Network module (community) structure has been a hot research topic in recent years. Many methods have been proposed for module detection and identification. Hierarchical structure of modules is shown to exist in many networks such as biological networks and social networks. Compared to the partitional module identification methods, less research is done on the inference of hierarchical modular ...

Scalable coordination is a key challenge in deploying massively multiagent systems. Resource usage is one part of agent behavior which naturally lends itself to abstraction. CyberOrgs is a model for hierarchical coordination of resource usage by multi-agent applications in a network of peer-owned resources. Programming constructs based on CyberOrgs allow resource trade and control reification w...

In this paper, we construct and compare algorithmic approaches to solve the Preference Consistency Problem for preference statements based on hierarchical models. Instances of this problem contain a set of preference statements that are direct comparisons (strict and non-strict) between some alternatives, and a set of evaluation functions by which all alternatives can be rated. An instance is c...

Network monitoring applications are used to monitor network traffic flows. Clustering techniques are used to extract network traffic patterns. Anomaly detection schemes are used to detect network attacks. Hierarchical and partitional clustering schemes are used to analyze network traffic data values. The hierarchical data analysis uses the structure and data values for the clustering process. T...

this study tries to codify a proper mathematical model which can be predict the costs of repair and maintaining the tractors as precisely as possible for three common models of tractors in shahid beheshti cultivation firm in andimeshk-ahvaz road of dezfoul. studied tractors include: newhland tm155 tractor which is chosen from the most perfect file of 10 tractor machines and jandier tractor-3140...

Recently, we have developed two methods for expression profile analysis. One is the automatic determination of cluster boundaries in hierarchical clustering of profiles [2], and another is the inference of a genetic network by application of graphical Gaussian modeling (GGM) [4]. Here, we synthesize the newly developed methods into a system, named ASIAN (Automatic System for Inferring A Network...

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree d...

We describe a biologically plausible model of dynamic recognition and learning in the visual cortex based on the statistical theory of Kalman filtering from optimal control theory. The model utilizes a hierarchical network whose successive levels implement Kalman filters operating over successively larger spatial and temporal scales. Each hierarchical level in the network predicts the current v...

The hierarchical hypercube network is suitable for massively parallel systems. The number of links in the hierarchical hypercube network forms a compromise between those of the hypercube and the cube-connected cycles. Recently, some interesting properties of the hierarchical hypercube network were investigated. Since the hierarchical hypercube is bipartite. A bipartite graph is bipancyclic if i...

The structure of people's conceptual knowledge of concrete nouns has traditionally been viewed as hierarchical (Collins & Quillian, 1969). For example, superordinate concepts (vegetable) are assumed to reside at a higher level than basic-level concepts (carrot). A feature-based attractor network with a single layer of semantic features developed representations of both basic-level and superordi...