Search results for "dissimilarity"

showing 10 items of 16 documents

Comparing pollen spectra from modified Tauber traps and moss samples: examples from a selection of woodlands across Europe

2010

This paper compares pollen spectra derived from modified Tauber traps and moss samples from a selection of woodland types from Bulgaria, the Czech Republic, Georgia, Greece, Poland, Switzerland and Wales. The study examines the representation of individual taxa in the two sampling media and aims to ascertain the duration of pollen deposition captured by a moss. The latter aim was pursued through the calculation of dissimilarity indexes to assess how many years of pollen deposited in a pollen trap yield percentage values that are most similar to those obtained from the moss. The results are broadly scattered; the majority of moss samples being most similar to several years of pollen depositi…

0106 biological sciences010506 paleontologyArcheologyWoodlandPlant ScienceBiostratigraphy580 Plants (Botany)medicine.disease_causeMoss sample; Modified Tauber trap; Surface pollen deposition; Collecting efficiency; Representation of tree taxa; Dissimilarity measures010603 evolutionary biology01 natural sciencesPollenBotanymedicineHolocene0105 earth and related environmental sciencesbiologyPalaeontologyPaleontologySediment15. Life on landbiology.organism_classificationMossDeposition (aerosol physics)Environmental scienceWoody plant
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Global functional variation in alpine vegetation

2021

International audience; Questions. What are the functional trade-offs of vascular plant species in global alpine ecosystems? How is functional variation related to vegetation zones, climatic groups and biogeographic realms? What is the relative contribution of macroclimate and evolutionary history in shaping the functional variation of alpine plant communities? Location. Global. Methods. We compiled a data set of alpine vegetation with 5,532 geo-referenced plots, 1,933 species and six plant functional traits. We used principal component analysis to quantify functional trade-offs among species and trait probability density to assess the functional dissimilarity of alpine vegetation in differ…

0106 biological sciencesVascular plantAlpine plant[SDE.MCG]Environmental Sciences/Global Changesalpine vegetationPlant Science[SDV.BID]Life Sciences [q-bio]/Biodiversity010603 evolutionary biology01 natural sciencesmacroclimatephylogenetic dissimilaritytrait poolGeographical distanceEcosystemtrait probability density[SDV.EE]Life Sciences [q-bio]/Ecology environmentalpine biomes; alpine vegetation; evolutionary history; functional convergence; macroclimate; phylogenetic dissimilarity; trait pools; trait probability densityEcologybiologyPhylogenetic treeEcologyfunctional convergenceVegetation15. Life on landbiology.organism_classificationalpine biomesGeographyTrait[SDE.BE]Environmental Sciences/Biodiversity and Ecologyalpine biomeevolutionary historytrait poolsDistance matrices in phylogeny010606 plant biology & botanyJournal of Vegetation Science
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Do plant-based biogeographical regions shape aphyllophoroid fungal communities in Europe?

2018

Aim: Aphyllophoroid fungi are associated with plants, either using plants as a resource (as parasites or decomposers) or as symbionts (as mycorrhizal partners). In spite of their strong association with plants, it is unknown how much plant distributions determine their biogeographical patterns compared with environmental factors such as climate and human land use. In this study, our aims are to (1) describe the spatial diversity patterns of aphyllophoroid fungi in Europe and (2) identify the factors shaping these patterns. Location: Europe, as well as the adjacent Subarctic to Arctic islands (Greenland, Faroe Islands, Iceland, Svalbard), Palestine and the south-east coast of the Caspian Sea…

0106 biological sciencesVascular plantBeta diversitynestednessCONSERVATIONBeta diversityBiodiversitycommunity dissimilarityspecies turnover010603 evolutionary biology01 natural sciencessouthmacrofungispecies richness1183 Plant biology microbiology virologyEcology Evolution Behavior and Systematics2. Zero hungerEcologybiologyEcologyWOOD-INHABITING FUNGISettore BIO/02 - Botanica SistematicaCOMPONENTSSpecies diversity15. Life on landnorthbiology.organism_classificationEVOLUTIONARY HISTORIESSubarctic climateCLIMATEGeographyTEMPERATE FORESTSPATTERNSNestednessta1181BIODIVERSITYOrdinationSpecies richnessBRYOPHYTES010606 plant biology & botany
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Dissimilarity Application for Medical Imaging Classification

2005

In the traditional way of learning from examples of objects the classifiers are built in a feature space. However, alternative ways can be found by constructing decision rules on dissimilarity (distance) representations. In such a recognition process a new object is described by its distances to (a subset of) die training samples. The use of the dissimilarities is especially of interest when features are difficult to obtain or when they have a little discriminative power. Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 col…

Breast cancerDissimilarityComputer assisted diagnosiComputer aided diagnosimammographyCo-occurrence matrixMedical image processingimage segmentationNeural network
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One-Sided Prototype Selection on Class Imbalanced Dissimilarity Matrices

2012

In the dissimilarity representation paradigm, several prototype selection methods have been used to cope with the topic of how to select a small representation set for generating a low-dimensional dissimilarity space. In addition, these methods have also been used to reduce the size of the dissimilarity matrix. However, these approaches assume a relatively balanced class distribution, which is grossly violated in many real-life problems. Often, the ratios of prior probabilities between classes are extremely skewed. In this paper, we study the use of renowned prototype selection methods adapted to the case of learning from an imbalanced dissimilarity matrix. More specifically, we propose the…

Class (computer programming)business.industryPattern recognitionPattern RecognitionMachine learningcomputer.software_genreSet (abstract data type)Matrix (mathematics)Distribution (mathematics)DissimilarityOne sidedPattern recognition (psychology)Artificial intelligenceRepresentation (mathematics)businesscomputerSelection (genetic algorithm)Mathematics
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Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.

2007

Abstract Background Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rath…

Computer scienceAlgorismesPrediction by partial matchingCompression dissimilaritycomputer.software_genreBiochemistryProtein Structure SecondaryPhylogenetic studiesStructural BiologySequence Analysis ProteinDatabases Proteinlcsh:QH301-705.5Biological dataNCDApplied MathematicsGenomicsClassificationCDComputer Science ApplicationsBenchmarking:Informàtica::Informàtica teòrica [Àrees temàtiques de la UPC]Universal compression dissimilarityArea Under CurveMetric (mathematics)lcsh:R858-859.7Data miningAlgorithmsData compressionResearch Article:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]Normalization (statistics)lcsh:Computer applications to medicine. Medical informaticsBioinformatics Sequence Alignment AlgorithmsSet (abstract data type)Similarity (network science)Normalized compression sissimilarityData compression (Computer science)AnimalsHumansAmino Acid SequenceMolecular BiologyBiologyDades -- Compressió (Informàtica)USMUniversal similarity metricProteinsUCDProtein Structure TertiaryData setGenòmicaStatistical classificationlcsh:Biology (General)ROC CurvecomputerSequence AlignmentSoftwareBMC bioinformatics
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Dissimilarity Application in Digitized Mammographic Images Classification.

2006

Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the traditional way of learning from examples of objects the classifiers are built in a feature space. However, an alternative ways can be found by constructing decision rules on dissimilarity (distance) representations. In such a recognition process a new object is described by its distances to (a subset of) the training samples. The use of the dissimilarities is especially of interest when features are difficult to obtain or when they have a little discrim…

DissimilarityBreast CancerNeural NetworkCooccurrence matrixComputer Aided Detection.
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A New Dissimilarity Measure for Clustering Seismic Signals

2011

Hypocenter and focal mechanism of an earthquake can be determined by the analysis of signals, named waveforms, related to the wave field produced and recorded by a seismic network. Assuming that waveform similarity implies the similarity of focal parameters, the analysis of those signals characterized by very similar shapes can be used to give important details about the physical phenomena which have generated an earthquake. Recent works have shown the effectiveness of cross-correlation and/or cross-spectral dissimilarities to identify clusters of seismic events. In this work we propose a new dissimilarity measure between seismic signals whose reliability has been tested on real seismic dat…

Focal mechanismSimilarity (geometry)Cross-correlationHypocenterSettore INF/01 - InformaticaComputer sciencebusiness.industryHomogeneity (statistics)Pattern recognitioncomputer.software_genreMeasure (mathematics)Physics::GeophysicsSettore GEO/11 - Geofisica ApplicataWaveformArtificial intelligenceData miningbusinessCluster analysiscomputerDissimilarity measure Clustering Seismic Signals
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Deepen Into the Social Segregation of Secondary Schools in the Community of Madrid

2021

Recientes estudios han mostrado que la segregación escolar por nivel socioeconómico en la Comunidad de Madrid es muy alta, la más alta de España, y una de las más elevadas de Europa. Esta investigación profundiza en el conocimiento de la segregación escolar por nivel socioeconómico en educación secundaria con datos recientes mediante la consecución de tres objetivos: a) estimando su magnitud con diversas estrategias, calculando su perfil para 19 grupos minoritarios y comparándola con otras Comunidades; b) estudiando el papel de los centros públicos, privados concertados y no concertados; y c) determinando la aportación del programa de bilingüismo a la segregación. Se realiza una explotación…

GovernmentEducación secundariaIndex (economics)Secondary educationMadridEducacióneducationGeneral Engineering:SOCIOLOGÍA [UNESCO]Educational inequalityIndex of dissimilarityGeographySegregación escolarEquidad educativaUNESCO::SOCIOLOGÍANivel socioeconómicoSocioeconomicsSocioeconomic statusInclusion (education)Neuroscience of multilingualism
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Convergence and divergence in organization of phytoplankton communities under various regimes of physical and biological control

2010

The hypothesis that physical constraints may be as important, if not more important, than biological ones in shaping the structure of phytoplankton assemblage was tested by analyzing longterm (11–29 years) phytoplankton series in eight lakes and nine sites located along a latitudinal gradient in the Northern hemisphere. Phytoplankton biomass was used and similarity of assemblages in same months of the annual data sets was then calculated by subtracting the Bray–Curtis dissimilarity index from 1. The extent of biological and physical forcing was partly based on ‘‘expert evaluation’’: the importance of four physical (light availability, temperature, conductivity, and sediment stirring up) and…

Index of dissimilarityBiomass (ecology)EcologyPhytoplanktonTemperate climateNorthern HemisphereEcosystemPhytoplankton biomass Phytoplankton composition Similarity PEG model Biological control Ecosystem functioningForcing (mathematics)Physical geographyAquatic SciencePlanktonBiologyHydrobiologia
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