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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

En temporär hälsoanpassning eller kvarstående samhällsförändring? : Två Pingstförsamlingar i södra Norrland och dess digitala anpassningar vid Covid-19

Näslund Sandström, Hannah January 2022 (has links)
This study aims to investigate how the nature, structure and experience of religious life has changed in two Pentecostal churches during Covid-19 and how digital supplements were used and interpreted. A further aim is to investigate the consequences of the usage of digital media and how digital media is being used today, after the Public Health restrictions have been eased. Heidi Campbell, who is a prominent researcher in the subject of digital religion, has developed the theory Religious-social shaping of technology or RSST. The theory claims that communities' digital use is based on the community's historical background and tradition; these create common precedents that either have an innovative, accepting or deviant attitude towards new media. The material created in this study discusses through Campbell’s theory of digital usages that the impact digitalization has had on the organization, authority and community has been dominant. The result is that the churches after the easing of restrictions is resistant against digital media, since it removes the feeling of solidarity.
2

Image Segmentation With Improved Region Modeling

Ersoy, Ozan 01 December 2004 (has links) (PDF)
Image segmentation is an important research area in digital image processing with several applications in vision-guided autonomous robotics, product quality inspection, medical diagnosis, the analysis of remotely sensed images, etc. The aim of image segmentation can be defined as partitioning an image into homogeneous regions in terms of the features of pixels extracted from the image. Image segmentation methods can be classified into four main categories: 1) clustering methods, 2) region-based methods, 3) hybrid methods, and 4) bayesian methods. In this thesis, major image segmentation methods belonging to first three categories are examined and tested on typical images. Moreover, improvements are also proposed to well-known Recursive Shortest-Spanning Tree (RSST) algorithm. The improvements aim to better model each region during merging stage. Namely, grayscale histogram, joint histogram and homogeneous texture are used for better region modeling.

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