Hand Gesture Detection & Recognition System

The project introduces an application using computer vision for Hand gesture recognition. A camera records a live video stream, from which a snapshot is taken with the help of interface. The system is trained for each type of count hand gestures (one, two, three, four, and five) at least once. After that a test gesture is given to it and the system tries to recognize it.A research was carried out on a number of algorithms that could best differentiate a hand gesture. It was found that the diagonal sum algorithm gave the highest accuracy rate. In the preprocessing phase, a self-developed algorithm removes the background of each training gesture. After that the image is converted into a binary image and the sums of all diagonal elements of the picture are taken. This sum helps us in differentiating and classifying different hand gestures.Previous systems have used data gloves or markers for input in the system. I have no such constraints for using the system. The user can give hand gestures in view of the camera naturally. A completely robust hand gesture recognition system is still under heavy research and development; the implemented system serves as an extendible foundation for future work.

Faktorer på avdelningen som påverkar den kortvariga sjukfrånvaron : En fallstudie av tre avdelningar med olika storlek

Bakgrund: Sjukfrånvaron är ett fenomen som snabbt ökar i Sverige idag. Detta är något som kostar stora summor pengar varje år men trots detta finns relativt lite forskning på området. Den forskning som finns i området undersöker till stor del endast den långvariga sjukfrånvaron. Författarna av denna studie har tydligt identifierat en lucka i forskningen vad gäller kortvarig sjukfrånvaro. Syfte: Denna studie syftar därmed att undersöka storleken på avdelningen samt chefens kommunikation och interaktions påverkan på kortvarig sjukfrånvaro. Resultat: Undersökningen resultat är sammanställt ur dels en enkät som de anställda på tre avdelningar inom ett internationellt produktionsföretag fått besvara och dels tre intervjuer genomförda med en HR-chef och två chefer över avdelningarna. Resultatet blev att fem kategorikoder identifierades; Avdelningens storlek, Chefens kommunikation och interaktion, Frånvarokultur, Arbetsuppgifter och Hälsoarbete. Slutsats: Den främsta slutsats som denna undersökning resulterat i är att storleken på avdelningen påverkar de anställdas möjlighet snarare än deras tendens till att vara kortvarigt sjukfrånvarande. Den faktor som istället anses påverka den kortvariga sjukfrånvaron är hur chefen kommunicerar och integrerar med de anställda. Fokus bör därmed läggas vid denna faktor i försök att antingen minska eller kontrollera den kortvariga sjukfrånvaron på avdelningen

Increasing the power of genome wide association studies in natural populations using repeated measures : evaluation and implementation

1. Genomewide association studies (GWAS) enable detailed dissections of the genetic basis for organisms' ability to adapt to a changing environment. In long-term studies of natural populations, individuals are often marked at one point in their life and then repeatedly recaptured. It is therefore essential that a method for GWAS includes the process of repeated sampling. In a GWAS, the effects of thousands of single-nucleotide polymorphisms (SNPs) need to be fitted and any model development is constrained by the computational requirements. A method is therefore required that can fit a highly hierarchical model and at the same time is computationally fast enough to be useful. 2. Our method fits fixed SNP effects in a linear mixed model that can include both random polygenic effects and permanent environmental effects. In this way, the model can correct for population structure and model repeated measures. The covariance structure of the linear mixed model is first estimated and subsequently used in a generalized least squares setting to fit the SNP effects. The method was evaluated in a simulation study based on observed genotypes from a long-term study of collared flycatchers in Sweden. 3. The method we present here was successful in estimating permanent environmental effects from simulated repeated measures data. Additionally, we found that especially for variable phenotypes having large variation between years, the repeated measurements model has a substantial increase in power compared to a model using average phenotypes as a response. 4. The method is available in the R package RepeatABEL. It increases the power in GWAS having repeated measures, especially for long-term studies of natural populations, and the R implementation is expected to facilitate modelling of longitudinal data for studies of both animal and human populations.