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A novel design of the KASUMI block cipher using one-hot residue number system
, Article Middle East Journal of Scientific Research ; Volume 11, Issue 8 , 2012 , Pages 1078-1086 ; 19909233 (ISSN) ; Sharif University of Technology
2012
Abstract
The KASUMI block cipher is used for the cellular communications networks and safety of many wireless standards. Third generation cellular network technology (3G) permits to transmit information, voice and video at very high data rates never seen before that will revolutionize personal communications and information exchange. On the other hand, Residue Number System (RNS) is a modular representation and is evidenced to be serviceable equipment in many applications which need high-speed computations and high-performance components. RNS is a non-weighted and integer number system that can support secure, highspeed, low-power, parallel and carry-free arithmetic. For attaining the most...
Reliable and high-speed KASUMI block cipher by residue number system code
, Article World Applied Sciences Journal ; Volume 17, Issue 9 , 2012 , Pages 1149-1158 ; 18184952 (ISSN) ; Sharif University of Technology
2012
Abstract
Third generation cellular network technology (3G) can revolutionize communications and data exchanges between many people in a more overwhelming fashion than 2G and 2.5G networks did. The 3G UMTS, the 3G GSM and the 3G GPRS rely on the KASUMI block cipher. Therefore, increasing speed, decreasing power consumption and error detection/correction are the major concerns of the KASUMI algorithm and its generation. On the other hand, Residue Number System is a non-weighted number system and it is currently considered as an important method for high-speed, low-power, parallel and carry-free arithmetic realizations. Redundant Residue Number System is an extension of RNS that also supports error...
Designing an Automated and Smart Electric Power Distribution System
, M.Sc. Thesis Sharif University of Technology ; Vakilian, Mehdi (Supervisor)
Abstract
Feeder reconfiguration is one of the most prominent tasks for loss reduction, reliability improvement and also congestion alleviation in distribution networks. Besides improving abovementioned operational issues, during a long period of time, proper switching in appropriate times can causes a lot of economic savings. Furthermore, it can be intensified when capacitors are implemented and controlled in the network. To reach this purpose, most of the previous literature focuses merely on the power grid reconfiguration. Few of these researches have considered this problem as a dynamic one and studied that in a period of time, e.g. one day, considering fixed level of loads despite the others that...
Proposing a Control Strategy for Treatment of Hepatitis C Disease
, M.Sc. Thesis Sharif University of Technology ; Shahrokhi, Mohammad (Supervisor)
Abstract
Due to the importance of hepatitis disease, especially hepatitis C, from public health view point, this research aims to investigate and suggest an efficient medical therapy for this disease. First, available models are analyzed and the suitable one is chosen. Three controllers namely, fixed PI, adaptive PI and exact linearization control (GLC) are designed to control the hepatitis C disease using the drug efficacy as the manipulated variabel. Controller parameters are determined by the Genetic Algorithm (GA) and their performances are evaluated using the selected model. Uncertainties have been considerd in both model structure and parameters and controllers performances are investigated in...
A parametric study on residual stresses and forging load in cold radial forging process
, Article International Journal of Advanced Manufacturing Technology ; Volume 33, Issue 1-2 , 2007 , Pages 7-17 ; 02683768 (ISSN) ; Movahhedy, M. R ; Sharif University of Technology
2007
Abstract
In this work, a comprehensive study of radial forging process is presented through 2-D axisymmetric and 3-D finite element simulations while considering internal tube profile. The tube used in this investigation has four internal helical grooves along its length. The material is modeled with the elastic-plastic behavior, and sliding-sticking friction model is utilized to model the die-workpiece and mandrel-workpiece contacts. The numerical results in the 2-D case are compared with available experimental data. Residual stresses in the forged product, stress concentration around the grooves, pressure distribution on the hammers and mandrel and maximum forging load are studied. The effects of...
Business Process Oriented Software Engineering
, M.Sc. Thesis Sharif University of Technology ; Habibi, Jafar (Supervisor)
Abstract
Enterprises are founded according to their business processes based on its targets. For implementing an Information System, first it is required to analyze, design and model of the processes based on a specific methodology.The methodologies of software engineering usually used to be function oriented however object oriented is usual and practical todays. Analyzing the business processes according to one of these two concepts has some problems, however merging these two concepts, makes a powerful method in analyzing and designing of a system more easily and accurately.Some software development methodologies consider these two aspects in a way, however working with them has many complexities...
A Lightweight Deep Learning Model for Online Network Traffic
, M.Sc. Thesis Sharif University of Technology ; Jalili, Rasool (Supervisor)
Abstract
Traffic classification is crucial for the execution of many security and managerial tasks in a network, such as identifying malicious data, detecting disruptive users, and preventing the passage of traffic from certain applications. Nowadays, a significant portion of traffic in computer networks is encrypted. Therefore, the classification of encrypted traffic requires the use of solutions for analyzing encrypted traffic. In recent years, many solutions based on machine learning and deep learning have been proposed for analyzing encrypted traffic. While most of these solutions focus on improving the accuracy of network traffic classification, less attention has been paid to their...
UCS-NT: An unbiased compressive sensing framework for Network Tomography
, Article ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings ; 2013 , Pages 4534-4538 ; 15206149 (ISSN) ; 9781479903566 (ISBN) ; Rabiee, H. R ; Hashemifar, Z. S ; Sharif University of Technology
2013
Abstract
This paper addresses the problem of recovering sparse link vectors with network topological constraints that is motivated by network inference and tomography applications. We propose a novel framework called UCS-NT in the context of compressive sensing for sparse recovery in networks. In order to efficiently recover sparse specification of link vectors, we construct a feasible measurement matrix using this framework through connected paths. It is theoretically shown that, only O(k log(n)) path measurements are sufficient for uniquely recovering any k-sparse link vector. Moreover, extensive simulations demonstrate that this framework would converge to an accurate solution for a wide class of...
Detection of top-K central nodes in social networks: A compressive sensing approach
, Article Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, 25 August 2015 through 28 August 2015 ; 2015 , Pages 902-909 ; 9781450338547 (ISBN) ; Pei, J ; Tang, J ; Silvestri, F ; Sharif University of Technology
Association for Computing Machinery, Inc
2015
Abstract
In analysing the structural organization of a social network, identifying important nodes has been a fundamental problem. The concept of network centrality deals with the assessment of the relative importance of a particular node within the network. Most of the traditional network centrality definitions have a high computational cost and require full knowledge of network topological structure. On the one hand, in many applications we are only interested in detecting the top-k central nodes of the network with the largest values considering a specific centrality metric. On the other hand, it is not feasible to efficiently identify central nodes in a large real-world social network via...
Continual Learning Using Unsupervised Data
, M.Sc. Thesis Sharif University of Technology ; Soleymani Baghshah, Mahdieh (Supervisor)
Abstract
The existing continual learning methods are mainly focused on fully-supervised scenarios and are still not able to take advantage of unlabeled data available in the environment. Some recent works tried to investigate semi-supervised continual learning (SSCL) settings in which the unlabeled data are available, but it is only from the same distribution as the labeled data. This assumption is still not general enough for real-world applications and restricts the utilization of unsupervised data. In this work, we introduce Open-Set Semi-Supervised Continual Learning (OSSCL), a more realistic semi-supervised continual learning setting in which out-of-distribution (OoD) unlabeled samples in the...
Compressed sensing in cyber physical social systems
, Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; Volume 10760 LNCS , 2018 , Pages 287-305 ; 03029743 (ISSN) ; Ghalebi, K. E ; Movaghar, A ; Mahyar, H ; Sharif University of Technology
2018
Abstract
We overview the main results in Compressed Sensing and Social Networks, and discuss the impact they have on Cyber Physical Social Systems (CPSS), which are currently emerging on top of the Internet of Things. Moreover, inspired by randomized Gossip Protocols, we introduce TopGossip, a new compressed-sensing algorithm for the prediction of the top-k most influential nodes in a social network. TopGossip is able to make this prediction by sampling only a relatively small portion of the social network, and without having any prior knowledge of the network structure itself, except for its set of nodes. Our experimental results on three well-known benchmarks, Facebook, Twitter, and Barabási,...
Application of population balance equation in modeling of asphaltene particle size distribution and characterization of aggregation mechanisms under miscible gas Injection
, Article Journal of Molecular Liquids ; Volume 232 , 2017 , Pages 207-213 ; 01677322 (ISSN) ; Hamed Mahvelati, E ; Ameli, F ; Dabir, B ; Rashtchian, D ; Sharif University of Technology
Elsevier B.V
2017
Abstract
Particle size distribution (PSD) is an important factor that determines how asphaltene instability can damage porous media during natural depletion and enhanced oil recovery processes. In this work, aggregate size distribution under natural depletion and miscible nitrogen injection processes are determined via image analysis techniques and the results are modelled by population balance equation. Unimodal distribution curves in natural depletion show the dominance of particle-particle aggregation mechanism and the clustering is detected only around crude oil bubble point pressure. It is also observed that miscible nitrogen injection considerably increases the number and size of asphaltene...
Modeling interfacial tension of normal alkane-supercritical CO2 systems: Application to gas injection processes
, Article Fuel ; Volume 253 , 2019 , Pages 1436-1445 ; 00162361 (ISSN) ; Hemmati Sarapardeh, A ; Tatar, A ; Zanganeh, A ; Ayatollahi, S ; Sharif University of Technology
Elsevier Ltd
2019
Abstract
To study the gas injection scenario for successful implementation of enhanced oil recovery (EOR)processes, the prediction of interfacial tension (IFT)between injected gas and the crude oil is of paramount significance. In the present study, some intelligent methods were developed for determining IFT values between supercritical CO2 and normal alkanes. IFT was considered as a function of temperature, pressure, and molecular weight of normal alkanes. The developed methods were Multilayer perceptron (MLP), Genetic Algorithm Radial Basis Function (GA-RBF), and Conjugate Hybrid-PSO ANFIS (CHPSO-ANFIS). The average absolute percent relative errors (AAREs)for the stated techniques were found to be...
A novel simultaneous reconfiguration and capacitor switching method to improve distribution networks operation
, Article 2014 14th International Conference on Environment and Electrical Engineering, EEEIC 2014 - Conference Proceedings ; May , 2014 , pp. 295-300 ; ISBN: 9781479946617 ; Davari-Nejad, E ; Kamyab, F ; Vakilian, M ; Haghifam, M. R ; Sharif University of Technology
2014
Abstract
Due to the important role that distribution systems play in quality of power delivered to the customers, there has always been a great deal of interest in investigating different methods of efficiency enhancement for these networks. Two of these methods are Feeder Reconfiguration (FR) and Capacitor Allocation (CA); both have been widely employed to reduce losses and improve several other operational characteristics in electrical power distribution systems. As in FR process the topology of the network changes, it is necessary to change some previous settings; for instance: the capacity of capacitor banks in service in each bus, after each reconfiguration process. This is due to the fact that...
A dynamic method for feeder reconfiguration and capacitor switching in smart distribution systems
, Article International Journal of Electrical Power and Energy Systems ; Volume 85 , 2017 , Pages 200-211 ; 01420615 (ISSN) ; Ahmadifar, A ; Shariatkhah, M. H ; Vakilian, M ; Haghifam, M. R ; Sharif University of Technology
Elsevier Ltd
2017
Abstract
In distribution systems, feeder reconfiguration (FR) can lead to loss reduction, reliability improvement and some other economic savings. These advantages can be intensified by proper control and switching of Capacitor Banks (CBs). In this paper, using Ant Colony Optimization (ACO) technique, a novel method is proposed for simultaneous dynamic scheduling of FR and CB switching in the presence of DG units having uncertain and variant generations over time. This method is applicable to both smart and classic distribution systems. While for the latter, state estimation method should be used to estimate the loads at different buses by employing a limited number of measurements. The objective of...
Iranian national olympiad in informatics
, Article International Conference Joint with the 29th International Olympiad in Informatics, IOI 2017, 28 July 2017 through 4 August 2017 ; Volume 11, Issue Special Issue , 2017 , Pages 25-33 ; 18227732 (ISSN) ; Asadi, A ; Jabal Ameli, A ; Seddighin, S. R ; Shahmohammadi, F ; Sharif University of Technology
Vilnius University
2017
Detection of Central Nodes in Social Networks
, Ph.D. Dissertation Sharif University of Technology ; Movaghar, Ali (Supervisor) ; Rabiee, Hamid Reza (Supervisor)
Abstract
In analyzing the structural organization of many real-world networks, identifying important nodes has been a fundamental problem. The network centrality concept deals with the assessment of the relative importance of network nodes based on specific criteria. Central nodes can play significant roles on the spread of influence and idea in social networks, the user activity in mobile phone networks, the contagion process in biological networks, and the bottlenecks in communication networks. High computational cost and the requirement of full knowledge about the network topology are the most significant obstacles for applying the general concept of network centrality to large real-world social...
A low-cost sparse recovery framework for weighted networks under compressive sensing
, Article Proceedings - 2015 IEEE International Conference on Smart City, SmartCity 2015, Held Jointly with 8th IEEE International Conference on Social Computing and Networking, SocialCom 2015, 5th IEEE International Conference on Sustainable Computing and Communications, SustainCom 2015, 2015 International Conference on Big Data Intelligence and Computing, DataCom 2015, 5th International Symposium on Cloud and Service Computing, SC2 2015, 19 December 2015 through 21 December 2015 ; 2015 , Pages 183-190 ; 9781509018932 (ISBN) ; Rabiee, H. R ; Movaghar, A ; Hasheminezhad, R ; Ghalebi, E ; Nazemian, A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2015
Abstract
In this paper, motivated by network inference, we introduce a general framework, called LSR-Weighted, to efficiently recover sparse characteristic of links in weighted networks. The links in many real-world networks are not only binary entities, either present or not, but rather have associated weights that record their strengths relative to one another. Such models are generally described in terms of weighted networks. The LSR-Weighted framework uses a newly emerged paradigm in sparse signal recovery named compressive sensing. We study the problem of recovering sparse link vectors with network topological constraints over weighted networks. We evaluate performance of the proposed framework...
Secure deep-JSCC against multiple eavesdroppers
, Article Proceedings - IEEE Global Communications Conference, GLOBECOM ; 2023 , Pages 3433-3438 ; 23340983 (ISSN); 979-835031090-0 (ISBN) ; Letafati, M ; Erdemir, E ; Khalaj, B. H ; Behroozi, H ; Gündüz, D ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2023
Abstract
In this paper, a generalization of deep learning-aided joint source channel coding (Deep-JSCC) approach to secure communications is studied. We propose an end-to-end (E2E) learning-based approach for secure communication against multiple eavesdroppers over complex-valued fading channels. Both scenarios of colluding and non-colluding eavesdroppers are studied. For the colluding strategy, eavesdroppers share their logits to collaboratively infer private attributes based on ensemble learning method, while for the non-colluding setup they act alone. The goal is to prevent eavesdroppers from inferring private (sensitive) information about the transmitted images, while delivering the images to a...
Extracting implicit social relation for social recommendation techniques in user rating prediction
, Article 26th International World Wide Web Conference, WWW 2017 Companion, 3 April 2017 through 7 April 2017 ; 2019 , Pages 1343-1351 ; 9781450349147 (ISBN) ; Elahe Ghalebi, K ; Mahyar, H ; Grosu, R ; Firouzi, M ; Movaghar, A ; Sharif University of Technology
International World Wide Web Conferences Steering Committee
2019
Abstract
Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest items to users that might be interesting for them. Recent studies illustrate that incorporating social trust in Matrix Factorization methods demonstrably improves accuracy of rating prediction. Such approaches mainly use the trust scores explicitly expressed by users. However, it is often challenging to have users provide explicit trust scores of each other. There exist quite a few works, which propose Trust Metrics to compute and predict trust scores between users based on their interactions. In this paper, first we present how social relation can be extracted from users'...