Power properties if invariant tests for spatial autocorrelation in linear regression

This paper derives some exact power properties of tests for spatial autocorrelation in the context of a linear regression model. In particular, we characterize the circumstances in which the power vanishes as the autocorrelation increases, thus extending the work of Krämer (2005). More generally, the analysis in the paper sheds new light on how the power of tests for spatial autocorrelation is affected by the matrix of regressors and by the spatial structure. We mainly focus on the problem of residual spatial autocorrelation, in which case it is appropriate to restrict attention to the class of invariant tests, but we also consider the case when the autocorrelation is due to the presence of a spatially lagged dependent variable among the regressors. A numerical study aimed at assessing the practical relevance of the theoretical results is included

Entropy versus APE production: on the buoyancy power input in the oceans energy cycle

This letter argues that the current controversy about whether Wbuoyancy, the power input due to the surface buoyancy fluxes, is large or small in the oceans stems from two distinct and incompatible views on how Wbuoyancy relates to the volume-integrated work of expansion/contraction B. The current prevailing view is that Wbuoyancy should be identified with the net value of B, which current theories estimate to be small. The alternative view, defended here, is that only the positive part of B, i.e., the one converting internal energy into mechanical energy, should enter the definition of Wbuoyancy, since the negative part of B is associated with the non-viscous dissipation of mechanical energy. Two indirect methods suggest that by contrast, the positive part of B is potentially large.

Neural networks for power systems alarm handling

A multi-layered architecture of self-organizing neural networks is being developed as part of an intelligent alarm processor to analyse a stream of power grid fault messages and provide a suggested diagnosis of the fault location. Feedback concerning the accuracy of the diagnosis is provided by an object-oriented grid simulator which acts as an external supervisor to the learning system. The utilization of artificial neural networks within this environment should result in a powerful generic alarm processor which will not require extensive training by a human expert to produce accurate results.

Testing for spatial autocorrelation: the regressors that make the power disappear

We show that for any sample size, any size of the test, and any weights matrix outside a small class of exceptions, there exists a positive measure set of regression spaces such that the power of the Cli-Ord test vanishes as the autocorrelation increases in a spatial error model. This result extends to the tests that dene the Gaussian power envelope of all invariant tests for residual spatial autocorrelation. In most cases, the regression spaces such that the problem occurs depend on the size of the test, but there also exist regression spaces such that the power vanishes regardless of the size. A characterization of such particularly hostile regression spaces is provided.

Adaptive alarm processor for fault diagnosis on power transmission networks

The authors describe a learning classifier system (LCS) which employs genetic algorithms (GA) for adaptive online diagnosis of power transmission network faults. The system monitors switchgear indications produced by a transmission network, reporting fault diagnoses on any patterns indicative of faulted components. The system evaluates the accuracy of diagnoses via a fault simulator developed by National Grid Co. and adapts to reflect the current network topology by use of genetic algorithms.

Power distribution network design aided by an expert system

The next couple of years will see the need for replacement of a large amount of life-expired switchgear on the UK 11 kV distribution system. Latest technology and alternative equipment have made the choice of replacement a complex task. The authors present an expert system as an aid to the decision process for the design of the 11 kV power distribution network.

Power control requirements in linear decorrelating detectors for CDMA

This paper addresses the effects of synchronisation errors (time delay, carrier phase, and carrier frequency) on the performance of linear decorrelating detectors (LDDs). A major effect is that all LDDs require certain degree of power control in the presence of synchronisation errors. The multi-shot sliding window algorithm (SLWA) and hard decision method (HDM) are analysed and their power control requirements are examined. Also, a more efficient one-shot detection scheme, called “hard-decision based coupling cancellation”, is proposed and analysed. These schemes are then compared with the isolation bit insertion (IBI) approach in terms of power control requirements.

The power of NMR. Part 1: the beginnings

Nuclear mnagnetic resonance (NMR) spectroscopy involves the excitation of nuclei by electromagnetic radiation in the radio-frequency range of the electromagnetic spectrum. For a nucleus to absorb energy from radiowaves in this way, it must hve the quantum mechanical property of spin. A spinning nucleus, such as that of the hydrogen atom, will dopt one f only two possible states when placed in a magnetic field. (In NMR, the hydrogen nucleus is often referred to as a proton, and is given the abbreviation 1H.) Az the strength of the magnetic field is increased, there is a proportional increase in the energy 'gap' between these two states. We can predic the resonant frequency at which any spinning nucleus will absorb energy from radio-frequency radiation as it jumps from the lower energy state to the upper state.

A new study on the power distribution of OFDMA, SC-FDMA and CP-CDMA signals

This paper explores a new technique to calculate and plot the distribution of instantaneous transmit envelope power of OFDMA and SC-FDMA signals from the equation of Probability Density Function (PDF) solved numerically. The Complementary Cumulative Distribution Function (CCDF) of Instantaneous Power to Average Power Ratio (IPAPR) is computed from the structure of the transmit system matrix. This helps intuitively understand the distribution of output signal power if the structure of the transmit system matrix and the constellation used are known. The distribution obtained for OFDMA signal matches complex normal distribution. The results indicate why the CCDF of IPAPR in case of SC-FDMA is better than OFDMA for a given constellation. Finally, with this method it is shown again that cyclic prefixed DS-CDMA system is one case with optimum IPAPR. The insight that this technique provides may be useful in designing area optimised digital and power efficient analogue modules.