104 research outputs found
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CBDI: Combined Banzhaf & Diversity Index for Finding Critical Nodes
Critical node discovery plays a vital role in assessing the vulnerability of a network to an abrupt change, such as an adversarial attack or human intervention. In this paper, we propose a new metric to characterize the criticality of a node in an arbitrary network which we refer to as the Combined Banzhaf & Diversity Index (CBDI). The metric utilizes a diversity index which is based on the variability of a node’s attributes relative to its neighbors and the Banzhaf Power Index which characterizes the degree of participation of a node in forming shortest paths. The Banzhaf power index is inspired from the theory of voting games in game theory. We evaluate the performance of the new metric using simulations. Our results indicate that in a number of network topologies, the proposed metric outperforms other proposals which have appeared in the literature. The proposed CBDI index chooses more critical nodes which, when removed, degrade network performance to a greater extent than if critical nodes based on other criticality metrics were removed
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On the Complexity of Average Path length for Biological Networks and Patterns
Path length calculation is a frequent requirement in studies related to graph theoretic problems such as genetics. Standard method to calculate average path length of a graph requires traversing all nodes in the graph repeatedly, which is computationally expensive for graphs containing large number of nodes. We propose a novel method to calculate average path length for graphs commonly required in the studies of genetics. The proposed method is computationally less expensive and less time consuming compared to standard method. In this paper, a mathematical formulation is provided that calculates Average Path Length for graphs commonly present in biological networks, at the cost of uniform time complexity, for different size of networks
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Spectral Partitioning for Node Criticality
Finding critical nodes in a network is a significant task, highly relevant to network vulnerability and security. We consider the node criticality problem as an algebraic connectivity minimization problem where the objective is to choose nodes which minimize the algebraic connectivity of the resulting network. Previous suboptimal solutions of the problem suffer from the computational complexity associated with the implementation of a maximization consensus algorithm. In this work, we use spectral partitioning concepts introduced by Fiedler, to propose a new suboptimal solution which significantly reduces the implementation complexity. Our approach, combined with recently proposed distributed Fiedler vector calculation algorithms enable each node to decide by itself whether it is a critical node. If a single node is required then the maximization algorithm is applied on a restricted set of nodes within the network. We derive a lower bound for the achievable algebraic connectivity when nodes are removed from the network and we show through simulations that our approach leads to algebraic connectivity values close to this lower bound. Similar behaviour is exhibited by other approaches at the expense, however, of a higher implementation complexity
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Combined Banzhaf & Diversity Index (CBDI) for critical node detection
Critical node discovery plays a vital role in assessing the vulnerability of a computer network to malicious attacks and failures and provides a useful tool with which one can greatly improve network security and reliability. In this paper, we propose a new metric to characterize the criticality of a node in an arbitrary computer network which we refer to as the Combined Banzhaf & Diversity Index (CBDI). The metric utilizes a diversity index which is based on the variability of a node׳s attributes relative to its neighbours and the Banzhaf power index which characterizes the degree of participation of a node in forming shortest paths. The Banzhaf power index is inspired from the theory of voting games in game theory. The proposed metric is evaluated using analysis and simulations. The criticality of nodes in a network is assessed based on the degradation in network performance achieved when these nodes are removed. We use several performance metrics to evaluate network performance including the algebraic connectivity which is a spectral metric characterizing the connectivity robustness of the network. Extensive simulations in a number of network topologies indicate that the proposed CBDI index chooses more critical nodes which, when removed, degrade network performance to a greater extent than if critical nodes based on other criticality metrics were removed
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Adding the reliability on tree based topology construction algorithms for wireless sensor networks
Topology control is a technique used in wireless sensor networks to maximize energy efficiency and network lifetime. In previous literature, many tree based techniques have been proposed to save energy and increase the network lifetime. In tree based algorithms, the most promising solution is the formation of a network backbone, which serves on behalf of rest of the nodes in the network and therefore leading towards Connected Dominating Set (CDS) formulation. However, one imminent problem with all tree based solution is a compromise on network reliability. Therefore, to address reliability issues in tree based solutions, in this paper, we propose Poly3 which maintains cliques of size three in order to achieve network reliability on top of the CDS algorithm. This makes the network more robust to link removal. Our empirical and mathematical analysis reveals that Poly3 provides better reliability than algorithms of the same kind
Impact of GIS on Performance of Cellular Companies in Pakistan
Abstract: The aim of this research study is to determine the impact of GIS on cellular companies in Pakistan. The research has a profound background containing the performance and IT levels in the companies. An efficient exploitation of IT has become decisive in improving inclusive operations. This research study is based upon the concept of a service-product bundle consisted of three elements: IT applications, dedicated IT departmental study and explicit study of companies globalization level. Thorough Quadrant Analysis data was analyzed to determine the impact of Global information system of companies with its impact ratio. Results based on the analysis illustrate the significance of GIS in the cellular companies with the IT applications
Epidemiology of substance abuse among migrants compared to native born population in primary care.
BACKGROUND AND OBJECTIVES: Research in the United States tends to indicate that immigrants from most sociogeographic regions have considerably lower substance use disorder (SUD) rates than native born individuals. We aimed to analyze the differences between immigrants and native born population regarding substance abuse and dependence. This objective was approached using data from the ARACAT cross-sectional multicenter study in primary care settings of two different Spanish regions: Aragon and Catalonia. METHODS: Three thousand six patients (1,503 immigrants randomly selected and 1,503 native born paired by age and gender) were interviewed using the Mini-International Neuropsychiatric Interview. RESULTS: Reported substance abuse and dependence were more prevalent in the native born population than in immigrants (alcohol abuse 5.1% vs. 2.6% p < .0001, alcohol dependence 3.3% vs. 2.6% n.s., other abuse 3.4% vs. .4% p < .0001, other dependence .5% vs. 4.0% p < .0001). Large differences were detected between different ethnic groups. Sociodemographic characteristics such as female gender, older age, higher level of education or stable housing (among others), were found to be protective against different SUDs. CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE: Immigrants have lower levels of alcohol and substance abuse, however, those that do consume show higher levels of both comorbid mental disorders and problematic alcohol/substance use. It would appear to be the case that issues specific to immigrant cultures, such as extreme stigmatization of substance and alcohol use, may serve to promote social marginalization and inhibit treatment access
Lymphocyte deficiency limits Epstein-Barr virus latent membrane protein 1 induced chronic inflammation and carcinogenic pathology in vivo
Background: The importance of the malignant cell environment to its growth and survival is becoming increasingly apparent, with dynamic cross talk between the neoplastic cell, the leukocyte infiltrate and the stroma. Most cancers are accompanied by leukocyte infiltration which, contrary to an anticipated immuno-protective role, could be contributing to tumour development and cancer progression. Epstein-Barr virus (EBV) associated cancers, including nasopharyngeal carcinoma and Hodgkin's Disease, show a considerable leukocyte infiltration which surrounds the neoplastic cells, raising the questions as to what role these cells play in either restricting or supporting the tumour and what draws the cells into the tumour. In order to begin to address this we have studied a transgenic model of multistage carcinogenesis with epithelial expression of the EBV primary oncoprotein, latent membrane protein 1 (LMP1). LMP1 is expressed particularly in the skin, which develops a hyperplastic pathology soon after birth.
Results: The pathology advances with time leading to erosive dermatitis which is inflamed with a mixed infiltrate involving activated CD8+ T-cells, CD4+ T-cells including CD4+/CD25+/FoxP3+ Treg cells, mast cells and neutrophils. Also significant dermal deposition of immunoglobulin-G (IgG) is observed as the pathology advances. Along with NF-kappaB activation, STAT3, a central factor in inflammation regulation, is activated in the transgenic tissue. Several inflammatory factors are subsequently upregulated, notably CD30 and its ligand CD153, also leukocyte trafficking factors including CXCL10, CXCL13, L-selectin and TGF beta 1, and inflammatory cytokines including IL-1 beta, IL-3 and the murine IL-8 analogues CXCL1, CXCL2 and CXCL5-6, amongst others. The crucial role of mature T- and/or B-lymphocytes in the advancing pathology is demonstrated by their elimination, which precludes mast cell infiltration and limits the pathology to an early, benign stage.
Conclusions: LMP1 can lead to the activation of several key factors mediating proliferation, angiogenesis and inflammation in vivo. With the initiation of an inflammatory programme, leukocyte recruitment follows which then itself contributes to the progressing pathology in these transgenic mice, with a pivotal role for B-and/or T-cells in the process. The model suggests a basis for the leukocyte infiltrate observed in EBV-associated cancer and its supporting role, as well as potential points for therapeutic intervention
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