Network support for integrated design

A framework of network support for utilization of integrated design over the Internet has been developed. The techniques presented also applicable for Intranet/Extranet. The integrated design system was initially developed for local application in a single site. With the network support, geographically dispersed designers can collaborate a design task through out the total design process, quickly respond to clients’ requests and enhance the design argilty. In this paper, after a brief introduction of the integrated design system, the network support framework is presented, followed by description of two key techniques involved: Java Saverlet approach for remotely executing a large program and online CAD collaboration

Implementation of QoS onto virtual bus network

Quality of Service (QoS) is a key issue in a multimedia environment because multimedia applications are sensitive to delay. The virtual bus architecture is a hierarchical access network structure that has been proposed to simplify network signaling. The network employs an interconnection of hierarchical database to support advanced routing of the signaling and traffic load. Therefore, the requirements and management of quality of service is important in the virtual bus network particularly to support multimedia applications. QoS and traffic parameters are specified for each class type and the OMNeT model has been described

A Real time network at home

This paper proposes a home network which integrates both real-time and non-real-time capabilities for one coherent, distributed architecture. Such a network is not yet available. Our network will support inexpensive, small appliances as well as more expensive, large appliances. The network is based on a new type of real-time token protocol that uses scheduling to achieve optimal token-routing through the network. Depending on the scheduling algorithm, bandwidth utilisations of 100 percent are possible. Token management, to prevent token-loss or multiple tokens, is essential to support a dynamic, plug-and-play configuration. Small appliances, like sensors, would contain low-cost, embedded processors with limited computing power, which can handle lightweight network protocols. All other operations can be delegated to other appliances that have sufficient resources. This provides a basis for transparency, as it separates controlling and controlled object. Our network will support this. We will show the proposed architecture of such a network and present experiences with and preliminary research of our design

A Concurrent Fuzzy-Neural Network Approach for Decision Support Systems

Decision-making is a process of choosing among alternative courses of action for solving complicated problems where multi-criteria objectives are involved. The past few years have witnessed a growing recognition of Soft Computing technologies that underlie the conception, design and utilization of intelligent systems. Several works have been done where engineers and scientists have applied intelligent techniques and heuristics to obtain optimal decisions from imprecise information. In this paper, we present a concurrent fuzzy-neural network approach combining unsupervised and supervised learning techniques to develop the Tactical Air Combat Decision Support System (TACDSS). Experiment results clearly demonstrate the efficiency of the proposed technique

Social working memory: neurocognitive networks and directions for future research.

Navigating the social world requires the ability to maintain and manipulate information about people's beliefs, traits, and mental states. We characterize this capacity as social working memory (SWM). To date, very little research has explored this phenomenon, in part because of the assumption that general working memory systems would support working memory for social information. Various lines of research, however, suggest that social cognitive processing relies on a neurocognitive network (i.e., the "mentalizing network") that is functionally distinct from, and considered antagonistic with, the canonical working memory network. Here, we review evidence suggesting that demanding social cognition requires SWM and that both the mentalizing and canonical working memory neurocognitive networks support SWM. The neural data run counter to the common finding of parametric decreases in mentalizing regions as a function of working memory demand and suggest that the mentalizing network can support demanding cognition, when it is demanding social cognition. Implications for individual differences in social cognition and pathologies of social cognition are discussed

Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy

Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention