978 resultados para automated online-coaching


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A new online method is presented for estimation of the angular randomwalk and rate randomwalk coefficients of inertial measurement unit gyros and accelerometers. In the online method, a state-space model is proposed, and recursive parameter estimators are proposed for quantities previously measured from offline data techniques such as the Allan variance method. The Allan variance method has large offline computational effort and data storage requirements. The technique proposed here requires no data storage and computational effort of approximately 100 calculations per data sample.

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Background Breastfeeding is recognised as the optimal method for feeding infants with health gains made by reducing infectious diseases in infancy; and chronic diseases, including obesity, in childhood, adolescence and adulthood. Despite this, exclusivity and duration in developed countries remains resistant to improvement. The objectives of this research were to test if an automated mobile phone text messaging intervention, delivering one text message a week, could increase “any” breastfeeding rates and improve breastfeeding self-efficacy and coping. Methods Women were eligible to participate if they were: over eighteen years; had an infant less than three months old; were currently breastfeeding; no diagnosed mental illness; and used a mobile phone . Women in the intervention group received MumBubConnect, a text messaging service with automated responses delivered once a week for 8 weeks. Women in the comparison group received their usual care and were sampled two years after the intervention group. Data collection included online surveys at two time points, week zero and week nine, to measure breastfeeding exclusivity and duration, coping, emotions, accountability and self-efficacy. A range of statistical analyses were used to test for differences between groups. Hierarchical regression was used to investigate change in breastfeeding outcome, between groups, adjusting for co-variates. Results The intervention group had 120 participants at commencement and 114 at completion, the comparison group had 114 participants at commencement and 86 at completion. MumBubConnect had a positive impact on the primary outcome of breastfeeding behaviors with women receiving the intervention more likely to continue exclusive breastfeeding; with a 6% decrease in exclusive breastfeeding in the intervention group, compared to a 14% decrease in the comparison group (p < 0.001). This remained significant after controlling for infant age, mother’s income, education and delivery type (p = 0.04). Women in the intervention group demonstrated active coping and were less likely to display emotions-focussed coping (p < .001). There was no discernible statistical effect on self-efficacy or accountability. Conclusions A fully automated text messaging services appears to improve exclusive breastfeeding duration. The service provides a well-accepted, personalised support service that empowers women to actively resolve breastfeeding issues. Trial registration Australian New Zealand Clinical Trials Registry: ACTRN12614001091695.

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Now is not the time to increase the strength of copyright law. Copyright law is facing a crisis of legitimacy: consumers increasingly appear to doubt its moral weight. To a large extent, this can be traced to the fact that Australian consumers do not believe they are being treated fairly by (predominantly US-based) copyright producers and distributors. Compared to their overseas peers, Australian consumers pay much more for access to books, films, television, and computer games, and are often subjected to long delays before material is available in Australia. Our research shows that this perceived unfairness increases the willingness of Australian consumers to seek out alternative distribution channels. Put simply, the failure of content distributors to meet consumer demand in Australia is a leading factor in copyright infringement. This submission argues that the best strategy to reduce copyright infringement in Australia, at the present time, is for distributors to focus on providing timely, affordable, convenient and fair access to copyright goods. Until this is done, the prevalence of copyright infringement in Australia should be seen as essentially a market problem, rather than a legal one. The Australian Government, meanwhile, should address the recommendations of the IT Pricing Report as a matter a priority. As a first step, the Government should urgently consider repealing the IP exception to competition law in s 51(3), as recommended by the Ergas committee, the IT Pricing report, and the ALRC. This change alone may go a long way to enhancing the efficiency of the copyright market in Australia.

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This submission focuses on the adverse effects that the Government’s proposals are likely to have on the legitimate use of copyright works. Copyright exists to support the production of new expression. Because new expression always builds on existing culture, any extension of copyright protection necessarily also increases the costs of creative expression. As a threshold matter, we do not believe that these further increases to the force of copyright law are justified. In recent years, the balance at the heart of copyright law has tipped too far in the direction of established producers and distributors, and now imposes unnecessary costs on ordinary creators. The available evidence does not support a further increase in the penalties and enforcement mechanisms available under copyright law.

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Double-pulse tests are commonly used as a method for assessing the switching performance of power semiconductor switches in a clamped inductive switching application. Data generated from these tests are typically in the form of sampled waveform data captured using an oscilloscope. In cases where it is of interest to explore a multi-dimensional parameter space and corresponding result space it is necessary to reduce the data into key performance metrics via feature extraction. This paper presents techniques for the extraction of switching performance metrics from sampled double-pulse waveform data. The reported techniques are applied to experimental data from characterisation of a cascode gate drive circuit applied to power MOSFETs.

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This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

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A new Bachelor of Science (BSc) course was introduced at Queensland University of Technology (QUT) in 2013 and focused on inquiry-based, collaborative and active learning. Two of the first year units required that students carry out a group poster assessment task. This poster provides a preliminary evaluation from an academic staff perspective of the assessment approach used, whereby students created digital posters to utilise the affordances of new learning spaces. The digital posters approach was first introduced to a group of academic staff from the Science and Engineering Faculty (SEF) in 2012 during a professional development program to explicitly develop skills and shared understandings of teaching in collaborative learning spaces (Steel & Andrews, 2012). Considerations were given to the pedagogical requirements of a poster assessment task, the affordances of the learning space and an identification of possible benefits of using Google Sites to create digital posters. Positive feedback from this group (as highlighted in the quotes shown) and subsequent approval from unit coordinators for two of the new first year BSc units meant that the approach was adopted for Semester 1, 2013 with approximately 360 students in each unit.

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The enactment of learning to become a science teacher in online mode is an emotionally charged experience. We attend to the formation, maintenance and disruption of social bonds experienced by online preservice science teachers as they shared their emotional online learning experiences through blogs, or e-motion diaries, in reaction to videos of face-to-face lessons. A multi-theoretic framework drawing on microsociological perspectives of emotion informed our hermeneutic interpretations of students’ first-person accounts reported through an e-motion diary. These accounts were analyzed through our own database of emotion labels constructed from the synthesis of existing literature on emotion across a range of fields of inquiry. Preservice science teachers felt included in the face-to-face group as they watched videos of classroom transactions. The strength of these feelings of social solidarity were dependent on the quality of the video recording. E-motion diaries provided a resource for interactions focused on shared emotional experiences leading to formation of social bonds and the alleviation of feelings of fear, trepidation and anxiety about becoming science teachers. We offer implications to inform practitioners who wish to improve feelings of inclusion amongst their online learners in science education.

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Purpose The aim of the study was to determine the association, agreement, and detection capability of manual, semiautomated, and fully automated methods of corneal nerve fiber length (CNFL) quantification of the human corneal subbasal nerve plexus (SNP). Methods Thirty-three participants with diabetes and 17 healthy controls underwent laser scanning corneal confocal microscopy. Eight central images of the SNP were selected for each participant and analyzed using manual (CCMetrics), semiautomated (NeuronJ), and fully automated (ACCMetrics) software to quantify the CNFL. Results For the entire cohort, mean CNFL values quantified by CCMetrics, NeuronJ, and ACCMetrics were 17.4 ± 4.3 mm/mm2, 16.0 ± 3.9 mm/mm2, and 16.5 ± 3.6 mm/mm2, respectively (P < 0.01). CNFL quantified using CCMetrics was significantly higher than those obtained by NeuronJ and ACCMetrics (P < 0.05). The 3 methods were highly correlated (correlation coefficients 0.87–0.98, P < 0.01). The intraclass correlation coefficients were 0.87 for ACCMetrics versus NeuronJ and 0.86 for ACCMetrics versus CCMetrics. Bland–Altman plots showed good agreement between the manual, semiautomated, and fully automated analyses of CNFL. A small underestimation of CNFL was observed using ACCMetrics with increasing the amount of nerve tissue. All 3 methods were able to detect CNFL depletion in diabetic participants (P < 0.05) and in those with peripheral neuropathy as defined by the Toronto criteria, compared with healthy controls (P < 0.05). Conclusions Automated quantification of CNFL provides comparable neuropathy detection ability to manual and semiautomated methods. Because of its speed, objectivity, and consistency, fully automated analysis of CNFL might be advantageous in studies of diabetic neuropathy.

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Devising assessment tasks for large units that embrace academic goals of authenticity and assessment variety can be a challenge. We developed an online Role-Play Assessment Initiative for first year nursing students in bioscience. Students responded to a case study by preparing two role-play dialogues: as a nurse with the patient, and between two nurses. The aims were to assess whether the students could: 1) understand the underlying disease process (pathophysiology) and relate it to clinical practice; 2) use language appropriate for lay and medical conversation; and 3) apply information using active learning. We conducted a student survey using quantitative questions (Likert scale: 1=strongly disagree to 5=strongly agree), and qualitative questions. 65 completed surveys were received. 80% of respondents agreed (includes agree or strongly agree) that it was a useful way to learn and understand pathophysiology of the case study. 86% agreed that it was useful to apply pathophysiology from lectures to a clinical setting. Overall, students found it enjoyable, which is beneficial for enhanced student engagement, and agreed that it allowed them to work well in a group (74% and 85%, respectively). Most qualitative suggestions for improvement related to group work, despite the encouraging response to group work in quantitative questions. Most positive comments surrounded different communication with a nurse compared with a patient. These results demonstrate that students developed deeper understanding of pathophysiology through active learning and were able to expand their nursing career skills during the role-play. Learning using role-play to simulate the workforce has fostered active learning.

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Background: The prevalence of type 2 diabetes is rising with the majority of patients practicing inadequate disease self-management. Depression, anxiety, and diabetes-specific distress present motivational challenges to adequate self-care. Health systems globally struggle to deliver routine services that are accessible to the entire population, in particular in rural areas. Web-based diabetes self-management interventions can provide frequent, accessible support regardless of time and location Objective: This paper describes the protocol of an Australian national randomized controlled trial (RCT) of the OnTrack Diabetes program, an automated, interactive, self-guided Web program aimed to improve glycemic control, diabetes self-care, and dysphoria symptoms in type 2 diabetes patients. Methods: A small pilot trial is conducted that primarily tests program functionality, efficacy, and user acceptability and satisfaction. This is followed by the main RCT, which compares 3 treatments: (1) delayed program access: usual diabetes care for 3 months postbaseline followed by access to the full OnTrack Diabetes program; (2) immediate program: full access to the self-guided program from baseline onward; and (3) immediate program plus therapist support via Functional Imagery Training (FIT). Measures are administered at baseline and at 3, 6, and 12 months postbaseline. Primary outcomes are diabetes self-care behaviors (physical activity participation, diet, medication adherence, and blood glucose monitoring), glycated hemoglobin A1c (HbA1c) level, and diabetes-specific distress. Secondary outcomes are depression, anxiety, self-efficacy and adherence, and quality of life. Exposure data in terms of program uptake, use, time on each page, and program completion, as well as implementation feasibility will be conducted. Results: This trial is currently underway with funding support from the Wesley Research Institute in Brisbane, Australia. Conclusions: This is the first known trial of an automated, self-guided, Web-based support program that uses a holistic approach in targeting both type 2 diabetes self-management and dysphoria. Findings will inform the feasibility of implementing such a program on an ongoing basis, including in rural and regional locations.

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Extending Lash and Urry's (1994) notion of new "imagined communities" through information and communication structures, I ask the question: Are emergent teachers happy when they interact in online learning environments? This question is timely in the context of the ubiquity of online media and its pervasiveness in teachers' everyday work and lives. The research is important nationally and internationally, because the current research is contradictory. On the one hand, feelings of isolation and frustration have been cited as common emotions experienced in many online environments (Su, Bonk, Magjuka, Liu, & Lee, 2005). Yet others report that online communities encourage a sense of belonging and support (Mills, 2011). Emotions are inherently social, are central to learning and online interaction (Shen, Wang, & Shen, 2009). The presentations reports the use of e-motion blogs to explore emotional states of emergent primary teachers in an online learning context as they transition into their first field experience in schools. The original research was conducted with a graduate class of 64 secondary science pre-service teachers in Science Education Curriculum Studies in a large Australian university, including males and females from a variety of cultural backgrounds, aged 17-55 years. Online activities involved the participants watching a series of streamed live lectures within a course of 8 weeks duration, providing a varied set of learning experiences, such as viewing live teaching demonstrations. Each week, participants provided feedback on learning by writing and posting an e-motion diary or web log about their emotional response. The blogs answered the question: What emotions you experience during this learning experience? The descriptive data set included 284 online posts, with students contributing multiple entries. The Language of Appraisal framework, following Martin and White (2005), was used to cluster the discrete emotions within six affect groups. The findings demonstrated that the pre-service teachers' emotional responses tended towards happiness and satisfaction within the typology of affect groups - un/happiness, in/security, and dis/satisfaction. Fewer participants reported that online learning mode triggered negative feelings of frustration, and when this occurred, it often pertained expectations of themselves in the forthcoming field experience in schools or as future teachers. The findings primarily contribute new understanding about emotional states in online communities, and recommendations are provided for supporting the happiness and satisfaction of emergent teachers as they interact in online communities. It demonstrates that online environments can play an important role in fulfilling teachers' need for social interaction and inclusion.

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This paper presents an online, unsupervised training algorithm enabling vision-based place recognition across a wide range of changing environmental conditions such as those caused by weather, seasons, and day-night cycles. The technique applies principal component analysis to distinguish between aspects of a location’s appearance that are condition-dependent and those that are condition-invariant. Removing the dimensions associated with environmental conditions produces condition-invariant images that can be used by appearance-based place recognition methods. This approach has a unique benefit – it requires training images from only one type of environmental condition, unlike existing data-driven methods that require training images with labelled frame correspondences from two or more environmental conditions. The method is applied to two benchmark variable condition datasets. Performance is equivalent or superior to the current state of the art despite the lesser training requirements, and is demonstrated to generalise to previously unseen locations.

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This research showed that online counselling has the potential to increase the help-seeking of secondary school students - especially those who suffer from high levels of psychological distress. An investigation of why school counsellors are currently reluctant to provide an online counselling service identified a number of barriers to implementing such a potentially vital service. Response to focus groups and surveys completed by students and school counsellors indicated that more distressed students prefer to use online counselling and they would use it for sensitive topics. School counsellors remain concerned about effectiveness, ethical, legal and privacy issues as well as potential misuse of the service. Recommendations for implementation are made.

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An automated melanoma diagnosis system, the so-called Skin Polar-probe, was developed to improve the chances of early detection of skin cancers and help save the lives of melanoma victims. The system will offer unique benefits to aid early detection of melanoma - the key to reducing deaths caused by this cancer.