A key distinction between today's and tomorrow's wireless networks is the appetite for reliability to enable emerging mission-critical services such as ultra-reliable low-latency communication (URLLC) and hyper-reliable low-latency communication (HRLLC), the staple mission-critical services in IMT-2020 (5G) and IMT-2023 (6G), for which reliable and resilient communication is a must. However, achieving ultra-reliable communication is challenging because of these services' stringent reliability and latency requirements and the stochastic nature of wireless networks. A natural way of increasing reliability and reducing latency is to provision additional network resources to compensate for uncertainty in wireless networks caused by fading, interference, mobility, and time-varying network load, among others. Thus, an important step to enable mission-critical services is to identify and quantify what it takes to support ultra-reliable communication in mobile networks -- a process often referred to as dimensioning. This dissertation focuses on resource dimensioning, notably spectrum, for ultra-reliable wireless communication. This dissertation proposes a set of methods for spectrum dimensioning based on concepts from risk analysis, extreme value theory, and meta distributions. These methods reveal that each ``nine'' in reliability (e.g., five-nines in 99.999%) roughly translates into an order of magnitude increase in the required bandwidth. In ultra-reliability regimes, the required bandwidth can be in the order of tens of gigahertz, far beyond what is typically available in today's networks, making it challenging to provision resources for ultra-reliable communication. Accordingly, this dissertation also investigates alternative approaches to provide resources to enable ultra-reliable communication services in mobile networks. Particularly, this dissertation considers multi-operator network sharing and multi-connectivity as alternatives to make additional network resources available to enhance network reliability and proposes multi-operator connectivity sharing, which combines multi-operator network sharing with multi-connectivity. Our studies, based on simulations, real-world data analysis, and mathematical models, suggest that multi-operator connectivity sharing -- in which mobiles multi-connect to base stations of operators in a sharing arrangement -- can reduce the required bandwidth significantly because underlying operators tend to exhibit characteristics attractive to reliability, such as complementary coverage during periods of impaired connectivity, facilitating the support for ultra-reliable communication in future mobile networks. / Doctor of Philosophy / A key distinction between today's and tomorrow's wireless networks is the appetite for reliability to enable emerging mission-critical services in 5G and 6G, for which ultra-reliable communication is a must. However, achieving ultra-reliable communication is challenging because of these services' stringent reliability and latency requirements and the stochastic nature of wireless networks. Reliability often comes at the cost of additional network resources to compensate for uncertainty in wireless networks. Thus, an important step to enable ultra-reliable communication is to identify and quantify what it takes to support mission-critical services in mobile networks -- a process often denoted as dimensioning. This dissertation focuses on spectrum dimensioning and proposes a set of methods to identify suitable spectrum bands and required bandwidth for ultra-reliable communication. These methods reveal that the spectrum needs for ultra-reliable communication can be beyond what is typically available in today's networks, making it challenging to provide adequate resources to support ultra-reliable communication services in mobile networks. Alternatively, we propose multi-operator connectivity sharing: mobiles simultaneously connect to multiple base stations of different operators. Our studies suggest that multi-operator connectivity sharing can reduce the spectrum needs in ultra-reliability regimes significantly, being an attractive alternative to enable ultra-reliable communication in future mobile networks.

This cumulative dissertation includes four peer-reviewed and published articles. It evaluates three open-access radar quantitative precipitation estimate (QPE) products from the German Weather Service (DWD) with different temporal resolutions. The improved length and quality of the DWD’s radar QPE products allows a detailed assessment of existing statistical precipitation characteristics and scaling laws, which are established on the basis of traditional point measurements only. The focus of the thesis is on heavy to extreme rainfall and scaling characteristics in time and space. The first publication is a comprehensive assessment of spatio-temporal heavy rainfall pattern in context of urban rainfall modification. The analysis identifies storm alteration by the city of Berlin using the RADOLAN-RW product, suitable for event analysis. Six storm categories were identified and newly introduced tools, such as the amplification factor helped to quantify the changes. The second and third publications focus on the re-evaluation of point-based findings from literature. The first compares depth-duration relationships based on 400,000+ grid cells within Germany for durations of 10 min to 3 days based on 16 years of RADKLIM-YW (5 min and 1 km spatio-temporal resolution) with a well-established global rainfall maxima curve. The German regional curve showed a 'three-phase-regime', governed by the temporal structure of very few extreme rainfall events. Three groups of curve characteristics for single grid cells were identified, based on the rainstorms that had occurred at the individual location. The third article shows the significance of using moving time interval maxima (M-Maxima) over fixed maxima (F-Maxima) and also helps to describe the probabilistic nature of the distribution of potential correction factors, in this case the Sampling Adjustment Factor (SAF), more accurately. It uses both RADKLIM products in order to compare different base resolutions and its effects on the results. Findings add new insights into the importance of identifying good correction factors and also consider the distribution of them instead of using average factors as usually done in practice. The fourth publication studies a new method to extrapolate extreme rainfall to sub-pixel scale via a simple scaling approach, based on 19 years of RADKLIM-RW (hourly and 1 km spatio-temporal resolution) and four regions within Germany of each 256 km x 256 km. Almost smooth power laws were observed when looking at the depth-area-relationships, depending on the considered data length and regions. Closer to the resolution of the radar data (1x1 km²), other influencing factors lead to a shift in rainfall characteristics and thus a bend of the relationship. The two rainfall classes of more convective and more advective characteristics generally had a strong influence on all results of the thesis and are highly dependent on the temporal resolution of the data. The gridded radar QPE data helped to reveal characteristics such as the correlation of small areas with high rain rates (connected to convective pattern) and larger areas with lower rain rates (connected to advective pattern). The analysed radar QPE products are suitable for analysing spatial and temporal rainfall pattern. However, for extreme values, uncertainty remains, since it is not clear if very extreme values are outliers or 'true' observations. / Diese kumulative Dissertation umfasst vier begutachtete und veröffentlichte Artikel. Sie wertet drei frei zugängliche Radarkomposite (QPE) des Deutschen Wetterdienstes (DWD) mit unterschiedlichen zeitlichen Auflösungen aus. Die verbesserte Länge und Qualität dieser Produkte ermöglicht eine detaillierte Bewertung vorhandener Niederschlagscharakteristika, die auf Punktmessungen beruhen. Der Schwerpunkt der Arbeit liegt dabei auf Stark- bis Extremniederschlägen und deren Skalierungseigenschaften. Die erste Veröffentlichung ist eine umfassende Bewertung der raum-zeitlichen Starkregenmuster im Kontext der städtischen Niederschlagsmodifikation. Die Analyse identifiziert den Einfluss der Stadt Berlins auf Starkregenereignisse unter Verwendung des RADOLAN-RW-Produkts. Sechs Kategorien von Niederschlagsmodifikationen wurden identifiziert und neu eingeführte Werkzeuge, wie der Verstärkungsfaktor, halfen bei der Quantifizierung der Veränderungen. Die zweite und dritte Publikationen konzentrieren sich auf die Neubewertung von punktbasierten Erkenntnissen aus der Literatur. Erstere vergleicht Niederschlags-Dauer-Beziehungen auf der Basis von mehr als 400.000 Rasterzellen innerhalb Deutschlands für Dauern von 10 min bis 3 Tagen auf der Grundlage von 16 Jahren RADKLIM-YW (5 min und 1 km räumlich-zeitliche Auflösung) mit einer bekannten globalen Niederschlagsmaximumkurve. Die regionale Kurve in Deutschland zeigte ein 'Drei-Phasen-Regime', das durch die zeitliche Struktur von sehr wenigen extremen Niederschlagsereignissen bestimmt wird. Es wurden drei Gruppen von Kurvencharakteristika für einzelne Gitterzellen identifiziert, die auf den am jeweiligen Standort aufgetretenen Regenfällen basieren. Zweitere zeigt die Bedeutung der Verwendung von gleitenden (M-Maxima) gegenüber festen Niederschlagsmaxima (F-Maxima) und hilft dabei, die probabilistische Natur der Verteilung potenzieller Korrekturfaktoren, in unserem Fall des 'Sampling Adjustment Factor' (SAF), genauer zu beschreiben. Es wurden beide RADKLIM-Produkte verwendet, um verschiedene Basisauflösungen und ihre Auswirkungen auf die Ergebnisse zu vergleichen. Die Ergebnisse liefern neue Erkenntnisse darüber, wie wichtig es ist, gute Korrekturfaktoren zu ermitteln und auch deren Verteilung zu berücksichtigen, anstatt wie in der Praxis üblich Durchschnittsfaktoren zu verwenden. Die vierte Veröffentlichung untersucht eine neue Methode zur Extrapolation extremer Niederschläge mittels eines einfachen Skalierungsansatzes, basierend auf 19 Jahren RADKLIM-RW (stündliche und 1 km räumlich-zeitliche Auflösung) und vier Regionen in Deutschland mit jeweils 256 km x 256 km. Es wurden nahezu perfekte Potenzgesetze in der Beziehung von Niederschlag und Fläche beobachtet, abhängig von der betrachteten Datenlänge und den Regionen. Nahe an der Auflösung des Radars (1x1 km²) knicken die Beziehungen ab, was auf eine Veränderung der Niederschlagscharakteristika hinweist. Die beiden Niederschlagsklassen mit eher konvektiven und eher advektiven Eigenschaften hatten generell einen starken Einfluss auf alle Ergebnisse der Arbeit und sind stark von der zeitlichen Auflösung der Daten abhängig. Die Radarkomposite halfen dabei, Merkmale wie die Korrelation von kleinen Gebieten mit hohen Niederschlagsmengen (verbunden mit konvektiven Mustern) und größeren Gebieten mit niedrigeren Niederschlagsmengen (verbunden mit advektiven Mustern) aufzuzeigen. Die analysierten Radarkomposite sind für die Analyse räumlicher und zeitlicher Niederschlagsmuster geeignet. Bei Extremwerten bleibt jedoch eine gewisse Unsicherheit, da nicht klar ist, ob es sich bei sehr extremen Werten um Ausreißer oder 'echte' Beobachtungen handelt.

3D scene understanding is an important problem that has experienced great progress in recent years, in large part due to the development of state-of-the-art methods for 3D object detection. However, the performance of 3D object detectors can suffer in scenarios where extreme occlusion of objects is present, or the number of object classes is large. In this paper, we study the problem of inferring 3D counts from densely packed scenes with heterogeneous objects. This problem has applications to important tasks such as inventory management or automatic crop yield estimation. We propose a novel regression-based method, CountNet3D, that uses mature 2D object detectors for finegrained classi- fication and localization, and a PointNet backbone for geo- metric embedding. The network processes fused data from images and point clouds for end-to-end learning of counts. We perform experiments on a novel synthetic dataset for inventory management in retail, which we construct and make publicly available to the community. We also have a proprietary dataset we've collected of real-world scenes. In addition we run experiments to quantify the uncertainty of the models and evaluate the confidence of our predic- tions. Our results show that regression-based 3D counting methods systematically outperform detection-based meth- ods, and reveal that directly learning from raw point clouds greatly assists count estimation under extreme occlusion.

The advancement of laboratory based Extreme Ultraviolet (EUV) radiation has escalated with the desire to use EUV as a source for semiconductor device printing. Laser plasmas based on a mass-limited target concept, developed within the Laser Plasma Laboratory demonstrate a much needed versatility for satisfying rigorous source requirements. This concept produces minimal debris concerns and allows for the attainment of high repetition rates as well as the accommodation of various laser and target configurations. This work demonstrates the generation of EUV radiation by creating laser plasmas from mass-limited targets with indium, tin, and antimony doped droplets. Spectral emission from the laser plasmas is quantified using a flat-field spectrometer. COWAN code oscillator strength predications for each of the dopants were convolved with narrow Gaussian functions creating synthetic spectra for the EUV region between 10 nm - 20 nm. A preliminary comparison was made between the theoretical spectra and experimental results. From this comparison, ion stage transitions for each of the hot dense plasmas generated were assessed.

The study of race relations in England developed in the modern era amongst conflict between races, political parties and local communities. England, consisting of a predominantly white population, is an interesting case of race relations in that immigrants of color seem to be in the center of many of the most controversial conflicts of the past century. Existing research on race relations in England suggests that the region is largely racist due to the conflicts of the past and the current political success of the anti-immigrant extreme right-wing parties (ERPs). But the times at which these parties have been successful compared with high levels of animosity towards non-white immigrant groups have not been thoroughly studied in the past decade. This research will attempt to answer questions regarding racial hostility and ERP success. Do ERPs receive support from purely racist groups during times of high levels of immigration? Or is their racist rhetoric cloaked by logical justification for anti-immigrant policies? ERPs such as the British National Party and The National Front have risen, fallen, evolved and dissolved since the 1960s. They have, in some cases, worked together to gain votes, but eventually break apart to form small, non-political factions that concentrate on social protests. Most recently, England has seen the decline of these particular ERPs, although anti-immigrant social groups still remain strong. Those that were associated with recently dissolved ERPs may turn their attention United Kingdom Independence Party (UKIP), a party that has a message similar to the BNP, but has a more consistent and attractive political platform. UKIP is an anti-immigrant party and its current success is an interesting case study in this thesis.

This study investigates the relationship between the current migration crisis in Europe and the escalation of far-right voting which has been witnessed since it's beginning. In order to do so this study utilized correlation experiments and detailed case studies to explore the relationship between legislative vote shares and asylum applications for the years 2009-2017 in the EU member states of Hungary, Germany, France, Greece and the UK. Control variables of GDP, unemployment and terrorist attacks have also been utilized to measure alternative causes of far-right voting. Results of these experiments vary quite a bit from state to state - finding differing potential causal factors in each case study. Germany, France and the UK show results which indicate that an increase in asylum applications potentially influence far-right voting habits. Greece does not show this type of result, but does show correlation with control variables. Hungarian experiments however do not produce correlation with any variables tested, but has the strongest presence of far-right activity which may indicate that Hungarian far-right success is attributed to their long history of far-right activity.

The ‘extreme female brain’ (EFB) is derived from the empathising - systemising theory (E-S) which hypothesises that sex differences in cognition exist on a continuum, based on abilities in ‘empathising’ and ‘systemising’ (Baron-Cohen, 2003). The EFB profile; extreme empathising alongside deficient systemising, has received little attention in social cognitive neuroscience research, compared to the extreme male brain, which has advanced the knowledge of sex differences in the expression of autism. Currently, there is no solid evidence of a clinical pathology relating to the EFB nor a marker of cognition associated with a person’s ‘place’ on the E-S continuum. Here, an episodic memory paradigm with social and non-social conditions was given to participants along with measures of empathising and systemising. Scores on the social condition predicted where a person lies on the E-S continuum. The thesis then investigated the hypothesis that schizophrenia is expressed in the feminised profile (Badcock & Crepsi, 2006) and the presumption that empathising and systemising demonstrate a tradeoff. Elements of paranoia were associated with an empathising bias. However, a bias in systemising ability was associated with schizotypy along with a significant overlap in the expression of autistic traits and schizotypy. Therefore, schizophrenia as a whole is unlikely to be the pathology seen in the EFB, rather, the positive symptoms of schizophrenia. A trade-off between empathising and systemising was seen but only in participants over 36 years. These results have significant implications for assessment and treatment of neuropsychological disorders and provide more specific details on the potential EFB pathology. ii

No description available.

No description available.

No description available.