357 resultados para Multi microprocessor applications


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Proposed transmission smart grids will use a digital platform for the automation of substations operating at voltage levels of 110 kV and above. The IEC 61850 series of standards, released in parts over the last ten years, provide a specification for substation communications networks and systems. These standards, along with IEEE Std 1588-2008 Precision Time Protocol version 2 (PTPv2) for precision timing, are recommended by the both IEC Smart Grid Strategy Group and the NIST Framework and Roadmap for Smart Grid Interoperability Standards for substation automation. IEC 61850-8-1 and IEC 61850-9-2 provide an inter-operable solution to support multi-vendor digital process bus solutions, allowing for the removal of potentially lethal voltages and damaging currents from substation control rooms, a reduction in the amount of cabling required in substations, and facilitates the adoption of non-conventional instrument transformers (NCITs). IEC 61850, PTPv2 and Ethernet are three complementary protocol families that together define the future of sampled value digital process connections for smart substation automation. This paper describes a specific test and evaluation system that uses real time simulation, protection relays, PTPv2 time clocks and artificial network impairment that is being used to investigate technical impediments to the adoption of SV process bus systems by transmission utilities. Knowing the limits of a digital process bus, especially when sampled values and NCITs are included, will enable utilities to make informed decisions regarding the adoption of this technology.

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In order to achieve meaningful reductions in individual ecological footprints, individuals must dramatically alter their day to day behaviours. Effective interventions will need to be evidence based and there is a necessity for the rapid transfer or communication of information from the point of research, into policy and practice. A number of health disciplines, including psychology and public health, share a common mission to promote health and well-being and it is becoming clear that the most practical pathway to achieving this mission is through interdisciplinary collaboration. This paper argues that an interdisciplinary collaborative approach will facilitate research that results in the rapid transfer of findings into policy and practice. The application of this approach is described in relation to the Green Living project which explored the psycho-social predictors of environmentally friendly behaviour. Following a qualitative pilot study, and in consultation with an expert panel comprising academics, industry professionals and government representatives, a self-administered mail survey was distributed to a random sample of 3000 residents of Brisbane and Moreton Bay (Queensland, Australia). The Green Living survey explored specific beliefs which included attitudes, norms, perceived control, intention and behaviour, as well as a number of other constructs such as environmental concern and altruism. This research has two beneficial outcomes. First, it will inform a practical model for predicting sustainable living behaviours and a number of local councils have already expressed an interest in making use of the results as part of their ongoing community engagement programs. Second, it provides an example of how a collaborative interdisciplinary project can provide a more comprehensive approach to research than can be accomplished by a single disciplinary project.

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As computer applications become more available—both technically and economically—construction project managers are increasingly able to access advanced computer tools capable of transforming the role that project managers have typically performed. Competence at using these tools requires a dual commitment in training—from the individual and the firm. Improving the computer skills of project managers can provide construction firms with a competitive advantage to differentiate from others in an increasingly competitive international market. Yet, few published studies have quantified what existing level of competence construction project managers have. Identification of project managers’ existing computer application skills is a necessary first step to developing more directed training to better capture the benefits of computer applications. This paper discusses the yet to be released results of a series of surveys undertaken in Malaysia, Singapore, Indonesia, Australia and the United States through QUT’s School of Construction Management and Property and the M.E. Rinker, Sr. School of Building Construction at the University of Florida. This international survey reviews the use and reported competence in using a series of commercially-available computer applications by construction project managers. The five different country locations of the survey allow cross-national comparisons to be made between project managers undertaking continuing professional development programs. The results highlight a shortfall in the ability of construction project managers to capture potential benefits provided by advanced computer applications and provide directions for targeted industry training programs. This international survey also provides a unique insight to the cross-national usage of advanced computer applications and forms an important step in this ongoing joint review of technology and the construction project manager.

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A trend in design and implementation of modern industrial automation systems is to integrate computing, communication and control into a unified framework at different levels of machine/factory operations and information processing. These distributed control systems are referred to as networked control systems (NCSs). They are composed of sensors, actuators, and controllers interconnected over communication networks. As most of communication networks are not designed for NCS applications, the communication requirements of NCSs may be not satisfied. For example, traditional control systems require the data to be accurate, timely and lossless. However, because of random transmission delays and packet losses, the control performance of a control system may be badly deteriorated, and the control system rendered unstable. The main challenge of NCS design is to both maintain and improve stable control performance of an NCS. To achieve this, communication and control methodologies have to be designed. In recent decades, Ethernet and 802.11 networks have been introduced in control networks and have even replaced traditional fieldbus productions in some real-time control applications, because of their high bandwidth and good interoperability. As Ethernet and 802.11 networks are not designed for distributed control applications, two aspects of NCS research need to be addressed to make these communication networks suitable for control systems in industrial environments. From the perspective of networking, communication protocols need to be designed to satisfy communication requirements for NCSs such as real-time communication and high-precision clock consistency requirements. From the perspective of control, methods to compensate for network-induced delays and packet losses are important for NCS design. To make Ethernet-based and 802.11 networks suitable for distributed control applications, this thesis develops a high-precision relative clock synchronisation protocol and an analytical model for analysing the real-time performance of 802.11 networks, and designs a new predictive compensation method. Firstly, a hybrid NCS simulation environment based on the NS-2 simulator is designed and implemented. Secondly, a high-precision relative clock synchronization protocol is designed and implemented. Thirdly, transmission delays in 802.11 networks for soft-real-time control applications are modeled by use of a Markov chain model in which real-time Quality-of- Service parameters are analysed under a periodic traffic pattern. By using a Markov chain model, we can accurately model the tradeoff between real-time performance and throughput performance. Furthermore, a cross-layer optimisation scheme, featuring application-layer flow rate adaptation, is designed to achieve the tradeoff between certain real-time and throughput performance characteristics in a typical NCS scenario with wireless local area network. Fourthly, as a co-design approach for both a network and a controller, a new predictive compensation method for variable delay and packet loss in NCSs is designed, where simultaneous end-to-end delays and packet losses during packet transmissions from sensors to actuators is tackled. The effectiveness of the proposed predictive compensation approach is demonstrated using our hybrid NCS simulation environment.

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In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.

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Human hair fibres are ubiquitous in nature and are found frequently at crime scenes often as a result of exchange between the perpetrator, victim and/or the surroundings according to Locard's Principle. Therefore, hair fibre evidence can provide important information for crime investigation. For human hair evidence, the current forensic methods of analysis rely on comparisons of either hair morphology by microscopic examination or nuclear and mitochondrial DNA analyses. Unfortunately in some instances the utilisation of microscopy and DNA analyses are difficult and often not feasible. This dissertation is arguably the first comprehensive investigation aimed to compare, classify and identify the single human scalp hair fibres with the aid of FTIR-ATR spectroscopy in a forensic context. Spectra were collected from the hair of 66 subjects of Asian, Caucasian and African (i.e. African-type). The fibres ranged from untreated to variously mildly and heavily cosmetically treated hairs. The collected spectra reflected the physical and chemical nature of a hair from the near-surface particularly, the cuticle layer. In total, 550 spectra were acquired and processed to construct a relatively large database. To assist with the interpretation of the complex spectra from various types of human hair, Derivative Spectroscopy and Chemometric methods such as Principal Component Analysis (PCA), Fuzzy Clustering (FC) and Multi-Criteria Decision Making (MCDM) program; Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and Geometrical Analysis for Interactive Aid (GAIA); were utilised. FTIR-ATR spectroscopy had two important advantages over to previous methods: (i) sample throughput and spectral collection were significantly improved (no physical flattening or microscope manipulations), and (ii) given the recent advances in FTIR-ATR instrument portability, there is real potential to transfer this work.s findings seamlessly to on-field applications. The "raw" spectra, spectral subtractions and second derivative spectra were compared to demonstrate the subtle differences in human hair. SEM images were used as corroborative evidence to demonstrate the surface topography of hair. It indicated that the condition of the cuticle surface could be of three types: untreated, mildly treated and treated hair. Extensive studies of potential spectral band regions responsible for matching and discrimination of various types of hair samples suggested the 1690-1500 cm-1 IR spectral region was to be preferred in comparison with the commonly used 1750-800 cm-1. The principal reason was the presence of the highly variable spectral profiles of cystine oxidation products (1200-1000 cm-1), which contributed significantly to spectral scatter and hence, poor hair sample matching. In the preferred 1690-1500 cm-1 region, conformational changes in the keratin protein attributed to the α-helical to β-sheet transitions in the Amide I and Amide II vibrations and played a significant role in matching and discrimination of the spectra and hence, the hair fibre samples. For gender comparison, the Amide II band is significant for differentiation. The results illustrated that the male hair spectra exhibit a more intense β-sheet vibration in the Amide II band at approximately 1511 cm-1 whilst the female hair spectra displayed more intense α-helical vibration at 1520-1515cm-1. In terms of chemical composition, female hair spectra exhibit greater intensity of the amino acid tryptophan (1554 cm-1), aspartic and glutamic acid (1577 cm-1). It was also observed that for the separation of samples based on racial differences, untreated Caucasian hair was discriminated from Asian hair as a result of having higher levels of the amino acid cystine and cysteic acid. However, when mildly or chemically treated, Asian and Caucasian hair fibres are similar, whereas African-type hair fibres are different. In terms of the investigation's novel contribution to the field of forensic science, it has allowed for the development of a novel, multifaceted, methodical protocol where previously none had existed. The protocol is a systematic method to rapidly investigate unknown or questioned single human hair FTIR-ATR spectra from different genders and racial origin, including fibres of different cosmetic treatments. Unknown or questioned spectra are first separated on the basis of chemical treatment i.e. untreated, mildly treated or chemically treated, genders, and racial origin i.e. Asian, Caucasian and African-type. The methodology has the potential to complement the current forensic analysis methods of fibre evidence (i.e. Microscopy and DNA), providing information on the morphological, genetic and structural levels.

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This paper demonstrates the capabilities of wavelet transform (WT) for analyzing important features related to bottleneck activations and traffic oscillations in congested traffic in a systematic manner. In particular, the analysis of loop detector data from a freeway shows that the use of wavelet-based energy can effectively identify the location of an active bottleneck, the arrival time of the resulting queue at each upstream sensor location, and the start and end of a transition during the onset of a queue. Vehicle trajectories were also analyzed using WT and our analysis shows that the wavelet-based energies of individual vehicles can effectively detect the origins of deceleration waves and shed light on possible triggers (e.g., lane-changing). The spatiotemporal propagations of oscillations identified by tracing wavelet-based energy peaks from vehicle to vehicle enable analysis of oscillation amplitude, duration and intensity.

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Spatially offset Raman spectroscopy (SORS) is a powerful new technique for the non-invasive detection and identification of concealed substances and drugs. Here, we demonstrate the SORS technique in several scenarios that are relevant to customs screening, postal screening, drug detection and forensics applications. The examples include analysis of a multi-layered postal package to identify a concealed substance; identification of an antibiotic capsule inside its plastic blister pack; analysis of an envelope containing a powder; and identification of a drug dissolved in a clear solvent, contained in a non-transparent plastic bottle. As well as providing practical examples of SORS, the results highlight several considerations regarding the use of SORS in the field, including the advantages of different analysis geometries and the ability to tailor instrument parameters and optics to suit different types of packages and samples. We also discuss the features and benefits of SORS in relation to existing Raman techniques, including confocal microscopy, wide area illumination and the conventional backscattered Raman spectroscopy. The results will contribute to the recognition of SORS as a promising method for the rapid, chemically-specific analysis and detection of drugs and pharmaceuticals.

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Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.

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The journalism revolution is upon us. In a world where we are constantly being told that everyone can be a publisher and challenges are emerging from bloggers, Twitterers and podcasters, journalism educators are inevitably reassessing what skills we now need to teach to keep our graduates ahead of the game. QUT this year tackled that question head-on as a curriculum review and program restructure resulted in a greater emphasis on online journalism. The author spent a week in the online newsrooms of each of two of the major players – ABC online news and thecouriermail.com to watch, listen and interview some of the key players. This, in addition to interviews with industry leaders from Fairfax and news.com, lead to the conclusion that while there are some new skills involved in new media much of what the industry is demanding is in fact good old fashioned journalism. Themes of good spelling, grammar, accuracy and writing skills and a nose for news recurred when industry players were asked what it was that they would like to see in new graduates. While speed was cited as one of the big attributes needed in online journalism, the conclusion of many of the players was that the skills of a good down-table sub or a journalist working for wire service were not unlike those most used in online newsrooms.

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This paper uses dynamic computer simulation techniques to develop and apply a multi-criteria procedure using non-destructive vibration-based parameters for damage assessment in truss bridges. In addition to changes in natural frequencies, this procedure incorporates two parameters, namely the modal flexibility and the modal strain energy. Using the numerically simulated modal data obtained through finite element analysis of the healthy and damaged bridge models, algorithms based on modal flexibility and modal strain energy changes before and after damage are obtained and used as the indices for the assessment of structural health state. The application of the two proposed parameters to truss-type structures is limited in the literature. The proposed multi-criteria based damage assessment procedure is therefore developed and applied to truss bridges. The application of the approach is demonstrated through numerical simulation studies of a single-span simply supported truss bridge with eight damage scenarios corresponding to different types of deck and truss damage. Results show that the proposed multi-criteria method is effective in damage assessment in this type of bridge superstructure.

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Bana et al. proposed the relation formal indistinguishability (FIR), i.e. an equivalence between two terms built from an abstract algebra. Later Ene et al. extended it to cover active adversaries and random oracles. This notion enables a framework to verify computational indistinguishability while still offering the simplicity and formality of symbolic methods. We are in the process of making an automated tool for checking FIR between two terms. First, we extend the work by Ene et al. further, by covering ordered sorts and simplifying the way to cope with random oracles. Second, we investigate the possibility of combining algebras together, since it makes the tool scalable and able to cover a wide class of cryptographic schemes. Specially, we show that the combined algebra is still computationally sound, as long as each algebra is sound. Third, we design some proving strategies and implement the tool. Basically, the strategies allow us to find a sequence of intermediate terms, which are formally indistinguishable, between two given terms. FIR between the two given terms is then guaranteed by the transitivity of FIR. Finally, we show applications of the work, e.g. on key exchanges and encryption schemes. In the future, the tool should be extended easily to cover many schemes. This work continues previous research of ours on use of compilers to aid in automated proofs for key exchange.

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Drawing on primary data and adjunct material, this article adopts a critical self-reflexive approach to a three-year, Australian Research Council-funded projectthat explored themes around 'employment citizenship'for high school students in Queensland. The article addresses three overlapping areas that reflect some of the central dilemmas and challenges arising through the project- consent in the context of research ethics, questionnaire administration in schools, and focus group research practice. It contributes to the broader methodological literature addressing research with young people by canvassing pragmatic suggestions for future school-based research, and research addressing adolescent employment.