485 resultados para Space flight training


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In this paper, we consider a time-space fractional diffusion equation of distributed order (TSFDEDO). The TSFDEDO is obtained from the standard advection-dispersion equation by replacing the first-order time derivative by the Caputo fractional derivative of order α∈(0,1], the first-order and second-order space derivatives by the Riesz fractional derivatives of orders β 1∈(0,1) and β 2∈(1,2], respectively. We derive the fundamental solution for the TSFDEDO with an initial condition (TSFDEDO-IC). The fundamental solution can be interpreted as a spatial probability density function evolving in time. We also investigate a discrete random walk model based on an explicit finite difference approximation for the TSFDEDO-IC.

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This paper addresses the challenges of transfer of training back to the workplace for programme and project managers who are being groomed for the leadership of large and complex projects. The paper draws on the experience of the development and delivery of Queensland University of Technology (QUT) education programs: an Executive Masters of Complex Project Management and a series of Continuing Professional Development (CPD) events for an Australian government agency, Defence Materiel Organisation (DMO). Drawing on notions of ‘far transfer’ (Laker 1990; Noe, 1986) and ‘transfer climate’ (Kozlowski & Salas, 1993; Yamnill & McLean, 2001), the paper describes the steps undertaken to achieve a design that ensures that programme and project leadership skills developed through these corporate education programs become successfully embedded back in the organisation. Further, the paper reports on a small qualitative study where the programme success was evaluated by the organisational sponsor, senior leaders and program participants. Nine interviews were conducted and analysed to identify the success of far transfer and transfer climate four months after the return of program participants from cohort 1 2008 to the workplace.

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"This book focuses on issues in literacy and technology at the K-12 level in a holistic manner so that the needs of teachers and researchers can be addressed through the use of state-of-the-art perspectives"

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The type and quality of youth identities ascribed to young people living in residual housing areas present opportunities for action as well as structural constraints. In this book three ethnographies, based on a youth work practitioner's observations, interviews and participation in local networks, identify young people's resistant identities. Through an analysis of social exclusion, youth policies and interviews with young people, youth workers and their managers, the book outlines a contingent network of relationships that hinder informal learning. Globalisation, individualisation, welfare/education reform and the rise of cultural social movements act upon youth identities and steer youth policies to subordinate the notion of informal group learning. Drawing on Castells' and Touraine's sociological models of identity, the book explores youth as a category of time and residual housing areas as a category of space, as they pertain to local dynamics of social exclusion.

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This paper acknowledges the influences that a generation Y population brings to dance training methodologies and examines this impact in a tertiary context. Over the last 4 years, Queensland University of Technology has been modifying their curriculum for new students transitioning from the private dance studio into the prevocational university environment. An intensive training program was designed to empower the student creating effective entry points for common understandings in the learning and teaching of dance techniques with improved and accelerated learning outcomes. This paper shares these philosophies and practices in training for life-long learning that prepare the young dancer for longevity in the industry.

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The studio-gameon event was supported by the Institute of the Creative Industries and Innovation and the Faculty of IT as part of the State Library of Queensland GAME ON exhibition (ex Barbican, UK) The studio produced a full game in six weeks. It was a curated event, a live web-based exhibition, a performance for the public and the team produced a digital / creative work which is available for download. The studio enabled a team of students to experience the pressures of a real game studio within the space of the precincts but also very much in the public eye. It was a physical hypothesis of the University's mantra - "for the real world" statement: Studio GameOn is an opportunity running alongside the GAME ON exhibition at the State Library of Queensland. The exhibition itself is open to the public from November 17th through to February 15th. The studio runs from January 5th to February 13th 2009. The Studio GameOn challenge? To put together a team of game developers and make a playable game in six weeks! The studio-game on team consists of a group of game developers in training - the team members are all students who are either half-way through or completing a qualification in game design and all its elements - we have designers, artists, programmers and productionteam members. We are also fortunate to have an Industry Board consisting of local Queensland Games professionals: John Passfield (Red Sprite Studios), Adrian Cook (WIldfire Studios) and Duncan Curtis and Marko Grgic (The 3 Blokes). We also invite the public to play with us - there is an ideas box both on-site at the State Library and a number of ways to communicate with us on this studio website.

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Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

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Reforms to the national research and research training system by the Commonwealth Government of Australia sought to effectively connect research conducted in universities to Australia's national innovation system. Research training has a key role in ensuring an adequate supply of highly skilled people for the national innovation system. During their studies, research students produce and disseminate a massive amount of new knowledge. Prior to this study, there was no research that examined the contribution of research training to Australia's national innovation system despite the existence of policy initiatives aiming to enhance this contribution. Given Australia's below average (but improving) innovation performance compared to other OECD countries, the inclusion of Finland and the United States provided further insights into the key research question. This study examined three obvious ways that research training contributes to the national innovation systems in the three countries: the international mobility and migration of research students and graduates, knowledge production and distribution by research students, and the impact of research training as advanced human capital formation on economic growth. Findings have informed the concept of a research training culture of innovation that aims to enhance the contribution of research training to Australia's national innovation system. Key features include internationally competitive research and research training environments; research training programs that equip students with economically-relevant knowledge and the capabilities required by employers operating in knowledge-based economies; attractive research careers in different sectors; a national commitment to R&D as indicated by high levels of gross and business R&D expenditure; high private and social rates of return from research training; and the horizontal coordination of key organisations that create policy for, and/or invest in research training.

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This design research concerns the generation of spaces that fully respond to people’s presence and their activities and spatialises the dynamics of a full body massage. Researched though digital and physical modelling full size physical form was constructed using Ethylene Vinyl Acetate (EVA) foam with three-dimensional shape defined by a computer generated cutting pattern, and assembled into a non-linear articulated surface.

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The purpose of the current article was to explore perceptions of transitional employment and training and development amongst blue collar workers employed in technical, trade, operations or physical and labour-intensive occupations within the local government system.

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This paper considers the pros and cons of using Behavioural cloning for the development of low-level helicopter automation modules. Over the course of this project several Behavioural cloning approaches have been investigated. The results of the most effective Behavioural cloning approach are then compared to PID modules designed for the same aircraft. The comparison takes into consideration development time, reliability, and control performance. It has been found that Behavioural cloning techniques employing local approximators and a wide state-space coverage during training can produce stabilising control modules in less time than tuning PID controllers. However, performance and reliabity deficits have been found to exist with the Behavioural Cloning, attributable largely to the time variant nature of the dynamics due to the operating environment, and the pilot actions being poor for teaching. The final conclusion drawn here is that tuning PID modules remains superior to behavioural cloning for low-level helicopter automation.

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We are thesis examiners within the Australian academic system who formed a “community of practice” to try to resolve some of the issues we were facing. Stories of examiners reflecting on and examining their own practice are a notable silence in the higher degree research literature. In this study we have adopted a storytelling inquiry method that involved telling our practitioner stories, firstly to each other and then to a wider audience through this paper. We then identified issues that we believe are relevant to other thesis examiners. We have also found that engaging in a “community of practice” is itself a valuable form of examiner professional development. Key Words: Thesis Examiner Training, Storytelling, and Practitioner Research

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This paper presents a novel matched rotation precoding (MRP) scheme to design a rate one space-frequency block code (SFBC) and a multirate SFBC for MIMO-OFDM systems with limited feedback. The proposed rate one MRP and multirate MRP can always achieve full transmit diversity and optimal system performance for arbitrary number of antennas, subcarrier intervals, and subcarrier groupings, with limited channel knowledge required by the transmit antennas. The optimization process of the rate one MRP is simple and easily visualized so that the optimal rotation angle can be derived explicitly, or even intuitively for some cases. The multirate MRP has a complex optimization process, but it has a better spectral efficiency and provides a relatively smooth balance between system performance and transmission rate. Simulations show that the proposed SFBC with MRP can overcome the diversity loss for specific propagation scenarios, always improve the system performance, and demonstrate flexible performance with large performance gain. Therefore the proposed SFBCs with MRP demonstrate flexibility and feasibility so that it is more suitable for a practical MIMO-OFDM system with dynamic parameters.

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This volume examines the social, cultural, and political implications of the shift from traditional forms of print-based libraries to the delivery of online information in educational contexts. Despite the central role of libraries in literacy and learning, research of them has, in the main, remained isolated within the disciplinary boundaries of information and library science. By contrast, this book problematizes and thereby mainstreams the field. It brings together scholars from a wide range of academic fields to explore the dislodging of library discourse from its longstanding apolitical, modernist paradigm. Collectively, the authors interrogate the presuppositions of current library practice and examine how library as place and library as space blend together in ways that may be both complementary and contradictory. Seeking a suitable term to designate this rapidly evolving and much contested development, the editors devised the word “libr@ary,” and use the term arobase to signify the conditions of formation of new libraries within contexts of space, knowledge, and capital.

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The over representation of novice drivers in crashes is alarming. Research indicates that one in five drivers’ crashes within their first year of driving. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the drive. This paper presents a system that evaluates the data stream acquired from multiple in-vehicle sensors (acquired from Driver Vehicle Environment-DVE) using fuzzy rules and classifies the driving manoeuvres (i.e. overtake, lane change and turn) as low risk or high risk. The fuzzy rules use parameters such as following distance, frequency of mirror checks, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvre to assess risk. The fuzzy rules to estimate risk are designed after analysing the selected driving manoeuvres performed by driver trainers. This paper focuses mainly on the difference in gaze pattern for experienced and novice drivers during the selected manoeuvres. Using this system, trainers of novice drivers would be able to empirically evaluate and give feedback to the novice drivers regarding their driving behaviour.