This dissertation deals with dynamics of engineering structures and principally discusses the identification of the modal parameters (i.e., natural frequencies, damping ratios and vibration modes) using output-only information, the excitation sources being considered as unknown and unmeasurable. To solve these kind of problems, a quite large selection of techniques is available in the scientific literature, each of them possessing its own features, advantages and limitations. One common limitation of most of the methods concerns the post-processing procedures that have proved to be delicate and time consuming in some cases, and usually require good users expertise. The constant concern of this work is thus the simplification of the result interpretation in order to minimize the influence of this ungovernable parameter. A new modal parameter estimation approach is developed in this work. The proposed methodology is based on the so-called Blind Source Separation techniques, that aim at reducing large data set to reveal its essential structure. The theoretical developments demonstrate a one-to-one relationship between the so-called mixing matrix and the vibration modes. Two separation algorithms, namely the Independent Component Analysis and the Second-Order Blind Identification, are considered. Their performances are compared, and, due to intrinsic features, one of them is finally identified as more suitable for modal identification problems. For the purpose of comparison, numerous academic case studies are considered to evaluate the influence of parameters such as damping, noise and nondeterministic excitations. Finally, realistic examples dealing with a large number of active modes, typical impact hammer modal testing and operational testing conditions, are studied to demonstrate the applicability of the proposed methodology for practical applications.

Jag har undersökt vilken matematisk kommunikation som förekommer i förskolebarnets bygglek. Jag valde metoden videoinspelning där jag observerade fem olika bygglekssituationer som jag sedan tolkade och analyserade. För att få en större förståelse kring byggmiljön ställde jag också några frågor till pedagoger som ansvarade för konstruktionsverkstaden. Resultatet visade att det konkreta materialet förstärkte översättningsledet från det barnet redan kan (första ordningens språk) till det barnet ännu inte förstår (andra ordningens språk). Pedagogerna kunde med materialets hjälp göra ett matematiskt begrepp konkretare. Barnen kom i kontakt med många olika matematiska begrepp, både jämförelseord, lägesord och ordningstal. Det visade sig att vissa barn inte alla gånger använde rätt terminologi, men barnen hade ändå en gemensam förståelse för varandra. Pedagogerna utmanade, förde dialog och såg till att byggmaterialet var inspirerande, tillgängligt och välsorterat. / I have examined what type of mathematical communication is used by children in their constructional play. I used video recording as a method, and observed five different situations that I later interpreted and analyzed. To get a better understanding of the environment of construction I raised some questions to the teachers responsible for the construction work shop. The result showed that the concrete material enforced the translational link from what the child already knows (language of the first order) to what the child not yet understands (language of the second order). The teachers could use the material to make mathematical concepts more concrete. The children where introduced to many different mathematical concepts, both comparative words, words of position, and ordinal numbers. It turned out that some children where not always using the right terminology, but the children still had a common understanding of each other. The teachers challenged, conducted dialogues, and made sure that the building material was inspiring, available, and well sorted.

The question of whether or not school makes a difference in preparing students for democratic citizenship has been debated for a long time in political science and curriculum studies. These discussions are mostly based on the results of international surveys measuring students’ political attitudes, values and participation. However, we first need to define what kind of prepared citizens are needed. This article takes on the definition issue and presents new perspectives by exploring how teachers in Social Science (Samhällskunskap) and their students in Sweden reason about engagement when they address complex societal issues such as globalisation. Based on interviews with a number of teachers and students I will argue that in order to understand what is going on in school we need to interpret Social Science teaching in terms of first- and second-order concepts, where the second-order concepts could be seen as "how to think like a social scientist". I will make a case that there is a didactic dilemma for teachers trying to educate students who are both trained in disciplinary thinking and leave school as politically engaged. However, this dilemma is not unsolvable and I will hold a position that it might contain answers to some of the questions that political scientists deal with in terms of engagement.

In this dissertation, we introduce a novel text representation method mainly used for text classification purpose. The presented representation method is initially based on a variety of closeness relationships between pairs of words in text passages within the entire corpus. This representation is then used as the basis for our multi-level lightweight ontological representation method (TOR-FUSE), in which documents are represented based on their contexts and the goal of the learning task. The method is unlike the traditional representation methods, in which all the documents are represented solely based on the constituent words of the documents, and are totally isolated from the goal that they are represented for. We believe choosing the correct granularity of representation features is an important aspect of text classification. Interpreting data in a more general dimensional space, with fewer dimensions, can convey more discriminative knowledge and decrease the level of learning perplexity. The multi-level model allows data interpretation in a more conceptual space, rather than only containing scattered words occurring in texts. It aims to perform the extraction of the knowledge tailored for the classification task by automatic creation of a lightweight ontological hierarchy of representations. In the last step, we will train a tailored ensemble learner over a stack of representations at different conceptual granularities. The final result is a mapping and a weighting of the targeted concept of the original learning task, over a stack of representations and granular conceptual elements of its different levels (hierarchical mapping instead of linear mapping over a vector). Finally the entire algorithm is applied to a variety of general text classification tasks, and the performance is evaluated in comparison with well-known algorithms.

Bakgrund: 2010 presenterade SCB en undersökning om hur 403 000 jobb tillsattes (GP 2010). 79 000 av dessa tjänster tillsattes via personliga kontakter och ytterligare 100 000 där arbetsgivaren själv kontaktade den arbetssökande. Denna trend i användandet av det sociala kontaktnätet får stöd av Lena Hensvik, doktorand i nationalekonomi, i tidskriften Framtider (2012). Hon skriver att den sociala omgivningen såsom grannar, skolkamrater, tidigare kollegor och föräldrar har stor betydelse för hur vi får anställning eller inte. Hon menar att kontaktnätet är en viktig självinvestering då vårdandet av ens nätverk uppenbarligen kan underlätta jobbsökandet. Hensvik (2012) fortsätter skriva att det i dagens samhälle inte bara handlar om vem du är utan även vem du känner. Syfte: Tidigare forskning berättar att personliga kontakter är en av de faktorer som ökar anställningsbarheten. Vi vill därför ta vid där tidigare forskning slutar och göra en mer inriktad studie där vi fokuserar på personliga kontakter och kartlägger dess effekt i praktiken. Vi ämnar därför förklara personliga kontakters betydelse i samband med nyanställning av civilekonomer med examen från 2007-2012. Metod: Vi har valt att genomföra vår studie med en kvantitativ undersökningsdesign och ett deduktivt synsätt på relationen teori och forskning. Empiriska data har insamlats genom enkätundersökning. Slutsats: Vår slutsats är att personliga kontakter är användbara för civilekonomer i anställningsprocessen, att kontakterna till 90,4% leder dem till minst intervju och att kontakterna inte nödvändigtvis är de som är definierade som svaga, se Granovetters (1973, 1975) teorier om The Strength of Weak Ties. / Background: In 2010 SCB presented a survey of how 403 000 jobs were added (GP 2010). 79 000 of these were added through social contacts and another 100 000 by the employer himself who contacted the unemployed. This trend of using social contacts in the job-seeking process gets support by Hensvik, doctor in economics. In the magazine Framtider (2012) she writes that the social environment such as neighbours, class mates, former colleagues and parents have a big impact if we get an employment or not. Hensvik (2012) says that the caring of ones contacts is an important self-investment that improves your probabilities of getting an employment. She continues writing that in today’s society it’s not only important who you are but also who you know. Purpose: Previous research tells that social contacts are one of the factors that will improve your probabilities of getting employed. We will continue where previous research tends to end and aim for a more focused study where we measure the effects of using contacts in reality. The purpose of this thesis is to explain the contacts’ importance when employing former students with a Degree of Master of Science in Business and Economics. Method: We have conducted a questionnaire survey that was sent out to eight Swedish universities resulting in 100 responses. Conclusion: We have come to the conclusion that social contacts contribute in the recruitment process of former business students, that the use of contacts in 90,4% will get you far in the job-seeking process and that the helpful contacts are not necessarily the ones defined as weak ties, of which Granovetter (1973, 1975) would have argued.

La mayor parte de los sistemas de comunicaciones requieren el conocimiento previo del canal, el cual se suele estimar a partir de una secuencia de entrenamiento. Sin embargo, la transmisión de símbolos piloto se traduce en una reducción de la eficiencia espectral del sistema, lo que imposibilita que se alcancen los límites predichos por la Teoría de la Información. Este problema ha motivado el desarrollo de un gran número de técnicas para la estima e igualación ciega de canal, es decir, para la obtención del canal o la fuente sin necesidad de transmitir una señal de entrenamiento. Normalmente, estas técnicas se basan en el conocimiento previo de ciertas características de la señal, tales como su pertenencia a un alfabeto finito, o sus estadísticos de orden superior. Sin embargo, en el caso de sistemas de múltiples entradas y salidas (MIMO), se ha demostrado que los estadísticos de segundo orden de las observaciones proporcionan la información suficiente para resolver el problema ciego.El objetivo de esta Tesis consiste en la obtención de nuevas técnicas para la estima e igualación ciega de canales MIMO, tanto en sistemas con redundancia espacial, como en casos más generales en los que las fuentes no presentan ningún tipo particular de estructura. De manera general, los métodos propuestos se basan en los estadísticos de segundo orden de las observaciones. Sin embargo, las técnicas se presentan desde un punto de vista determinista, es decir, los algoritmos propuestos explotan directamente la estructura de las matrices de datos, lo que permite obtener resultados más precisos cuando se dispone de un número reducido de observaciones. Adicionalmente, la reformulación de los criterios propuestos como problemas clásicos del análisis estadístico de señales, ha permitido la obtención de algoritmos adaptativos eficientes para la estima e igualación de canales MIMO. En primer lugar se aborda el caso de sistemas sin redundancia. Más concretamente, se analiza el problema de igualación ciega de canales MIMO selectivos en frecuencia, el cual se reformula como un conjunto de problemas de análisis de correlaciones canónicas (CCA). La solución de los problemas CCA se puede obtener de manera directa mediante un problema de autovalores generalizado. Además, en esta Tesis se presenta un algoritmo adaptativo basado en la reformulación de CCA como un conjunto de problemas de regresión lineal acoplados. De esta manera, se obtienen nuevos algoritmos bloque y adaptativos para la igualación ciega de canales MIMO de una manera sencilla. Finalmente, el método propuesto se basa, como muchas otras técnicas ciegas, en el conocimiento a priori del orden del canal, lo que constituye un problema casi tan complicado como el de la estima o igualación ciega. Así, en el caso de canales de una entrada y varias salidas (SIMO), la combinación de la técnica propuesta con otros métodos para la estima ciega del canal permite obtener un nuevo criterio para extracción del orden de este tipo de canalesEn segundo lugar se considera el problema de estima ciega de canal en sistemas con algún tipo de redundancia o estructura espacial, con especial interés en el caso de sistemas con codificación espacio-temporal por bloques (STBC). Específicamente, se propone una nueva técnica para la estima ciega del canal, cuya complejidad se reduce a la extracción del autovector principal de una matriz de correlación modificada. El principal problema asociado a este tipo de sistemas viene dado por la existencia de ciertas ambigüedades a la hora de estimar el canal. En esta Tesis se plantea el problema de identificabilidad de una manera general, y en el caso de códigos ortogonales (OSTBCs) se presentan varios nuevos teoremas que aseguran la identificabilidad del canal en un gran número de casos. Adicionalmente, se proponen varias técnicas para la resolución de las ambigüedades, tanto en el caso OSTBC como para códigos más generales. En concreto, se introduce el concepto de diversidad de código, que consiste en la combinación de varios códigos STBC. Esta técnica permite resolver las indeterminaciones asociadas a un gran número de problemas, y en su versión más sencilla se reduce a una precodificación no redundante consistente en una simple rotación o permutación de las antenas transmisoras.En definitiva, en esta Tesis se abordan los problemas de estima e igualación ciega de canal en sistemas MIMO, y se presentan varias técnicas ciegas, cuyas prestaciones se evalúan mediante un gran número de ejemplos de simulación. / The majority of communication systems need the previous knowledge of the channel, which is usually estimated by means of a training sequence. However, the transmission of pilot symbols provokes a reduction in bandwidth efficiency, which precludes the system from reaching the limits predicted by the Information Theory. This problem has motivated the development of a large number of blind channel estimation and equalization techniques, which are able to obtain the channel or the source without the need of transmitting a training signal. Usually, these techniques are based on the previous knowledge of certain properties of the signal, such as its belonging to a finite alphabet, or its higher-order statistics. However, in the case of multiple-input multiple-output (MIMO) systems, it has been proven that the second order statistics of the observations provide the sufficient information for solving the blind problem.The aim of this Thesis is the development of new blind MIMO channel estimation and equalization techniques, both in systems with spatial redundancy, and in more general cases where the sources do not have any particular spatial structure. In general, the proposed methods are based on the second order statistics of the observations. However, the techniques are presented from a deterministic point of view, i.e., the proposed algorithms directly exploit the structure of the data matrices, which allows us to obtain more accurate results when only a reduced number of observations is available. Additionally, the reformulation of the proposed criteria as classical statistical signal processing problems is exploited to obtain efficient adaptive algorithms for MIMO channel estimation and equalization.Firstly, we consider the case of systems without spatial redundancy. Specifically, we analyze the problem of blind equalization of frequency selective MIMO channels, which is reformulated as a set of canonical correlation analysis (CCA) problems. The solution of the CCA problems can be obtained by means of a generalized eigenvalue problem. In this Thesis, we present a new adaptive algorithm based on the reformulation of CCA as a set of coupled linear regression problems. Therefore, new batch and adaptive algorithms for blind MIMO channel equalization are easily obtained. Finally, the proposed method, as well as many other blind techniques, is based on the previous knowledge of the channel order, which is a problem nearly as complicated as the blind channel estimation or equalization. Thus, in the case of single-input multiple-output (SIMO) channels, the combination of the proposed technique with other blind channel estimation methods provides a new criterion for the order extraction of this class of channels.Secondly, we consider the problem of blind channel estimation in systems with some kind of redundancy or spatial structure, with special interest in space-time block coded (STBC) systems. Specifically, a new blind channel estimation technique is proposed, whose computational complexity reduces to the extraction of the principal eigenvector of a modified correlation matrix. The main problem in these cases is due to the existence of certain ambiguities associated to the blind channel estimation problem. In this Thesis the general identifiability problem is formulated and, in the case of orthogonal codes (OSTBCs), we present several new theorems which ensure the channel identifiability in a large number of cases. Additionally, several techniques for the resolution of the ambiguities are proposed, both in the OSTBC case as well as for more general codes. In particular, we introduce the concept of code diversity, which consists in the combination of several STBCs. This technique avoids the ambiguities associated to a large number of problems, and in its simplest version it reduces to a non-redundant precoding consisting of a single rotation or permutation of the transmit antennas.In summary, in this Thesis the blind MIMO channel estimation and equalization problems are analyzed, and several blind techniques are presented, whose performance is evaluated by means of a large number of simulation examples.

The research on optimal reinsurance design dated back to the 1960’s. For nearly half a century, the quest for optimal reinsurance designs has remained a fascinating subject, drawing significant interests from both academicians and practitioners. Its fascination lies in its potential as an effective risk management tool for the insurers. There are many ways of formulating the optimal design of reinsurance, depending on the chosen objective and constraints. In this thesis, we address the problem of optimal reinsurance designs from an insurer’s perspective. For an insurer, an appropriate use of the reinsurance helps to reduce the adverse risk exposure and improve the overall viability of the underlying business. On the other hand, reinsurance incurs additional cost to the insurer in the form of reinsurance premium. This implies a classical risk and reward tradeoff faced by the insurer. The primary objective of the thesis is to develop theoretically sound and yet practical solution in the quest for optimal reinsurance designs. In order to achieve such an objective, this thesis is divided into two parts. In the first part, a number of reinsurance models are developed and their optimal reinsurance treaties are derived explicitly. This part focuses on the risk measure minimization reinsurance models and discusses the optimal reinsurance treaties by exploiting two of the most common risk measures known as the Value-at-Risk (VaR) and the Conditional Tail Expectation (CTE). Some additional important economic factors such as the reinsurance premium budget, the insurer’s profitability are also considered. The second part proposes an innovative method in formulating the reinsurance models, which we refer as the empirical approach since it exploits explicitly the insurer’s empirical loss data. The empirical approach has the advantage that it is practical and intuitively appealing. This approach is motivated by the difficulty that the reinsurance models are often infinite dimensional optimization problems and hence the explicit solutions are achievable only in some special cases. The empirical approach effectively reformulates the optimal reinsurance problem into a finite dimensional optimization problem. Furthermore, we demonstrate that the second-order conic programming can be used to obtain the optimal solutions for a wide range of reinsurance models formulated by the empirical approach.

This study focuses on developing structural health monitoring techniques to detect damage in deepwater risers subjected to vortex-induced vibration (VIV), and studying vibration control strategies to extend the service life of offshore structures. Vibration-based damage detection needs both responses from the undamaged and damaged deepwater risers. Because no experimental data for damaged deepwater risers is available, a model to predict the VIV responses of deepwater risers with given conditions is needed, which is the forward problem. In this study, a new three dimensional (3D) analytical model is proposed considering coupled VIV (in-line and cross-flow) for top-tensioned riser (TTR) with wake oscillators. The model is verified by direct numerical simulations and experimental data. The inverse problem is to detect damage using VIV responses from the analytical models with/without damage, where the change between dynamic properties obtained from riser responses represents damage. The inverse problem is performed in two steps: blind identification and damage detection. For blind identification, a wavelet modified second order blind identification (WMSOBI) method and a complex WMSOBI (CWMSOBI) method are proposed to extract modal properties from output only responses for standing and traveling wave vibration, respectively. Numerical simulations and experiments validate the effectiveness of proposed methods. For damage detection, a novel weighted distribution force change (WDFC) index (for standing wave) and a phase angle change (PAC) index (for traveling wave) are proposed and proven numerically. Experiments confirm that WDFC can accurately locate damage and estimate damage severity. Furthermore, a new fatigue damage estimation method involving WMSOBI, S-N curve and Miner's rule is proposed and proven to be effective using field test data. Vibration control is essential to extend the service life and enhance the safety of offshore structures. Literature review shows that semi-active control devices are potentially a good solution. A novel semi-active control strategy is proposed to tune the damper properties to match the dominant frequency of the structural response in real-time. The effectiveness of proposed strategy in vibration reduction for deepwater risers and offshore floating wind turbines is also validated through numerical studies.

The research on optimal reinsurance design dated back to the 1960’s. For nearly half a century, the quest for optimal reinsurance designs has remained a fascinating subject, drawing significant interests from both academicians and practitioners. Its fascination lies in its potential as an effective risk management tool for the insurers. There are many ways of formulating the optimal design of reinsurance, depending on the chosen objective and constraints. In this thesis, we address the problem of optimal reinsurance designs from an insurer’s perspective. For an insurer, an appropriate use of the reinsurance helps to reduce the adverse risk exposure and improve the overall viability of the underlying business. On the other hand, reinsurance incurs additional cost to the insurer in the form of reinsurance premium. This implies a classical risk and reward tradeoff faced by the insurer. The primary objective of the thesis is to develop theoretically sound and yet practical solution in the quest for optimal reinsurance designs. In order to achieve such an objective, this thesis is divided into two parts. In the first part, a number of reinsurance models are developed and their optimal reinsurance treaties are derived explicitly. This part focuses on the risk measure minimization reinsurance models and discusses the optimal reinsurance treaties by exploiting two of the most common risk measures known as the Value-at-Risk (VaR) and the Conditional Tail Expectation (CTE). Some additional important economic factors such as the reinsurance premium budget, the insurer’s profitability are also considered. The second part proposes an innovative method in formulating the reinsurance models, which we refer as the empirical approach since it exploits explicitly the insurer’s empirical loss data. The empirical approach has the advantage that it is practical and intuitively appealing. This approach is motivated by the difficulty that the reinsurance models are often infinite dimensional optimization problems and hence the explicit solutions are achievable only in some special cases. The empirical approach effectively reformulates the optimal reinsurance problem into a finite dimensional optimization problem. Furthermore, we demonstrate that the second-order conic programming can be used to obtain the optimal solutions for a wide range of reinsurance models formulated by the empirical approach.

In recent years, there has been a surge of research interest in the analysis of time series and spatial data. While on one hand more and more sophisticated models are being developed, on the other hand the resulting theory and estimation process has become more and more involved. This dissertation addresses the development of statistical inference procedures for data exhibiting dependencies of varied form and structure. In the first work, we consider estimation of the mean squared prediction error (MSPE) of the best linear predictor of (possibly) nonlinear functions of finitely many future observations in a stationary time series. We develop a resampling methodology for estimating the MSPE when the unknown parameters in the best linear predictor are estimated. Further, we propose a bias corrected MSPE estimator based on the bootstrap and establish its second order accuracy. Finite sample properties of the method are investigated through a simulation study. The next work considers nonparametric inference on spatial data. In this work the asymptotic distribution of the Discrete Fourier Transformation (DFT) of spatial data under pure and mixed increasing domain spatial asymptotic structures are studied under both deterministic and stochastic spatial sampling designs. The deterministic design is specified by a scaled version of the integer lattice in IRd while the data-sites under the stochastic spatial design are generated by a sequence of independent random vectors, with a possibly nonuniform density. A detailed account of the asymptotic joint distribution of the DFTs of the spatial data is given which, among other things, highlights the effects of the geometry of the sampling region and the spatial sampling density on the limit distribution. Further, it is shown that in both deterministic and stochastic design cases, for "asymptotically distant" frequencies, the DFTs are asymptotically independent, but this property may be destroyed if the frequencies are "asymptotically close". Some important implications of the main results are also given.