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Johansson, Jan Olof
Alternative names
Publications (5 of 5) Show all publications
Johansson, J.-O. (2008). Datorn i matematikundervisningen: Lägesbeskrivning avseende Halmstads grundskolor 2007. Halmstad: Högskolan i Halmstad
Open this publication in new window or tab >>Datorn i matematikundervisningen: Lägesbeskrivning avseende Halmstads grundskolor 2007
2008 (Swedish)Report (Other academic)
Abstract [sv]

Detta är en rapport över en kvantitativ undersökning om förhållanden i matematikundervisningen i grundskolan med hjälp av datorer. Syftet har varit att få en bild av omfattning, tillämpning samt lärarnas utbildning för undervisning med hjälp av dator. Resultaten skall kunna användas som underlag för flera studier i datoranvändning i matematikundervisningen.

Place, publisher, year, edition, pages
Halmstad: Högskolan i Halmstad, 2008. p. 29
Series
Research on Education and Learning within the School of Teacher Education ; 2008:3
Keywords
dator, matematik, lärare, skola
National Category
Pedagogy
Identifiers
urn:nbn:se:hh:diva-2360 (URN)2082/2762 (Local ID)2082/2762 (Archive number)2082/2762 (OAI)
Available from: 2009-02-26 Created: 2009-02-26 Last updated: 2018-03-23Bibliographically approved
Johansson, J. O. & Hössjer, O. G. (2005). A shot-noise model for paper fibres with non-uniform random orientations. Scandinavian Journal of Statistics, 32(3), 351-363
Open this publication in new window or tab >>A shot-noise model for paper fibres with non-uniform random orientations
2005 (English)In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 32, no 3, p. 351-363Article in journal (Refereed) Published
Abstract [en]

The surface properties of newsprint and other paper qualities are to a great extent determined by the properties of the cellulose fibres. An appropriate description of these fibres as they appear in the paper is therefore important and can be used for quality classification and process monitoring. We suggest a model that considers the fibre geometry and appearance. It is based on a two-dimensional shot-noise process. The model is fit by minimizing a weighted least squares distance between the model-based and estimated covariance functions and this provides estimates of the fibre size, intensity and the non-uniform distribution of the fibre orientation. The model is applied to simulated and real data.

Place, publisher, year, edition, pages
Oxford: Blackwell Publishing, 2005
Keywords
covariance function, fibre process, newsprint, shot-noise, weighted non-linear estimation
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:hh:diva-18717 (URN)10.1111/j.1467-9469.2005.00449.x (DOI)000231145600001 ()2-s2.0-24344488474 (Scopus ID)
Available from: 2012-07-12 Created: 2012-06-25 Last updated: 2018-03-22Bibliographically approved
Johansson, J.-O. (2001). Parameter-estimation in the auto-binomial model using the coding-and pseudo-likelihood method approached with simulated annealing and numerical optimization. Pattern Recognition Letters, 22(11), 1233-1246
Open this publication in new window or tab >>Parameter-estimation in the auto-binomial model using the coding-and pseudo-likelihood method approached with simulated annealing and numerical optimization
2001 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 22, no 11, p. 1233-1246Article in journal (Refereed) Published
Abstract [en]

In texture analysis, the Gibbs sampler constitutes an important tool in the generation of synthetic textures. The textures are modeled as distributions with specified parameters. In this paper, we study the estimation process of the parameters in such distributions and compare Besags coding method with a pseudo-likelihood method. We also compare simulated annealing with the Newton-Raphson method to find the global maximum of a likelihood or pseudo-likelihood function. For some textures, the two methods differ but in most case there are no important differences between them. The two maximization methods find the same maximum, but the Newton-Raphson method is much faster. However, the Newton-Raphson method cannot be applied in some cases when the location of the maximum differs too much from the starting points. Here, it is often possible to find the global maximum using simulated annealing. The methods have been used in an application with newsprint.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2001
Keywords
Estimation, Annealing, Encoding (symbols), Optimization, Textures
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:hh:diva-3432 (URN)10.1016/S0167-8655(01)00055-1 (DOI)000170125300006 ()2-s2.0-0035452212 (Scopus ID)
Available from: 2010-02-17 Created: 2009-12-01 Last updated: 2018-03-23Bibliographically approved
Johansson, J.-O. (2000). Measuring homogeneity of planar point-patterns by using kurtosis. Pattern Recognition Letters, 21(13-14), 1149-1156
Open this publication in new window or tab >>Measuring homogeneity of planar point-patterns by using kurtosis
2000 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 21, no 13-14, p. 1149-1156Article in journal (Refereed) Published
Abstract [en]

Kurtosis is generally associated with measurements of peakedness of a distribution. In this paper, we suggest a method where kurtosis can be used as a measure of homogeneity of any quantifiable property on a planar surface. A 2-dimensional, continuous and uniform distribution has kurtosis equal to 5.6. This value is also the limiting value for a discrete uniform distribution defined on a regular, rectangular grid when the number of grid points tend to infinity. Measurements of a planar surface, taken at regular grid points, are considered as realizations of random fields. These are associated with 2-dimensional random variables from which the value of kurtosis can be computed and used as a measure of the homogeneity of the field. A deviation from 5.6 indicates that the stochastic variable is not uniformly distributed and that the corresponding random field is not homogeneous. The model is applied on the spatial variation of the roughness on the surface of newsprint, an application where homogeneity is very important.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2000
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:hh:diva-3431 (URN)10.1016/S0167-8655(00)00076-3 (DOI)000165759000008 ()2-s2.0-0034541122 (Scopus ID)
Available from: 2010-02-17 Created: 2009-12-01 Last updated: 2018-03-23Bibliographically approved
Johansson, J.-O. (2000). Modelling the surface structure of newsprint. Journal of Applied Statistics, 27(4), 425-438
Open this publication in new window or tab >>Modelling the surface structure of newsprint
2000 (English)In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 27, no 4, p. 425-438Article in journal (Refereed) Published
Abstract [en]

The Gibbs distribution is often used to model micro-textures. This includes a definition of a neighbourhood system. If a micro-texture contains a large-scale variation, the neighbourhood system will be large, which implies many parameters in the corresponding Gibbs distribution. The estimation of the parameters for such models will be difficult and time consuming. I suggest, in this paper, a separation of the micro-texture into a large-scale variation and a small-scale variation and model each source of variation with a Gibbs distribution. This method is applied on full-tone print of newsprint to model the variation caused by print mottle. In this application, the large-scale variation is mainly caused by fibre flocculation and clustering and the small-scale variation contains the variation of the fibres and fines on and between the clusters. The separate description of these two variations makes it possible to relate different kinds of paper qualities to the appropriate source of variation.

Place, publisher, year, edition, pages
London: Taylor & Francis, 2000
Keywords
Business Mathematics, Mathematical Statistics, Medical Statistics, Statistical Theory and Methods, Statistics, Statistics for Social Sciences, Statistics for the Biological Sciences
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:hh:diva-3433 (URN)10.1080/02664760050003614 (DOI)000086901700003 ()2-s2.0-0004398996 (Scopus ID)
Available from: 2010-02-15 Created: 2009-12-01 Last updated: 2018-03-23Bibliographically approved
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