886 resultados para Localization real-world challenges
Resumo:
Studies of experimental grassland communities have demonstrated that plant diversity can stabilize productivity through species asynchrony, in which decreases in the biomass of some species are compensated for by increases in others. However, it remains unknown whether these findings are relevant to natural ecosystems, especially those for which species diversity is threatened by anthropogenic global change. Here we analyse diversity-stability relationships from 41 grasslands on five continents and examine how these relationships are affected by chronic fertilization, one of the strongest drivers of species loss globally. Unmanipulated communities with more species had greater species asynchrony, resulting in more stable biomass production, generalizing a result from biodiversity experiments to real-world grasslands. However, fertilization weakened the positive effect of diversity on stability. Contrary to expectations, this was not due to species loss after eutrophication but rather to an increase in the temporal variation of productivity in combination with a decrease in species asynchrony in diverse communities. Our results demonstrate separate and synergistic effects of diversity and eutrophication on stability, emphasizing the need to understand how drivers of global change interactively affect the reliable provisioning of ecosystem services in real-world systems.
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Addressing the Crew Scheduling Problem (CSP) in transportation systems can be too complex to capture all details. The designed models usually ignore or simplify features which are difficult to formulate. This paper proposes an alternative formulation using a Mixed Integer Programming (MIP) approach to the problem. The optimisation model integrates the two phases of pairing generation and pairing optimisation by simultaneously sequencing trips into feasible duties and minimising total elapsed time of any duty. Crew scheduling constraints in which the crew have to return to their home depot at the end of the shift are included in the model. The flexibility of this model comes in the inclusion of the time interval of relief opportunities, allowing the crew to be relieved during a finite time interval. This will enhance the robustness of the schedule and provide a better representation of real-world conditions.
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Healthy governance systems are key to delivering sound environmental management outcomes from global to local scales. There are, however, surprisingly few risk assessment methods that can pinpoint those domains and sub-domains within governance systems that are most likely to influence good environmental outcomes at any particular scale, or those if absent or dysfunctional, most likely to prevent effective environmental management. This paper proposes a new risk assessment method for analysing governance systems. This method is then tested through its preliminary application to a significant real-world context: governance as it relates to the health of Australia's Great Barrier Reef (GBR). The GBR exists at a supra-regional scale along most of the north eastern coast of Australia. Brodie et al (2012 Mar. Pollut. Bull. 65 81-100) have recently reviewed the state and trend of the health of the GBR, finding that overall trends remain of significant concern. At the same time, official international concern over the governance of the reef has recently been signalled globally by the International Union for the Conservation of Nature (IUCN). These environmental and political contexts make the GBR an ideal candidate for use in testing and reviewing the application of improved tools for governance risk assessment. © 2013 IOP Publishing Ltd.
Resumo:
Understanding the key factors that influence the evidentiary basis for practice and using skills in retrieving evidence that informs practice change are essential to the development of a health professional's career, regardless of the discipline. This chapter focuses on the key links between research and practice, particularly how health professionals use various sources of evidence and new knowledge to inform and improve the effectiveness of their practice in order to benefit the health of clients. Evidence-based practice and research utilisation are two major global research/practice initiatives that form the basis for this chapter. Examples that illustrate the real-world application of these initiatives are included in the Research Alive and Case Study sections. How practice change can be facilitated within health organisations is also briefly introduced.
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This study explores people's risk taking behaviour after having suffered large real-world losses following a natural disaster. Using the margins of the 2011 Australian floods (Brisbane) as a natural experimental setting, we find that homeowners who were victims of the floods and face large losses in property values are 50% more likely to opt for a risky gamble -- a scratch card giving a small chance of a large gain ($500,000) -- than for a sure amount of comparable value ($10). This finding is consistent with prospect theory predictions regarding the adoption of a risk-seeking attitude after a loss.
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This is an exploratory study into the effective use of embedding custom made audiovisual case studies (AVCS) in enhancing the student’s learning experience. This paper describes a project that used AVCS for a large divergent cohort of undergraduate students, enrolled in an International Business course. The study makes a number of key contributions to advancing learning and teaching within the discipline. AVCS provide first hand reporting of the case material, where the students have the ability to improve their understanding from both verbal and nonverbal cues. The paper demonstrates how AVCS can be embedded in a student-centred teaching approach to capture the students’ interest and to enhance a deep approach to learning by providing real-world authentic experience.
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Real world business process models may consist of hundreds of elements and have sophisticated structure. Although there are tasks where such models are valuable and appreciated, in general complexity has a negative influence on model comprehension and analysis. Thus, means for managing the complexity of process models are needed. One approach is abstraction of business process models-creation of a process model which preserves the main features of the initial elaborate process model, but leaves out insignificant details. In this paper we study the structural aspects of process model abstraction and introduce an abstraction approach based on process structure trees (PST). The developed approach assures that the abstracted process model preserves the ordering constraints of the initial model. It surpasses pattern-based process model abstraction approaches, allowing to handle graph-structured process models of arbitrary structure. We also provide an evaluation of the proposed approach.
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Companies use business process models to represent their working procedures in order to deploy services to markets, to analyze them, and to improve upon them. Competitive markets necessitate complex procedures, which lead to large process specifications with sophisticated structures. Real world process models can often incorporate hundreds of modeling constructs. While a large degree of detail complicates the comprehension of the processes, it is essential to many analysis tasks. This paper presents a technique to abstract, i.e., to simplify process models. Given a detailed model, we introduce abstraction rules which generalize process fragments in order to bring the model to a higher abstraction level. The approach is suited for the abstraction of large process specifications in order to aid model comprehension as well as decomposing problems of process model analysis. The work is based on process structure trees that have recently been introduced to the field of business process management.
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Business processes are an important instrument for understanding and improving how companies provide goods and services to customers. Therefore, many companies have documented their business processes well, often in the Event-driven Process Chains (EPC). Unfortunately, in many cases the resulting EPCs are rather complex, so that the overall process logic is hidden in low level process details. This paper proposes abstraction mechanisms for process models that aim to reduce their complexity, while keeping the overall process structure. We assume that functions are marked with efforts and splits are marked with probabilities. This information is used to separate important process parts from less important ones. Real world process models are used to validate the approach.
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Behavioral models capture operational principles of real-world or designed systems. Formally, each behavioral model defines the state space of a system, i.e., its states and the principles of state transitions. Such a model is the basis for analysis of the system’s properties. In practice, state spaces of systems are immense, which results in huge computational complexity for their analysis. Behavioral models are typically described as executable graphs, whose execution semantics encodes a state space. The structure theory of behavioral models studies the relations between the structure of a model and the properties of its state space. In this article, we use the connectivity property of graphs to achieve an efficient and extensive discovery of the compositional structure of behavioral models; behavioral models get stepwise decomposed into components with clear structural characteristics and inter-component relations. At each decomposition step, the discovered compositional structure of a model is used for reasoning on properties of the whole state space of the system. The approach is exemplified by means of a concrete behavioral model and verification criterion. That is, we analyze workflow nets, a well-established tool for modeling behavior of distributed systems, with respect to the soundness property, a basic correctness property of workflow nets. Stepwise verification allows the detection of violations of the soundness property by inspecting small portions of a model, thereby considerably reducing the amount of work to be done to perform soundness checks. Besides formal results, we also report on findings from applying our approach to an industry model collection.
Resumo:
Businesses document their operational processes as process models. The common practice is to represent process models as directed graphs. The nodes of a process graph represent activities and directed edges constitute activity ordering constraints. A flexible process graph modeling approach proposes to generalize process graph structure to a hypergraph. Obtained process structure aims at formalization of ad-hoc process control flow. In this paper we discuss aspects relevant to concurrent execution of process activities in a collaborative manner organized as a flexible process graph. We provide a real world flexible process scenario to illustrate the approach.
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Millions flock to their computers, consoles, mobile phones, tablets, and social networks each day to play World of Warcraft, Farmville, Scrabble, and countless other games, generating billions in sales each year. The careful and skillful construction of these games is built on decades of research into human motivation and psychology: A well-designed game goes right to the motivational heart of the human psyche. In For the Win, authors Kevin Werbach and Dan Hunter argue persuasively that gamemakers need not be the only ones benefiting from game design. Werbach and Hunter are lawyers and World of Warcraft players who created the world’s first course on gamification at the Wharton School of the University of Pennsylvania. In their book, they reveal how game thinking—addressing problems like a game designer—can motivate employees and customers and create engaging experiences that can transform your business. For the Win reveals how a wide range of companies are successfully using game thinking. It also offers an explanation of when gamifying makes the most sense and a 6-step framework for using games for marketing, productivity enhancement, innovation, employee motivation, customer engagement, and more. In this informative guide, Werbach and Hunter reveal how game thinking can yield winning solutions to real-world business problems. Let the games begin!
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Clinical experience, or experience in the ‘real world’ of practice, is a fundamental component of many health professional courses. It often involves students undertaking practical experience in clinical workplace settings, typically referred to as clinical placements, under the supervision of health professionals. Broadly speaking, the role of clinical supervisors, or teachers, is aimed at assisting students to integrate the theoretical and skills based components of the curriculum within the context of patient/client care (Erstzen et al 2009). Clinical experience also provides students with the opportunity to assimilate the attitudes, values and skills which they require to become appropriately skilled professionals in the environments in which they will eventually practise. However, clinical settings are particularly challenging learning environments for students. Unlike classroom learning, students in the clinical setting frequently find themselves involved in unplanned and often complex activities with patients and other health care providers, being supervised by a variety of clinical staff who have very different methods and styles of teaching, and negotiating bureaucratic or hierarchical structures in busy clinical workplaces where they may only be spending a limited amount of time. Kilminster et al (2007) also draw attention to tensions that may exist between the learning needs of students and the provision of quality care or need to prevent harm to the patient (e.g. Elkind et al 2007). All of these factors complicate the realisation of clinical education goals and underscore the need for effective clinical teaching practices that maximise student learning in clinical environments. This report provides a summary of work that has been achieved in relation to ALTC projects and fellowships associated with clinical teaching, and a review of scholarly publications relevant to this field. The report also makes recommendations based on issues identified and/or where further work is indicated. The projects and fellowships reviewed cover a range of discipline areas including Biology, Paramedic Practice, Clinical Exercise Physiology, Occupational Therapy, Speech Pathology, Physiotherapy, Pharmacy, Nursing and Veterinary Science. The main areas of focus cover issues related to curriculum, particularly in relation to industry expectations of ‘work-ready’ graduates and the implications for theoretical and practical, or clinical preparation; development of competency assessment tools that are nationally applicable across discipline-specific courses; and improvement of clinical learning through strategies targeting the clinical learning environment, building the teaching capacity of clinical supervisors and/or enhancing the clinical learning/teaching process.
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Validation is an important issue in the development and application of Bayesian Belief Network (BBN) models, especially when the outcome of the model cannot be directly observed. Despite this, few frameworks for validating BBNs have been proposed and fewer have been applied to substantive real-world problems. In this paper we adopt the approach by Pitchforth and Mengersen (2013), which includes nine validation tests that each focus on the structure, discretisation, parameterisation and behaviour of the BBNs included in the case study. We describe the process and result of implementing a validation framework on a model of a real airport terminal system with particular reference to its effectiveness in producing a valid model that can be used and understood by operational decision makers. In applying the proposed validation framework we demonstrate the overall validity of the Inbound Passenger Facilitation Model as well as the effectiveness of the validity framework itself.
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The Internet Corporation for Assigned Names and Numbers (ICANN) is an institution besieged. It has endeavored to be democratic but its attempts to do so have been disastrous. The typical explanation for this is that the problem is with ICANN: it fails to meet its democratic obligations. My view is that the problem is with our understanding of "democracy." Democracy is an empty concept that fails to describe few, if any, of our genuine political commitments. In the real world, the failings inherent in "democracy" have been papered over by some unusual characteristics of the physical political process. However, in online trans-national institutions like ICANN, democracy is exposed as a poor substitute for a number of other conceptions of our political commitments. This Article seeks to articulate these political commitments and to explain why democracy and ICANN are such a poor mix. It begins by charting the rise of ICANN and its attempts to be democratic. It then explains why democracy is an empty shell of a concept. It then explores some features of democracy and ICANN, explaining why the online world exposes limitations in implications of democracy such as the nature of the demos, the idea of constituencies, direct democracy, voting, and the like. It concludes that ICANN's example demonstrates that democracy is in fact anything but a coherent general theory of political action. We need to consider, then, whether we should continue to berate ICANN for its undemocratic actions.