Search results for " mining"

showing 10 items of 1548 documents

Boosting Design Space Explorations with Existing or Automatically Learned Knowledge

2012

During development, processor architectures can be tuned and configured by many different parameters. For benchmarking, automatic design space explorations (DSEs) with heuristic algorithms are a helpful approach to find the best settings for these parameters according to multiple objectives, e.g. performance, energy consumption, or real-time constraints. But if the setup is slightly changed and a new DSE has to be performed, it will start from scratch, resulting in very long evaluation times. To reduce the evaluation times we extend the NSGA-II algorithm in this article, such that automatic DSEs can be supported with a set of transformation rules defined in a highly readable format, the fuz…

Boosting (machine learning)Fuzzy ruleFuzzy Control LanguageComputer scienceDecision treeBenchmarkingData miningEnergy consumptionGridcomputer.software_genreMulti-objective optimizationcomputercomputer.programming_language
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Evaluation of Record Linkage Methods for Iterative Insertions

2009

Summary Objectives: There have been many developments and applications of mathematical methods in the context of record linkage as one area of interdisciplinary research efforts. However, comparative evaluations of record linkage methods are still underrepresented. In this paper improvements of the Fellegi-Sunter model are compared with other elaborated classification methods in order to direct further research endeavors to the most promising methodologies. Methods: The task of linking records can be viewed as a special form of object identification. We consider several non-stochastic methods and procedures for the record linkage task in addition to the Fellegi-Sunter model and perform an e…

Boosting (machine learning)Medical Records Systems ComputerizedComputer scienceDecision treeHealth Informaticscomputer.software_genreMachine learningFuzzy LogicHealth Information ManagementGermanyExpectation–maximization algorithmHumansRegistriesAdvanced and Specialized NursingElectronic Data ProcessingModels Statisticalbusiness.industryData CollectionDecision TreesSupport vector machineClassification methodsMedical Record LinkageData miningArtificial intelligencebusinesscomputerAlgorithmsSoftwareRecord linkageMethods of Information in Medicine
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Improving clustering of Web bot and human sessions by applying Principal Component Analysis

2019

View references (18) The paper addresses the problem of modeling Web sessions of bots and legitimate users (humans) as feature vectors for their use at the input of classification models. So far many different features to discriminate bots’ and humans’ navigational patterns have been considered in session models but very few studies were devoted to feature selection and dimensionality reduction in the context of bot detection. We propose applying Principal Component Analysis (PCA) to develop improved session models based on predictor variables being efficient discriminants of Web bots. The proposed models are used in session clustering, whose performance is evaluated in terms of the purity …

Bot detectionPrincipal Component AnalysisPCALog analysisComputer sciencek-meansInternet robotcomputer.software_genreClassificationWeb botDimensionality reductionClusteringWeb serverPrincipal component analysisFeature selectionData miningCluster analysiscomputerCommunications of the ECMS
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Functional connectivity inference from fMRI data using multivariate information measures

2022

Abstract Shannon’s entropy or an extension of Shannon’s entropy can be used to quantify information transmission between or among variables. Mutual information is the pair-wise information that captures nonlinear relationships between variables. It is more robust than linear correlation methods. Beyond mutual information, two generalizations are defined for multivariate distributions: interaction information or co-information and total correlation or multi-mutual information. In comparison to mutual information, interaction information and total correlation are underutilized and poorly studied in applied neuroscience research. Quantifying information flow between brain regions is not explic…

Brain MappingComputer scienceEntropyCognitive NeuroscienceConditional mutual informationBrainMultivariate normal distributionMutual informationcomputer.software_genreMagnetic Resonance ImagingInteraction informationRedundancy (information theory)Artificial IntelligenceEntropy (information theory)Computer SimulationTotal correlationInformation flow (information theory)Data miningcomputerNeural Networks
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Post-task Effects on EEG Brain Activity Differ for Various Differential Learning and Contextual Interference Protocols

2017

A large body of research has shown superior learning rates in variable practice compared to repetitive practice. More specifically, this has been demonstrated in the contextual interference (CI) and in the differential learning (DL) approach that are both representatives of variable practice. Behavioral studies have indicate different learning processes in CI and DL. Aim of the present study was to examine immediate post-task effects on electroencephalographic (EEG) brain activation patterns after CI and DL protocols that reveal underlying neural processes at the early stage of motor consolidation. Additionally, we tested two DL protocols (gradual DL, chaotic DL) to examine the effect of di…

Brain activity and meditationAlpha (ethology)ElectroencephalographySomatosensory system050105 experimental psychologylcsh:RC321-57103 medical and health sciencesBehavioral Neuroscience0302 clinical medicineText miningMotor systemmedicinedifferential learning0501 psychology and cognitive sciencesEEGlcsh:Neurosciences. Biological psychiatry. NeuropsychiatryBiological PsychiatryOriginal Researchcontextual interferencemedicine.diagnostic_testbusiness.industryrepetitive learning05 social sciencesCortex (botany)Psychiatry and Mental healthNeuropsychology and Physiological PsychologyNeurologyPsychologyMotor learningbusinessNeurosciencemotor learning030217 neurology & neurosurgeryNeuroscienceFrontiers in Human Neuroscience
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Intraparenchymal Brain Hemorrhage: "Birdlime" Effect Usefulness.

2018

The authors previously reported the novel transposition techniquefor microvascular decompression (MVD) using a tissue glue-coated collagen sponge (TachoSil Tissue Sealing Sheet; CSLBehring KK, Tokyo, Japan) soaked withfibrin glue (Tisseel 2-Component Fibrin Sealant, Vapor-Heated; Baxter Healthcare,Glendale, California, USA), termed the“birdlime”technique

Brain hemorrhagePathologymedicine.medical_specialtybusiness.industrySettore MED/27 - NeurochirurgiaAdhesiveBrainMicrovascular Decompression SurgeryText miningAdhesivesMedicineHumansSurgeryNeurology (clinical)businessIntracranial HemorrhagesIntracranial HemorrhageHumanCerebral HemorrhageWorld neurosurgery
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Fast dendrogram-based OTU clustering using sequence embedding

2014

Biodiversity assessment is an important step in a metagenomic processing pipeline. The biodiversity of a microbial metagenome is often estimated by grouping its 16S rRNA reads into operational taxonomic units or OTUs. These metagenomic datasets are typically large and hence require effective yet accurate computational methods for processing.In this paper, we introduce a new hierarchical clustering method called CRiSPy-Embed which aims to produce high-quality clustering results at a low computational cost. We tackle two computational issues of the current OTU hierarchical clustering approach: (1) the compute-intensive sequence alignment operation for building the distance matrix and (2) the …

Brown clusteringCURE data clustering algorithmSingle-linkage clusteringCorrelation clusteringCanopy clustering algorithmData miningBiologyHierarchical clustering of networksCluster analysiscomputer.software_genrecomputerHierarchical clusteringProceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics
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Biosynthesis of Sinapigladioside, an Antifungal Isothiocyanate from Burkholderia Symbionts

2021

Abstract Sinapigladioside is a rare isothiocyanate‐bearing natural product from beetle‐associated bacteria (Burkholderia gladioli) that might protect beetle offspring against entomopathogenic fungi. The biosynthetic origin of sinapigladioside has been elusive, and little is known about bacterial isothiocyanate biosynthesis in general. On the basis of stable‐isotope labeling, bioinformatics, and mutagenesis, we identified the sinapigladioside biosynthesis gene cluster in the symbiont and found that an isonitrile synthase plays a key role in the biosynthetic pathway. Genome mining and network analyses indicate that related gene clusters are distributed across various bacterial phyla including…

Burkholderia gladioliAntifungal AgentsBurkholderianatural productsMolecular ConformationMutagenesis (molecular biology technique)Microbial Sensitivity Tests010402 general chemistry01 natural sciencesBiochemistrychemistry.chemical_compoundBiosynthesisVery Important PaperIsothiocyanatesGene clustergenome miningBacterial phylaMolecular Biologybiology010405 organic chemistryCommunicationOrganic Chemistrybiology.organism_classificationCommunications0104 chemical sciencesBiosynthetic PathwaysBurkholderiaBiochemistrychemistryIsothiocyanateHypocrealesMolecular MedicinebiosynthesisisothiocyanateBacteriaChembiochem
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Insect-associated bacteria assemble the antifungal butenolide gladiofungin by non-canonical polyketide chain termination

2020

Abstract Genome mining of one of the protective symbionts (Burkholderia gladioli) of the invasive beetle Lagria villosa revealed a cryptic gene cluster that codes for the biosynthesis of a novel antifungal polyketide with a glutarimide pharmacophore. Targeted gene inactivation, metabolic profiling, and bioassays led to the discovery of the gladiofungins as previously‐overlooked components of the antimicrobial armory of the beetle symbiont, which are highly active against the entomopathogenic fungus Purpureocillium lilacinum. By mutational analyses, isotope labeling, and computational analyses of the modular polyketide synthase, we found that the rare butenolide moiety of gladiofungins deriv…

Burkholderia gladioliAntifungal AgentsBurkholderianatural productsantifungal compoundsMicrobial Sensitivity TestsBiosynthesis010402 general chemistry01 natural sciencesCatalysisPurpureocillium lilacinumPolyketide4-ButyrolactonePolyketide synthasegenome miningGene clusterAnimalsButenolidebiology010405 organic chemistryCommunicationGeneral Chemistrybiology.organism_classificationCommunications0104 chemical sciencesColeopteraBiochemistryPolyketidesHypocrealesbiology.proteinLactimidomycinPharmacophore
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Domain-Specific Characteristics of Data Quality

2017

The research discusses the issue how to describe data quality and what should be taken into account when developing an universal data quality management solution. The proposed approach is to create quality specifications for each kind of data objects and to make them executable. The specification can be executed step-by-step according to business process descriptions, ensuring the gradual accumulation of data in the database and data quality checking according to the specific use case. The described approach can be applied to check the completeness, accuracy, timeliness and consistency of accumulated data.

Business processComputer sciencecomputer.file_formatcomputer.software_genreElectronic mailData modelingUnified Modeling LanguageData qualityData miningExecutableCompleteness (statistics)Data objectscomputercomputer.programming_languageProceedings of the 2017 Federated Conference on Computer Science and Information Systems
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