979 resultados para LEVEL SET METHODS


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The article offers an example of using a mixed methods design that was implemented when investigating depression among Chinese older persons in Macau. A challenge in designing the study was that in light of literature on Chinese culture and somatization theory, the acceptability of the methodology was uncertain. Participants (n = 31) were purposively selected and quantitative data were collected using multiple standardized measures. Questions raised by the quantitative approach were then reflected through in-depth interviews. Four dominant categories emerged: (a) negative thinking, (b) physical limitations and complaints, (c) present living conditions and social support, and (d) the lives participants have lived. There was a high level of congruence between quantitative scores and narratives. The research approach was acceptable to the participants, and the findings contributed to an understanding of depression and therapeutic interventions for that population within Chinese culture.

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Background: There are few validated measures of organizational context and none that we located are parsimonious and address modifiable characteristics of context. The Alberta Context Tool (ACT) was developed to meet this need. The instrument assesses 8 dimensions of context, which comprise 10 concepts. The purpose of this paper is to report evidence to further the validity argument for ACT. The specific objectives of this paper are to: (1) examine the extent to which the 10 ACT concepts discriminate between patient care units and (2) identify variables that significantly contribute to between-unit variation for each of the 10 concepts.

Methods: 859 professional nurses (844 valid responses) working in medical, surgical and critical care units of 8 Canadian pediatric hospitals completed the ACT. A random intercept, fixed effects hierarchical linear modeling (HLM) strategy was used to quantify and explain variance in the 10 ACT concepts to establish the ACT’s ability to discriminate between units. We ran 40 models (a series of 4 models for each of the 10 concepts) in which we systematically assessed the unique contribution (i.e., error variance reduction) of different variables to between-unit variation. First, we constructed a null model in which we quantified the variance overall, in each of the concepts. Then we controlled for the contribution of individual level variables (Model 1). In Model 2, we assessed the contribution of practice specialty (medical, surgical, critical care) to variation since it was central to construction of the sampling frame for the study. Finally, we assessed the contribution of additional unit level variables (Model 3).

Results: The null model (unadjusted baseline HLM model) established that there was significant variation between units in each of the 10 ACT concepts (i.e., discrimination between units). When we controlled for individual characteristics, significant variation in the 10 concepts remained. Assessment of the contribution of specialty to between-unit variation enabled us to explain more variance (1.19% to 16.73%) in 6 of the 10 ACT concepts. Finally, when we assessed the unique contribution of the unit level variables available to us, we were able to explain additional variance (15.91% to 73.25%) in 7 of the 10 ACT concepts.

Conclusion: The findings reported here represent the third published argument for validity of the ACT and adds to the evidence supporting its use to discriminate patient care units by all 10 contextual factors. We found evidence of relationships between a variety of individual and unit-level variables that explained much of this between-unit variation for each of the 10 ACT concepts. Future research will include examination of the relationships between the ACT’s contextual factors and research utilization by nurses and ultimately the relationships between context, research utilization, and outcomes for patients.

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We present a comparative evaluation of the state-of-art algorithms for detecting pedestrians in low frame rate and low resolution footage acquired by mobile sensors. Four approaches are compared: a) The Histogram of Oriented Gradient (HoG) approach [1]; b) A new histogram feature that is formed by the weighted sum of both the gradient magnitude and the filter responses from a set of elongated Gaussian filters [2] corresponding to the quantised orientation, called Histogram of Oriented Gradient Banks (HoGB) approach; c) The codebook based HoG feature with branch-and-bound (efficient subwindow search) algorithm [3] and; d) The codebook based HoGB approach. Results show that the HoG based detector achieves the highest performance in terms of the true positive detection, the HoGB approach has the lowest false positives whilst maintaining a comparable true positive rate to the HoG, and the codebook approaches allow computationally efficient detection.

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Automatically partitioning instructional videos into topic sections is a challenging problem in e-learning environments for efficient content management and cataloging. This paper addresses this problem by proposing a novel density function to delineate sections underscored by changes in topics in instructional and training videos. The content density function draws guidance from the observation that topic boundaries coincide with the ebb and flow of the 'density' of content shown in these videos. Based on this function, we propose two methods for high-level segmentation by determining topic boundaries. We study the performance of the two methods on eight training videos, and our experimental results demonstrate the effectiveness and robustness of the two proposed high-level segmentation algorithms for learning media.

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The problem of deriving spatial relationships between objects in general requires high level abstract representation, and it would pose difficulties even for human observer. Based on a formalism for spatial layouts proposed earlier [KiV92, VeK921, we present methods for deducing high level spatial relations between objects by an active, sighted agent in a large-scale environment. The deduction of spatial relations is based on simple visual clues, and thus this technique is more feasible than schemes that rely on complex object recognition.

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Decentralisation, provincial government, and regional autonomy continue as influential factors in Papua New Guinea’s political economy.  The role played in creating PNG’s provincial government system by separatist movements in East New Britain, Bougainville and elsewhere is acknowledged.  However, as the Constitutional Planning Committee (CPC) discovered during its program of consultations with the Papua New Guinean people from 1972 to 1974, there was a strong groundswell around the country for district-level governments.  This article investigates how the CPC stimulated discussion of this issue through its own activities, and how the people in their discussion groups responded to the CPC’s ‘Discussion Paper on Relations Between the Central Government and Other Levels of Government’.

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Background: Cardiovascular diseases (CVD) cause 1.8 million premature (<75 years) death annually in Europe. The majority of these deaths are preventable with the most efficient and cost-effective approach being on the population level. The aim of this position paper is to assist authorities in selecting the most adequate management strategies to prevent CVD.

Design and Methods:
Experts reviewed and summarized the published evidence on the major modifiable CVD risk factors: food, physical inactivity, smoking, and alcohol. Population-based preventive strategies focus on fiscal measures (e.g. taxation), national and regional policies (e.g. smoke-free legislation), and environmental changes (e.g. availability of alcohol).

Results: Food is a complex area, but several strategies can be effective in increasing fruit and vegetables and lowering intake of salt, saturated fat, trans-fats, and free sugars. Tobacco and alcohol can be regulated mainly by fiscal measures and national policies, but local availability also plays a role. Changes in national policies and the built environment will integrate physical activity into daily life.

Conclusion: Societal changes and commercial influences have led to the present unhealthy environment, in which default option in life style increases CVD risk. A challenge for both central and local authorities is, therefore, to ensure healthier defaults. This position paper summarizes the evidence and recommends a number of structural strategies at international, national, and regional levels that in combination can substantially reduce CVD.

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Background: Lower socioeconomic status (SES) is strongly associated with a higher prevalence of major cardiovascular risk factors, but few studies have examined changes in these risk factors over time according to SES. We aimed to determine whether SES is a predictor of the change in cardiovascular risk factor levels in a contemporary Australian adult cohort

Methods: Participants in the population-based AusDiab study aged 25+ years who attended both baseline and 5-year follow-up examinations (n=5 954) were categorised according to their level of education at baseline. Cardiovascular risk factor data at both time points were ascertained through questionnaire and physical measurement. Analysis was stratified by gender.

Results: The mean levels of systolic blood pressure, total cholesterol and the prevalence of smoking decreased between the two time points across all educational categories. Increases were also seen in mean BMI and the prevalence of diabetes. For blood pressure, the smallest decrease was seen among men with lower education (age-adjusted difference from higher education 2.8 mmHg, 95% CI 1.0 to 4.6). For total cholesterol, the decrease was greatest among women with lower education (age-adjusted difference from higher education 0.11 mmol/l, 95% CI 0.19 to 0.02). Among those "not at risk" at baseline for each risk factor, women with lower education were more likely than those with higher education to progress to being "at risk" for BMI (age-adjusted odds ratio 1.60, 95% CI 1.09 to 2.35).

Conclusion: Educational gradients narrowed for total cholesterol in women, but widened for systolic blood pressure in men and remained static for other risk factors. Lower education was also associated with an earlier onset of overweight or obesity in women. Given current socioeconomic gradients in risk factors levels, these findings suggest that social inequalities in CVD will persist and may even widen in the future.

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OBJECTIVE--To examine the role of area-level socioeconomic status (SES) on the development of abnormal glucose metabolism (AGM) using national, population-based data.

RESEARCH DESIGN AND METHODS--The Australian Diabetes, Obesity and Lifestyle (AusDiab) study is a national, population-based, longitudinal study of adults aged [greater than or equal to] 25 years. A sample of 4,572 people provided complete baseline (1999 to 2000) and 5-year follow-up (2004 to 2005) data relevant for these analyses. Incident AGM was assessed using fasting plasma glucose and 2-h plasma glucose from oral glucose tolerance tests, and demographic, socioeconomic, and behavioral data were collected by interview and questionnaire. Area SES was defined using the Index of Relative Socioeconomic Disadvantage. Generalized linear mixed models were used to examine the relationship between area SES and incident AGM, with adjustment for covariates and correction for cluster design effects.

RESULTS--Area SES predicted the development of AGM, after adjustment for age, sex, and individual SES. People living in areas with the most disadvantage were significantly more likely to develop AGM, compared with those living in the least deprived areas (odds ratio 1.53; 95% CI 1.07-2.18). Health behaviors (in particular, physical activity) and central adiposity appeared to partially mediate this relationship.

CONCLUSIONS--Our findings suggest that characteristics of the physical, social, and economic aspects of local areas influence diabetes risk. Future research should focus on identifying the aspects of local environment that are associated with diabetes risk and how they might be modified.

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Background Australian mortality rates are higher in regional and remote areas than in major cities. The degree to which this is driven by variation in modifiable risk factors is unknown.

Methods We applied a risk prediction equation incorporating smoking, cholesterol and blood pressure to a national, population based survey to project all-causes mortality risk by geographic region. We then modelled life expectancies at different levels of mortality risk by geographic region using a risk percentiles model. Finally we set high values of each risk factor to a target level and modelled the subsequent shift in the population to lower levels of mortality risk and longer life expectancy.

Results Survival is poorer in both Inner Regional and Outer Regional/Remote areas compared to Major Cities for men and women at both high and low levels of predicted mortality risk. For men smoking, high cholesterol and high systolic blood pressure were each associated with the mortality difference between Major Cities and Outer Regional/Remote areas--accounting for 21.4%, 20.3% and 7.7% of the difference respectively. For women smoking and high cholesterol accounted for 29.4% and 24.0% of the difference respectively but high blood pressure did not contribute to the observed mortality differences. The three risk factors taken together accounted for 45.4% (men) and 35.6% (women) of the mortality difference. The contribution of risk factors to the corresponding differences for inner regional areas was smaller, with only high cholesterol and smoking contributing to the difference in men-- accounting for 8.8% and 6.3% respectively-- and only smoking contributing to the difference in women--accounting for 12.3%.

Conclusions These results suggest that health intervention programs aimed at smoking, blood pressure and total cholesterol could have a substantial impact on mortality inequities for Outer Regional/Remote areas. Background: Australian mortality rates are higher in regional and remote areas than in major cities. The degree to which this is driven by variation in modifiable risk factors is unknown. Methods. We applied a risk prediction equation incorporating smoking, cholesterol and blood pressure to a national, population based survey to project all-causes mortality risk by geographic region. We then modelled life expectancies at different levels of mortality risk by geographic region using a risk percentiles model. Finally we set high values of each risk factor to a target level and modelled the subsequent shift in the population to lower levels of mortality risk and longer life expectancy. Results: Survival is poorer in both Inner Regional and Outer Regional/Remote areas compared to Major Cities for men and women at both high and low levels of predicted mortality risk. For men smoking, high cholesterol and high systolic blood pressure were each associated with the mortality difference between Major Cities and Outer Regional/Remote areas - accounting for 21.4%, 20.3% and 7.7% of the difference respectively. For women smoking and high cholesterol accounted for 29.4% and 24.0% of the difference respectively but high blood pressure did not contribute to the observed mortality differences. The three risk factors taken together accounted for 45.4% (men) and 35.6% (women) of the mortality difference. The contribution of risk factors to the corresponding differences for inner regional areas was smaller, with only high cholesterol and smoking contributing to the difference in men - accounting for 8.8% and 6.3% respectively - and only smoking contributing to the difference in women - accounting for 12.3%. Conclusions: These results suggest that health intervention programs aimed at smoking, blood pressure and total cholesterol could have a substantial impact on mortality inequities for Outer Regional/Remote areas.

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The effect of mental reinstatement of context was examined using a 4*5*2 factorial design incorporating four age groups (6-year-olds, 8-year-olds, 11-year-olds and adults), two retention intervals (1 day and 2 weeks after the stimulus event) and five interview conditions. The interview conditions included; free recall, mental reinstatement-environment (where the setting was reinstated but no event-related detail was provided in the mnemonic instruction), mental reinstatement-event (where specific event-related content was provided), mental reinstatement-combined (a combination of the two above-mentioned methods) and specific questions. Overall, mental reinstatement (irrespective of the type) was found to enhance correct recall performance compared to free recall and (unlike specific questions) it did not lead to greater number of commission errors. Contrary to our initial predictions, however, there was no evidence of any special benefit of mental reinstatement for children and the effect of the technique did not vary consistently as a function of retention interval.

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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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Literature surrounding the Knowledge Management process of identifying what knowledge exists within an organisation is scarce. This research project set out to fill the research gaps surrounding that particular Knowledge Management process called Knowledge Identification. This paper reports on the findings of a survey sent to 973 Australian organisations to investigate their Knowledge Identification practices. The survey findings show that while organisations do perceive Knowledge Identification to be important, the practice of KI has not reached mainstream adoption yet. The reasons why and why not, and the range of methods organisations currently use to establish what knowledge exists within their four walls are identified. The survey findings also reveal two opposing approaches organisations take in practising KI: proactive KI and reactive KI.

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In named entity recognition (NER) for biomedical literature, approaches based on combined classifiers have demonstrated great performance improvement compared to a single (best) classifier. This is mainly owed to sufficient level of diversity exhibited among classifiers, which is a selective property of classifier set. Given a large number of classifiers, how to select different classifiers to put into a classifier-ensemble is a crucial issue of multiple classifier-ensemble design. With this observation in mind, we proposed a generic genetic classifier-ensemble method for the classifier selection in biomedical NER. Various diversity measures and majority voting are considered, and disjoint feature subsets are selected to construct individual classifiers. A basic type of individual classifier – Support Vector Machine (SVM) classifier is adopted as SVM-classifier committee. A multi-objective Genetic algorithm (GA) is employed as the classifier selector to facilitate the ensemble classifier to improve the overall sample classification accuracy. The proposed approach is tested on the benchmark dataset – GENIA version 3.02 corpus, and compared with both individual best SVM classifier and SVM-classifier ensemble algorithm as well as other machine learning methods such as CRF, HMM and MEMM. The results show that the proposed approach outperforms other classification algorithms and can be a useful method for the biomedical NER problem.

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Objective: The objective of this study was to identify school environmental characteristics associated with moderate to vigorous physical activity during school recess, including morning and lunch breaks.

Methods: Accelerometry data, child-level characteristics and school physical activity, policy and socio-cultural data were collected from 408 sixth grade children (mean age 11 years) attending 27 metropolitan primary schools in Perth, Western Australia. Hierarchical modelling identified key characteristics associated with children's recess moderate to vigorous physical activity (RMVPA).

Results: Nearly 40% of variability in children's RMVPA was explained by school environment and individual characteristics identified in this study. Children's higher daily RMVPA was associated with newer schools, schools with a higher number of grassed surfaces per child and fewer shaded grassed surfaces, and the physical education coordinator meeting Australian physical activity guidelines.

Conclusions:
Characteristics of the school physical and social environments are strongly correlated with children's MPVA during recess.