125 resultados para task domains,


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Purpose: Students often read for long periods and prolonged reading practice may be important for developing reading skills. For students with low vision, reading at a close working distance imposes high demands on their near visual functions, which might make it difficult to sustain prolonged reading. The aim of this study was to investigate the performance of a prolonged reading task by students with low vision. Method: Forty students with low vision, aged from eight to 20 years and without any intellectual, reading or learning disability, were recruited through the Paediatric Low Vision Clinic, Buranda, Queensland. Following a preliminary vision examination, reading performance measures—critical print size (CPS), maximum oral reading rates (MORR), near text visual acuity— were recorded using the Bailey-Lovie text reading charts before and after a 30-minute prolonged reading task. Results: The mean age of the participants was 13.03 ± 3 years. The distance and near visual acuities ranged between -0.1 to 1.24 logMAR and 0.0 to 1.60 logMAR, respectively. The mean working distance of the participants was 11.2 ± 5.8 cm. Most of the participants (65 per cent) in this study were able to complete the prolonged reading task. Overall, there was no significant change in CPS, MORR and near text visual acuity following the prolonged task (p > 0.05). MORR was significantly correlated to age and near text visual acuity (p < 0.05). Conclusions: In this study, students with low vision were able to maintain their reading performance over a 30-minute prolonged reading task. Overall, there was no significant increase or decrease in reading performance following a prolonged reading task performed at their habitual close working distances but there were wide individual variations within the group.

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Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

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The androgen receptor (AR) is a ligand-activated transcription factor of the nuclear receptor superfamily that plays a critical role in male physiology and pathology. Activated by binding of the native androgens testosterone and 5-dihydrotestosterone, the AR regulates transcription of genes involved in the development and maintenance of male phenotype and male reproductive function as well as other tissues such as bone and muscle. Deregulation of AR signaling can cause a diverse range of clinical conditions, including the X-linked androgen insensitivity syndrome, a form of motor neuron disease known as Kennedy’s disease, and male infertility. In addition, there is now compelling evidence that the AR is involved in all stages of prostate tumorigenesis including initiation, progression, and treatment resistance. To better understand the role of AR signaling in the pathogenesis of these conditions, it is important to have a comprehensive understanding of the key determinants of AR structure and function. Binding of androgens to the AR induces receptor dimerization, facilitating DNA binding and the recruitment of cofactors and transcriptional machinery to regulate expression of target genes. Various models of dimerization have been described for the AR, the most well characterized interaction being DNA-binding domain- mediated dimerization, which is essential for the AR to bind DNA and regulate transcription. Additional AR interactions with potential to contribute to receptor dimerization include the intermolecular interaction between the AR amino terminal domain and ligand-binding domain known as the N-terminal/C-terminal interaction, and ligand-binding domain dimerization. In this review, we discuss each form of dimerization utilized by the AR to achieve transcriptional competence and highlight that dimerization through multiple domains is necessary for optimal AR signaling.

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BACKGROUND: Support and education for parents faced with managing a child with atopic dermatitis is crucial to the success of current treatments. Interventions aiming to improve parent management of this condition are promising. Unfortunately, evaluation is hampered by lack of precise research tools to measure change. OBJECTIVES: To develop a suite of valid and reliable research instruments to appraise parents' self-efficacy for performing atopic dermatitis management tasks; outcome expectations of performing management tasks; and self-reported task performance in a community sample of parents of children with atopic dermatitis. METHODS: The Parents' Eczema Management Scale (PEMS) and the Parents' Outcome Expectations of Eczema Management Scale (POEEMS) were developed from an existing self-efficacy scale, the Parental Self-Efficacy with Eczema Care Index (PASECI). Each scale was presented in a single self-administered questionnaire, to measure self-efficacy, outcome expectations, and self-reported task performance related to managing child atopic dermatitis. Each was tested with a community sample of parents of children with atopic dermatitis, and psychometric evaluation of the scales' reliability and validity was conducted. SETTING AND PARTICIPANTS: A community-based convenience sample of 120 parents of children with atopic dermatitis completed the self-administered questionnaire. Participants were recruited through schools across Australia. RESULTS: Satisfactory internal consistency and test-retest reliability was demonstrated for all three scales. Construct validity was satisfactory, with positive relationships between self-efficacy for managing atopic dermatitis and general perceived self-efficacy; self-efficacy for managing atopic dermatitis and self-reported task performance; and self-efficacy for managing atopic dermatitis and outcome expectations. Factor analyses revealed two-factor structures for PEMS and PASECI alike, with both scales containing factors related to performing routine management tasks, and managing the child's symptoms and behaviour. Factor analysis was also applied to POEEMS resulting in a three-factor structure. Factors relating to independent management of atopic dermatitis by the parent, involving healthcare professionals in management, and involving the child in the management of atopic dermatitis were found. Parents' self-efficacy and outcome expectations had a significant influence on self-reported task performance. CONCLUSIONS: Findings suggest that PEMS and POEEMS are valid and reliable instruments worthy of further psychometric evaluation. Likewise, validity and reliability of PASECI was confirmed.

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Vigilance declines when exposed to highly predictable and uneventful tasks. Monotonous tasks provide little cognitive and motor stimulation and contribute to human errors. This paper aims to model and detect vigilance decline in real time through participant’s reaction times during a monotonous task. A lab-based experiment adapting the Sustained Attention to Response Task (SART) is conducted to quantify the effect of monotony on overall performance. Then relevant parameters are used to build a model detecting hypovigilance throughout the experiment. The accuracy of different mathematical models are compared to detect in real-time – minute by minute - the lapses in vigilance during the task. We show that monotonous tasks can lead to an average decline in performance of 45%. Furthermore, vigilance modelling enables to detect vigilance decline through reaction times with an accuracy of 72% and a 29% false alarm rate. Bayesian models are identified as a better model to detect lapses in vigilance as compared to Neural Networks and Generalised Linear Mixed Models. This modelling could be used as a framework to detect vigilance decline of any human performing monotonous tasks.

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The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create hypovigilance and impair performance towards critical events. Identifying such impairment in monotonous conditions has been a major subject of research, but no research to date has attempted to predict it in real-time. This pilot study aims to show that performance decrements due to monotonous tasks can be predicted through mathematical modelling taking into account sensation seeking levels. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants‟ performance. The framework for prediction developed on this task could be extended to a monotonous driving task. A Hidden Markov Model (HMM) is proposed to predict participants‟ lapses in alertness. Driver‟s vigilance evolution is modelled as a hidden state and is correlated to a surrogate measure: the participant‟s reactions time. This experiment shows that the monotony of the task can lead to an important decline in performance in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.

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Engineering graduates of today are required to adapt to a rapidly changing work environment. In particular, they are expected to demonstrate enhanced capabilities in both mono-disciplinary and multi-disciplinary teamwork environments. Engineering education needs, as a result, to further focus on developing group work capabilities amongst engineering graduates. Over the last two years, the authors trialed various group work strategies across two engineering disciplines. In particular, the effect of group formation on students' performance, task management, and social loafing was analyzed. A recently developed online teamwork management tool, Teamworker, was used to collect students' experience of the group work. Analysis showed that students who were allowed to freely allocate to any group were less likely to report loafing from other team members, than students who were pre-allocated to a group. It also showed that performance was more affected by the presence or absence of a leader in pre-allocated rather than free-allocated groups.

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This paper analyzes effects of different practice task constraints on heart rate (HR) variability during 4v4 smallsided football games. Participants were sixteen football players divided into two age groups (U13, Mean age: 12.4±0.5 yrs; U15: 14.6±0.5). The task consisted of a 4v4 sub-phase without goalkeepers, on a 25x15 m field, of 15 minutes duration with an active recovery period of 6 minutes between each condition. We recorded players’ heart rates using heart rate monitors (Polar Team System, Polar Electro, Kempele, Finland) as scoring mode was manipulated (line goal: scoring by dribbling past an extended line; double goal: scoring in either of two lateral goals; and central goal: scoring only in one goal). Subsequently, %HR reserve was calculated with the Karvonen formula. We performed a time-series analysis of HR for each individual in each condition. Mean data for intra-participant variability showed that autocorrelation function was associated with more short-range dependence processes in the “line goal” condition, compared to other conditions, demonstrating that the “line goal” constraint induced more randomness in HR response. Relative to inter-individual variability, line goal constraints demonstrated lower %CV and %RMSD (U13: 9% and 19%; U15: 10% and 19%) compared with double goal (U13: 12% and 21%; U15: 12% and 21%) and central goal (U13: 14% and 24%; U15: 13% and 24%) task constraints, respectively. Results suggested that line goal constraints imposed more randomness on cardiovascular stimulation of each individual and lower inter-individual variability than double goal and central goal constraints.

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Gaze and movement behaviors of association football goalkeepers were compared under two video simulation conditions (i.e., verbal and joystick movement responses) and three in situ conditions (i.e., verbal, simplified body movement, and interceptive response). The results showed that the goalkeepers spent more time fixating on information from the penalty kick taker’s movements than ball location for all perceptual judgment conditions involving limited movement (i.e., verbal responses, joystick movement, and simplified body movement). In contrast, an equivalent amount of time was spent fixating on the penalty taker’s relative motions and the ball location for the in situ interception condition, which required the goalkeepers to attempt to make penalty saves. The data suggest that gaze and movement behaviors function differently, depending on the experimental task constraints selected for empirical investigations. These findings highlight the need for research on perceptual— motor behaviors to be conducted in representative experimental conditions to allow appropriate generalization of conclusions to performance environments.

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This paper presents a modified approach to evaluate access control policy similarity and dissimilarity based on the proposal by Lin et al. (2007). Lin et al.'s policy similarity approach is intended as a filter stage which identifies similar XACML policies that can be analysed further using more computationally demanding techniques based on model checking or logical reasoning. This paper improves the approach of computing similarity of Lin et al. and also proposes a mechanism to calculate a dissimilarity score by identifying related policies that are likely to produce different access decisions. Departing from the original algorithm, the modifications take into account the policy obligation, rule or policy combining algorithm and the operators between attribute name and value. The algorithms are useful in activities involving parties from multiple security domains such as secured collaboration or secured task distribution. The algorithms allow various comparison options for evaluating policies while retaining control over the restriction level via a number of thresholds and weight factors.

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In this paper we extend the concept of speaker annotation within a single-recording, or speaker diarization, to a collection wide approach we call speaker attribution. Accordingly, speaker attribution is the task of clustering expectantly homogenous intersession clusters obtained using diarization according to common cross-recording identities. The result of attribution is a collection of spoken audio across multiple recordings attributed to speaker identities. In this paper, an attribution system is proposed using mean-only MAP adaptation of a combined-gender UBM to model clusters from a perfect diarization system, as well as a JFA-based system with session variability compensation. The normalized cross-likelihood ratio is calculated for each pair of clusters to construct an attribution matrix and the complete linkage algorithm is employed to conduct clustering of the inter-session clusters. A matched cluster purity and coverage of 87.1% was obtained on the NIST 2008 SRE corpus.

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In team sports such as rugby union, a myriad of decisions and actions occur within the boundaries that compose the performance perceptual- motor workspace. The way that these performance boundaries constrain decision making and action has recently interested researchers and has involved developing an understanding of the concept of constraints. Considering team sports as complex dynamical systems, signifies that they are composed of multiple, independent agents (i.e. individual players) whose interactions are highly integrated. This level of complexity is characterized by the multiple ways that players in a rugby field can interact. It affords the emergence of rich patterns of behaviour, such as rucks, mauls, and collective tactical actions that emerge due to players’ adjustments to dynamically varying competition environments. During performance, the decisions and actions of each player are constrained by multiple causes (e.g. technical and tactical skills, emotional states, plans, thoughts, etc.) that generate multiple effects (e.g. to run or pass, to move forward to tackle or maintain position and drive the opponent to the line), a prime feature in a complex systems approach to team games performance (Bar- Yam, 2004). To establish a bridge between the complexity sciences and learning design in team sports like rugby union, the aim of practice sessions is to prepare players to pick up and explore the information available in the multiple constraints (i.e. the causes) that influence performance. Therefore, learning design in training sessions should be soundly based on the interactions amongst players (i.e.teammates and opponents) that will occur in rugby matches. To improve individual and collective decision making in rugby union, Passos and colleagues proposed in previous work a performer- environment interaction- based approach rather than a traditional performer- based approach (Passos, Araújo, Davids & Shuttleworth, 2008).

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Background: Caring for family members with dementia can be a long-term, burdensome task resulting in physical and emotional distress and impairment. Research has demonstrated significantly lower levels of selfefficacy among family caregivers of people with dementia (CGs) than caregivers of relatives with non-dementia diseases. Intervention studies have also suggested that the mental and physical health of dementia CGs could be improved through the enhancement of their self-efficacy. However, studies are limited in terms of the influences of caregiver self-efficacy on caregiver behaviour, subjective burden and health-related quality of life. Of particular note is that there are no studies on the applicability of caregiver self-efficacy in the social context of China. Objective: The purpose of this thesis was to undertake theoretical exploration using Bandura’s (1997) self-efficacy theory to 1) revise the Revised Caregiving Self-Efficacy Scale (C-RCSES) (Steffen, McKibbin, Zeiss, Gallagher-Thompson, & Bandura, 2002), and 2) explore determinants of caregiver self-efficacy and the role of caregiver self-efficacy and other conceptual constructs (including CGs’ socio-demographic characteristics, CRs’ impairment and CGs’ social support) in explaining and predicting caregiver behaviour, subjective burden and health-related quality of life among CGs in China. Methodology: Two studies were undertaken: a qualitative elicitation study with 10 CGs; and a cross-sectional survey with 196 CGs. In the first study, semi-structured interviews were conducted to explore caregiver behaviours and corresponding challenges for their performance. The findings of the study assisted in the development of the initial items and domains of the Chinese version of the Revised Caregiving Self-Efficacy Scale (C-RCSES). Following changes to items in the scale, the second study, a cross-sectional survey with 196 CGs was conducted to evaluate the psychometric properties of C-RCSES and to test a hypothesised self-efficacy model of family caregiving adapted from Bandura’s theory (1997). Results: 35 items were generated from the qualitative data. The content validity of the C-RCSES was assessed and ensured in Study One before being used for the cross-sectional survey. Eight items were removed and five subscales (caregiver self-efficacy for gathering information about treatment, symptoms and health care; obtaining support; responding to problematic behaviours; management of household, personal and medical care; and controlling upsetting thoughts about caregiving) were identified after principal component factor analysis on the cross-sectional survey data. The reliability of the scale is acceptable: the Cronbach’s alpha coefficients for the whole scale and for each subscale were all over .80; and the fourweek test-retest reliabilities for the whole scale and for each subscale ranged from .64 to .85. The concurrent, convergent and divergent validity were also acceptable. CGs reported moderate levels of caregiver self-efficacy. Furthermore, the level of self-efficacy for management of household, personal and medical care was relatively high in comparison to those of the other four domains of caregiver self-efficacy. Caregiver self-efficacy was also significantly influenced by CGs’ socio-demographic characteristics and the caregiving external factors (CR impairment and social support that CGs obtained). The level of caregiver behaviour that CGs reported was higher than that reported in other Chinese research. CGs’ socio-demographics significantly influenced caregiver behaviour, whereas caregiver self-efficacy did not influence caregiver behaviour. Regarding the two external factors, CGs who cared for highly impaired relatives reported high levels of caregiver behaviour, but social support did not influence caregiver behaviour. Regarding caregiver subjective burden and health-related quality of life, CGs reported moderate levels of subjective burden, and their level of healthrelated quality of life was significantly lower than that of the general population in China. The findings also indicated that CGs’ subjective burden and health-related quality of life were influenced by all major factors in the hypothesised model, including CGs’ socio-demographics, CRs’ impairment, social support that CGs obtained, caregiver self-efficacy and caregiver behaviour. Of these factors, caregiver self-efficacy and social support significantly improved their subjective burden and health-related quality of life; whereas caregiver behaviour and CRs’ impairment were detrimental to CGs, such as increasing subjective burden and worsening health-related quality of life. Conclusion: While requiring further exploration, the qualitative study was the first qualitative research conducted in China to provide an in-depth understanding of CGs’ caregiving experience, including their major caregiver behaviours and the corresponding challenges. Meanwhile, although the C-RCSES needs further psychometric testing, it is a useful tool for assessing caregiver self-efficacy in Chinese populations. Results of the qualitative and quantitative study provide useful information for future studies regarding the explanatory power of caregiver self-efficacy to caregiver behaviour, subjective burden and health-related quality of life. Additionally, integrated with Bandura’s theory, the findings from the quantitative study also suggested a further study exploring the role of outcome expectations in caregiver behaviour, subjective burden and healthrelated quality of life.

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Even though there is substantial agreement about the nature of rural contexts, practice principles, and factors influencing practice we still do not have a framework for organising this knowledge in a way that can directly inform the practitioner in their day-to-day work. In this paper, we introduce the concepts 'practice domains', 'domain location', and 'domain alignment' that, taken together, provide such a framework. We suggest that each practitioner works within a number of practice domains. A domain is a discourse about practice comprising narratives about how a social worker should practise and which factors they should take most account of in their practice decision making. Each practitioner, and each practice process, can be located somewhere within each domain (domain location) and also situated amongst domains according to their relative alignment with each of them (domain alignment). In this paper, we present this framework and show how it is useful for practitioners in understanding practice, identifying factors influencing it, and making practice decisions in immediate, concrete situations.