Long-term trends in f0 F2 over Grahamstown using Neural Networks

Many authors have claimed to have found long-term trends in f0 F2 , or the lack thereof, for different stations. Such investigations usually involve gross assumptions about the variation of f0 F2 with solar activity in order to isolate the long-term trend, and the variation with magnetic activity is often ignored completely. This work describes two techniques that make use of Neural Networks to isolate long-term variations from variations due to season, local time, solar and magnetic activity. The techniques are applied to f0 F2 data from Grahamstown, South Africa (26 E, 33 S). The maximum long-term change is shown to be extremely linear, and negative for most hours and days. The maximum percentage change tends to occur in summer in the afternoon, but is noticeably dependent on solar activity. The effect of magnetic activity on the percentage change is not marked

Neural network-based ionospheric modelling over the South African region

During the past decade, South African scientists have pioneered research in the field of ionospheric modelling using the technique of neural networks (NNs). Global ionospheric models have always been insufficient for the South African region owing to an historical paucity of available data. Within the past 10 years, however, three new ionospheric sounders have been installed locally and are operating continuously. These sounders are located at Grahamstown (33.3°S, 26.5°E), Louisvale (28.5°S, 21.2°E) and Madimbo (22.4°S, 30.9°E). The addition of a modern sounder at Grahamstown enlarged the ionospheric database for this station to 30 years, making this archive a considerable asset for ionospheric research. Quality control and online availability of the data has also added to its attraction. An important requirement for empirical modelling, but especially for employing NNs, is a large database describing the history of the relationship between the ionosphere and the geophysical parameters that define its behaviour. This review describes the path of South African ionospheric modelling over the past 10 years, the role of NNs in this development, the international collaborations that have arisen from this, and the future of ionospheric modelling in South Africa

Guidelines for fabrication of hybrid microcircuits

Document is summary of approaches that may be taken in designing hybrid microcircuits similar to those for aerospace application

An analysis of automatically scaled F1 layer data over Grahamstown, South Africa

This paper describes an analysis of automatically scaled F1 layer data over Grahamstown, South Africa (33.3°S, 26.5°E). An application for real time raytracing through the South African ionosphere was identified, and for this application real time evaluation of the electron density profile is essential. Raw real time virtual height data are provided by a Lowell Digisonde (DPS), which employs the automatic scaling software, ARTIST whose output includes the virtual-to-real height data conversion. Experience has shown that there are times when the raytracing performance is degraded because of difficulties surrounding the real time characterisation of the F1 region by ARTIST. The purpose of this investigation is to establish the extent of the problem, the times and conditions under which it occurs, with a view to formulating remedial alternative strategies, such as predictive modelling

Neural network-based prediction techniques for global modeling of M(3000)F2 ionospheric parameter

In recent times neural networks (NNs) have been employed to solve many problems in ionospheric predictions. This paper illustrates a new application of NNs in developing a global model of the ionospheric propagation factor M(3000)F2. NNs were trained with daily hourly values of M(3000)F2 from various ionospheric stations spanning the period 1964–1986 with the following temporal and spatial input parameters: Universal Time, geographic latitude, magnetic inclination, magnetic declination, solar zenith angle, day of the year, A16 index (a 2-day running mean of the 3-h planetary magnetic ap index), R2 index (a 2-month running mean of sunspot number), and the angle of meridian relative to the subsolar point. The performance of the NNs was verified by comparing the predicted values of M(3000)F2 with observed values from a few selected ionospheric stations and the IRI (International Reference Ionosphere) model (CCIR M(3000)F2 model) predicted values. The results obtained compared favourably with the IRI model. Based on the error differences, the result obtained justifies the potential of the NN technique for the predictions of M(3000)F2 values on a global scale

Near-real time foF2 predictions using neural networks

This paper describes the use of the neural network (NN) technique for the development of a near-real time global foF2 (NRTNN) empirical model. The data used are hourly daily values of foF2 from 26 worldwide ionospheric stations (based on availability) during the period 1976–1986 for training the NN and between 1977 and 1989 for verifying the prediction accuracy. The training data set includes all periods of quiet and disturbed geomagnetic conditions. Two categories of input parameters were used as inputs to the NN. The first category consists of geophysical parameters that are temporally or spatially related to the training stations. The second category, which is related to the foF2 itself, consists of three recent past observations of foF2 (i.e. real-time foF2 (F0), 2 h (F−2) and 1 h (F−1) prior to F0) from four control stations (i.e. Boulder (40.0°N, 254.7°E), Grahamstown (33.3°S, 26.5°E), Dourbes (50.1°N, 4.6°E) and Port Stanley (51.7°S, 302.2°E). The performance of the NRTNN was verified under both geomagnetically quiet and disturbed conditions with observed data from a few verification stations. A comparison of the root mean square error (RMSE) differences between measured values and the NRTNN predictions with our earlier standard foF2 NN empirical model is also illustrated. The results reveal that NRTNN will predict foF2 in near-real time with about 1 MHz RMSE difference anywhere on the globe, provided real time data is available at the four control stations. From the results it is also evident that in addition to the geophysical information from any geographical location, recent past observations of foF2 from these control stations could be used as inputs to a NN for near-real time foF2 predictions. Results also reveal that there is a temporal correlation between measured foF2 values at different locations

Magnetization dynamics in the single-molecule magnet Fe8 under pulsed microwave irradiation

We present measurements on the single molecule magnet Fe8 in the presence of pulsed microwave radiation at 118 GHz. The spin dynamics is studied via time resolved magnetization experiments using a Hall probe magnetometer. We investigate the relaxation behavior of magnetization after the microwave pulse. The analysis of the experimental data is performed in terms of different contributions to the magnetization after-pulse relaxation. We find that the phonon bottleneck with a characteristic relaxation time of 10 to 100 ms strongly affects the magnetization dynamics. In addition, the spatial effect of spin diffusion is evidenced by using samples of different sizes and different ways of the sample's irradiation with microwaves.Comment: 14 pages, 12 figure

Electron spin-orbit splitting in InGaAs/InP quantum well studied by means of the weak antilocalization and spin-zero effects in tilted magnetic fields

The coupling between Zeeman spin splitting and Rashba spin-orbit terms has been studied experimentally in a gated InGaAs/InP quantum well structure by means of simultaneous measurements of the weak antilocalization (WAL) effect and beating in the SdH oscillations. The strength of the Zeeman splitting was regulated by tilting the magnetic field with the spin-zeros in the SdH oscillations, which are not always present, being enhanced by the tilt. In tilted fields the spin-orbit and Zeeman splittings are not additive, and a simple expression is given for the energy levels. The Rashba parameter and the electron g-factor were extracted from the position of the spin zeros in tilted fields. A good agreement is obtained for the spin-orbit coupling strength from the spin-zeros and weak antilocalization measurements.Comment: Accepted for publication in Semiconductors Science and Technolog