533 resultados para Machines à vecteurs de support


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As the proportion of older employees in the workforce is growing, researchers have become increasingly interested in the association between age and occupational well-being. The curvilinear nature of relationships between age and job satisfaction and between age and emotional exhaustion is well-established in the literature, with employees in their late 20s to early 40s generally reporting lower levels of occupational well-being than younger and older employees. However, the mechanisms underlying these curvilinear relationships are so far not well understood due to a lack of studies testing mediation effects. Based on an integration of role theory and research from the adult development and career literatures, this study examined time pressure, work–home conflict, and coworker support as mediators of the relationships between age and job satisfaction and between age and emotional exhaustion. Data came from 771 employees between 17 and 74 years of age in the construction industry. Results showed that employees in their late 20s to early 40s had lower job satisfaction and higher emotional exhaustion than younger and older employees. Time pressure and coworker support fully mediated both the U-shaped relationship between age and job satisfaction and the inversely U-shaped relationship between age and emotional exhaustion. These findings suggest that organizational interventions may help increase the relatively low levels of occupational well-being in certain age groups.

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This paper presents a novel place recognition algorithm inspired by the recent discovery of overlapping and multi-scale spatial maps in the rodent brain. We mimic this hierarchical framework by training arrays of Support Vector Machines to recognize places at multiple spatial scales. Place match hypotheses are then cross-validated across all spatial scales, a process which combines the spatial specificity of the finest spatial map with the consensus provided by broader mapping scales. Experiments on three real-world datasets including a large robotics benchmark demonstrate that mapping over multiple scales uniformly improves place recognition performance over a single scale approach without sacrificing localization accuracy. We present analysis that illustrates how matching over multiple scales leads to better place recognition performance and discuss several promising areas for future investigation.

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The purpose of this study was to explore associations between forms of social support and levels of psychological distress during pregnancy. Methods: A cross-sectional analysis of 2,743 pregnant women from south-east Queensland, Australia, was conducted utilising data collected between 2007-2011 as part of the Environments for Healthy Living (EFHL) project, Griffith University. Psychological distress was measured using the Kessler 6; social support was measured using the following four factors: living with a partner, living with parents or in-laws, self-perceived social network, and area satisfaction. Data were analysed using an ordered logistic regression model controlling for a range of socio-demographic factors. Results: There was an inverse association between self-perceived strength of social networks and levels of psychological distress (OR = 0.77; 95%CI: 0.70, 0.85) and between area satisfaction and levels of psychological distress (OR = 0.77; 95%CI: 0.69, 0.87). There was a direct association between living with parents or in-laws and levels of psychological distress (OR = 1.50; 95%CI: 1.16, 1.96). There was no statistically significant association between living with a partner and the level of psychological distress of the pregnant woman after accounting for household income. Conclusion: Living with parents or in-laws is a strong marker for psychological distress. Strategies aiming to build social support networks for women during pregnancy have the potential to provide a significant benefit. Policies promoting stable family relationships and networks through community development could also be effective in promoting the welfare of pregnant women.

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In this paper, a novel data-driven approach to monitoring of systems operating under variable operating conditions is described. The method is based on characterizing the degradation process via a set of operation-specific hidden Markov models (HMMs), whose hidden states represent the unobservable degradation states of the monitored system while its observable symbols represent the sensor readings. Using the HMM framework, modeling, identification and monitoring methods are detailed that allow one to identify a HMM of degradation for each operation from mixed-operation data and perform operation-specific monitoring of the system. Using a large data set provided by a major manufacturer, the new methods are applied to a semiconductor manufacturing process running multiple operations in a production environment.

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Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.

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The critical role that family plays in Chinese Heritage Language learning has gained increasing attention from psychological, political and sociological scholarship. Guided by Bourdieu’s notion of ‘habitus’, our mixed methods sociological study firstly addresses the need for quantitative evidence on the relationship between family support and Chinese Heritage Language proficiency through a survey of 230 young Chinese Australians; and then explores the dynamics of family support of Chinese Heritage Language learning through multiple interviews with five participants. The interview data demonstrate ongoing intergenerational reproduction of Chinese Heritage Language through various forms of family inculcation. Learners’ transition from resistance to commitment is a focus of the analysis. Extant research struggles to theorise the reasons behind this transition. We offer a Bourdieusian explanation that construes the transition as ‘habitus realisation’. Our study has implications for Chinese Heritage Language researchers, Chinese immigrant parents and Chinese teachers.

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The emerging growth of Web 2.0 has been observed by users in the workplace, and has therefore encouraged organisations to introduce Web 2.0 technologies in their businesses. Although its adoption is beneficial, it could meets with employees resistance due to some organisational factors. The successful implementation of Enterprise Web 2.0 is based on employee adoption of such social technology. Using a qualitative study, this research explores how organizational support can influence employees’ adoption of Enterprise Web 2.0. The findings show that organisational support encourages and facilitates a smooth adoption. Such support can be provided by management and colleagues in several forms: developing a Web 2.0 strategy, providing required resources for such training, recognising and encouraging adopters, and involving managers in the adoption.

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Effective control of morphology and electrical connectivity of networks of single-walled carbon nanotubes (SWCNTs) by using rough, nanoporous silica supports of Fe catalyst nanoparticles in catalytic chemical vapor deposition is demonstrated experimentally. The very high quality of the nanotubes is evidenced by the G-to-D Raman peak ratios (>50) within the range of the highest known ratios. Transitions from separated nanotubes on smooth SiO2 surface to densely interconnected networks on the nanoporous SiO2 are accompanied by an almost two-order of magnitude increase of the nanotube density. These transitions herald the hardly detectable onset of the nanoscale connectivity and are confirmed by the microanalysis and electrical measurements. The achieved effective nanotube interconnection leads to the dramatic, almost three-orders of magnitude decrease of the SWCNT network resistivity compared to networks of similar density produced by wet chemistry-based assembly of preformed nanotubes. The growth model, supported by multiscale, multiphase modeling of SWCNT nucleation reveals multiple constructive roles of the porous catalyst support in facilitating the catalyst saturation and SWCNT nucleation, consistent with the observed higher density of longer nanotubes. The associated mechanisms are related to the unique surface conditions (roughness, wettability, and reduced catalyst coalescence) on the porous SiO2 and the increased carbon supply through the supporting porous structure. This approach is promising for the direct integration of SWCNT networks into Si-based nanodevice platforms and multiple applications ranging from nanoelectronics and energy conversion to bio- and environmental sensing.

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The digital era is proving to be one of disruption, where new technologies matched with innovative business models can be harnessed to attack even the most established of companies. For businesses with the relative certainty of captive customer bases, such as airports, the ability to digitally diversify offers the opportunity to venture into new modes of operation. For an airport, this opportunity can also be leveraged to sustain superior customer support regardless of a customer’s location in the world. This research paper presents a case study of the development of an Australian Airport Corporation’s mobile application as part of a greater digital strategy initiative using a design-led approach to innovate. An action research method provides the platform for an intensive embedded practice and study of design-led innovation within the major Australian Airport Corporation. The findings reveal design-led innovation to be a crucial in-house idea generation and concept development capability enabling the bridging of distinct corporate domains associated with commercialisation, operations and customer experience. A Digital Innovation Checklist is presented as an output of this research which structures an organizational approach toward digital channel innovation. The practitioner’s checklist is designed to aid in the future development of digital channels within the broader spectrum of strategy by addressing business assumptions.

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This ethnography presents a contextualised understanding of frontline knowledge used in the support to people ageing with an intellectual disability who live in accommodation and support services in south-east Queensland. The study identified that disability support workers accessed a range of knowledges which they synthesised into a dynamic and responsive locale knowledge, and subsequently translated into everyday acts of support within contexts of multi-faceted complexity. Findings from the study have numerous implications for the knowledge development activities of formal service and educational systems within Australia's newly implemented National Disability Insurance Scheme.

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A matched case-control study of mortality to children under age five was conducted to consider associations with parents' socio-economic status and social support in the Farafenni Demographic Surveillance Site (DSS). Cases and controls were selected from Farafenni DSS, matched on date of birth, and parents were interviewed about personal resources and social networks. Parents with the lowest personal socio-economic status and social support were identified. Multivariate multinomial regression was used to consider whether the children of these parents were at increased risk of either infant or 1-4 mortality, in separate models using either parents' characteristics. There was no benefit found for higher SES or better social support with respect to child mortality. Children of fathers who had the poorest social support had lower 1-4 mortality risk (OR=0.52, p=0.037). Given that socio-economic status was not associated with child mortality, it seems unlikely that the explanation for the link between father's social support and mortality is linked to resource availability. Explanations for the risk effect of father's social ties may lie in decision-making around health maintenance and health care for children.

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S. japonicum infection is believed to be endemic in 28 of the 80 provinces of the Philippines and the most recent data on schistosomiasis prevalence have shown considerable variability between provinces. In order to increase the efficient allocation of parasitic disease control resources in the country, we aimed to describe the small scale spatial variation in S. japonicum prevalence across the Philippines, quantify the role of the physical environment in driving the spatial variation of S. japonicum, and develop a predictive risk map of S. japonicum infection. Data on S. japonicum infection from 35,754 individuals across the country were geo-located at the barangay level and included in the analysis. The analysis was then stratified geographically for Luzon, the Visayas and Mindanao. Zero-inflated binomial Bayesian geostatistical models of S. japonicum prevalence were developed and diagnostic uncertainty was incorporated. Results of the analysis show that in the three regions, males and individuals aged ≥ 20 years had significantly higher prevalence of S. japonicum compared with females and children <5 years. The role of the environmental variables differed between regions of the Philippines. S. japonicum infection was widespread in the Visayas whereas it was much more focal in Luzon and Mindanao. This analysis revealed significant spatial variation in prevalence of S. japonicum infection in the Philippines. This suggests that a spatially targeted approach to schistosomiasis interventions, including mass drug administration, is warranted. When financially possible, additional schistosomiasis surveys should be prioritized to areas identified to be at high risk, but which were underrepresented in our dataset.

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Parents whose children are identified as having experienced or being at risk of experiencing significant harm potentially provide an invaluable dimension to our understanding of the circumstances that result in child abuse or neglect and how best to respond to these invariably complex situations. This paper reports findings from a study of the experiences of six parents. In-depth interviews were conducted with four mothers and two fathers who had been referred to an intensive family support services by the Queensland statutory child protection authority. Using a critical ecological perspective, the study focused on identifying and understanding the experiences of the parents in using formal family support services, including aspects of service delivery that were helpful or unhelpful. Parents also commented on their experiences of statutory child protection services. Service components and worker qualities that parents identified as being helpful included being accessible, targeted and integrated and being able to meet a continuum of needs, from a micro to a broader level. Their reports provide invaluable insight into how formal family support services, including child protection services, can better meet the needs of parents in addressing the recurring problem of child maltreatment.

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Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.