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 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.

Symmetrisk Lupoid onychodystrofi, SLO, beskrevs för första gången på mitten av 90-talet. Sjukdomen karaktäriseras av att alla klor avlossas inom en kort tidsperiod utan att andra samtidiga systemiska fynd ses. Den bakomliggandeorsaken till sjukdomen är ännu inte känd, men eftersom liknande histologiska fynd som vid systemisk lupus erythematosus, SLE och kutan lupus erythematosus, LE, kan identifieras har en autoimmun bakgrund misstänkts.Hörnstenen i SLE-diagnostiken är ANA-test, för att påvisa cirkulerande antinukleära antikroppar. I enstaka studier har man tidigare hos vissa hundar med SLO kunnat påvisa ANA.Syftet med den här studien har varit att göra ANA-test på hundar med symmetrisk kloavlossning och SLO, samt att genom journalstudier beskriva hur sjukdomen ser ut i Sverige idag.Hundar provtagna och testade för ANA är sju bearded collies, fem riesenschnauzer, tre Rhodesian ridgeback och en toypudel samt tolv kontrollhundar av raserna bearded collie, riesenschnauzer och Rhodesian ridgeback. Samtliga hundar var negativa för ANA.

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.

I föreliggande studie har unga flickors attityder till ätande över tid studeras, samt sambandet mellan föräldrars attityder till mat och ätande och deras döttrars attityder. Detta gjordes genom frågeformulären Children´s Eating Attitudes Test (ChEAT) och Eating Attitudes Test (EAT), från IDA-projektet (Identification of Dieting in Adolescent girls) som delades ut i 40 olika skolor i Uppsala län år 1995 samt 2000. Resultatet visade att det var elva procent av 14åringarna som låg i riskzonen (riskbeteende = 16-72 p) för att utveckla ett stört ätbeteende, medan det inte var någon utav nioåringarna som låg i riskzonen (M 9år = 1,88 M 14 år = 4,35p=.001). Inget signifikant samband mellan varken mammans och flickornas ätbeteende eller pappans och flickornas ätbeteende kunde ses. För att problem med ätstörningar hos ungaflickor ska minska tycker författarna att det är viktigt att föräldrar informeras om hur tidigt deras barn blir medvetna om kroppsideal samt matfrågor.

Reading old handwritten documents can be a real challenge for genealogists, especially as some documents in Sweden are written in the old German alphabet that is not used today. Much research has been done on how to enable computers to read old handwritten documents, but computers have so far not reached the level of reading that expert humans have. The focus seems to be on the computers reading the document with or without the help of human experts, with the aim of making the documents available in easily read form. I have, however, not found any research on how computers can help non-expert humans trying to read handwritten documents. In this project I have focused especially on beginning genealogists as reading gets easier with practice, and you need the help more in the beginning. By conducting interviews and observations with genealogists I established that reading is an issue and that there are many factors involved that make it difficult to read.

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 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.

AimThe aim of the study was to develop a method for the survey of play movement demands and temporal patterns in order to enable a descriptive study of the defensive players in American Football. The overall aim was to  improve the understanding of how American Football is played to create opportunities for enhancement of current or developing new training methods to better suit football.MethodFifty plays from a Division 3 college football game on video from 2005 was divided into sequences of action for one player each from the defensive line, linebackers and defensive backs and analyzed with the video analyzing software cSwing. Every players sequence of action was recorded in a spreadsheet and noted on a scaled football field where distances were measured and together with time stamps from cSwing velocity was calculated.ResultsUsing this method it was possible to describe the play movement demands and temporal patterns which was the main task of the study. The defensive end worked on an average 4.61 seconds per play, the distance was 12.4 meters and average speed 2.5 m×s-1. The linebacker worked on an average 4.35 s per play, 13.7 m and at a mean speed of 3.0 m×s-1.