>Magister Scientiae - MSc / In Monte Carlo path simulations, which are used extensively in computational -finance, one is interested in the expected value of a quantity which is a functional of the solution to a stochastic differential equation [M.B. Giles, Multilevel Monte Carlo Path Simulation: Operations Research, 56(3) (2008) 607-617] where we have a scalar function with a uniform Lipschitz bound. Normally, we discretise the stochastic differential equation numerically. The simplest estimate for this expected value is the mean of the payoff (the value of an option at the terminal period) values from N independent path simulations. The multilevel Monte Carlo path simulation method recently introduced by Giles exploits strong convergence properties to improve the computational complexity by combining simulations with different levels of resolution. This new method improves on the computational complexity of the standard Monte Carlo approach by considering Monte Carlo simulations with a geometric sequence of different time steps following the approach of Kebaier [A. Kebaier, Statistical Romberg extrapolation: A new variance reduction method and applications to options pricing. Annals of Applied Probability 14(4) (2005) 2681- 2705]. The multilevel method makes computation easy as it estimates each of the terms of the estimate independently (as opposed to the Monte Carlo method) such that the computational complexity of Monte Carlo path simulations is minimised. In this thesis, we investigate this method in pricing path-dependent options and the computation of option price sensitivities also known as Greeks.

Analysis of time series data constitutes an important activity in many scientific disciplines. Over the last years there has been an increase in the collection of time series data in all scientific fields and disciplines, such as the industry and engineering. Due to the increasing size of the time series datasets, new automated time series data mining techniques have been devised for comparing time series data and present information in a logical and easily comprehensible structure.In systems biology in particular, time series are used to the study biological systems. The time series representations of a systems’ dynamics behaviour are multivariate time series. Time series are considered multivariate when they contain observations for more than one variable component. The biological systems’ dynamics time series contain observations for every feature component that is included in the system; they thus are multivariate time series. Recently, there has been an increasing interest in the collection of biological time series. It would therefore be beneficial for systems biologist to be able to compare these multivariate time series.Over the last decade, the field of time series analysis has attracted the attention of people from different scientific disciplines. A number of researchers from the data mining community focus their efforts on providing solutions on numerous problems regarding different time series data mining tasks. Different methods have been proposed for instance, for comparing, indexing and clustering, of univariate time series. Furthermore, different methods have been proposed for creating abstract representations of time series data and investigating the benefits of using these representations for data mining tasks.The introduction of more advanced computing resources facilitated the collection of multivariate time series, which has become common practise in various scientific fields. The increasing number of multivariate time series data triggered the demand for methods to compare them. A small number of well-suited methods have been proposed for comparing these multivariate time series data.All the currently available methods for multivariate time series comparison are more than adequate for comparing multivariate time series with the same dimensionality. However, they all suffer the same drawback. Current techniques cannot process multivariate time series with different dimensions. A proposed solution for comparing multivariate time series with arbitrary dimensions requires the creation of weighted averages. However, the accumulation of weights data is not always feasible.In this project, a new method is proposed which enables the comparison of multivariate time series with arbitrary dimensions. The particular method is evaluated on multivariate time series from different disciplines in order to test the methods’ applicability on data from different fields of science and industry. Lastly, the newly formed method is applied to perform different time series data mining analyses on a set of biological data.

This thesis reviewed various heavy tailed distributions and Extreme Value Theory (EVT) to estimate the catastrophic losses simulated from Florida Public Hurricane Loss Projection Model (FPHLPM). We have compared risk measures such as Probable Maximum Loss (PML) and Tail Value at Risk (TVaR) of the selected distributions with empirical estimation to capture the characteristics of the loss data as well as its tail distribution. Generalized Pareto Distribution (GPD) is the main focus for modeling the tail losses in this application. We found that the hurricane loss data generated from FPHLPM were consistent with historical losses and were not as heavy as expected. The tail of the stochastic annual maximum losses can be explained by an exponential distribution. This thesis also touched on the philosophical implication of small probability, high impact events such as Black Swan and discussed the limitations of quantifying catastrophic losses for future inference using statistical methods.

Coworkers can play an important role in helping each other overcome stressful circumstances (Beehr, Jex, Stacy, & Murray, 2000; LaRocco & Jones, 1978; Viswesvaran, Sanchez, & Fisher, 1999), yet work-family researchers have paid significantly less attention to coworker-provided support than they have to supervisor-provided support (Kossek, Pichler, Bodner, & Hammer, 2011). This thesis contributes to the occupational health literature by providing empirical evidence of the benefits of a novel construct termed work-family supportive coworker behavior (WFSCB) – defined as any supportive action that a coworker can take to contribute to the improved management of an individual’s work and family role demands. A phenomenological qualitative investigation revealed five categories of WFSCB that were tested using three quantitative samples to develop and validate a multidimensional measure. The findings indicated that four dimensions of behavior best reflect WFSCB including: 1) emotional support, 2) facilitating work adjustments, 3) sharing resources and knowledge, and 4) proactively developing solutions. In testing the criterion-related validity of the new measure, this research provides evidence of the positive relationship between these behaviors and various work-family outcomes, as higher levels of WFSCB were associated with lower levels of work-to-family conflict, and higher levels of work-family balance, work-family positive spillover, and overall life satisfaction. In addition, the utility of WFSCB as a source of informal workplace support was underscored based on evidence of its incremental validity in the prediction of these same outcome variables over and above a measure of general coworker support (i.e., emotional and instrumental support). Practically, these findings suggest that general measures of coworker support may fall short in assessing a broad spectrum of supportive coworker behaviors that can significantly contribute to improved work-family outcomes. Overall, the results of this research program will place scholars in a better position to provide prescriptive advice to organizations and employees on the behaviors that they can engage in towards one another to promote improved work-family integration for individuals and more broadly, to contribute to a work-family supportive organizational climate.

L'utilisation d'images de modalités différentes est très répandue dans la résolution de problèmes liés aux applications de la télédétection. La raison principale est que chaque image d'une certaine modalité contient des informations spécifiques qui peuvent être intégrées en un modèle unique, afin d'améliorer notre connaissance à propos d'une scène spécifique. A cause du grand volume de données disponibles, ces intégrations doivent être réalisées de manière automatique. Cependant, un problème apparaît dès les premiers stades du processus : la recherche, dans des images de modalités différentes, de régions en correspondance. Ce problème est difficile à résoudre car la décision de regrouper des régions doit nécessairement reposer sur la part d'information commune aux images, même si les modalités sont différentes. Dans cette thèse, nous nous proposons donc d'apporter une contribution à la résolution de ce problème / The use of several images of various modalities has been proved to be quite useful for solving problems arising in many different applications of remote sensing. The main reason is that each image of a given modality conveys its own part of specific information, which can be integrated into a single model in order to improve our knowledge on a given area. With the large amount of available data, any task of integration must be performed automatically. At the very first stage of an automated integration process, a rather direct problem arises : given a region of interest within a first image, the question is to find out its equivalent within a second image acquired over the same scene but with a different modality. This problem is difficult because the decision to match two regions must rely on the common part of information supported by the two images, even if their modalities are quite different. This is the problem that we wish to address in this thesis

The Banach spaces L(X, Y), K(X, Y), Lw*(X*, Y), and Kw*(X*, Y) are studied to determine when they contain the classical Banach spaces co or l ∞. The complementation of the Banach space K(X, Y) in L(X, Y) is discussed as well as what impact this complementation has on the embedding of co or l∞ in K(X, Y) or L(X, Y). Results concerning the complementation of the Banach space Kw*(X*, Y) in Lw*(X*, Y) are also explored and how that complementation affects the embedding of co or l ∞ in Kw*(X*, Y) or Lw*(X*, Y). The l p spaces for 1 ≤ p < ∞ are studied to determine when the space of compact operators from one l p space to another contains co. The paper contains a new result which classifies these spaces of operators. Results of Kalton, Feder, and Emmanuele concerning the complementation of K(X, Y) in L(X, Y) are generalized. A new result using vector measures is given to provide more efficient proofs of theorems by Kalton, Feder, Emmanuele, Emmanuele and John, and Bator and Lewis as well as a new proof of the fact that l ∞ is prime.

Measuring Biodiversity is an important phenomenon to serve best to our ecology and also keep environment sound. Variety of life on different levels, like an ecosystem, life forms on a site, landscape collectively known as Biodiversity. Species richness and evenness combine measures as Biodiversity. Separate formula, index, equation are widely using to measure Biodiversity in each level. Swedish Environmental Protection Agency aimed to establish an index that consists of landscape functionality and landscape heterogeneity. For landscape functionality assessment, there BBCI (Biotope biodiversity Capacity index) is going to use. High BBCI indicates a high biodiversity for each biotope. However, empirically estimate species richness how much matched with BBCI that not been evaluated. The aim of this paper to see the relationship between empirical estimated Biodiversity and BBCI. A relationship between Shannon diversity index and BBCI also ran to see the matches between them. Collect the empirical data from selected 15 landscapes using Artportalen.se and sort the data for further calculation. Results showed that there was a strong positive relationship between empirical estimated Biodiversity and BBCI. Again Shannon diversity index and BBCI also demonstrated a positive correlation between them. It showed BBCI could explain 60%-69% of species richness data and 17%-22% of Shannon diversity index. It indicates the acceptance of theoretical study of measure Biodiversity.

The gun barrel is one of the most important parts of the whole artillery system. During firing, the wear leads to reduced performance and availability. Wear in gun barrels has different types of erosion mechanisms, in particular chemical-, thermal- and mechanical erosion. This takes place in the internal ballistic process when the projectile is fired from the gun barrel and it will affect the external ballistic parameters. Therefore, an equipment is needed to monitor and measure the wear inside different calibre gun barrels. Wear in gun barrels takes place under extreme conditions during firing due tohigh gas pressures and high temperatures arise as propellant burns. The present thesis aims to develop a type of measuring equipment that should be able to measure and monitor wear inside gun barrels between the diameter ranges of A-C mm. In this master thesis, the product development process has been adapted in order to reach the following goal which is to accomplish a technical solution for the problem associated with wear in gun barrels. The product development process is a systematical approach of developing new products. The different steps that have been evaluated are the product specification, generation of concepts, selection of concepts and layout- and detail design. Before these steps where performed, a project plan was done in order to organize the project. This was then followed by a literature review to obtain information about the problems in the project and to find inspiration from similar applications. The results of the product development process led to a concept of a moveable measure-head which uses a crawler to move inside the gun barrel and adapters to be able to use inside different calibre gun barrels. Then a rotating 3D-laser scanner to measure the change in diameter of the bore. A laser distance sensor and a receiver in order to measure the straightness and to be able to know the position of the moving measure-head in the gun barrel. At last, a wireless camera to monitor the wear inside the gun barrel. The selected concept has been developed and potential solutions for the problem have been described and formed. For the next phase of the project, the concept needs to be developed into a complete model. The next phase of the project is the prototype testing phase.

In this study I examine the joint effect of explanations and monetary incentives on employees' effort allocation decisions in a multi-action setting. A rich literature in economics indicates that monetary incentives substantially influence employees' decisions. This literature demonstrates that the size of the incentive for a given performance measure should consider the measure's sensitivity, congruence and precision. Research in psychology demonstrates the decision influencing effects of explanations (a non-monetary factor) on employees' decisions through perceptions of fairness. I expect that effort allocation decisions are influenced both by explanations and monetary incentives: I hypothesize that providing reasonable and complete explanations substantively alter agents' action choices relative to a setting with monetary incentives alone. Using student subjects in experiments, I find that monetary incentives matter. Moreover, for sizeable monetary incentives, providing a detailed explanation modifies behavior favorably relative to when an unclear explanation is provided. However, for all of the considered monetary incentives, merely requesting a desired course of action is also enough to modify behavior favorably. This study contributes to the accounting literature by providing evidence of a decision influencing benefit associated with the use of explanations such as causal maps employed by firms adopting the balanced scorecard. This study also contributes to the organizational justice literature by providing evidence regarding the interaction effect of multiple antecedents of justice.

This thesis is focused to design and implementation of wireless weather station. The first part deals with possibilities of measurement in meteorology. The next part of thesis includes the choice of suitable sensors and conception of device. The next part of thesis contains design of the schematic of outdoor station and control unit. The last chapter is focused to testing accuracy and measuring basic parameters of disigned conception.