This thesis presents a novel distributed control method which allows a collection of independently mobile robotic units, with two or three dimensional movement, to self-assemble into self-repairing hierarchical structures. The proposed method utilises a simple model of the cellular adhesion mechanisms observed in biological cells, allowing the robotic units to form virtually bonded aggregates which behave as predicted by Steinberg’s differential adhesion hypothesis. Simulated robotic units based on the design of the subaquatic HYDRON module are introduced as a possible platform on which the model can be implemented. The units are used to carry out a detailed investigation of the model behaviour and parameter space focusing on the two main tasks of rounding and sorting in both two and three dimensions. These tasks assess the model’s ability to reach a thermodynamically stable configuration when the aggregates consist of either a single population of units or multiple populations of units with differing adhesive properties. The results are analysed in detail with particular attention given to the role of random movements in determining the overall performance, and demonstrate that this model provides a very robust solution to these complex tasks. Finally, a possible extension of this work is presented in which the original model is combined with a genetic regulatory network controller. The performance of this composite is evaluated, and the benefits of this hybrid approach, in which a powerful control system manipulates a robust self-organising behaviour, are discussed.

Approved for public release; distribution in unlimited. / Some battlefield models have a component in them which models the time it takes for an observer to detect a target. Different observers may have different mean detection times due to various factors such as the type of sensor used, environmental conditions, fatigue of the observer, etc. Two parametric models for the distribution of time to target detection are considered which can incorporate these factors. Maximum likelihood estimation procedures for the parameters are described. Results of simulation experiments to study the small sample behavior of the estimators are presented. / http://archive.org/details/modelsfortargetd00baed / Major, Korean Air Force

Hierarchical materials offer great promise for high-performance sensors and catalysis carriers. Well-defined hierarchically porous materials are promising candidates for a wide range of applications relating to biosensors, separations, drug delivery, surface-enhanced Raman scattering (SERS), etc. Research on synthetic methodologies is expanding. However, fabrication of hierarchical porous structures with tunable pore dimension and shape, controllable pore distribution and interconnectivity is still a challenging task in materials science. One of the main tasks of this work is to establish a facile and reliable approach of making well-defined hierarchically porous materials. Then, based on those multimodal porous structures, different functions and applications can be realized. This work utilizes a direct hard templating method to obtain hierarchical porous structures with a well-defined bimodal distribution of the pores based on hierarchical templates. The hierarchical templates were prepared by synthetically joining appropriately functionalized commercially available polystyrene (PS) latex spheres together. Two different coupling reactions were used to form the hierarchical templates: carbodiimide-assisted coupling of COOH groups with NH2 groups and base-assisted coupling of epoxy groups with NH2 groups. Two different morphologies of templates, "raspberry-like" and "strawberry-like" were made. The template can be defined by the sizes of both the "core" and the "satellite" spheres, and altering the coverage of "satellites" on the "core". The main advantage of this strategy is the tailorability of the size and shape of the hierarchical templates, which allows an easy and independent adjustment to the multiporosity of the material structure design. Also, the monodispersed hierarchical templates are constructed of only one material, can be isolated, and can be assembled using standard template packing procedures that have been used for unimodal porous material fabrication described in published literature. Based on the predefined monodispersed hierarchical templates, multimodal porous silica, bimodal porous gold film and porous capsules were fabricated in this work as representative 3D, 2D, and 0D hierarchical porous structures, respectively. Because the template was predefined as one whole body, the connectivity between the big pores and small pores is guaranteed. The way the templates are packed together on a surface also ensures connections between each "template-shaped pore cluster". The uniform interconnectivity and ordered arrangement among the pores allows the different modals of pores to communicate with each other. The different hierarchical porous materials made in this work were characterized with SEM, TEM, AFM, XPS, STEM, gas adsorption, and mercury intrusion porosity. The results indicate that the multimodal porous materials can be successfully fabricated using predefined hierarchical templates. The different arrangement (3D, 2D, 0D) of those templates and the independent tailorability of the pore sizes provide more flexibility and control on the hierarchical porous material fabrication. The main parts of this work are as follows: (1) Fabrication and characterization of morphology controllable hierarchical templates (2) Fabrication and characterization of various multimodal porous structures of different materials based on the obtained templates (3) Study of the application of hierarchical porous gold electrode obtained and (4) The comparison between conventional porous structures and hierarchical porous structures.

Cloud computing is nowadays a popular computing paradigm. Computers are interconnected via network and jointly offer a lot of computing performance. SOFA 2 is a hierarchical component system offering a distributed run-time environment; therefore, it is a suitable environment for cloud computing. Applications are composed from components; each component may run on different computer in the `cloud'. The deployment of the components influences the overall performance of the application and the utilization of resources in the `cloud'; therefore, it has to be planned carefully. In this thesis, an algorithm for automated deployment planning of hierarchical component-based applications is proposed and further implemented in the SOFA 2 system. The algorithm incorporates components' demands and machines' resources in order to maximize performance of the deployed applications. The thesis also proposes and implements extensions that allow using the SOFA 2 component system as an actual cloud platform.

In the wake of rising energy costs, there is a critical need for sustainable energy management of commercial and residential buildings. Buildings consume approximately 40% of total energy consumed in the US, and current methods to reduce this level of consumption include energy monitoring, smart sensing, and advanced integrated building control. However, the building industry has been slow to replace current PID and rule-based control strategies with more advanced strategies such as model-based building control. This is largely due to the additional cost of accurately modeling the dynamics of the building and the general uncertainty that model-based controllers can be reliably used in real conditions. The first half of this thesis addresses the challenge of constructing accurate grey-box building models for control using model identification. Current identification methods poorly estimate building model parameters because of the complexity of the building model structure, and fail to do so quickly because these methods are not scalable for large buildings. Therefore, we introduce the notion of parameter identifiability to determine those parameters in the building model that may not be accurately estimated and we use this information to strategically improve the identifiability of the building model. Finally, we present a decentralized identification scheme to reduce the computational effort and time needed to identify large buildings. The second half of this thesis discusses the challenge of using uncertain building models to reliably control building temperature. Under real conditions, building models may not match the dynamics of the building, which directly causes increased building energy consumption and poor thermal comfort. To reduce the impact of model uncertainty on building control, we pose the model-based building control problem as a robust control problem using well-known H1 control methods. Furthermore, we introduce a tuning law to reduce the conservativeness of a robust building control strategy in the presence of high model uncertainty, both in a centralized and decentralized building control framework.

As redes Peer-to-Peer (P2P) tornaram-se nos últimos anos um método atrativo para a distribuição de conteúdo multimídia através da Internet. Muitos fatores contribuíram para esse sucesso, mas os custos baixos de distribuição e a escalabilidade inerente das redes P2P, na qual os consumidores de conteúdo também são fontes potenciais, estão entre os mais proeminentes. Entretanto, a efetividade e desempenho de várias redes P2P populares (como as que usam o protocolo BitTorrent) é consideravelmente dependente de quão bem o tracker (que é o elemento responsável pela identificação e gerência dos participantes de uma rede P2P do tipo BitTorrent) seleciona os peers que irão fornecer o conteúdo. Os peers escolhidos pelo tracker irão afetar diretamente a percepção do usuário sobre o desempenho do serviço e o uso dos recursos de rede. Além disso, as redes P2P usualmente não tem percepção de localidade, resultando em uma utilização não otimizada dos recursos de rede. A fim de abordar estas questões, nesta tese é apresentada uma proposta inédita de uma arquitetura de trackers hierárquicos para localidade orientada a redes P2P gerenciadas e baseadas no protocolo BitTorrent. Na tese é identificado, através de experimentação, que o uso da arquitetura proposta conduz a uma melhora significativa no desempenho da rede sem comprometer a experiência do usuário. Dentre as melhorias, a principal é o controle do tráfego de dados trafegado entre os peers através da escolha dos peers feita pelo tracker com base em informações da rede e regras de negócio. Essa melhoria permite que a rede possa ser gerenciada de maneira pró-ativa e o dinamismo de adaptação da rede às condições adversas possa ser obtido por meio de políticas de configuração que são acionadas por gatilhos pré-determinados. Nesta tese são usados gatilhos baseados em tempo (data/horário) para exemplificar a abordagem de mudança de políticas programável. / Peer-to-Peer (P2P) networks have become an attractive method for distributing multimedia content over the Internet in the last years. Several factors contributed to this success, but the low distribution costs and the inherent scalability of P2P networks, in which content consumers are also potential sources, are among of the most prominent. However, the effectiveness and performance of several popular P2P networks (such as those that use the BitTorrent protocol) is considerably dependent on how well the tracker (which is the element responsible for the identification and management of participants in BitTorrent P2P networks) selects peers that will provide the content. The peers chosen by the tracker will directly affect the user\'s perception about the service performance and proper deployment of the of network resources. In addition, P2P networks usually have no sense of locality, resulting in a non-optimal utilization of network resources. In order to address these issues, this thesis presents a novel hierarchical tracker architecture using P2P locality for managed networks based on a modified version of the BitTorrent protocol. This thesis shows, through experimentation, that the adoption of the proposed architecture leads to significant network efficiency improvements without compromising end-user experience. Among the improvements, the principal is the data flow control between the peers through the choice of peers given by tracker based on network information and business rules. This enhancement allows to manage the network proactively and to perform dynamic adaptation of the network due to adverse conditions. The network control can be achieved by setting policies that are driven by predetermined triggers. This thesis uses time-based triggers (date / time) to exemplify the approach of programmable policy change.

Bayesian hierarchical models are effective tools for small area estimation by pooling small datasets together. The pooling procedures allow individual areas to “borrow strength” from each other to desirably improve the estimation. This work is an extension of Nandram and Choi (2002), NC, to perform inference on finite population proportions when there exists non-identifiability of the missing pattern for nonresponse in binary survey data. We review the small-area selection model (SSM) in NC which is able to incorporate the non-identifiability. Moreover, the proposed SSM, together with the individual-area selection model (ISM), and the small-area pattern-mixture model (SPM) are evaluated by real crime data in Stasny (1991). Furthermore, the methodology is compared to ISM and SPM using simulated small area datasets. Computational issues related to the MCMC are also discussed.

In the oil and gas industry, statistical methods have been used for corrosion analysis for various asset systems such as pipelines, storage tanks, and so on. However, few industrial standards and guidelines provide comprehensive stepwise procedures for the usage of statistical approaches for corrosion analysis. For example, the UK HSE (2002) report "Guidelines for the use of statistics for analysis of sample inspection of corrosion" demonstrates how statistical methods can be used to evaluate corrosion samples, but the methods explained in the document are very basic and do not consider risk factors such as pressure, temperature, design, external factors and other factors for the analyses. Furthermore, often the industrial practice that uses linear approximation on localised corrosion such as pitting is considered inappropriate as pitting growth is not uniform. The aim of this research is to develop an approach that models the stochastic behaviour of localised corrosion and demonstrate how the influencing factors can be linked to the corrosion analyses, for predicting the remaining useful life of components in oil and gas plants. This research addresses a challenge in industry practice. Non-destructive testing (NDT) and inspection techniques have improved in recent years making more and more data available to asset operators. However, this means that these data need to be processed to extract meaningful information. Increasing computer power has enabled the use of statistics for such data processing. Statistical software such as R and OpenBUGS is available to users to explore new and pragmatic statistical methods (e.g. regression models and stochastic models) and fully use the available data in the field. In this thesis, we carry out extreme value analysis to determine maximum defect depth of an offshore conductor pipe and simulate the defect depth using geometric Brownian motion in Chapter 2. In Chapter 3, we introduce a Weibull density regression that is based on a gamma transformation proportional hazards model to analyse the corrosion data of piping deadlegs. The density regression model takes multiple influencing factors into account; this model can be used to extrapolate the corrosion density of inaccessible deadlegs with data available from other piping systems. In Chapter 4, we demonstrate how the corrosion prediction models in Chapters 2 and 3 could be used to predict the remaining useful life of these components. Chapter 1 sets the background to the techniques used, and Chapter 5 presents concluding remarks based on the application of the techniques.

Com a finalidade de facilitar a manipulação de documentos pelos usuários e aplicações, foram desenvolvidas no decorrer do tempo diversas formas para classificar e organizar esses documentos, incluindo a criação de diferentes mecanismos pertinentes a formatos de arquivos, os chamados sistemas de tipos de arquivos. É possível perceber nesse esforço uma crescente preocupação com a correta identificação dos arquivos e com a obtenção de maiores informações sobre seu conteúdo. Afinal, com esse conhecimento as aplicações e ambientes gráficos dos sistemas operacionais podem adicionar novas funcionalidades na manipulação de documentos e arquivos em geral. Neste trabalho se propõe um novo modelo e arquitetura para sistemas de tipos de arquivos. O modelo se baseia em um grafo de tipos representando relações hierárquicas e um índice de metadados de arquivos, usados em conjunto por funcionalidades que são disponibilizadas através de uma API. A construção do grafo de tipos, que desempenha papel central no modelo proposto, envolveu o estudo dos tipos de arquivos registrados nos principais sistemas operacionais, os tipos definidos pelo IANA (Internet Assigned Numbers Authority) e outros tipos comumente utilizados, com a finalidade de selecionálos e interrelacioná-los em uma hierarquia. A arquitetura proposta para o sistema de tipos é um middleware que oferece os serviços abstraindo operações de baixo nível específicos do sistema operacional. O modelo e arquitetura apresentados neste trabalho beneficia principalmente softwares que trabalham intensamente com arquivos, como IDEs (Integrated Development Environment) e ambientes gráficos. / Several strategies to classify and organize documents by users and applications has being developed in order to facilitate its manipulation, including creation of different mechanisms related to file formats, known as file type systems. It is possible to notice in these works an increasing concern about file identification correctness and obtaining further information regarding its contents as well. This knowledge allow application and graphical environments of operating systems adding new functionalities on manipulation of documents and files. The present work proposes a new model and architecture to file type systems. The model is based on a file type graph representing hierarchical relationships and an index of file metadata. Both are used by functionalities provided through an API. To build the graph of file types, central piece on the proposed model, it was necessary to study file types registered on the most imporant operating systems, types defined by IANA and other types commonly used. The goal is to collect file types and interlink them in a hierarchy. The proposed architecture for the file type system is a middleware which provides services hiding native operating systems low level operations. The model and architecture presented in this work is specially useful to softwares that handle files intensely, like IDEs (Integrated Development Environment) and graphical environments.

As redes Peer-to-Peer (P2P) tornaram-se nos últimos anos um método atrativo para a distribuição de conteúdo multimídia através da Internet. Muitos fatores contribuíram para esse sucesso, mas os custos baixos de distribuição e a escalabilidade inerente das redes P2P, na qual os consumidores de conteúdo também são fontes potenciais, estão entre os mais proeminentes. Entretanto, a efetividade e desempenho de várias redes P2P populares (como as que usam o protocolo BitTorrent) é consideravelmente dependente de quão bem o tracker (que é o elemento responsável pela identificação e gerência dos participantes de uma rede P2P do tipo BitTorrent) seleciona os peers que irão fornecer o conteúdo. Os peers escolhidos pelo tracker irão afetar diretamente a percepção do usuário sobre o desempenho do serviço e o uso dos recursos de rede. Além disso, as redes P2P usualmente não tem percepção de localidade, resultando em uma utilização não otimizada dos recursos de rede. A fim de abordar estas questões, nesta tese é apresentada uma proposta inédita de uma arquitetura de trackers hierárquicos para localidade orientada a redes P2P gerenciadas e baseadas no protocolo BitTorrent. Na tese é identificado, através de experimentação, que o uso da arquitetura proposta conduz a uma melhora significativa no desempenho da rede sem comprometer a experiência do usuário. Dentre as melhorias, a principal é o controle do tráfego de dados trafegado entre os peers através da escolha dos peers feita pelo tracker com base em informações da rede e regras de negócio. Essa melhoria permite que a rede possa ser gerenciada de maneira pró-ativa e o dinamismo de adaptação da rede às condições adversas possa ser obtido por meio de políticas de configuração que são acionadas por gatilhos pré-determinados. Nesta tese são usados gatilhos baseados em tempo (data/horário) para exemplificar a abordagem de mudança de políticas programável. / Peer-to-Peer (P2P) networks have become an attractive method for distributing multimedia content over the Internet in the last years. Several factors contributed to this success, but the low distribution costs and the inherent scalability of P2P networks, in which content consumers are also potential sources, are among of the most prominent. However, the effectiveness and performance of several popular P2P networks (such as those that use the BitTorrent protocol) is considerably dependent on how well the tracker (which is the element responsible for the identification and management of participants in BitTorrent P2P networks) selects peers that will provide the content. The peers chosen by the tracker will directly affect the user\'s perception about the service performance and proper deployment of the of network resources. In addition, P2P networks usually have no sense of locality, resulting in a non-optimal utilization of network resources. In order to address these issues, this thesis presents a novel hierarchical tracker architecture using P2P locality for managed networks based on a modified version of the BitTorrent protocol. This thesis shows, through experimentation, that the adoption of the proposed architecture leads to significant network efficiency improvements without compromising end-user experience. Among the improvements, the principal is the data flow control between the peers through the choice of peers given by tracker based on network information and business rules. This enhancement allows to manage the network proactively and to perform dynamic adaptation of the network due to adverse conditions. The network control can be achieved by setting policies that are driven by predetermined triggers. This thesis uses time-based triggers (date / time) to exemplify the approach of programmable policy change.