Heavy rainfall is a common source of disasters in Taiwan. In recent years, floods have become more frequent and more severe. Therefore, there is a need for more research on Taiwanese flood preparedness. This study aims to study Kaohsiung residents¡¦ risk perception and preparation for floods, using Rogers¡¦ (1983) protection motivation theory as the theoretical model. A convenience sample of 256 residents answered the questionnaire in this study. Results found that respondents¡¦ perception of flood risk and perception of weather forecast (its timeliness, accuracy and comprehensibility) could affect their intent to prepare. These findings suggest that the government should put more effort into flood risk education and improve the quality and trustworthiness of weather forecast.

MV is the traditional method to treat international portfolio selection problems, which bases its theory on the assumption of Normal Distribution. However, during economy recession the portfolio return turns out to be a fat tail distribution. Therefore, in this sense, we explore Roy’s SF criterion and apply the extreme theory to the historical data. We demonstrate how such portfolios would perform during the Asian Crisis, IT Bubble Bust and the Financial Crisis separately. We also compare the SF portfolio’s performance to the MV portfolio’s performance, therefore to check, SF and MV portfolio, which will outperform during bust and boom of the economy. The Asian Crisis was marked with great currency devaluation and lower currency return on equity. The Dot.Com Bubble Busts was known for its sharp plummet in the stock market, while, the Financial Crisis was known as the large falls in the US stock market and elsewhere. They are the extreme events of the world capital markets, which in some way contribute to the non-normal distribution. Simulated results over the 1997-2010 period which include six busts and booms: the Asian Crisis, period after Asian Crisis, IT Bubble Bust, period after IT Bubble Bust, The Financial Crisis and period after The Financial Crisis, indicate that SF portfolio outperforms MV portfolio during most of the times, this result is especially obvious for Indonesian and Thailand.

Recent hurricanes in the Gulf of Mexico (e.g., Ivan, Dennis, Katrina, Rita and Ike) were observed to develop wave conditions that were near or exceeded the predicted 100-year conditions. As a result, many offshore facilities, as well as coastal infrastructure, which were designed to withstand the 100-year condition, were damaged. New estimates of extreme conditions, which incorporate recently observed maxima, are needed to provide better guidelines for design of coastal and offshore structures. Berek et al. (2007) have used modeled data to develop new criteria, but these estimates can be very sensitive to the data and to the statistical methods used in the development. Berek's estimates also do not cover the entire Gulf of Mexico. We have developed updated estimates of the 100-year extreme wave conditions for the entire Gulf of Mexico using a more comprehensive approach. First, the applicability of standard parametric wind models was examined and appropriate adjustments to the Rankine vortex model were developed to reduce the wind field errors during hurricane conditions. The adjusted winds reduced the error by up to 25 percent compared to the original Rankine vortex model. To obtain reliable wave data, merged wind fields were generated using the NCEP/NCAR Reanalysis 1 project modeled wind data for background wind and the parametric wind model for hurricane conditions. Next, the SWAN wave model was used for the 51-year period from 1958 to 2008 along with multiple statistical methods (Gumbel, Weibull and GEV-Generalized Extreme Value distribution). The effect of the recent hurricane season (2004-2008) shows that maximum 100-year wave height values and their distribution changes. A resampling technique (bootstrap) is used to evaluate and select the optimum statistical method to estimate more appropriate extreme wave conditions.

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<p> </p><p>Agila metoder är en relativt ny ansats inom programvaruutvecklingsområdet och ses som en reaktion mot plandrivna metoder som har svårt att hantera oförutsägbara och skiftande krav. Agila metoder förespråkar nära och frekvent kundkommunikation och iterativt arbete för att ständigt kunna skapa, prioritera och verifiera krav. Dock uppmärksammar inte agila metoder aspekter som berör programvarans användbarhet. Syftet med rapporten är därför att integrera användarcentrerad design för att öka fokus mot programvarans användbarhet hos agila metoder. Användarcentrerad design är en process som fokuserar på användbarhet genom att användarna är en central aspekt i utvecklingsprocessen. Genom litteraturstudie identifierades förutsättningar men även hinder och svårigheter för en integrering av agila metoder och användarcentrerad design. Med de identifierade föutsättningarna som grund har sedan den användarcentrerade designprocessen prototyping integrerats med den agila metoden Extreme Programming. Resultatet blev en artefakt som integrerar Extreme Programming och prototyping och ökar möjligheten att utveckla en användbar programvara.</p><p> </p>

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Extreme right-wing political parties and movements are growing in number and size all over Europe and in their tail, an increased political focus on immigration and its pros and cons. Sweden is no exception to the European trend and the Swedish extreme right-wing political party, Sverigedemokraterna, became the third largest political party in the latest elections for the Swedish parliament in 2014. The objective of this study is to contribute to the current debate on rising right-wing party affiliation through an analysis of the reasons for extreme right-wing voting behavior of immigrants in Sweden. Through a case-study based on six in-depth interviews with immigrants voting for Sverigedemokraterna, the study looks into issues regarding social group identification as the issue of identification with or repudiation of the ‘outgroup’ appears, from previously conducted research, to be a key issue. An analysis of policy documents of Sverigedemokraterna, previously conducted research and finally an interview conducted by a Swedish anti-racist organization is also included in the case-study. The study shows that the reasons behind immigrant extreme right-wing voting behavior present substantial similarities with other highly represented groups of extreme right-wing voters in that voting is, in line with Realistic Conflict Theory, encouraged by a perceived socio-economic threat emanating from an identified ‘outgroup’. Further, the study validates the assumption of ‘in-’ and ‘outgroup’ identification as being a key issue in determining motives behind extreme right-wing voting. The key explanatory factor of the voting behavior of the studied group indeed shows to be the rejection of an identification with a homogenous group of ‘immigrants’. Finally, the study shows that the rejection of an identification with a homogenous group of ‘immigrants’, removes the theoretical base for assuming that immigrants should be expected to show favorable attitudes towards the group of immigrants in general.

Marketing in social media has been studied extensively in recent years, but not specifically for extreme-sport oriented companies. Even though most of the extreme-oriented companies are using social media for marketing, only a few pay special attention to its risks and possibilities. The purpose of this study is to identify extreme-sport oriented companies' practices to use social media as a marketing tool. I interviewed eight extreme- oriented companies and athletes. In addition to interviews, I also performed a four weeks observation in social media, mostly in Facebook and Twitter, and made notions about companies' practices in using social media for marketing. Almost all interviewed companies (88 %) were using social media. They usually posted updates about once a week and did not have a marketing strategy. However, it is possible that larger companies, which were not directly interviewed in this study, have a clear strategy for marketing in social media. Interviewed companies used social media in an improvised and unplanned manner. However, through trial and error, extreme-sport oriented companies have found their way to use social media effectively. Writing posts in social media about new products, upcoming events, offers, extreme-sport pictures or films and up-to-date information about the company seemed to be a good way to use social media for marketing. Most of the extreme-sport oriented companies can find social media a very useful marketing tool, but only if they have resources and time to invest to be active on social media.

The thesis describes the methodology of evaluation of extreme events and development of cartographic information system for this purpose. Existing complex risk assessment systems in the world are analysed highlighting their advantages and disadvantages. Author proposes original integrated risk assessment methodology based on integration of information from different geographic data sources. A cartographic information system designed by the author allows for the assessment of extreme events threats and risks. The developed methodology includes methodology of cartographic information system component development and deployment. The work describes necessary extreme events data, methods of their collection and database design principles. The created model enables the user to collect the data on extreme hazard events and to aggregate several threats into a single synthetic threat. The concepts of risks and threats and risk assessment methodology are explained. The author introduces project of an information system operating in the Lithuanian Geographic Information Infrastructure and integrated in the Lithuania spatial information portal. The system is tested with several consistent spatial data sets for Lithuania. The thesis presents experimental results that show increased geological and meteorological risk areas in Lithuania. Finally, methodological and practical conclusions about the methods and system customization, reliability and compliance with standards are presented. / Disertacijoje aprašoma ekstremalių įvykių vertinimo kartografinės informacinės sistemos kūrimo metodologija. Analizuojamos pasaulyje egzistuojančios kompleksinės rizikos vertinimo sistemos išryškinami jų trūkumai ir privalumai. Atliktos analizės pagrindu sukuriama originali daugeliu duomenų šaltinių pagrįsta kompleksinio rizikos vertinimo metodologija ir aprašoma autoriaus suprojektuota informacinė sistema leidžianti vertinti ekstremalių įvykių grėsmes ir riziką. Sukurta metodologija apima kartografinės informacinės sistemos sudedamųjų dalių kūrimo ir diegimo metodiką. Aprašomi sistemos veikimui reikiamų duomenų tipai, jų surinkimas, ekstremalių įvykių duomenų bazės kaupimo principai, sukuriamas ekstremalių įvykių grėsmių skaičiavimo ir kelių grėsmių apjungimo į vieną sintetinę grėsmę modelis. Aprašomas rizikos ir grėsmės santykis ir rizikos vertinimo metodologija. Disertacijoje taip pat pateikiama visos sistemos, veikiančios Lietuvos geografinės informacijos infrastruktūroje, ir integruotos Lietuvos erdvinės informacijos portale projektas. Sistema išbandyta su Lietuvoje pasiekiamais ir realiai egzistuojančiais erdvinių duomenų rinkiniais. Pateikiami eksperimento metu gauti rezultatai, rodantys padidintų geologinių ir meteorologinių rizikos rajonus Lietuvoje. Darbo pabaigoje pateikiamos metodologinės ir praktinės išvados apie metodų ir sistemos pritaikymą, patikimumą ir atitikimą standartams.

In financial risk management it is essential to be able to model dependence in markets and portfolios in an accurate and efficient way. A high positive dependence between assets in a portfolio can be devastating, especially in times of crises, since losses will most likely occur at the same time in all assets for such a portfolio. The dependence is therefore directly linked to the risk of the portfolio. The risk can be estimated by several different risk measures, for example Value-at-Risk and Expected shortfall. This paper studies some different ways to measure risk and model dependence, both in a theoretical and empirical way. The main focus is on copulas, which is a way to model and construct complex dependencies. Copulas are a useful tool since it allows the user to separately specify the marginal distributions and then link them together with the copula. However, copulas can be quite complex to understand and it is not trivial to know which copula to use. An implemented copula model might give the user a "black-box" feeling and a severe model risk if the user trusts the model too much and is unaware of what is going. Another model would be to use the linear correlation which is also a way to measure dependence. This is an easier model and as such it is believed to be easier for all users to understand. However, linear correlation is only easy to understand in the case of elliptical distributions, and when we move away from this assumption (which is usually the case in financial data), some clear drawbacks and pitfalls become present. A third model, called historical simulation, uses the historical returns of the portfolio and estimate the risk on this data without making any parametric assumptions about the dependence. The dependence is assumed to be incorporated in the historical evolvement of the portfolio. This model is very easy and very popular, but it is more limited than the previous two models to the assumption that history will repeat itself and needs much more historical observations to yield good results. Here we face the risk that the market dynamics has changed when looking too far back in history. In this paper some different copula models are implemented and compared to the historical simulation approach by estimating risk with Value-at-Risk and Expected shortfall. The parameters of the copulas are also investigated under calm and stressed market periods. This information about the parameters is useful when performing stress tests. The empirical study indicates that it is difficult to distinguish the parameters between the stressed and calm market period. The overall conclusion is; which model to use depends on our beliefs about the future distribution. If we believe that the distribution is elliptical then a correlation model is good, if it is believed to have a complex dependence then the user should turn to a copula model, and if we can assume that history will repeat itself then historical simulation is advantageous.