726 resultados para Training method
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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 paper presents an analysis of phasor measurement method for tracking the fundamental power frequency to show if it has the performance necessary to cope with the requirements of power system protection and control. In this regard, several computer simulations presenting the conditions of a typical power system signal especially those highly distorted by harmonics, noise and offset, are provided to evaluate the response of the Phasor Measurement (PM) technique. A new method, which can shorten the delay of estimation, has also been proposed for the PM method to work for signals free of even-order harmonics.
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Purpose: The cornea is known to be susceptible to forces exerted by eyelids. There have been previous attempts to quantify eyelid pressure but the reliability of the results is unclear. The purpose of this study was to develop a technique using piezoresistive pressure sensors to measure upper eyelid pressure on the cornea. Methods: The technique was based on the use of thin (0.18 mm) tactile piezoresistive pressure sensors, which generate a signal related to the applied pressure. A range of factors that influence the response of this pressure sensor were investigated along with the optimal method of placing the sensor in the eye. Results: Curvature of the pressure sensor was found to impart force, so the sensor needed to remain flat during measurements. A large rigid contact lens was designed to have a flat region to which the sensor was attached. To stabilise the contact lens during measurement, an apparatus was designed to hold and position the sensor and contact lens combination on the eye. A calibration system was designed to apply even pressure to the sensor when attached to the contact lens, so the raw digital output could be converted to actual pressure units. Conclusions: Several novel procedures were developed to use tactile sensors to measure eyelid pressure. The quantification of eyelid pressure has a number of applications including eyelid reconstructive surgery and the design of soft and rigid contact lenses.
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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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Automatic Speech Recognition (ASR) has matured into a technology which is becoming more common in our everyday lives, and is emerging as a necessity to minimise driver distraction when operating in-car systems such as navigation and infotainment. In “noise-free” environments, word recognition performance of these systems has been shown to approach 100%, however this performance degrades rapidly as the level of background noise is increased. Speech enhancement is a popular method for making ASR systems more ro- bust. Single-channel spectral subtraction was originally designed to improve hu- man speech intelligibility and many attempts have been made to optimise this algorithm in terms of signal-based metrics such as maximised Signal-to-Noise Ratio (SNR) or minimised speech distortion. Such metrics are used to assess en- hancement performance for intelligibility not speech recognition, therefore mak- ing them sub-optimal ASR applications. This research investigates two methods for closely coupling subtractive-type enhancement algorithms with ASR: (a) a computationally-efficient Mel-filterbank noise subtraction technique based on likelihood-maximisation (LIMA), and (b) in- troducing phase spectrum information to enable spectral subtraction in the com- plex frequency domain. Likelihood-maximisation uses gradient-descent to optimise parameters of the enhancement algorithm to best fit the acoustic speech model given a word se- quence known a priori. Whilst this technique is shown to improve the ASR word accuracy performance, it is also identified to be particularly sensitive to non-noise mismatches between the training and testing data. Phase information has long been ignored in spectral subtraction as it is deemed to have little effect on human intelligibility. In this work it is shown that phase information is important in obtaining highly accurate estimates of clean speech magnitudes which are typically used in ASR feature extraction. Phase Estimation via Delay Projection is proposed based on the stationarity of sinusoidal signals, and demonstrates the potential to produce improvements in ASR word accuracy in a wide range of SNR. Throughout the dissertation, consideration is given to practical implemen- tation in vehicular environments which resulted in two novel contributions – a LIMA framework which takes advantage of the grounding procedure common to speech dialogue systems, and a resource-saving formulation of frequency-domain spectral subtraction for realisation in field-programmable gate array hardware. The techniques proposed in this dissertation were evaluated using the Aus- tralian English In-Car Speech Corpus which was collected as part of this work. This database is the first of its kind within Australia and captures real in-car speech of 50 native Australian speakers in seven driving conditions common to Australian environments.
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Aim: This study aimed to enhance the capacity of oncology nurses to provide supportive care for patients with advanced cancer who have dependent children. ---------- Method: This was a pilot study of an educational intervention comprising a study-developed self-directed learning manual, supported by a day-long communication skills training workshop. Evaluation pre- and post-training included measures of stress and burnout, self-reports of confidence and attitudes, responses to clinical vignettes and video-taped interviews with simulated patients.---------- Results: Nurses found the educational intervention highly acceptable, and reported increased confidence in their ability to provide information and support for parents, and to initiate discussion about emotional issues. There were significant improvements in general communication skills and skills specific to this training, as well as reduced use of blocking.---------- Conclusion: Brief communication skills training supplemented with tailored educational resources can enhance confidence skills and knowledge of oncology nurses regarding their supportive care of parents with advanced cancer.
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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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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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An algorithm to improve the accuracy and stability of rigid-body contact force calculation is presented. The algorithm uses a combination of analytic solutions and numerical methods to solve a spring-damper differential equation typical of a contact model. The solution method employs the recently proposed patch method, which especially suits the spring-damper differential equations. The resulting semi-analytic solution reduces the stiffness of the differential equations, while performing faster than conventional alternatives.
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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.
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Several approaches have been proposed to recognize handwritten Bengali characters using different curve fitting algorithms and curvature analysis. In this paper, a new algorithm (Curve-fitting Algorithm) to identify various strokes of a handwritten character is developed. The curve-fitting algorithm helps recognizing various strokes of different patterns (line, quadratic curve) precisely. This reduces the error elimination burden heavily. Implementation of this Modified Syntactic Method demonstrates significant improvement in the recognition of Bengali handwritten characters.