This paper proposes a novel dataflow architecture called DFNET (DataFlow architecture on the interNET), which realizes a scalable dynamic dataflow computer on a packet switching network. A vast amount of research on dataflow computers has been extensively performed during, in particular, 1970s and 1980s as a promising approach for realizing very high-speed computers. In spite of the large amoun...

This paper presents our latest investigations of the jointly trained maximum entropy and recurrent neural network language models for Code-Switching speech. First, we explore extensively the integration of part-of-speech tags and language identifier information in recurrent neural network language models for CodeSwitching. Second, the importance of the maximum entropy model is demonstrated alon...

In this paper we illustrate a new protocol stack, namely the FCNS (Future Core Networks System), primarily designed for carrying signalling information in the UMTS core network packet switched domain that will provide interoperability with the circuit switched domain and greater flexibility, robustness and security than the proposed schemes from the telecommunications community. The paper is di...

In this paper, the authors present a method of measuring the switching time of a dual redundant NIC. The accuracy of the authors’ method of measuring switching time can reach milliseconds. The authors’ method uses Internet Control Message Protocol (ICMP) packets to test, is easy to operate, has high precision, and can be applied to all types of dual redundant device switching time measurement. ...

This article discusses the identification of nonlinear dynamic systems using multi-layer perceptrons (MLP). It focuses on both the structure uncertainty and parameter uncertainty which have been widely explored in the 10 literature of nonlinear system identification. The main contribution is that an integrated analytic framework is proposed for automated neural network structure selection, para...

The functional reconfiguration of central neuronal networks, a phenomenon by which neurons change their participation in network operation, is important for organizing adaptive behaviors. Such reconfiguration can be expressed in a long-lasting manner (hours, days) after a training paradigm. The present study shows that such a long-lasting network reconfiguration requires a cooperation of both p...