136 resultados para computer science and engineering
em Queensland University of Technology - ePrints Archive
Resumo:
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.
Resumo:
The QUT Extreme Science and Engineering program provides free hands-on workshops to schools, presented by scientists and engineers to students from prep to year 12 in their own classrooms. The workshops are tied to the school curriculum and give students access to professional quality instruments, helping to stimulate their interest in science and engineering, with the aim of generating a greater take up of STEM related subjects in the senior high school years. In addition to engaging students in activities, workshop presenters provide role models of both genders, helping to breakdown preconceived ideas of the type of person who becomes a scientist or engineer and demystifying the university experience. The Extreme Science and Engineering vans have been running for 10 years and as such demonstrate a sustainable and reproducible model for schools engagement. With funding provided through QUT’s Widening Participation Equity initiative (HEPPP funded) the vans which averaged 120 school visits each year has increased to 150+ visits in 2010. Additionally 100+ workshops (hands-on and career focused) have been presented to students from low socio-economic status schools, on the three QUT campuses in 2011. While this is designed as a long-term initiative the short term results have been very promising, with 3000 students attending the workshops in the first six months and teacher and students feedback has been overwhelmingly positive.
Resumo:
Policy makers increasingly recognise that an educated workforce with a high proportion of Science, Technology, Engineering and Mathematics (STEM) graduates is a pre-requisite to a knowledge-based, innovative economy. Over the past ten years, the proportion of first university degrees awarded in Australia in STEM fields is below the global average and continues to decrease from 22.2% in 2002 to 18.8% in 2010 [1]. These trends are mirrored by declines between 20% and 30% in the proportions of high school students enrolled in science or maths. These trends are not unique to Australia but their impact is of concern throughout the policy-making community. To redress these demographic trends, QUT embarked upon a long-term investment strategy to integrate education and research into the physical and virtual infrastructure of the campus, recognising that expectations of students change as rapidly as technology and learning practices change. To implement this strategy, physical infrastructure refurbishment/re-building is accompanied by upgraded technologies not only for learning but also for research. QUT’s vision for its city-based campuses is to create vibrant and attractive places to learn and research and to link strongly to the wider surrounding community. Over a five year period, physical infrastructure at the Gardens Point campus was substantially reconfigured in two key stages: (a) a >$50m refurbishment of heritage-listed buildings to encompass public, retail and social spaces, learning and teaching “test beds” and research laboratories and (b) destruction of five buildings to be replaced by a $230m, >40,000m2 Science and Engineering Centre designed to accommodate retail, recreation, services, education and research in an integrated, coordinated precinct. This landmark project is characterised by (i) self-evident, collaborative spaces for learning, research and social engagement, (ii) sustainable building practices and sustainable ongoing operation and; (iii) dynamic and mobile re-configuration of spaces or staffing to meet demand. Innovative spaces allow for transformative, cohort-driven learning and the collaborative use of space to prosecute joint class projects. Research laboratories are aggregated, centralised and “on display” to the public, students and staff. A major visualisation space – the largest multi-touch, multi-user facility constructed to date – is a centrepiece feature that focuses on demonstrating scientific and engineering principles or science oriented scenes at large scale (e.g. the Great Barrier Reef). Content on this visualisation facility is integrated with the regional school curricula and supports an in-house schools program for student and teacher engagement. Researchers are accommodated in a combined open-plan and office floor-space (80% open plan) to encourage interdisciplinary engagement and cross-fertilisation of skills, ideas and projects. This combination of spaces re-invigorates the on-campus experience, extends educational engagement across all ages and rapidly enhances research collaboration.
Resumo:
Purpose The purpose of this study was to evaluate the validity of the CSA activity monitor as a measure of children's physical activity using energy expenditure (EE) as a criterion measure. Methods Thirty subjects aged 10 to 14 performed three 5-min treadmill bouts at 3, 4, and 6 mph, respectively. While on the treadmill, subjects wore CSA (WAM 7164) activity monitors on the right and left hips. (V) over dot O-2 was monitored continuously by an automated system. EE was determined by multiplying the average (V) over dot O-2 by the caloric equivalent of the mean respiratory exchange ratio. Results Repeated measures ANOVA indicated that both CSA monitors were sensitive to changes in treadmill speed. Mean activity counts from each CSA unit were not significantly different and the intraclass reliability coefficient for the two CSA units across all speeds was 0.87. Activity counts from both CSA units were strongly correlated with EE (r = 0.86 and 0.87, P < 0.001). An EE prediction equation was developed from 20 randomly selected subjects and cross-validated on the remaining 10. The equation predicted mean EE within 0.01 kcal.min(-1). The correlation between actual and predicted values was 0.93 (P < 0.01) and the SEE was 0.93 kcal.min(-1). Conclusion These data indicate that the CSA monitor is a valid and reliable tool for quantifying treadmill walking and running in children.
Resumo:
Nowadays, Workflow Management Systems (WfMSs) and, more generally, Process Management Systems (PMPs) are process-aware Information Systems (PAISs), are widely used to support many human organizational activities, ranging from well-understood, relatively stable and structures processes (supply chain management, postal delivery tracking, etc.) to processes that are more complicated, less structured and may exhibit a high degree of variation (health-care, emergency management, etc.). Every aspect of a business process involves a certain amount of knowledge which may be complex depending on the domain of interest. The adequate representation of this knowledge is determined by the modeling language used. Some processes behave in a way that is well understood, predictable and repeatable: the tasks are clearly delineated and the control flow is straightforward. Recent discussions, however, illustrate the increasing demand for solutions for knowledge-intensive processes, where these characteristics are less applicable. The actors involved in the conduct of a knowledge-intensive process have to deal with a high degree of uncertainty. Tasks may be hard to perform and the order in which they need to be performed may be highly variable. Modeling knowledge-intensive processes can be complex as it may be hard to capture at design-time what knowledge is available at run-time. In realistic environments, for example, actors lack important knowledge at execution time or this knowledge can become obsolete as the process progresses. Even if each actor (at some point) has perfect knowledge of the world, it may not be certain of its beliefs at later points in time, since tasks by other actors may change the world without those changes being perceived. Typically, a knowledge-intensive process cannot be adequately modeled by classical, state of the art process/workflow modeling approaches. In some respect there is a lack of maturity when it comes to capturing the semantic aspects involved, both in terms of reasoning about them. The main focus of the 1st International Workshop on Knowledge-intensive Business processes (KiBP 2012) was investigating how techniques from different fields, such as Artificial Intelligence (AI), Knowledge Representation (KR), Business Process Management (BPM), Service Oriented Computing (SOC), etc., can be combined with the aim of improving the modeling and the enactment phases of a knowledge-intensive process. The 1st International Workshop on Knowledge-intensive Business process (KiBP 2012) was held as part of the program of the 2012 Knowledge Representation & Reasoning International Conference (KR 2012) in Rome, Italy, in June 2012. The workshop was hosted by the Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti of Sapienza Universita di Roma, with financial support of the University, through grant 2010-C26A107CN9 TESTMED, and the EU Commission through the projects FP7-25888 Greener Buildings and FP7-257899 Smart Vortex. This volume contains the 5 papers accepted and presented at the workshop. Each paper was reviewed by three members of the internationally renowned Program Committee. In addition, a further paper was invted for inclusion in the workshop proceedings and for presentation at the workshop. There were two keynote talks, one by Marlon Dumas (Institute of Computer Science, University of Tartu, Estonia) on "Integrated Data and Process Management: Finally?" and the other by Yves Lesperance (Department of Computer Science and Engineering, York University, Canada) on "A Logic-Based Approach to Business Processes Customization" completed the scientific program. We would like to thank all the Program Committee members for the valuable work in selecting the papers, Andrea Marrella for his valuable work as publication and publicity chair of the workshop, and Carola Aiello and the consulting agency Consulta Umbria for the organization of this successful event.
Resumo:
In many applications of active noise control (ANC), an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to adjust the secondary path estimation. Comparative simulation results shown in this paper indicate effectiveness of the proposed method.
Resumo:
An electrified railway system includes complex interconnections and interactions of several subsystems. Computer simulation is the only viable means for system evaluation and analysis. This paper discusses the difficulties and requirements of effective simulation models for this specialized industrial application; and the development of a general-purpose multi-train simulator.
Resumo:
A breaker restrike is an abnormal arcing phenomenon, leading to a possible breaker failure. Eventually, this failure leads to interruption of the transmission and distribution of the electricity supply system until the breaker is replaced. Before 2008, there was little evidence in the literature of monitoring techniques based on restrike measurement and interpretation produced during switching of capacitor banks and shunt reactor banks in power systems. In 2008 a non-intrusive radiometric restrike measurement method and a restrike hardware detection algorithm were developed by M.S. Ramli and B. Kasztenny. However, the limitations of the radiometric measurement method are a band limited frequency response as well as limitations in amplitude determination. Current restrike detection methods and algorithms require the use of wide bandwidth current transformers and high voltage dividers. A restrike switch model using Alternative Transient Program (ATP) and Wavelet Transforms which support diagnostics are proposed. Restrike phenomena become a new diagnostic process using measurements, ATP and Wavelet Transforms for online interrupter monitoring. This research project investigates the restrike switch model Parameter „A. dielectric voltage gradient related to a normal and slowed case of the contact opening velocity and the escalation voltages, which can be used as a diagnostic tool for a vacuum circuit-breaker (CB) at service voltages between 11 kV and 63 kV. During current interruption of an inductive load at current quenching or chopping, a transient voltage is developed across the contact gap. The dielectric strength of the gap should rise to a point to withstand this transient voltage. If it does not, the gap will flash over, resulting in a restrike. A straight line is fitted through the voltage points at flashover of the contact gap. This is the point at which the gap voltage has reached a value that exceeds the dielectric strength of the gap. This research shows that a change in opening contact velocity of the vacuum CB produces a corresponding change in the slope of the gap escalation voltage envelope. To investigate the diagnostic process, an ATP restrike switch model was modified with contact opening velocity computation for restrike waveform signature analyses along with experimental investigations. This also enhanced a mathematical CB model with the empirical dielectric model for SF6 (sulphur hexa-fluoride) CBs at service voltages above 63 kV and a generalised dielectric curve model for 12 kV CBs. A CB restrike can be predicted if there is a similar type of restrike waveform signatures for measured and simulated waveforms. The restrike switch model applications are used for: computer simulations as virtual experiments, including predicting breaker restrikes; estimating the interrupter remaining life of SF6 puffer CBs; checking system stresses; assessing point-on-wave (POW) operations; and for a restrike detection algorithm development using Wavelet Transforms. A simulated high frequency nozzle current magnitude was applied to an Equation (derived from the literature) which can calculate the life extension of the interrupter of a SF6 high voltage CB. The restrike waveform signatures for a medium and high voltage CB identify its possible failure mechanism such as delayed opening, degraded dielectric strength and improper contact travel. The simulated and measured restrike waveform signatures are analysed using Matlab software for automatic detection. Experimental investigation of a 12 kV vacuum CB diagnostic was carried out for the parameter determination and a passive antenna calibration was also successfully developed with applications for field implementation. The degradation features were also evaluated with a predictive interpretation technique from the experiments, and the subsequent simulation indicates that the drop in voltage related to the slow opening velocity mechanism measurement to give a degree of contact degradation. A predictive interpretation technique is a computer modeling for assessing switching device performance, which allows one to vary a single parameter at a time; this is often difficult to do experimentally because of the variable contact opening velocity. The significance of this thesis outcome is that it is a non-intrusive method developed using measurements, ATP and Wavelet Transforms to predict and interpret a breaker restrike risk. The measurements on high voltage circuit-breakers can identify degradation that can interrupt the distribution and transmission of an electricity supply system. It is hoped that the techniques for the monitoring of restrike phenomena developed by this research will form part of a diagnostic process that will be valuable for detecting breaker stresses relating to the interrupter lifetime. Suggestions for future research, including a field implementation proposal to validate the restrike switch model for ATP system studies and the hot dielectric strength curve model for SF6 CBs, are given in Appendix A.
Resumo:
Deterministic computer simulation of physical experiments is now a common technique in science and engineering. Often, physical experiments are too time consuming, expensive or impossible to conduct. Complex computer models or codes, rather than physical experiments lead to the study of computer experiments, which are used to investigate many scientific phenomena. A computer experiment consists of a number of runs of the computer code with different input choices. The Design and Analysis of Computer Experiments is a rapidly growing technique in statistical experimental design. This paper aims to discuss some practical issues when designing a computer simulation and/or experiments for manufacturing systems. A case study approach is reviewed and presented.
Resumo:
Deterministic computer simulations of physical experiments are now common techniques in science and engineering. Often, physical experiments are too time consuming, expensive or impossible to conduct. Complex computer models or codes, rather than physical experiments lead to the study of computer experiments, which are used to investigate many scientific phenomena of this nature. A computer experiment consists of a number of runs of the computer code with different input choices. The Design and Analysis of Computer Experiments is a rapidly growing technique in statistical experimental design. This thesis investigates some practical issues in the design and analysis of computer experiments and attempts to answer some of the questions faced by experimenters using computer experiments. In particular, the question of the number of computer experiments and how they should be augmented is studied and attention is given to when the response is a function over time.
Resumo:
Governments have recognised that the technological trades rely on knowledge embedded traditionally in science, technology, engineering and mathematics (STEM) disciplines. However, there is substantial evidence that students are turning away from these subjects in schools because the school curriculum is seen as irrelevant, with clear implications for not just vocational education but also higher education. In this paper, we report preliminary findings on the development of two curricula that attempt to integrate science and mathematics with workplace knowledge and practices. We argue that these curricula provide educational opportunities for students to pursue their preferred career pathways. These curricula were co-developed by industry and educational personnel across three industry sectors, namely, mining industry, aerospace and wine tourism. The aim was to provide knowledge appropriate for students moving from school to the workplace as trade apprentices in the respective industries. The analysis of curriculum and associated policy documents reveals that the curricula adopt applied learning orientations through teaching strategies and assessment practices which focus on practical skills. However, although key theoretical science and maths concepts have been well incorporated, the extent to which knowledge deriving from workplace practices is included varies across the curricula. The extent to which applications of concepts are included in the models depends on a number of factors not least the relevant expertise of the teacher as a practitioner in the industry. Our findings highlight the importance of teachers having substantial practical industry experience and the role that whole school policies play in attempts to align the range of learning experiences with the needs of industry.
Resumo:
Social networking sites (SNSs), with their large numbers of users and large information base, seem to be perfect breeding grounds for exploiting the vulnerabilities of people, the weakest link in security. Deceiving, persuading, or influencing people to provide information or to perform an action that will benefit the attacker is known as “social engineering.” While technology-based security has been addressed by research and may be well understood, social engineering is more challenging to understand and manage, especially in new environments such as SNSs, owing to some factors of SNSs that reduce the ability of users to detect the attack and increase the ability of attackers to launch it. This work will contribute to the knowledge of social engineering by presenting the first two conceptual models of social engineering attacks in SNSs. Phase-based and source-based models are presented, along with an intensive and comprehensive overview of different aspects of social engineering threats in SNSs.