ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Networked based technologies (i.e. TCP/IP) have come to play an important role in the evolution of telemetry post processing services. A paramount issue when using networking to access/move telemetry data is security. In past years papers have focused on individual security technologies and how they could be used to secure telemetry data. This paper will review currently available network based security technologies, update readers on enhancements, and discuss their appropriate uses in the various phases of telemetry post-processing and analysis activities.

Phase measuring Profilometry (PMP) is an important technique used in 3D data acquisition. Many variations of the PMP technique exist in the research world. The technique involves projecting phase shifted versions of sinusoidal patterns with known frequency. The 3D information is obtained from the amount of phase deviation that the target object introduces in the captured patterns. Using patterns based on single frequency result in projecting a large number of patterns necessary to achieve minimal reconstruction errors. By using more than one frequency, that is multi-frequency, the error is reduced with the same number of total patterns projected as in the single frequency case. The first major goal of our research work is to minimize the error in 3D reconstruction for a given scan time using multiple frequency sine wave patterns. A mathematical model to estimate the optimal frequency values and the number of phase shift patterns based on stochastic analysis is given. Experiments are conducted by implementing the mathematical model to estimate the optimal frequencies and the number of patterns projected for each frequency level used. The reduction in 3D reconstruction errors and the quality of the 3D data obtained shows the validity of the proposed mathematical model. The second major goal of our research work is the implementation of a post-processing algorithm based on stereo correspondence matching adapted to structured light illumination. Composite pattern is created by combining multiple phase shift patterns and using principles from communication theory. Composite pattern is a novel technique for obtaining real time 3D depth information. The depth obtained by the demodulation of captured composite patterns is generally noisy compared to the multi-pattern approach. In order to obtain realistic 3D depth information, we propose a post-processing algorithm based on dynamic programming. Two different communication theory principles namely, Amplitude Modulation (AM) and Double Side Band Suppressed Carrier (DSBSC) are used to create the composite patterns. As a result of this research work, we developed a series of low-cost structured light scanners based on the multi-frequency PMP technique and tested them for their accuracy in different 3D applications. Three such scanners with different camera systems have been delivered to Toyota for vehicle assembly line inspection. All the scanners use off the shelf components. Two more scanners namely, the single fingerprint and the palmprint scanner developed as part of the Department of Homeland Security grant are in prototype and testing stages.

A demanda por métodos de análise e descoberta de conhecimento em grandes bases de dados tem fortalecido a pesquisa em Mineração de Dados. Dentre as tarefas associadas a essa área, tem-se Regras de Associação. Vários algoritmos foram propostos para tratamento de Regras de Associação, que geralmente tˆem como resultado um elevado número de regras, tornando o Pós-processamento do conhecimento uma etapa bastante complexa e desafiadora. Existem medidas para auxiliar essa etapa de avaliação de regras, porém existem lacunas referentes a inexistência de um método intuitivo para priorizar e selecionar regras. Além disso, não é possível encontrar metodologias específicas para seleção de regras considerando mais de uma medida simultaneamente. Esta tese tem como objetivo a proposição, desenvolvimento e implementação de uma metodologia para o Pós-processamento de Regras de Associação. Na metodologia proposta, pequenos grupos de regras identificados como potencialmente interessantes são apresentados ao usuário especialista para avaliação. Para tanto, foram analisados métodos e técnicas utilizadas em Pós-processamento de conhecimento, medidas objetivas para avaliação de Regras de Associação e algoritmos que geram regras. Dessa perspectiva foram realizados experimentos para identificar o potencial das medidas a serem empregadas como filtros de Regras de Associação. Uma avaliação gráfica apoiou o estudo das medidas e a especificação da metodologia proposta. Aspecto inovador da metodologia proposta é a utilização do método de Pareto e a combinação de medidas para selecionar as Regras de Associação. Por fim foi implementado um ambiente para avaliação de Regras de Associação, denominado ARInE, viabilizando o uso da metodologia proposta. / The large demand of methods for knowledge discovery and analysis in large databases has continously increased the research in data mining area. Among the tasks associated to this area, one can find Association Rules. Several algorithms have been proposed for treating Association Rules. However, these algorithms give as results a huge amount of rules, making the knowledge post-processing phase very complex and challeging. There are several measures that can be used in this evaluation phase, but there are also some limitations regarding to the ausence of an intuitive method to rank and select rules. Moreover, it is not possible to find especific methodologies for selecting rules, considering more than one measure simultaneously. This thesis has as objective the proposal, development and implementation of a postprocessing methodology for Association Rules. In the proposed methodology, small groups of rules, which have been identified as potentialy interesting, are presented to the expert for evaluation. In this sense, methods and techniques for knowledge post-processing, objective measures for rules evaluation, and Association Rules algorithms have been analized. From this point of view, several experiments have been realized for identifying the potential of such measures to be used to filter Association Rules. The study of measures and the specification of the proposed methodology have been supported by a graphical evaluation. The novel aspect of the proposed methodology consists on using the Pareto’s method and combining measures for selecting Association Rules. Finally, an enviroment for evaluating Association Rules, named as ARInE, has been implemented according to the proposed methodology.

Mineração de Dados é um processo de natureza iterativa e interativa responsável por identificar padrões em grandes conjuntos de dados, objetivando extrair conhecimento válido, útil e inovador a partir desses. Em Mineração de Dados, Regras de Associação é uma técnica que consiste na identificação de padrões intrínsecos ao conjunto de dados. Essa técnica tem despertado grande interesse nos pesquisadores de Mineração de Dados e nas organizações, entretanto, a mesma possui o inconveniente de gerar grande volume de conhecimento no formato de regras, dificultando a análise e interpretação dos resultados pelo usuário. Nesse contexto, este trabalho tem como objetivo principal generalizar e eliminar Regras de Associação não interessantes e/ou redundantes, facilitando, dessa maneira, a análise das regras obtidas com relação à compreensibilidade e tamanho do conjunto de regras. A generalização das Regras de Associação é realizada com o uso de taxonomias. Entre os principais resultados deste trabalho destacam-se a proposta e a implementação do algoritmo GART e do módulo computacional RulEE-GAR. O algoritmo GART (Generalization of Association Rules using Taxonomies - Generalização de Regras de Associação usando Taxonomias) utiliza taxonomias para generalizar Regras de Associação. Já o módulo RulEE-GAR, além de facilitar o uso do algoritmo GART durante a identificação de taxonomias e generalização de regras, provê funcionalidades para analisar as Regras de Associação generalizadas. Os experimentos realizados, neste trabalho, mostraram que o uso de taxonomias na generalização de Regras de Associação pode reduzir o volume de um conjunto de regras. / Data Mining refers to the process of finding patterns in large data sets. The Association Rules in Data Mining try to identify intrinsic behaviors of the data set. This has motivated researchers of Data Mining and organizations. However, the Association Rules have the inconvenient of generating a great amount of knowledge in the form of rules. This makes the analysis and interpretation of the results difficult for the user. Taking this into account, the main objective of this research is the generalization and elimination of non-interesting and/or redundant Association Rules. This facilite the analysis of the rules with respect to the compreensibility and the size of the rule set. The generalization is realized using taxonomies. The main results of this research are the proposal and the implementation of the algorithm GART and of the computational module RulEE-GAR. The algorithm GART (Generalization of Association Rules using Taxonomies) uses taxonomies to generalize Association Rules. The module RulEE-GAR facilitates the use of the algorithm GART in the identification of taxonomies and generalization of rules and provide functionalities to the analysis of the generalized Association Rules. The results of experiments showed that the employment of taxonomies in the generalization of Association Rules can reduce the size of a rule set.

Para o sucesso do processo de mineração de dados é importante que o conhecimento extraí?do seja compreensível e interessante para que o usuário final possa utilizá-lo em um sistema inteligente ou em processos de tomada de decisão. Um grande problema, porém, é identificado quando a tarefa de mineração de dados denominada associação é utilizada: a geração de um grande volume de regras. Taxonomias podem ser utilizadas para facilitar a análise e interpretação das regras de associação, uma vez que as mesmas provêm uma visão de como os itens podem ser hierarquicamente classificados. Em função dessa hierarquia é possível obter regras mais gerais que representem um conjunto de itens. Dentro desse contexto, neste trabalho é apresentada uma metodologia para construção semi-automática de taxonomias, que inclui procedimentos automáticos e interativos para a realização dessa tarefa. Essa combinação possibilita a utilização do conhecimento do especialista e também o auxilia na identificação de grupos. Entre os principais resultados deste trabalho, pode-se destacar a proposta e implementação do algoritmo SACT (Semi-automatic Construction of Taxonomies - Construção Semi-automática de Taxonomias), que provê a utilização da metodologia proposta. Para viabilizar a utilização do algoritmo, foi desenvolvido o módulo computacional RulEESACT. Com o objetivo de viabilizar e analisar a qualidade da metodologia proposta e do módulo desenvolvido, foi realizado um estudo de caso no qual foram construída taxonomias para duas bases de dados utilizando o RulEE-SACT. Uma das taxonomias foi analisada e validada por uma especialista do domínio. Posteriormente, as taxonomias e as bases de transações foram fornecidas para dois algoritmos de generalização de regras de associação a fim de analisar a aplicação das taxonomias geradas / I n the data mining process it is important that the extracted knowledge is understandable and interesting to the final user, so it can be used to support in the decision making. However, the data mining task named association has one problem: it generates a big volume of rules. Taxonomies can be used to facilitate the analysis and interpretation of association rules, because they provide an hierarchical vision of the items. This hierarchy enables the obtainment of more general rules, which represent a set of items. In this context, a methodology to semi-automatically construct taxonomies is proposed in this work. This methodology includes automatic and interactives procedures in order to construct the taxonomies, using the specialist?s knowledge and also assisting in the identification of groups. One of the main results of this work is the proposal and implementation of the SACT (Semi-automatic Construction of Taxonomies) algorithm, which provides the use of the proposed methodology. In order to facilitate the use of this algorithm, a computational module named RulEE-SACT was developed. Aiming to analyze the viability and quality of the proposed methodology and the developed module, a case study was done. In this case study, taxonomies of two databases were constructed using the RulEE-SACT. One of them was analyzed and validated by a domain specialist. Then the taxonomies and the databases were supplied to two algorithms which generalize association rules, aiming to analyze the use of the generated taxonomies

Une des pistes majeures pour obtenir des turbines à gaz moins polluantes est l'utilisation de chambres de combustion fonctionnant en régime prémélangé pauvre. Cependant, dans de tels régimes de fonctionnement, la flamme obtenue est cependant plus facilement sujette aux instabilités thermo-acoustiques.Dans cette thèse, un brûleur étagé swirlé fonctionnant au propane a été employé pour illustrer une méthode d'analyse de la combustion prémélangée. Cette installation a été étudiée à l'aide de diagnostics classiques (micros, PLIF, film à haute cadence de la flamme).La stratégie de post-traitement développée dans cette thèse utilise par contre des outils eux aussi classiques (PSD, moyenne de phase) mais aussi une méthode d'analyse avancée, la Décomposition en Modes Dynamiques. Celle-ci est notamment étudiée em détail afin d'en cerner les avantages et les limitations dans le cadre de l'analye des instabilités de combustion. / One of the major ways of reducing pollutant emissions in gas turbines is using combustion chambers with lean premixed mixtures. However, in such operating conditions the flame is more susceptible to thermo-acoustic instabilities. In the present work, a propane-fed swirled burner using two injection stages is used to illustrate a post-processing strategy for premixed combustion analysis. This model burner has been studied using classic diagnostics (microphones, PLIF, highspeed imaging).The strategy developed in the present work uses both classic postprocessing tools (PSD, phase averaging) and an advanced method, the Dynamic Mode Decomposition. In particular, this method is studied in detail and compared to more lassic ones in order to clearly point its advantages as well as its shortcomings when used to study combustion instabilities.

Mineração de Dados é um processo de natureza iterativa e interativa responsável por identificar padrões em grandes conjuntos de dados, objetivando extrair conhecimento válido, útil e inovador a partir desses. Em Mineração de Dados, Regras de Associação é uma técnica que consiste na identificação de padrões intrínsecos ao conjunto de dados. Essa técnica tem despertado grande interesse nos pesquisadores de Mineração de Dados e nas organizações, entretanto, a mesma possui o inconveniente de gerar grande volume de conhecimento no formato de regras, dificultando a análise e interpretação dos resultados pelo usuário. Nesse contexto, este trabalho tem como objetivo principal generalizar e eliminar Regras de Associação não interessantes e/ou redundantes, facilitando, dessa maneira, a análise das regras obtidas com relação à compreensibilidade e tamanho do conjunto de regras. A generalização das Regras de Associação é realizada com o uso de taxonomias. Entre os principais resultados deste trabalho destacam-se a proposta e a implementação do algoritmo GART e do módulo computacional RulEE-GAR. O algoritmo GART (Generalization of Association Rules using Taxonomies - Generalização de Regras de Associação usando Taxonomias) utiliza taxonomias para generalizar Regras de Associação. Já o módulo RulEE-GAR, além de facilitar o uso do algoritmo GART durante a identificação de taxonomias e generalização de regras, provê funcionalidades para analisar as Regras de Associação generalizadas. Os experimentos realizados, neste trabalho, mostraram que o uso de taxonomias na generalização de Regras de Associação pode reduzir o volume de um conjunto de regras. / Data Mining refers to the process of finding patterns in large data sets. The Association Rules in Data Mining try to identify intrinsic behaviors of the data set. This has motivated researchers of Data Mining and organizations. However, the Association Rules have the inconvenient of generating a great amount of knowledge in the form of rules. This makes the analysis and interpretation of the results difficult for the user. Taking this into account, the main objective of this research is the generalization and elimination of non-interesting and/or redundant Association Rules. This facilite the analysis of the rules with respect to the compreensibility and the size of the rule set. The generalization is realized using taxonomies. The main results of this research are the proposal and the implementation of the algorithm GART and of the computational module RulEE-GAR. The algorithm GART (Generalization of Association Rules using Taxonomies) uses taxonomies to generalize Association Rules. The module RulEE-GAR facilitates the use of the algorithm GART in the identification of taxonomies and generalization of rules and provide functionalities to the analysis of the generalized Association Rules. The results of experiments showed that the employment of taxonomies in the generalization of Association Rules can reduce the size of a rule set.

Dentre as técnicas de mineração de dados encontra-se a associação, a qual identifica todas as associações intrínsecas contidas na base de dados. Entretanto, essa característica, vantajosa por um lado, faz com que um grande número de padrões seja gerado, sendo que muito deles, mesmo sendo estatisticamente aceitos, são triviais, falsos, ou irrelevantes à aplicação. Além disso, a técnica de associação tradicional gera padrões compostos apenas por itens contidos na base de dados, o que leva à extração, em geral, de um conhecimento muito específico. Essa especificidade dificulta a obtenção de uma visão geral do domínio pelos usuários finais, que visam a utilização/exploração de conhecimentos úteis e compreensíveis. Assim, o pós-processamento das regras descobertas se torna um importante tópico, uma vez que há a necessidade de se validar as regras obtidas. Diante do exposto, este trabalho apresenta uma abordagem de pós-processamento de regras de associação que utiliza conhecimento de domínio, expresso via taxonomias, para obter um conjunto de regras de associação generalizadas compacto e representativo. Além disso, a fim de avaliar a representatividade de padrões generalizados, é apresentado também neste trabalho um estudo referente à utilização de medidas de interesse objetivas quando aplicadas a regras de associação generalizadas. Nesse estudo, a semântica da generalização é levada em consideração, já que cada uma delas fornece uma visão distinta do domínio. Como resultados desta tese, foi possível observar que: um conjunto de regras de associação pode ser compactado na presença de um conjunto de taxonomias; para cada uma das semânticas de generalização existe um conjunto de medidas mais apropriado para ser utilizado na avaliação de regras generalizadas / The association technique, one of the data mining techniques, identifies all the intrinsic associations in database. This characteristic, which can be advantageous on the one hand, generates a large number of patterns. Many of these patterns, even statistically accepted, are trivial, spurious, or irrelevant to the application. In addition, the association technique generates patterns composed only by items in database, which in general implies a very specific knowledge. This specificity makes it difficult to obtain a general view of the domain by the final users, who aims the utilization/exploration of useful and comprehensible knowledge . Thus, the post-processing of the discovered rules becomes an important topic, since it is necessary to validate the obtained rules. In this context, this work presents an approach for post-processing association rules that uses domain knowledge, expressed by taxonomies, to obtain a reduced and representative generalized association rule set. In addition, in order to evaluate the representativeness of generalized patterns, a study referent to the use of objective interest measures when applied to generalized association rules is presented. In this study, the generalization semantics is considered, since each semantic provides a distinct view of the domain. As results of this thesis, it was possible to observe that: an association rule set can be compacted with a taxonomy set; for each generalization semantic there is a measure set that is more appropriate to be used in the generalized rules evaluation

The disposal of sewage sludge is becoming an ever-increasing problem and a range of re-use options are being developed, with traditional composting and advanced alkaline stabilisation emerging as priority re-use alternatives in NSW. However, concerns have been raised regarding the dissemination of sludge related pathogens in the environment. Salmonella spp pose the greatest risk since they have the ability to proliferate in the absence of human and animal hosts. Composting processes eliminate salmonellae from sludge, but the opportunity for post-processing recontamination is considerable. This project examined the significance of post-processing recontamination of Salmonella broughton, introduced into composted sludge and N-Virosoil. In compost, inactivation rates of S. broughton showed an inverse relationship with simulated processing temperatures, with competitive exclusion by autocthonous compost flora thought to be the major mechanism of inhibition. S. broughton numbers were reduced to below the limits of detection after several weeks. S. broughton inactivation was also assessed in processed N-Virosoil and was found to be more immediate. It was concluded that both compost and N.Virosoil products have a low potential to support the regrowth of Salmonella spp. / Master of Science (Hons)(Environmental Science)

Micro-Electro-Mechanical Systems (MEMS) varactors have the potential to replace conventional varactor diodes, due to their high loss and non-linearity, in many applications such as phase shifters, oscillators, and tunable filters. The objective of this thesis is to develop novel MEMS varactors to improve the capacitance tuning ratio, linearity, and quality factor. Several novel varactor configurations are developed, analyzed, fabricated and tested. They are built by using standard MEMS fabrication processes, as well as monolithic integration techniques in CMOS technology. The first capacitor consists of two movable plates, loaded with a nitride layer that exhibits an analog continuous capacitance tuning ratio. To decrease the the parasitic capacitance, a trench in the silicon substrate under the capacitor is adopted. The use of an insulation dielectric layer on the bottom plate of the MEMS capacitor increases the capacitors’ tuning ratio. Experimental and theoretical results are presented for two versions of the proposed capacitor with different capacitance values. The measured capacitance tuning ratio is 280% at 1 GHz. The proposed MEMS vararctor is built using the MetalMUMPs process. The second, third, and fourth capacitors have additional beams that are called carrier beams. The use of the carrier beams makes it possible to obtain an equivalent nonlinear spring constant, which increases the capacitors’ analog continuous tuning ratio. A lumped element model and a continuous model of the proposed variable capacitors are developed. The continuous model is simulated by commercial software. A detailed analysis for the steady state of the capacitors is presented. The measured capacitance tuning ratios of these three capacitors are 410%, 400% and 470%, respectively at 1 GHz. Also, the selfresonance frequency is measured and found to exceed 11 GHz. The proposed MEMS variable capacitors are built by the PolyMUMPs process. The fifth novel parallel-plate MEMS varactor has thin-film vertical comb actuators as its driver. Such an actuator can vertically displace both plates of the parallel-plate capacitor. By making use of the fringing field, this actuator exhibits linear displacement behavior, caused by the induced electrostatic force of the actuator’s electrodes. The proposed capacitor has a low parasitic capacitance and linear deflection due to the mechanically connected and electrically isolated actuators to the capacitor’s parallel-plates. The measured tuning capacitance ratio is 7:1 (600%) at 1 GHz. The fabricated MEMS varactor exhibits a self resonance frequency of 9 GHz and built by MetalMUMPs process. The sixth parallel-plate MEMS varactor exhibits a linear response and high tuning capacitance ratio. The capacitor employs the residual stress of the chosen bi-layer, and the non-linear spring constants from the suspended cantilevers to obtain a non-linear restoring force that compensates for the nonlinear electrostatic force induced between the top and bottom plates. Two existing techniques are used to widen the tuning range of the proposed capacitor. The first technique is to decrease the parasitic capacitance by etching the lossy substrate under the capacitor’s plates. The second technique is employed to increase the capacitance density, where the areas between the top and bottom plates overlap, by applying a thin film of dielectric material, deposited by the atomic layer deposition (ALD) technique. The measured linear continuous tuning ratio for the proposed capacitor, built in the PolyMUMPs process, is 5:1 (400%). The seventh and eighth MEMS variable capacitors have plates that curl up. These capacitors are built in 0.35 μm CMOS technology from the interconnect metallization layers. The plates of the presented capacitors are intentionally curled upward to control the tuning performance. A newly developed maskless post-processing technique that is appropriate for MEMS/CMOS circuits is proposed. it consists of dry and wet etching steps, developed to integrate the proposed MEMS varactors in CMOS technology. Mechanically, the capacitors are simulated by the finite element method in ANSYS, and the results are compared with the measured results. The seventh capacitor is a tri-state structure that exhibits a measured tuning range of 460% at 1 GHz with a flat capacitance response that is superior to that of conventional digital capacitors. The proposed capacitor is simulated in HFSS and the extracted capacitance is compared with the measured capacitance over a frequency range of 1 GHz to 5 GHz. The eighth capacitor is an analog continuous structure that demonstrates a measured continuous tuning range of 115% at 1 GHz with no pull-in. The measured quality factor for both CMOSbased capacitors is more than 300 at 1.5 GHz. The proposed curled-plate capacitors have a small area and can be realized to build a System-on-Chip (SoC). Finally, a tunable band pass filter that utilizes the MEMS variable capacitors in 0.18 μm CMOS technology from TSMC is designed, modeled and fabricated.