Forecasts are important to decision-making and risk assessment in many domains. Since current database systems do not provide integrated support for forecasting, it is usually done outside the database system by specially trained experts using forecast models. However, integrating model-based forecasting as a first-class citizen inside a DBMS speeds up the forecasting process by avoiding exporting the data and by applying database-related optimizations like reusing created forecast models. It especially allows subsequent processing of forecast results inside the database. In this demo, we present our prototype F2DB based on PostgreSQL, which allows for transparent processing of forecast queries. Our system automatically takes care of model maintenance when the underlying dataset changes. In addition, we offer optimizations to save maintenance costs and increase accuracy by using derivation schemes for multidimensional data. Our approach reduces the required expert knowledge by enabling arbitrary users to apply forecasting in a declarative way.

No description available.

A importância de se considerar os volumes na análise dos movimentos de preços de ações pode ser considerada uma prática bastante aceita na área financeira. No entanto, quando se olha para a produção científica realizada neste campo, ainda não é possível encontrar um modelo unificado que inclua os volumes e as variações de preços para fins de análise de preços de ações. Neste trabalho é apresentado um modelo computacional que pode preencher esta lacuna, propondo um novo índice para analisar o preço das ações com base em seus históricos de preços e volumes negociados. O objetivo do modelo é o de estimar as atuais proporções do volume total de papéis negociados no mercado de uma ação (free float) distribuídos de acordo com os seus respectivos preços passados de compra. Para atingir esse objetivo, foi feito uso da modelagem dinâmica financeira aplicada a dados reais da bolsa de valores de São Paulo (Bovespa) e também a dados simulados por meio de um modelo de livro de ordens (order book). O valor do índice varia de acordo com a diferença entre a atual porcentagem do total de papéis existentes no mercado que foram comprados no passado a um preço maior do que o preço atual da ação e a sua respectiva contrapartida, que seria a atual porcentagem de papéis existentes no mercado que foram comprados no passado a um preço menor do que o preço atual da ação. Apesar de o modelo poder ser considerado matematicamente bastante simples, o mesmo foi capaz de melhorar significativamente a performance financeira de agentes operando com dados do mercado real e com dados simulados, o que contribui para demonstrar a sua racionalidade e a sua aplicabilidade. Baseados nos resultados obtidos, e também na lógica bastante intuitiva que está por trás deste modelo, acredita-se que o índice aqui proposto pode ser bastante útil na tarefa de ajudar os investidores a definir intervalos ideais para compra e venda de ações no mercado financeiro. / The importance of considering the volumes to analyze stock prices movements can be considered as a well-accepted practice in the financial area. However, when we look at the scientific production in this field, we still cannot find a unified model that includes volume and price variations for stock prices assessment purposes. In this paper we present a computer model that could fulfill this gap, proposing a new index to evaluate stock prices based on their historical prices and volumes traded. The aim of the model is to estimate the current proportions of the total volume of shares available in the market from a stock distributed according with their respective prices traded in the past. In order to do so, we made use of dynamic financial modeling and applied it to real financial data from the Sao Paulo Stock Exchange (Bovespa) and also to simulated data which was generated trough an order book model. The value of our index varies based on the difference between the current proportion of shares traded in the past for a price above the current price of the stock and its respective counterpart, which would be the proportion of shares traded in the past for a price below the current price of the stock. Besides the model can be considered mathematically very simple, it was able to improve significantly the financial performance of agents operating with real market data and with simulated data, which contributes to demonstrate its rationale and its applicability. Based on the results obtained, and also on the very intuitive logic of our model, we believe that the index proposed here can be very useful to help investors on the activity of determining ideal price ranges for buying and selling stocks in the financial market.

A importância de se considerar os volumes na análise dos movimentos de preços de ações pode ser considerada uma prática bastante aceita na área financeira. No entanto, quando se olha para a produção científica realizada neste campo, ainda não é possível encontrar um modelo unificado que inclua os volumes e as variações de preços para fins de análise de preços de ações. Neste trabalho é apresentado um modelo computacional que pode preencher esta lacuna, propondo um novo índice para analisar o preço das ações com base em seus históricos de preços e volumes negociados. O objetivo do modelo é o de estimar as atuais proporções do volume total de papéis negociados no mercado de uma ação (free float) distribuídos de acordo com os seus respectivos preços passados de compra. Para atingir esse objetivo, foi feito uso da modelagem dinâmica financeira aplicada a dados reais da bolsa de valores de São Paulo (Bovespa) e também a dados simulados por meio de um modelo de livro de ordens (order book). O valor do índice varia de acordo com a diferença entre a atual porcentagem do total de papéis existentes no mercado que foram comprados no passado a um preço maior do que o preço atual da ação e a sua respectiva contrapartida, que seria a atual porcentagem de papéis existentes no mercado que foram comprados no passado a um preço menor do que o preço atual da ação. Apesar de o modelo poder ser considerado matematicamente bastante simples, o mesmo foi capaz de melhorar significativamente a performance financeira de agentes operando com dados do mercado real e com dados simulados, o que contribui para demonstrar a sua racionalidade e a sua aplicabilidade. Baseados nos resultados obtidos, e também na lógica bastante intuitiva que está por trás deste modelo, acredita-se que o índice aqui proposto pode ser bastante útil na tarefa de ajudar os investidores a definir intervalos ideais para compra e venda de ações no mercado financeiro. / The importance of considering the volumes to analyze stock prices movements can be considered as a well-accepted practice in the financial area. However, when we look at the scientific production in this field, we still cannot find a unified model that includes volume and price variations for stock prices assessment purposes. In this paper we present a computer model that could fulfill this gap, proposing a new index to evaluate stock prices based on their historical prices and volumes traded. The aim of the model is to estimate the current proportions of the total volume of shares available in the market from a stock distributed according with their respective prices traded in the past. In order to do so, we made use of dynamic financial modeling and applied it to real financial data from the Sao Paulo Stock Exchange (Bovespa) and also to simulated data which was generated trough an order book model. The value of our index varies based on the difference between the current proportion of shares traded in the past for a price above the current price of the stock and its respective counterpart, which would be the proportion of shares traded in the past for a price below the current price of the stock. Besides the model can be considered mathematically very simple, it was able to improve significantly the financial performance of agents operating with real market data and with simulated data, which contributes to demonstrate its rationale and its applicability. Based on the results obtained, and also on the very intuitive logic of our model, we believe that the index proposed here can be very useful to help investors on the activity of determining ideal price ranges for buying and selling stocks in the financial market.

Esta tesis contribuye a la literatura analizando los efectos causales que el estado de salud tiene sobre la participación laboral en la población en edad de trabajar. De este modo, analiza los efectos que un deterioro en el estado de salud tiene sobre la participación laboral del individuo, así como los efectos de proveer cuidados informales sobre la participación laboral femenina. El primer capítulo utiliza una aproximación empírica homogénea en nueve países europeos, lo que hace posible relacionar las diferencias encontradas con diferencias en el contexto institucional. El segundo capítulo analiza el papel que juega el estado de salud en las transiciones hacia y fuera del empleo. Los resultados muestran que el estado de salud general afecta simétricamente las entradas y salidas del empleo, mientras que cambios en el estado de salud mental sólo influyen el riesgo de abandonar el empleo. El tercer capítulo examina los efectos de varios tipos de cuidados informales en el comportamiento laboral femenino. Los resultados sugieren que los costes de oportunidad laborales aparecen en aquellas mujeres que conviven con la persona dependiente, al mismo tiempo que los efectos negativos surgen cuando se proveen cuidados informales por un período superior al año. / This thesis aims to contribute to the literature with an attempt to identify the causal effects of health on labour market outcomes in the working-age population. I analyse the effects of the onset of a health shock on the individuals' labour market outcomes, and also the effects of caregiving on female labour participation. The first chapter uses a homogeneous empirical framework to estimate the first set of effects on nine European countries, which allows me to relate the empirical estimates to differences in social security arrangements across these countries. The second chapter analyses the role of health in exits out of and entries into employment and the results show that general health affects symmetrically entries into and exits out of employment, but changes in mental health status influence only the hazard of non-employment for the stock sample of workers. The third chapter examines the effects of various types of informal care on female labour behaviour and the results suggest the existence of labour opportunity costs for those women who live with the dependent person they care for, and the negative effects appear when caregiving for more than a year.

The problem of low domestic savings is inherent in most Southern African Development Community (SADC) countries. This has motivated most of the SADC countries to institute policies that seek to attract foreign capital to cover the investment deficit that arises from low domestic savings rates. This study gives robust conclusions on the effectiveness of individual tax incentives commonly used by SADC countries in attracting foreign mobile capital. This study has broadened the dimensions research can take in analysing the contribution of tax incentives to Foreign Direct Investment (FDI) inflows into developing countries. In separating individual tax incentives mainly used in the SADC region the study gives a robust analysis on the impact of each tax incentive on FDI inflows into SADC countries. The tax incentives used in this study are: tax holidays, corporate income tax (CIT), reduced CIT in specific sectors and losses carried forward. The study also derives data indices for governance, infrastructure and economic policy variables which gives the study clean and reliable data for efficient regression results. These macroeconomic data derivations assist in giving the FDI attraction analysis more variables and well behaved data in drawing conclusions. Through an analysis and comparison of trends in FDI inflows and stock data in different African regions the study draws important conclusions on the impact of the socio-economic environment in FDI attraction. The study, in consultation with data from the period 2004 to 2013 separates the SADC countries into four panels based on resource richness. Panel 1 includes the resources-rich countries, Panel 2 the resources-poor countries, Panel 3 all SADC countries, except South Africa and Panel 4 all the SADC countries. Each of the estimate models in this study, use individual tax incentives variables to avoid the effects of collinearity between different tax incentives variables and to improve the predictive power of the panel data models. This study derived tax incentives data for individual SADC countries, from Ernst and Young’s worldwide tax data. Regular tax incentives in the SADC are derived from tax holidays, corporate income tax (CIT); losses carried forward and reduced CIT in specific sectors. This study seeks to achieve two major objectives: firstly, to establish the effectiveness of tax incentives in attracting FDI inflows into SADC countries, and, secondly, to establish other variables that influence FDI inflows into SADC countries. The study estimated four panels for SADC countries, separated according to resource richness. This was done because different types of FDI are dependent on the available resources in developing countries and thus factors that influence the FDI inflows differ according to resource richness. Resource-seeking FDI moves to resources-rich economies, market-seeking FDI goes to economies that have access to larger markets and efficiency-seeking and strategic-asset-seeking FDI move to economies that ensure efficient use of their capital resources. Thus, as expected, factors that attract FDI to countries in the separate panels differ in direction of causality and magnitude of impact. The study adopts a system Generalised Method of Moments (SYS GMM) methodology to address the problem of endogeneity associated with dynamic panel data models. The estimated results established that tax holidays positively explain FDI inflows in Panel 2. CIT was found to negatively affect FDI inflows into all SADC countries despite their particular category of resource-richness. Losses carried forward are insignificant in all panels and reduced CIT in specific sectors negatively influences FDI inflows in Panel 1 and surprisingly positively influences FDI inflows in Panel 2. The lagged FDI variable shows a positive relationship with current year FDI inflows. The governance index is significant and positively affects FDI inflows in panels 1, 3 and 4. Panel 2 shows a negative relationship between governance and FDI inflows. Market potential measured by GDP growth rate is insignificantly different from zero in all the four panels in the study and negatively signed, except in models A and C of Panel 2. The stock of infrastructure is significant and negatively signed in all the panels. The log natural resources variable though insignificant in some models, mainly, exhibit a significant and negative effect in most models of the study’s panel estimations. The trade openness variable is positively related to FDI inflows in Panel 1. Panel 2 show negative effects of trade openness to FDI inflows. Financial globalisation significantly impacts positive FDI inflows in all the four panels. The economic policy variable is insignificant in all the four panels of the study, except, in model B of Panel 1 where it is weakly significant at 10% level and negatively signed. The study concludes that tax incentives are important in FDI attraction in the SADC countries; therefore, an effective tax mix that ensures efficient use of tax incentives is important to ensure sustainable FDI inflows into the region. Good governance is important in the region for FDI inflows to increase. Increasing government rents from natural resources reduces FDI inflows in the SADC. Previous year flows of FDI are positively related to current year inflows, thus consistent FDI attraction policies in the SADC are important. Infrastructure in the SADC should be consistently improved to ensure suitability with the dynamic nature of foreign investment. Financial markets should be developed to ensure effective flow of capital and growth in economies through more investment. / Economics / D. Com.. (Economics)

Il existe une grande variabilité dans la réponse aux chimiothérapies anticancéreuses. Ses sources sont diverses: génétiques, physiologiques, comorbidités, médicaments associés, etc. La marge thérapeutique de ces médicaments étant généralement étroite, une telle variabilité peut avoir de graves conséquences: toxicités graves ou absence d'effet thérapeutique. Plusieurs approches pour adapter individuellement les posologies ont été proposées: a priori (basées sur l'information génétique, la taille corporelle, les fonctions d'élimination, etc.) et a posteriori (sur les informations de mesures d'exposition au médicament et/ou effets). La modélisation à effets-mixtes de la pharmacocinétique et de la pharmacodynamie (PK-PD), combinée avec une estimation bayésienne des effets individuels, est la meilleure méthode pour individualiser des schémas posologiques a posteriori. Dans cette thèse, une nouvelle approche pour ajuster les doses sur la base des prédictions données par un modèle pour les observations catégorielles de toxicité a été développée et explorée par simulation. Les aspects plus techniques concernant l'estimation des paramètres individuels ont été analysés pour déterminer les facteurs de bonne performance de la méthode. Ces travaux étaient basés sur l'exemple du syndrome mains-pieds induit par la capécitabine dans le traitement du cancer colorectal. Une revue des modèles pharmacodynamiques de données discrètes (catégorielles, de comptage, de survie) a été effectuée. Enfin, des analyses PK-PD de l'hydroxyurée dans le traitement de la drépanocytose ont été réalisées pour comparer des différentes posologies et déterminer les modalités optimales de suivi du traitement / There is high variability in response to cancer chemotherapies among patients. Its sources are diverse: genetic, physiologic, comorbidities, concomitant medications, environment, compliance, etc. As the therapeutic window of anticancer drugs is usually narrow, such variability may have serious consequences: severe (even life-threatening) toxicities or lack of therapeutic effect. Therefore, various approaches to individually tailor treatments and dosing regimens have been developed: a priori (based on genetic information, body size, drug elimination functions, etc.) and a posteriori (that is using information of measurements of drug exposure and/or effects). Mixed-effects modelling of pharmacokinetics and pharmacodynamics (PK-PD), combined with Bayesian maximum a posteriori probability estimation of individual effects, is the method of choice for a posteriori adjustments of dosing regimens. In this thesis, a novel approach to adjust the doses on the basis of predictions, given by a model for ordered categorical observations of toxicity, was developed and investigated by computer simulations. More technical aspects concerning the estimation of individual parameters were analysed to determine the factors of good performance of the method. These works were based on the example of capecitabine-induced hand-and-foot syndrome in the treatment of colorectal cancer. Moreover, a review of pharmacodynamic models for discrete data (categorical, count, time-to-event) was performed. Finally, PK-PD analyses of hydroxyurea in the treatment of sickle cell anemia were performed and used to compare different dosing regimens and determine the optimal measures for monitoring the treatment

Non-monetary deprivation indicators are now widely used for studying and measuring poverty in Europe. However, despite their prevalence, the empirical performance of existing deprivation scales has rarely been examined. This thesis i) identifies possible conceptual problems of existing deprivation scales such as indexing, missing dimensions and threshold; ii) empirically assesses the extent of possible error in measurement related to these conceptual problems; and iii) offer an alternative way for constructing deprivation measures to mitigate the identified conceptual problems. The thesis consists of four stand-alone papers, accompanied by an overarching introduction and conclusion. The first three papers provide empirical evidence on the empirical consequences of the missing dimensions and threshold problems for the measurement and analysis of poverty, while the fourth paper exemplifies a concept-led multidimensional design that can reduce the error introduced by these conceptual problems. The analysis is generally held for 25 EU countries using European Survey of Income and Living Conditions (EU-SILC); only in the second paper, the analysis is done for the UK using British Household Panel Survey (BHPS).

Available security standards for RFID networks (e.g. ISO/IEC 29167) are designed to secure individual tag-reader sessions and do not protect against active attacks that could also compromise the system as a whole (e.g. tag cloning or replay attacks). Proper traffic characterization models of the communication within an RFID network can lead to better understanding of operation under “normal” system state conditions and can consequently help identify security breaches not addressed by current standards. This study of RFID traffic characterization considers two piecewise-constant data smoothing techniques, namely Bayesian blocks and Knuth’s algorithms, over time-tagged events and compares them in the context of rate-based anomaly detection. This was accomplished using data from experimental RFID readings and comparing (1) the event counts versus time if using the smoothed curves versus empirical histograms of the raw data and (2) the threshold-dependent alert-rates based on inter-arrival times obtained if using the smoothed curves versus that of the raw data itself. Results indicate that both algorithms adequately model RFID traffic in which inter-event time statistics are stationary but that Bayesian blocks become superior for traffic in which such statistics experience abrupt changes.