12 resultados para multi-site analysis
em University of Queensland eSpace - Australia
Resumo:
Slag composition determines the physical and chemical properties as well as the application performance of molten oxide mixtures. Therefore, it is necessary to establish a routine instrumental technique to produce accurate and precise analytical results for better process and production control. In the present paper, a multi-component analysis technique of powdered metallurgical slag samples by X-ray Fluorescence Spectrometer (XRFS) has been demonstrated. This technique provides rapid and accurate results, with minimum sample preparation. It eliminates the requirement for a fused disc, using briquetted samples protected by a layer of Borax(R). While the use of theoretical alpha coefficients has allowed accurate calibrations to be made using fewer standard samples, the application of pseudo-Voight function to curve fitting makes it possible to resolve overlapped peaks in X-ray spectra that cannot be physically separated. The analytical results of both certified reference materials and industrial slag samples measured using the present technique are comparable to those of the same samples obtained by conventional fused disc measurements.
Resumo:
QTL detection experiments in livestock species commonly use the half-sib design. Each male is mated to a number of females, each female producing a limited number of progeny. Analysis consists of attempting to detect associations between phenotype and genotype measured on the progeny. When family sizes are limiting experimenters may wish to incorporate as much information as possible into a single analysis. However, combining information across sires is problematic because of incomplete linkage disequilibrium between the markers and the QTL in the population. This study describes formulae for obtaining MLEs via the expectation maximization (EM) algorithm for use in a multiple-trait, multiple-family analysis. A model specifying a QTL with only two alleles, and a common within sire error variance is assumed. Compared to single-family analyses, power can be improved up to fourfold with multi-family analyses. The accuracy and precision of QTL location estimates are also substantially improved. With small family sizes, the multi-family, multi-trait analyses reduce substantially, but not totally remove, biases in QTL effect estimates. In situations where multiple QTL alleles are segregating the multi-family analysis will average out the effects of the different QTL alleles.
Resumo:
This article reports a longitudinal study that examined mergers between three large multi-site public-sector organizations. Both qualitative and quantitative methods of analysis are used to examine the effect of leadership and change management strategies on acceptance of cultural change by individuals. Findings indicate that in many cases the change that occurs as a result of a merger is imposed on the leaders themselves, and it is often the pace of change that inhibits the successful re-engineering of the culture. In this respect, the success or otherwise of any merger hinges on individual perceptions about the manner in which the process is handled and the direction in which the culture is moved. Communication and a transparent change process are important, as this will often determine not only how a leader will be regarded, but who will be regarded as a leader. Leaders need to be competent and trained in the process of transforming organizations to ensure that individuals within the organization accept the changes prompted by a merger.
Resumo:
The present investigation aimed to critically examine the factor structure and psychometric properties of the Anxiety Sensitivity Index - Revised (ASI-R). Confirmatory factor analysis using a clinical sample of adults (N = 248) revealed that the ASI-R could be improved substantially through the removal of 15 problematic items in order to account for the most robust dimensions of anxiety sensitivity. This modified scale was renamed the 21-item Anxiety Sensitivity Index (21-item ASI) and reanalyzed with a large sample of normative adults (N = 435), revealing configural and metric invariance across groups. Further comparisons with other alternative models, using multi-sample analysis, indicated the 21-item ASI to be the best fitting model for both groups. There was also evidence of internal consistency, test-retest reliability, and construct validity for both samples suggesting that the 21-item ASI is a useful assessment device for investigating the construct of anxiety sensitivity in both clinical and normative populations.
Resumo:
Aim To test whether addition of moderation-orientated cue exposure (CE) or CE after dysphoric mood induction ( emotional CE, ECE) improved outcomes above those from cognitive-behaviour therapy alone (CBT) in people who drank when dysphoric. Design Multi-site randomized controlled trial comparing CBT with CBT + CE and CBT + ECE. Setting Out-patient rooms in academic treatment units in Brisbane and Sydney, Australia. Participants People with alcohol misuse and problems controlling consumption when dysphoric (n = 163). Those with current major depressive episode were excluded. Intervention Eight weekly 75-minute sessions of individual treatment for alcohol problems were given to all participants, with CBT elements held constant across conditions. From session 2, CBT + CE participants resisted drinking while exposed to alcohol cues, with two priming doses of their preferred beverage being given in some sessions. After an initial CE session, CBT + ECE participants recalled negative experiences before undertaking CE, to provide exposure to emotional cues of personal relevance. Measurements Alcohol consumption, related problems, alcohol expectancies, self-efficacy and depression. Results Average improvements were highly significant across conditions, with acceptable maintenance of effects over 12 months. Both treatment retention and effects on alcohol consumption were progressively weaker in CBT + CE and CBT + ECE than in CBT alone. Changes in alcohol dependence and depression did not differ across conditions. Conclusions These data do not indicate that addition of clinic-based CE to standard CBT improves outcomes. A different approach to the management of craving may be required.
Resumo:
Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone condition. The objective of this work was to compare the Tropical Rapid Appraisal of Riparian Condition (TRARC) method to a satellite image based approach. TRARC was developed for rapid assessment of the environmental condition of savanna riparian zones. The comparison assessed mapping accuracy, representativeness of TRARC assessment, cost-effectiveness, and suitability for multi-temporal analysis. Two multi-spectral QuickBird images captured in 2004 and 2005 and coincident field data covering sections of the Daly River in the Northern Territory, Australia were used in this work. Both field and image data were processed to map riparian health indicators (RHIs) including percentage canopy cover, organic litter, canopy continuity, stream bank stability, and extent of tree clearing. Spectral vegetation indices, image segmentation and supervised classification were used to produce RHI maps. QuickBird image data were used to examine if the spatial distribution of TRARC transects provided a representative sample of ground based RHI measurements. Results showed that TRARC transects were required to cover at least 3% of the study area to obtain a representative sample. The mapping accuracy and costs of the image based approach were compared to those of the ground based TRARC approach. Results proved that TRARC was more cost-effective at smaller scales (1-100km), while image based assessment becomes more feasible at regional scales (100-1000km). Finally, the ability to use both the image and field based approaches for multi-temporal analysis of RHIs was assessed. Change detection analysis demonstrated that image data can provide detailed information on gradual change, while the TRARC method was only able to identify more gross scale changes. In conclusion, results from both methods were considered to complement each other if used at appropriate spatial scales.
Resumo:
Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this paper, we consider the case of imprecise environments, where little may be known about these factors and they may well vary significantly when the system is applied. Specifically, the use of precision-recall analysis is investigated and compared to the more well known performance measures such as error-rate and the receiver operating characteristic (ROC). We argue that while ROC analysis is invariant to variations in class priors, this invariance in fact hides an important factor of the evaluation in imprecise environments. Therefore, we develop a generalised precision-recall analysis methodology in which variation due to prior class probabilities is incorporated into a multi-way analysis of variance (ANOVA). The increased sensitivity and reliability of this approach is demonstrated in a remote sensing application.