O presente estudo compreendeu a caracterização dos estuários de Santos/São Vicente e Cananéia quanto aos processos naturais e antrópicos; e o estudo de traçadores biológicos - foraminíferos. Estas regiões foram escolhidas, sobretudo devido ao antagonismo no que tange o impacto antrópico e, ainda, à sua complexidade ambiental. Os resultados hidrogeoquímicos, nutrientes e concentração de metais confirmaram a maior influência humana no estuário de Santos/São Vicente, principalmente na área mais interna do sistema, em comparação com a baixa influência antropogênica do estuário de Cananéia. A distribuição dos foraminíferos bentônicos como traçadores do gradiente de tensão ecológica (natural e antrópica) foi discutida a partir da análise de amostras coletadas nos sedimentos superficiais dos estuários, comparando-se a fauna, porém, sem desconsiderar as divergências espaciais das áreas em questão. Amostras foram coletadas para realização de análise qualitativa e quantitativa, além da análise micrométrica das testas dos foraminíferos. Os resultados obtidos revelaram que a distribuição das associações de foraminíferos refletiu o padrão natural em Cananéia, no que diz respeito tanto a abundância quanto ao tamanho específico. Os dados biométricos revelaram que a região de Cananéia concentra os maiores diâmetros médios, que estão sempre associados com as campanhas de inverno. Tal fato evidencia que a matéria orgânica elevada no verão contribui para o aumento da população e não de tamanho médio de organismos. Isso demonstra um esforço reprodutivo que provavelmente visa aproveitar a disponibilidade de alimento do verão. Outros resultados pertinentes foram: estabelecimento das espécies Buliminella elegantissima e Pararotalia cananeiaensis em locais que não são correspondentes no que diz respeito às características ambientais, denotando a plasticidade destas espécies em traçar uma rota de transporte e estabelecimento, que geralmente está relacionado à deposição da matéria orgânica. A partir dos dados obtidos pode-se concluir que os foraminíferos se comportam de maneira singular, de acordo com o tensor que está regendo seu estabelecimento, e através da análise de sua distribuição, foi possível inferir se um tensor antrópico ou ambiental influenciou o estabelecimento de espécies de foraminíferos nos estuários de Santos e Cananéia. / This study had as a goal to characterize two estuaries, Santos/São Vicente and Cananéia, regarding to natural and anthropogenic parameters. Besides that, the biological trace elements - foraminiferal assemblage. The study has been held along the two estuarine areas, and both of them have shown bio-geographical patternal patches. These study areas were chosen in accordance with their antagonist impact approach and their environmental complexity. Among the advantages on developing studies that uses bioindicators to evaluate na environmental quality patterns, it is evident the large amount of experiments on the water and sediments that these areas are constantly under over than three decades. The hydrochemical results, organic content and heavy metal confirm the human influence at Santos estuary, mainly in the internal áreas, in comparison with the low rate anthropogenic influence from Cananéia estuary. Foraminiferal distribution as a ecológical tracer, both natural and human made, was discussed from sediment samples from both áreas, but always concerning about the oceanographic differences. Samples were picked up aldo to biometric analysis on the foraminiferal shells. Results show that foraminiferal distribution follows the natural patterns as the first way, both relating to abundance and size. Biometric data revealed that the largest diameter average was always associated with the winter samples. It is such evidence that the high level of organic matter contributes incrising the population, but no longer raising its diameter size. This is a sight for a reproductive effort in order to not miss out food availability during the summer. Another relevant result is: Buliminella elegantissima and Pararotalia cananeiaensis establishment in areas where they wouldnt normally settle down, denoting they do not correspond with the same variable in both study areas. This fact evidences the plasticity of these species on fitting different environment characteristic in order to establish and to reproduce. This is generally associated with organic matter deposition and makes foraminiferal distribution a singular pattern that allows determining a natural or an anthropogenic influence.

Este trabalho apresenta um estudo sobre os principais sistemas de segurança utilizados em instalações elétricas automatizadas, com enfoque no controle de acesso físico, utilizando tecnologias biométricas. São apresentadas neste trabalho as principais características dos sistemas de segurança aplicados à detecção e combate de incêndios, ao controle do acesso físico, ao controle interno e externo da segurança, como circuitos fechados de televisão e controle de segurança perimetral, e as tecnologias biométricas que podem ser usadas para o controle de acesso de pessoas. É apresentado o desenvolvimento de um protótipo de baixo custo, utilizando tecnologia biométrica para o controle de acesso físico, assim como as principais vantagens e desvantagens, algoritmos e relações custo-benefício para o uso de biometria em sistemas de segurança. O estudo mostra que o uso da biometria como ferramenta para a melhoria dos sistemas de segurança existentes é uma tendência mundial, no entanto, existe uma preocupação crescente sobre a confidencialidade das informações biométricas das pessoas. / This work presents a study of the main security systems used in automatized electric installations, with approach in the physical access control, using biometric technologies. The main characteristics of the security systems applied to the detection and fire combat, to the physical access control, to the internal and external security control, as closed-circuits television and perimetral security control, and the biometric technologies are presented in this work that can be used for the people access control. The development of a low cost prototype is presented, using biometric technology for the physical access control, as well as the main advantages and disadvantages, algorithms and cost-benefit relations for the use of biometry in security systems. The study shows that the use of the biometry as tool for the existing security systems improvement is a world-wide trend, however, an increasing concern exists of the people biometric information confidentiality.

Mobile devices, such as smartphones and wearable devices, have become a popular platform to deliver recommendations and interact with users. To learn the decision rule of assigning recommendations, i.e. policy, neither one homogeneous policy for all users nor completely heterogeneous policy for each user is appropriate. Many attempts have been made to learn a policy for making recommendations using observational mobile health (mHealth) data. The majority of them focuses on a homogeneous policy, that is a one-fit-to-all policy for all users. It is a fair starting point for mHealth study, but it ignores the underlying user heterogeneity. Users with similar behavior pattern may have unobservable underlying heterogeneity. To solve this problem, we develop a personalized learning framework that models both population and personalized effect simultaneously. In the first part of this dissertation, we address the personalized policy learning problem using longitudinal mHealth application usage data. Personalized policy represents a paradigm shift from developing a single policy that may prescribe personalized decisions by tailoring. Specifically, we aim to develop the best policy, one per user, based on estimating random effects under generalized linear mixed model. With many random effects, we consider new estimation method and penalized objective to circumvent high-dimensional integrals for marginal likelihood approximation. We establish consistency and optimality of our method with endogenous application usage. We apply our method to develop personalized prompt schedules in 294 application users, with a goal to maximize the prompt response rate given past application usage and other contextual factors. We found the best push schedule given the same covariates varied among the users, thus calling for personalized policies. Using the estimated personalized policies would have achieved a mean prompt response rate of 23% in these users at 16 weeks or later: this is a remarkable improvement on the observed rate (11%), while the literature suggests 3%-15% user engagement at 3 months after download. The proposed method compares favorably to existing estimation methods including using the R function glmer in a simulation study. In the second part of this dissertation, we aim to solve a practical problem in the mHealth area. Low response rate has been a major issue that blocks researchers from collecting high quality mHealth data. Therefore, developing a prompting system is important to keep user engagement and increase response rate. We aim to learn personalized prompting time for users in order to gain a high response rate. An extension of the personalized learning algorithm is applied on the Intellicare data that incorporates penalties of the population effect parameters and personalized effect parameters into learning the personalized decision rule of sending prompts. The number of personalized policy parameters increases with sample size. Since there is a large number of users in the Intellicare data, it is challenging to estimate such high dimensional parameters. To solve the computational issue, we employ a bagging method that first bootstraps subsamples and then ensembles parameters learned from each subsample. The analysis of Intellicare data shows that sending prompts at a personalized hour helps achieve a higher response rate compared to a one-fit-to-all prompting hour.

In population health, the study of unobserved, or latent, heterogeneity in longitudinal data may help inform public health interventions. Growth mixture modeling is a flexible tool for modeling latent heterogeneity in longitudinal data. However, the application of growth mixture models to certain data types, namely, complex survey data and electronic health records, is underdeveloped. For valid statistical inferences in complex survey data, features of the sample design must be incorporated into statistical analysis. In electronic health records, the application of growth mixture modeling is challenged by high levels of missing values. In this dissertation, I have three goals: First, I propose a Bayesian growth mixture model for complex survey data in which I directly incorporate features of the complex sample design. Second, I extend a Bayesian growth mixture model of multiple longitudinal health outcomes collected in electronic health records to a shared parameter model that can account for dierent missing data assumptions. Third, I develop open-source software packages in R for each method that can be used for model tting, selection, and checking.

Ultrasound is the primary modality for fetal imaging, but Magnetic Resonance Imaging nowadays has a valuable complementary role as it often reveals findings that alter pregnancy management. Knowledge on some clinically relevant areas of the normal fetal development is still lacking, and this was the aim of this project. We wanted 1) to obtain reference MRI data of normal brain measurements before 24 gestation weeks (GW), 2) to study the development of the hippocampus, 3) to study the development of the ear and 4) to test the ability of MRI for evaluating the lip and palate. For this, we retrospectively analysed a database with 464 in vivo and 21 post mortem fetal MRI examinations. Study I evaluated a series of 70 normal fetuses. A table of normal brain measurements from 17 to 23 GW was built, the first in the literature that includes ages below 20 GW. Study II focused on the evolution of the hippocampus from 18 to 38 GW by evaluating 3 post mortem and 60 in vivo MRI examinations. Our results suggested this area to develop later and more asymmetrically than previously thought. Study III analysed a series of 122 normal MRI in vivo and 16 MRI post mortem. We described the development of the fetal ear in vivo for the first time in the literature, realizing that the value of MRI is limited by the size of the structures evaluated. In study IV, 60 brain-targeted MRI examinations of 55 normal fetuses and 5 fetuses with orofacial clefts were blindly reviewed by two readers, focusing on the lips and palates. Our results suggest a high accuracy of MRI in the evaluation of this area, regardless of fetal age or previous ultrasound findings. This thesis brings new knowledge on the normal development of the fetal brain and cranium.

published_or_final_version / Industrial Engineering / Master / Master of Philosophy

The study was aimed to estimate biological changes in segetal flora in spring barley agrophytocenoses differing in weed suppressive ability. Research subject – spring barley varieties of different stem height (tall-stemmed, of moderate height, short-stemmed) and annual weeds. Research tasks: 1. To estimate yield forming elements of spring barley: emergence, tillering, biomass growth, plant height, and leaf area index. 2. To study weed suppressive ability of tall-stemmed, of moderate height, and short-stemmed spring barley. 3. To assess biological changes in annual weeds growing in different competition environments under field and greenhouse conditions. 4. By relating spring barley and weed growth indicators, to estimate factors (weed suppressive ability of spring barley as influenced by stand density and sowing time) exerting a significant effect on crop-weed competition in an agrophytocenose. / Įvertinti segetalinės floros biologinius pokyčius skirtingo konkurencingumo vasarinių miežių agrofitocenozėje. Tyrimų objektas – vasarinių miežių aukštaūgiai, vidutinio aukščio, žemaūgiai augalai ir trumpaamžės piktžolės. Tyrimų uždaviniai: 1. Įvertinti vasarinių miežių derlių formuojančius elementus: augalų sudygimą, krūmijimąsi, žaliosios masės priaugimą, aukštį ir lapų ploto indeksą (LAI). 2. Ištirti aukštaūgių, vidutinio aukščio ir žemaūgių vasarinių miežių augalų gebą konkuruoti su piktžolėmis. 3. Įvertinti trumpaamžių piktžolių, augančių skirtingomis konkurencijos sąlygomis, biologinius pokyčius lauko ir šiltnamio sąlygomis. 4. Siejant vasarinių miežių ir piktžolių augimo rodiklius, įvertinti veiksnius (skirtingo konkurencingumo veisles ir nevienodą pasėlio tankumą bei vasarinių miežių sėjos laiką), turinčius esminės įtakos augalų konkurencijai agrofitocenozėje.

The analysis of longitudinal binary data can be undertaken using any of the three families of models namely, marginal, random effects and conditional models. Each family of models has its own respective merits and demerits. The models are applied in the analysis of binary longitudinal data for childhood disease data namely the Respiratory Syncytial Virus (RSV) data collected from a study in Kilifi, coastal Kenya. The marginal model was fitted using generalized estimating equations (GEE). The random effects models were fitted using ‘Proc GLIMMIX’ and ‘NLMIXED’ in SAS and then again in Genstat. Because the data is a state transition type of data with the Markovian property the conditional model was used to capture the dependence of the current response to the previous response which is known as the history. The data set has two main complicating issues. Firstly, there is the question of developing a stochastically based probability model for the disease process. In the current work we use direct likelihood and generalized linear modelling (GLM) approaches to estimate important disease parameters. The force of infection and the recovery rate are the key parameters of interest. The findings of the current work are consistent and in agreement with those in White et al. (2003). The aspect of time dependence on the RSV disease is also highlighted in the thesis by fitting monthly piecewise models for both parameters. Secondly, there is the issue of incomplete data in the analysis of longitudinal data. Commonly used methods to analyze incomplete longitudinal data include the well known available case analysis (AC) and last observation carried forward (LOCF). However, these methods rely on strong assumptions such as missing completely at random (MCAR) for AC analysis and unchanging profile after dropout for LOCF analysis. Such assumptions are too strong to generally hold. In recent years, methods of analyzing incomplete longitudinal data have become available with weaker assumptions, such as missing at random (MAR). Thus we make use of multiple imputation via chained equations that require the MAR assumption and maximum likelihood methods that result in the missing data mechanism becoming ignorable as soon as it is MAR. Thus we are faced with the problem of incomplete repeated non–normal data suggesting the use of at least the Generalized Linear Mixed Model (GLMM) to account for natural individual heterogeneity. The comparison of the parameter estimates using the different methods to handle the dropout is strongly emphasized in order to evaluate the advantages of the different methods and approaches. The survival analysis approach was also utilized to model the data due to the presence of multiple events per subject and the time between these events. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermarizburg, 2008.

Estimation of current levels of human immunodeficiency virus (HIV) incidence is essential for monitoring the impact of an epidemic, determining public health priorities, assessing the impact of interventions and for planning purposes. However, there is often insufficient data on incidence as compared to prevalence. A direct approach is to estimate incidence from longitudinal cohort studies. Although this approach can provide direct and unbiased measure of incidence for settings where the study is conducted, it is often too expensive and time consuming. An alternative approach is to estimate incidence from cross sectional survey using biomarkers that distinguish between recent and non-recent/longstanding infections. The original biomarker based approach proposes the detection of HIV-1 p24 antigen in the pre-seroconversion period to identify persons with acute infection for estimating HIV incidence. However, this approach requires large sample sizes in order to obtain reliable estimates of HIV incidence because the duration of antigenemia before antibody detection is short, about 22.5 days. Subsequently, another method that involves dual antibody testing system was developed. In stage one, a sensitive test is used to diagnose HIV infection and a less sensitive test such is used in the second stage to distinguish between long standing infections and recent infections among those who tested positive for HIV in stage one. The question is: how do we combine this data with other relevant information, such as the period an individual takes from being undetectable by a less sensitive test to being detectable, to estimate incidence? The main objective of this thesis is therefore to develop likelihood based method that can be used to estimate HIV incidence when data is derived from cross sectional surveys and the disease classification is achieved by combining two biomarker or assay tests. The thesis builds on the dual antibody testing approach and extends the statistical framework that uses the multinomial distribution to derive the maximum likelihood estimators of HIV incidence for different settings. In order to improve incidence estimation, we develop a model for estimating HIV incidence that incorporate information on the previous or past prevalence and derive maximum likelihood estimators of incidence assuming incidence density is constant over a specified period. Later, we extend the method to settings where a proportion of subjects remain non-reactive to a less sensitive test long after seroconversion. Diagnostic tests used to determine recent infections are prone to errors. To address this problem, we considered a method that simultaneously makes adjustment for sensitivity and specificity. In addition, we also showed that sensitivity is similar to the proportion of subjects who eventually transit the “recent infection” state. We also relax the assumption of constant incidence density by proposing linear incidence density to accommodate settings where incidence might be declining or increasing. We extend the standard adjusted model for estimating incidence to settings where some subjects who tested positive for HIV antibodies were not tested by a less sensitive test resulting in missing outcome data. Models for the risk factors (covariates) of HIV incidence are considered in the last but one chapter. We used data from Botswana AIDS Impact (BAIS) III of 2008 to illustrate the proposed methods. The general conclusion and recommendations for future work are provided in the final chapter. / Theses (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2013.

In recent times, there has been an increase in national security awareness with a focus on improving current practices relating to the identification and verification of individuals and the reduction of identity fraud. One tool that has been found to assist in these areas is biometrics. This thesis examines some biometric technologies that may be potentially suitable for surveillance and access control applications, and shows why facial recognition technology has been the focus of this study. Despite the testing reported in the literature discussing attempts to solve the problems with facial recognition operational performance, facial recognition has not been widely implemented in security applications to date. The reported testing regimes vary in terms of the date of testing, methodology used for the study, evaluation type, test size and the extent to which possible variations of each variable were examined. To summarise what is known about the effect each variable has on performance, a baseline model of variables together with a ranking scheme is defined and utilised to create a starting point for the research. The research described in this thesis focuses on how to improve the operational performance of two dimensional facial recognition systems by building upon the baseline model of variables and by better understanding how the variables affect facial recognition performance. To improve on the baseline model, systems engineering techniques are used to identify the functional components of a generic facial recognition system, the relationships between them, and the variables that affect those relationships. This identifies other variables that may affect performance. In order to determine which variables affect performance, and how, a series of technical, scenario and operational experiments are conducted to test a selection of the variables. It is shown that this results in a greater understanding of how facial recognition systems react to different variables in operational environments. A revised model of ranked variables is produced that can then be used by current and prospective stakeholders of biometric systems, system designers, integrators and testers to ensure that the majority of the variables are considered when designing, installing, commissioning, or testing facial recognition systems. The findings of this research can also be used to critically analyse existing facial recognition system implementations in order to identify areas where performance increases are possible. This is confirmed in part throughout the two year testing phase of this research where data collected from initial experiments were used as a starting point to improve the performance of later operational experiments. Finally, this thesis identifies that the revised model of variables is sufficiently generic to be used as a starting point for analysing a system using any biometric technology. This is supported by using iris recognition technology as a test case. It is anticipated that with an increased knowledge of how some systems are affected by certain variables, and by better controlling those variables, an increase in performance is possible for access control and surveillance security applications that utilise biometric technologies. / thesis (PhDElectronicSystemsEngineering)--University of South Australia, 2005.