Magnetic Position and Orientation Tracking System

Three-axis generation and sensing of quasi-static magneticdipole fields provide information sufficient to determine both the position and orientation of the sensor relative to the source. Linear rotation transformations based upon the previous measurements are applied to both the source excitation and sensor output vectors, yielding quantities that are linearly propotional to small changes in the position and orientation. Changes are separated using linear combinations of sensor output vectors, transformed to the desired coordinate frame, and used to update the previous measurements. Practical considerations for a head-tracking application are discussed.     

Progress in space weather predictions and applications

The methods of today’s predictions of space weather and effects are so much more advanced and yesterday’s statistical methods are now replaced by integrated knowledge-based neuro-computing models and MHD methods. Within the ESA Space Weather Programme Study a real-time forecast service has been developed for space weather and effects. This prototype is now being implemented for specific users. Today’s applications are not only so many more but also so much more advanced and user-oriented. A scientist needs real-time predictions of a global index as input for an MHD model calculating the radiation dose for EVAs. A power company system operator needs a prediction of the local value of a geomagnetically induced current. A science tourist needs to know whether or not aurora will occur. Soon we might even be able to predict the tropospheric climate changes and weather caused by the space weather.     

On the electrodynamics of counter stream in pulsar’s inner annular cap region

The electric properties of pulsar’s inner annular gap are explored in this paper. Under two main assumptions, (1) the pulsar is alive, (2) the total charge of pulsar should not vary with time, the condition for the acceleration of negative particle in the annular region is derived. The acceleration condition is j₋ ? 0.5j₊, i.e., the current carried by negative particles is greater than or equal to 0.5 times of the current carried by positive particles. This condition holds even when the backward flow of positive particles exists in the annular region. It is noted that the outflow of negative particles offers good opportunities to understand the current closure problem of pulsar as well as wide radiation beam of pulsar observed at high energy band.     

Electromagnetic waves observed by Venus Express at periapsis: Detection and analysis techniques

The magnetometer on Venus Express was designed to be able to obtain 128 Hz samples of the magnetic field from two sensors in a gradiometer configuration. This mode is used around periapsis to determine whether the signals reported at low altitudes near 100 Hz, had the properties of electromagnetic waves generated by electric discharges in the Venus atmosphere. The lack of a magnetic cleanliness program and the shortness of the magnetometer boom make this a challenging measurement. Fortunately the signals are sufficiently strong that they can be easily resolved with rather straightforward analysis techniques.     

Sunspot cycle 23 descent to an unusual minimum and forecasts for cycle 24 activity

The decay phase of the sunspot cycle 23 exhibited two unusual features. First, it lasted too long. Second, the interplanetary magnetic field intensity at earth orbit reached the lowest value since in situ measurements in space began in October 1963. These physical anomalies significantly altered the early forecasts for the sunspot activity parameters for cycle 24, made by several colleagues. We note that there was a significant change in the solar behavior during cycle 22. We discuss the observed trends and their effect on our empirical solar activity forecast technique, leading to our prediction for cycle 24 parameters; cycle 24 will be only half as active as cycle 23, reaching its peak in May 2013. We speculate on the possible implications of this outcome on future earth climate change and the ensuing socio-economic consequences.     

The effect of gravity on surface temperature and net photosynthetic rate of plant leaves.

To clarify the effects of gravity on heat/gas exchange between plant leaves and the ambient air, the leaf temperatures and net photosynthetic rates of plant leaves were evaluated at 0.01, 1.0, 1.5 and 2.0 G of 20 seconds each during a parabolic airplane flight. Thermal images of leaves were captured using infrared thermography at an air temperature of 26 degrees C, a relative humidity of 15% and an irradiance of 260 W m-2. The net photosynthetic rates were determined by using a chamber method with an infrared gas analyzer at an air temperature of 20 degrees C, a relative humidity of 50% and a photosynthetic photon flux of 0.5 mmol m-2 s-1. The mean leaf temperature increased by 1 degree C and the net photosynthetic rate decreased by 13% with decreasing gravity levels from 1.0 to 0.01 G. The leaf temperature decreased by 0.5 degree C and the net photosynthetic rate increased by 7% with increasing gravity levels from 1.0 to 2.0 G. Heat/gas exchanges between leaves and the ambient air were more retarded at lower gravity levels. A restricted free air convection under microgravity conditions in space would limit plant growth by retarding heat and gas exchanges between leaves and the ambient air.     

Hypothesis-test-based landcover change detection using multi-temporal satellite images – A comparative study

Remote sensing images and technologies have been widely applied to environmental monitoring, in particular landuse/landcover classification and change detection. However, the uncertainties involved in such applications have not been fully addressed. In this paper two hypothesis-test-based change detection methods, namely the bivariate joint distribution method and the conditional distribution method, are proposed to tackle the uncertainties in change detection by making decisions based on the desired level of significance. Both methods require a data set of class-dependent no-change pixels to form the basis for class-dependent hypothesis test. Using an exemplar study area in central Taiwan, performance of the proposed methods are shown to be significantly superior to two other commonly applied methods (the post-classification comparison and the image differencing methods) in terms of the overall change detection accuracies. The conditional distribution method takes into consideration the correlation between digital numbers of the pre- and post-images and the effect of the known pre-image digital number on the range of the post-image digital number, and therefore yields the highest change detection accuracy. It is also demonstrated that the class-dependent change detection is crucial for accurate landuse/landcover change detection.     

Indirect search for Dark Matter with H.E.S.S.

Observations of the Galactic center region with the H.E.S.S. telescopes have established the existence of a steady, extended source of gamma-ray emission coinciding with the position of the super massive black hole Sgr A^*. This is a remarkable finding given the expected presence of dense self-annihilating Dark Matter in the Galactic center region. The self-annihilation process is giving rise to gamma-ray production through hadronization including the production of neutral pions which decay into gamma-rays but also through (loop-suppressed) annihilation into final states of almost mono-energetic photons. We study the observed gamma-ray signal (spectrum and shape) from the Galactic center in the context of Dark Matter annihilation and indicate the prospects for further indirect Dark Matter searches with H.E.S.S.     

Solar flare forecasting model supported with artificial neural network techniques

Nowadays operational models for solar activity forecasting are still based on the statistical relationship between solar activity and solar magnetic field evolution. In order to set up this relationship, many parameters have been proposed to be the measures. Conventional measures are based on the sunspot group classification which provides limited information from sunspots. For this reason, new measures based on solar magnetic field observations are proposed and a solar flare forecasting model supported with an artificial neural network is introduced. This model is equivalent to a person with a long period of solar flare forecasting experience.