The effects of Kanban in software development teams : a study of the implementation at Sandvik

In software development organizations there is sometimes a need for change. In order to meet continuously increasing demands from their customers, Sandvik IT Services- SITS, at Sandvik in Sweden, required improving the way they worked with software development. Due to issues like a lot of work in progress and lot of simultaneous tasks for individuals in the teams that caused stress, it was almost impossible to address the question of working with improvements. In order to enable the improvement process Kanban was introduced in the software development teams. Kanban for software development is a change method created by David J. Anderson. The purpose of this thesis is twofold. One part is to assess what effects Kanban has had on the software development teams. The other part is to make a documentation of the Kanban implementation process at SITS. The documentation has been made on the basis of both company internal resources and observations of the Kanban implementation process. The effects of Kanban have been researched with an interview survey to the teams that have gone through the Kick start of the Kanban process. The result of the thesis is also twofold. One part of the result is an extensive documentation of the implementation process of Kanban at SITS. The other part is an assessment of the effects that Kanban has had at SITS. The major effects have been that the teams are experiencing less stress, more focus on quality and better customer collaboration. It is also evident is that it takes time for some effects to evolve when implementing Kanban

Simultaneous prediction of symptom severity and cause in data from a test battery for Parkinson patients, using machine learning methods

The main purpose of this thesis project is to prediction of symptom severity and cause in data from test battery of the Parkinson’s disease patient, which is based on data mining. The collection of the data is from test battery on a hand in computer. We use the Chi-Square method and check which variables are important and which are not important. Then we apply different data mining techniques on our normalize data and check which technique or method gives good results.The implementation of this thesis is in WEKA. We normalize our data and then apply different methods on this data. The methods which we used are Naïve Bayes, CART and KNN. We draw the Bland Altman and Spearman’s Correlation for checking the final results and prediction of data. The Bland Altman tells how the percentage of our confident level in this data is correct and Spearman’s Correlation tells us our relationship is strong. On the basis of results and analysis we see all three methods give nearly same results. But if we see our CART (J48 Decision Tree) it gives good result of under predicted and over predicted values that’s lies between -2 to +2. The correlation between the Actual and Predicted values is 0,794in CART. Cause gives the better percentage classification result then disability because it can use two classes.

Fitting conditional and simultaneous autoregressive spatial models in hglm

We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.

Differences in muscle activity during hand dexterity tasks between women with arthritis and a healthy reference group

Background. Impaired hand function is common in patients with arthritis and it affects performance of daily activities; thus, hand exercises are recommended. There is little information on the extent to which the disease affects activation of the flexor and extensor muscles during these hand-dexterity tasks. The purpose of this study was to compare muscle activation during such tasks in subjects with arthritis and in a healthy reference group. Methods. Muscle activation was measured in m. extensor digitorium communis (EDC) and in m. flexor carpi radialis (FCR) with surface electromyography (EMG) in women with rheumatoid arthritis (RA, n = 20), hand osteoarthritis (HOA, n = 16) and in a healthy reference group (n = 20) during the performance of four daily activity tasks and four hand exercises. Maximal voluntary isometric contraction (MVIC) was measured to enable intermuscular comparisons, and muscle activation is presented as %MVIC. Results. The arthritis group used a higher %MVIC than the reference group in both FCR and EDC when cutting with a pair of scissors, pulling up a zipper and—for the EDC—also when writing with a pen and using a key (p < 0.02). The exercise “rolling dough with flat hands” required the lowest %MVIC and may be less effective in improving muscle strength. Conclusions. Women with arthritis tend to use higher levels of muscle activation in daily tasks than healthy women, and wrist extensors and flexors appear to be equally affected. It is important that hand training programs reflect real-life situations and focus also on extensor strength.