997 resultados para vector competence


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The Electrocardiogram (ECG) is an important bio-signal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. The HRV signal can be used as a base signal to observe the heart's functioning. These signals are non-linear and non-stationary in nature. So, higher order spectral (HOS) analysis, which is more suitable for non-linear systems and is robust to noise, was used. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, we have extracted seven features from the heart rate signals using HOS and fed them to a support vector machine (SVM) for classification. Our performance evaluation protocol uses 330 subjects consisting of five different kinds of cardiac disease conditions. We demonstrate a sensitivity of 90% for the classifier with a specificity of 87.93%. Our system is ready to run on larger data sets.

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The number of children with special health care needs surviving infancy and attending school has been increasing. Due to their health status, these children may be at risk of low social-emotional and learning competencies (e.g., Lightfoot, Mukherjee, & Sloper, 2000; Zehnder, Landolt, Prchal, & Vollrath, 2006). Early social problems have been linked to low levels of academic achievement (Ladd, 2005), inappropriate behaviours at school (Shiu, 2001) and strained teacher-child relationships (Blumberg, Carle, O‘Connor, Moore, & Lippmann, 2008). Early learning difficulties have been associated with mental health problems (Maughan, Rowe, Loeber, & Stouthamer-Loeber, 2003), increased behaviour issues (Arnold, 1997), delinquency (Loeber & Dishion, 1983) and later academic failure (Epstein, 2008). Considering the importance of these areas, the limited research on special health care needs in social-emotional and learning domains is a factor driving this research. The purpose of the current research is to investigate social-emotional and learning competence in the early years for Australian children who have special health care needs. The data which informed this thesis was from Growing up in Australia: The Longitudinal Study of Australian Children. This is a national, longitudinal study being conducted by the Commonwealth Department of Families, Housing, Community Services and Indigenous Affairs. The study has a national representative sample, with data collection occurring biennially, in 2004 (Wave 1), 2006 (Wave 2) and 2008 (Wave 3). Growing up in Australia uses a cross-sequential research design involving two cohorts, an Infant Cohort (0-1 at recruitment) and a Kindergarten Cohort (4-5 at recruitment). This study uses the Kindergarten Cohort, for which there were 4,983 children at recruitment. Three studies were conducted to address the objectives of this thesis. Study 1 used Wave 1 data to identify and describe Australian children with special health care needs. Children who identified as having special health care needs through the special health care needs screener were selected. From this, descriptive analyses were run. The results indicate that boys, children with low birth weight and children from families with low levels of maternal education are likely to be in the population of children with special health care needs. Further, these children are likely to be using prescription medications, have poor general health and are likely to have specific condition diagnoses. Study 2 used Wave 1 data to examine differences between children with special health care needs and their peers in social-emotional competence and learning competence prior to school. Children identified by the special health care needs screener were chosen for the case group (n = 650). A matched case control group of peers (n = 650), matched on sex, cultural and linguistic diversity, family socioeconomic position and age, were the comparison group. Social-emotional competence was measured through Social/Emotional Domain scores taken from the Growing up in Australia Outcome Index, with learning competence measured through Learning Domain scores. Results suggest statistically significant differences in scores between the two groups. Children with special health care needs have lower levels of social-emotional and learning competence prior to school compared to their peers. Study 3 used Wave 1 and Wave 2 data to examine the relationship between special health care needs at Wave 1 and social-emotional competence and learning competence at Wave 2, as children started school. The sample for this study consisted of children in the Kindergarten Cohort who had teacher data at Wave 2. Results from multiple regression models indicate that special health care needs prior to school (Wave 1) significantly predicts social-emotional competence and learning competence in the early years of school (Wave 2). These results indicate that having special health care needs prior to school is a risk factor for the social-emotional and learning domains in the early years of school. The results from these studies give valuable insight into Australian children with special health care needs and their social-emotional and learning competence in the early years. The Australia population of children with special health care needs were primarily male children, from families with low maternal education, were likely to be of poor health and taking prescription medications. It was found that children with special health care needs were likely to have lower social-emotional competence and learning competence prior to school compared to their peers. Results indicate that special health care needs prior to school were predictive of lower social-emotional and learning competencies in the early years of school. More research is required into this unique population and their competencies over time. However, the current research provides valuable insight into an under researched 'at risk' population.

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Background The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

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Gaussian mixture models (GMMs) have become an established means of modeling feature distributions in speaker recognition systems. It is useful for experimentation and practical implementation purposes to develop and test these models in an efficient manner particularly when computational resources are limited. A method of combining vector quantization (VQ) with single multi-dimensional Gaussians is proposed to rapidly generate a robust model approximation to the Gaussian mixture model. A fast method of testing these systems is also proposed and implemented. Results on the NIST 1996 Speaker Recognition Database suggest comparable and in some cases an improved verification performance to the traditional GMM based analysis scheme. In addition, previous research for the task of speaker identification indicated a similar system perfomance between the VQ Gaussian based technique and GMMs

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Data from Growing Up in Australia: The Longitudinal Study of Australian Children is used to examine the associations between playgroup participation and the outcomes for children aged 4 to 5 years. Controlling for a range of socio-economic and family characteristics, playgroup participation across the ages of 0-3 years was used to predict learning competence and social-emotional functioning outcomes at age 4-5 years. For learning competence, both boys and girls from disadvantaged families scored 3-4% higher if they attended playgroup when aged 0-1 and 2-3 years compared to boys and girls from disadvantaged families who did not attend playgroup. For social and emotional functioning, girls from disadvantaged families who attended playgroup when they were aged 0-1 and 2-3 years scored nearly 5% higher than those who did not attend. Demographic characteristics also showed that disadvantaged families were the families least likely to access these services. Despite data limitations, this study provides evidence that continued participation in playgroups is associated with better outcomes for children from disadvantaged families.

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A fundamental aspect of work integrated learning (WIL) is the development of professional competence, the ability of students to perform in the work place. Alignment theory therefore suggests that the assessment of WIL should include an assessment of students’ demonstration of professional competence in the workplace. The assessment of professional competence in WIL is, however, problematic. It may be impractical for the academic supervisor to directly assess professional competence if there is a large number of students in external placements. If evidence of professional competence is provided by the student, the student’s ability to articulate his or her own capabilities will interfere with the validity of the assessment. If evidence of professional competency is provided by the supervisor then the assessment is heavily dependent on the individual supervisor and may be unreliable. This paper will examine the literature relating to the assessment of professional competence in WIL. The paper will be informed by the author’s experience in coordinating a WIL subject in an undergraduate law course. It will recommend that a mix of evidence provided by the student, the workplace supervisor and the academic supervisor should be used to assess professional competence in WIL.

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Robust speaker verification on short utterances remains a key consideration when deploying automatic speaker recognition, as many real world applications often have access to only limited duration speech data. This paper explores how the recent technologies focused around total variability modeling behave when training and testing utterance lengths are reduced. Results are presented which provide a comparison of Joint Factor Analysis (JFA) and i-vector based systems including various compensation techniques; Within-Class Covariance Normalization (WCCN), LDA, Scatter Difference Nuisance Attribute Projection (SDNAP) and Gaussian Probabilistic Linear Discriminant Analysis (GPLDA). Speaker verification performance for utterances with as little as 2 sec of data taken from the NIST Speaker Recognition Evaluations are presented to provide a clearer picture of the current performance characteristics of these techniques in short utterance conditions.

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This study explored the developing intercultural competence of fourth-year Australian education pre-service teachers through a core unit of study on inclusive education, following a service-learning pathway. The Australian pre-service teachers volunteered to be 'of service' to a cohort of second-year Malaysian pre-service teachers studying in Australia in a transnational twinning program. Students participated in a Patches program which included writing 'patches' (reflections) and engaging in social exchanges. Data were gathered from focus group interviews, written reflection logs and Patches writing books and were analysed through Butin's (2005) four-lenses of service-learning: technical, cultural, political and post-modern lenses. Data revealed that initially the Australian pre-service teachers felt their presumptions but by the end of the semester embraced the basic tenants of inclusion and were able to project how they could take their new understandings into the classroom as inclusive teachers.

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The psychologists in the western world, including Australia, are required to be culturally competent due to the cultural diversity of these societies. Previous studies conducted in North America and Europe have found multicultural teaching, clinical experience with culturally diverse clients, and discussion of multicultural counselling issues in supervision to be related to the practitioner’s cultural competency. The present study examined factors contributing to trainee psychologists’ perceived level of cultural competence. It was hypothesised that multicultural teaching, clinical experience and supervision would be related to students’ level of cultural competence. One hundred and twenty seven postgraduate clinical psychology students completed an online survey battery that included demographic information, a social desirability measure, and the Multicultural Mental Health Awareness Scale (Khawaja, Gomez & Turner, 2009). This hypothesis was partially supported. Clinical experience and supervision focusing on multicultural issues were found to be related to participants’ perceived cultural competence, however, multicultural teaching was not. These results provide insight into how universities around Australia can facilitate future psychologists’ competence in working with clients from different cultural backgrounds.

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Objective: This paper aims to integrate nurse practitioner literature on competence and capability with post graduate and nursing literature on e‑portfolios in order to demonstrate the potential merits of e‑portfolios in nurse practitioner education for competence and capability development. Primary Argument In the Nurse Practitioner Standards Project, competence and capability were proposed as key criteria to assess candidates in nurse practitioner educational courses. Portfolios have traditionally been used to demonstrate competence in nursing and are integral to nursing education as well. An examination of the portfolio and electronic portfolio literature in postgraduate nursing education and professional practice indicates that these portfolios fall under two main structures, each with different purposes: 1) A spinal column structure, with evidence and reflective pieces aligned to competency standards or course objectives, for the purposes of meeting prescribed competencies, professional development planning and showcasing evidence for authorisation or potential employers; and 2) A cake mix structure, which consists of a reflective narrative tying evidence together, which enables a greater focus on personal learning journeys, reflection and the development of personal qualities. Finally, evidence from the general nursing literature suggests the complexity of e‑portfolios in assessment and evaluation can be overcome by using qualitative research methods. Conclusion: To meet the competence and capability needs of nurse practitioners, portfolios could be used, for competence and showcasing and for learning and capability. Further research would be useful to refine and explore the use of e‑portfolios to meet the needs of NP candidates and their educators, clinical mentors, authorisation personal and employers. The current evidence on nurse practitioner education, competence, capability and e‑portfolios points to the integration of the use of an e‑portfolio into current nurse practitioner curriculum models to meet the unique needs of nurse practitioner candidates.

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This paper introduces the Weighted Linear Discriminant Analysis (WLDA) technique, based upon the weighted pairwise Fisher criterion, for the purposes of improving i-vector speaker verification in the presence of high intersession variability. By taking advantage of the speaker discriminative information that is available in the distances between pairs of speakers clustered in the development i-vector space, the WLDA technique is shown to provide an improvement in speaker verification performance over traditional Linear Discriminant Analysis (LDA) approaches. A similar approach is also taken to extend the recently developed Source Normalised LDA (SNLDA) into Weighted SNLDA (WSNLDA) which, similarly, shows an improvement in speaker verification performance in both matched and mismatched enrolment/verification conditions. Based upon the results presented within this paper using the NIST 2008 Speaker Recognition Evaluation dataset, we believe that both WLDA and WSNLDA are viable as replacement techniques to improve the performance of LDA and SNLDA-based i-vector speaker verification.