409 resultados para decision tree


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There is an increasing awareness of sustainability and climate change and its impact on infrastructure and engineering asset management in design, construction, and operations. Sustainability rating tools have been proposed and/or developed that provide ratings of infrastructure projects in differing phases of their life cycle on sustainability. This paper provides an overview of decision support systems using sustainability rating framework that can be used to prioritize or select tasks and activities within projects to enhance levels of sustainability outcomes. These systems can also be used to prioritize projects within an organization to optimize sustainability outcomes within an allocated budget.

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Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

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Decision-making is such an integral aspect in health care routine that the ability to make the right decisions at crucial moments can lead to patient health improvements. Evidence-based practice, the paradigm used to make those informed decisions, relies on the use of current best evidence from systematic research such as randomized controlled trials. Limitations of the outcomes from randomized controlled trials (RCT), such as “quantity” and “quality” of evidence generated, has lowered healthcare professionals’ confidence in using EBP. An alternate paradigm of Practice-Based Evidence has evolved with the key being evidence drawn from practice settings. Through the use of health information technology, electronic health records (EHR) capture relevant clinical practice “evidence”. A data-driven approach is proposed to capitalize on the benefits of EHR. The issues of data privacy, security and integrity are diminished by an information accountability concept. Data warehouse architecture completes the data-driven approach by integrating health data from multi-source systems, unique within the healthcare environment.

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Study/Objective This paper describes a program of research examining emergency messaging during the response and early recovery phases of natural disasters. The objective of this suite of studies is to develop message construction frameworks and channels that maximise community compliance with instructional messaging. The research has adopted a multi-hazard approach and considers the impact of formal emergency messages, as well as informal messages (e.g., social media posts), on community compliance. Background In recent years, media reports have consistently demonstrated highly variable community compliance to instructional messaging during natural disasters. Footage of individuals watching a tsunami approaching from the beach or being over-run by floodwaters are disturbing and indicate the need for a clearer understanding of decision making under stress. This project’s multi-hazard approach considers the time lag between knowledge of the event and desired action, as well as how factors such as message fatigue, message ambiguity, and the interplay of messaging from multiple media sources are likely to play a role in an individual’s compliance with an emergency instruction. Methods To examine effective messaging strategy, we conduct a critical analysis of the literature to develop a framework for community consultation and design experiments to test the potential for compliance improvement. Results Preliminary results indicate that there is, as yet, little published evidence on which to base decisions about emergency instructional messages to threatened communities. Conclusion The research described here will contribute improvements in emergency instructional message compliance by generating an evidence-based framework that takes into account behavioural compliance theory, the psychology of decision making under stress, and multiple channels of communication including social media.

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This paper is based on a study examining the impact of young people’s backgrounds and educational experiences on career choice capability with the aim of informing education policy. A total of 706 students from secondary schools (Years 9-12) in New South Wales, Australia took part in an online survey. This paper focuses on the differences found between groups on the basis of their educational experiences. Participants who were uncertain of their future career plans were more likely to attend non-selective, non-metropolitan schools and were more likely to hold negative attitudes towards school. Career ‘uncertain’ students were also less likely to be satisfied with the elective subjects offered at their school and reported less access to career education sessions. It is concluded that timely career information and guidance should be provided to students and their families in order to allow them to more meaningfully make use of the resources and opportunities available to them with a view toward converting these into real world benefits.

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The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.

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A wide range of decision-making models have been offered to assist in making ethical decisions in the workplace. Those that are based on normative moral frameworks typically include elements of traditional moral philosophy such as consequentialist and/or deontological␣ethics. This paper suggests an alternative model drawing on Jean-Paul Sartre’s existentialism. Accordingly, the model focuses on making decisions in full awareness of one’s freedom and responsibility. The steps of the model are intended to encourage reflection of one’s projects and one’s situation and the possibility of refusing the expectations of others. A case study involving affirmative action in South Africa is used to demonstrate the workings of the model and a number of strengths and weaknesses are identified. Despite several weaknesses that can be raised regarding existential ethics, the model’s success lies in the way that it reframes ethical dilemmas in terms of individual freedom and responsibility, and in its acceptance and analysis of subjective experiences and personal situations

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This chapter examines the challenges and opportunities associated with planning for competitive, smart and healthy cities. The chapter is based on the assumptions that a healthy city is an important prerequisite for a competitive city and a fundamental outcome of smart cities. Thus, it is preeminent to understand the planning decision support system based on local determinants of health, economic and social factors. One of the major decision support systems is e-health and this chapter will focus on the role of e-health planning, by utilising web-based geographic decision support systems. The proposed novel decision support system would provide a powerful and effective platform for stakeholders to access online information for a better decision-making while empowering community participation. The chapter also highlights the need for a comprehensive conceptual framework to guide the decision process of planning for healthy cities in association with opportunities and limitations. In summary, this chapter provides the critical insights of using information science-based framework and suggest online decision support methods, as part of a broader e-health approach for creating a healthy, competitive and smart city.

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The aim of this thesis is to examine how risk tolerance and risk perception, two important but often misunderstood constructs, jointly influence client investment decisions in a financial advice context. By distinguishing the roles of these two risk constructs in client decision-making, in this thesis a new direction in studying financial/investment risks is provided while practice and regulation in the financial services industry is potentially informed. Based on the literature relating to risks and individual decision-making, a theoretical framework is developed and relevant hypotheses are tested in two studies with financial adviser clients in Australia. Results reveal that financial risk tolerance influences asset allocation both directly and indirectly through risk perception. The intervening role of risk perception suggests that risk tolerance affects how clients perceive the riskiness of an investment product which influences client decision-making.

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Monte-Carlo Tree Search (MCTS) is a heuristic to search in large trees. We apply it to argumentative puzzles where MCTS pursues the best argumentation with respect to a set of arguments to be argued. To make our ideas as widely applicable as possible, we integrate MCTS to an abstract setting for argumentation where the content of arguments is left unspecified. Experimental results show the pertinence of this integration for learning argumentations by comparing it with a basic reinforcement learning.

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This paper details the design and performance assessment of a unique collision avoidance decision and control strategy for autonomous vision-based See and Avoid systems. The general approach revolves around re-positioning a collision object in the image using image-based visual servoing, without estimating range or time to collision. The decision strategy thus involves determining where to move the collision object, to induce a safe avoidance manuever, and when to cease the avoidance behaviour. These tasks are accomplished by exploiting human navigation models, spiral motion properties, expected image feature uncertainty and the rules of the air. The result is a simple threshold based system that can be tuned and statistically evaluated by extending performance assessment techniques derived for alerting systems. Our results demonstrate how autonomous vision-only See and Avoid systems may be designed under realistic problem constraints, and then evaluated in a manner consistent to aviation expectations.

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Although species of Syzygium are abundant components of the rainforests in Queensland and New South Wales, little is known about the anatomy of the Australian taxa. Here we describe the foliar anatomy and micromorphology of Syzygium floribundum (syn: Waterhousea floribunda) using standard protocols for scanning electron microscopy (SEM) and light microscopy. Syzygium floribundum possesses dorsiventral leaves with cyclo-staurocytic stomata, single epidermis, internal phloem, rhombus-shaped calcium oxalate crystals and complex-open midrib. In general, leaf anatomical and micromorphological characters are common with some species of the tribe Syzygieae. However, this particular combination of leaf characters has not been reported in a species of the genus. The anatomy of the species is typical of mesophytic taxa.

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This is an ongoing research investigating the use of health information technologies (HIT) to improve clinical decision-making processes. Effective and timely clinical decision-making can lead to positive improvements in patient’s health outcome...

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The cognitive benefits of biophilia have been studied quite extensively, dating as far back as the 1980s, while studies into economic benefits are still in their infancy. Recent research has attempted to quantify a number of economic returns on biophilic elements; however knowledge in this field is still ad hoc and highly variable. Many studies acknowledge difficulties in discerning information such as certain social and aesthetic benefits. While conceptual understanding of the physiological and psychological effects of exposure to nature is widely recognised and understood, this has not yet been systematically translated into monetary terms. It is clear from the literature that further research is needed to both obtain data on the economics of biophilic urbanism, and to create the business case for biophilic urbanism. With this in mind, this paper will briefly highlight biophilic urbanism referencing previous work in the field. It will then explore a number of emergent gaps in the measurable economic understanding of these elements and suggest opportunities for engaging decision makers in the business case for biophilic urbanism. The paper concludes with recommendations for moving forward through targeted research and economic analysis.

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This chapter explains how customers make purchase decisions and how these decisions are influenced not only by the service marketer but also by the customers own emotions. While decision-making is described from the perspective of purchasing services rather than purchasing goods, we challenge the traditional notion that customers make informed, rational and well-thought-out decisions. Rather customers are often driven by subjective feelings such as emotions. We present evidence of how these emotions influence the behavior of customers, their attitudes and evaluation of the service, as well as final decision-making processes.