy was investigated by molecular dynamics method. Powder metallurgy is a relatively new method for production of industrial parts by pouring powder into die and compaction to desired density. One can reach parts with higher quality and strength by decreasing size of powder’s particles and entering the nano scale. Particle with smaller size have higher specific surface and due more intensity to react. Classic methods for investigation of this process don’t cover the atomic scale effects, so using newer procedures such as molecular dynamics is highly recommended. In present research, at first compaction of...

Reduction of Communication Cost and Effect of Heterogeneity in Federated Learning Via Efficient Clustering of Users

, M.Sc. Thesis Sharif University of Technology Babaei Vavdareh, Mehdi (Author) ; Behroozi, Hamid (Supervisor) ; Hossein Khalaj, Babak (Supervisor)

Abstract

Nowadays sharing data between users and organizations can be difficult due to privacy and legal reasons. Therefore, real-world data is not fully exploited by machine learning methods. A novel model training method called Federated Learning was proposed to alleviate the aforementioned problem by enabling users to jointly train learning models without sharing data. Federated learning utilization faces many challenges among which high communication cost, statistical heterogeneity and system heterogeneity are most important. This research deals with these challenges by proposing two methods of Reduced Clustering Federated Learning (RCFL) and Weighted Federated Distillation (WFD). Moreover, we...

Identification of the Set of Single Nucleotide Variants in Genome Responsible for the Differentiation of Expression of Genes

, M.Sc. Thesis Sharif University of Technology Khatami, Mahshid (Author) ; Rabiee, Hamid Reza (Supervisor) ; Beigi, Hamid (Supervisor)

Abstract

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...

Synthesis & Characterization of Au-HKUST-1 Nanocomposite and Evaluation of Plasmonic Properties of Gold Nanoparticles in this Nanocomposite

, M.Sc. Thesis Sharif University of Technology Moazzeni, Hamid Reza (Author) ; Madaah Hosseini, Hamid Reza (Supervisor)

Abstract

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...

Live Layered Video Streaming over Multichannel P2P Networks

, M.Sc. Thesis Sharif University of Technology Ghalebi, Elahe (Author) ; Rabiee, Hamid Reza (Supervisor)

Abstract

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...

Local Community Detection in Social

, M.Sc. Thesis Sharif University of Technology Rajabi, Arezoo (Author) ; Rabiee, Hamid Reza (Supervisor)

Abstract

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...

Improving Graph Construction for Semi-supervised Learning in Computer Vision Applications

, M.Sc. Thesis Sharif University of Technology Mahdieh, Mostafa (Author) ; Rabiee, Hamid Reza (Supervisor)

Abstract

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...

Investigating Conformal Vector Field on Riemannian Manifolds

, M.Sc. Thesis Sharif University of Technology Hessam, Hamed (Author) ; Fanai, Hamid Reza (Supervisor)

Abstract

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...

Network Topology Inference from Incomplete Data

, M.Sc. Thesis Sharif University of Technology Siyari, Payam (Author) ; Rabiee, Hamid Reza (Supervisor)

Abstract

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...

Continuous Time Modeling of Marked Events

, Ph.D. Dissertation Sharif University of Technology Hosseini, Abbas (Author) ; Rabiee, Hamid Reza (Supervisor)

Abstract

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...

Analysis and Modeling of User Behavior over Social Media

, Ph.D. Dissertation Sharif University of Technology Khodadadi, Ali (Author) ; Rabiee, Hamid Reza (Supervisor)

Abstract

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....

Transportation Planning in the Product Distribution Chain According to Traffic Criteria

, Ph.D. Dissertation Sharif University of Technology Babaei, Ardavan (Author) ; Akbari Jokar, Mohammad Reza (Supervisor) ; Khedmati, Majid (Supervisor)

Abstract

Increased costs due to fuel consumption by vehicles, air pollution and greenhouse gas emissions, safety concerns in accidents, social concerns regarding the satisfaction of the users of roads and routes, and increased delivery time of goods are among the important issues that highlight the need to consider traffic congestion in the supply chain planning. In addition, in supply chains goods are generally transported by medium and heavy transportation vehicles. Their higher weights, bigger sizes and lower speeds are among the characteristics of these vehicles that cause traffic congestion. Therefore, it is necessary to address the topic of traffic congestion in the supply chain planning....

Development of An Agent-based Framework For Optimization of Water and Energy Network Structure

, Ph.D. Dissertation Sharif University of Technology Babaei, Farshid (Author) ; Bozrogmehry Boozarjomehry, Ramin (Supervisor) ; Pishvaie, Mahmoud Reza (Supervisor)

Abstract

Information and Communication Technology and Artificial Intelligence (AI) can support the transition from traditional practices toward smart supply chain coordination schemes. Such a direction allows for integrating organizational levels of natural gas transportation enterprises, comprising Location, Inventory, and Routing Problem (LIRP) decisions. Specific works have investigated the LIRP of natural gas-to-product and energy networks. However, due to the absence of a systematic ICT-assisted mindset, no study has been oriented from the perspective of the dynamic inventory management and geographic data-driven features of land resources. To handle these challenges, this study partially...

Using Statistical Pattern Recognition on Gene Expression Data for Prediction of Cancer

, M.Sc. Thesis Sharif University of Technology Hajiloo, Mohsen (Author) ; Rabiee, Hamid Reza (Supervisor)

Abstract

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...

Relations Between Dynamical Systems And Knot Theory

, M.Sc. Thesis Sharif University of Technology Madani, Meysam (Author) ; Fanaii, Hamid Reza (Supervisor)

Abstract

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...

Sampling in Large-Scale Complex Networks

, Ph.D. Dissertation Sharif University of Technology Salehi, Mostafa (Author) ; Rabiei, Hamid Reza (Supervisor)

Abstract

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...

Active Learning in Image Retrieval

, M.Sc. Thesis Sharif University of Technology Fadaee, Mohsen (Author) ; Rabiei, Hamid Reza (Supervisor)

Abstract

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....

Image Classification Using Sparse Representation

, M.Sc. Thesis Sharif University of Technology Haghiri, Siyavash (Author) ; Rabiee, Hamid Reza (Supervisor)

Abstract

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...