As the Web evolves unexpectedly fast, information grows explosively. Useful resources become more and more difficult to find because of their dynamic and unstructured characteristics. A vertical search engine is designed and implemented towards a specific domain. Instead of processing the giant volume of miscellaneous information distributed in the Web, a vertical search engine targets at identifying relevant information in specific domains or topics and eventually provides users with up-to-date information, highly focused insights and actionable knowledge representation. As the mobile device gets more popular, the nature of the search is changing. So, acquiring information on a mobile device poses unique requirements on traditional search engines, which will potentially change every feature they used to have. To summarize, users are strongly expecting search engines that can satisfy their individual information needs, adapt their current situation, and present highly personalized search results. In my research, the next generation vertical search engine means to utilize and enrich existing domain information to close the loop of vertical search engine's system that mutually facilitate knowledge discovering, actionable information extraction, and user interests modeling and recommendation. I investigate three problems in which domain taxonomy plays an important role, including taxonomy generation using a vertical search engine, actionable information extraction based on domain taxonomy, and the use of ensemble taxonomy to catch user's interests. As the fundamental theory, ultra-metric, dendrogram, and hierarchical clustering are intensively discussed. Methods on taxonomy generation using my research on hierarchical clustering are developed. The related vertical search engine techniques are practically used in Disaster Management Domain. Especially, three disaster information management systems are developed and represented as real use cases of my research work.

Despite disaster managers’ best efforts, inter-organizational disaster management suffers from varying levels of success. One factor that is likely to account for these variations is team mutual understanding, also known as common ground. To validate the potential effect of common ground in disaster management, the thesis investigates common ground in several interviews with disaster managers and in an experimental study involving an inter-organizational disaster event scenario. Analysis of interviews revealed that disaster managers perceived gaps in understanding between responders, the importance of mutual understanding, and perceived common ground similarly to depictions in theory with a few exceptions. Analyses of the experimental study indicated that contextual factors of Team composition, Problem solving approach and Type of tasks differently impacted measures of performance and implicit coordination, and that implicit coordination partially mediated and supressed the relationship between contextual factors and decision quality. Findings suggest the variation in disaster managers’ performance can be ascribed to common ground, implicit coordination, and contextual factors. Moreover, results showed the satisfaction with outcome did not correlate with expert rated quality of decision; and that while satisfaction related to consensus and quality of the decision was linked to generating alternative ideas and debate. Collaboration proved to be more effective in public communication tasks, especially for homogenous team composition. The findings support initiatives for more cross-training and further lab and field experiments.

No description available.

The ambition of this thesis is to fulfill two aims. The first aim is theory development, by presenting a theoretical framework where climate change adaptation (CCA) and disaster risk reduction (DRR) are combined. The second aim is empirical, where the theoretical framework is used to analyze an example of DRR with an ambition to include CCA. An integrated approach is beneficial for the achievement of sustainable development and for strengthening resilience to hazards (Schipper 2009; Mitchell et al 2010). However, the two fields largely operate in separate which can cause reversed development outcomes and hamper the overall objectives of both DRR and CCA. The ambition of this thesis is hence to investigate to what extent the approach is used within humanitarian aid organizations today, with a specific focus on the International Federation of Red Cross and Red Crescent Societies (IFRC). The method used is a qualitative content analysis of the “Integrated Flood Resilience Programme” in Bangladesh (IFRP) conducted by the IFRC. The main finding of the study suggests a surprising progress of including CCA and climate change as components within DRR. However, there are still core aspects of an integrated approach missing in the project. For instance, there is no inclusion of an environmental risk assessment or alignment with climate frameworks, except for parts of the Sustainable Development Goals. Moreover, the efforts associated with CCA are perceived unspecific in comparison to other parts of the project. This thesis therefore reaffirms some of the conclusions made by other scholars (e.g. Mitchell et al 2010; Schipper 2009: Thomalla et al 2006; Hammond 2017), implying that DRR and CCA still mostly operate separately.

This thesis examines how local knowledge is identified and implemented in disaster responseand recovery programmes conducted by international aid organizations. The case that isexamined in the analysis is the International Federation of Red Cross and Red CrescentSocieties response and recovery operations conducted in the aftermath of the Nepalearthquake 2015-2019. Using the method of content analysis, the final report of the Nepaloperation is analyzed using categorizations of local knowledge and informed by previousresearch on local knowledge in disaster operations, along with international aid organizations'engagement with local knowledge.The main findings of this study shows that the implementation of activities that utilize orseeks to identify local knowledge is heavily concentrated to the recovery phase of theoperation, with no activities informed by local knowledge found in the response phase. Allcategories of local knowledge are found throughout the operation, with socio-culturalknowledge being the most prominently utilized, whilst environmental knowledge andorganizational knowledge remains underrepresented. Activities that were not informed bylocal knowledge, or utilized local knowledge to some degree created unintendedconsequences, suggesting that for a productive utilization of local knowledge, it has to beconsidered in all steps of the operational planning.

Bakgrund: Katastrofer orsakar stor skada på samhällen och människor samt är svåra att förebygga helt. Trycket på sjukvården ökar markant till följd av katastrofer. Sjuksköterskorna är den professionen som blivit synonym med katastrofvård. Syfte: Syftet med litteraturstudien var att belysa sjuksköterskors upplevelser av att vårda i ett katastrofdrabbat område. Metod: Studien genomfördes som en allmän litteraturstudie med induktiv ansats. Underlaget blev åtta kvalitativa resultatartiklar som bearbetades genom en innehållsanalys. Resultat: Studiens resultat påvisade att vårda i en katastrofvar mer komplext och hade fler dimensioner än vården i en icke katastrofmiljö. Sjuksköterskorna upplevde påfrestningar i form av yttre faktorer som farliga miljöer, bristande resurser, utmattande arbetsförhållanden och kulturella skillnader. Sjuksköterskorna mötte moraliska dilemman och tvingades till ställningstaganden med direkt påverkan på egen och patientens hälsa. En ökad emotionell och fysisk belastning på sjuksköterskorna förekom under katastrofen Konklusion: Sjuksköterskornas upplevelser grundade sig i de yttre faktorerna som i sin tur skapade moraliska dilemman. De upplevelserna la grunden till de emotionella och fysiska påfrestningarna som sjuksköterskorna upplevde. Det finns behov av vidare forskning kring omvårdnad i katastrofer för att möjliggöra bättre förberedelser vilket skulle stärka sjuksköterskornas resiliens och därav öka kvalitén på vården. / Background: Disasters cause great damage to communities as well as people and arehard to entirely prevent. The amount of workload on healthcare is heavily increased as aresult of a disaster. The nursing profession has become synonymous with disaster care. Aim: The aim of this study was to illustrate nurses' experiences of caring in a disasterstricken area. Method: The method used in this study was a general literature study with an inductive approach. Eight qualitative articles became the basis of this study and these were processed through a content analysis. Result: The result in this study showedthat caring in a disaster was more complex and featured additional dimensions compared to that of a non disaster-stricken environment. The nurses experienced strains from external factors such as dangerous environments, lack of resources, exhausting working conditions and cultural differences. The nurses were caught in ethical dilemmas and were forced to make the hard choices which had a direct impact on theirown and the patients health. An increase in emotional and physical load on the nurseswas apparent throughout the disaster. Conclusion: The nurses' experiences were based on external factors which in turn created ethical dilemmas. These experiences lay the foundation for the emotional and physical strains on the nurses. There is a need forfurther research of disaster nursing to improve the preparations which would in turn strengthen the nurses resilience and thereby increase the quality of care.

No description available.

Understanding human mobility patterns is important for severe weather warning since these patterns can help identify where people are in time and in space when flash floods, tornados, high winds and hurricanes are occurring or are predicted to occur. A GIS (Geographic Information Science) data model was proposed to describe the spatial-temporal human activity. Based on this model, a metric was designed to represent the spatial-temporal activity intensity of human mobility, and an index was generated to quantitatively describe the change in human activities. By analyzing high-resolution human mobility data, the paper verified that human daily mobility patterns could be clearly described with the proposed methods. This research was part of a National Science Foundation grant on next generation severe weather warning systems. Data was collected from a specialized mobile app for severe weather warning, called CASA Alerts, which is being used to analyze different aspects of human behavior in response to severe weather warnings. The data set for this research uses GPS location data from more than 300 APP users during a 14 month period (location was reported at 2 minutes interval, or at based on a 100m change in location). A targeted weather warning strategy was proposed as a result of this research, and future research questions were discussed.

The intent of this study was to develop a sixty minute, mediated practical first aid teaching unit for the missionary system of the Church of Jesus Christ of Latter-day Saints.

It is critical to provide an efficient and accurate information system in the post-disaster phase for individuals' in order to access and obtain the necessary resources in a timely manner; but current map based post-disaster management systems provide all emergency resource lists without filtering them which usually leads to high levels of energy consumed in calculation. Also an effective post-disaster management system (PDMS) will result in distribution of all emergency resources such as, hospital, storage and transportation much more reasonably and be more beneficial to the individuals in the post disaster period. In this Dissertation, firstly, semi-supervised learning (SSL) based graph systems was constructed for PDMS. A Graph-based PDMS' resource map was converted to a directed graph that presented by adjacent matrix and then the decision information will be conducted from the PDMS by two ways, one is clustering operation, and another is graph-based semi-supervised optimization process. In this study, PDMS was applied for emergency resource distribution in post-disaster (responses phase), a path optimization algorithm based ant colony optimization (ACO) was used for minimizing the cost in post-disaster, simulation results show the effectiveness of the proposed methodology. This analysis was done by comparing it with clustering based algorithms under improvement ACO of tour improvement algorithm (TIA) and Min-Max Ant System (MMAS) and the results also show that the SSL based graph will be more effective for calculating the optimization path in PDMS. This research improved the map by combining the disaster map with the initial GIS based map which located the target area considering the influence of disaster. First, all initial map and disaster map will be under Gaussian transformation while we acquired the histogram of all map pictures. And then all pictures will be under discrete wavelet transform (DWT), a Gaussian fusion algorithm was applied in the DWT pictures. Second, inverse DWT (iDWT) was applied to generate a new map for a post-disaster management system. Finally, simulation works were proposed and the results showed the effectiveness of the proposed method by comparing it to other fusion algorithms, such as mean-mean fusion and max-UD fusion through the evaluation indices including entropy, spatial frequency (SF) and image quality index (IQI). Fuzzy set model were proposed to improve the presentation capacity of nodes in this GIS based PDMS.