20 resultados para Connectivity mapping


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Activity systems are the cognitively linked groups of activities that consumers carry out as a part of their daily life. The aim of this paper is to investigate how consumers experience value through their activities, and how services fit into the context of activity systems. A new technique for illustrating consumers’ activity systems is introduced. The technique consists of identifying a consumer’s activities through an interview, then quantitatively measuring how the consumer evaluates the identified activities on three dimensions: Experienced benefits, sacrifices and frequency. This information is used to create a graphical representation of the consumer’s activity system, an “activityscape map”. Activity systems work as infrastructure for the individual consumer’s value experience. The paper contributes to value and service literature, where there currently are no clearly described standardized techniques for visually mapping out individual consumer activity. Existing approaches are service- or relationship focused, and are mostly used to identify activities, not to understand them. The activityscape representation provides an overview of consumers’ perceptions of their activity patterns and the position of one or several services in this pattern. Comparing different consumers’ activityscapes, it shows the differences between consumers' activity structures, and provides insight into how services are used to create value within them. The paper is conceptual; an empirical illustration is used to indicate the potential in further empirical studies. The technique can be used by businesses to understand contexts for service use, which may uncover potential for business reconfiguration and customer segmentation.

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Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.

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In Taita Hills, south-eastern Kenya, remnants of indigenous mountain rainforests play a crucial role as water towers and socio-cultural sites. They are pressurized due to poverty, shortage of cultivable land and the fading of traditional knowledge. This study examines the traditional ecological knowledge of Taitas and the ways it may be applied within transforming natural resource management regimes. I have analyzed some justifications for and hindrances to ethnodevelopment and participatory forest management in light of recently renewed Kenyan forest policies. Mixed methods were applied by combining an ethnographic approach with participatory GIS. I learned about traditionally protected forests and their ecological and cultural status through a seek out the expert method and with remote sensing data and tools. My informants were: 107 household interviewees, 257 focus group participants, 73 key informants and 87 common informants in participatory mapping. Religious leaders and state officials shared their knowledge for this study. I have gained a better understanding of the traditionally protected forests and sites through examining their ecological characteristics and relation to social dynamics, by evaluating their strengths and hindrances as sites for conservation of cultural and biological diversity. My results show that, these sites are important components of a complex socio-ecological system, which has symbolical status and sacred and mystical elements within it, that contributes to the connectivity of remnant forests in the agroforestry dominated landscape. Altogether, 255 plant species and 220 uses were recognized by the tradition experts, whereas 161 species with 108 beneficial uses were listed by farmers. Out of the traditionally protected forests studied 47 % were on private land and 23% on community land, leaving 9% within state forest reserves. A paradigm shift in conservation is needed; the conservation area approach is not functional for private lands or areas trusted upon communities. The role of traditionally protected forests in community-based forest management is, however, paradoxal, since communal approaches suggests equal participation of people, whereas management of these sites has traditionally been the duty of solely accredited experts in the village. As modernization has gathered pace such experts have become fewer. Sacredness clearly contributes but, it does not equal conservation. Various social, political and economic arrangements further affect the integrity of traditionally protected forests and sites, control of witchcraft being one of them. My results suggest that the Taita have a rich traditional ecological knowledge base, which should be more determinately integrated into the natural resource management planning processes.

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Road transport and infrastructure has a fundamental meaning for the developing world. Poor quality and inadequate coverage of roads, lack of maintenance operations and outdated road maps continue to hinder economic and social development in the developing countries. This thesis focuses on studying the present state of road infrastructure and its mapping in the Taita Hills, south-east Kenya. The study is included as a part of the TAITA-project by the Department of Geography, University of Helsinki. The road infrastructure of the study area is studied by remote sensing and GIS based methodology. As the principal dataset, true colour airborne digital camera data from 2004, was used to generate an aerial image mosaic of the study area. Auxiliary data includes SPOT satellite imagery from 2003, field spectrometry data of road surfaces and relevant literature. Road infrastructure characteristics are interpreted from three test sites using pixel-based supervised classification, object-oriented supervised classifications and visual interpretation. Road infrastructure of the test sites is interpreted visually from a SPOT image. Road centrelines are then extracted from the object-oriented classification results with an automatic vectorisation process. The road infrastructure of the entire image mosaic is mapped by applying the most appropriate assessed data and techniques. The spectral characteristics and reflectance of various road surfaces are considered with the acquired field spectra and relevant literature. The results are compared with the experimented road mapping methods. This study concludes that classification and extraction of roads remains a difficult task, and that the accuracy of the results is inadequate regardless of the high spatial resolution of the image mosaic used in this thesis. Visual interpretation, out of all the experimented methods in this thesis is the most straightforward, accurate and valid technique for road mapping. Certain road surfaces have similar spectral characteristics and reflectance values with other land cover and land use. This has a great influence for digital analysis techniques in particular. Road mapping is made even more complicated by rich vegetation and tree canopy, clouds, shadows, low contrast between roads and surroundings and the width of narrow roads in relation to the spatial resolution of the imagery used. The results of this thesis may be applied to road infrastructure mapping in developing countries on a more general context, although with certain limits. In particular, unclassified rural roads require updated road mapping schemas to intensify road transport possibilities and to assist in the development of the developing world.