934 resultados para Self-techniques
Resumo:
Whole-body computer control interfaces present new opportunities to engage children with games for learning. Stomp is a suite of educational games that use such a technology, allowing young children to use their whole body to interact with a digital environment projected on the floor. To maximise the effectiveness of this technology, tenets of self-determination theory (SDT) are applied to the design of Stomp experiences. By meeting user needs for competence, autonomy, and relatedness our aim is to increase children's engagement with the Stomp learning platform. Analysis of Stomp's design suggests that these tenets are met. Observations from a case study of Stomp being used by young children show that they were highly engaged and motivated by Stomp. This analysis demonstrates that continued application of SDT to Stomp will further enhance user engagement. It also is suggested that SDT, when applied more widely to other whole-body multi-user interfaces, could instil similar positive effects.
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Objectives: To develop and test preliminary reliability and validity of a Self-Efficacy Questionnaire for Chinese Family Caregivers (SEQCFC). Methods: A cross-sectional survey of 196 family caregivers (CGs) of people with dementia (CGs) was conducted to determine the factor structure of a SEQCFC of people with dementia. Following factor analyses, preliminary testing was performed, including internal consistency, 4-week test retest reliability, and construct and convergent validity. Results: Factor analyses with direct oblimin rotation were performed. Eight items were removed and five subscales(selfefficacy for gathering information about treatment, symptoms and health care; obtaining support; responding to behaviour disturbances; managing household, personal and medical care; and managing distress associated with caregiving) were identified. The Cronbach’s alpha coefficients for the whole scale and for each subscale were all over 0.80. The 4-week testretest reliabilities for the whole scale and for each subscale ranged from 0.64 to 0.85. The convergent validity was acceptable. Conclusions: Evidence for the preliminary testing of the SEQCFC was encouraging. A future follow-up study using confirmatory factor analysis with a new sample from different recruitment centres in Shanghai will be conducted. Future psychometric property testings of the questionnaire will be required for CGs from other regions of mainland China.
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This paper reports on a four year Australian Research Council funded Linkage Project titled Skilling Indigenous Queensland, conducted in regional areas of Queensland, Australia from 2009 to 2013. The project sought to investigate vocational education, training (VET) and teaching, Indigenous learners’ needs, employer cultural and expectations and community culture and expectations to identify best practice in numeracy teaching for Indigenous VET learners. Specifically it focused on ways to enhance the teaching and learning of courses and the associated mathematics in such courses to benefit learners and increase their future opportunities of employment. To date thirty-nine teachers/trainers/teacher aides and two hundred and thirty-one students consented to participate in the project. Nine VET courses were nominated to be the focus on the study. This paper focuses on questionnaire and interview responses from four trainers, two teacher aides and six students. In recent years a considerable amount of funding has been allocated to increasing Indigenous Peoples’ participation in education and employment. This increased funding is predicated on the assumption that it will make a difference and contribute to closing the education gap between Indigenous and non-Indigenous Australians (Council of Australia Governments, 2009). The central tenet is that access to education for Indigenous People will create substantial social and economic benefits for regional and remote Indigenous People. The project’s aim is to address some of the issues associated with the gap. To achieve the aims, the project adopted a mixed methods design aimed at benefitting research participants and included: participatory collaborative action research (Kemmis & McTaggart, 1988) and, community research (Smith, 1999). Participatory collaborative action research refers to a is a “collective, self-reflective enquiry undertaken by participants in social situations in order to improve the rationality and justice of their own social and educational practices” (Kemmis et al., 1988, p. 5). Community research is described as an approach that “conveys a much more intimate, human and self-defined space” (p. 127). Community research relies on and validates the community’s own definitions. As the project is informed by the social at a community level, it is described as “community action research or emancipatory research” (Smith, 1999, p. 127). It seeks to demonstrate benefit to the community, making positive differences in the lives of Indigenous People and communities. The data collection techniques included survey questionnaires, video recording of teaching and learning processes, teacher reflective video analysis of teaching, observations, semi-structured interviews and student numeracy testing. As a result of these processes, the findings indicate that VET course teachers work hard to adopt contextualising strategies to their teaching, however this process is not always straight forward because of the perceptions of how mathematics has been taught and learned historically. Further teachers, trainers and students have high expectations of one another with the view to successful outcomes from the courses.
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The objective of this paper was to explore experiences of ‘immediate-uptake’ (intermediate licensure at age 17-18 years, n = 928) and ‘delayed-uptake’ (intermediate licensure at age 19-20 years, n = 158) driver’s licence holders in the Australian state of Queensland. In Queensland, the graduated driver licence program applies to all novices irrespective of age. Drivers who obtained a Provisional 1 (intermediate) (P1) licence completed a survey exploring pre-Licence and Learner experiences, including the Behaviour of Young Novice Drivers Scale (BYNDS). Six months later, 351 drivers from this sample (n = 300 immediate-uptake) completed a survey exploring P1 driving. Delayed-uptake Learners reported significantly more difficulty gaining driving practice, which appeared to be associated with significantly greater engagement in unsupervised driving during the Learner period. Whilst a larger proportion of delayed-uptake novices, particularly males, reported the use of more active punishment avoidance strategies (avoiding Police, talking themselves out of a ticket) in the P1 phase, there was no significant difference in the BYNDS scores in the Learner and P1 phases according to licence-uptake category. Delayed-uptake novices report more difficulty meeting GDL requirements and place themselves at increased risk by driving unsupervised during the Learner licence phase. Additional efforts such as mentoring programs which can support the delayed-uptake Learner in meeting their GDL obligations merit further consideration to allow this novice group to gain the full benefits of the GDL program and to reduce their risk of harm in the short-term.
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Background: There are strong logical reasons why energy expended in metabolism should influence the energy acquired in food-intake behavior. However, the relation has never been established, and it is not known why certain people experience hunger in the presence of large amounts of body energy. Objective: We investigated the effect of the resting metabolic rate (RMR) on objective measures of whole-day food intake and hunger. Design: We carried out a 12-wk intervention that involved 41 overweight and obese men and women [mean ± SD age: 43.1 ± 7.5 y; BMI (in kg/m2): 30.7 ± 3.9] who were tested under conditions of physical activity (sedentary or active) and dietary energy density (17 or 10 kJ/g). RMR, daily energy intake, meal size, and hunger were assessed within the same day and across each condition. Results: We obtained evidence that RMR is correlated with meal size and daily energy intake in overweight and obese individuals. Participants with high RMRs showed increased levels of hunger across the day (P < 0.0001) and greater food intake (P < 0.00001) than did individuals with lower RMRs. These effects were independent of sex and food energy density. The change in RMR was also related to energy intake (P < 0.0001). Conclusions: We propose that RMR (largely determined by fat-free mass) may be a marker of energy intake and could represent a physiologic signal for hunger. These results may have implications for additional research possibilities in appetite, energy homeostasis, and obesity. This trial was registered under international standard identification for controlled trials as ISRCTN47291569.
Resumo:
Objective: To examine the association between individual- and neighborhood-level disadvantage and self-reported arthritis. Methods: We used data from a population-based cross-sectional study conducted in 2007 among 10,757 men and women ages 40–65 years, selected from 200 neighborhoods in Brisbane, Queensland, Australia using a stratified 2-stage cluster design. Data were collected using a mail survey (68.5% response). Neighborhood disadvantage was measured using a census-based composite index, and individual disadvantage was measured using self-reported education, household income, and occupation. Arthritis was indicated by self-report. Data were analyzed using multilevel modeling. Results: The overall rate of self-reported arthritis was 23% (95% confidence interval [95% CI] 22–24). After adjustment for sociodemographic factors, arthritis prevalence was greatest for women (odds ratio [OR] 1.5, 95% CI 1.4–1.7) and in those ages 60–65 years (OR 4.4, 95% CI 3.7–5.2), those with a diploma/associate diploma (OR 1.3, 95% CI 1.1–1.6), those who were permanently unable to work (OR 4.0, 95% CI 3.1–5.3), and those with a household income <$25,999 (OR 2.1, 95% CI 1.7–2.6). Independent of individual-level factors, residents of the most disadvantaged neighborhoods were 42% (OR 1.4, 95% CI 1.2–1.7) more likely than those in the least disadvantaged neighborhoods to self-report arthritis. Cross-level interactions between neighborhood disadvantage and education, occupation, and household income were not significant. Conclusion: Arthritis prevalence is greater in more socially disadvantaged neighborhoods. These are the first multilevel data to examine the relationship between individual- and neighborhood-level disadvantage upon arthritis and have important implications for policy, health promotion, and other intervention strategies designed to reduce the rates of arthritis, indicating that intervention efforts may need to focus on both people and places.
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CTAC2012 was the 16th biennial Computational Techniques and Applications Conference, and took place at Queensland University of Technology from 23 - 26 September, 2012. The ANZIAM Special Interest Group in Computational Techniques and Applications is responsible for the CTAC meetings, the first of which was held in 1981.
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Modern mobile computing devices are versatile, but bring the burden of constant settings adjustment according to the current conditions of the environment. While until today, this task has to be accomplished by the human user, the variety of sensors usually deployed in such a handset provides enough data for autonomous self-configuration by a learning, adaptive system. However, this data is not fully available at certain points in time, or can contain false values. Handling potentially incomplete sensor data to detect context changes without a semantic layer represents a scientific challenge which we address with our approach. A novel machine learning technique is presented - the Missing-Values-SOM - which solves this problem by predicting setting adjustments based on context information. Our method is centered around a self-organizing map, extending it to provide a means of handling missing values. We demonstrate the performance of our approach on mobile context snapshots, as well as on classical machine learning datasets.
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A routine activity for a sports dietitian is to estimate energy and nutrient intake from an athlete's self-reported food intake. Decisions made by the dietitian when coding a food record are a source of variability in the data. The aim of the present study was to determine the variability in estimation of the daily energy and key nutrient intakes of elite athletes, when experienced coders analyzed the same food record using the same database and software package. Seven-day food records from a dietary survey of athletes in the 1996 Australian Olympic team were randomly selected to provide 13 sets of records, each set representing the self-reported food intake of an endurance, team, weight restricted, and sprint/power athlete. Each set was coded by 3-5 members of Sports Dietitians Australia, making a total of 52 athletes, 53 dietitians, and 1456 athlete-days of data. We estimated within- and between- athlete and dietitian variances for each dietary nutrient using mixed modeling, and we combined the variances to express variability as a coefficient of variation (typical variation as a percent of the mean). Variability in the mean of 7-day estimates of a nutrient was 2- to 3-fold less than that of a single day. The variability contributed by the coder was less than the true athlete variability for a 1-day record but was of similar magnitude for a 7-day record. The most variable nutrients (e.g., vitamin C, vitamin A, cholesterol) had approximately 3-fold more variability than least variable nutrients (e.g., energy, carbohydrate, magnesium). These athlete and coder variabilities need to be taken into account in dietary assessment of athletes for counseling and research.
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We consider Cooperative Intrusion Detection System (CIDS) which is a distributed AIS-based (Artificial Immune System) IDS where nodes collaborate over a peer-to-peer overlay network. The AIS uses the negative selection algorithm for the selection of detectors (e.g., vectors of features such as CPU utilization, memory usage and network activity). For better detection performance, selection of all possible detectors for a node is desirable but it may not be feasible due to storage and computational overheads. Limiting the number of detectors on the other hand comes with the danger of missing attacks. We present a scheme for the controlled and decentralized division of detector sets where each IDS is assigned to a region of the feature space. We investigate the trade-off between scalability and robustness of detector sets. We address the problem of self-organization in CIDS so that each node generates a distinct set of the detectors to maximize the coverage of the feature space while pairs of nodes exchange their detector sets to provide a controlled level of redundancy. Our contribution is twofold. First, we use Symmetric Balanced Incomplete Block Design, Generalized Quadrangles and Ramanujan Expander Graph based deterministic techniques from combinatorial design theory and graph theory to decide how many and which detectors are exchanged between which pair of IDS nodes. Second, we use a classical epidemic model (SIR model) to show how properties from deterministic techniques can help us to reduce the attack spread rate.
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An optical system which performs the multiplication of binary numbers is described and proof-of-principle experiments are performed. The simultaneous generation of all partial products, optical regrouping of bit products, and optical carry look-ahead addition are novel features of the proposed scheme which takes advantage of the parallel operations capability of optical computers. The proposed processor uses liquid crystal light valves (LCLVs). By space-sharing the LCLVs one such system could function as an array of multipliers. Together with the optical carry look-ahead adders described, this would constitute an optical matrix-vector multiplier.
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Introduction: Undergraduate students studying the Bachelor of Radiation Therapy at Queensland University of Technology (QUT) attend clinical placements in a number of department sites across Queensland. To ensure that the curriculum prepares students for the most common treatments and current techniques in use in these departments, a curriculum matching exercise was performed. Methods: A cross-sectional census was performed on a pre-determined “Snapshot” date in 2012. This was undertaken by the clinical education staff in each department who used a standardized proforma to count the number of patients as well as prescription, equipment, and technique data for a list of tumour site categories. This information was combined into aggregate anonymized data. Results: All 12 Queensland radiation therapy clinical sites participated in the Snapshot data collection exercise to produce a comprehensive overview of clinical practice on the chosen day. A total of 59 different tumour sites were treated on the chosen day and as expected the most common treatment sites were prostate and breast, comprising 46% of patients treated. Data analysis also indicated that intensity-modulated radiotherapy (IMRT) use is relatively high with 19.6% of patients receiving IMRT treatment on the chosen day. Both IMRT and image-guided radiotherapy (IGRT) indications matched recommendations from the evidence. Conclusion: The Snapshot method proved to be a feasible and efficient method of gathering useful
Resumo:
How can marketers stop speeding motorists and binge drinking? Two experiments show that the beliefs consumers have about the degree to which they define themselves in terms of their close relationships (i.e., relational-interdependent self-construal (RISC)) offer useful insights into the effectiveness of communications for two key social marketing issues—road safety (Study 1, New Zealand sample) and alcohol consumption (Study 2, English sample). Further, self-referencing is a mechanism for these effects. Specifically, people who define themselves in terms of their close relationships (high-RISCs) respond most favorably to advertisements featuring a dyadic relationship (two people), and this favorable response is mediated by self-referencing. In contrast, people who do not include close relationships in their sense of self (low-RISCs) respond most favorably to self-reference advertisements featuring solitary models.
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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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The study adopts a multi-dimensional construct of self-esteem to examine the relationship between self-perception and psychological adjustment in order to identify specific dimensions that discriminate between disturbed and non-disturbed groups. The disturbed group (n = 33) is derived from a clinical sample and are matched with a non-disturbed group (n = 33) of adolescents. Results indicate that dimensional self-concept scores are significantly lower for clinical subjects while there are no significant differences between groups on the mathematics, honesty, and physical ability dimensions. These findings provide a more fine grained understanding of the relationship between self-esteem and psychological adjustment and emphasize the need to examine self-esteem in terms of its particular dimensions.