964 resultados para self-deployment algorithms
Resumo:
Continuities and changes in parenting sense of competence were examined for mothers of children with Down syndrome from early childhood to adolescence. The sample comprised 25 mothers whose child with Down syndrome was aged 4-6 years in the first phase of the study, and 11-15 years at the second time point. Maternal satisfaction with parenting increased over time, but there were no changes in parenting self-efficacy. Scores on these measures were no different from those reported in a normative sample of mothers of typically developing children, suggesting that the challenges of parenting a child with Down syndrome do not impact significantly on parenting sense of competence during the early childhood and adolescent periods. There were some significant relationships of maternal sense of competence with child characteristics and self-reported parenting style, mostly in the expected direction.
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This paper describes part of an action research study that was designed to explore the outcomes of an ongoing program in which the participants, a group of domestic and international pre-service teachers and lecturers, worked together in reflective writing workshops. While the primary long-term goal of the program was to develop the intercultural competence and understanding of all of the participants through social activities, the development of social relationships was initiated and supported by involving the participants in weekly writing workshops that focused on shared salient skills of critical reflective thinking and writing. The focus of this paper is upon the outcomes for the international students, a cohort of second year pre-service teachers from Malaysia. Findings indicated that the program was successful in developing the Malaysian pre-service teachers’ self-confidence in perceiving themselves as writers and future teachers of writing, in shifting their focus from writing product to writing process and content, and in increasing the depth of their critical reflective thinking and writing
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This paper presents an approach for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera’s optical center and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. Previous methods for auto-calibration of cameras based on pure rotations fail to work in these two degenerate cases. In addition, our approach includes a modified RANdom SAmple Consensus (RANSAC) algorithm, as well as improved integration of the radial distortion coefficient in the computation of inter-image homographies. We show that these modifications are able to increase the overall efficiency, reliability and accuracy of the homography computation and calibration procedure using both synthetic and real image sequences
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The study presents a multi-layer genetic algorithm (GA) approach using correlation-based methods to facilitate damage determination for through-truss bridge structures. To begin, the structure’s damage-suspicious elements are divided into several groups. In the first GA layer, the damage is initially optimised for all groups using correlation objective function. In the second layer, the groups are combined to larger groups and the optimisation starts over at the normalised point of the first layer result. Then the identification process repeats until reaching the final layer where one group includes all structural elements and only minor optimisations are required to fine tune the final result. Several damage scenarios on a complicated through-truss bridge example are nominated to address the proposed approach’s effectiveness. Structural modal strain energy has been employed as the variable vector in the correlation function for damage determination. Simulations and comparison with the traditional single-layer optimisation shows that the proposed approach is efficient and feasible for complicated truss bridge structures when the measurement noise is taken into account.
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Optimising the container transfer schedule at the multimodal terminals is known to be NP-hard, which implies that the best solution becomes computationally infeasible as problem sizes increase. Genetic Algorithm (GA) techniques are used to reduce container handling/transfer times and ships' time at the port by speeding up handling operations. The GA is chosen due to the relatively good results that have been reported even with the simplest GA implementations to obtain near-optimal solutions in reasonable time. Also discussed, is the application of the model to assess the consequences of increased scheduled throughput time as well as different strategies such as the alternative plant layouts, storage policies and number of yard machines. A real data set used for the solution and subsequent sensitivity analysis is applied to the alternative plant layouts, storage policies and number of yard machines.
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Background: Sleepiness is a direct contributor to a substantial proportion of fatal and severe road cashes. A number of technological solutions designed to detect sleepiness have been developed, but self-awareness of increasing sleepiness remains a critical component in on-road strategies for mitigating this risk. In order to take appropriate action when sleepy, drivers’ perceptions of their level of sleepiness must be accurate. Aims: This study aimed to assess capacity to accurately identify sleepiness and self-regulate driving cessation during a validated driving simulator task. Participants: Participants comprised 26 young adult drivers (20-28 years). The drivers had open licenses but no other exclusion criteria where used. Methods: Participants woke at 5am, and took part in a laboratory-based hazard perception driving simulation, either at mid-morning or mid-afternoon. Established physiological measures (including EEG) and subjective measures (sleepiness ratings) previously found sensitive to changes in sleepiness levels were utilised. Participants were instructed to ‘drive’ until they believed that sleepiness had impaired their ability to drive safely. They were then offered a nap opportunity. Results: The mean duration of the drive before cessation was 39 minutes (±18 minutes). Almost all (23/26) of the participants then achieved sleep during the nap opportunity. These data suggest that the participants’ perceptions of sleepiness were specific. However, EEG data from a number of participants suggested very high levels of sleepiness prior to driving cessation, suggesting poor sensitivity. Conclusions: Participants reported high levels of sleepiness while driving after very moderate sleep restriction. They were able to identify increasing sleepiness during the test period, could decide to cease driving and in most cases were sufficiently sleepy to achieve sleep during the daytime session. However, the levels of sleepiness achieved prior to driving cessation suggest poor accuracy in self-perception and regulation. This presents practical issues for the implementation of fatigue and sleep-related strategies to improve driver safety.
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Background to the Problem: Improving nurses' self-efficacy and job satisfaction may improve the quality of nursing care to patients. Moreover, to work effectively and consistently with professional nursing standards, nurses have to believe they are able to make decisions about their practice. In order to identify what strategies and professional development programmes should be developed and implemented for registered nurses in the Australian context, a comprehensive profile of registered nurses and factors that affect nursing care in Australia needs to be available. However, at present, there is limited information available on a) the perceived caring efficacy and job satisfaction of registered nurses in Australia, and b) the relationships between the demographic variables general self-efficacy, work locus of control, coping styles, the professional nursing practice environment and caring efficacy and job satisfaction of registered nurses in Australia. This is the first study to 1) investigate relationships between caring efficacy and job satisfaction with factors such as general self-efficacy, locus of control and coping, 2) the nursing practice environment in the Australian context and 3) conceptualise a model of caring efficacy and job satisfaction in the Australian context. Research Design and Methods: This study used a two-phase cross-sectional survey design. A pilot study was conducted in order to determine the validity and reliability of the survey instruments and to assess the effectiveness of the participant recruitment process. The second study of the research involved investigating the relationships between the socio-demographic, dependent and independent variables. Socio-demographic variables included age, gender, level of education, years of experience, years in current job, employment status, geographical location, specialty area, health sector, state and marital status. Other independent variables in this study included general self-efficacy, work locus of control, coping styles and the professional nursing practice environment. The dependent variables were job satisfaction and caring efficacy. Results: A confirmatory factor analysis of the Brisbane Practice Environment Measure (B-PEM) was conducted. A five-factor structure of the B-PEM was confirmed. Relationships between socio-demographic variables, caring efficacy and job satisfaction, were identified at the bivariate and multivariable levels. Further, examination using structural equation modelling revealed general self-efficacy, work locus of control, coping style and the professional nursing practice environment contributed to caring efficacy and job satisfaction of registered nurses in Australia. Conclusion: This research contributes to the literature on how socio-demographic, personal and environmental variables (work locus of control, general self-efficacy and the nursing practice environment) influence caring efficacy and job satisfaction in registered nurses in Australia. Caring efficacy and job satisfaction may be improved if general self-efficacy is high in those that have an internal work locus of control. The study has also shown that practice environments that provide the necessary resources improve job satisfaction in nurses. The results have identified that the development and implementation of strategies for professional development and orientation programmes that enhance self-efficacy and work locus of control may contribute to better quality nursing practice and job satisfaction. This may further assist registered nurses towards focusing on improving their practice abilities. These strategies along with practice environments that provide the necessary resources for nurses to practice effectively may lead to better job satisfaction. This information is important for nursing leaders, healthcare organisations and policymakers, as the development and implementation of these strategies may lead to better recruitment and retention of nurses. The study results will contribute to the national and international literature on self-efficacy, job satisfaction and nursing practice.
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Facial expression is an important channel of human social communication. Facial expression recognition (FER) aims to perceive and understand emotional states of humans based on information in the face. Building robust and high performance FER systems that can work in real-world video is still a challenging task, due to the various unpredictable facial variations and complicated exterior environmental conditions, as well as the difficulty of choosing a suitable type of feature descriptor for extracting discriminative facial information. Facial variations caused by factors such as pose, age, gender, race and occlusion, can exert profound influence on the robustness, while a suitable feature descriptor largely determines the performance. Most present attention on FER has been paid to addressing variations in pose and illumination. No approach has been reported on handling face localization errors and relatively few on overcoming facial occlusions, although the significant impact of these two variations on the performance has been proved and highlighted in many previous studies. Many texture and geometric features have been previously proposed for FER. However, few comparison studies have been conducted to explore the performance differences between different features and examine the performance improvement arisen from fusion of texture and geometry, especially on data with spontaneous emotions. The majority of existing approaches are evaluated on databases with posed or induced facial expressions collected in laboratory environments, whereas little attention has been paid on recognizing naturalistic facial expressions on real-world data. This thesis investigates techniques for building robust and high performance FER systems based on a number of established feature sets. It comprises of contributions towards three main objectives: (1) Robustness to face localization errors and facial occlusions. An approach is proposed to handle face localization errors and facial occlusions using Gabor based templates. Template extraction algorithms are designed to collect a pool of local template features and template matching is then performed to covert these templates into distances, which are robust to localization errors and occlusions. (2) Improvement of performance through feature comparison, selection and fusion. A comparative framework is presented to compare the performance between different features and different feature selection algorithms, and examine the performance improvement arising from fusion of texture and geometry. The framework is evaluated for both discrete and dimensional expression recognition on spontaneous data. (3) Evaluation of performance in the context of real-world applications. A system is selected and applied into discriminating posed versus spontaneous expressions and recognizing naturalistic facial expressions. A database is collected from real-world recordings and is used to explore feature differences between standard database images and real-world images, as well as between real-world images and real-world video frames. The performance evaluations are based on the JAFFE, CK, Feedtum, NVIE, Semaine and self-collected QUT databases. The results demonstrate high robustness of the proposed approach to the simulated localization errors and occlusions. Texture and geometry have different contributions to the performance of discrete and dimensional expression recognition, as well as posed versus spontaneous emotion discrimination. These investigations provide useful insights into enhancing robustness and achieving high performance of FER systems, and putting them into real-world applications.
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The purpose of this study was to develop a Self-Efficacy Questionnaire for Chinese Family Caregivers. Semi-structured interviews with 10 family caregivers of people with dementia were conducted to explore how Chinese caregivers manage caregiving and what difficulties they face. The findings of the study assisted in the development of the instrument. Five categories of caregiver behaviours were identified from the qualitative data: 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. The challenges of caregiving were also identified, including deterioration of care recipients, particularly their behaviour disturbances, a shortage of supportive resources, stigmatization of dementia among the general population, as well as increased distress and decreased social activities due to increased care demand. The findings were used to develop the Self-Efficacy Questionnaire for Chinese Family Caregivers, and 35 items comprising five subscales (representing the above five categories of caregiver behaviour) were generated.
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The increasingly widespread use of large-scale 3D virtual environments has translated into an increasing effort required from designers, developers and testers. While considerable research has been conducted into assisting the design of virtual world content and mechanics, to date, only limited contributions have been made regarding the automatic testing of the underpinning graphics software and hardware. In the work presented in this paper, two novel neural network-based approaches are presented to predict the correct visualization of 3D content. Multilayer perceptrons and self-organizing maps are trained to learn the normal geometric and color appearance of objects from validated frames and then used to detect novel or anomalous renderings in new images. Our approach is general, for the appearance of the object is learned rather than explicitly represented. Experiments were conducted on a game engine to determine the applicability and effectiveness of our algorithms. The results show that the neural network technology can be effectively used to address the problem of automatic and reliable visual testing of 3D virtual environments.
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Parents are at risk for inactivity; however, research into understanding parental physical activity (PA) is scarce. We integrated self-determined motivation, planning, and the theory of planned behavior (TPB) to better understand parental PA. Parents (252 mothers, 206 fathers) completed a main questionnaire assessing measures underpinning these constructs and a 1-week follow-up of PA behavior to examine whether self-determined motivation indirectly influenced intention via the TPB variables (i.e., attitude, subjective norm, and perceived behavioral control) and intention indirectly influenced behavior via planning. We found self-determined motivation on intention was fully mediated by the TPB variables and intention on behavior was partially mediated by the planning variables. In addition, slight differences in the model’s paths between the sexes were revealed. The results illustrate the range of important determinants of parental PA and provide support for the integrated model in explaining PA decision making as well as the importance of examining sex differences.
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Despite the significant health benefits attributed to breastfeeding, rates in countries, such as Australia, continue to remain static or to decline. Typically, the tangible support offered for women to support breastfeeding behaviours takes the form of face-to-face advice from health professionals, peer counselling via not-for-profit organizations such as the ABA, and provision of information through websites, pamphlets, and books. Prior research indicates that face-to-face support is more effective than telephone contact (Britton, McCormic, Renfrew, Wade, & King, 2009). Given the increasing costs associated with the provision of personalized face-to-face professional support and the need for some women to maximize privacy, discretion, and judgment-free consultations, there is a gap that could be filled by the use of m-technologies such as text messaging and other social media. The research team developed MumBubConnect; a two-way SMS system which combined the personalized aspects of face-to-face contact but maintained levels of privacy. The use of SMS was immediate, portable, and overcame many of the barriers associated with embarrassment. An Page 205 of 312 online survey of 130 breastfeeding mothers indicated that MumBubConnect facilitated the seeking of social support using m-technology, increased self-efficacy and maintained the desire behaviour.
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Recent studies have implicated the hypocretin/orexinergic system in reward-seeking behavior. Almorexant, a dual orexin/hypocretin R1 and R2 receptor antagonist, has proven effective in preclinical studies in promoting sleep in animal models and was in Phase III clinical trials for sleep disorders. The present study combines behavioral assays with in vitro biochemical and electrophysiological techniques to elucidate the role of almorexant in ethanol and sucrose intake. Using an operant self-administration paradigm, we demonstrate that systemic administration of almorexant decreased operant selfadministration of both 20% ethanol and 5% sucrose. We further demonstrate that intraventral tegmental area (VTA) infusions, but not intra substantia nigra infusions, of almorexant reduced ethanol self-administration. Extracellular recordings performed in VTA neurons revealed that orexin-A increased firing and this enhancement of firing was blocked by almorexant. The results demonstrate that orexin/hypocretin receptors in distinct brain regions regulate ethanol and sucrose mediated behaviors.