Sharif Digital Repository

In this paper1 we consider higher isoperimetric numbers of a (finite directed) graph. In this regard we focus on the nth mean isoperimetric constant of a directed graph as the minimum of the mean outgoing normalized flows from a given set of n disjoint subsets of the vertex set of the graph. We show that the second mean isoperimetric constant in this general setting, coincides with (the mean version of) the classical Cheeger constant of the graph, while for the rest of the spectrum we show that there is a fundamental difference between the nth isoperimetric constant and the number obtained by taking the minimum over all n-partitions. In this direction, we show that our definition is the... 

Let LL be a reversible Markovian generator on a finite set View the MathML sourceV. Relations between the spectral decomposition of LL and subpartitions of the state space View the MathML sourceV into a given number of components which are optimal with respect to min–max or max–min Dirichlet connectivity criteria are investigated. Links are made with higher-order Cheeger inequalities and with a generic characterization of subpartitions given by the nodal domains of an eigenfunction. These considerations are applied to generators whose positive rates are supported by the edges of a discrete cycle ZNZN, to obtain a full description of their spectra and of the shapes of their eigenfunctions, as... 

Topology of a mobile wireless sensor/ad hoc network is prone to link breakages due to node mobility which compels the periodic re-construction of the topology in so called ""hello"" intervals. The problem addressed in this paper is determining the maximum ""hello"" interval preserving the connectivity of a homogeneous topology with high probability. In order to study the optimum ""hello"" interval, statistical topology lifetime (STL) is formally defined as a value of ""hello"" interval that ensures statistical connectivity with a given threshold. Temporal properties of the topology are studied based on two phenomena; one concerning a connectivity phase transition with time and the other one... 

Flocking through leader following structures in mobile networks raises attractive control problems. Due to limited sensing radii, leaders locally influence a network of agents. In this paper, we consider the problem of real-time maximization of flocking velocity. By using local information and a Particle-Swarm-Optimization (PSO) algorithm, a Leader Agent (LA) actively motivates flocking at high speed. The LA manages topology of the network in its neighborhood and increases flocking velocity. PSO output quality and calculation costs show that the proposed optimization algorithm is practically feasible. A case-study is also presented  

The petroleum industry tends to paint an optimistic picture with respect to future petroleum availability. In order to anticipate demand, the size of connected volume of hydrocarbon of fields needs to be known. During the early stage of life of a reservoir, due to the lake of certain data, connected volume of hydrocarbon is usually based on analogues or rules of thumb and not detailed reservoir modeling. Therefore, there is a great incentive to produce physically-based methodologies to make an estimation of connected volume of hydrocarbon. Percolation theory is used to estimate the connected volume of hydrocarbon very fast. Furthermore, the result has been validated against areal field... 

Complicated sedimentary processes control the spatial distribution of geological heterogeneities. This serves to make the nature of the fluid flow in the hydrocarbon reservoirs immensely complex. Proper modeling of these heterogeneities and evaluation of their connectivity are crucial and affects all aspects of fluid flow. Since the natural variability of heterogeneity occurs in a myriad of length scales, accurate modeling of the rock type connectivity requires a very fine scheme, which is computationally very expensive. Hence, this makes other alternative methods such as the percolation approach attractive and necessary. The percolation approach considers the hypothesis that a reservoir can... 

The connectivity of high conductivity pathways in geological formations depend on the spatial distribution of geological heterogeneities that may appear on various length scales. Appropriate modeling of this is crucial within in hydrology and petroleum systems. The approach taken in this study is to use percolation theory to quantify the connectivity, hydraulic conductivity, and breakthrough time behavior between an injector and a producer within such systems. In particular, a three-dimensional overlapping sandbody model is considered which assumes that the geological formation can be split into either conductive flow units (i. e., good sands) or non-conductive units (i. e., poor sands). The... 

Reservoir characterization, especially during early stages of reservoir life, is very uncertain, due to the scarcity of data. Reservoir connectivity and permeability evaluation is of great importance in reservoir characterization. The conventional approach to addressing this is computationally very expensive and time consuming. Therefore, there is a great incentive to produce much simpler alternative methods. In this paper, we use a statistical approach called the percolation theory, which considers a hypothesis wherein the reservoir can be split into either permeable (i.e. sand/fracture) or impermeable flow units (i.e. shale/matrix), and assumes that the connectivity of permeability... 

We present a Vector Dark Matter (VDM) model that explains the 3.5 keV line recently observed in the XMM-Newton observatory data from galaxy clusters. In this model, dark matter is composed of two vector bosons, V and V', which couple to the photon through an effective generalized Chern-Simons coupling, gV. V' is slightly heavier than V with a mass splitting mV' - mV 3.5 keV. The decay of V' to V and a photon gives rise to the 3.5 keV line. The production of V and V' takes place in the early universe within the freeze-in framework through the effective gV coupling when mV' < T < Λ, Λ being the cut-off above which the effective gV coupling is not valid. We introduce a high energy model that... 

Recommender systems have become an important issue in network science. Collaborative filtering and its variants are the most widely used approaches for building recommender systems, which have received great attention in both academia and industry. In this paper, we studied the relationship between recommender systems and connectivity of users-items bipartite network. This results in a novel recommendation algorithm. In our method recommended items are selected based on the eigenvector corresponding to the algebraic connectivity of the graph - the second smallest eigenvalue of the Laplacian matrix. Since recommending an item to a user equals to adding a new link to the users-items bipartite... 

In this paper we investigated the structural properties of the ultra high voltage power transmission network of Iran. We modeled the power grid as a network with 105 nodes and 142 connection links. We found that the Iranian power grid displays a relatively moderate clustering coefficient-much larger than that of corresponding random networks-and small characteristics path length comparable to that of corresponding random networks; i.e. the power grid is a small-world network with exponential degree distribution. Global efficiency was considered as an indicator of grid's performance and the influence of random and intentional nodal failures on the efficiency was investigated. We also studied... 

Herein, we present the large scale fabrication of carbon nanotubes (CNT) electrodes supported on flexible polymeric sheets by subsequent multilayer inkjet printing of a silver layer for electrical connection, CNT layers as active electrode material and an insulation layer to define a stand-alone CNT active electrode area with high accuracy. Optical and electrochemical characterization using several redox mediators demonstrates the reproducibility of the electrode surfaces and their functionality even with a single inkjet printed CNT layer. These electrodes are targeted to the clinical sector for the determination of the antioxidant power (AOP) of biologically relevant fluids by... 

The inclusion ideal graph of a ring R, denoted by In(R), is a graph whose vertices are all non-trivial left ideals of R and two distinct left ideals I and J are adjacent if and only if I⊆J or J⊆I. In this paper, we show that In(R) is not connected if and only if R≅M2(D) or D1×D2, for some division rings, D, D1 and D2. Moreover, if R is connected, then diam(In(R))≤3. We prove that if In(R) is a tree, then In(R) is a star graph or P4. Also, In(R) is a complete graph if and only if R is a uniserial ring. Next, it is shown that the inclusion ideal graph of Mn(D) for a division ring D and a natural number n>3 is not regular  

Synchronization behavior of electroencephalographic (EEG) signals is important for decoding information processing in the human brain. Modern multichannel EEG allows a transition from traditional measurements of synchronization in pairs of EEG signals to whole-brain synchronization maps. The latter can be based on bivariate measures (BM) via averaging over pair-wise values or, alternatively, on multivariate measures (MM), which directly ascribe a single value to the synchronization in a group. In order to compare BM versus MM, we applied nine different estimators to simulated multivariate time series with known parameters and to real EEGs. We found widespread correlations between BM and MM,... 

This paper presents an effective current injection method for a single phase grid-connected PV inverter with LCL filter. The main objective of the proposed control strategy is to compensate the resonance effect of the LCL filter. In the proposed control strategy, a resonance compensator is augmented to the conventional proportional resonance (PR) controller to attenuate current oscillations in resonance frequency of LCL filter. The proposed strategy robustly regulates the output current of grid connected inverter in various grid impedances and provides a high quality current injection capability for the PV inverter in harmonic polluted condition of the grid voltage. The performance of the... 

This study considers blood flow in total cavopulmonary connection (TCPC) morphology created in Fontan surgical procedure in patients with a single ventricle heart disease. Ordinary process of TCPC operation reduces pulmonary blood flow pulsatility since the right ventricle being bypassed. This reduction may limit the long term outcome of Fontan circulation. There is an idea of increasing pulmonary flow pulsations by keeping Main Pulmonary Artery (MPA) partially open while it was closed in ordinary TCPC operation. The purpose of the present study is to verify the effects of Antegrade Flow (AF) coming through stenosed MPA on pulmonary flow pulsations. The 3D geometry is reconstructed from CT... 

This paper deals with a refined analysis and modification of existing results on the flocking algorithms proposed for the second order dynamic agents. In the present work, the limiting condition of ever connectivity is removed and it is proved that the flocking can be reached if only the union of the network proximity graphs during nonoverlapping time intervals becomes connected frequently enough. Also, it is proved that including a static virtual leader cannot model the group objective of achieving the desired velocity and it will stop eventually at a predefined point in the space. The convergence rate to this fixed point is determined too. The last contribution of this paper is definition... 

DC microgrids (DC-MGs) are becoming popular as an effective means to integrate various renewable energy resources. Conventionally, the droop control is adopted as a decentralized control strategy for proper power sharing without using any communication link. However, the conventional droop control often deteriorates due to the effects of unequal line resistances. In this paper, a control strategy is proposed for a DC-MG to achieve perfect power sharing considering the effects of line resistances. The DC-MG under study consists of a photovoltaic system, two energy storage systems, a grid-connected converter system, and dc loads. The control strategy of the converters is addressed under... 

Localization is a crucial problem in wireless sensor networks and most of the localization algorithms given in the literature are non-adaptive and designed for fixed sensor networks. In this paper, we propose a learning based localization algorithm for mobile wireless sensor networks. By this technique, mobility in the network will be discovered by two crucial methods in the beacons: position and distance checks methods. These two methods help to have accurate localization and constrain communication just when it is necessary. The proposed method localizes the nodes based on connectivity information (hop count), which doesn't need extra hardware and is cost efficient. The experimental... 

Electroencephalography (EEG)-based functional brain networks have been investigated frequently in health and disease. It has been shown that a number of graph theory metrics are disrupted in brain disorders. EEG-based brain networks are often studied in the whole-brain framework, where all the nodes are grouped into a single network. In this study, we studied the brain networks in two hemispheres and assessed whether there are any hemispheric-specific patterns in the properties of the networks. To this end, resting state closed-eyes EEGs from 44 healthy individuals were processed and the network structures were extracted separately for each hemisphere. We examined neurophysiologically...