Philosophiae Doctor - PhD / The Table Mountain Group (TMG) Formation is the lowest member of the Cape Supergroup which consists of sediments deposited from early Ordovician to early Carboniferous times, approximately between 500 and 340 million years ago. The Table Mountain Group (TMG) aquifer system is exposed along the west and south coasts of South Africa. It is a regional fractured rock aquifer that has become a major source of bulk water supply to meet the agricultural and urban water requirements of the Western and Eastern Cape Provinces of South Africa. The TMG aquifer system comprises of an approximately 4000 m thick sequence of quartz arenite and minor shale layers deposited in a shallow, but extensive, predominantly eastwest striking asin, changing to a northwest orientation at the west coast. The medium to coarse grain size and relative purity of some of the quartz arenites, together with their well indurated nature and fracturing due to folding and faulting in the fold belt, enhance both the quality of the groundwater and its exploitation potential for agricultural and domestic water supply purposes and its hot springs for recreation. The region is also home to some unique and indigenous floral species (fynbos) of worldwide importance. These and other groundwater dependent vegetation are found on the series of mountains, mountain slopes and valleys in the Cape Peninsula. The hydrogeology of the TMG consists of intermontane and coastal domains which have different properties but are interconnected. The former is characterized by direct recharge from rain and snow melt, deep groundwater circulation with hot springs and low conductivity groundwater. The coastal domain is characterized by shallow groundwater occurrence usually with moderate to poor quality, indirect recharge from rainfall of shallow circulation and where springs occur they are usually cold. The sustainable utilization of the TMG aquifer addressed the issues of the groundwater flow dynamics, recharge and discharge to and from the aquifer; challenges of climate change and climate variability and their potential impact on the aquifer system. The concept of safe yield, recharge and the capture principle and the integration of sustainable yield provided the basis for sustainable utilization with the adaptive management approach. Methodology used included the evaluation of recharge methods and estimates in the TMG aquifer and a GIS based water balance recharge estimation. The evaluation of natural discharges and artificial abstractions from the TMG aquifer system as well as its potential for future development. The Mann-Kendal trend analysis was used to test historical and present records of temperature and rainfall for significant trends as indication for climate variability and change. The determination of variability index of rainfall and standard precipitation index were additional analyses to investigate variability. The use of a case study from the Klein (Little) Karoo Rural Water Supply Scheme (KKRWSS) within the TMG study area was a test case to assess the sustainable utilization of TMG aquifers. Results show that recharge varies in time and space between 1% and 55% of MAP as a result of different hydrostratigraphic units of the TMG based on geology, hydrology, climate, soil, vegetation and landuse patterns however, the average recharge is from 1% to 5% of MAP. The TMG receives recharge mainly through its 37,000 km2 of outcrop largely exposed on mountainous terrain. Natural discharges from the TMG include 11 thermal and numerous cold spring discharges, baseflow to streams and reservoirs, and seepage to the ocean. Results from this study also show increasing temperature trend over the years while rainfall trend generally remain unchanged in the study area. Rainfall variability persists hence the potential for floodsand droughts in the region remain. Global and Regional Models predict about 10% to 25% reduction in rainfall and increase in variability in future. Impacts of his change in climate will affect the different types of aquifers in various ways. Increase in temperature and reduction in rainfall will increase evapotranspiration, reduce surface flows and eventually reduce shallow aquifer resources. Coastal aquifers risk upsurge in salinisation from sea level rise and increase in abstractions from dwindling surface water resources. While floods increase the risk of contamination to shallow aquifers droughts put pressure on all aquifers especially deep aquifers which are considered to be more reliable due to the fact that they are far removed from surface conditions. Future population growth and increase in freshwater demand will put more pressure on groundwater. Recharge to groundwater have been over-estimated in certain areas in the past leading to high abstraction rates from boreholes causing extensive groundwater storage depletion evident by high decline in groundwater levels in these areas and hampering sustainable management of the aquifer resources. Over-abstraction have resulted in loss of stream flow and baseflow reduction to streams during summer, complete loss of springs and reduction of flow to others. Flow to wetlands, riparian vegetation, and sometimes loss and shifts in dependent ecosystems have also resulted from over-abstraction. Sustainability has spatial and temporal implications due to changing climate and demand. The study recommends adaptive management practices in which several factors are considered in managing groundwater together with surface water resources in order to maintain ecological and environmental integrity. The KKRWSS and other groundwater supply schemes in the Western and Eastern Cape Provinces demonstrate the huge potential of the TMG to provide freshwatersupply for domestic and irrigation water needs however, the huge decline in groundwater levels due to over-abstraction in the KKRWSS and other groundwater schemes underscores the need for sustainable utilization of the TMG groundwater resources for present and future generations with minimal impacts on the quality, dependent hydrological and ecosystems as well as the environment. / South Africa

This diploma thesis on the topic "Use of financial analysis as an instrument of investment decision-making" processes the financial evaluation of the economy and the effectiveness of selected investment decisions in the past years using methods of financial analysis. For this purpose, I chose the monitored period from 2012 to 2018. In the first part of the thesis, attention is paid to the evaluation of performance and financial sustainability in terms of implemented and planned investments of the theoretical base. The methods and analyzes used also include the methodology of their calculation. The second part deals with the individual indicators applied to Škoda Auto a.s., based in Mladá Boleslav a subsidiary of the Volkswagen Group. In addition, this section addresses the approach and decision making of the management of the company on investment projects that have already been planned or are planned in the near future, and recommendations are proposed for improving.

Investigation of changes in the rainfall-runoff regimes of rivers and its extremes has become more important especially in the context of ongoing and future climate changes. The main aim of this study is to investigate the key factors involved in these changes and thus influence the hydrological regime. Trends and changes in climatic and hydrological variables are detected and the development of flood and drought extremes is assessed. Several methods are used to identify trends and examine their changes; the Mann-Kendall test, linear regression, simple mass curves, and comparative analysis (IHA). Flood extremity is evaluated based on flood activity levels and return period (N-year flood event), frequency and seasonality using the threshold method and culmination day. Extremity, frequency and seasonality of meteorological drought are evaluated by the threshold method, followed by de Martonne Aridity index and Relative precipitation index. Hydrological drought is evaluated based on Base flow index, Low flow index and threshold method. The main variables involved in these analyzes were annual, seasonal and monthly discharge, air temperature, precipitation and snow cover. The database of the base and other calculated variables is compiled for the period from 1931/1961 to 2010/2012. Trends and changes...

The value of remote sensing data is particularly evident where an areal monitoring is needed to provide information on the earth's surface development. The use of temporal high resolution time series data allows for detecting short-term changes. In Kogi State in Nigeria different vegetation types can be found. As the major population in this region is living in rural communities with crop farming the existing vegetation is slowly being altered. The expansion of agricultural land causes loss of natural vegetation, especially in the regions close to the rivers which are suitable for crop production. With regard to these facts, two questions can be dealt with covering different aspects of the development of vegetation in the Kogi state, the determination and evaluation of the general development of the vegetation in the study area (trend estimation) and analyses on a short-term behavior of vegetation conditions, which can provide information about seasonal effects in vegetation development. For this purpose, the GIMMS-NDVI data set, provided by the NOAA, provides information on the normalized difference vegetation index (NDVI) in a geometric resolution of approx. 8 km. The temporal resolution of 15 days allows the already described analyses. For the presented analysis data for the period 1981-2012 (31 years) were used. The implemented work flow mainly applies methods of time series analysis. The results show that in addition to the classical seasonal development, artefacts of different vegetation periods (several NDVI maxima) can be found in the data. The trend component of the time series shows a consistently positive development in the entire study area considering the full investigation period of 31 years. However, the results also show that this development has not been continuous and a simple linear modeling of the NDVI increase is only possible to a limited extent. For this reason, the trend modeling was extended by procedures for detecting structural breaks in the time series.

A problem that is prevalent for testers at Ericsson is that performance test results are continuously generated but not analyzed. The time between occurrence of problems and information about the occurrence is long and variable. This is due to the manual analysis of log files that is time consuming and tedious. The requested solution is automation with an algorithm that analyzes the performance and notifies when problems occur. A binary classifier algorithm, based on statistical methods, was developed and evaluated as a solution to the stated problem. The algorithm was evaluated with simulated data and produced an accuracy of 97.54 %, to detect trend breaks. Furthermore, correlation analysis was carried out between performance and hardware to gain insights in how hardware configurations affect test runs. / Ett allmänt förekommande problem för testare på Ericsson är att resultat från flera prestandatester genereras kontinuerligt men inte analyseras. Tiden mellan förekommande fel och informationen av dessa är hög och varierande. Detta på grund av manuell analys av loggfiler som är tidsödande och ledsamt. Den efterfrågade lösningen är automatisering med en algoritm, baserad på statistisk metodik, som analyserar data om prestanda och meddelar när problem förekommer. En algoritm för binär klassifikation utvecklades och utvärderades som lösning till det fastställda problemet. Algoritmen utvärderades med simulerad data och alstrade en noggrannhet på 97,54%, för att detektera trendbrott. Dessutom utfördes korrelationsanalys mellan prestandan och hårdvaran för att få insikt i hur hårdvarukonfigurationen påverkar testkörningar.

To look for scientific literature, there are specialized databases and search engines to simplify the process. In order to quickly assess the quality of a given paper, there are different indices meant to quantify the success and impact an author has had within the scientific community. However, these indices have some flaws and could potentially be exploited. In this thesis, we aim to gather publication data from cyber security conferences, identify unknown patterns and trends as well as to introduce a new index or metric that better captures the impact of authors in the field than current common indices. We found that the cyber security community is in a healthy state with no obvious exploitation of common indices. With one notable exception, there is near equal distribution between citations within sub-communities and outside of them. We also found that the majority of authors with several publications chose to publish for several different conferences, not just one of them. Furthermore, new and growing trends in cyber security research were found to be ”machine learning”, ”blockchain” and ”differential privacy”. As for the conferences, it appears that USENIX has overtaken CCS in recent years as the conference with the highest publication output. While no attempts to exploit the common indices were identified, we believe that the risk is still there. We also identify other flaws with the usage of the common metrics in the cyber security research field. As such, we suggest the adoption of the pure R-index with a normalized proportional counting as the score calculation method, since it takes the number and order of the authors into consideration, as well as that it does not discriminate against authors with few publications with many citations. / För att hitta vetenskaplig literatur finns det särskilda databaser och sökmotorer för att förenkla processen. För att snabbt kunna uppskatta kvaliteten hos en given vetenskaplig text finns det olika index menade att snabbt och enkelt kunna kvantifiera en författares inflytande och framgång inom vetenskapen. Det finns dock brister och sätt att utnyttja dessa index. I den här rapporten har vi som mål att samla in data från datasäkerhetskonferenser, identifiera okända mönster och trender samt att introducera ett nytt index som bättre fångar författares inflytande än nuvarande standarder. Vi fann att cyberäkerhet som forskningsområde är välmående och utan uppenbara utnyttjanden av de vanligaste indexen. Med ett enda undantag sker det nästan lika mycket citeringar mellan olika delgemenskaper som inom dem. Vi fann även att majoriteten av författare med flera publikationer valt att publicera i flera olika konferenser och inte bara en. Vidare fann vi att ”machine learning”, ”blockchain” och ”differential privacy” är nya och växande trender. Vad gäller konferenser visar det sig att USENIX har gått om CCS på senare år som den konferens med störst publikationsutflöde. Även om vi inte identifierade något missbruk tror vi att det fortfarande finns risk för det. Vi identifierade även andra brister med användningen av de vanligaste indexen i cybersäkerhetsforskningsområdet. Av dessa anledningar föreslår vi användningen av det så kallade ”pure R-index” med en normaliserad proportionell räkning som poängberäkningsmetod, eftersom att det tar antalet samt ordningen av författare i hänsyn, samt att det inte heller diskriminerar mot författare med få publikationer med många citeringar.

This study is concerned with developing a model to identify small-medium U.K. companies at risk of financial failure up to five years in advance. The importance of small companies in an economy, the impact of their failures, and the lack of failure research with respect to . this population, provided justification for this study. The research was undertaken in two stages. The first stage included a detailed description and discussion of the nature and role of small business in the UK economy, heir relevance, problems and Government involvement in this sector, together with literature review and assessment of past research relevant to this study. The second stage was involved with construction of the models using multiple discriminant analysis, applied to published accountancy data for two groups of failed and nonfailed companies. The later stage was performed in three parts : (1) evaluating five discriminant models for each of five years prior to failure; (2) testing the performance of each of the .five models over time on data not used . in their construction; (3) testing the discriminant models on a validation sample. The purpose was to establish the "best" discriminant model. "Best" was determined according to classification ability of the model and interpretation of variables. Finally a model comprising seven financial ratios measuring four aspects of a company's financial profile, such as profitability, gearing, capital turnover and liquidity was chosen. The model has shown to be a valid tool for predicting companies' health up to five years in advance. / Ministry of Higher Education and Scientific Research of the Iraqi Government.

High dimensional space-time datasets are available nowadays in various aspects of life such as economy, agriculture, health, environment, etc. Meanwhile, it is challenging to reveal possible connections between climate change and weather extreme events such as hurricanes or tornadoes. In particular, the relationship between tornado occurrence and climate change has remained elusive. Moreover, modeling multivariate spatio-temporal data is computationally expensive. There is great need to computationally feasible models that account for temporal, spatial, and inter-variables dependence. Our research focuses on those areas in two ways. First, we investigate connections between changes in tornado risk and the increase in atmospheric instability over Oklahoma. Second, we propose two multiscale spatio-temporal models, one for multivariate Gaussian data, and the other for matrix-variate Gaussian data. Those frameworks are novel additions to the existing literature on Bayesian multiscale models. In addition, we have proposed parallelizable MCMC algorithms to sample from the posterior distributions of the model parameters with enhanced computations. / Doctor of Philosophy / Over 1000 tornadoes are reported every year in the United States causing massive losses in lives and possessions according to the National Oceanic and Atmospheric Administration. Therefore, it is worthy to investigate possible connections between climate change and tornado occurrence. However, there are massive environmental datasets in three or four dimensions (2 or 3 dimensional space, and time), and the relationship between tornado occurrence and climate change has remained elusive. Moreover, it is computationally expensive to analyze those high dimensional space-time datasets. In part of our research, we have found a significant relationship between occurrence of strong tornadoes over Oklahoma and meteorological variables. Some of those meteorological variables have been affected by ozone depletion and emissions of greenhouse gases. Additionally, we propose two Bayesian frameworks to analyze multivariate space-time datasets with fast and feasible computations. Finally, our analyses indicate different patterns of temperatures at atmospheric altitudes with distinctive rates over the United States.

Hastigheten för globalt utdöende är betydligt högre nu jämfört med den förmänskliga tiden, och utan åtgärder kommer utdöendet att accelerera. Detta medför ett stort ansvar på beslutsfattare som måste agera i förhållande till detta. Därför är det viktigt att kunna följa upp den biologiska mångfalden för att ta strategiska beslut, något som endast sker i begränsad skala på kommunal nivå i Sverige. Vidare finns det mycket medborgardata kring artrikedom, där frivilliga medborgare rapporterar fynd de gjort i databasen Artportalen. Möjligheten att utnyttja denna typ av data undersöks i denna fallstudie av Tierps kommun, där trenden för den biologiska mångfalden undersöktes. Därefter användes hypotesprövning för att kvantifiera osäkerheten i de resultat som framtogs. Däremot hävdar flera forskare att det finns utmaningar med att använda sådan data, därför ämnade denna studie även att undersöka dessa problem med den använda datan. Därmed togs det fram kompletterande information om plats, tid och arter för att analysera detta. Studien visade en övergripande negativ trend för den biologiska mångfalden i Tierps kommun, vilket validerades av hypotesprövningen. Gällande problemen som undersöktes kunde det konstateras att många fynd var centrerade runt särskilda platser, månader och arter, vilket begränsar möjligheten att dra säkra slutsatser gällande hela den biologiska mångfalden i kommunen. Sammanfattningsvis kunde det konstateras att de resultat som framtogs skulle behöva kompletteras av annan data alternativt av andra tillvägagångssätt. / The rate of global extinction is significantly higher today compared to the prehuman times, and without action, the extinction will accelerate. This means that there is great pressure on decision-makers to take action. It is therefore important to monitor biodiversity to make strategic decisions, something that municipalities in Sweden only do at a limited scale. At the same time, there are loads of citizen science data on species richness, where unsolicited citizens report their findings in the database Artportalen. The opportunity to utilize this type of data is explored in this case study of Tierps kommun, where the trend of biodiversity is examined. Additionally, hypothesis testing was used to quantify the uncertainty in the results. However, several scientists claim that there are challenges using such data, therefore this study also aimed to explore these. To do this, complementary information regarding time, space and species were gathered and analyzed. The results indicated that a general negative trend could be identified in biodiversity for the municipality of Tierp, which was validated with the hypothesis testing. Regarding the problems that were examined, it could be ascertained that most of the discoveries were limited to specific places, months and species, which limits the possibility to draw certain conclusions regarding the entire biodiversity in the municipality. In conclusion, it could be stated that the results that were produced need to be complemented by other data, alternatively by other methods.

O conhecimento das tendências temporais da qualidade das águas é importante no diagnóstico ambiental de bacias hidrográficas, permitindo avaliar como os corpos d’água vem respondendo ao longo dos anos, em termos qualitativos, à crescente intervenção antrópica. O objetivo deste trabalho é caracterizar a qualidade das águas dos rios das bacias do Piracicaba, Mogi-Guaçu, Turvo Grande, Peixe, Aguapeí, São José dos Dourados e Alto Paranapanema utilizando postos monitorados pela CETESB (Companhia de Tecnologia de Saneamento Ambiental), no período entre 1979 e 2001. Os parâmetros biogeoquímicos avaliados quanto a sua tendência temporal e magnitude foram: oxigênio dissolvido (OD), demanda bioquímica de oxigênio (DBO), nitrogênio total, nitrato, fósforo total, cloreto, amônio e coliformes fecais. A análise de tendência temporal exige uma metodologia específica, uma vez que as séries temporais obtidas não seguem uma distribuição normal, as amostragens são realizadas irregularmente, os dados apresentam sazonalidade e são dependentes da vazão dos rios. Essa metodologia é dividida em análise gráfica e aplicação de testes de tendência, onde inicialmente realiza-se uma análise exploratória dos dados, seguida da confirmação através de testes estatísticos. Os resultados mostraram que de uma maneira geral existe uma degradação da qualidade das águas na maior parte das bacias, representado pelas tendências positivas nos parâmetros (DBO, nitrogênios, fósforo total, cloreto e coliformes fecais) e negativa no parâmetro (OD). Dentre as bacias hidrográficas analisadas a bacia do rio Piracicaba é a mais severamente afetada com variações mais acentuadas na magnitude representada pelo coeficiente de regressão, seguida pelas bacias dos rios Mogi-Guaçu, Turvo Grande, Peixe e Aguapeí, sendo que por outro lado, as bacias do Alto Paranapanema e São José dos Dourados são as menos afetadas. / The knowledge of time trends of water quality is important for the environmental diagnosis of hydrographic basins, allowing the evaluation of how water bodies are responding through the years, in qualitative terms, to the growing antropogenic interventions (actions). The aim of this work is to characterize the water quality of rivers of the Piracicaba, Mogi-Guaçu, Turvo Grande, Peixe, Aguapeí, São José dos Dourados and Alto Paranapanema basins using stations monitored by CETESB (Companhia de Tecnologia de Saneamento Ambiental), in the period from 1979 to 2001. The biogeochemical parameters evaluated concerning its time trend and magnitude were: dissolved oxygen (DO), biochemical oxygen demand (BOD), total nitrogen, nitrate, total phosphorus, chloride, ammonia and fecal coliforms. Time trend analysis demands a specific methodology, since the time series obtained are not normally distributed, the sampling are performed irregularly, it can present seasonal periodicities and dependence on the rivers discharges. This methodology is divided in graphical analysis and application of trend tests, where initially an exploratory analysis of data is performed, followed by confirmation through statistical tests. The results showed that in a general there exists degradation of the water quality in most of the basins, represented by the positive trends of the parameters (BOD, nitrogens, total phosphorus, clorate and fecal coliforms) and negative trend of the parameter (DO). Among the analysed hydrographic basins, the Piracicaba river basin is the most severely affected with higher variations in the magnitude represented by the regression coeficient, followed by the basins of the Mogi-Guaçu, Turvo Grande, Peixe and Aguapeí rivers. On the other hand, the Alto Paranapanema and São José dos Dourados basins are the least affected.