750 resultados para CLASSIFICATIONS


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The resource potential of shallow water tables for cropping systems has been investigated using the Australian sugar industry as a case study. Literature concerning shallow water table contributions to sugarcane crops has been summarised, and an assessment of required irrigation for water tables to depths of 2 m investigated using the SWIMv2.1 soil water balance model for three different soils. The study was undertaken because water availability is a major limitation for sugarcane and other crop production systems in Australia and knowledge on how best to incorporate upflow from water tables in irrigation scheduling is limited. Our results showed that for the three soils studied (representing a range of permeabilities as defined by near-saturated hydraulic conductivities), no irrigation would be required for static water tables within 1 m of the soil surface. Irrigation requirements when static water tables exceeded 1 m depth were dependent on the soil type and rooting characteristics (root depth and density). Our results also show that the near-saturated hydraulic conductivities are a better indicator of the ability of water tables below 1 m to supply sufficient upflow as opposed to soil textural classifications. We conclude that there is potential for reductions in irrigation and hence improvements in irrigation water use efficiency in areas where shallow water tables are a low salinity risk: either fresh, or the local hydrology results in net recharge. (C) 2003 Elsevier B.V. All rights reserved.

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Quantitative olfactory assessment is often neglected in clinical practice, although olfactory loss can assist diagnosis and leads to significant morbidity. The aim of this study was to develop normative data for the Australian population for the 'Sniffin' Sticks', an internationally established olfactory function test. As in other populations, Australian females performed better than males and both lost olfactory function with age. From the normative data, criterion test scores for males and females were established for clinical classifications ('normosmic', 'hyposmic', and 'anosmic'). These clinical classifications were assessed in Parkinson's patients: 81.1 % were anosmic or severely hyposmic and only 7.7% were normosmic. A new term ('prebyosmia') is introduced to describe age-related loss of olfactory capacity of unknown aetiology. With these norms, the Sniffin' Sticks can be used in the Australian population to compare an individual's olfactory function against the population of others of similar age and sex and to identify olfactory dysfunction. (C) 2003 Elsevier Ltd. All rights reserved.

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Coarse-resolution thematic maps derived from remotely sensed data and implemented in GIS play an important role in coastal and marine conservation, research and management. Here, we describe an approach for fine-resolution mapping of land-cover types using aerial photography and ancillary GIs and ground data in a large (100 x 35 km) subtropical estuarine system (Moreton Bay, Queensland, Australia). We have developed and implemented a classification scheme representing 24 coastal (subtidal, intertidal. mangrove, supratidal and terrestrial) cover types relevant to the ecology of estuarine animals, nekton and shorebirds. The accuracy of classifications of the intertidal and subtidal cover types, as indicated by the agreement between the mapped (predicted) and reference (ground) data, was 77-88%, depending on the zone and level of generalization required. The variability and spatial distribution of habitat mosaics (landscape types) across the mapped environment were assessed using K-means clustering and validated with Classification and Regression Tree models. Seven broad landscape types could be distinguished and ways of incorporating the information on landscape composition into site-specific conservation and field research are discussed. This research illustrates the importance and potential applications of fine-resolution mapping for conservation and management of estuarine habitats and their terrestrial and aquatic wildlife. (c) 2005 Elsevier Ltd. All rights reserved.

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Purpose. To use a taxonomy of goal content, developed in community-based brain injury rehabilitation to examine and compare the content of goals set within two different service settings; and to further examine the potential of the taxonomy to be a reliable and comprehensive framework for classifying goals. Method. Qualitative analysis and categorization of 1492 goal statements extracted from a community-based brain injury rehabilitation service over two time periods (1996-97, 1998-99), and cross-organizational comparison of ratings of goal classifications using a random sample of 100 goal statements drawn from this data set and the original 1765 goal statements used in developing the taxonomy. Results. Application of the taxonomy beyond the original service setting in which it was developed indicated a strong inter-rater reliability, with a high test-retest agreement reported over time. For both services, a small number of categories accounted for a substantial proportion of goals set within the two time periods, while considerable change was evident in goals between the two periods for one service. Further, both placed emphasis on individually focused goals rather than relationship or family-related goals. Conclusion. The taxonomy provides a reliable means for classifying goals and is a useful tool for exploration of the multiple influences on goal setting. Further application of the taxonomy to examine the relative influence on goal setting of client factors versus a range of organizational factors would be beneficial.

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Purpose: To evaluate the validity of a uniaxial accelerometer (MTI Actigraph) for measuring physical activity in people with acquired brain injury (ABI) using portable indirect calorimetry (Cosmed K4b(2)) as a criterion measure. Methods: Fourteen people with ABI and related gait pattern impairment (age 32 +/- 8 yr) wore an MTI Actigraph that measured activity (counts(.)min-(1)) and a Cosmed K4b(2) that measured oxygen consumption (mL(.)kg(-1.)min(-1)) during four activities: quiet sitting (QS) and comfortable paced (CP), brisk paced (BP), and fast paced (FP) walking. MET levels were predicted from Actigraph counts using a published equation and compared with Cosmed measures. Predicted METs for each of the 56 activity bouts (14 participants X 4 bouts) were classified (light, moderate, vigorous, or very vigorous intensity) and compared with Cosmed-based classifications. Results: Repeated-measures ANOVA indicated that walking condition intensities were significantly different (P < 0.05) and the Actigraph detected the differences. Overall correlation between measured and predicted METs was positive, moderate, and significant (r = 0.74). Mean predicted METs were not significantly different from measured for CP and BP, but for FP walking, predicted METs were significantly less than measured (P < 0.05). The Actigraph correctly classified intensity for 76.8% of all activity bouts and 91.5% of light- and moderate-intensity bouts. Conclusions: Actigraph counts provide a valid index of activity across the intensities investigated in this study. For light to moderate activity, Actigraph-based estimates of METs are acceptable for group-level analysis and are a valid means of classifying activity intensity. The Actigraph significantly underestimated higher intensity activity, although, in practice, this limitation will have minimal impact on activity measurement of most community-dwelling people with ABI.

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Systematic protocols that use decision rules or scores arc, seen to improve consistency and transparency in classifying the conservation status of species. When applying these protocols, assessors are typically required to decide on estimates for attributes That are inherently uncertain, Input data and resulting classifications are usually treated as though they arc, exact and hence without operator error We investigated the impact of data interpretation on the consistency of protocols of extinction risk classifications and diagnosed causes of discrepancies when they occurred. We tested three widely used systematic classification protocols employed by the World Conservation Union, NatureServe, and the Florida Fish and Wildlife Conservation Commission. We provided 18 assessors with identical information for 13 different species to infer estimates for each of the required parameters for the three protocols. The threat classification of several of the species varied from low risk to high risk, depending on who did the assessment. This occurred across the three Protocols investigated. Assessors tended to agree on their placement of species in the highest (50-70%) and lowest risk categories (20-40%), but There was poor agreement on which species should be placed in the intermediate categories, Furthermore, the correspondence between The three classification methods was unpredictable, with large variation among assessors. These results highlight the importance of peer review and consensus among multiple assessors in species classifications and the need to be cautious with assessments carried out 4), a single assessor Greater consistency among assessors requires wide use of training manuals and formal methods for estimating parameters that allow uncertainties to be represented, carried through chains of calculations, and reported transparently.

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A key component of the venom of many Australian snakes belonging to the elapid family is a toxin that is structurally and functionally similar to that of the mammalian prothrombinase complex. In mammals, this complex is responsible for the cleavage of prothrombin to thrombin and is composed of factor Xa in association with its cofactors calcium, phospholipids, and factor Va. The snake prothrombin activators have been classified on the basis of their requirement for cofactors for activity. The two major subgroups described in Australian elapid snakes, groups C and D, are differentiated by their requirement for mammalian coagulation factor Va. In this study, we describe the cloning, characterization, and comparative analysis of the factor X- and factor V-like components of the prothrombin activators from the venom glands of snakes possessing either group C or D prothrombin activators. The overall domain arrangement in these proteins was highly conserved between all elapids and with the corresponding mammalian clotting factors. The deduced protein sequence for the factor X-like protease precursor, identified in elapids containing either group C or D prothrombin activators, demonstrated a remarkable degree of relatedness to each other (80%-97%). The factor V-like component of the prothrombin activator, present only in snakes containing group C complexes, also showed a very high degree of homology (96%-98%). Expression of both the factor X- and factor V-like proteins determined by immunoblotting provided an additional means of separating these two groups at the molecular level. The molecular phylogenetic analysis described here represents a new approach for distinguishing group C and D snake prothrombin activators and correlates well with previous classifications.

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The gastrointestinal tracts of multi-cellular blood-feeding parasites are targets for vaccines and drugs. Recently, recombinant vaccines that interrupt the digestion of blood in the hookworm gut have shown efficacy, so we explored the intestinal transcriptomes of the human and canine hookworms, Necator americanus and Ancylostoma caninum, respectively. We used Laser Microdissection Microscopy to dissect gut tissue from the parasites, extracted the RNA and generated cDNA libraries. A total of 480 expressed sequence tags were sequenced from each library and assembled into contigs, accounting for 268 N. americanus genes and 276 A. caninum genes. Only 17% of N. americanus and 36% of A. caninum contigs were assigned Gene Ontology classifications. Twenty-six (9.8%) N. americanus and 18 (6.5%) A. caninum contigs did not have homologues in any databases including dbEST-of these novel clones, seven N. americanus and three A. caninum contigs had Open Reading Frames with predicted secretory signal peptides. The most abundant transcripts corresponded to mRNAs encoding cholesterol-and fatty acid-binding proteins, C-type lectins, Activation-Associated Secretory Proteins, and proteases of different mechanistic classes, particularly astacin-like metallopeptidases. Expressed sequence tags corresponding to known and potential recombinant vaccines were identified and these included homologues of proteases, anti-clotting factors, defensins and integral membrane proteins involved in cell adhesion. (c) 2006 Australian Society for Parasitology Inc Published by Elsevier Ltd. All fights reserved.

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Onsite wastewater treatment systems aim to assimilate domestic effluent into the environment. Unfortunately failure of such systems is common and inadequate effluent treatment can have serious environmental implications. The capacity of a particular soil to treat wastewater will change over time. The physical properties influence the rate of effluent movement through the soil and its chemical properties dictate the ability to renovate effluent. A research project was undertaken to determine the role that physical and chemical soil properties play in predicting the long-term behaviour of soil under effluent irrigation and to determine if they have a potential function as early indicators of adverse effects of effluent irrigation on treatment sustainability. Principal Component Analysis (PCA) and Cluster Analysis grouped the soils independently of their soil classifications and allowed us to distinguish the most suitable soils for sustainable long term effluent irrigation and determine the most influential soil parameters to characterise them. Multivariate analysis allowed a clear distinction between soils based on the cation exchange capacities. This in turn correlated well with the soil mineralogy. Mixed mineralogy soils in particular sodium or magnesium dominant soils are the most susceptible to dispersion under effluent irrigation. The soil Exchangeable Sodium Percentage (ESP) was identified as a crucial parameter and was highly correlated with percentage clay, electrical conductivity, exchangeable sodium, exchangeable magnesium and low Ca:Mg ratios (less than 0.5).

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It is often debated whether migraine with aura (MA) and migraine without aura (MO) are etiologically distinct disorders. A previous study using latent class analysis (LCA) in Australian twins showed no evidence for separate subtypes of MO and MA. The aim of the present study was to replicate these results in a population of Dutch twins and their parents, siblings and partners (N = 10,144). Latent class analysis of International Headache Society (IHS)-based migraine symptoms resulted in the identification of 4 classes: a class of unaffected subjects (class 0), a mild form of nonmigrainous headache (class 1), a moderately severe type of migraine (class 2), typically without neurological symptoms or aura (8% reporting aura symptoms), and a severe type of migraine (class 3), typically with neurological symptoms, and aura symptoms in approximately half of the cases. Given the overlap of neurological symptoms and nonmutual exclusivity of aura symptoms, these results do not support the MO and MA subtypes as being etiologically distinct. The heritability in female twins of migraine based on LCA classification was estimated at .50 (95% confidence intervals [0CI} .27 -.59), similar to IHS-based migraine diagnosis (h(2) = .49, 95% Cl .19-.57). However, using a dichotomous classification (affected-unaffected) decreased heritability for the IHS-based classification (h(2) = .33, 95% Cl .00-.60), but not the LCA-based classification (h(2) = .51, 95% Cl. 23-.61). Importantly, use of the LCA-based classification increased the number of subjects classified as affected. The heritability of the screening question was similar to more detailed LCA and IHS classifications, suggesting that the screening procedure is an important determining factor in genetic studies of migraine.

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In this article, we propose a framework, namely, Prediction-Learning-Distillation (PLD) for interactive document classification and distilling misclassified documents. Whenever a user points out misclassified documents, the PLD learns from the mistakes and identifies the same mistakes from all other classified documents. The PLD then enforces this learning for future classifications. If the classifier fails to accept relevant documents or reject irrelevant documents on certain categories, then PLD will assign those documents as new positive/negative training instances. The classifier can then strengthen its weakness by learning from these new training instances. Our experiments’ results have demonstrated that the proposed algorithm can learn from user-identified misclassified documents, and then distil the rest successfully.

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Learning from mistakes has proven to be an effective way of learning in the interactive document classifications. In this paper we propose an approach to effectively learning from mistakes in the email filtering process. Our system has employed both SVM and Winnow machine learning algorithms to learn from misclassified email documents and refine the email filtering process accordingly. Our experiments have shown that the training of an email filter becomes much effective and faster

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There have been many models developed by scientists to assist decision-makers in making socio-economic and environmental decisions. It is now recognised that there is a shift in the dominant paradigm to making decisions with stakeholders, rather than making decisions for stakeholders. Our paper investigates two case studies where group model building has been undertaken for maintaining biodiversity in Australia. The first case study focuses on preservation and management of green spaces and biodiversity in metropolitan Melbourne under the umbrella of the Melbourne 2030 planning strategy. A geographical information system is used to collate a number of spatial datasets encompassing a range of cultural and natural assets data layers including: existing open spaces, waterways, threatened fauna and flora, ecological vegetation covers, registered cultural heritage sites, and existing land parcel zoning. Group model building is incorporated into the study through eliciting weightings and ratings of importance for each datasets from urban planners to formulate different urban green system scenarios. The second case study focuses on modelling ecoregions from spatial datasets for the state of Queensland. The modelling combines collaborative expert knowledge and a vast amount of environmental data to build biogeographical classifications of regions. An information elicitation process is used to capture expert knowledge of ecoregions as geographical descriptions, and to transform this into prior probability distributions that characterise regions in terms of environmental variables. This prior information is combined with measured data on the environmental variables within a Bayesian modelling technique to produce the final classified regions. We describe how linked views between descriptive information, mapping and statistical plots are used to decide upon representative regions that satisfy a number of criteria for biodiversity and conservation. This paper discusses the advantages and problems encountered when undertaking group model building. Future research will extend the group model building approach to include interested individuals and community groups.

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Sex segregation in employment is a phenomenon that can be observed and analysed at different levels, ranging from comparisons between broad classifications by industry or occupation through to finely defined jobs within such classifications. From an aggregate perspective, the contribution of information technology (IT) employment to sex segregation is clear--it remains a highly male-dominated field apparently imbued with the ongoing masculinity of science and technology. While this situation is clearly contrary to hopes of a new industry freed from traditional distinctions between 'men's' and 'women's' work, it comes as little surprise to most feminist and labour studies analysts. An extensive literature documents the persistently masculine culture of IT employment and education (see, among many, Margolis and Fisher 2002; Wajcman 1991; Webster 1996; Wright 1996, 1997), and the idea that new occupations might escape sexism by sidestepping 'old traditions' has been effectively critiqued by writers such as Adam, who notes the fallacy of assuming a spontaneous emergence of equality in new settings (2005: 140).

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The Operator Choice Model (OCM) was developed to model the behaviour of operators attending to complex tasks involving interdependent concurrent activities, such as in Air Traffic Control (ATC). The purpose of the OCM is to provide a flexible framework for modelling and simulation that can be used for quantitative analyses in human reliability assessment, comparison between human computer interaction (HCI) designs, and analysis of operator workload. The OCM virtual operator is essentially a cycle of four processes: Scan Classify Decide Action Perform Action. Once a cycle is complete, the operator will return to the Scan process. It is also possible to truncate a cycle and return to Scan after each of the processes. These processes are described using Continuous Time Probabilistic Automata (CTPA). The details of the probability and timing models are specific to the domain of application, and need to be specified using domain experts. We are building an application of the OCM for use in ATC. In order to develop a realistic model we are calibrating the probability and timing models that comprise each process using experimental data from a series of experiments conducted with student subjects. These experiments have identified the factors that influence perception and decision making in simplified conflict detection and resolution tasks. This paper presents an application of the OCM approach to a simple ATC conflict detection experiment. The aim is to calibrate the OCM so that its behaviour resembles that of the experimental subjects when it is challenged with the same task. Its behaviour should also interpolate when challenged with scenarios similar to those used to calibrate it. The approach illustrated here uses logistic regression to model the classifications made by the subjects. This model is fitted to the calibration data, and provides an extrapolation to classifications in scenarios outside of the calibration data. A simple strategy is used to calibrate the timing component of the model, and the results for reaction times are compared between the OCM and the student subjects. While this approach to timing does not capture the full complexity of the reaction time distribution seen in the data from the student subjects, the mean and the tail of the distributions are similar.