This thesis presents a Bayesian approach to incorporate historical data. Usually, in statistical inference, a large data size is required to establish a strong evidence. However, in most bioassay experiments, dataset is of limited size. Here, we proposed a method that is able to incorporate control groups data from historical studies. The approach is framed in the context of testing whether an increased dosage of the chemical is associated with increased probability of the adverse event. To test whether such a relationship exists, the proposed approach compares two logit models via Bayes factor. In particular, we eliminate the effect of survival time by using poly-k test. We test the performance of the proposed approach by applying it to six simulated scenarios. / Thesis / Master of Science (MSc) / This thesis presents a Bayesian approach to incorporate historical data. Usually, in statistical inference, a large data size is required to establish a strong evidence. However, in most bioassay experiments, dataset is of limited size. Here, we proposed a method that is able to incorporate control groups data from historical studies. The approach is framed in the context of testing whether an increased dosage of the chemical is associated with increased probability of the adverse event. To test whether such a relationship exists, the proposed approach compares two logit models via Bayes factor. In particular, we eliminate the effect of survival time by using poly-k test. We test the performance of the proposed approach by applying it to six simulated scenarios.

The overall objective of this thesis is to compare and contrast alternative measures of wellbeing in New Zealand during the 19th -early 20th centuries from a spatial perspective by collecting, collating and analyzing new economic, social and anthropometric data. Provincial data was collected from the Statistics New Zealand Annual Reports and New Zealand Census. Anthropometric data was derived from the personnel records of New Zealanders serving in WWI, which only became available to the public in 2005. Time-series tests for convergence and causality have been applied to analyze New Zealand’s economic history, where appropriate. The last quarter of the 19th century in New Zealand was a period of rapid change both in terms of economic and demographic indicators. Prior to the universal convergence of the existing monetary-based measures of wellbeing across Provinces, there were some apparent disparities in the commodity price and real wage series, as well as urban-rural differences in occupation-specific real wages and infant mortality trends. There was also no single pattern of stature decline across provinces during 1871-1898, or between urban and rural areas, where disparities were particularly apparent. The traditional view of the healthy and wealthy New Zealand could only be established at an aggregate level, during a certain time period and for a certain ethnic group (New Zealand European only). Using Provincial data for the period 1874-1919 I have been able to show that improvements in real wages and a decrease in education inequality (between females and males) corresponded to lower infant deaths and thus better health outcomes, while increased dwelling density created unfavorable conditions for infants’ chances of survival. Anthropometric data was used in conjunction with socio-economic provincial data to establish the relationship between stature, urbanization, real wages and infant mortality. The results showed that dwelling density (overcrowding) and general economic conditions were both important in determining stature outcomes during 1870-1900, while the effect of infant mortality on stature was negligible. Most importantly, it has been demonstrated that in New Zealand stature represents a much more robust measure of living standards than real wages or health indicators on their own, at least during the 1870-1900 period.

The aim of this research is to propose an alternative approach to determine the maintainability prediction for aircraft components. In this research, the author looks at certain areas of the maintainability prediction process where missteps or misapplications most commonly occur. The first of these is during the early stage of the Design for Maintainability (DfMt) process. The author discovered the importance of utilising historical information or feedback information. The second area is during the maintainability prediction where the maintenance of components is quantified; here, the author proposes having the maximum target for each individual maintainability component. This research attempts to utilise aircraft maintenance historical data and information (i.e. feedback information systems). Aircraft feedback information contains various types of information that could be used for future improvement rather than just the failure elements. Literature shows that feedback information such as Service Difficulty Reporting System (SDRS) and Air Accidents Investigation Branch, (AAIB) reports have helped to identify the critical and sensitive components that need more attention for further improvement. This research consists of two elements. The first is to identity and analyse historical data. The second is to identify existing maintainability prediction methodologies and propose an improved methodology. The 10 years’ data from Federal Aviation Administration (FAA) SDRS data of all aircraft were collected and analysed in accordance with the proposed methodology before the processes of maintainability allocation and prediction were carried out. The maintainability was predicted to identify the potential task time for each individual aircraft component. The predicted tasks time in this research has to be in accordance with industrial real tasks time were possible. One of the identified solutions is by using maintainability allocation methodology. The existing maintainability allocation methodology was improved, tested, and validated by using several case studies. The outcomes were found to be very successful. Overall, this research has proposed a new methodology for maintainability prediction by integrating two important elements: historical data information, and maintainability allocation. The study shows that the aircraft maintenance related feedback information systems analyses were very useful for deciding maintainabilityeffectiveness; these include planning, organising maintenance and design improvement. There is no doubt that historical data information has the ability to contribute an important role in design activities. The results also show that maintainability is an importance measure that can be used as a guideline for managing efforts made for the improvement of aircraft components.

Obstacles sometimes limit enrollment in randomized clinical trials of an exper- imental product versus an active control, making it desirable to augment the ran- domized control group with historical control groups. However, bias between control groups with respect to the mean outcome could lead to spurious conclusions. Meth- ods are necessary that allow for the combination of control groups while controlling for bias. Pocock (1976) developed a Bayesian test to address this need, but it requires sub- jective specification of the variance of the bias between the randomized and historical control groups and is designed to include only a single historical control group. In the context of an actively controlled non-inferiority trial, we extend his method on three fronts. First, we replace subjective specification of the variance of the bias with empirically driven estimates. Second, we develop an adaptive design that re-powers a trial based on an interim estimate of the variance of the bias using observed data. Third, we modify the test to include multiple historical control groups. When including a single historical control group, simulations show that the true bias, if known, can be used in place of the variance of the bias, and that this estimate ivmaintains Type I Error with no loss in power as compared to using the true variance of the bias. Further, we show that using an empirical estimate of the bias to estimate the variance of bias may result in moderately inflated Type I Error, but that using a conservative estimate of the bias (the upper bound of a 90% confidence interval) maintains Type I Error. Simulations also demonstrate that using an estimate of the bias at the interim and conclusion provides designed power but may result in moder- ately inflated Type I Error. Therefore, a conservative estimate of the bias should be used at trial end when using this approach. Lastly, it is shown that if an adequate number of multiple historical control groups are available, the modified test maintains Type I Error when using bias estimates. These methods provide objective guidance on parameter estimation, but further research is necessary in order to improve power.

Today, when businesses and organizations are generating huge volumes of data; the applications like Web 2.0 or social networking requires processing of petabytes of data. Stock Exchange Systems are among the ones that process large amount of quotes and trades on a daily basis. The limited database storage ability is a major bottleneck in meeting up the challenge of providing efficient access to information. Further to this, varying data are the major source of information for the financial industry. This data needs to be read and written efficiently in the database; this is quite costly when it comes to traditional Relational Database Management System. RDBMS is good for different scenarios and can handle certain types of data very well, but it isn’t always the perfect choice. The existence of innovative architectures allows the storage of large data in an efficient manner. “Not only SQL” brings an effective solution through the provision of an efficient information storage capability. NOSQL is an umbrella term for various new data store. The NOSQL databases have gained popularity due to different factors that include their open source nature, existence of non-relational data store, high-performance, fault-tolerance, and scalability to name a few. Nowadays, NOSQL databases are rapidly gaining popularity because of the advantages that they offer compared to RDBMS. The major aim of this research is to find an efficient solution for storing and processing the huge volume of data for certain variants. The study is based on choosing a reliable, distributed, and efficient NOSQL database at Cinnober Financial Technology AB. The research majorly explores NOSQL databases and discusses issues with RDBMS; eventually selecting a database, which is best suited for financial data management. It is an attempt to contribute the current research in the field of NOSQL databases which compares one such NOSQL database Apache Cassandra with Apache Lucene and the traditional relational database MySQL for financial management. The main focus is to find out which database is the preferred choice for different variants. In this regard, the performance test framework for a selected set of candidates has also been taken into consideration.

The aim of this research is to propose an alternative approach to determine the maintainability prediction for aircraft components. In this research, the author looks at certain areas of the maintainability prediction process where missteps or misapplications most commonly occur. The first of these is during the early stage of the Design for Maintainability (DfMt) process. The author discovered the importance of utilising historical information or feedback information. The second area is during the maintainability prediction where the maintenance of components is quantified; here, the author proposes having the maximum target for each individual maintainability component. This research attempts to utilise aircraft maintenance historical data and information (i.e. feedback information systems). Aircraft feedback information contains various types of information that could be used for future improvement rather than just the failure elements. Literature shows that feedback information such as Service Difficulty Reporting System (SDRS) and Air Accidents Investigation Branch, (AAIB) reports have helped to identify the critical and sensitive components that need more attention for further improvement. This research consists of two elements. The first is to identity and analyse historical data. The second is to identify existing maintainability prediction methodologies and propose an improved methodology. The 10 years’ data from Federal Aviation Administration (FAA) SDRS data of all aircraft were collected and analysed in accordance with the proposed methodology before the processes of maintainability allocation and prediction were carried out. The maintainability was predicted to identify the potential task time for each individual aircraft component. The predicted tasks time in this research has to be in accordance with industrial real tasks time were possible. One of the identified solutions is by using maintainability allocation methodology. The existing maintainability allocation methodology was improved, tested, and validated by using several case studies. The outcomes were found to be very successful. Overall, this research has proposed a new methodology for maintainability prediction by integrating two important elements: historical data information, and maintainability allocation. The study shows that the aircraft maintenance related feedback information systems analyses were very useful for deciding maintainabilityeffectiveness; these include planning, organising maintenance and design improvement. There is no doubt that historical data information has the ability to contribute an important role in design activities. The results also show that maintainability is an importance measure that can be used as a guideline for managing efforts made for the improvement of aircraft components.

This research is motivated by an issue frequently encountered in environmental water quality evaluation. Many times, the sample size of water monitoring data is too small to have adequate power. Here, we present a Bayesian power prior approach by incorporating the current data and historical data and/or the data collected at neighboring stations to make stronger statistical inferences on the parameters of interest. The elicitation of power prior distributions is based on the availability of historical data, and is realized by raising the likelihood function of the historical data to a fractional power. The power prior Bayesian analysis has been proven to be a useful class of informative priors in Bayesian inference. In this dissertation, we propose a modified approach to constructing the joint power prior distribution for the parameter of interest and the power parameter. The power parameter, in this modified approach, quantifies the heterogeneity between current and historical data automatically, and hence controls the influence of historical data on the current study in a sensible way. In addition, the modified power prior needs little to ensure its propriety. The properties of the modified power prior and its posterior distribution are examined for the Bernoulli and normal populations. The modified and the original power prior approaches are compared empirically in terms of the mean squared error (MSE) of parameter estimates as well as the behavior of the power parameter. Furthermore, the extension of the modified power prior to multiple historical data sets is discussed, followed by its comparison with the random effects model. Several sets of water quality data are studied in this dissertation to illustrate the implementation of the modified power prior approach with normal and Bernoulli models. Since the power prior method uses information from sources other than current data, it has advantages in terms of power and estimation precision for decisions with small sample sizes, relative to methods that ignore prior information. / Ph. D.

O objetivo desta tese é identificar e descrever variações espacial, sazonal e multidecadal, com dados históricos, e padrões ecológicos locais na ictiofauna do estuário Cananéia-Iguape (ECI) em relação a fatores ecológicos naturais e/ou aqueles induzidos pelo aporte exógeno do rio Ribeira de Iguape (RI) através do canal artificial Valo Grande (VG). Demonstrou-se a relação de atributos hidrológicos, sazonalidade e espacialidade com a estruturação da diversidade da assembléia no infralitoral inconsolidado em escala local (i.e. dentro de um setor estuarino do ECI, a baía do Trapandé) utilizando delineamento amostral espacial e sazonalmente estratificado com amostragens mensais (julho/2009 junho/2010) com rede otter-trawl. Identificaram-se dois padrões locais na estrutura da assembleia: persistência sazonal de maior riqueza e abundância no interior (ambientalmente favorável) do que foz da baía (hidrodinamicamente instável) e variabilidade dessa estrutura espacial pelo efeito da interação entre profundidade, temperatura e ritmos sazonais populacionais. O ECI abrigou 246 espécies entre 1962 e 2010 e 214 entre 1993 e 2010. De acordo com extrapoladores matemáticos, há mais de 173 espécies no habitat demersal do eixo sul. Durante o período chuvoso, riqueza e abundância na ictiofauna do eixo sul aumentam com o incremento do recrutamento e agregações reprodutivas, estimuladas pelo pico de produtividade no ECI, e das migrações massivas à jusante, devido à forte redução das condições estuarinas no eixo norte. Propõe-se uma metacomunidade organizada por efeitos de massa entre a assembleia da baía do Trapandé e o pool regional de populações marinhas. A degradação das condições estuarinas pelo aporte do RI limitou a dispersão de espécies estuarino-residentes e marinho-migrantes no ECI. Isso determinou um gradiente espacial de perda generalizada de abundância, riqueza e diversidade funcional acompanhando consistentemente o gradiente espacial de impacto. O sinal desse efeito antrópico foi suficientemente elevado para ser detectado mesmo sob interferência de outras fontes de variabilidade espacial, temporal e ambiental. A redução da vazão do RI ao ECI para sua recuperação ecológica, estabelecida pelas autoridades governamentais, é uma medida que também restaurará a dispersão multiespecífica e, assim, a funcionalidade ecossistêmica da ictiofauna / The aim of the present thesis is to identify and describe spatial, seasonal, and multidecadal variations, by using historical data, and local ecological patterns in the fish fauna of the Cananéia-Iguape Estuary (ECI) in relation to ecological factors and/or factors derived from the exogenous discharge of the Ribeira de Iguape River (RI) flowing through the Valo Grande artificial channel. It was demonstrated the relation of hydrological attributes, seasonality, and spatiality with the beta diversity of the soft bottom infralitoral fish assemblage in local scale (i.e. within an ECI estuarine sector, the Trapandé Bay) with a seasonally and spatially stratified sampling design and monthly sampling (July/2009 June/2010) using otter-trawl net. Two patterns were identified: (I) fish species richness and abundance were higher and seasonally persistent in inner (environmentally favorable habitat) than in outer sector of bay; and (II) a variability of this fish faunas spatial structure induced by the effect of the interaction among depth, water temperature, and seasonal rhythms of fish populations. ECI hold 246 fish species between 1962 and 2010 and 214 species between 1993 and 2010. Mathematic extrapolators estimated > 173 species in the south axis of ECI. In rainy season, fish species richness and abundance in south axis increase with increasing (I) massive immigration of individuals from north axis of ECI due to the highest RI discharge and lowest salinity; (II) massive recruitments and reproductive aggregations and activities, which are coupled with the peak of primary and secondary productivity in ECI. It is proposed the existence of a metacommunity ruled by mass effect between assemblage of Trapandé bay and regional pool of marine populations. The degradation of ECIs estuarine conditions due to RI inflow limited multispecific dispersion among resident estuarine and marine species. This resulted in a spatial gradient of generalized loss in abundance, richness, and function in the fish fauna structure that strongly follow the spatial gradient of impact. The signal of this anthropogenic effect was enough high to be revealed even under interference from other sources of environmental, spatial, and temporal variability. The reduction of RI inflow to ECI in order to recover its ecological estuarine conditions is a governmental authorities correct decision to also recover the fish dispersion and, thus, the ecosystem functionality of fish fauna

O objetivo desta tese é identificar e descrever variações espacial, sazonal e multidecadal, com dados históricos, e padrões ecológicos locais na ictiofauna do estuário Cananéia-Iguape (ECI) em relação a fatores ecológicos naturais e/ou aqueles induzidos pelo aporte exógeno do rio Ribeira de Iguape (RI) através do canal artificial Valo Grande (VG). Demonstrou-se a relação de atributos hidrológicos, sazonalidade e espacialidade com a estruturação da diversidade da assembléia no infralitoral inconsolidado em escala local (i.e. dentro de um setor estuarino do ECI, a baía do Trapandé) utilizando delineamento amostral espacial e sazonalmente estratificado com amostragens mensais (julho/2009 junho/2010) com rede otter-trawl. Identificaram-se dois padrões locais na estrutura da assembleia: persistência sazonal de maior riqueza e abundância no interior (ambientalmente favorável) do que foz da baía (hidrodinamicamente instável) e variabilidade dessa estrutura espacial pelo efeito da interação entre profundidade, temperatura e ritmos sazonais populacionais. O ECI abrigou 246 espécies entre 1962 e 2010 e 214 entre 1993 e 2010. De acordo com extrapoladores matemáticos, há mais de 173 espécies no habitat demersal do eixo sul. Durante o período chuvoso, riqueza e abundância na ictiofauna do eixo sul aumentam com o incremento do recrutamento e agregações reprodutivas, estimuladas pelo pico de produtividade no ECI, e das migrações massivas à jusante, devido à forte redução das condições estuarinas no eixo norte. Propõe-se uma metacomunidade organizada por efeitos de massa entre a assembleia da baía do Trapandé e o pool regional de populações marinhas. A degradação das condições estuarinas pelo aporte do RI limitou a dispersão de espécies estuarino-residentes e marinho-migrantes no ECI. Isso determinou um gradiente espacial de perda generalizada de abundância, riqueza e diversidade funcional acompanhando consistentemente o gradiente espacial de impacto. O sinal desse efeito antrópico foi suficientemente elevado para ser detectado mesmo sob interferência de outras fontes de variabilidade espacial, temporal e ambiental. A redução da vazão do RI ao ECI para sua recuperação ecológica, estabelecida pelas autoridades governamentais, é uma medida que também restaurará a dispersão multiespecífica e, assim, a funcionalidade ecossistêmica da ictiofauna / The aim of the present thesis is to identify and describe spatial, seasonal, and multidecadal variations, by using historical data, and local ecological patterns in the fish fauna of the Cananéia-Iguape Estuary (ECI) in relation to ecological factors and/or factors derived from the exogenous discharge of the Ribeira de Iguape River (RI) flowing through the Valo Grande artificial channel. It was demonstrated the relation of hydrological attributes, seasonality, and spatiality with the beta diversity of the soft bottom infralitoral fish assemblage in local scale (i.e. within an ECI estuarine sector, the Trapandé Bay) with a seasonally and spatially stratified sampling design and monthly sampling (July/2009 June/2010) using otter-trawl net. Two patterns were identified: (I) fish species richness and abundance were higher and seasonally persistent in inner (environmentally favorable habitat) than in outer sector of bay; and (II) a variability of this fish faunas spatial structure induced by the effect of the interaction among depth, water temperature, and seasonal rhythms of fish populations. ECI hold 246 fish species between 1962 and 2010 and 214 species between 1993 and 2010. Mathematic extrapolators estimated > 173 species in the south axis of ECI. In rainy season, fish species richness and abundance in south axis increase with increasing (I) massive immigration of individuals from north axis of ECI due to the highest RI discharge and lowest salinity; (II) massive recruitments and reproductive aggregations and activities, which are coupled with the peak of primary and secondary productivity in ECI. It is proposed the existence of a metacommunity ruled by mass effect between assemblage of Trapandé bay and regional pool of marine populations. The degradation of ECIs estuarine conditions due to RI inflow limited multispecific dispersion among resident estuarine and marine species. This resulted in a spatial gradient of generalized loss in abundance, richness, and function in the fish fauna structure that strongly follow the spatial gradient of impact. The signal of this anthropogenic effect was enough high to be revealed even under interference from other sources of environmental, spatial, and temporal variability. The reduction of RI inflow to ECI in order to recover its ecological estuarine conditions is a governmental authorities correct decision to also recover the fish dispersion and, thus, the ecosystem functionality of fish fauna

Wireless Sensor Networks (WSNs) are deployed widely for various applications. A variety of useful data are generated by these deployments. Since WSNs have limited resources and unreliable communication links, traditional data management techniques are not suitable. Therefore, designing effective data management techniques for WSNs becomes important. In this dissertation, we address three key issues of data management in WSNs. For data collection, a scheme of making some nodes sleep and estimating their values according to the other active nodes’ readings has been proved energy-efficient. For the purpose of improving the precision of estimation, we propose two powerful estimation models, Data Estimation using a Physical Model (DEPM) and Data Estimation using a Statistical Model (DESM). Most of existing data processing approaches of WSNs are real-time. However, historical data of WSNs are also significant for various applications. No previous study has specifically addressed distributed historical data query processing. We propose an Index based Historical Data Query Processing scheme which stores historical data locally and processes queries energy-efficiently by using a distributed index tree. Area query processing is significant for various applications of WSNs. No previous study has specifically addressed this issue. We propose an energy-efficient in-network area query processing scheme. In our scheme, we use an intelligent method (Grid lists) to describe an area, thus reducing the communication cost and dropping useless data as early as possible. With a thorough simulation study, it is shown that our schemes are effective and energy- efficient. Based on the area query processing algorithm, an Intelligent Monitoring System is designed to detect various events and provide real-time and accurate information for escaping, rescuing, and evacuation when a dangerous event happened.