Forecasting UK real estate cycle phases with leading indicators: a probit approach

This paper examines the significance of widely used leading indicators of the UK economy for predicting the cyclical pattern of commercial real estate performance. The analysis uses monthly capital value data for UK industrials, offices and retail from the Investment Property Databank (IPD). Prospective economic indicators are drawn from three sources namely, the series used by the US Conference Board to construct their UK leading indicator and the series deployed by two private organisations, Lombard Street Research and NTC Research, to predict UK economic activity. We first identify turning points in the capital value series adopting techniques employed in the classical business cycle literature. We then estimate probit models using the leading economic indicators as independent variables and forecast the probability of different phases of capital values, that is, periods of declining and rising capital values. The forecast performance of the models is tested and found to be satisfactory. The predictability of lasting directional changes in property performance represents a useful tool for real estate investment decision-making

A Neural Network Measurement of Relative Military Security: The Case of Greece and Cyprus

This paper aims at introducing a relative security measure, applicable to evaluating the impact of arms races on the military security of allies. This measure is based on demographic criteria, which play a dominant role in a number of arms races involving military alliances. The case of Greece and Cyprus, on one hand, and Turkey on the other, is the one to which our relative security measure is applied and tested. Artificial neural networks were trained to forecast the future behaviour of relative security. The high forecasting performance permitted the application of alternative scenarios for predicting the impact of the Greek - Turkish arms race on the relative security of the Greek - Cypriot alliance.Arms Race, Neural Networks, Relative Military Security

Financial Versus Human Resources in the Greek-Turkish Arms Race: A Forecasting Investigation Using Artificial Neural Networks

This paper aims at forecasting the burden on the Greek economy resulting from the arms race against Turkey and at concentrating on the leading determinants of this burden. The military debt and the defence share of GDP are employed alternatively in order to approximate the measurement of the arms race pressure on Greece, and the method used is that of artificial neural networks. The use of a wide variety of explanatory variables in combination with the promising results derived, suggest that the impact on the Greek economy resulting from this arms race is determined, to a large extent, by demographic factors which strongly favour the Turkish side. Prediction on both miltary debt and defence expenditure exhibited highly satisfactory accuracy, while the estimation of input significance, indicates that variables describing the Turkish side are often dominant over the corresponding Greek ones.Greek Military Debt, Defence Expenditure, Neural Networks

Broadband rotor noise analyses

The various mechanisms which generate broadband noise on a range of rotors studied include load fluctuations due to inflow turbulence, due to turbulent boundary layers passing the blades' trailing edges, and due to tip vortex formation. Existing analyses are used and extensions to them are developed to make more accurate predictions of rotor noise spectra and to determine which mechanisms are important in which circumstances. Calculations based on the various prediction methods in existing experiments were compared. The present analyses are adequate to predict the spectra from a wide variety of experiments on fans, full scale and model scale helicopter rotors, wind turbines, and propellers to within about 5 to 10 dB. Better knowledge of the inflow turbulence improves the accuracy of the predictions. Results indicate that inflow turbulence noise depends strongly on ambient conditions and dominates at low frequencies. Trailing edge noise and tip vortex noise are important at higher frequencies if inflow turbulence is weak. Boundary layer trailing edge noise, important, for large sized rotors, increases slowly with angle of attack but not as rapidly as tip vortex noise

Computational Intelligence in Exchange-Rate Forecasting

This paper applies computational intelligence methods to exchange rate forecasting. In particular, it employs neural network methodology in order to predict developments of the Euro exchange rate versus the U.S. Dollar and the Japanese Yen. Following a study of our series using traditional as well as specialized, non-parametric methods together with Monte Carlo simulations we employ selected Neural Networks (NNs) trained to forecast rate fluctuations. Despite the fact that the data series have been shown by the Rescaled Range Statistic (R/S) analysis to exhibit random behaviour, their internal dynamics have been successfully captured by certain NN topologies, thus yielding accurate predictions of the two exchange-rate series.Exchange - rate forecasting, Neural networks

Reports and Maps of the Geological Survey Released Only in the Open Files, 1966

There is a reference to the Espey "Some effects on urbanization on storm runoff, Waller Creek".Waller Creek Working Grou

General anesthesia does not have persistent effects on attention in rodents

Background: Studies in animals have shown that general anesthesia can cause persistent spatial memory impairment, but the influence of anesthetics on other cognitive functions is unclear. This study tested whether exposure to general anesthesia without surgery caused a persistent deficit in attention in rodents.Methods: To evaluate whether anesthesia has persistent effects on attention, rats were randomized to three groups. Group A was exposed for 2 h to isoflurane anesthesia, and tested the following seven days for attentional deficits. Group B was used as a control and received room air before attentional testing. Since there is some evidence that a subanesthetic dose of ketamine can improve cognition and reduce disorders of attention after surgery, rats in group C were exposed to isoflurane anesthesia in combination with a ketamine injection before cognitive assessment. Attention was measured in rats using the 5-Choice Serial Reaction Time Task, for which animals were trained to respond with a nose poke on a touchscreen to a brief, unpredictable visual stimulus in one of five possible grid locations to receive a food reward. Attention was analyzed as % accuracy, % omission, and premature responses.Results: Evaluating acute attention by comparing baseline values with data from the day after intervention did not reveal any differences in attentional measurements. No significant differences were seen in % accuracy, % omission, and premature responses for the three groups tested for 7 consecutive days.Conclusion: These data in healthy rodents suggest that general anesthesia without surgery has no persistent effect on attention and the addition of ketamine does not alter the outcome