Search results for "Machine"

showing 10 items of 2592 documents

Strain gradient elasticity within the symmetric BEM formulation

2014

The symmetric Galerkin Boundary Element Method is used to address a class of strain gradient elastic materials featured by a free energy function of the (classical) strain and of its (first) gradient. With respect to the classical elasticity, additional response variables intervene, such as the normal derivative of the displacements on the boundary, and the work-coniugate double tractions. The fundamental solutions - featuring a fourth order partial differential equations (PDEs) system - exhibit singularities which in 2D may be of the order 1/ r 4 . New techniques are developed, which allow the elimination of most of the latter singularities. The present paper has to be intended as a resear…

Partial differential equationStrain gradient elasticity Symmetric Galerkin BEM.Mechanical Engineeringlcsh:Mechanical engineering and machineryStrain gradient elasticityMathematical analysislcsh:TA630-695Symmetric Galerkin BEMlcsh:Structural engineering (General)Directional derivativeStrain gradientFourth orderMechanics of MaterialsGravitational singularitylcsh:TJ1-1570Elasticity (economics)Galerkin methodSettore ICAR/08 - Scienza Delle CostruzioniBoundary element methodStrain gradient elasticity; Symmetric Galerkin BEM.MathematicsFrattura ed Integrità Strutturale
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Pascal and the question of technique

2017

The purpose of the essay is to discuss some implications of Pascal's philosophical discourse on the problem of technique and his rejections of Cartesian metaphysics. Author shows a singular perspective about technic in Blaise Pascal's philosophy. This perspective marks the difference with Descartes, linking technic to hearth and memory.

PascalMachineTechniqueHeartSettore M-FIL/01 - Filosofia TeoreticaPascal Technic Descartes Hearth Heidegger.
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Identifying the primary site of origin of MRI brain metastases from lung and breast cancer following a 2D radiomics approach

2017

Detection of brain metastases in patients with undiagnosed primary cancer is unusual but still an existing phenomenon. In these cases, identifying the cancer site of origin is non-feasible by visual examination of magnetic resonance (MR) images. Recently, radiomics has been proposed to analyze differences among classes of visually imperceptible imaging characteristics. In this study we analyzed 46 T1-weighted MR images of brain metastases from 29 patients: 29 of lung and 17 of breast origin. A total of 43 radiomics texture features were extracted from the metastatic lesions. Support vector machine (SVM) and k-nearest neighbors (k-NN) classifiers were implemented to evaluate the classificati…

Pathologymedicine.medical_specialtyLungmedicine.diagnostic_testbusiness.industryFeature extractionCancerMagnetic resonance imagingmedicine.disease030218 nuclear medicine & medical imagingSupport vector machine03 medical and health sciences0302 clinical medicineBreast cancermedicine.anatomical_structureRadiomicsmedicineRadiologybusinessQuantization (image processing)030217 neurology & neurosurgery2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)
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Support vector machine classification of brain metastasis and radiation necrosis based on texture analysis in MRI

2015

Purpose To develop a classification model using texture features and support vector machine in contrast-enhanced T1-weighted images to differentiate between brain metastasis and radiation necrosis. Methods Texture features were extracted from 115 lesions: 32 of them previously diagnosed as radiation necrosis, 23 as radiation-treated metastasis and 60 untreated metastases; including a total of 179 features derived from six texture analysis methods. A feature selection technique based on support vector machine was used to obtain a subset of features that provide optimal performance. Results The highest classification accuracy evaluated over test sets was achieved with a subset of ten features…

Pathologymedicine.medical_specialtymedicine.diagnostic_testReceiver operating characteristicbusiness.industryMagnetic resonance imagingPattern recognitionFeature selectionmedicine.diseaseMetastasisSupport vector machineRadiation necrosismedicineRadiology Nuclear Medicine and imagingArtificial intelligencebusinessClassifier (UML)Brain metastasisJournal of Magnetic Resonance Imaging
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Bagging, bumping, multiview, and active learning for record linkage with empirical results on patient identity data

2011

Record linkage or deduplication deals with the detection and deletion of duplicates in and across files. For this task, this paper introduces and evaluates two new machine-learning methods (bumping and multiview) together with bagging, a tree-based ensemble-approach. Whereas bumping represents a tree-based approach as well, multiview is based on the combination of different methods and the semi-supervised learning principle. After providing a theoretical background of the methods, initial empirical results on patient identity data are given. In the empirical evaluation, we calibrate the methods on three different kinds of training data. The results show that the smallest training data set, …

Patient Identification SystemsTraining setComputer scienceActive learning (machine learning)business.industryHealth InformaticsEmpirical Researchcomputer.software_genreMachine learningComputer Science ApplicationsTask (project management)Set (abstract data type)Tree (data structure)Artificial IntelligenceIdentity (object-oriented programming)HumansBumpingMedical Record LinkageArtificial intelligenceData miningbusinesscomputerSoftwareRecord linkageComputer Methods and Programs in Biomedicine
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On the Construction of Optimum Categories in Biomedical Data Recognition Problems

1979

The recognition of patterns within sets of biomedical data involves the following problems: a) Proper recording of the data to be used b) Extraction of suitable features c) Choice of categories or classes which are relevant to the medical decision task d) Estimation of the underlying distributions in the case of using parametric methods e) Choice of an adequate classification rule Whereas a lot of theories and procedures exists for most of these steps — particularly in the field of computer-aided differential diagnosis of electrocardiograms (ECG) (see [6]) — there has been only rare considerations on the problems of definition of appropriate categories.

Pattern vectorComputer sciencebusiness.industryQuadratic classifierMachine learningcomputer.software_genreField (computer science)Task (project management)Biomedical dataClassification ruleParametric methodsArtificial intelligencebusinesscomputer
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Effect of Morphology and Size of Halloysite Nanotubes on Functional Pectin Bionanocomposites for Food Packaging Applications

2017

Pectin bionanocomposite films filled with various concentrations of two different types of halloysite nanotubes were prepared and characterized in this study as potential films for food packaging applications. The two types of halloysite nanotubes were long and thin (patch) (200-30 000 nm length) and short and stubby (Matauri Bay) (50-3000 nm length) with different morphological, physical, and dispersibility properties. Both matrix (pectin) and reinforcer (halloysite nanotubes) used in this study are considered as biocompatible, natural, and low-cost materials. Various characterization tests including Fourier transform infrared spectroscopy, field emission scanning electron microscopy, rele…

PectinScanning electron microscopeHalloysite nanotube02 engineering and technology01 natural sciencesPackaging machineContact angleBionanocompositeHeat resistanceGeneral Materials ScienceComposite materialSettore CHIM/02 - Chimica FisicapectinNanotubesYarn Antimicrobial filmFourier transform infrared spectroscopypatch halloysiteSalicylic acidDynamic mechanical analysis021001 nanoscience & nanotechnologyReinforcementPackagingPolyethylenepectin Kaoliniteantimicrobial filmPectinsAluminum SilicatesBiocompatibility0210 nano-technologyScanning electron microscopyMicroorganismMaterials sciencefood.ingredientBiocompatibilityengineering.materialDynamic mechanical analysi010402 general chemistryHalloysiteFood packagingfoodUltimate tensile strengthFourier transform infrared spectroscopyContact angleBacteriaField emission microscopeFunctional foodthermal resistanceHalloysite0104 chemical sciencesNanotubeBiological materialengineeringClayACS Applied Materials & Interfaces
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A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a re…

2021

Introduction Outcome predictions of patients with congenital diaphragmatic hernia (CDH) still have some limitations in the prenatal estimate of postnatal pulmonary hypertension (PH). We propose applying Machine Learning (ML), and Deep Learning (DL) approaches to fetuses and newborns with CDH to develop forecasting models in prenatal epoch, based on the integrated analysis of clinical data, to provide neonatal PH as the first outcome and, possibly: favorable response to fetal endoscopic tracheal occlusion (FETO), need for Extracorporeal Membrane Oxygenation (ECMO), survival to ECMO, and death. Moreover, we plan to produce a (semi)automatic fetus lung segmentation system in Magnetic Resonanc…

Pediatricsmedicine.medical_treatmentretrospective studyDiagnostic RadiologyCohort StudiesStudy ProtocolMathematical and Statistical TechniquesPregnancyMedicine and Health SciencesLung volumesMultidisciplinarymedicine.diagnostic_testRadiology and ImagingStatisticsQRSoftware EngineeringMagnetic Resonance ImagingPulmonary Imagingmachine learningObstetric ProceduresPhysical SciencesEngineering and TechnologyMedicineFemaleCohort studyComputer and Information Sciencesmedicine.medical_specialtyImaging TechniquesHypertension PulmonaryScienceSurgical and Invasive Medical ProceduresResearch and Analysis MethodsPulmonary hypertensionComputer SoftwareDiagnostic MedicineArtificial IntelligenceCongenital Diaphragmatic Hernia Pulmonary Ipertension Deep Learning protocolmedicineExtracorporeal membrane oxygenationHumansHerniaStatistical MethodsRetrospective StudiesFetal surgerybusiness.industrydiaphragmatic herniasegmentationInfant NewbornBiology and Life SciencesNeonatesCongenital diaphragmatic herniadeep learningRetrospective cohort studyMagnetic resonance imagingmedicine.diseaseSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Hernias Diaphragmatic CongenitalbusinessMathematicsDevelopmental BiologyForecasting
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On the use of a laboratory-scale Pelton wheel water turbine in renewable energy education

2008

Abstract A laboratory-scale Pelton turbine for hydroelectric generation has been constructed and used in the educational curriculum of The Renewable Energy Programme at the University of Jyvaskyla. The construction of the Pelton turbine, the experimental apparatus and the measurement procedure are described. The apparatus is simple to make and uses inexpensive components, most of which can be found in standard science laboratories. From the experimental results, the turbine was found to have a maximum mechanical efficiency of 0.47 ± 0.02 for a water flow rate of 0.17 l / s . The Pelton turbine and apparatus demonstrate the principles of hydropower and are well suited for education in renewa…

Pelton wheelEngineeringRenewable Energy Sustainability and the Environmentbusiness.industryWater flowWater turbineMechanical engineeringHydraulic machineryLaboratory scalebusinessTurbineHydropowerRenewable energyRenewable Energy
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Hyperspectral system for early detection of rottenness caused by Penicillium digitatum in mandarins

2008

Abstract Nowadays, the detection of fruit infected with Penicillium sp. fungi on packing lines is carried out manually under ultraviolet illumination. Ultraviolet sources induce visible fluorescence of essential oils, present in the skin of citrus and which are released by the action of fungi, thus increasing the contrast between sound and rotten skin. This work analyses a set of techniques aimed at detecting rotten citrus without the use of UV lighting. The techniques used include hyperspectral image acquisition, pre-processing and calibration, feature selection and segmentation using linear and non-linear methods for classification of fruits. Different methods such as correlation analysis…

Penicillium digitatumbiologybusiness.industryMachine visionHyperspectral imagingFeature selectionPattern recognitionMutual informationImage segmentationbiology.organism_classificationLinear discriminant analysisComputer visionSegmentationArtificial intelligencebusinessFood ScienceMathematics
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