From the earliest days of mass production in the automotive industry there has been a progressive move towards the use of flexible manufacturing systems that cater for product variants that meet market demands. In recent years this market has become more demanding with pressures from legislation, globalisation and increased customer expectations. This has lead to the current trends of mass customisation in production. In order to support this manufacturing systems are not only becoming more flexible† to cope with the increased product variants, but also more agile‡ such that they may respond more rapidly to market changes. Modularisation§ is widely used to increase the agility of automation systems, such that they may be more readily reconfigured¶. Also with globalisation into India and Asia semi-automatic machines (machines that interact with human operators) are more frequently used to reduce capital outlay and increase flexibility. There is an increasing need for tools and methodologies that support this in order to improve design robustness, reduce design time and gain a competitive edge in the market. The research presented in this thesis is built upon the work from COMPAG/COMPANION (COMponent- based Paradigm for AGile automation, and COmmon Model for PArtNers in automatION), and as part of the BDA (Business Driven Automation), SOCRADES (Service Oriented Cross-layer infrastructure for Distributed smart Embedded deviceS), and IMC-AESOP (ArchitecturE for Service- Oriented Process – monitoring and control) projects conducted at Loughborough University UK. This research details the design and implementation of a toolkit for building and simulating automation systems comprising components with behaviour described using Finite State Machines (FSM). The research focus is the development of the engineering toolkit that can support the automation system lifecycle from initial design through commissioning to maintenance and reconfiguration as well as the integration of a virtual human. This is achieved using a novel data structure that supports component definitions for control, simulation, maintenance and the novel integration of a virtual human into the automation system operation.

Made available in DSpace on 2014-06-12T15:57:59Z (GMT). No. of bitstreams: 2 arquivo3240_1.pdf: 2429983 bytes, checksum: 9b9eff719ea26a708f6868c5df873358 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2010 / Universidade de Pernambuco / Um dos maiores desafios para a indústria de embarcados é fornecer produtos com alto nível de qualidade e funcionalidade, a um baixo custo e curto tempo de desenvolvimento, disponibilizando-o rapidamente ao mercado, aumentando assim, o retorno dos investimentos. Os requisitos de custo e tempo de desenvolvimento têm sido abordados com bastante êxito pela engenharia de software baseada em componentes (CBSE) aliada à técnica de reuso de componentes. No entanto, a utilização da abordagem CBSE sem as devidas verificações da qualidade dos componentes utilizados, pode trazer conseqüências catastróficas (Jezequel et al., 1997). A utilização de mecanismos apropriados de pesquisa, seleção e avaliação da qualidade de componentes são considerados pontos chave na adoção da abordagem CBSE. Diante do exposto, esta tese propõe uma Metodologia para Avaliação da Qualidade de Componentes de Software Embarcados sob diferentes aspectos. A idéia é solucionar a falta de consistência entre as normas ISO/IEC 9126, 14598 e 2500, incluindo o contexto de componente de software e estendendo-o ao domínio de sistemas embarcados. Estas normas provêem definições de alto nível para características e métricas para produtos de software, mas não provêem formas de usá-las efetivamente, tornando muito difícil aplicá-las sem adquirir mais informações de outras fontes. A Metodologia é composta de quatro módulos que se complementam em busca da qualidade, através de um processo de avaliação, um modelo de qualidade, técnicas de avaliação agrupadas por níveis de qualidade e uma abordagem de métricas. Desta forma, ela auxilia o desenvolvedor de sistemas embarcado no processo de seleção de componentes, avaliando qual componente melhor se enquadra nos requisitos do sistema. É utilizada por avaliadores terceirizados quando contratados por fornecedores a fim de obter credibilidade em seus componentes. A metodologia possibilita avaliar a qualidade do componente embarcado antes do mesmo ser armazenado em um sistema de repositório, especialmente no contexto do framework robusto para reuso de software, proposto por Almeida (Almeida, 2004)

Progress

A software component model is the cornerstone of any Component-based Software Development (CBSD) methodology. Such a model defines the modelling elements for constructing software systems. In software system modelling, it is necessary to capture the three elements of a system's behaviour: (i) control (ii) computation and (iii) data. Within a system, computations are performed according to the flow of control or the flow of data, depending on whether computations are control-driven or data-driven. Computations are function evaluations, assignments, etc., which transform data when invoked by control or data flow. Therefore a component model should be able to model control flow, data flow as well as computations. Current component models all model computations, but beside computations tend to model either control flow only or data flow only, but not both. In this thesis, we present a new component model which can model both control flow and data flow. It contains modelling elements that capture control flow and data flow explicitly. Furthermore, the modelling of control flow is separate from that of data flow; this enables the modelling of both control-driven and data-driven computations. The feasibility of the model is shown by means of an implementation of the model, in the form of a prototype tool. The usefulness of the model is then demonstrated for a specific domain, the embedded systems domain, as well as a generic domain. For the embedded systems domain, unlike current models, our model can be used to construct systems that are both control-driven and data-driven. In a generic domain, our model can be used to construct domain models, by constructing control flows and data flows which together define a domain model.

Construction of semi-automatic equipment DCR 231 means for company Mubea saving money in long-range target. This economy profit rises with time period of the equipment active usage. The equipment is designed as a universal tool of automatic production step for inserting reinforcement tubes into tubular stabilizer bars. Inserting of these tubes into the both stabilizer ends brings higher strength of supported areas. Benefit of stabilizer bar reinforcement only on its ends is a lower mass leads to reduction of the whole axle mass. The equipment in global scale helps to reduce the costs connected with daily vehicle usage.

We study a periodic review assemble-to-order (ATO) system introduced by Akcay and Xu (2004) which jointly optimizes the base stock levels and the component allocation with an independent base stock policy and a first-come- first-served allocation rule. The formulation is a non-smooth and thus theoretically and computationally challenging. In their computational experiments, Akcay and Xu (2004) modified the right hand side of the inventory availability constraints by substituting linear functions for piece-wise linear ones. This modification may have a significant impact on low budget levels. The optimal solutions obtained via the original formulation, i.e., the formulation without modification, include zero base stock levels for some components and thus indicate a bias against component commonality. We study the impact of component commonality on periodic review ATO systems. We show that lowering component commonality may yield a higher type-II service level. The lower degree of component commonality is achieved via separating inventories of the same component for different products. We substantiate this property via computational and theoretical approaches. We show that for low budget levels the use of separate inventories of the same component for different products can achieve a higher reward than with shared inventories. Finally, considering a simple ATO system with one component shared by two products, we characterize the budget ranges such that either separate or shared inventory component (i.e., component commonality) is beneficial. / Thesis / Doctor of Philosophy (PhD)

The AICPA recently released new authoritative audit guidance related to group audits of nonpublic organizations which requires group engagement teams to be involved in the work of a component auditor, including certain minimum baseline requirements and the option for more extensive involvement at the group auditor's discretion. Accordingly, group audits create a scenario where auditors are under the direct oversight of a component audit supervisor, yet their work product is monitored and used by the group engagement team when expressing an opinion on the group financial statements. To my knowledge, prior accounting research has not explored the complexity of auditor decision making in a group audit scenario. Drawing on theory from motivated reasoning, this study investigates how the level of group engagement team involvement in component audit work may influence auditor decision making when a component audit supervisor has expressed preferences for more or less professional skepticism during the component audit process. Prior research in non-group audit settings finds the preferences of audit supervisors can influence the skepticism exhibited by their subordinates. However, in a group audit setting I find that the effects of component supervisor preferences interact with the level of group engagement team involvement in component auditors' work to influence component auditors' budgeted audit hours and planned substantive audit procedures. Results showed that during an accounts receivable audit planning task, auditors who faced an optimistic component supervisor recommended the use of more audit hours and suggested confirming a greater percentage of the accounts receivable balance when a group engagement team chose to be more actively involved in the component audit process than when the group engagement team chose only to review component audit work. However, there were no differences in budgeted audit hours or planned audit procedures when auditors faced a skeptical component supervisor, regardless of the level of group engagement team involvement. Thus, increased involvement of the group engagement team mitigated the influence of an optimistic component supervisor on auditor decision making, but did not significantly influence component auditor judgments when auditors faced a more conservative component supervisor. Path analyses indicated this phenomenon was caused by auditors' sense of pressure to reach appropriate audit conclusions induced by the increased involvement of the group engagement team. These results suggest that the effects of supervisor preferences are complex within a group audit environment, such that the nature of instructions received from a group engagement team may mitigate the effects of supervisor preferences on component auditor decision making. This research has implications for audit practice as it relates to the implementation of the new group audit standard as well as for regulators who establish future auditing guidance. / Ph. D.

Mycobacterium tuberculosis, the causative organism of the disease tuberculosis (TB) in humans, leads to nearly two million deaths each year. This versatile pathogen can exist in highly distinct physiological states such as asymptomatic latent TB infection where bacilli lie dormant or as active TB disease in which the bacilli replicate in macrophages. The pathogenic lifestyle requires the tubercle bacillus to sense and respond to multiple environmental cues to ensure its survival. Such stimuli include hypoxia, nutrient limitation, presence of reactive oxygen and reactive nitrogen intermediates, pH alterations, and cell wall/ membrane stress. Two component systems (TCSs) form the primary apparatus for sensing and responding to environmental cues in bacteria. A prototypical TCS is composed of a sensory protein called sensor kinase (SK) and a response generating protein called response regulator (RR). M. tuberculosis encodes 11 genetically paired TCSs, 2 orphan sensor kinases and six orphan response regulator proteins. Studies of the TB bacilli using transcriptional profiling and gene knockouts have revealed that TCSs play an important role in facilitating successful adaptation to diverse environmental conditions encountered within the host. The mtrAB and prrAB genes encoding corresponding TCSs have been shown to be essential for survival, mprAB for persistence and devRS for hypoxic adaptation. Further, inactivation of the TCSs regX3-senX3, tcrXY, trcRS, phoPR or kdpDE was shown to affect the growth and/or virulence of M. tuberculosis in animal infection models. The SK and RR proteins of TCSs are modular and contain variable input and output domains coupled to conserved ‘transmitter’ and ‘receiver’ domains. Despite the modular nature and extensive homology of SK and RR proteins across TCSs, which may allow non-cognate interactions, it is believed that crosstalk across different TCSs is not favored and that individual pathways are generally well insulated. The existing profiling studies have been performed on the TCSs of bacterial species containing a relatively large number of TCSs. In those studies, specificity and insulation have been the norm and thus become the prevalent paradigm of TCS signaling. In vitro genome wide phosphotransfer profiling has revealed only a few cross- communication nodes in the TCSs of Escherichia coli (~3%), while none in Caulobacter crescentus (in 352 interactions tested, in short time duration) and Myxococcus xanthus (in 250 interactions tested). Yet, many instances of cross talk have been reported in literature. For example, E. coli TCSs PmrAB and EnvZ-OmpR show cross-communication with QseBC and ArcBA, and many more. In M. tuberculosis, indirect evidence of the existence of such cross regulation has originated from studies where mutations in phoPR have been shown to affect the expression of the TCS devRS and its regulon. It is thus interesting to examine the extent of crosstalk in the TCSs of M. tuberculosis, which has an exceptionally small number of TCS proteins compared to E. coli. As mentioned earlier, M. tuberculosis H37Rv has 11 cognate pairs of TCSs, 2 orphan sensor kinases and 6 orphan response regulators. To study the entire landscape, we aimed to study all 221 connections between SK and RR proteins including 12 cognate interactions. While 10 of the cognate TCS interactions were established in the literature, two putative systems KdpDE and NarSL and 5 orphan response regulators were still uncharacterized, therefore we initiated our work with the characterization of these TCSs. At the biochemical level, the KdpDE two component system of M. tuberculosis is not well studied, though one report showed interaction of the C-terminal domain of KdpD SK and KdpE RR using yeast two hybrid assay and another reported the interaction of the SK with LRP protein. Besides these associations, there is no evidence for the functionality of KdpDE system. Similarly, NarSL system also has not been characterized and it not known whether these putative two component proteins are functional. The initial part of the study includes the characterization of these two TCSs, NarS-NarL and KdpD-KdpE, at biochemical and physiological levels. In our studies we demonstrated that KdpDE system is a bonafide two component system of M. tuberculosis, and KdpD SK undergoes autophosphorylation at His642 residue in presence of Mg+2 ions and then it transfers phosphoryl group to a conserved Asp52 residue on the KdpE RR protein. The acid-base stability analysis revealed the nature of chemical bonds present in the KdpD and KdpE proteins, and further confirmed that KdpD and KdpE are typical SK and RR respectively. SPR analysis demonstrated that KdpD and KdpE proteins interact under basal non-phosphorylated conditions and the interaction affinity reduced when SK was phosphorylated. The reduction in the interaction affinity indicated towards a possible dissociation of SK and RR protein during phosphotransfer, which allows RRs to exert their regulatory effect. On the similar line, the phosphorylation defective SK (KdpDH642Q) had least affinity with KdpE suggesting that perhaps this mutant SK, fails to interact with the RR. We have also shown that both the kdpD and kdpE genes are in the same operon and are up regulated in potassium ions limitation and osmotic stress conditions. Overall, using the biochemical approaches, we have established that Rv1027c–Rv1028c operon of M. tuberculosis encodes a functional and a typical KdpDE two component signal transduction system. Using the similar biochemical and biophysical approaches, we have demonstrated that NarS-NarL proteins constitute a functional TCS and His241 and Asp61 are the phosphorylatable residues. In contrast to KdpDE which shows typical behaviour of TCS, NarSL TCS showed atypical behaviour. Malhotra and group’s work on NarSL suggested that there is cross-regulation between NarS/NarL and DevS/DosT/DevR systems. We addressed this possibility on three separate levels, by examining (i) the cross-phosphorylation of DevR and NarL RRs by non-cognate sensor kinases NarS and DevS/DosT respectively, (ii) the interaction between DevR and NarL RR proteins, and (iii) examining the effect of DevR-NarL interactions on their DNA binding properties. Our studies ruled out the presence of any physiologically relevant phosphorylation mediated cross-talk between NarS/NarL and DevS/DosT/DevR. We identified that the cross talk between these TCSs could be explained on the basis of interaction between NarL and DevR RRs and their subsequent binding to the target gene promoter regions for concerted regulation of gene expression. We also identified that DevR activation is critical for cooperative action with NarL. This process comes out as a novel mechanism of gene regulation via heteromerization of RRs. We hypothesized that formation of NarL-DevR heteromers may arise because of high sequence similarities. Conclusively, our study provides insights into the functionality of M. tuberculosis NarL/NarS TCS and regulatory function of NarL protein which acts in concert with another RR, DevR. Overall, NarS-NarL system showed an atypical, novel mode of gene regulation involving RR heteromerization. Subsequent to the basic biochemical characterization of NarSL and KdpDE system, the genome wide phosphotransfer profiling was done to identify the cross-connections between TCSs. Remarkably, we found that specificity was the exception rather than the rule. While only three of the TCS pairs were completely specific, all the other nine TCS pairs exhibited crosstalk, including a few that were highly promiscuous. We classified the interactions as specific, one-to-many, and many-to-one signaling circuits. We also profiled all the RRs including the orphans for their ability to accept phosphoryl group from a low molecular weight donor, acetyl phosphate, and interestingly found that only two RRs DevR and NarL were capable of accepting phosphoryl group from such a donor. Interestingly, none of the orphan RRs accepted phosphoryl group from any donor, neither SKs nor low molecular weight phospho donors, warranting further analysis of their roles and presence in the M. tuberculosis genome. Our exhaustive map of the crosstalk between the TCSs of M. tuberculosis sets the stage for a renewed view of TCS signaling and proposes a dispersive-integrative landscape for TCS signaling rather than one of insulation. As an extension of our basic characterization work of NarSL TCS, we also attempted to understand the localization pattern of NarS sensor kinase in M. smegmatis cells using fluorescence approaches. It is known that many bacterial receptors including sensor kinases form clusters or show specific localization patterns inside the cell. We found that NarS shows distinct cellular localization pattern. However, the functional significance of this localization pattern is not obvious yet and warrants further investigations. We also developed a few non-radioactive methods to study interaction between two component systems to overcome the limitations associated with radioactive experiments in studying TCSs. We developed fluorescence resonance energy transfer (FRET) to study in vitro interaction between two component proteins which was sensitive to the phosphorylation status of the proteins. Using fluorescently tagged SKs and RRs, we determined a change in FRET for KdpDE and NarSL TCS pairs in vitro. Our study thus also provides an alternative approach to study TCS signaling, using an easier, non-radioactive and high throughput approach. In summary, our study presents the evidence of an alternative paradigm of bacterial signaling, where significant crosstalk between the underlying TCSs prevails. The new paradigm is expected to have important implications in our understanding of the virulence and pathogenesis of bacterial infections. Overall, our studies (i) allowed the establishment of functionality of all paired TCSs encoded in the genome of M. tuberculosis including NarSL and KdpDE TCSs, (ii) identified the novel mechanism of gene regulation by NarL RR and DevR, (iii) demonstrated the existence of TCS signaling which is contrary to the existing notion of specificity (iv) showed the distinct localization pattern of NarS and (v) developed non-radioactive approaches to study two component interactions.

Doctor of Philosophy / This thesis is based on research on financial time series analysis using pattern recognition methods. The first part of this research focuses on univariate time series analysis using different pattern recognition methods. First, probabilities of basic patterns are used to represent the features of a section of time series. This feature can remove noise from the time series by statistical probability. It is experimentally proven that this feature is successful for pattern repeated time series. Second, a multiscale Gaussian gravity as a pattern relationship measurement which can describe the direction of the pattern relationship is introduced to pattern clustering. By searching for the Gaussian-gravity-guided nearest neighbour of each pattern, this clustering method can easily determine the boundaries of the clusters. Third, a method that unsupervised pattern classification can be transformed into multiscale supervised pattern classification by multiscale supervisory time series or multiscale filtered time series is presented. The second part of this research focuses on multivariate time series analysis using pattern recognition. A systematic method is proposed to find the independent variables of a group of share prices by time series clustering, principal component analysis, independent component analysis, and object recognition. The number of dependent variables is reduced and the multivariate time series analysis is simplified by time series clustering and principal component analysis. Independent component analysis aims to find the ideal independent variables of the group of shares. Object recognition is expected to recognize those independent variables which are similar to the independent components. This method provides a new clue to understanding the stock market and to modelling a large time series database.

Doctor of Philosophy / This thesis is based on research on financial time series analysis using pattern recognition methods. The first part of this research focuses on univariate time series analysis using different pattern recognition methods. First, probabilities of basic patterns are used to represent the features of a section of time series. This feature can remove noise from the time series by statistical probability. It is experimentally proven that this feature is successful for pattern repeated time series. Second, a multiscale Gaussian gravity as a pattern relationship measurement which can describe the direction of the pattern relationship is introduced to pattern clustering. By searching for the Gaussian-gravity-guided nearest neighbour of each pattern, this clustering method can easily determine the boundaries of the clusters. Third, a method that unsupervised pattern classification can be transformed into multiscale supervised pattern classification by multiscale supervisory time series or multiscale filtered time series is presented. The second part of this research focuses on multivariate time series analysis using pattern recognition. A systematic method is proposed to find the independent variables of a group of share prices by time series clustering, principal component analysis, independent component analysis, and object recognition. The number of dependent variables is reduced and the multivariate time series analysis is simplified by time series clustering and principal component analysis. Independent component analysis aims to find the ideal independent variables of the group of shares. Object recognition is expected to recognize those independent variables which are similar to the independent components. This method provides a new clue to understanding the stock market and to modelling a large time series database.