Results 1 - 10 of 146

A General Encoding Framework for Representing Network Measurement and Topology Data

by A Brown , M Swany , † , J Zurawski
"... SUMMARY Scientific applications are evolving rapidly and rely heavily on the network for data movement, communication, control, and result collection. Efforts to construct intelligent software that is aware of network status as well as features related to the logical and physical aspects of the top ..."
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infrastructure [1]. We present a general model used to represent both network measurements collected from performance tools as well as describing the physical and logical characteristics of the underlying network. This system is currently being standardized in the Open Grid Forum to enable other uses within

Reverse engineering of regulatory networks in human B cells.

by Katia Basso , Adam A Margolin , Gustavo Stolovitzky , Ulf Klein , Riccardo Dalla-Favera , Andrea Califano - Nat. Genet. , 2005
"... Cellular phenotypes are determined by the differential activity of networks linking coregulated genes. Available methods for the reverse engineering of such networks from genome-wide expression profiles have been successful only in the analysis of lower eukaryotes with simple genomes. Using a new m ..."
Abstract - Cited by 178 (2 self) - Add to MetaCart
). Although scale-free networks may represent a common blueprint for all cellular constituents, evidence of scale-free topology in higher-order eukaryotic cells is currently limited to coexpression networks 3,4 , which tend to identify entire subpathways rather than individual interactions. Identifying

Nonparametric belief propagation for self-localization of sensor networks

by Alexander T. Ihler, John W. Fisher III, Randolph L. Moses, Alan S. Willsky - IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS , 2005
"... Automatic self-localization is a critical need for the effective use of ad-hoc sensor networks in military or civilian applications. In general, self-localization involves the combination of absolute location information (e.g. GPS) with relative calibration information (e.g. distance measurements b ..."
Abstract - Cited by 98 (3 self) - Add to MetaCart
to the network topology and use this observation to reformulate the problem within a graphical model framework. We then present and demonstrate the utility of nonparametric belief propagation (NBP), a recent generalization of particle filtering, for both estimating sensor locations and representing location

An Evolutionary Framework for AS-Level Internet Topology Modeling

by Ruomei Gao, Ellen Zegura
"... Models for network topology form a crucial component in the analysis of protocols. This paper systematically investigates a variety of evolutionary models for autonomous system (AS) level Internet topology. Evolution-based models produce a topology incrementally, attempting to reflect the growth pa ..."
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patterns of the actual topology. While evolutionary models are appealing, they have generally not agreed as closely with measurements of real data as non-evolutionary models. We attempt to understand what factor contributes to a “good ” evolutionary model. Our systematic study consists of a relatively

Please cite: Statistical Applications in Genetics and Molecular Biology (2005). A General Framework for Weighted Gene Co-expression Network Analysis

by Bin Zhang, Steve Horvath, Departments Of Human Genetics
"... Gene co-expression networks are increasingly used to explore the system-level functionality of genes. The network construction is conceptually straightforward: nodes represent genes and nodes are connected if the corresponding genes are significantly co-expressed across appropriately chosen tissue s ..."
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samples. In reality, it is tricky to define the connections between the nodes in such networks. An important question is whether it is biologically meaningful to encode gene co-expression using binary information (connected=1, unconnected=0). We describe a general framework for ‘soft ’ thresholding

Link Prediction Based on Graph Topology: The Predictive Value of the Generalized Clustering Coefficient

by Zan Huang , 2006
"... Predicting linkages among data objects is a fundamental data mining task in various application domains, including recommender systems, information retrieval, automatic Web hyperlink generation, record linkage, and communication surveillance. In many contexts link prediction is entirely based on the ..."
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implications on link prediction. This paper represents initial efforts to explore the connection between link prediction and graph topology. The focus is exclusively on the predictive value of the clustering coefficient measure. The standard clustering coefficient measure is generalized to capture higher

Hierarchies relating Topology and Geometry

by Walter Kropatsch Yll, Walter G. Kropatsch, Yll Haxhimusa, Pascal Lienhardt , 2004
"... Cognitive Vision has to represent, reason and learn about objects in its environment it has to manipulate and react to. There are deformable objects like humans which cannot be described easily in simple geometric terms. In many cases they are composed of several pieces forming a "structure ..."
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over time by up-projecting individual measurements. The construction of the hierarchies follows the philosophy to reduce the data amount at each higher level of the hierarchy by a reduction factor > 1 while preserving important topological properties like connectivity and inclusion.

A Holistic Framework for Realistic, Reproducible, Real-world Sensor Network Experimentation

by Iliya Gurov, Tu Darmstadt, I. Problem Statement
"... In order to correctly investigate and understand wireless sensor network (WSN) protocols such as data collection, dis-semination, and IPv6 integration, real-world experiments need to be executed in a comparable and systematic way. Current WSN sites are built around specific scenarios and environ-men ..."
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In order to correctly investigate and understand wireless sensor network (WSN) protocols such as data collection, dis-semination, and IPv6 integration, real-world experiments need to be executed in a comparable and systematic way. Current WSN sites are built around specific scenarios and environ

Generalized Louvain method for community detection in large networks

by unknown authors
"... Abstract—In this paper we present a novel strategy to discover the community structure of (possibly, large) networks. This approach is based on the well-know concept of network modularity optimization. To do so, our algorithm exploits a novel measure of edge centrality, based on the κ-paths. This te ..."
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Abstract—In this paper we present a novel strategy to discover the community structure of (possibly, large) networks. This approach is based on the well-know concept of network modularity optimization. To do so, our algorithm exploits a novel measure of edge centrality, based on the κ

Generalized Louvain Method for Community Detection in Large Networks

by unknown authors
"... Abstract—In this paper we present a novel strategy to discover the community structure of (possibly, large) networks. This approach is based on the well-know concept of network modularity optimization. To do so, our algorithm exploits a novel measure of edge centrality, based on the κ-paths. This te ..."
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Abstract—In this paper we present a novel strategy to discover the community structure of (possibly, large) networks. This approach is based on the well-know concept of network modularity optimization. To do so, our algorithm exploits a novel measure of edge centrality, based on the κ
Results 1 - 10 of 146