Exploiting ground-based measurements of the Global Positioning System for numerical weather prediction

Data assimilation provides an initial atmospheric state, called the analysis, for Numerical Weather Prediction (NWP). This analysis consists of pressure, temperature, wind, and humidity on a three-dimensional NWP model grid. Data assimilation blends meteorological observations with the NWP model in a statistically optimal way. The objective of this thesis is to describe methodological development carried out in order to allow data assimilation of ground-based measurements of the Global Positioning System (GPS) into the High Resolution Limited Area Model (HIRLAM) NWP system. Geodetic processing produces observations of tropospheric delay. These observations can be processed either for vertical columns at each GPS receiver station, or for the individual propagation paths of the microwave signals. These alternative processing methods result in Zenith Total Delay (ZTD) and Slant Delay (SD) observations, respectively. ZTD and SD observations are of use in the analysis of atmospheric humidity. A method is introduced for estimation of the horizontal error covariance of ZTD observations. The method makes use of observation minus model background (OmB) sequences of ZTD and conventional observations. It is demonstrated that the ZTD observation error covariance is relatively large in station separations shorter than 200 km, but non-zero covariances also appear at considerably larger station separations. The relatively low density of radiosonde observing stations limits the ability of the proposed estimation method to resolve the shortest length-scales of error covariance. SD observations are shown to contain a statistically significant signal on the asymmetry of the atmospheric humidity field. However, the asymmetric component of SD is found to be nearly always smaller than the standard deviation of the SD observation error. SD observation modelling is described in detail, and other issues relating to SD data assimilation are also discussed. These include the determination of error statistics, the tuning of observation quality control and allowing the taking into account of local observation error correlation. The experiments made show that the data assimilation system is able to retrieve the asymmetric information content of hypothetical SD observations at a single receiver station. Moreover, the impact of real SD observations on humidity analysis is comparable to that of other observing systems.

Precision Measurement of the X(3872) Mass in J/ψπ+π- Decays

We present an analysis of the mass of the X(3872) reconstructed via its decay to J/psi pi+ pi- using 2.4 fb^-1 of integrated luminosity from ppbar collisions at sqrt(s) = 1.96 TeV, collected with the CDF II detector at the Fermilab Tevatron. The possible existence of two nearby mass states is investigated. Within the limits of our experimental resolution the data are consistent with a single state, and having no evidence for two states we set upper limits on the mass difference between two hypothetical states for different assumed ratios of contributions to the observed peak. For equal contributions, the 95% confidence level upper limit on the mass difference is 3.6 MeV/c^2. Under the single-state model the X(3872) mass is measured to be 3871.61 +- 0.16 (stat) +- 0.19 (syst) MeV/c^2, which is the most precise determination to date.

Conditionally One of 'Us' : A Study of Print Media, Minorities and Positioning Practices

This study deals with how ethnic minorities and immigrants are portrayed in the Finnish print media. The study also asks how media users of various ethnocultural backgrounds make sense of these mediated stories. A more general objective is to elucidate negotiations of belonging and positioning practices in an increasingly complex society. The empirical part of the study is based on content analysis and qualitative close reading of 1,782 articles in five newspapers (Hufvudstadsbladet, Vasabladet, Helsingin Sanomat, Iltalehti and Ilta-Sanomat) during various research periods between 1999 and 2007. Four case studies on print media content are followed up by a focus group study involving 33 newspaper readers of Bosnian, Somalian, Russian, and 'native' Finnish backgrounds. The study draws from different academic and intellectual traditions; mainly media and communication studies, sociology and social psychology. The main theoretical framework employed is positioning theory, as developed by Rom Harré and others. Building on this perspective, situational self-positioning, positioning by others, and media positioning are seen as central practices in the negotiation of belonging. In support of contemporary developments in social sciences, some of these negotiations are seen as occurring in a network type of communicative space. In this space, the media form one of the most powerful institutions in constructing, distributing and legitimising values and ideas of who belongs to 'us', and who does not. The notion of positioning always involves an exclusionary potential. This thesis joins scholars who assert that in order to understand inclusionary and exclusionary mechanisms, the theoretical starting point must be a recognition of a decent and non-humiliating society. When key insights are distilled from the five empirical cases and related to the main theories, one of the major arguments put forward is that the media were first and foremost concerned with a minority actor's rightful or unlawful belonging to the Finnish welfare system. However, in some cases persistent stereotypes concerning some immigrant groups' motivation to work, pay taxes and therefore contribute are so strong that a general idea of individualism is forgotten in favour of racialised and stagnated views. Discussants of immigrant background also claim that the positions provided for minority actors in the media are not easy to identify with; categories are too narrow, journalists are biased, the reporting is simplifying and carries labelling potential. Hence, although the will for the communicative space to be more diverse and inclusive exists — and has also in many cases been articulated in charters, acts and codes — the positioning of ethnic minorities and immigrants differs significantly from the ideal.

Vision based indoor positioning in a retail environment

Modern smart phones often come with a significant amount of computational power and an integrated digital camera making them an ideal platform for intelligents assistants. This work is restricted to retail environments, where users could be provided with for example navigational in- structions to desired products or information about special offers within their close proximity. This kind of applications usually require information about the user's current location in the domain environment, which in our case corresponds to a retail store. We propose a vision based positioning approach that recognizes products the user's mobile phone's camera is currently pointing at. The products are related to locations within the store, which enables us to locate the user by pointing the mobile phone's camera to a group of products. The first step of our method is to extract meaningful features from digital images. We use the Scale- Invariant Feature Transform SIFT algorithm, which extracts features that are highly distinctive in the sense that they can be correctly matched against a large database of features from many images. We collect a comprehensive set of images from all meaningful locations within our domain and extract the SIFT features from each of these images. As the SIFT features are of high dimensionality and thus comparing individual features is infeasible, we apply the Bags of Keypoints method which creates a generic representation, visual category, from all features extracted from images taken from a specific location. A category for an unseen image can be deduced by extracting the corresponding SIFT features and by choosing the category that best fits the extracted features. We have applied the proposed method within a Finnish supermarket. We consider grocery shelves as categories which is a sufficient level of accuracy to help users navigate or to provide useful information about nearby products. We achieve a 40% accuracy which is quite low for commercial applications while significantly outperforming the random guess baseline. Our results suggest that the accuracy of the classification could be increased with a deeper analysis on the domain and by combining existing positioning methods with ours.

High-precision diode-laser-based temperature measurement for air refractive index compensation

We present a laser-based system to measure the refractive index of air over a long path length. In optical distance measurements it is essential to know the refractive index of air with high accuracy. Commonly, the refractive index of air is calculated from the properties of the ambient air using either Ciddor or Edlén equations, where the dominant uncertainty component is in most cases the air temperature. The method developed in this work utilises direct absorption spectroscopy of oxygen to measure the average temperature of air and of water vapor to measure relative humidity. The method allows measurement of temperature and humidity over the same beam path as in optical distance measurement, providing spatially well matching data. Indoor and outdoor measurements demonstrate the effectiveness of the method. In particular, we demonstrate an effective compensation of the refractive index of air in an interferometric length measurement at a time-variant and spatially non-homogenous temperature over a long time period. Further, we were able to demonstrate 7 mK RMS noise over a 67 m path length using 120 s sample time. To our knowledge, this is the best temperature precision reported for a spectroscopic temperature measurement.