962 resultados para GROUP SELECTION
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R. Jensen and Q. Shen, 'Webpage Classification with ACO-enhanced Fuzzy-Rough Feature Selection,' Proceedings of the Fifth International Conference on Rough Sets and Current Trends in Computing (RSCTC 2006), LNAI 4259, pp. 147-156, 2006.
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C. Shang and Q. Shen. Aiding classification of gene expression data with feature selection: a comparative study. Computational Intelligence Research, 1(1):68-76.
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Q. Shen and R. Jensen, 'Approximation-based feature selection and application for algae population estimation,' Applied Intelligence, vol. 28, no. 2, pp. 167-181, 2008. Sponsorship: EPSRC RONO: EP/E058388/1
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Computational Intelligence and Feature Selection provides a high level audience with both the background and fundamental ideas behind feature selection with an emphasis on those techniques based on rough and fuzzy sets, including their hybridizations. It introduces set theory, fuzzy set theory, rough set theory, and fuzzy-rough set theory, and illustrates the power and efficacy of the feature selections described through the use of real-world applications and worked examples. Program files implementing major algorithms covered, together with the necessary instructions and datasets, are available on the Web.
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The purpose of this study is to produce a series of Conceptual Ecological Models (CEMs) that represent sublittoral rock habitats in the UK. CEMs are diagrammatic representations of the influences and processes that occur within an ecosystem. They can be used to identify critical aspects of an ecosystem that may be studied further, or serve as the basis for the selection of indicators for environmental monitoring purposes. The models produced by this project are control diagrams, representing the unimpacted state of the environment free from anthropogenic pressures. It is intended that the models produced by this project will be used to guide indicator selection for the monitoring of this habitat in UK waters. CEMs may eventually be produced for a range of habitat types defined under the UK Marine Biodiversity Monitoring R&D Programme (UKMBMP), which, along with stressor models, are designed to show the interactions within impacted habitats, would form the basis of a robust method for indicator selection. This project builds on the work to develop CEMs for shallow sublittoral coarse sediment habitats (Alexander et al 2014). The project scope included those habitats defined as ‘sublittoral rock’. This definition includes those habitats that fall into the EUNIS Level 3 classifications A3.1 Atlantic and Mediterranean high energy infralittoral rock, A3.2 Atlantic and Mediterranean moderate energy infralittoral rock, A3.3 Atlantic and Mediterranean low energy infralittoral rock, A4.1 Atlantic and Mediterranean high energy circalittoral rock, A4.2 Atlantic and Mediterranean moderate energy circalittoral rock, and A4.3 Atlantic and Mediterranean low energy circalittoral rock as well as the constituent Level 4 and 5 biotopes that are relevant to UK waters. A species list of characterising fauna to be included within the scope of the models was identified using an iterative process to refine the full list of species found within the relevant Level 5 biotopes. A literature review was conducted using a pragmatic and iterative approach to gather evidence regarding species traits and information that would be used to inform the models and characterise the interactions that occur within the sublittoral rock habitat. All information gathered during the literature review was entered into a data logging pro-forma spreadsheet that accompanies this report. Wherever possible, attempts were made to collect information from UK-specific peer-reviewed studies, although other sources were used where necessary. All data gathered was subject to a detailed confidence assessment. Expert judgement by the project team was utilised to provide information for aspects of the models for which references could not be sourced within the project timeframe. A multivariate analysis approach was adopted to assess ecologically similar groups (based on ecological and life history traits) of fauna from the identified species to form the basis of the models. A model hierarchy was developed based on these ecological groups. One general control model was produced that indicated the high-level drivers, inputs, biological assemblages, ecosystem processes and outputs that occur in sublittoral rock habitats. In addition to this, seven detailed sub-models were produced, which each focussed on a particular ecological group of fauna within the habitat: ‘macroalgae’, ‘temporarily or permanently attached active filter feeders’, ‘temporarily or permanently attached passive filter feeders’, ‘bivalves, brachiopods and other encrusting filter feeders’, ‘tube building fauna’, ‘scavengers and predatory fauna’, and ‘non-predatory mobile fauna’. Each sub-model is accompanied by an associated confidence model that presents confidence in the links between each model component. The models are split into seven levels and take spatial and temporal scale into account through their design, as well as magnitude and direction of influence. The seven levels include regional to global drivers, water column processes, local inputs/processes at the seabed, habitat and biological assemblage, output processes, local ecosystem functions, and regional to global ecosystem functions. The models indicate that whilst the high level drivers that affect each ecological group are largely similar, the output processes performed by the biota and the resulting ecosystem functions vary both in number and importance between groups. Confidence within the models as a whole is generally high, reflecting the level of information gathered during the literature review. Physical drivers which influence the ecosystem were found to be of high importance for the sublittoral rock habitat, with factors such as wave exposure, water depth and water currents noted to be crucial in defining the biological assemblages. Other important factors such as recruitment/propagule supply, and those which affect primary production, such as suspended sediments, light attenuation and water chemistry and temperature, were also noted to be key and act to influence the food sources consumed by the biological assemblages of the habitat, and the biological assemblages themselves. Output processes performed by the biological assemblages are variable between ecological groups depending on the specific flora and fauna present and the role they perform within the ecosystem. Of particular importance are the outputs performed by the macroalgae group, which are diverse in nature and exert influence over other ecological groups in the habitat. Important output processes from the habitat as a whole include primary and secondary production, bioengineering, biodeposition (in mixed sediment habitats) and the supply of propagules; these in turn influence ecosystem functions at the local scale such as nutrient and biogeochemical cycling, supply of food resources, sediment stability (in mixed sediment habitats), habitat provision and population and algae control. The export of biodiversity and organic matter, biodiversity enhancement and biotope stability are the resulting ecosystem functions that occur at the regional to global scale. Features within the models that are most useful for monitoring habitat status and change due to natural variation have been identified, as have those that may be useful for monitoring to identify anthropogenic causes of change within the ecosystem. Biological, physical and chemical features of the ecosystem have been identified as potential indicators to monitor natural variation, whereas biological factors and those physical /chemical factors most likely to affect primary production have predominantly been identified as most likely to indicate change due to anthropogenic pressures.
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Clustering analysis of data from DNA microarray hybridization studies is an essential task for identifying biologically relevant groups of genes. Attribute cluster algorithm (ACA) has provided an attractive way to group and select meaningful genes. However, ACA needs much prior knowledge about the genes to set the number of clusters. In practical applications, if the number of clusters is misspecified, the performance of the ACA will deteriorate rapidly. In fact, it is a very demanding to do that because of our little knowledge. We propose the Cooperative Competition Cluster Algorithm (CCCA) in this paper. In the algorithm, we assume that both cooperation and competition exist simultaneously between clusters in the process of clustering. By using this principle of Cooperative Competition, the number of clusters can be found in the process of clustering. Experimental results on a synthetic and gene expression data are demonstrated. The results show that CCCA can choose the number of clusters automatically and get excellent performance with respect to other competing methods.
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The focus group interview is an increasingly common qualitative research method used by health professionals. General approaches to conducting focus groups have been published. There has, however, been minimal exploration of issues regarding the use of focus groups with palliative care populations and data analysis procedures have been underreported. The aim of this paper is to provide a guide for conducting focus groups drawing on palliative care examples. A succinct outline of why, when and how to use focus groups is offered. Key ethical and practical issues are explored as well as considerations for data analysis. This guide offers researchers and clinicians fundamental strategies for the use of focus groups within the palliative care context.
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This paper presents the rational for the selection of fluids for use in a model based study of sub and supercritical Waste Heat Recovery (WHR) Organic Rankine Cycle (ORC). The study focuses on multiple vehicle heat sources and the potential of WHR ORC’s for its conversion into useful work. The work presented on fluid selection is generally applicable to any waste heat recovery system, either stationary or mobile and, with careful consideration, is also applicable to single heat sources. The fluid selection process presented reduces the number of potential fluids from over one hundred to a group of under twenty fluids for further refinement in a model based WHR ORC performance study. The selection process uses engineering judgement, legislation and, where applicable, health and safety as fluid selection or de-selection criteria. This paper also investigates and discusses the properties of specific ORC fluids with regard to their impact on the theoretical potential for delivering efficient WHR ORC work output. The paper concludes by looking at potential temperature and pressure WHR ORC limits with regard to fluid properties thereby assisting with the generation of WHR ORC simulation boundary conditions.
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Analysis of colorectal carcinoma (CRC) tissue for KRAS codon 12 or 13 mutations to guide use of anti-epidermal growth factor receptor (EGFR) therapy is now considered mandatory in the UK. The scope of this practice has been recently extended because of data indicating that NRAS mutations and additional KRAS mutations also predict for poor response to anti-EGFR therapy. The following document provides guidance on RAS (i.e., KRAS and NRAS) testing of CRC tissue in the setting of personalised medicine within the UK and particularly within the NHS. This guidance covers issues related to case selection, preanalytical aspects, analysis and interpretation of such RAS testing.
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The discovery of somatic mutations, primarily JAK2V617F and CALR, in classic BCR-ABL1-negative myeloproliferative neoplasms (MPNs) has generated interest in the development of molecularly targeted therapies, whose accurate assessment requires a standardized framework. A working group, comprised of members from European LeukemiaNet (ELN) and International Working Group for MPN Research and Treatment (IWG-MRT), prepared consensus-based recommendations regarding trial design, patient selection and definition of relevant end points. Accordingly, a response able to capture the long-term effect of the drug should be selected as the end point of phase II trials aimed at developing new drugs for MPNs. A time-to-event, such as overall survival, or progression-free survival or both, as co-primary end points, should measure efficacy in phase III studies. New drugs should be tested for preventing disease progression in myelofibrosis patients with early disease in randomized studies, and a time to event, such as progression-free or event-free survival should be the primary end point. Phase III trials aimed at preventing vascular events in polycythemia vera and essential thrombocythemia should be based on a selection of the target population based on new prognostic factors, including JAK2 mutation. In conclusion, we recommended a format for clinical trials in MPNs that facilitates communication between academic investigators, regulatory agencies and drug companies.
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Building on the instrumental model of group conflict (IMGC), the present experiment investigates the support for discriminatory and meritocratic method of selections at university in a sample of local and immigrant students. Results showed that local students were supporting in a larger proportion selection method that favors them over immigrants in comparison to method that consists in selecting the best applicants without considering his/her origin. Supporting the assumption of the IMGC, this effect was stronger for locals who perceived immigrants as competing for resources. Immigrant students supported more strongly the meritocratic selection method than the one that discriminated them. However, contrasting with the assumption of the IMGC, this effect was only present in students who perceived immigrants as weakly competing for locals' resources. Results demonstrate that selection methods used at university can be perceived differently depending on students' origin. Further, they suggest that the mechanisms underlying the perception of discriminatory and meritocratic selection methods differ between local and immigrant students. Hence, the present experiment makes a theoretical contribution to the IMGC by delimiting its assumptions to the ingroup facing a competitive situation with a relevant outgroup. Practical implication for universities recruitment policies are discussed.
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Affiliation: Département de Biochimie, Université de Montréal
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Extensive social choice theory is used to study the problem of measuring group fitness in a two-level biological hierarchy. Both fixed and variable group size are considered. Axioms are identified that imply that the group measure satisfies a form of consequentialism in which group fitness only depends on the viabilities and fecundities of the individuals at the lower level in the hierarchy. This kind of consequentialism can take account of the group fitness advantages of germ-soma specialization, which is not possible with an alternative social choice framework proposed by Okasha, but which is an essential feature of the index of group fitness for a multicellular organism introduced by Michod, Viossat, Solari, Hurand, and Nedelcu to analyze the unicellular-multicellular evolutionary transition. The new framework is also used to analyze the fitness decoupling between levels that takes place during an evolutionary transition.
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A key problem in object recognition is selection, namely, the problem of identifying regions in an image within which to start the recognition process, ideally by isolating regions that are likely to come from a single object. Such a selection mechanism has been found to be crucial in reducing the combinatorial search involved in the matching stage of object recognition. Even though selection is of help in recognition, it has largely remained unsolved because of the difficulty in isolating regions belonging to objects under complex imaging conditions involving occlusions, changing illumination, and object appearances. This thesis presents a novel approach to the selection problem by proposing a computational model of visual attentional selection as a paradigm for selection in recognition. In particular, it proposes two modes of attentional selection, namely, attracted and pay attention modes as being appropriate for data and model-driven selection in recognition. An implementation of this model has led to new ways of extracting color, texture and line group information in images, and their subsequent use in isolating areas of the scene likely to contain the model object. Among the specific results in this thesis are: a method of specifying color by perceptual color categories for fast color region segmentation and color-based localization of objects, and a result showing that the recognition of texture patterns on model objects is possible under changes in orientation and occlusions without detailed segmentation. The thesis also presents an evaluation of the proposed model by integrating with a 3D from 2D object recognition system and recording the improvement in performance. These results indicate that attentional selection can significantly overcome the computational bottleneck in object recognition, both due to a reduction in the number of features, and due to a reduction in the number of matches during recognition using the information derived during selection. Finally, these studies have revealed a surprising use of selection, namely, in the partial solution of the pose of a 3D object.
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Introduction: the 5, 10-methylenetetrahydrofolate reductase (MTHFR) is an essential enzyme in folate metabolism; their polymorphisms have been associated with heart disease risk increase, obstetric problems, neural tube defects in fetuses and cancer susceptibility. This gene has a single nucleotide polymorphism, a C-T change at nucleotide 677, which affects significantly its enzymatic activity. Objective: because of the biological importance of this enzyme and the Colombian population genetic heterogeneity characteristic, a study was performed to determine allele and genotype frequencies of MTHFR C677T polymorphism in healthy individuals, taking into account that in Colombia there are only studies that have involved case-control methodology. Methods: we analyzed this polymorphism trough the amplification of the DNA of a 206 students sample population. Additionally, Colombian overall frequencies were calculated, using data from healthy controls reported in other studies. Results: a Hardy-Weinberg disequilibri m was found in the sample tested. For the Colombian data, we found that the global population was in equilibrium. Conclusion: T allele population frequency seems to be under positive selection pressure, which is reflected in the population allele increase, despite its deleterious effect. A Spanish study reported similar results and identified folic acid supplementation on expectant mothers as a probably cause of this change.