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Artificial neural networks have been used to solve different problems, one being survival analysis of medical data. For survival analysis, the main interest is often how samples become sorted by their outputs, which makes survival analysis a rank based problem. A rank based error function lacks a gradient, which makes gradient descent based training difficult. A genetic training algorithm, based o

This is a bachelor thesis bent on introducing the field of exoplanet research. It primarily includes descriptions of the various detection methods, with some detail into how the methods yield parameter estimates by means of least-squares algorithms. The feasibility of combining state-of-the-art astrometric capabilities of Gaia and radial velocity measurements from ground level is briefly discussed

This bachelor thesis contains an introduction into supersymmetric quantum mechanics(SUSYQM). SUSYQM provides a different way of solving quantum mechanical problems. The thesis explains the basic concepts of SUSYQM, such as the factorization of a Hamiltonian, the definition of its superpotential and the shape invariant potentials. The SUSYQM framework was applied to some problems such as the infini

An analysis of two-particle angular correlations was recently performed on measurements taken from pp collisions at $\sqrt{s}$ = 7 TeV by ALICE at the LHC. The correlations for mesons are in good agreement with simulations performed in Monte Carlo event generators such as PYTHIA and PHOJET, but there is a significant difference for baryons. We here investigate particle production mechanisms in PYT

We take a look at the properties of scalar fields in anti--de--Sitter space in five dimensions. More specifically we define bulk--to--boundary and bulk--to--bulk propagators for a five--dimensional scalar field and use these to calculate four--point functions. Finally we take a look at two--point functions and three--point functions and numerically calculate masses, residues and decay constants fo

Popular Abstract in English In the past decade, mobile wireless communication have had a tremendous impact on the way people perceive and use mobile devices, most popularly the mobile phone. Apart from making phone calls, they are capable of being cameras to take pictures and videos, able to browse the Internet, do video calling and much more just like an yesteryear computer. The wireless medium iThe demand for spectrum resources in cellular systems worldwide has seen a tremendous escalation in the recent past. The mobile phones of today are capable of being cameras taking pictures and videos, able to browse the Internet, do video calling and much more than an yesteryear computer. Due to the variety and the amount of information that is being transmitted the demand for spectrum resources i

In this Master thesis we extend the Standard Model with an additional $U(1)$ gauge group and an additional Higgs doublet with a lepton specific $\mathbb{Z}_2$ symmetry. This is used in a gauged version of the Froggatt-Nielsen mechanism to describe the observed masses and mixings among fermions. To reproduce these observables and satisfy the anomaly constraints posed by the new gauge symmetry metho

The Schwarzschild metric and the Kerr metric describe the gravitational fields around static and rotating black holes, respectively. Here, we derive the Kerr metric in a simpler way than how it was derived originally and determine the stability of the Schwarzschild metric. The Kerr metric was derived by using the Einstein-Hilbert action as well as directly from the Einstein field equations. In ord

In the use of articial neural networks (ANN) for real-life applications there is a need for determining the importance of each input variable for the decisions of the articial neural network. By comparing more complex ANN:s with the simple perceptron, a basic method to determine some form of importance is found. This is tested on three dierent datasets of which one is based on a real life dataset

The purpose of this thesis is to explore how individuals perceive a personal brand online on social media, compared to how it is perceived offline in real life, and whether there is a difference in the perception of the personal brand. By using Instagram as an empirical context, this thesis explores similarities and differences in the perceptions of a personal brand from a perspective of ordinary

We present a generalisation of the flavour-ordering method applied to the chiral nonlinear sigma model with any number of flavours. We use an extended Lagrangian with terms containing any number of derivatives, organised in a power-counting hierarchy. The method allows diagrammatic computations at tree-level with any number of legs at any order in the power-counting. Using an automated implementat

Direct coupling analysis (DCA) models correlations in sets of related (homologous) protein sequences using a Potts-like spin model ansatz. From the couplings of the Potts model, derived by inverse statistical mechanics, residue-pair contacts in the 3D structure of the protein are predicted. In this thesis, this approach is applied to structures from the HP model on a square lattice. All HP sequenc

This paper proposes and investigates a Bayesian relation between optimal L2 regularization strengths and the number of training patterns and hidden nodes used for an artificial neural network. The results support the proposed dependence for number of training patterns, while the dependence on hidden architecture was less clear. Finally, applying different regularization strengths on different laye

We simulate the velocities of formed Black Holes to determine the fraction of retained Black Holes in 152 Globular Clusters. The model we used for the escape velocity is from Plummer. The scenarios of the natal kick are Neutronstar like kicks and momentum conserving kicks. We also consider the binary fraction which affect the retention of Black Holes. A typical Globular Cluster retains 0 or 102 Bl