521 resultados para Selection techniques


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Cane fibre content has increased over the past ten years. Some of that increase can be attributed to new varieties selected for release. This paper reviews the existing methods for quantifying the fibre characteristics of a variety, including fibre content and fibre quality measurements – shear strength, impact resistance and short fibre content. The variety selection process is presented and it is reported that fibre content has zero weighting in the current selection index. An updated variety selection approach is proposed, potentially replacing the existing selection process relating to fibre. This alternative approach involves the use of a more complex mill area level model that accounts for harvesting, transport and processing equipment, taking into account capacity, efficiency and operational impacts, along with the end use for the bagasse. The approach will ultimately determine a net economic value for the variety. The methodology lends itself to a determination of the fibre properties that have a significant impact on the economic value so that variety tests can better target the critical properties. A low-pressure compression test is proposed as a good test to provide an assessment of the impact of a variety on milling capacity. NIR methodology is proposed as a technology to lead to a more rapid assessment of fibre properties, and hence the opportunity to more comprehensively test for fibre impacts at an earlier stage of variety development.

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Background Supine imaging modalities provide valuable 3D information on scoliotic anatomy, but the altered spine geometry between the supine and standing positions affects the Cobb angle measurement. Previous studies report a mean 7°-10° Cobb angle increase from supine to standing, but none have reported the effect of endplate pre-selection or whether other parameters affect this Cobb angle difference. Methods Cobb angles from existing coronal radiographs were compared to those on existing low-dose CT scans taken within three months of the reference radiograph for a group of females with adolescent idiopathic scoliosis. Reformatted coronal CT images were used to measure supine Cobb angles with and without endplate pre-selection (end-plates selected from the radiographs) by two observers on three separate occasions. Inter and intra-observer measurement variability were assessed. Multi-linear regression was used to investigate whether there was a relationship between supine to standing Cobb angle change and eight variables: patient age, mass, standing Cobb angle, Risser sign, ligament laxity, Lenke type, fulcrum flexibility and time delay between radiograph and CT scan. Results Fifty-two patients with right thoracic Lenke Type 1 curves and mean age 14.6 years (SD 1.8) were included. The mean Cobb angle on standing radiographs was 51.9° (SD 6.7). The mean Cobb angle on supine CT images without pre-selection of endplates was 41.1° (SD 6.4). The mean Cobb angle on supine CT images with endplate pre-selection was 40.5° (SD 6.6). Pre-selecting vertebral endplates increased the mean Cobb change by 0.6° (SD 2.3, range −9° to 6°). When free to do so, observers chose different levels for the end vertebrae in 39% of cases. Multi-linear regression revealed a statistically significant relationship between supine to standing Cobb change and fulcrum flexibility (p = 0.001), age (p = 0.027) and standing Cobb angle (p < 0.001). The 95% confidence intervals for intra-observer and inter-observer measurement variability were 3.1° and 3.6°, respectively. Conclusions Pre-selecting vertebral endplates causes minor changes to the mean supine to standing Cobb change. There is a statistically significant relationship between supine to standing Cobb change and fulcrum flexibility such that this difference can be considered a potential alternative measure of spinal flexibility.

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This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

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Description of a patient's injuries is recorded in narrative text form by hospital emergency departments. For statistical reporting, this text data needs to be mapped to pre-defined codes. Existing research in this field uses the Naïve Bayes probabilistic method to build classifiers for mapping. In this paper, we focus on providing guidance on the selection of a classification method. We build a number of classifiers belonging to different classification families such as decision tree, probabilistic, neural networks, and instance-based, ensemble-based and kernel-based linear classifiers. An extensive pre-processing is carried out to ensure the quality of data and, in hence, the quality classification outcome. The records with a null entry in injury description are removed. The misspelling correction process is carried out by finding and replacing the misspelt word with a soundlike word. Meaningful phrases have been identified and kept, instead of removing the part of phrase as a stop word. The abbreviations appearing in many forms of entry are manually identified and only one form of abbreviations is used. Clustering is utilised to discriminate between non-frequent and frequent terms. This process reduced the number of text features dramatically from about 28,000 to 5000. The medical narrative text injury dataset, under consideration, is composed of many short documents. The data can be characterized as high-dimensional and sparse, i.e., few features are irrelevant but features are correlated with one another. Therefore, Matrix factorization techniques such as Singular Value Decomposition (SVD) and Non Negative Matrix Factorization (NNMF) have been used to map the processed feature space to a lower-dimensional feature space. Classifiers with these reduced feature space have been built. In experiments, a set of tests are conducted to reflect which classification method is best for the medical text classification. The Non Negative Matrix Factorization with Support Vector Machine method can achieve 93% precision which is higher than all the tested traditional classifiers. We also found that TF/IDF weighting which works well for long text classification is inferior to binary weighting in short document classification. Another finding is that the Top-n terms should be removed in consultation with medical experts, as it affects the classification performance.

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An opportunistic relay selection scheme improving cooperative diversity is devised using the concept of a virtual SIMO-MISO antenna array. By incorporating multiple users as a virtual distributed antenna, not only helps combat fading but also provides significant advantage in terms of energy consumption. The proposed efficient multiple relay selection uses the concept of the distributed Alamouti scheme in a time varying environment to realize cooperative networking in wireless relay networks and provides the platform for outage, Diversiy-Multiplexing Tradeoff (DMT) and Bit-Error-Rate (BER) analysis to conclude that it is capable of achieving promising diversity gains by operating at much lower SNR when compared with conventional relay selection methods. It also has the added advantage of conserving energy for the relays that are reachable but not selected for the cooperative communication.

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Aggressive driving has been associated with engagement in other risky driving behaviours, such as speeding; while drivers using their mobile phones have an increased crash risk, despite the tendency to reduce their speed. Research has amassed separately for mobile phone use and aggressive driving among younger drivers, however little is known about the extent to which these behaviours may function independently and in combination to influence speed selection behaviour. The main aim of the current study was to investigate the effect of driver aggression (measured by the Driving Anger Expression Inventory) and mobile phone use on speed selection by young drivers. The CARRS-Q advanced driving simulator was used to test the speed selection of drivers aged 18 to 26 years (N = 32) in a suburban (60kph zone) driving context. A 2 (level of driving anger expression: low, high) X 3 (mobile phone use condition: baseline, hands-free, hand-held) mixed factorial ANOVA was conducted with speed selection as the dependent variable. Results revealed a significant main effect for mobile phone use condition such that speed selection was lowest for the hand-held condition and highest for the baseline condition. Speed selection, however, was not significantly different across the levels of driving anger expression; nor was there a significant interaction effect between the mobile phone use and driving anger expression. As young drivers are over-represented in road crash statistics, future research should further investigate the combined impact of driver aggression and mobile phone use on speed selection.

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In male tephritid fruit flies of the genus Bactrocera, feeding on secondary plant compounds (sensu lato male lures = methyl eugenol, raspberry ketone and zingerone) increases male mating success. Ingested male lures alter the male pheromonal blend, normally making it more attractive to females and this is considered the primary mechanism for the enhanced mating success. However, the male lures raspberry ketone and zingerone are known, across a diverse range of other organisms, to be involved in increasing energy metabolism. If this also occurs in Bactrocera, then this may represent an additional benefit to males as courtship is metabolically expensive and lure feeding may increase a fly's short-term energy. We tested this hypothesis by performing comparative RNA-seq analysis between zingerone-fed and unfed males of Bactrocera tryoni. We also carried out behavioural assays with zingerone- and cuelure-fed males to test whether they became more active. RNA-seq analysis revealed, in zingerone-fed flies, up-regulation of 3183 genes with homologues transcripts to those known to regulate intermale aggression, pheromone synthesis, mating and accessory gland proteins, along with significant enrichment of several energy metabolic pathways and gene ontology terms. Behavioural assays show significant increases in locomotor activity, weight reduction and successful mating after mounting; all direct/indirect measures of increased activity. These results suggest that feeding on lures leads to complex physiological changes, which result in more competitive males. These results do not negate the pheromone effect, but do strongly suggest that the phytochemical-induced sexual selection is governed by both female preference and male competitive mechanisms.

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Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.

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Overarching Research Questions Are ACT motorists aware of roadside saliva based drug testing operations? What is the perceived deterrent impact of the operations? What factors are predictive of future intentions to drug drive? What are the differences between key subgroups

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Identifying product families has been considered as an effective way to accommodate the increasing product varieties across the diverse market niches. In this paper, we propose a novel framework to identifying product families by using a similarity measure for a common product design data BOM (Bill of Materials) based on data mining techniques such as frequent mining and clus-tering. For calculating the similarity between BOMs, a novel Extended Augmented Adjacency Matrix (EAAM) representation is introduced that consists of information not only of the content and topology but also of the fre-quent structural dependency among the various parts of a product design. These EAAM representations of BOMs are compared to calculate the similarity between products and used as a clustering input to group the product fami-lies. When applied on a real-life manufacturing data, the proposed framework outperforms a current baseline that uses orthogonal Procrustes for grouping product families.

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Evolutionary algorithms are playing an increasingly important role as search methods in cognitive science domains. In this study, methodological issues in the use of evolutionary algorithms were investigated via simulations in which procedures were systematically varied to modify the selection pressures on populations of evolving agents. Traditional roulette wheel, tournament, and variations of these selection algorithms were compared on the “needle-in-a-haystack” problem developed by Hinton and Nowlan in their 1987 study of the Baldwin effect. The task is an important one for cognitive science, as it demonstrates the power of learning as a local search technique in smoothing a fitness landscape that lacks gradient information. One aspect that has continued to foster interest in the problem is the observation of residual learning ability in simulated populations even after long periods of time. Effective evolutionary algorithms balance their search effort between broad exploration of the search space and in-depth exploitation of promising solutions already found. Issues discussed include the differential effects of rank and proportional selection, the tradeoff between migration of populations towards good solutions and maintenance of diversity, and the development of measures that illustrate how each selection algorithm affects the search process over generations. We show that both roulette wheel and tournament algorithms can be modified to appropriately balance search between exploration and exploitation, and effectively eliminate residual learning in this problem.

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Limbal microvascular endothelial cells (L-MVEC) contribute to formation of the corneal-limbal stem cell niche and to neovascularization of diseased and injuries corneas. Nevertheless, despite these important roles in corneal health and disease, few attempts have been made to isolate L-MVEC with the view to studying their biology in vitro. We therefore explored the feasibility of generating primary cultures of L-MVEC from cadaveric human tissue. We commenced our study by evaluating growth conditions (MesenCult-XF system) that have been previously found to be associated with expression of the endothelial cell surface marker thrombomodulin/CD141, in crude cultures established from collagenase-digests of limbal stroma. The potential presence of L-MVEC in these cultures was examined by flow cytometry using a more specific marker for vascular endothelial cells, CD31/PECAM-1. These studies demonstrated that the presence of CD141 in crude cultures established using the MesenCult-XF system is unrelated to L-MVEC. Thus we subsequently explored the use of magnetic assisted cell sorting (MACS) for CD31 as a tool for generating cultures of L-MVEC, in conjunction with more traditional endothelial cell growth conditions. These conditions consisted of gelatin-coated tissue culture plastic and MCDB-131 medium supplemented with fetal bovine serum (10% v/v), D-glucose (10 mg/mL), epidermal growth factor (10 ng/mL), heparin (50 μg/mL), hydrocortisone (1 μg/mL) and basic fibroblast growth factor (10 ng/mL). Our studies revealed that use of endothelial growth conditions are insufficient to generate significant numbers of L-MVEC in primary cultures established from cadaveric corneal stroma. Nevertheless, through use of positive-MACS selection for CD31 we were able to routinely observe L-MVEC in cultures derived from collagenase-digests of limbal stroma. The presence of L-MVEC in these cultures was confirmed by immunostaining for von Willebrand factor (vWF) and by ingestion of acetylated low-density lipoprotein. Moreover, the vWF+ cells formed aligned cell-to-cell ‘trains’ when grown on Geltrex™. The purity of L-MVEC cultures was found to be unrelated to tissue donor age (32 to 80 years) or duration in eye bank corneal preservation medium prior to use (3 to 10 days in Optisol) (using multiple regression test). Optimal purity of L-MVEC cultures was achieved through use of two rounds of positive-MACS selection for CD31 (mean ± s.e.m, 65.0 ± 20.8%; p<0.05). We propose that human L-MVEC cultures generated through these techniques, in conjunction with other cell types, will provide a useful tool for exploring the mechanisms of blood vessel cell growth in vitro.

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This research provides an assessment tool that assists the selection process of sustainability in detached suburban housing. It investigates the implications of using different design and construction methods including architecturally designed houses, developer housing and prefabricated houses. The study simulates one example of the three types of houses that have been chosen to fulfil a real client brief on a real site on the Sunshine Coast, Queensland Australia. Criteria for sustainability assessment are formulated based on literature reviews, exemplar designs and similar research projects for which the houses can be adequately evaluated. This criterion covers aspects including energy use, materials and thermal performance. The data is collected using computer models and sustainability assessment software to compare and draw conclusions on the success of each house. Our study indicates that architecturally designed housing with prefabricated building techniques are a better alternative to generic developer style housing. Our research provides an insight into the implications of three key elements of sustainability including energy use, materials and thermal performance. Designers, builders, developers and home-buyers are given an insight into some options currently available on the housing market and how the choices made during early design stages can provide a more positive environmental impact.

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To maximize energetic savings, female bats often roost communally whilst pregnant or with non-volant dependents, whereas male bats more often roost alone; however, differences in selection of roosts by sex have not often been investigated. Better understanding of female colony locations could focus management to protect the majority of bats. New Zealand's long-tailed bat (Chalinolobus tuberculatus) roost in exotic plantation forest, where sex-specific roost selection has not been investigated, and therefore such management is not possible. We investigated sex-specific roost selection by long-tailed bats for the first time. Roosts and paired nonroosts were characterized testing predictions that males and females select roosts that differ from non-roosts, and males and females select different roosts. Females and males chose Pinus radiata roosts that differed from non-roost trees. Results suggest each sex chose roosts that maximized energetic savings. Female bats used roosts closer to water sources, that warmed earlier in the day, which allowed maintenance of high temperatures. Males appeared to choose roosts that allowed torpor use for long periods of the day. Males may be less selective with their roost locations than females, as they roosted further from water sources. This could allow persistence of male bats in marginal habitat. As all female long-tailed bats chose roosts within 150 m of waterways, management to protect bats could be focused here. To protect bats least able to escape when roosts are harvested, harvest of forest stands selected by female bats as roost sites should be planned when bats are not heavily pregnant nor have non-volant dependents.

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Individuals' home ranges are constrained by resource distribution and density, population size, and energetic requirements. Consequently, home ranges and habitat selection may vary between individuals of different sex and reproductive conditions. Whilst home ranges of bats are well-studied in native habitats, they are often not well understood in modified landscapes, particularly exotic plantation forests. Although Chalinolobus tuberculatus (Vespertilionidae, Chiroptera) are present in plantation forests throughout New Zealand their home ranges have only been studied in native forest and forest-agricultural mosaic and no studies of habitat selection that included males had occurred in any habitat type. Therefore, we investigated C. tuberculatus home range and habitat selection within exotic plantation forest. Home range sizes did not differ between bats of different reproductive states. Bats selected home ranges with higher proportions of relatively old forest than was available. Males selected edges with open unplanted areas within their home ranges, which females avoided. We suggest males use these edges, highly profitable foraging areas with early evening peaks in invertebrate abundance, to maintain relatively low energetic demands. Females require longer periods of invertebrate activity to fulfil their needs so select older stands for foraging, where invertebrate activity is higher. These results highlight additional understanding gained when data are not pooled across sexes. Mitigation for harvest operations could include ensuring that areas suitable for foraging and roosting are located within a radius equal to the home range of this bat species.