In this paper we present two methods for path delay fault testing of circuit-switched Benes Multistage Interconnection Networks (MINs) with centralized control. Although the number of paths is O(n3), the first method ...
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It is a classical result from graph theory that the edges of an l-regular bipartite graph can be colored using exactly l colors so that edges that share an endpoint are assigned different colors. In this paper we stud...
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Web based systems have been shown to be useful tools for supporting educational communication for teachers and students. In this paper we present such a system, which is an integrated distributed learning environment ...
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Web based systems have been shown to be useful tools for supporting educational communication for teachers and students. In this paper we present such a system, which is an integrated distributed learning environment (IDLE). We present the technical description of this IDLE and we discuss its main characteristics like the transmission of multimedia data over the network, the manipulation of the educational procedure and the management of the users. In addition we list the functionalities of the IDLE and also discuss some implementation issues.
This paper deals with the multiple medium access problem in the packet radio environment. Under the framework of Network-assisted Diversity Multiple Access (NDMA), a recently proposed multiple access method, rotationa...
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This paper deals with the multiple medium access problem in the packet radio environment. Under the framework of Network-assisted Diversity Multiple Access (NDMA), a recently proposed multiple access method, rotational invariance and PARAllel FACtor (PARAFAC) analysis signal processing tools are employed for blind collision resolution. The proposed approach (dubbed B-NDMA for Blind NDMA) overcomes the difficulty of orthogonal identification codes required by the original protocol, thereby improving channel utilization and system capacity, while being insensitive to multipath effects and synchronization errors. Performance issues are addressed both analytically and numerically.
In this paper we present a decomposition approach based on duality theory for line maintenance scheduling with transmission and voltage constraints. The given formulation consists of a master program and sub-problems ...
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In this paper we present a decomposition approach based on duality theory for line maintenance scheduling with transmission and voltage constraints. The given formulation consists of a master program and sub-problems with two independent programs. In the master problem, the maintenance problem is solved and in the subproblems, transmission and voltage problems are solved independently. Since cancelling a transaction or purchasing reactive power relates to the loss of revenue, the trade-off between maintenance cost and revenue loss is be optimized in the proposed method. The test results on the modified IEEE 118-bus system demonstrate that limits on transmission and voltage affect the line maintenance scheduling and increase the maintenance cost. While introducing the loss of revenue as one of the objective functions, the proposed method is flexible enough to accommodate various pricing objectives and methods.
This paper proposes a novel fuzzy-neural network for chattering free sliding mode control. Firstly, soft computing which is the fusion or combination of fuzzy systems, neural networks and genetic algorithms is studied...
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This paper proposes a novel fuzzy-neural network for chattering free sliding mode control. Firstly, soft computing which is the fusion or combination of fuzzy systems, neural networks and genetic algorithms is studied. Then, by taking advantages of fuzzy systems and neural networks a novel fuzzy-neural network with a general parameter learning algorithm and system structure determination is developed. The network is based on a local basis function network. The general parameter method (GP) is based on GMDH (group methods of data handling). The GP is used for a learning algorithm and the structure determination of the developed fuzzy neural network. As the resulting network needs only fuzzy inference computation with GP calculations, which is, generally speaking, the combination of soft and hard computing, called computational intelligence, is suitable to solve nonlinear problems, it especially needs a little computation time. Therefore, it is easy to implement with a HITACHI RISC+DSP microprocessor fast enough for real time operations. The developed signal processor is self-organizing, self-tuning and automated designed. In order to confirm the feasibility of fault diagnosis performance by the developed network, it is applied to chattering free sliding mode control. It is found that the developed method is suitable to other nonlinear control methods.
Epitaxial PbZr0.52Ti0.48O3/YBa2Cu3O7-x heterostructures on Nd:YAlO3 and MgO substrates were fabricated by KrF pulsed laser deposition. The coercive electric field of the PZT films increased with decrease of the film t...
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Epitaxial PbZr0.52Ti0.48O3/YBa2Cu3O7-x heterostructures on Nd:YAlO3 and MgO substrates were fabricated by KrF pulsed laser deposition. The coercive electric field of the PZT films increased with decrease of the film thickness from 1.2 μm to 0.04 μm, while the magnitude of spontaneous polarization was almost constant in this thickness range. It was found that the dependence of the film thickness d on the coercive electric field Ec was Ec ∝ d-2/3. This results from that the PZT/YBCO heterostructure has the one dimensional ferroelectric domain growth without non-ferroelectric phase. The polarization of Au/PZT/YBCO/(MgO or YAlO) capacitors can be changed by the applied voltage below 5 V.
We explore the intricacies of the duality of data hiding and data compression to help develop optimal data hiding techniques for images, that can reasonably resist lossy compression. The problem of efficient data hidi...
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We explore the intricacies of the duality of data hiding and data compression to help develop optimal data hiding techniques for images, that can reasonably resist lossy compression. The problem of efficient data hiding is split into two sub-problems-one of maximizing the resource-which is the permitted distortion of images, and the other of efficient use of the resource by means of sophisticated signaling techniques. Various options for the solutions of the former problem are proposed and their advantages and disadvantages explored. An optimal data hiding scheme making "good" use of the resource, using sophisticated signaling techniques is proposed.
In this paper, we analyze the existence of asymptotic error expansion of Nystrom solution for two-dimensional nonlinear Fredholm integral of the second kind. We show that the Nystrom solution admits an error expansion...
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In this paper, we analyze the existence of asymptotic error expansion of Nystrom solution for two-dimensional nonlinear Fredholm integral of the second kind. We show that the Nystrom solution admits an error expansion in powers of the step-size h and the step-size k. For a special choice of the numerical quadrature, the leading terms in the error expansion for the Nystrom solution contain only even powers of h and k, beginning with terms h2p and k2q. These expansions are useful for the application of Richardson extrapolation and for obtaining sharper error bounds. Numerical examples show that how Richardson extrapolation gives a remarkable increase of precision, in addition to faster convergence.
A new neural network-based fault classification strategy for hard multiple faults in analog circuits is proposed. The magnitude of the harmonics of the Fourier components of the circuit response at different test node...
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A new neural network-based fault classification strategy for hard multiple faults in analog circuits is proposed. The magnitude of the harmonics of the Fourier components of the circuit response at different test nodes due to a sinusoidal input signal are first measured or simulated. A selection criterion for determining the best components that describe the circuit behaviour under fault-free (nominal) and fault situations is presented. An algorithm that estimates the overlap between different faults in the measurement space is also introduced. The learning vector quantization neural network is then effectively trained to classify circuit faults. Performance measures reveal very high classification accuracy in both training and testing stages. Two different examples, which demonstrate the proposed strategy, are described.
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