725 resultados para voluntary programs


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Practice based learning in Northern Ireland is a core element of social work education and comprising 50% of the degree programme for undergraduate and postgraduate students. This article presents evidence about the perceptions of practice learning from voluntary sector/non-government organisation (NGO) placement providers and final year social work students on social work degree programmes in Northern Ireland in 2011. It draws on data from 121 respondents from189 final year students and focus group interviews with voluntary sector providers offering 16% (85) of the total placements available to students. The agencies who participated in the research study provide a total of 55 PLOs to social work students, and are therefore fairly representative in terms of voluntary sector (NGO) provision. The article locates these data in the context of practice learning pedagogy and the changes introduced by the Regional Strategy for Practice Learning Provision in Northern Ireland 2010–2015. Several themes emerged including; induction, support and guidance, practice educator/student relationship, professional identity and confidence in risk assessment and decision-making. Social work educators, placement providers and employers must be cognisant of newly qualified social workers’ needs in terms of consolidating knowledge within the formative stages of their professional development.

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Although Answer Set Programming (ASP) is a powerful framework for declarative problem solving, it cannot in an intuitive way handle situations in which some rules are uncertain, or in which it is more important to satisfy some constraints than others. Possibilistic ASP (PASP) is a natural extension of ASP in which certainty weights are associated with each rule. In this paper we contrast two different views on interpreting the weights attached to rules. Under the first view, weights reflect the certainty with which we can conclude the head of a rule when its body is satisfied. Under the second view, weights reflect the certainty that a given rule restricts the considered epistemic states of an agent in a valid way, i.e. it is the certainty that the rule itself is correct. The first view gives rise to a set of weighted answer sets, whereas the second view gives rise to a weighted set of classical answer sets.

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Answer set programming is a form of declarative programming that has proven very successful in succinctly formulating and solving complex problems. Although mechanisms for representing and reasoning with the combined answer set programs of multiple agents have already been proposed, the actual gain in expressivity when adding communication has not been thoroughly studied. We show that allowing simple programs to talk to each other results in the same expressivity as adding negation-as-failure. Furthermore, we show that the ability to focus on one program in a network of simple programs results in the same expressivity as adding disjunction in the head of the rules.

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Many problems in artificial intelligence can be encoded as answer set programs (ASP) in which some rules are uncertain. ASP programs with incorrect rules may have erroneous conclusions, but due to the non-monotonic nature of ASP, omitting a correct rule may also lead to errors. To derive the most certain conclusions from an uncertain ASP program, we thus need to consider all situations in which some, none, or all of the least certain rules are omitted. This corresponds to treating some rules as optional and reasoning about which conclusions remain valid regardless of the inclusion of these optional rules. While a version of possibilistic ASP (PASP) based on this view has recently been introduced, no implementation is currently available. In this paper we propose a simulation of the main reasoning tasks in PASP using (disjunctive) ASP programs, allowing us to take advantage of state-of-the-art ASP solvers. Furthermore, we identify how several interesting AI problems can be naturally seen as special cases of the considered reasoning tasks, including cautious abductive reasoning and conformant planning. As such, the proposed simulation enables us to solve instances of the latter problem types that are more general than what current solvers can handle.

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PURPOSE. To explore factors potentially influencing the success or failure of rural Chinese hospitals in increasing cataract surgical output and quality. METHODS. Focus groups (FGs, n = 10) were conducted with hospital administrators, doctors, and nurses at 28 county hospitals in Guangdong Province. Discussions explored respondents' views on increasing surgical volume and quality and improving patient satisfaction. Respondents numerically ranked possible strategies to increase surgical volume and quality and patient satisfaction. FG transcripts were independently coded by two reviewers utilizing the constant comparative method following the grounded theory approach, and numerical responses were scored and ranked. RESULTS. Ten FGs and 77 ranking questionnaires were completed by 33 administrators, 23 doctors, and 21 nurses. Kappa values for the two coders were greater than 0.7 for all three groups. All groups identified a critical need for enhanced management training for hospital directors. Doctors and nurses suggested reducing surgical fees to enhance uptake, although administrators were resistant to this. Although doctors saw the need to improve equipment, administrators felt current material conditions were adequate. Respondents agreed that patient satisfaction was generally high, and did not view increasing patient satisfaction as a priority. CONCLUSIONS. Our findings highlight agreements and disagreements among the three stakeholder groups about improving surgical output and quality, which can inform strategies to improve cataract programs in rural China. Respondents' beliefs about high patient satisfaction are not in accord with other studies in the area, highlighting a potential area for intervention. © 2013 The Association for Research in Vision and Ophthalmology, Inc.

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Current scientific evidence supports the recommendation to initiate or continue the practice of physical exercise in healthy pregnant women. Group exercise programs have positive effects in improving health and well-being, as well as social support. In order to understand the scientific evidence in this field, and the outcomes in maternal health, it has generated wide interest in exploring the studies carried out with more relevant group exercise programs. The aim of this systematic review was to evaluate the available evidence on the effectiveness of group exercise programs in improving women’s and newborns health outcomes during pregnancy. Three databases were used to conduct literature searches and strict inclusion and exclusion criteria were employed. Seventeen studies were selected for analysis. All studies were randomized control trials conducted with pregnant women that evaluated the effect of group exercise programs on the health outcomes of mother and newborn. Most studies followed a supervised structured exercise program including a main aerobic part, resistance training, pelvic floor training and stretching and relaxation sections. The significant effects of the programs are related with improved maternal perception of health status, lower maternal weight gain, improved levels of maternal glucose tolerance, improved aerobic fitness and muscular strength, lower frequency of urinary incontinence, improved sick leave due to lumbopelvic pain, fewer cesarean and instrumental deliveries, higher newborn Apgar score and faster postpartum recovery. Exercise and health professionals should advise pregnant women that aerobic group exercise during pregnancy improves a wide range of health outcomes for the women and newborn

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A previous paper showed that young children performed better when working as individuals rather than in pairs on a drill and practice program. This paper reports an analysis of behaviour and talk for individuals and single sex pairs using a computer-based drill and practice activity to explain differences in performance. Results indicated that individuals were more likely to be task-focused and to complete tasks successfully than children working in pairs. Differences were found in off-task activity, behaviours and type of talk. Grouping and verbal interaction are discussed in relation to the type of task/program that children are asked to undertake, and how both task and peer presence may constrain the child's task focus and performance when reinforcing pre-existing knowledge.

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Power systems have been suffering huge changes mainly due to the substantial increase of distributed generation and to the operation in competitive environments. Virtual power players can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Resource management gains an increasing relevance in this competitive context, while demand side active role provides managers with increased demand elasticity. This makes demand response use more interesting and flexible, giving rise to a wide range of new opportunities.This paper proposes a methodology for managing demand response programs in the scope of virtual power players. The proposed method is based on the calculation of locational marginal prices (LMP). The evaluation of the impact of using demand response specific programs on the LMP value supports the manager decision concerning demand response use. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus network with intensive use of distributed generation.

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The design and development of simulation models and tools for Demand Response (DR) programs are becoming more and more important for adequately taking the maximum advantages of DR programs use. Moreover, a more active consumers’ participation in DR programs can help improving the system reliability and decrease or defer the required investments. DemSi, a DR simulator, designed and implemented by the authors of this paper, allows studying DR actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. DemSi considers the players involved in DR actions, and the results can be analyzed from each specific player point of view.

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In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

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The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.