Estimating starting point of conduction of CMOS gates

To model effectively the output waveform and propagation delay of a CMOS gate, knowledge of the time point at which it starts to conduct is essential. An efficient method for calculating analytically this time point taking into account the structure of the gate and the input waveform, is introduced. Such a method can easily be integrated into a timing analysis system     

Influence of Ag admixtures on the crystallization of amorphous Fe75Si9B16

This work studies the influence of the Ag admixtures on the crystallization of the amorphous Fe₇₅Si₉B₁₆ alloy, with the aid of electric and magnetic measurements. It is concluded that the solid solubility of the Ag in these alloys is very small, reaching 2 at% at most. Because of microsegregation, the presence of even these minimal admixtures accelerates the crystallization procedure.     

Vertical two-phase flow identification using advanced instrumentation and neural networks

Most two-phase flow measurements, including void fraction measurements, depend on correct flow regime identification. There are two steps taken towards the successful identification of flow regimes: first, develop a non-intrusive instrument to demonstrate area-averaged void fluctuations and second, develop a non-linear mapping approach to perform objective identification of flow regimes. In this paper, an advanced non-intrusive impedance void-meter provides input signals to neural networks which are used to identify flow regimes. After training, both supervised and self-organizing neural network learning paradigms performed flow regime identification successfully. The methodology presented holds considerable promise for multiphase flow diagnostic and measurement applications.     

On some reliability estimation problems in random and partitiontesting

Studies have shown that random testing can be an effective testing strategy. One of the goals of testing is to estimate the reliability of the program from the test outcomes. The authors extend the Thayer-Lipow-Nelson reliability model (R. Thayer et al., 1978) to account for the cost of errors. They also compare random testing with partition testing by examining upper confidence bounds for the cost weighted performance of the two strategies     

Australian Electricity Market

A neurofuzzy methodology for online nodal load prediction is introduced that exploits the power of artificial neural networks (ANN) and fuzzy logic. ANNs are used to capture the power consumption patterns specific to a customer, while a fuzzy logic module detects departures from equilibrium (that is, previously established consumption patterns). The fuzzy-logic-based (FL) module (called PROTREN) performs signal trend identification. The proposed methodology improves the adaptability of the forecasting system to sudden changes or special events that may influence the load by temporarily distorting the general pattern and thus rendering the load signal highly unpredictable. Experiments have been performed to verify the effectiveness of the new methodology. Results show that the methodology has a better performance than those using traditional forecasting methodologies, especially when special events influencing the load occur.     

On the high temperature electrical resistivity behaviour of Cu55-Ni45 alloy

Resistivity measurements supplemented with electron microscopy investigation in a Cu₅₅-Ni₄₅ alloy are reported, in the temperature range 273–700 K. An anomalous high temperature resistivity minimum is observed at 673 K whereas at the same temperature diffuse intensity maxima appear. It is suggested that the resistivity minimum could be attributed to the effect of short range order cluster formation.     

On the structural and transport properties of the Ni-Fe invar alloy system

Several experiments concerning structural, electrical and magnetic properties of the NiFe alloy system near the composition range Fe₃Ni and temperatures ranging from 300 to 1000 K have been conducted. TEM studies using a heating stage showed transformation α→v upon heating and v→α upon cooling. Electrical resistivity measurements in the same temperature range indicate also the presence of (α+v) phase, whereas magnetic measurements in the temperature range 4,2–1000 K and fields up to 100 kOe show no indication of an ordered state.     

Metallic post coated by a dielectric tube in waveguide,a NB filter design

Contents The discontinuity problem of a metallic post coated by a dielectric tube in a rectangular waveguide has been solved numerically.—From the solution parametric curves have been derived displaying the parameters of the T-equivalent circuit in dependence of the post geometrie. Several cases of the dielectric tube permittivity are considered. For some special relations between the frequency, the dielectric constant and the radius of the post the reflection or the transmission coefficient becomes equal to zero. These relations give narrow-band filters. Experimental results have shown the utility of the method as a filter design tool.

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Metallstift, der in einem Hohlleiter von einem dielektrischen Mantel umgeben ist, eine Entwurfsmethode für NB Filter

Übersicht Das Problem der Diskontinuität eines dielektrisch ummantelten Metallstiftes in einem Hohlleiter ist numerisch gelöst worden. Parameterkurven sind aus der Lösung abgeleitet worden und stellen die Parameter des T-äquivalenten Stromkreises in Abhängigkeit von der Geometrie des Stiftes dar, wobei unterschiedliche Permeabilitäten des dielektrischen Mantels berücksichtigt wurden. Für bestimmte Verhältnisse zwischen der Frequenz, der Dielektrizitätskonstanten und des Stiftradius wird der Reflektions- oder der Transmissionskoeffizient gleich Null. Diese Verhältnisse ergeben NB-Filter. Versuchsergebnisse haben die Nützlichkeit der Methode als Verfahren für den Filterentwurf gezeigt.

     

A neurofuzzy methodology for impedance-based multiphase flow identification

A neurofuzzy methodology for flow identification based on signals obtained from an impedance void meter is presented. The methodology combines the filtering and interpolative capabilities of neural networks with the representational advantages of fuzzy systems for the purpose of mapping idiosyncratic area-averaged impedance measurements to multiphase flow regimes. It has been shown that electrical signals representing the conductance of the intervening medium can be used to infer crucial flow parameters, and that area-averaged signals contain sufficient information about flow regime and the structure of its two-phase constituents. The neurofuzzy approach is a promising means for reconstructing the visual imagery of flow in a process, analogous to tomography, and holds considerable promise for multiphase flow diagnostic and measurement applications in the nuclear as well as in the petroleum, biomedical, and food-processing industries.