No description available.

When an out of hospital cardiac arrest (OHCA) occurs, time is of the utmost importance. For every minute that the arrest goes untreated, the chance of survival decreases rapidly. The most common treatment, that is also the most known, is Cardiopulmonary Resuscitation (CPR). Thanks to new technology, the defibrillator is no longer a tool only available to hospital personnel but to anyone who knows where they are located. The objective of this thesis is partly to visualize OHCA occurrences as well as visualize the differences in OHCA occurrences between locations and years. The thesis will analyze where the optimal locations of AEDs are based on a number of variables such as location and year, which is referred to as risk analysis. The analysis was performed by using daytime and nighttime population data from Statistics Sweden (SCB) in combination with heart disease statistics from the national patient register of Socialstyrelsen as well as socio-economic data from SCB. Along with that data, AED locations at the end of 2013 and OHCA data from 2006 up until 2013 was used in visualizations and risk analysis. In order to determine the final optimal placement through the risk analysis, a Geographical Information System (GIS) tool named Multi-Criteria Evaluation (MCE) was used. This tool enabled the weighting of the different parameters against each other, which was integral for the final result. In order to visualize differences, e.g. between two years, a raster was created which consisted of a density difference between the two years. This analysis method shows the spots where there is a majority of either case, e.g. if one area had a larger number of OHCA cases one year compared to previous year. Simple plots were included to show an overview of the problem e.g. where OHCA occurred between the years 2006 and 2013. The results implied that the recommended locations of AEDs while using daytime population data were located in commercial areas. Recommended AEDs from using the nighttime population data was located differently but was located as well as clusters in residential areas. A large source of error in the analysis was the prior heart disease data. The chosen method, an assignment of a percentage chance of heart disease per age group, is a rough and inexact approximation of the actual heart disease statistics. Had there been data about exactly where patients with prior heart disease live and work, the results would most likely be even better. / När ett hjärtstopp utanför sjukhus (OHCA) inträffar, är tiden av yttersta vikt. För varje minut som hjärtstoppet går obehandlat minskar snabbt chansen för överlevnad. Den vanligaste behandlingen, som även är den mest kända, är hjärt- och lungräddning. Tack vare ny teknik är defibrillatorn inte längre ett verktyg som endast är tillgänglig för sjukvårdspersonal utan för alla som vet var de finns. Syftet med denna uppsats är att delvis visualisera förekomsten av OHCA men även att åskådliggöra skillnaderna mellan platser och år. I studien analyseras även, baserat på ett antal variabler, var de optimala platserna för Automatiska Externa Defibrillatorer (AED) är. Denna del av analysen är benämnd som riskanalys. Analysen genomfördes med hjälp av att använda dag- och nattidsbefolkningsdata från Statistiska Centralbyrån (SCB) i kombination med hjärtsjuksdomsstatistik från Socialstyrelsens nationella patientsregister och även socioekonomiska data från SCB. Dessa data, samt AED data från slutet av 2013 och OHCA data daterat från 2006 till 2013 användes både till visualiseringen och till riskanalysen. För att bestämma de slutgiltiga optimala platserna genom riskanalysen användes ett Geografiskt Information System (GIS) verktyg som heter multikriterieanalys (MCE). Detta verktyg gör det möjligt att vikta de olika parametrarna mot varandra, vilket var väsentligt för det slutgiltiga resultatet. För att kunna visualisera skillnader, till exempel mellan två år, skapades ett raster som bestod av en densitetskillnad mellan de två åren. Denna analysmetod kunde sedan visualisera var det finns en majoritet av det ena fallet, till exempel om ett område hade fler hjärtstopp ett år jämfört med tidigare år. Enklare kartor användes för att ge en översikt, till exempel var OHCA har skett mellan åren 2006 och 2013. Resultatet tyder på att de rekommenderade platserna för AED då dagtidsbefolkningsdata användes hamnade i områden med många arbetsplatser. De optimala platserna för AED med nattidsbefolkningsdata var annorlunda utplacerade men hamnade även dem i kluster i befolkningstäta områden med mycket bostäder. En av de större felkällorna i analysen tros vara hjärtsjuksdomsstatistiken. Den metod som användes var att extrahera ålder- och könsgrupper från ett patientregister vilket är en grov och inexakt approximation av den faktiska hjärtsjuksdomsstatistiken. Hade tillgång till data om var befolkning med hjärtsjukdomar faktiskt bor och arbetar funnits, kunde resultatet blivit mer pålitligt.

Humanitarian help organisations today may benefit on improving their location analysis when placing field hospitals in countries hit by a disasters or catastrophe. The main objective of this thesis is to develop and evaluate a spatial decision support method for strategic placing of field hospitals for two time perspectives, long term (months) and short term (weeks). Specifically, the possibility of combining existing infrastructure and satellite data is examined to derive a suitability map for placing field hospitals. Haut-Katanga in Congo is used as test area where exists a large variety of ground features and has been visited by aid organisations in the past due to epidemics and warzones. The method consists of several steps including remote sensing for estimation of population density, a Multi Criteria Evaluation (MCE) for analysis of suitability, and visualization in a webmap. The Population density is used as a parameter for an MCE operation to create a decision support map for locating field hospitals. Other related information such as road network, water source and landuse is also taken into consideration in MCE. The method can generate a thematic map that highlights the suitability value of different areas for field hospitals. By using webmap related technologies, these suitability maps are also dynamic and accessible through the Internet. This new approach using the technology of dasymetric mapping for population deprival together with an MCE process, yielded a method with the result being both a standalone population distribution and a suitability map for placing field hospitals with the population distribution taken into consideration. The use of dasymetric mapping accounted for higher resolution and the ability to derive new population distributions on demand due to changing conditions rather than using pre-existing methods with coarser resolution and a more seldom update rate. How this method can be used in other areas is also analysed. The result of the study shows that the created maps are reasonable and can be used to support the locating of field hospitals by narrowing down the available areas to be considered. The results from MCE are compared to a real field hospital scenario, and it is shown that the proposed method narrows down the localisation options and shortens the time required for planning an operation. The method is meant to be used together with other decision methods which involves non spatial factors that are beyond the scope of this thesis.

The model training algorithm is a critical component in the statistical pattern recognition approaches which are based on the Bayes decision theory. Conventional applications of the Bayes decision theory usually assume uniform error cost and result in a ubiquitous use of the maximum a posteriori (MAP) decision policy and the paradigm of distribution estimation as practice in the design of a statistical pattern recognition system. The minimum classification error (MCE) training method is proposed to overcome some substantial limitations for the conventional distribution estimation methods. In this thesis, three aspects of the MCE method are generalized. First, an optimal classifier/recognizer design framework is constructed, aiming at minimizing non-uniform error cost.A generalized training criterion named weighted MCE is proposed for pattern and speech recognition tasks with non-uniform error cost. Second, the MCE method for speech recognition tasks requires appropriate management of multiple recognition hypotheses for each data segment. A modified version of the MCE method with a new approach to selecting and organizing recognition hypotheses is proposed for continuous phoneme recognition. Third, the minimum verification error (MVE) method for detection-based automatic speech recognition (ASR) is studied. The MVE method can be viewed as a special version of the MCE method which aims at minimizing detection/verification errors. We present many experiments on pattern recognition and speech recognition tasks to justify the effectiveness of our generalizations.

Molecular Nanomagnets have been proposed as plausible candidates in a variety of futuristic applications. Thorough understanding of the magnetic properties of these systems is therefore necessary to develop devices that include such units. The aim of this thesis is to synthesise and structurally and magnetically characterise a range of systems that could be used as elementary units in three proposed applications such as: data storage devices, magnetic refrigerants and qubits for quantum computing. A series of mixed 3d/4f metal complexes were synthesised through solvothermal reactions and characterised by X-ray single crystal diffraction and SQUID magnetometry. Through indirect methods it was possible to obtain high magnetic entropy change for some systems. It was also possible to obtain some insight into the magnetic interactions within the systems through modelling the magnetic data. The role of the 4f-4f and 3d-4f interactions in two sets of molecules is also described. The first study is in an asymmetric dysprosium dimer, where through a range of experimental techniques and advanced theoretical methods, such ab-initio calculations we are able to explain the role of the intramolecular interactions and their effect on the SMM properties of this system. Similarly, insight into the role of the 3d-4f interactions is achieved through the observation of the magnetic behaviour of a family of 27 tetranuclear systems, though SQUID data and ab-initio calculations. Finally, chemical functionalization of a well-proposed qubits, namely {Cr7Ni} and subsequent reaction with a redox active metal ion, CoII/III, two {Cr7Ni} systems are linked. The magnitude of the exchange interaction between the {Cr7Ni}-CoII-{Cr7Ni} was determined through Electron Paramagnetic Resonance. Furthermore, by chemical oxidation/reduction of the cobalt between paramagnetic and diamagneticstates, i.e. CoII and CoIII respectively, we demonstrate that the interaction can be switched ON/OFF. This characteristic makes of these systems candidates to function as a SWAP gate.

A rapid development of wind energy has been approved globally within the last few years due to the common recognition of this renewable energy technology. It is seen as one of the most promising substitutions to fossil fuels which have been exploited for over one century but were proved to be a crucial factor of human-induced climate change. However, even though wind energy has been regarded to be clean, resource saving and environmentally friendly, it still poses special problems and concerns to the surrounding social-ecological system. Thereby it requires careful selection of sites of installation. This paper provides an overview of wind energy and its development in the recent decade and focus on elaborating different issues involved in wind energy development. This is done through a case study of applying GIS tools in selecting suitable locations for onshore wind power plants in Västmanland County of Sweden.

No description available.

When natural disasters such as earthquakes happen, there is a need for an efficient method to support humanitarian aid organizations in the decision making process. One such decision is placement of Foreign Field Hospitals to assist with medical help.To support such a decision lots of different information and data needs to be gathered and combined. The main objectives of this thesis are to collect existing data published shortly after the earthquake in Haiti 2010 as well as data published up to two months after the earthquake. The data is then to be evaluated according to adequacy for analysis and the result of the analysis to be compared to the actual placements of the field hospitals after the 2010 earthquake.The method used in this analysis is Multi Criteria Evaluation (MCE). Data regarding population, elevation, roads, land use, damage, climate, water, health facility locations and airport location are collected and weighted relative with the Analytic Hierarchy Process (AHP) with weights retrieved from a questionnaire sent out to Non-Governmental Organizations (NGOs) and countries involved in the disaster relief. The result obtained from the MCE is a final suitability map depicting areas that are suitable according to the different factors.The data availability for the thesis project is an issue, due to lack of data published shortly after the earthquake. Some of the data used in the analysis do not have the sufficient detail level. Still, an analysis can be performed where suitable areas are obtained.The suitable locations found in the analysis agree well in most cases with where the actual FFHs are placed, however a few locations are not in proximity to where the suitable areas lie. A few of the locations were located in areas exposed to frequently floods. Even though the data availability and quality leaves things to desire, the analysis method shows promising results for future research. The approach could help aggregating information from different sources and provide support in pre-dispatch organization, already having a set of suitable locations to arrive to.

No description available.

Os sistemas naturais e humanos são considerados sistemas integrados, com interações complexas e de caráter fortemente multidisciplinar. A abordagem da limnologia da paisagem, como um princípio holístico para avaliar as relações complexas entre a bacia de captação e o reservatório, é de grande importância na produção de diagnósticos consistentes. O modelo de tomada de decisão foi produzido por meio de literatura especializada, conhecimento de especialistas, Processo Hierárquico Analítico (AHP) e Avaliação Multicritério (MCE). O modelo foi desenvolvido para atuar em escala da paisagem, considerando a bacia de captação como a escala observacional. Foram selecionados sete critérios (variáveis preditoras) para determinar o grau de fragilidade ambiental para o processo de eutrofização antrópica em reservatórios tropicais: Variáveis Intrínsecas do Reservatório: (1) morfometria (profundidade) e Tempo de Retenção (RT); (2) Variáveis Limnológicas: Zona Eufótica e presença de macrófitas de crescimento intensivo; (3) Variáveis Antrópicas: Fonte de Poluição Difusa Potencial; e (4) Variáveis Hidrológicas: Taxa de Sedimentação e escoamento superficial potencial. No processo de ponderação das variáveis, todas as matrizes foram consistentes e os especialistas priorizaram o Escoamento Superficial potencial e a Fonte de Poluição Difusa Potencial com os principais responsáveis pelo processo de eutrofização antrópica. Apesar dos critérios e pesos serem fixos para os reservatórios tropicais, existe a possibilidade de ajuste do modelo de acordo com situações especiais, já que o modelo é flexível suficiente para ser utilizados em outras bacias de captação, com características diferentes e intrínsecas. O modelo também é adaptável em função da disponibilidade de base de dados / The human and natural systems are integrated systems, with complex interactions and a strong multidisciplinary character. The application of landscape limnology, as a holistic principle to address the complex relationships between the watershed and reservoir, are of great importance to produce consistent diagnoses and predictions. The GIS-based model was performed by using literature, expert knowledge, Analytical Hierarchy Process (AHP) and Multi-Criteria Evaluation (MCE). The model was performed in a landscape scale considering the watershed as the observational scale. We selected seven criteria (predictor variables) to assess the environmental fragility to human-induced eutrophication in tropical reservoirs: (1) Intrinsic Reservoir Variables: morphometry (depth) and Retention Time (RT); (2) Limnological Variables: euphotic zone and intensive-growth macrophytes presence; (3) Anthropic Variable: Potential Non-Point Source (NPS); and (4) Hydrological Variable: Sedimentation Rate and Potential Runoff. In the weighting process, all matrices were consistent and the experts prioritized the potential runoff and potential NPS criteria as the main drivers of human-induced eutrophication. Although the criteria and its weights are considered fixed for any tropical reservoir, it is possible to adjust them according to specific situations since the model proposed is flexible enough to be used in different watersheds with different and intrinsic characteristics and adapted according to the database availability