Koulutuksellisen syrjäytymisriskin ennustettavuus yhteishakuvalintojen kautta tarkasteltuna : koulupudokkuusriskin yhteys oppilaan kognitiiviseen kompetenssiin, koulumenestykseen sekä itseä ja vanhempia koskeviin uskomuksiin

The objective of this study was to find factors that could predict educational dropout. Dropout risk was assessed against pupil’s cognitive competence, success in school, and personal beliefs regarding self and parents, while taking into account the pupil’s background and gender. Based on earlier research, an assumption was made that a pupil’s gender, success in school, and parent’s education would be related with dropping out. This study is part of a project funded by the Academy of Finland and led by Professor Jarkko Hautamäki. The project aims to use longitudinal study to assess the development of pupils’ skills in learning to learn. The target group of this study consisted all Finnish speaking ninth graders of a municipality in Southern Finland. There were in total 1534 pupils, of which 809 were girls and 725 boys. The assessment of learning to learn skills was performed about ninth graders in spring 2004. “Opiopi” test material was used in the assessment, consisting of cognitive tests and questions measuring beliefs. At the same time, pupils’ background information was collected together with their self-reported average grade of all school subjects. During spring 2009, the pupils’ joint application data from years 2004 and 2005 was collected from the Finnish joint application registers. The data were analyzed using quantitative methods assisted by the SPSS for Windows computer software. Analysis was conducted through statistical indices, differences in grade averages, multilevel model, multivariate analysis of variance, and logistic regression analysis. Based on earlier research, dropouts were defined as pupils that had not been admitted to or had not applied to second degree education under the joint application system. Using this definition, 157 students in the target group were classified as dropouts (10 % of the target group): 88 girls and 69 boys. The study showed that the school does not affect the drop-out risk but the school class explains 7,5 % of variation in dropout risk. Among girls, dropping out is predicted by a poor average grade, a lack of beliefs supporting learning, and an unrealistic primary choice in joint application system compared to one’s success in school. Among boys, a poor average grade, unrealistic choices in joint application system, and the belief of parent’s low appreciation of education were related to dropout risk. Keywords educational exclusion, school dropout, success in school, comprehensive school, learning to learn

Korkean käytettävyyden klusterointiteknologioiden vertailu

Tutkielma käsittelee korkean käytettävyyden klustereita. Tavoitteena on vertailla eri klusteriteknologioiden eroja ja arvioida tulosten perusteella sopivia käyttökohteita eri klusterituotteille. Samoja funktioita tarjoavat eri klusterituotteet asetetaan paremmuusjärjestykseen. Arviointi perustuu erilaisiin määrällisiin arvoihin, kuten solmulaitteiden maksimilukumäärä, sekä laadullisiin arvoihin, kuten käyttöönoton ja hallinnoinnin helppous. Erityisesti tavoitteena on tuoda esille eri tuotteiden vahvuuksia ja heikkouksia. Vertailtavia tuotteita ovat Microsoft Cluster Service (MSCS), TruCluster Server for Tru64 UNIX, Steeleye Lifekeeper for Windows ja Sun Cluster. ACM Computing Classification System (CSS): D.4 OPERATING SYSTEMS (C) D.4.5 Reliability

Consequences of Supersymmetry in the Early Universe

Currently, we live in an era characterized by the completion and first runs of the LHC accelerator at CERN, which is hoped to provide the first experimental hints of what lies beyond the Standard Model of particle physics. In addition, the last decade has witnessed a new dawn of cosmology, where it has truly emerged as a precision science. Largely due to the WMAP measurements of the cosmic microwave background, we now believe to have quantitative control of much of the history of our universe. These two experimental windows offer us not only an unprecedented view of the smallest and largest structures of the universe, but also a glimpse at the very first moments in its history. At the same time, they require the theorists to focus on the fundamental challenges awaiting at the boundary of high energy particle physics and cosmology. What were the contents and properties of matter in the early universe? How is one to describe its interactions? What kind of implications do the various models of physics beyond the Standard Model have on the subsequent evolution of the universe? In this thesis, we explore the connection between in particular supersymmetric theories and the evolution of the early universe. First, we provide the reader with a general introduction to modern day particle cosmology from two angles: on one hand by reviewing our current knowledge of the history of the early universe, and on the other hand by introducing the basics of supersymmetry and its derivatives. Subsequently, with the help of the developed tools, we direct the attention to the specific questions addressed in the three original articles that form the main scientific contents of the thesis. Each of these papers concerns a distinct cosmological problem, ranging from the generation of the matter-antimatter asymmetry to inflation, and finally to the origin or very early stage of the universe. They nevertheless share a common factor in their use of the machinery of supersymmetric theories to address open questions in the corresponding cosmological models.

Late-industrial sawmill customers.

The methods of secondary wood processing are assumed to evolve over time and to affect the requirements set for the wood material and its suppliers. The study aimed at analysing the industrial operating modes applied by joinery and furniture manufacturers as sawnwood users. Industrial operating mode was defined as a pattern of important decisions and actions taken by a company which describes the company's level of adjustment in the late-industrial transition. A non-probabilistic sample of 127 companies was interviewed, including companies from Denmark, Germany, the Netherlands, and Finland. Fifty-two of the firms were furniture manufacturers and the other 75 were producing windows and doors. Variables related to business philosophy, production operations, and supplier choice criteria were measured and used as a basis for a customer typology; variables related to wood usage and perceived sawmill performance were measured to be used to profile the customer types. Factor analysis was used to determine the latent dimensions of industrial operating mode. Canonical correlations analysis was applied in developing the final base for classifying the observations. Non-hierarchical cluster analysis was employed to build a five-group typology of secondary wood processing firms; these ranged from traditional mass producers to late-industrial flexible manufacturers. There is a clear connection between the amount of late-industrial elements in a company and the share of special and customised sawnwood it uses. Those joinery or furniture manufacturers that are more late-industrial also are likely to use more component-type wood material and to appreciate customer-oriented technical precision. The results show that the change is towards the use of late-industrial sawnwood materials and late-industrial supplier relationships.

CowLog

We have developed CowLog, which is open-source software for recording behaviors from digital video and is easy to use and modify. CowLog tracks the time code from digital video files. The program is suitable for coding any digital video, but the authors have used it in animal research. The program has two main windows: a coding window, which is a graphical user interface used for choosing video files and defining output files that also has buttons for scoring behaviors, and a video window, which displays the video used for coding. The windows can be used in separate displays. The user types the key codes for the predefined behavioral categories, and CowLog transcribes their timing from the video time code to a data file. CowLog comes with an additional feature, an R package called Animal, for elementary analyses of the data files. With the analysis package, the user can calculate the frequencies, bout durations, and total durations of the coded behaviors and produce summary plots from the data.

CowLog

We have developed CowLog, which is open-source software for recording behaviors from digital video and is easy to use and modify. CowLog tracks the time code from digital video files. The program is suitable for coding any digital video, but the authors have used it in animal research. The program has two main windows: a coding window, which is a graphical user interface used for choosing video files and defining output files that also has buttons for scoring behaviors, and a video window, which displays the video used for coding. The windows can be used in separate displays. The user types the key codes for the predefined behavioral categories, and CowLog transcribes their timing from the video time code to a data file. CowLog comes with an additional feature, an R package called Animal, for elementary analyses of the data files. With the analysis package, the user can calculate the frequencies, bout durations, and total durations of the coded behaviors and produce summary plots from the data.