Sharif Digital Repository

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... 

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... 

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... 

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,... 

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... 

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'... 

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'... 

This paper addresses the problem of identifying central nodes from the information flow standpoint in a social network. Betweenness centrality is the most prominent measure that shows the node importance from the information flow standpoint in the network. High betweenness centrality nodes play crucial roles in the spread of propaganda, ideologies, or gossips in social networks, the bottlenecks in communication networks, and the connector hubs in biological systems. In this paper, we introduce DICeNod, a new approach to efficiently identify central nodes in social networks without direct measurement of each individual node using compressive sensing, which is a well-known paradigm in sparse... 

Betweenness centrality is a prominent centrality measure expressing importance of a node within a network, in terms of the fraction of shortest paths passing through that node. Nodes with high betweenness centrality have significant impacts 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. Thus, identifying k-highest betweenness centrality nodes in networks will be of great interest in many applications. In this paper, we introduce CS-HiBet, a new method to efficiently detect top-k betweenness centrality nodes in networks, using compressive sensing.... 

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... 

One of the most relevant characteristics of social networks is community structure, in which network nodes are joined together in densely connected groups between which there are only sparser links. Uncovering these sparse links (i.e. intercommunity links) has a significant role in community detection problem which has been of great importance in sociology, biology, and computer science. In this paper, we propose a novel approach, called CS-ComDet, to efficiently detect the inter-community links based on a newly emerged paradigm in sparse signal recovery, called compressive sensing. We test our method on real-world networks of various kinds whose community structures are already known, and... 

Recommender Systems have become an attractive field within the recent decade because they facilitate users' selection process within limited time. Conventional recommender systems have proposed numerous methods focusing on recommendations to individual users. Recently, due to a significant increase in the number of users, studies in this field have shifted to properly identify groups of people with similar preferences and provide a list of recommendations for each group. Offering a recommendations list to each individual requires significant computational cost and it is therefore often not efficient. So far, most of the studies impose four restrictive assumptions: (1) limited number of... 

Four 5-, 10-, 20- and 30-story moment frames, representing low-, mid-, and two high-rise structures, were subjected to a great number of idealized directivity pulses. The amplitudes and periods of pulses vary from 0.02 g to 1.0 g and 0.5 to 12 sec, respectively. Over 1400 nonlinear dynamic analyses of low- to high-rise moment frames were performed which were feasible through using modified fish-bone model. The distribution of interstory drift along the height was studied and two applied contours were proposed: (i) the maximum interstory drift contour, and (ii) the critical story contour. These contours were demonstrated versus the ratio of natural period of the structure to the pulse period... 

In this article singular points of a parallel manipulator are obtained based on a novel geometrical method. Here we introduce the constrained plain method (CPM) and some of its application in parallel mechanism. Given the definition of constraint plane (CP) and infinite constraint plane (ICP) the dependency conditions of constraints is achieved with the use of a new theorem based on the Ceva geometrical theorem. The direction of angular velocity of a body is achieved by having three ICPs with the use of another theorem. Finally, with the use of the above two novel theorems singularities of the 3UPF_PU mechanism are obtained. It should be emphasized that this method is completely geometrical,... 

An analytical model is proposed to study the effect of particle size on melting enthalpy and entropy of metallic nanoparticles (NPs). The Mott's and Regel's equations for melting entropy in the combination of core average coordination number (CAC) and surface average coordination number (SAC) of freestanding NPs are considered. Clusters of icosahedral (IC), body centered cubic (BCC), and body centered tetragonal (BCT) structure without any vacancies and defects are modeled. Using the variable coordination number made this model to be in good agreement with experimental and molecular dynamic (MD) results of different crystal structures. The model predicts melting entropy and enthalpy of... 

Grinding is widely used for manufacturing of components that require fine surface finish and good dimensional accuracy. In this study a thermo-mechanical finite element analysis is conducted to find out how grinding parameters can affect temperature and residual stress distribution in the workpiece. Results of parametric study presented in this work indicate, by carefully selecting the grinding parameters, minimum thermal and mechanical damage can be achieved. Higher workpiece velocities produce higher surface residual stress. By increasing depths of cut, depth of tensile residual stresses increases. Convection heat coefficient does not have any considerable effect on surface residual stress... 

Adaptive Noise Cancellation (ANC) is a well-known technique for background noise reduction in automobile and vehicular environments. The noise fields in automobile and other vehicle interior obey the diffuse noise field model closely. On the other hand, the ANC does not provide sufficient noise reduction in the diffuse noise fields. In this paper, a new multistage post-filter is designed for ANC as a solution to diffuse noise conditions. The designed post-filter is a single channel Linear Prediction (LP) based speech enhancement system. The LP is performed by an adaptive lattice filter and attempts to extract speech components by using intermediate ANC signals. The post-filter has no... 

Shot peening is widely used to improve the fretting fatigue strength of critical surfaces. Fretting fatigue occurs in contacting parts that are subjected to fluctuating loads and sliding movements at the same time. This paper presents a sequential finite element simulation to investigate the shot peening effects on normal stress, shear stress, bulk stress and slip amplitude, which are considered to be the controlling parameters of fretting damage. The results demonstrated that among the modifications related to shot peening, compressive residual stress has a dominant effect on the fretting parameters