Search results for "pattern"

showing 10 items of 4203 documents

Multivariate statistical analysis of a large odorants database aimed at revealing similarities and links between odorants and odors

2017

International audience; The perception of odor is an important component of smell; the first step of odor detection, and the discrimination of structurally diverse odorants depends on their interactions with olfactory receptors (ORs). Indeed, the perception of an odor's quality results from a combinatorial coding, in which the deciphering remains a major challenge. Several studies have successfully established links between odors and odorants by categorizing and classifying data. Hence, the categorization of odors appears to be a promising way to manage odors. In the proposed study, we performed a computational analysis using odor descriptions of the odorants present in Flavor-Base 9th Edit…

0301 basic medicinemultidimensional scalingmedia_common.quotation_subjectAgglomerative hierarchical clusteringKohonen self-organizing mapsodorants03 medical and health sciences0302 clinical medicinePerceptionComputational analysisMultidimensional scalingmedia_commonChemistrybusiness.industrymusculoskeletal neural and ocular physiologyPattern recognitionKohonen self organizing mapGeneral Chemistrycategorization030104 developmental biologyCategorizationOdorodor notesagglomerative hierarchical clusteringArtificial intelligenceMultivariate statisticalbusiness[SDV.AEN]Life Sciences [q-bio]/Food and Nutrition030217 neurology & neurosurgerypsychological phenomena and processesFood Science
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Bacteria classification using minimal absent words

2017

Bacteria classification has been deeply investigated with different tools for many purposes, such as early diagnosis, metagenomics, phylogenetics. Classification methods based on ribosomal DNA sequences are considered a reference in this area. We present a new classificatier for bacteria species based on a dissimilarity measure of purely combinatorial nature. This measure is based on the notion of Minimal Absent Words, a combinatorial definition that recently found applications in bioinformatics. We can therefore incorporate this measure into a probabilistic neural network in order to classify bacteria species. Our approach is motivated by the fact that there is a vast literature on the com…

0301 basic medicinesupervised classificationRelation (database)Computer science0102 computer and information sciences01 natural sciencesMeasure (mathematics)03 medical and health sciencesProbabilistic neural networkcombinatorics on wordsprobabilistic neural networkminimal absent wordlcsh:R5-920Settore INF/01 - Informaticabusiness.industryBacterial taxonomyPattern recognitionbacteria classificationGeneral MedicineCombinatorics on words030104 developmental biology010201 computation theory & mathematicsMetagenomicsClassification methodsArtificial intelligencebusinesslcsh:Medicine (General)AIMS Medical Science
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Influence of the metaphysis positioning in a new reverse shoulder prosthesis

2016

Aim of this work is to investigate the behaviour of a new reverse shoulder prosthesis, characterized by a humeral metaphysis with a variable offset, designed to increase the range of movements and to reduce the impingement. In particular, by means of virtual prototypes of the prosthesis, different offset values of the humeral metaphysis have been analysed in order to find the best positioning able to maximize the range of movements of the shoulder joint. The abduction force of the deltoid, at different offset values, has been also estimated. The study has been organized as follows. In the first step, the point clouds of the surfaces of the different components of the prosthesis have been ac…

030222 orthopedicsScannerOffset (computer science)business.industryComputer scienceDeltoid curvePoint cloud030229 sport sciencesMetaphysisMoiré patternFinite element method03 medical and health sciences0302 clinical medicinemedicine.anatomical_structuremedicineComputer visionShoulder jointArtificial intelligencebusinessReverse Engineering CAD Reverse Shoulder Prosthesis Range of Movements
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Reinforcement learning in synthetic gene circuits.

2020

Synthetic gene circuits allow programming in DNA the expression of a phenotype at a given environmental condition. The recent integration of memory systems with gene circuits opens the door to their adaptation to new conditions and their re-programming. This lays the foundation to emulate neuromorphic behaviour and solve complex problems similarly to artificial neural networks. Cellular products such as DNA or proteins can be used to store memory in both digital and analog formats, allowing cells to be turned into living computing devices able to record information regarding their previous states. In particular, synthetic gene circuits with memory can be engineered into living systems to al…

0303 health sciencesArtificial neural networkComputer scienceQH02 engineering and technologyDNA021001 nanoscience & nanotechnologyQ1BiochemistryExpression (mathematics)Living systems03 medical and health sciencesComputingMethodologies_PATTERNRECOGNITIONNeuromorphic engineeringSynthetic geneHuman–computer interactionArtificial IntelligenceGenes SyntheticReinforcement learningQDGene Regulatory Networks0210 nano-technologyAdaptation (computer science)030304 developmental biologyElectronic circuitBiochemical Society transactions
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Multisite field potential recordings and analysis of the impulse propagation pattern in cardiac cells culture

2007

To provide further insights into the impulse propagation between cardiac myocytes, we performed multiparametric studies of excitation spread with cellular resolution in confluent monolayers of cultured cardiomyocytes (CM). Simultaneous paired intracellular recordings of action potentials in two individual CM revealed slight periodic spontaneous advances/delays in the interspike time lag. Multisite field potential recordings performed with microelectrode arrays (MEA) confirmed random and iterative cycle-to-cycle changes in the direction of excitation spread. These local spontaneous variations in the cardiac impulse propagation pathways may be a safety process protecting against microscopical…

0303 health sciencesMaterials sciencemedicine.diagnostic_test[SDV]Life Sciences [q-bio]Propagation patternTime lagDiscontinuous conduction030204 cardiovascular system & hematologyImpulse (physics)03 medical and health sciencesMicroelectrode[SPI]Engineering Sciences [physics]0302 clinical medicineCellular resolutionmedicineMyocyte[NLIN]Nonlinear Sciences [physics]ElectrocardiographyComputingMilieux_MISCELLANEOUS030304 developmental biologyBiomedical engineering
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Defining classifier regions for WSD ensembles using word space features

2006

Based on recent evaluation of word sense disambiguation (WSD) systems [10], disambiguation methods have reached a standstill. In [10] we showed that it is possible to predict the best system for target word using word features and that using this 'optimal ensembling method' more accurate WSD ensembles can be built (3-5% over Senseval state of the art systems with the same amount of possible potential remaining). In the interest of developing if more accurate ensembles, w e here define the strong regions for three popular and effective classifiers used for WSD task (Naive Bayes – NB, Support Vector Machine – SVM, Decision Rules – D) using word features (word grain, amount of positive and neg…

0303 health sciencesProbability learningWord-sense disambiguationComputer sciencebusiness.industryPattern recognition02 engineering and technologyDecision ruleSupport vector machine03 medical and health sciencesNaive Bayes classifier0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingStatistical analysisArtificial intelligencePolysemybusinessClassifier (UML)030304 developmental biology
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Betweenness Centrality for Networks with Non-Overlapping Community Structure

2018

Evaluating the centrality of nodes in complex networks is one of the major research topics being explored due to its wide range of applications. Among the various measures that have been developed over the years, Betweenness centrality is one of the most popular. Indeed, it has proved to be efficient in many real-world situations. In this paper, we propose an extension of the Betweenness centrality designed for networks with nonoverlapping community structure. It is a linear combination of the so-called “local” and “global” Betweenness measures. The Local measure takes into account the influence of a node at the community level while the global measure depends only on the interactions betwe…

0303 health sciencesTheoretical computer scienceComputer scienceNode (networking)Community structure[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Scale (descriptive set theory)Complex network01 natural sciencesMeasure (mathematics)010305 fluids & plasmas03 medical and health sciencesBetweenness centrality0103 physical sciencesCentralityLinear combinationComputingMilieux_MISCELLANEOUS030304 developmental biology
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Building an Optimal WSD Ensemble Using Per-Word Selection of Best System

2006

In Senseval workshops for evaluating WSD systems [1,4,9], no one system or system type (classifier algorithm, type of system ensemble, extracted feature set, lexical knowledge source etc.) has been discovered that resolves all ambiguous words into their senses in a superior way. This paper presents a novel method for selecting the best system for target word based on readily available word features (number of senses, average amount of training per sense, dominant sense ratio). Applied to Senseval-3 and Senseval-2 English lexical sample state-of-art systems, a net gain of approximately 2.5 – 5.0% (respectively) in average precision per word over the best base system is achieved. The method c…

0303 health sciencesWord-sense disambiguationComputer scienceSample (material)Speech recognition02 engineering and technologyBase (topology)SemanticsSupport vector machine03 medical and health sciencesPattern recognition (psychology)Classifier (linguistics)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingWord (computer architecture)030304 developmental biology
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Efficient Online Laplacian Eigenmap Computation for Dimensionality Reduction in Molecular Phylogeny via Optimisation on the Sphere

2019

Reconstructing the phylogeny of large groups of large divergent genomes remains a difficult problem to solve, whatever the methods considered. Methods based on distance matrices are blocked due to the calculation of these matrices that is impossible in practice, when Bayesian inference or maximum likelihood methods presuppose multiple alignment of the genomes, which is itself difficult to achieve if precision is required. In this paper, we propose to calculate new distances for randomly selected couples of species over iterations, and then to map the biological sequences in a space of small dimension based on the partial knowledge of this genome similarity matrix. This mapping is then used …

0303 health sciences[STAT.AP]Statistics [stat]/Applications [stat.AP]Computer scienceDimensionality reductionComputationDimension (graph theory)Complete graphMinimum spanning treeBayesian inferenceQuantitative Biology::Genomics03 medical and health sciencesComputingMethodologies_PATTERNRECOGNITION0302 clinical medicine[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]Algorithm030217 neurology & neurosurgeryEigenvalues and eigenvectorsDistance matrices in phylogenyComputingMilieux_MISCELLANEOUS030304 developmental biology
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genuMet: distinguish genuine untargeted metabolic features without quality control samples

2019

AbstractMotivationLarge-scale untargeted metabolomics experiments lead to detection of thousands of novel metabolic features as well as false positive artifacts. With the incorporation of pooled QC samples and corresponding bioinformatics algorithms, those measurement artifacts can be well quality controlled. However, it is impracticable for all the studies to apply such experimental design.ResultsWe introduce a post-alignment quality control method called genuMet, which is solely based on injection order of biological samples to identify potential false metabolic features. In terms of the missing pattern of metabolic signals, genuMet can reach over 95% true negative rate and 85% true posit…

0303 health sciencesbusiness.industryComputer sciencemedia_common.quotation_subject010401 analytical chemistryPattern recognition01 natural sciences0104 chemical sciences03 medical and health sciencesUntargeted metabolomicsQuality (business)Artificial intelligencebusinessMETABOLIC FEATURES030304 developmental biologymedia_common
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