984 resultados para Mitigation measures


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Evaluating the validity of formative variables has presented ongoing challenges for researchers. In this paper we use global criterion measures to compare and critically evaluate two alternative formative measures of System Quality. One model is based on the ISO-9126 software quality standard, and the other is based on a leading information systems research model. We find that despite both models having a strong provenance, many of the items appear to be non-significant in our study. We examine the implications of this by evaluating the quality of the criterion variables we used, and the performance of PLS when evaluating formative models with a large number of items. We find that our respondents had difficulty distinguishing between global criterion variables measuring different aspects of overall System Quality. Also, because formative indicators “compete with one another” in PLS, it may be difficult to develop a set of measures which are all significant for a complex formative construct with a broad scope and a large number of items. Overall, we suggest that there is cautious evidence that both sets of measures are valid and largely equivalent, although questions still remain about the measures, the use of criterion variables, and the use of PLS for this type of model evaluation.

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This paper presents the analysis of a choice experiment designed to estimate willingness-to-pay (WTP) to mitigate damages caused by invasive plant species in a rural community of Nepal. In order to address the cash constraints problem in a subsistence economy, two payment attributes, labour contribution and membership fee, were included in the choice sets. The results reveal that rural farmers have significant WTP for forest management activities, in terms of both cash and labour contributions. The results also suggest that rural farmers value their time in this context at a different rate from the current wage rate.

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Background
Error in self-reported measures of obesity has been frequently described, but the effect of self-reported error on recruitment into diabetes prevention programs is not well established. The aim of this study was to examine the effect of using self-reported obesity data from the Finnish diabetes risk score (FINDRISC) on recruitment into the Greater Green Triangle Diabetes Prevention Project (GGT DPP).

Methods
The GGT DPP was a structured group-based lifestyle modification program delivered in primary health care settings in South-Eastern Australia. Between 2004–05, 850 FINDRISC forms were collected during recruitment for the GGT DPP. Eligible individuals, at moderate to high risk of developing diabetes, were invited to undertake baseline tests, including anthropometric measurements performed by specially trained nurses. In addition to errors in calculating total risk scores, accuracy of self-reported data (height, weight, waist circumference (WC) and Body Mass Index (BMI)) from FINDRISCs was compared with baseline data, with impact on participation eligibility presented.

Results
Overall, calculation errors impacted on eligibility in 18 cases (2.1%). Of n = 279 GGT DPP participants with measured data, errors (total score calculation, BMI or WC) in self-report were found in n = 90 (32.3%). These errors were equally likely to result in under- or over-reported risk. Under-reporting was more common in those reporting lower risk scores (Spearman-rho = −0.226, p-value < 0.001). However, underestimation resulted in only 6% of individuals at high risk of diabetes being incorrectly categorised as moderate or low risk of diabetes.

Conclusions
Overall FINDRISC was found to be an effective tool to screen and recruit participants at moderate to high risk of diabetes, accurately categorising levels of overweight and obesity using self-report data. The results could be generalisable to other diabetes prevention programs using screening tools which include self-reported levels of obesity.

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Virtual reality and simulation are becoming increasingly important in modern society and it is essential to improve our understanding of system usability and efficacy from the users’ perspective. This paper introduces a novel evaluation method designed to assess human user capability when undertaking technical and procedural training using virtual training systems. The evaluation method falls under the user-centred design and evaluation paradigm and draws on theories of cognitive, skillbased and affective learning outcomes. The method focuses on user interaction with haptic-audio-visual interfaces and the complexities related to variability in users’ performance, and the adoption and acceptance of the technologies. A large scale user study focusing on object assembly training tasks involving selecting, rotating, releasing, inserting and manipulating 3D objects was performed. The study demonstrated the advantages of the method in obtaining valuable multimodal information for accurate and comprehensive evaluation of virtual training system efficacy. The study investigated how well users learn, perform, adapt to and perceive the virtual training. The results of the study revealed valuable aspects of the design and evaluation of virtual training systems contributing to an improved understanding of more usable virtual training systems.

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The analysis provided in this research ainis to improve the understanding of the structure and nature of organisations in the transport industry so that policy-makers and researchers can be informed about the impact of size of an organisation on its preparation for the transition to a low carboneconomy. Descriptive and infetential are calculated to aid in understanding how organisations manage their C02mitigation action and carbon emission disclosure. It is noted that small and medium sized companies appear to be less financially capable of responding to the challenges of transiting to a low carbon environment that large companies.