The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

This thesis is closely related to the Dynamically Self-Configuring Automotive System(DySCAS) project. DySCAS is a middleware for electronics in an automotive system. Thethesis work has been performed in cooperation with ENEA. Parts of the demonstrationplatform Self configurable High Availability and Policy based platform for Embeddedsystem (SHAPE) developed for the DySCAS project by ENEA have been used in theimplementation phase of this master thesis.The goal of this thesis was to evaluate how the Meteor MW, an offspring of the DySCASmiddleware, should handle QoS and to design a Quality of Service Manager (QoSM) for theMeteor MW that fulfilled hard real-time requirements. The thesis also had the objectiveof analysing and identifying the requirements on such a QoSM from a QoS perspective.Specifically the requirements to guarantee real-time support for applications running onthe MW.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The amount of information stored on the internet grows daily and naturally the requirements on the systems used to search for and analyse information increases. As a part in meeting the raised requirements this study investigates if it is possible for a automatised text analysis system to distinguish certain groups and categories of words in a text, and more specifically investigate if it is possible to distinguish words with a high information value from words with a low information value. This is important to enable optimizations of systems for global surveillance and information retrieval. The study is carried out using word spaces, which are often used in text analysis to model language. The distributional character of certain categories of words is examined by studying the intrinsic dimensionality of the space, locally around different words.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

The determination of the optical properties of biological tissue is an important issue in laser medicine. The optical properties define the tissue´s absorption and scattering behaviour, and can be expressed by quantities such as the albedo, the optical thickness and the anisotropy coefficient. During this project, a measurement system for the determination of the optical properties was built up. The system consists of a double integrating sphere set-up to perform the necessary reflection and transmission measurements, and a computer algorithm to calculate the optical properties from the measured data. This algorithm is called Inverse Adding Doubling method, and is based on a one-dimensional transport model.

The ability to tackle NP-hard problems has been greatly extended by the introduction of Metaheuristics (see Blum & Roli (2003)) for a summary of most Metaheuristics, general problem-independent optimisation algorithms extending the hill-climbing local search approach to escape local minima. One of these algorithms is Iterated Local Search (ILS) (Lourenco et al., 2002; Stützle, 1999a, p. 25ff), a recent easy to implement but powerful algorithm with results comparable or superior to other state-of-the-art methods for many combinatorial optimisation problems, among them the Traveling Salesman (TSP) and Quadratic Assignment Problem (QAP). ILS iteratively samples local minima by modifying the current local minimum and restartinga local search porcedure on this modified solution. This thesis will show how ILS can be implemented for MSA.

As the volumes are entering the world of computer graphics the pure volume visualisation becomes a more important tool in for example research and medical applications. But the advance in haptics --- force feedback from the computer --- is behind. In volume haptics no equal to the proxy method so popular in surface haptics has yet emerged. Some implementations of volume haptics even use surfaces as intermediate representations so that surface haptics can be used.The intention of this work was to create natural feeling haptic feedback from volumetric density data using pure volume haptics. The haptic algorithm would be implemented in Reachin API for the Reachin Desktop Display, together with other parts to build up a usable volume visualisation environment.To achieve the feeling of stiffness and friction dependent on tissue type, a proxy based method was developed.

Nötcenter Viken is a Swedish nucleus herd for dairy cattle. The goal for the farm is to select suitable mothers for the next top generation of bulls. Today the selection for udder health is based on a pedigree index and phenotype data. The pedigree index is based on the cow?s father and grandfathers breeding values.

This thesis compares the impact on disk performance in a GNU/Linux  environmentwith three encryption algorithms: AES,  Serpent and Twofish in three different implementations: DM-crypt, Loop-AES and Truecrypt. For all three algorithms a key length of 256 bits is used.The thesis shows that the least performance impact during data encryption, and thus file writing, is reached by using AES or Twofish encryption implemented in DM-crypt or TrueCrypt. The thesis shows that some data operations with a sufficiently low processor utilization barely affects disk performance at all if encrypted using the optimal implementation and algorithm.It is also discovered that the performance impact during data decryption, or file reading, can be minimized by using the most efficient implementation and algorithm. The best results are met with the AES or Twofish cipher, regardless of implementation.An important conclusion that  is  drawn is that it is hard to determine a superior encryption solution for all purposes. However, by reviewing and examining the collected data from all aspects of disk performance the AES implementation in TrueCrypt is, with small marginals, determined to be the most optimal..

A report on my thesis developing an algorithm to automatically classify a mammogram image as containing an implant or not and segmenting and masking any present breast implant in the image..