The land of the midnight sun: summer and winter journeys through Sweden, Norway, Lapland and Northern Finland - 1

Lisäpainokset: 3. p. London 1882, 4. p. London 1888.

The land of the midnight sun: summer and winter journeys through Sweden, Norway, Lapland and Northern Finland - 2

Lisäpainokset: 3. p. London 1882, 4. p. London 1888.

En sommer i Finmarken, Russisk Lapland og Nordkarelen: skildringer af land og folk af J. A. Friis

Lisäpainokset: 2. p. 1880 (299 s.).

Einer grossen richtigen Land-Charte : das Nord- und Ostlichen Teil von Europa und Asia in so weit solches das ganze Russische Reich mit Sibirien der grossen Tartarey in sich begreiffet ...

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Karta öfver Kung Karls Land upprättad under 1898 års svenska polarexpedition

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

M. Martin Helwigs erste Land-Charte vom Herzogthum Schlesien

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Vem är jag, vem är vi, vem är vem i vårt land? : kontextens betydelse för gruppidentifikation och stereotypier bland svensk- och finskspråkiga i Finland och Sverige

Anna Henning-Lindblomin väitöskirja Vem är jag, vem är vi, vem är vem i vårt land? : kontextens betydelse för gruppidentifikation och stereotypier bland svensk- och finskspråkiga i Finland och Sverige (Helsingin yliopisto 2012).

Kalmarsund och Öland

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Map of the United States and territories showing the extent of public surveys and military reservations, land grant R.R., rail roads, canals, and other details ...

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Evaluating land-use related environmental impacts of biomass value chains for decision-support : Comparison and testing of methodologies proposed for environmental life cycle assessment

Life cycle assessment (LCA) is one of the most established quantitative tools for environmental impact assessment of products. To be able to provide support to environmentally-aware decision makers on environmental impacts of biomass value-chains, the scope of LCA methodology needs to be augmented to cover landuse related environmental impacts. This dissertation focuses on analysing and discussing potential impact assessment methods, conceptual models and environmental indicators that have been proposed to be implemented into the LCA framework for impacts of land use. The applicability of proposed indicators and impact assessment frameworks is tested from practitioners' perspective, especially focusing on forest biomass value chains. The impacts of land use on biodiversity, resource depletion, climate change and other ecosystem services is analysed and discussed and the interplay in between value choices in LCA modelling and the decision-making situations to be supported is critically discussed. It was found out that land use impact indicators are necessary in LCA in highlighting differences in impacts from distinct land use classes. However, many open questions remain on certainty of highlighting actual impacts of land use, especially regarding impacts of managed forest land use on biodiversity and ecosystem services such as water regulation and purification. The climate impact of energy use of boreal stemwood was found to be higher in the short term and lower in the long-term in comparison with fossil fuels that emit identical amount of CO2 in combustion, due to changes implied to forest C stocks. The climate impacts of energy use of boreal stemwood were found to be higher than the previous estimates suggest on forest residues and stumps. The product lifetime was found to have much higher influence on the climate impacts of woodbased value chains than the origin of stemwood either from thinnings or final fellings. Climate neutrality seems to be likely only in the case when almost all the carbon of harvested wood is stored in long-lived wooden products. In the current form, the land use impacts cannot be modelled with a high degree of certainty nor communicated with adequate level of clarity to decision makers. The academia needs to keep on improving the modelling framework, and more importantly, clearly communicate to decision-makers the limited certainty on whether land-use intensive activities can help in meeting the strict mitigation targets we are globally facing.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.