924 resultados para IT support


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This study shows a possibility of using municipal sewage sludge after thermal treatment in the production of a filtering material to water treatment. Due to the fast urbanization and implementation of high standards for effluent in many countries in recent years, the sewage sludge is being produced in an ever increasing amount. Therefore, the use of sludge is a suitable solution for the expected large quantity of sludge. Dehydration of sludge was performed by controlled heating at temperatures of 1100 degrees C, 850 degrees C, 650 degrees C, 350 degrees C for 3 hours. After thermal treatment the sludge was characterized by X-ray fluorescence, TG/DTG/DTA, residue solubilization and residue lixiviation tests. The aim of the present work was to observe, thought the characterization techniques, if the treated sewage sludge is or not adequate to be used as filter material to water treatment. It will be verified which treatment temperature of the sludge offer possibility to its use in water treatment without carrying pollutants in concentrations out of the standards.

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Childhood sexual abuse has been found to be a risk factor for developing negative parenting self-perceptions later in life. Given this established relationship, it is crucial to investigate factors that may mitigate negative outcomes, such as family support. The present study used secondary analysis of a dataset of 265 predominantly African-American and low-income mothers. This study examined differences in parenting self-perceptions among mothers who experienced childhood sexual abuse and those who did not. Analyses revealed that mothers who experienced childhood sexual abuse did not differ in terms of parenting self-perceptions from non-sexually-abused mothers. After controlling for depression, there was no moderating effect of family support; however, a main effect for family support was observed. The results indicate that depression plays a larger role in mothers’ parenting self-perceptions than childhood sexual abuse, and that family support is beneficial for all mothers, regardless of sexual abuse status. Clinical implications are discussed.

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The inclusion of non-ipsative measures of party preference (in essence ratings for each of the parties of a political system) has become established practice in mass surveys conducted for election studies. They exist in different forms, known as thermometer ratings or feeling scores, likes and dislikes scores, or support propensities. Usually only one of these is included in a single survey, which makes it difficult to assess the relative merits of each. The questionnaire of the Irish National Election Study 2002 (INES2002) contained three different batteries of non-ipsative party preferences. This paper investigates some of the properties of these different indicators. We focus in particular on two phenomena. First, the relationship between non-ipsative preferences and the choices actually made on the ballot. In Ireland this relationship is more revealing than in most other countries owing to the electoral system (STV) which allows voters to cast multiple ordered votes for candidates from different parties. Second, we investigate the latent structure of each of the batteries of party preferences and the relationships between them. We conclude that the three instruments are not interchangeable, that they measure different orientations, and that one –the propensity to vote for a party– is by far preferable if the purpose of the study is the explanation of voters’ actual choice behaviour. This finding has important ramifications for the design of election study questionnaires.

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Any movement towards sustainable tourism is dependent not only upon the industry and other key stakeholders but also the demand side, namely the tourists. Yet, there is a limited literature from the demand point of view. In this area, contributions to an understanding of tourists’ support to sustainable development are necessary. This paper analyzes the main determinants in tourist behavior regarding the environmental considerations when they are making decisions about their holiday plans. General literature on this issue highlights the need to consider socio-economic variables of the individual as well as the attributes related of their style of living. If the econometric model takes into account all these variables simultaneously, then the linkage between contextual changes and tourists´ behaviour is enriched and it may be estimated more accurately. In this sense, a multilevel approach using a random-intercept logistic models is proposed, since tourists belong to a country are affected by the same contextual variables. The analysis comprises a joint dataset composed by microdata belong to the survey Attitudes of Europeans Towards Tourism, which corresponds to Flash Eurobarometer 281, macrodata from Eurostat (GDP in pps and GDP growth) and additional variables profiles from the 2005 Environmental Sustainability Index. Country-specific effects are calculated across the EU-27 countries, which corroborated that attitudes to the sustainable tourism are heterogeneous geo-graphically. The higher the level of GDP, the lower the level of tourists´ support. These results could be explained because tourists of richer countries already have to pay more tax for envi-ronmental protection. Age, gender and educational attainment are relevant. Motivations for travelling, size of the community, type of the destination, and environmental sustainability indi-cators of the place of residence are also important factors.

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Comunicação apresentada na 44th SEFI Conference, 12-­15 September 2016, Tampere, Finland

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An Interactive electronic Atlas (IeA) was developed to assist first-year nursing students with interpretation of laboratory-based prosected cadaveric material. It was designed, using pedagogically sound principles, as a student-centered resource accessible to students from a wide range of learning backgrounds. It consisted of a highly simplified interactive interface limited to essential anatomical structures and was intended for use in a blended learning situation. The IeA's nine modules mirrored the body systems covered in a Nursing Biosciences course, with each module comprising a maximum of 10 pages using the same template: an image displaying a cadaveric specimen and, in most cases, a corresponding anatomical model with navigation panes (menus) on one side. Cursor movement over the image or clicking the menu highlighted the structure with a transparent overlay and revealed a succinct functional description. The atlas was complemented by a multiple-choice database of nearly 1,000 questions using IeA images. Students' perceptions of usability and utility were measured by survey (n = 115; 57% of the class) revealing mean access of 2.3 times per week during the 12-week semester and a median time of three hours of use. Ratings for usability and utility were high, with means ranging between 4.24 and 4.54 (five-point Likert scale; 5 = strongly agree). Written responses told a similar story for both usability and utility. The role of providing basic computer-assisted learning support for a large first-year class is discussed in the context of current research into student-centered resources and blended learning in human anatomy.

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This research proposes an intelligent decision support system for acute lymphoblastic leukaemia diagnosis from microscopic blood images. A novel clustering algorithm with stimulating discriminant measures (SDM) of both within- and between-cluster scatter variances is proposed to produce robust segmentation of nucleus and cytoplasm of lymphocytes/lymphoblasts. Specifically, the proposed between-cluster evaluation is formulated based on the trade-off of several between-cluster measures of well-known feature extraction methods. The SDM measures are used in conjuction with Genetic Algorithm for clustering nucleus, cytoplasm, and background regions. Subsequently, a total of eighty features consisting of shape, texture, and colour information of the nucleus and cytoplasm sub-images are extracted. A number of classifiers (multi-layer perceptron, Support Vector Machine (SVM) and Dempster-Shafer ensemble) are employed for lymphocyte/lymphoblast classification. Evaluated with the ALL-IDB2 database, the proposed SDM-based clustering overcomes the shortcomings of Fuzzy C-means which focuses purely on within-cluster scatter variance. It also outperforms Linear Discriminant Analysis and Fuzzy Compactness and Separation for nucleus-cytoplasm separation. The overall system achieves superior recognition rates of 96.72% and 96.67% accuracies using bootstrapping and 10-fold cross validation with Dempster-Shafer and SVM, respectively. The results also compare favourably with those reported in the literature, indicating the usefulness of the proposed SDM-based clustering method.

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The influence of instructor support, family support and psychological capital (PsyCap) on the subjective well-being of postgraduate business students, including whether PsyCap mediates the proposed support – well-being relationship were examined in this study. It was further investigated whether family support moderates this proposed mediated relationship. Direct positive relationships between instructor support and well-being, and between PsyCap and well-being were found. It was also found that PsyCap mediates the instructor support – well-being relationship. Finally, it was found that family support moderates this mediated relationship in such a way that the relationship is stronger among students with lower levels of family support.

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We describe an experimental study testing the reuse of design knowledge as a method to support learning and use of parametric design in architecture.The use of parametric design systems and programming environments offer architects new opportunities, providing a powerful means to create geometries and allowing dynamic design exploration, but it can also impose substantial challenges.The proposition tested in this study is that the reuse of design knowledge can improve architects’ ability to use parametric modelling, and reduce the barriers to using programming in a design context.The paper explores and compares two approaches as a means of accessing and reusing existing design solutions: the reuse of abstract parametric ‘Design Patterns’ [1]; and secondly the reuse of parametric solutions from specific design cases (Case- Based Design).This paper outlines the principles and methods of ‘abstract’ versus ‘case-based’ approaches to reuse parametric solutions; and focuses on the results of their practical implementation through the statistical analysis of a comparative study involving 126 designers. In conclusion, it is proposed the outcomes from this study can be applied to inform the methodology for introducing parametric design in architecture and design disciplines.

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Accurate forecasting of wind power generation is quite an important as well as challenging task for the system operators and market participants due to its high uncertainty. It is essential to quantify uncertainties associated with wind power generation forecasts for their efficient application in optimal management of wind farms and integration into power systems. Prediction intervals (PIs) are well known statistical tools which are used to quantify the uncertainty related to forecasts by estimating the ranges of the future target variables. This paper investigates the application of a novel support vector machine based methodology to directly estimate the lower and upper bounds of the PIs without expensive computational burden and inaccurate assumptions about the distribution of the data. The efficiency of the method for uncertainty quantification is examined using monthly data from a wind farm in Australia. PIs for short term application are generated with a confidence level of 90%. Experimental results confirm the ability of the method in constructing reliable PIs without resorting to complex computational methods.

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PURPOSE: Although parent-implemented interventions for children with a speech-generating device (SGD) have been well researched, little is known about parents' or speech-language pathologists' (SLPs) views around parent training content. In this project, we aimed to identify areas that parents and SLPs consider should be included in training for families with a new SGD.

METHODS: Seven parents of children with an SGD and three SLPs who were new to the SGD field, participated in individual semi-structured interviews. Ten SLPs experienced in SGD practice took part in two focus groups. Data were analysed using grounded theory methods.

RESULTS: Participants identified the following areas suitable for inclusion in a family SGD training package: (a) content aimed at improving acceptance and uptake of the SGD, including technical guidance, customisation and reassurance around SGD misconceptions; (b) content around aided language development and (c) home practice strategies, including responsivity, aided language stimulation and managing children's motivation.

CONCLUSIONS: Participants identified diverse training targets, many of which are unexplored in parent-training research to date. Their recounted experiences illustrate the diversity of family capacity, knowledge and training priorities, and highlight the need for collaborative planning between families and SLPs at all stages of SGD training. Implications for Rehabilitation Training needs for families with a new speech generating device (SGD) are diverse, ranging from technology-specific competencies to broader areas, such as advocacy, teamwork and goal-setting skills. Each family with a new SGD will have a unique profile of training needs, determined by individual learning capacity, priorities, prior knowledge and experience, as well as their child's current communication skills and future support needs. Parents and speech-language pathologists (SLPs) may hold different priorities concerning family SGD training, necessitating ongoing team discussion.

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This study examined the impact of participating in the CollaborativeCare Skill Training Workshops on carers’ coping strategies, expressedemotion (EE), burden, distress, confidence in their loved one’scapacity to change, as well as the previously unexplored dimensionof accommodating and enabling of their loved one’s eatingdisorder behaviour. A non-experimental research design wasimplemented and 77 carers from Victoria, Australia participated inthe study and completed questionnaires at pre-and postinterventionand an 8-week follow-up. Significant reductionsoccurred in accommodation and enabling of some eating disorderbehaviours, as well as in carers’ maladaptive coping, EE, eatingdisorder-specific burden and psychological distress. Increasedconfidence that their loved one could change was also observed.These changes were maintained at a follow-up. Results suggestthat the workshop can be effective in decreasing carer use ofmaladaptive coping, carer distress and burden. Notably, it targetsand had contributed to reducing factors associated withmaintaining eating disorders such as accommodation and enablingof certain eating behaviours and high levels of EE. Modification tothe content of the workshop may be required to improve carers’adaptive coping and reduce certain behaviours whichaccommodate and enable the eating disorder.

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A pilot program for Aboriginal people with diabetes on Eyre Peninsula, South Australia, aimed to test the acceptability and impact of using the Flinders model of self-management care planing to improve patient self-management. A community development approach was used to conduct a twelve-month demonstration project. Aboriginal health workers (AHWs) conducted patient-centred, self-management assessment and care planning. Impacts were measured by patient-completed diabetes self-management assessment tool, goal achievement, quality of life and clinical measures at baseline and 12 months. Impact and acceptability were also assessed by semi-structured interviews and focus groups of AHWs. Sixty Aboriginal people with type 2 diabetes stated their main problems as family and social dysfunction, access to services, nutrition and exercise. Problems improved by 12% and goals by 26%, while quality of life scores showed no significant change. Self-management scores improved in five of six domains. Mean HbA1c reduced from 8.74-8.09 and mean blood pressure was unchanged. AHWs found the process acceptable and appropriate for them and their patients. It was concluded that a diabetes self-management program provided by AHWs is acceptable, improves self-management and is seen to be useful by Aboriginal communities. Barriers include lack of preventative health services, social problems and time pressure on staff. Enablers include community concern regarding the prevalence and mortality associated with diabetes.

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Chinese Medicine (CM) has become increasingly demanding globally. Recent World Health Organisation traditional and complementary medicine strategy of integrating CM to Western Medicine (WM) indicates that it is crucial that CM developments have strong literature, scientific, and evidence-based medical approval and support. To achieve this, there is a need to form a synthesis foundation or platform for future studies. This chapter serves to discover this synthesis that is suitable for CM by discussing the basics of inquiring and Knowledge Management (KM) systems. It suggests that CM should follow a combination of Hegelian and Kantian inquiring systems with the support of Singerian and Leibnizian inquiring systems and KM features. This proposed synthesis is one of the first, if not the first study to apply Churchman's inquiring systems into the context of CM and differentiate them from WM.

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Due to the prevalence of unlabeled data, semi-supervised learning has drawn significant attention and has been found applicable in many real-world applications. In this paper, we present the so-called Budgeted Semi-supervised Sup-port Vector Machine (BS3VM), a method that leverages the excellent generalization capacity of kernel-based method with the adjacent and distributive information carried in a spectral graph for semi-supervised learning purpose. The fact that the optimization problem of BS3VM can be solved directly in the primal form makes it fast and efficient in memory usage. We validate the proposed method on several benchmark datasets to demonstrate its accuracy and efficiency. The experimental results show that BS3VM can scale up efficiently to the large-scale datasets where it yields a comparable classification accuracy while simultaneously achieving a significant computational speed-up compared with the baselines.