Ionosphere-atmosphere interaction during solar proton events

Among the most striking natural phenomena affecting ozone are solar proton events (SPE), during which high-energy protons precipitate into the middle atmosphere in the polar regions. Ionisation caused by the protons results in changes in the lower ionosphere, and in production of neutral odd nitrogen and odd hydrogen species which then destroy ozone in well-known catalytic chemical reaction chains. Large SPEs are able to decrease the ozone concentration of upper stratosphere and mesosphere, but are not expected to significantly affect the ozone layer at 15--30~km altitude. In this work we have used the Sodankylä Ion and Neutral Chemistry Model (SIC) in studies of the short-term effects caused by SPEs. The model results were found to be in a good agreement with ionospheric observations from incoherent scatter radars, riometers, and VLF radio receivers as well as with measurements from the GOMOS/Envisat satellite instrument. For the first time, GOMOS was able to observe the SPE effects on odd nitrogen and ozone in the winter polar region. Ozone observations from GOMOS were validated against those from MIPAS/Envisat instrument, and a good agreement was found throughout the middle atmosphere. For the case of the SPE of October/November 2003, long-term ozone depletion was observed in the upper stratosphere. The depletion was further enhanced by the descent of odd nitrogen from the mesosphere inside the polar vortex, until the recovery occurred in late December. During the event, substantial diurnal variation of ozone depletion was seen in the mesosphere, caused mainly by the the strong diurnal cycle of the odd hydrogen species. In the lower ionosphere, SPEs increase the electron density which is very low in normal conditions. Therefore, SPEs make radar observations easier. In the case of the SPE of October, 1989, we studied the sunset transition of negative charge from electrons to ions, a long-standing problem. The observed phenomenon, which is controlled by the amount of solar radiation, was successfully explained by considering twilight changes in both the rate of photodetachment of negative ions and concentrations of minor neutral species. Changes in the magnetic field of the Earth control the extent of SPE-affected area. For the SPE of November 2001, the results indicated that for low and middle levels of geomagnetic disturbance the estimated cosmic radio noise absorption levels based on a magnetic field model are in a good agreement with ionospheric observations. For high levels of disturbance, the model overestimates the stretching of the geomagnetic field and the geographical extent of SPE-affected area. This work shows the importance of ionosphere-atmosphere interaction for SPE studies. By using both ionospheric and atmospheric observations, we have been able to cover for the most part the whole chain of SPE-triggered processes, from proton-induced ionisation to depletion of ozone.

Verkkoradio, musiikki ja radio - katsaus verkkoradioihin osana suomalaisten musiikin kuuntelua

This thesis examines Internet-radios and other web-based music services, and different ways these services are used in music listening in Finland. The research material was gathered in eight interviews that took place between spring 2005 and spring 2006 in southern Finland. The analysis distinguishes between five main types of Internet-radios: a) simulcasting, b) webcasting, c) podcasting, d) web-based sound archives, e) interactive music services. As a medium for music listening these combine aspects of computers and traditional radio. The role of Internet-radios in everyday life as well as different types of listening motivation are examined in the light of earlier research on taste, music listening and radio listening.

Semi-supervised learning of WLAN radio maps

In this thesis a manifold learning method is applied to the problem of WLAN positioning and automatic radio map creation. Due to the nature of WLAN signal strength measurements, a signal map created from raw measurements results in non-linear distance relations between measurement points. These signal strength vectors reside in a high-dimensioned coordinate system. With the help of the so called Isomap-algorithm the dimensionality of this map can be reduced, and thus more easily processed. By embedding position-labeled strategic key points, we can automatically adjust the mapping to match the surveyed environment. The environment is thus learned in a semi-supervised way; gathering training points and embedding them in a two-dimensional manifold gives us a rough mapping of the measured environment. After a calibration phase, where the labeled key points in the training data are used to associate coordinates in the manifold representation with geographical locations, we can perform positioning using the adjusted map. This can be achieved through a traditional supervised learning process, which in our case is a simple nearest neighbors matching of a sampled signal strength vector. We deployed this system in two locations in the Kumpula campus in Helsinki, Finland. Results indicate that positioning based on the learned radio map can achieve good accuracy, especially in hallways or other areas in the environment where the WLAN signal is constrained by obstacles such as walls.