824 resultados para Empirical Approach


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Objectives: This methodological paper reports on the development and validation of a work sampling instrument and data collection processes to conduct a national study of nurse practitioners’ work patterns. ---------- Design: Published work sampling instruments provided the basis for development and validation of a tool for use in a national study of nurse practitioner work activities across diverse contextual and clinical service models. Steps taken in the approach included design of a nurse practitioner-specific data collection tool and development of an innovative web-based program to train and establish inter rater reliability of a team of data collectors who were geographically dispersed across metropolitan, rural and remote health care settings. ---------- Setting: The study is part of a large funded study into nurse practitioner service. The Australian Nurse Practitioner Study is a national study phased over three years and was designed to provide essential information for Australian health service planners, regulators and consumer groups on the profile, process and outcome of nurse practitioner service. ---------- Results: The outcome if this phase of the study is empirically tested instruments, process and training materials for use in an international context by investigators interested in conducting a national study of nurse practitioner work practices. ---------- Conclusion: Development and preparation of a new approach to describing nurse practitioner practices using work sampling methods provides the groundwork for international collaboration in evaluation of nurse practitioner service.

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Regional safety program managers face a daunting challenge in the attempt to reduce deaths, injuries, and economic losses that result from motor vehicle crashes. This difficult mission is complicated by the combination of a large perceived need, small budget, and uncertainty about how effective each proposed countermeasure would be if implemented. A manager can turn to the research record for insight, but the measured effect of a single countermeasure often varies widely from study to study and across jurisdictions. The challenge of converting widespread and conflicting research results into a regionally meaningful conclusion can be addressed by incorporating "subjective" information into a Bayesian analysis framework. Engineering evaluations of crashes provide the subjective input on countermeasure effectiveness in the proposed Bayesian analysis framework. Empirical Bayes approaches are widely used in before-and-after studies and "hot-spot" identification; however, in these cases, the prior information was typically obtained from the data (empirically), not subjective sources. The power and advantages of Bayesian methods for assessing countermeasure effectiveness are presented. Also, an engineering evaluation approach developed at the Georgia Institute of Technology is described. Results are presented from an experiment conducted to assess the repeatability and objectivity of subjective engineering evaluations. In particular, the focus is on the importance, methodology, and feasibility of the subjective engineering evaluation for assessing countermeasures.

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A collaborative approach to home care (HC) delivery for older clients has taken centre stage (Nies, 2006). In Finland, public home help and home health care services have been combined to form the home care unit, whose goal is to provide a collaborative approach to care delivery through cooperation and sharing of responsibilities. In this model, the general practitioner (GP), home care nurses (HCN) and home help workers (HHW) care for shared clients. GPs and HCNs provide health care, such as monitoring of clients’ health status, and HHWs assist with personal care tasks such as dressing, washing and meal preparation. As the needs of older clients are multiple, collaboration is needed as one professional group cannot take sole responsibility (Nies, 2006). This paper reports on a study undertaken to examine home care unit care providers’ perspectives of the collaborative approach to HC delivery for older clients.

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This paper suggests an approach for finding an appropriate combination of various parameters for extracting texture features (e.g. choice of spectral band for extracting texture feature, size of the moving window, quantization level of the image, and choice of texture feature etc.) to be used in the classification process. Gray level co-occurrence matrix (GLCM) method has been used for extracting texture from remotely sensed satellite image. Results of the classification of an Indian urban environment using spatial property (texture), derived from spectral and multi-resolution wavelet decomposed images have also been reported. A multivariate data analysis technique called ‘conjoint analysis’ has been used in the study to analyze the relative importance of these parameters. Results indicate that the choice of texture feature and window size have higher relative importance in the classification process than quantization level or the choice of image band for extracting texture feature. In case of texture features derived using wavelet decomposed image, the parameter ‘decomposition level’ has almost equal relative importance as the size of moving window and the decomposition of images up to level one is sufficient and there is no need to go for further decomposition. It was also observed that the classification incorporating texture features improves the overall classification accuracy in a statistically significant manner in comparison to pure spectral classification.

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Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites

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This paper addresses the problem of constructing consolidated business process models out of collections of process models that share common fragments. The paper considers the construction of unions of multiple models (called merged models) as well as intersections (called digests). Merged models are intended for analysts who wish to create a model that subsumes a collection of process models - typically representing variants of the same underlying process - with the aim of replacing the variants with the merged model. Digests, on the other hand, are intended for analysts who wish to identify the most recurring fragments across a collection of process models, so that they can focus their efforts on optimizing these fragments. The paper presents an algorithm for computing merged models and an algorithm for extracting digests from a merged model. The merging and digest extraction algorithms have been implemented and tested against collections of process models taken from multiple application domains. The tests show that the merging algorithm produces compact models and scales up to process models containing hundreds of nodes. Furthermore, a case study conducted in a large insurance company has demonstrated the usefulness of the merging and digest extraction operators in a practical setting.

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In this paper, we present a microphone array beamforming approach to blind speech separation. Unlike previous beamforming approaches, our system does not require a-priori knowledge of the microphone placement and speaker location, making the system directly comparable other blind source separation methods which require no prior knowledge of recording conditions. Microphone location is automatically estimated using an assumed noise field model, and speaker locations are estimated using cross correlation based methods. The system is evaluated on the data provided for the PASCAL Speech Separation Challenge 2 (SSC2), achieving a word error rate of 58% on the evaluation set.

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This paper proposes a simple variation of the Allingham and Sandmo (1972) construct and integrates it to a dynamic general equilibrium framework with heterogeneous agents. We study an overlapping generations framework i n which agents must initially decide whether to evade taxes or not. In the event they decide to evade, they then have to decide the extent of income or wealth they wish to under-report. We find that in comparison with the basic approach, the ‘evade or not’ choice drastically reduced the extent of evasion in the economy. This outcome is the result of an anomaly intrinsic to the basic Allingham and Sandmo version of the model, which makes the evade-or-not extension a more suitable approach to modelling the issue. We also find that the basic model, and the model with and ‘evade-or-not’ choice have strikingly different political economy implications, , which suggest fruitful avenues of empirical research.

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Station track allocation is the critical component in the overall railway timetabling. Because of its intrinsic complexity and lack of modeling on station track layouts and train movement within station, analytical approach to attain optimal solution is not feasible. This study investigates the possibilities of applying a heuristic approach and identifies possible difficulties in practice. It is the first and important step to resolve one of the burning issues in the mainline railway operation in China.

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With the recent regulatory reforms in a number of countries, railways resources are no longer managed by a single party but are distributed among different stakeholders. To facilitate the operation of train services, a train service provider (SP) has to negotiate with the infrastructure provider (IP) for a train schedule and the associated track access charge. This paper models the SP and IP as software agents and the negotiation as a prioritized fuzzy constraint satisfaction (PFCS) problem. Computer simulations have been conducted to demonstrate the effects on the train schedule when the SP has different optimization criteria. The results show that by assigning different priorities on the fuzzy constraints, agents can represent SPs with different operational objectives.

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The use of appropriate financial incentives within construction projects can contribute to strong alignment of project stakeholder motivation with project goals. However, effective incentive system design can be a challenging task and takes skillful planning by client managers in the early stages of a project. In response to a lack of information currently available to construction clients in this area, this paper explores the features of a successful incentive system and identifies key learnings for client managers to consider when designing incentives. Our findings, based on data from a large Australian case study, suggest that key stakeholders place greater emphasis on the project management processes that support incentives than on the incentive itself. Further, contractors need adequate time and information to accurately estimate construction costs prior to their tender price submission to ensure cost-focused incentive goals remain achievable. Thus, client managers should be designing incentives as part of a supportive procurement strategy to maximize project stakeholder motivation and prevent goal misalignment.

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Organisations face increasing competition from new firms in emerging markets and their past superior products may no longer provide competitive advantage in markets based on different cost and value differentials. A shift in design practices from product solutions to health services which are accessible and affordable by all is required. This paper explores a design led approach to innovation to assist medical device companies develop new services and experiences and reshape their notions of the nature, development and deployment of health care services. This approach uses design tools and methodologies that are grounded in the authentic understandings of stakeholder experiences, to assist an organisation create a vision of likely future health care scenarios. Through this process, organisations can explore the complexities in the delivery of future health care services in new and emerging markets allowing them to tailor product and service solutions which focus on being accessible and affordable by all. The industry based case study for the design of health services in carried out in emerging economies. The contribution of this work in advancing research into design innovation and future research directions are also presented.

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Over the past ten years, minimally invasive plate osteosynthesis (MIPO) for the fixation of long bone fractures has become a clinically accepted method with good outcomes, when compared to the conventional open surgical approach (open reduction internal fixation, ORIF). However, while MIPO offers some advantages over ORIF, it also has some significant drawbacks, such as a more demanding surgical technique and increased radiation exposure. No clinical or experimental study to date has shown a difference between the healing outcomes in fractures treated with the two surgical approaches. Therefore, a novel, standardised severe trauma model in sheep has been developed and validated in this project to examine the effect of the two surgical approaches on soft tissue and fracture healing. Twenty four sheep were subjected to severe soft tissue damage and a complex distal femur fracture. The fractures were initially stabilised with an external fixator. After five days of soft tissue recovery, internal fixation with a plate was applied, randomised to either MIPO or ORIF. Within the first fourteen days, the soft tissue damage was monitored locally with a compartment pressure sensor and systemically by blood tests. The fracture progress was assessed fortnightly by x-rays. The sheep were sacrificed in two groups after four and eight weeks, and CT scans and mechanical testing performed. Soft tissue monitoring showed significantly higher postoperative Creatine Kinase and Lactate Dehydrogenase values in the ORIF group compared to MIPO. After four weeks, the torsional stiffness was significantly higher in the MIPO group (p=0.018) compared to the ORIF group. The torsional strength also showed increased values for the MIPO technique (p=0.11). The measured total mineralised callus volumes were slightly higher in the ORIF group. However, a newly developed morphological callus bridging score showed significantly higher values for the MIPO technique (p=0.007), with a high correlation to the mechanical properties (R2=0.79). After eight weeks, the same trends continued, but without statistical significance. In summary, this clinically relevant study, using the newly developed severe trauma model in sheep, clearly demonstrates that the minimally invasive technique minimises additional soft tissue damage and improves fracture healing in the early stage compared to the open surgical approach method.

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A high peak power demand at substations will result under Moving Block Signalling (MBS) when a dense queue of trains begins to start from a complete stop at the same time in an electrified railway system. This may cause the power supply interruption and in turn affect the train service substantially. In a recent study, measures of Starting Time Delay (STD) and Acceleration Rate Limit (ARL) are the possible approaches to reduce the peak power demand on the supply system under MBS. Nevertheless, there is no well-defined relationship between the two measures and peak power demand reduction (PDR). In order to attain a lower peak demand at substations on different traffic conditions and system requirements, an expert system is one of the possible approaches to procure the appropriate use of peak demand reduction measures. The main objective of this paper is to study the effect of the train re-starting strategies on the power demand at substations and the time delay suffered by the trains with the aid of computer simulation. An expert system is a useful tool to select various adoptions of STD and ARL under different operational conditions and system requirements.

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China has made great progress in constructing comprehensive legislative and judicial infrastructures to protect intellectual property rights. But levels of enforcement remain low. Estimates suggest that 90% of film and music products consumed in China are ‘pirated’ and in 2009 81% of the infringing goods seized at the US border originated from China. Despite of heavy criticism over its failure to enforce IPRs, key areas of China’s creative industries, including film, mobile-music, fashion and animation, are developing rapidly. This paper explores how the rapid expansion of China’s creative economy might be reconciled with conceptual approaches that view the CIs in terms of creativity inputs and IP outputs. It argues that an evolutionary understanding of copyright’s role in creative innovation might better explain China’s experiences and provide more general insights into the nature of the creative industries and the policies most likely to promote growth in this sector of the economy.