MAS platforms as an enabler of enterprise mobilisation: The state of the art

One of the main application areas for multi-agent systems technology is enterprise mobilization, wherein the main business process actors are nomadic workers. An agent's autonomy, sociality and intelligence are highly prized features when it comes to supporting those mobile workers who are geographically isolated from the main knowledge source (i.e. the corporate Intranet) and are frequently moving from one location to another. Based on experience gained from two field trials of applications (built using for multi-agent systems technology and running on lightweight handheld devices) that support mobile business processes for telecommunications service provisioning and maintenance, this paper proposes desirable metrics for any multi-agent systems platform intended for enterprise mobilisation use. These metrics are then used to compare a number of existing multi-agent systems platforms, and based on the results, this paper identifies some areas for improvement

On modeling and the use of the NASTRAN thermal analyzer

Eight alternative modeling techniques to specify prescribed temperature at grid or scalar points for transient thermal analyses are presented. Four cases are for constant temperatures, and the others are time varying temperature functions. Theoretical explications and detailed listing of input data cards used for illustrating different modelings are given. It is shown that the NTA is exploited to extend beyond its normal capabilities through innovative modeling techniques. In addition, the effect of node valency on the energy distribution grid points is illustrated and discussed. Guidelines to delineate this effect are given

NASTRAN thermal analyzer status, experience, and new developments

The unique finite element based NASTRAN Thermal Analyzer originally developed as a general purpose heat transfer analysis incorporated into the NASTRAN system is described. The current status, experiences from field applications, and new developments are included

Extraction of hidden information by efficient community detection in networks

Currently, we are overwhelmed by a deluge of experimental data, and network physics has the potential to become an invaluable method to increase our understanding of large interacting datasets. However, this potential is often unrealized for two reasons: uncovering the hidden community structure of a network, known as community detection, is difficult, and further, even if one has an idea of this community structure, it is not a priori obvious how to efficiently use this information. Here, to address both of these issues, we, first, identify optimal community structure of given networks in terms of modularity by utilizing a recently introduced community detection method. Second, we develop an approach to use this community information to extract hidden information from a network. When applied to a protein-protein interaction network, the proposed method outperforms current state-of-the-art methods that use only the local information of a network. The method is generally applicable to networks from many areas.Comment: 17 pages, 2 figures and 2 table