995 resultados para Active tracking


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This article focuses on the evaluation of thesis supervision and highlights the vast range of problem areas presently documented as significant areas of concern for both graduate students and their supervisors. Additionally, the authors report on a study completed in 1995, which surveyed all Australian universities about current evaluative practices in postgraduate supervision. The conclusion of this study was that the conduct of such evaluations appears to be minimal and is primarily designed to obtain an indicator of the general “health” of a university's postgraduate supervision rather than to foster improved supervisory practices. As part of the same study, the authors conducted University faculty-based student and supervisor focus groups. Key issues emerging from these focus groups were: (1) the importance of relational aspects of supervision as the student communicates over the long term with one or more supervisors; (2) the importance of systematic feedback, monitoring, and evaluation to the supervisory process; and (3) the lack of strategies to facilitate this evaluative feedback process. On the basis of these findings, the authors designed evaluative strategies to facilitate regular ongoing feedback between students and supervisors.

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The last few decades have witnessed a broad international movement towards the development of inclusive schools through targeted special education funding and resourcing policies. Student placement statistics are often used as a barometer of policy success but they may also be an indication of system change. In this paper, trends in student enrolments from the Australian state of New South Wales are considered in an effort to understand what effect inclusive education has had in this particular region of the world.

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Our everyday environment is full of text but this rich source of information remains largely inaccessible to mobile robots. In this paper we describe an active text spotting system that uses a small number of wide angle views to locate putative text in the environment and then foveates and zooms onto that text in order to improve the reliability of text recognition. We present extensive experimental results obtained with a pan/tilt/zoom camera and a ROS-based mobile robot operating in an indoor environment.

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This paper presents a novel power control strategy that decouples the active and reactive power for a synchronous generator connected to a power network. The proposed control paradigm considers the capacitance of the transmission line along with its resistance and reactance as-well. Moreover the proposed controller takes into account all cases of R-X relationships, thus allowing it to function in Virtual Power Plant (VPP) structures which operate at both medium voltage (MV) and low voltage (LV) levels. The independent control of active and reactive power is achieved through rotational transformations of the terminal voltages and currents at the synchronous generator's output. This paper details the control technique by first presenting the mathematical and electrical network analysis of the methodology and then successfully implementing the control using MATLAB-SIMULINK simulation.

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Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.

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This paper proposes a self-tuning feedforward active noise control (ANC) system with online secondary path modeling. The step-size parameters of the controller and modeling filters have crucial rule on the system performance. In literature, these parameters are adjusted by trial-and-error. In other words, they are manually initialized before system starting, which require performing extensive experiments to ensure the convergence of the system. Hence there is no guarantee that the system could perform well under different situations. In the proposed method, the appropriate values for the step-sizes are obtained automatically. Computer simulation results indicate the effectiveness of the proposed method.

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In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. 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 correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.

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Several approaches have been introduced in literature for active noise control (ANC) systems. Since FxLMS algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANC applications an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. This paper also proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Benefiting new version of FxLMS algorithm and not continually injection of white noise makes the system more desirable and improves the noise attenuation performance. Comparative simulation results indicate effectiveness of the proposed approach.

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An online secondary path modelling method using a white noise as a training signal is required in many applications of active noise control (ANC) to ensure convergence of the system. Not continually injection of white noise during system operation makes the system more desirable. The purposes of the proposed method are two folds: controlling white noise by preventing continually injection, and benefiting white noise with a larger variance. 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. This paper proposes a new approach for online secondary path modelling in feedfoward ANC systems. 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. Comparative simulation results shown in this paper indicate effectiveness of the proposed approach in controlling active noise.

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The aim of this systematic review was to examine the effect of Contrast Water Therapy (CWT) on recovery following exercise induced muscle damage. Controlled trials were identified from computerized literature searching and citation tracking performed up to February 2013. Eighteen trials met the inclusion criteria; all had a high risk of bias. Pooled data from 13 studies showed that CWT resulted in significantly greater improvements in muscle soreness at the five follow-up time points(<6, 24, 48, 72 and 96 hours) in comparison to passive recovery. Pooled data also showed that CWT significantly reduced muscle strength loss at each follow-up time (<6, 24, 48, 72 and 96 hours) in comparison to passive recovery. Despite comparing CWT to a large number of other recovery interventions, including cold water immersion, warm water immersion, compression, active recovery and stretching, there was little evidence for a superior treatment intervention. The current evidence base shows that CWT is superior to using passive recovery or rest after exercise; the magnitudes of these effects may be most relevant to an elite sporting population. There seems to be little difference in recovery outcome between CWT and other popular recovery interventions.

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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.

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This paper presents an Image Based Visual Servo control design for Fixed Wing Unmanned Aerial Vehicles tracking locally linear infrastructure in the presence of wind using a body fixed imaging sensor. Visual servoing offers improved data collection by posing the tracking task as one of controlling a feature as viewed by the inspection sensor, although is complicated by the introduction of wind as aircraft heading and course angle no longer align. In this work it is shown that the effects of wind alter the desired line angle required for continuous tracking to equal the wind correction angle as would be calculated to set a desired course. A control solution is then sort by linearizing the interaction matrix about the new feature pose such that kinematics of the feature can be augmented with the lateral dynamics of the aircraft, from which a state feedback control design is developed. Simulation results are presented comparing no compensation, integral control and the proposed controller using the wind correction angle, followed by an assessment of response to atmospheric disturbances in the form of turbulence and wind gusts

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Growing community concerns about the ecological, social, cultural and economic impact of housing and urban projects poses new challenges for those who have to deliver them. It is important that these concerns are addressed as part of the community engagement processes on projects. Community engagement is traditionally perceived as the purview of planners and disconnected from the building construction process. This is despite most project approval processes mandating on-going community engagement over the project’s entire lifetime. There is evidence that point to a culture of ambiguity and ambivalence among building professionals about their roles, responsibilities and expectations of community engagement during the construction phase of projects. This has contributed to a culture of distrust between communities and the construction industry. There is a clear need to build capacity among building professionals to empower them as active participants in community engagement processes which can promote better project outcomes and minimise delays and conflicts. This paper describes a process that utilises the Theory of Planned Behaviour as a framework to equip building professionals with the skills they need to engage effectively with local communities during the construction phase of projects.

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Aim: The movement from a medical model of disability to a more social model implies an imperative to include the views of people with ID in research regarding their care. Contemporary quality processes in improving care require consumer involvement at many levels and in doing so have shown better outcomes. A New Zealand research study is being undertaken utilizing focus groups with people with ID to understand their experiences during a psychiatric inpatient admission. The primary focus of this presentation will concern the literature review, undertaken as part of the study, of research in which people with ID have participated. Method: The literature review was conducted using a variety of electronic databases and search terms to identify studies with people with ID as active participants. Results: Only a few studies have been undertaken with people with ID as participants. While these studies demonstrate numerous benefits in including the voice of the person with ID this still remains absent from much of the research discourse. Conclusion: It is accepted and indeed advocated that people with ID have the same rights as others in regard to choosing whether or not they wish to participate in research. High response rates in the few identified studies indicated that people with ID are eager to be consulted. It is recommended that the unique needs of people with ID be taken into account in the research evidence base for future services.

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In Australia, as in some other western nations, governments impose accountability measures on educational institutions (Earl, 2005). One such accountability measure is the National Assessment Program - Literacy and Numeracy (NAPLAN) from which high-stakes assessment data is generated. In this article, a practical method of data analysis known as the Over Time Assessment Data Analysis (OTADA) is offered as an analytical process by which schools can monitor their current and over time performances. This analysis developed by the author, is currently used extensively in schools throughout Queensland. By Analysing in this way, teachers, and in particular principals, can obtain a quick and insightful performance overview. For those seeking to track the achievements and progress of year level cohorts, the OTADA should be considered.