En applikationsinfrastruktur för massutskick av e-post

In today's society it is becoming more and more important with direct marketing. Some of the direct marketing is done through e-mail, in which companies see an easy way to advertise himself. I did this thesis work at WebDoc Systems. They have a product that creates web documents directly in your browser, also called CMS. The CMS has a module for sending mass e-mail, but this module does not function properly and WebDoc Systems customers are dissatisfied with that part of the product. The problem with the module was that sometimes it didn't send the e-mail, and that it was not possible to obtain some form of follow-up information on the e-mail. The goal of this work was to develop a Web service that could easily send e-mail to many receivers, just as easily be able to view statistics on how mailing has gone. The first step was to do a literature review to get a good picture of available programming platforms, but also to be able create a good application infrastructure. The next step was to implement this design and improve it over time by using an iterative development methodology. The result was an application infrastructure that consists of three main parts and a plugin interface. The parts that were implemented were a Web service application, a Web application and a Windows service application. The three elements cooperate with each other and share a database, and plugins.

Computational study of the step size parameter of the subgradient optimization method

The subgradient optimization method is a simple and flexible linear programming iterative algorithm. It is much simpler than Newton's method and can be applied to a wider variety of problems. It also converges when the objective function is non-differentiable. Since an efficient algorithm will not only produce a good solution but also take less computing time, we always prefer a simpler algorithm with high quality. In this study a series of step size parameters in the subgradient equation is studied. The performance is compared for a general piecewise function and a specific p-median problem. We examine how the quality of solution changes by setting five forms of step size parameter.

Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation

This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

How single is ‘single’ : some pragmatic reflections on single versus multifaceted interventions to facilitate implementation

An earlier overview of systematic reviews and a subsequent editorial on single-component versus multifaceted interventions to promote knowledge translation (KT) highlight complex issues in implementation science. In this supplemented commentary, further aspects are in focus; we propose examples from (KT) studies probing the issue of single interventions. A main point is that defining what is a single and what is a multifaceted intervention can be ambiguous, depending on how the intervention is conceived. Further, we suggest additional perspectives in terms of strategies to facilitate implementation. More specifically, we argue for a need to depict not only what activities are done in implementation interventions, but to unpack functions in particular contexts, in order to support the progress of implementation science.