Search results for " mac"

showing 10 items of 3066 documents

Sparse Deconvolution Using Support Vector Machines

2008

Sparse deconvolution is a classical subject in digital signal processing, having many practical applications. Support vector machine (SVM) algorithms show a series of characteristics, such as sparse solutions and implicit regularization, which make them attractive for solving sparse deconvolution problems. Here, a sparse deconvolution algorithm based on the SVM framework for signal processing is presented and analyzed, including comparative evaluations of its performance from the points of view of estimation and detection capabilities, and of robustness with respect to non-Gaussian additive noise. Publicado

Blind deconvolutionSignal processingTelecomunicacionesSparse deconvolutionSupport vector machinesDual modelsbusiness.industryComputer sciencelcsh:ElectronicsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONlcsh:TK7800-8360Pattern recognitionSparse approximationRegularization (mathematics)lcsh:TelecommunicationSupport vector machineRobustness (computer science)lcsh:TK5101-6720Sysmology3325 Tecnología de las TelecomunicacionesArtificial intelligenceDeconvolutionbusinessDigital signal processing
researchProduct

On the decomposition of prefix codes

2017

Abstract In this paper we focus on the decomposition of rational and maximal prefix codes. We present an effective procedure that allows us to decide whether such a code is decomposable. In this case, the procedure also produces the factors of some of its decompositions. We also give partial results on the problem of deciding whether a rational maximal prefix code decomposes over a finite prefix code.

Block codePrefix codeGeneral Computer ScienceComputer science0102 computer and information sciences02 engineering and technologyPrefix grammarKraft's inequality01 natural sciencesPrefix codeTheoretical Computer SciencePrefix codes; Finite automata; Composition of codesComposition of codes0202 electrical engineering electronic engineering information engineeringDiscrete mathematicsSelf-synchronizing codeFinite-state machineSettore INF/01 - InformaticaComputer Science (all)Rational languageLinear codePrefixComposition of code010201 computation theory & mathematicsPrefix codes020201 artificial intelligence & image processingFinite automataComputer Science::Formal Languages and Automata Theory
researchProduct

Time course of changes in serum glucose, insulin, lipids and tissue lipase activities in macrosomic offspring of rats with streptozotocin-induced dia…

1999

The aim of this investigation was to determine the time course of changes in serum glucose, insulin and lipid levels, as well as lipid and protein content and lipolytic activities in insulin target organs (liver, adipose tissue and muscle), in macrosomic offspring of streptozotocin-induced mildly hyperglycaemic rats. Food intake and nutritional efficiency were also evaluated. Mild hyperglycaemia in pregnant rats was induced by intraperitoneal injection of streptozotocin (40 mg/kg body weight) on day 5 of gestation. Control pregnant rats were injected with citrate buffer. At birth, macrosomic pups (birth weight > 1.7 S.D. greater than the mean value for the control pups) had higher serum …

Blood GlucoseMalemedicine.medical_specialtyTime Factorsmedicine.medical_treatmentLipolysisAdipose tissueBiologyDiabetes Mellitus ExperimentalFetal Macrosomiachemistry.chemical_compoundEatingInsulin resistanceSex FactorsDiabetes mellitusAdipocyteInternal medicinemedicineFetal macrosomiaAnimalsInsulinObesityRats WistarMuscle SkeletalInsulinLipid metabolismGeneral MedicineLipasemedicine.diseaseStreptozotocinLipidsRatsEndocrinologychemistryAdipose TissueLiverFemalemedicine.drugClinical science (London, England : 1979)
researchProduct

Modulation of lipid metabolism by n-3 polyunsaturated fatty acids in gestational diabetic rats and their macrosomic offspring.

2005

The time course of changes in lipid metabolism by dietary n−3 PUFAs (polyunsaturated fatty acids) in streptozotocin-induced diabetic rats during pregnancy (days 12 and 21) and their macrosomic offspring at birth (day 0) and through adulthood (days 60 and 90) was studied with respect to adipose tissue, liver and serum lipid concentrations, and fatty acid composition. Glucose and insulin levels were also assessed in order to characterize the diabetic state of macrosomic offspring. Pregnant diabetic and control rats were fed either an Isio-4 or EPAX diet (enriched with n−3 PUFA). The same diets were also consumed by pups at weaning. Compared with control rats, during pregnancy diabetic rats ha…

Blood Glucosemedicine.medical_specialtyOffspringmedicine.medical_treatmentBiologyDiabetes Mellitus ExperimentalFetal Macrosomiachemistry.chemical_compoundDietary Fats UnsaturatedPregnancyDiabetes mellitusInternal medicinemedicineAnimalsInsulinRats Wistarchemistry.chemical_classificationTriglycerideCholesterolInsulinBody WeightLipid metabolismGeneral MedicineOrgan Sizemedicine.diseaseLipid MetabolismRatsDiabetes GestationalEndocrinologychemistryAdipose TissueAnimals NewbornLiverDocosahexaenoic acidlipids (amino acids peptides and proteins)FemalePolyunsaturated fatty acidClinical science (London, England : 1979)
researchProduct

Processing of rock core microtomography images: Using seven different machine learning algorithms

2016

The abilities of machine learning algorithms to process X-ray microtomographic rock images were determined. The study focused on the use of unsupervised, supervised, and ensemble clustering techniques, to segment X-ray computer microtomography rock images and to estimate the pore spaces and pore size diameters in the rocks. The unsupervised k-means technique gave the fastest processing time and the supervised least squares support vector machine technique gave the slowest processing time. Multiphase assemblages of solid phases (minerals and finely grained minerals) and the pore phase were found on visual inspection of the images. In general, the accuracy in terms of porosity values and pore…

Boosting (machine learning)010504 meteorology & atmospheric sciencesComputer performanceComputer sciencebusiness.industryFeature vectorPattern recognition010502 geochemistry & geophysics01 natural sciencesFuzzy logicSupport vector machineComputingMethodologies_PATTERNRECOGNITIONLeast squares support vector machineArtificial intelligenceComputers in Earth SciencesCluster analysisPorositybusiness0105 earth and related environmental sciencesInformation SystemsComputers & Geosciences
researchProduct

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
researchProduct

Real-time flaw detection on a complex object: comparison of results using classification with a support vector machine, boosting, and hyperrectangle-…

2006

We present a classification work performed on industrial parts using artificial vision, a support vector machine (SVM), boost- ing, and a combination of classifiers. The object to be controlled is a coated heater used in television sets. Our project consists of detect- ing anomalies under manufacturer production, as well as in classi- fying the anomalies among 20 listed categories. Manufacturer speci- fications require a minimum of ten inspections per second without a decrease in the quality of the produced parts. This problem is ad- dressed by using a classification system relying on real-time ma- chine vision. To fulfill both real-time and quality constraints, three classification algorit…

Boosting (machine learning)business.industryComputer scienceMachine visionFeature extractionDecision treeFeature selectionPattern recognitionMachine learningcomputer.software_genreAtomic and Molecular Physics and OpticsComputer Science ApplicationsSupport vector machineStatistical classificationHyperrectangleComputingMethodologies_PATTERNRECOGNITIONArtificial intelligenceElectrical and Electronic EngineeringbusinesscomputerJournal of Electronic Imaging
researchProduct

A COLLABORATIVE VIRTUAL REALITY ENVIRONMENT FOR NEUROSURGICAL PLANNING AND TRAINING

2007

OBJECTIVE We have developed a highly interactive virtual environment that enables collaborative examination of stereoscopic three-dimensional (3-D) medical imaging data for planning, discussing, or teaching neurosurgical approaches and strategies. MATERIALS AND METHODS The system consists of an interactive console with which the user manipulates 3-D data using hand-held and tracked devices within a 3-D virtual workspace and a stereoscopic projection system. The projection system displays the 3-D data on a large screen while the user is working with it. This setup allows users to interact intuitively with complex 3-D data while sharing this information with a larger audience. RESULTS We have…

Brain Diseasesbusiness.industryEducational TechnologyNeurosurgeryComputer-Assisted InstructionStereoscopyPlan (drawing)Virtual realitycomputer.software_genrelaw.inventionImaging Three-DimensionallawHuman–computer interactionVirtual machineMedical imagingHumansMedicineComputer SimulationSurgeryNeurology (clinical)businessProjection (set theory)computerComputer-Assisted InstructionInstructional simulationOperative Neurosurgery
researchProduct

A Neuroprotective Function for the Hematopoietic Protein Granulocyte-Macrophage Colony Stimulating Factor (GM-CSF)

2007

Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a hematopoietic cytokine responsible for the proliferation, differentiation, and maturation of cells of the myeloid lineage, which was cloned more than 20 years ago. Here we uncovered a novel function of GM-CSF in the central nervous system (CNS). We identified the GM-CSF α-receptor as an upregulated gene in a screen for ischemia-induced genes in the cortex. This receptor is broadly expressed on neurons throughout the brain together with its ligand and induced by ischemic insults. In primary cortical neurons and human neuroblastoma cells, GM-CSF counteracts programmed cell death and induces BCL-2 and BCL-Xl expression in a dose- a…

Brain InfarctionMaleProgrammed cell deathTime FactorsMyeloidmedicine.medical_treatmentDrug Evaluation Preclinicalbcl-X ProteinApoptosisBiologyNeuroprotectionBrain IschemiaPhosphatidylinositol 3-KinasesmedicineAnimalsHumansMyeloid CellsRats Long-EvansRats WistarProtein kinase BCell ProliferationCerebral CortexNeuronsDose-Response Relationship DrugGrowth factorGranulocyte-Macrophage Colony-Stimulating FactorCell DifferentiationNeurodegenerative DiseasesRatsUp-RegulationCell biologyDisease Models AnimalHaematopoiesisNeuroprotective Agentsmedicine.anatomical_structureGranulocyte macrophage colony-stimulating factorNeurologyBlood-Brain BarrierReceptors Granulocyte-Macrophage Colony-Stimulating FactorImmunologyNeurology (clinical)Signal transductionCardiology and Cardiovascular MedicineProto-Oncogene Proteins c-aktSignal Transductionmedicine.drugJournal of Cerebral Blood Flow & Metabolism
researchProduct

Mutual information-based feature selection for low-cost BCIs based on motor imagery

2016

In the present study a feature selection algorithm based on mutual information (MI) was applied to electro-encephalographic (EEG) data acquired during three different motor imagery tasks from two dataset: Dataset I from BCI Competition IV including full scalp recordings from four subjects, and new data recorded from three subjects using the popular low-cost Emotiv EPOC EEG headset. The aim was to evaluate optimal channels and band-power (BP) features for motor imagery tasks discrimination, in order to assess the feasibility of a portable low-cost motor imagery based Brain-Computer Interface (BCI) system. The minimal sub set of features most relevant to task description and less redundant to…

Brain-Computer InterfaceSupport Vector MachineDatabases FactualComputer scienceHeadsetSpeech recognitionFeature extractionBiomedical EngineeringReproducibility of ResultHealth InformaticsFeature selection02 engineering and technologyElectroencephalography03 medical and health sciences0302 clinical medicineMotor imagery0202 electrical engineering electronic engineering information engineeringmedicineHumans1707medicine.diagnostic_testbusiness.industryReproducibility of ResultsElectroencephalographyPattern recognitionMutual informationModels TheoreticalAlgorithmSupport vector machineBrain-Computer InterfacesSignal ProcessingSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaEidetic Imagery020201 artificial intelligence & image processingArtificial intelligencebusinessAlgorithms030217 neurology & neurosurgeryHuman2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
researchProduct