Search results for "means"

showing 10 items of 124 documents

El derecho y la revolución copernicana de Marx (Notas para un derecho científico a partir de ·El orden de El capital", de Carlos Fernández Liria y Lu…

2012

Taking for granted that Marx’s economic theory enjoys a scientific status and, furthermore, that it installed a real Copernican revolution in sociology, the present paper explores the possibility of deriving a system of law deserving the name of “scientific” in so far as it would be in keeping with the theses of the latter scientific theory. In this context, the paper argues against a claim recently sustained by Fernandez Liria and Alegre Zahonero, for whom a system of right compatible with Marx’s theory would be compatible, too, with the classic juridical formulations conceived during the Enlightenment. The main reason why this paper testifies against such compatibility is that the enlight…

PhilosophyMeans of productionmedia_common.quotation_subjectPhilosophyRealmEnlightenmentSocial scienceSocial classScientific theoryHumanitiesAutonomySubject mattermedia_commonLogos. Anales del Seminario de Metafísica
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A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning

2017

The aim of this study is to combine Biological Target Volume (BTV) segmentation and Gross Target Volume (GTV) segmentation in stereotactic neurosurgery.Our goal is to enhance Clinical Target Volume (CTV) definition, including metabolic and morphologic information, for treatment planning and patient follow-up.We propose a fully automatic approach for multimodal PET and MR image segmentation. This method is based on the Random Walker (RW) and Fuzzy C-Means clustering (FCM) algorithms. A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is presented, considering volume…

Radiotherapy PlanningBrain tumorHealth Informatics02 engineering and technologyFuzzy C-means clusteringRadiosurgeryBrain tumorsMultimodal ImagingING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI030218 nuclear medicine & medical imaging03 medical and health sciencesComputer-Assisted0302 clinical medicineRandom walker algorithm0202 electrical engineering electronic engineering information engineeringHumansMedicineSegmentationComputer visionRadiation treatment planningCluster analysisImage resolutionPET/MR imagingModality (human–computer interaction)Brain Neoplasmsbusiness.industryRadiotherapy Planning Computer-AssistedINF/01 - INFORMATICAMultimodal therapymedicine.diseaseRandom Walker algorithmMagnetic Resonance ImagingComputer Science ApplicationsBrain tumorGamma knife treatmentPositron-Emission Tomography020201 artificial intelligence & image processingMultimodal image segmentationBrain tumors; Fuzzy C-means clustering; Gamma knife treatments; Multimodal image segmentation; PET/MR imaging; Random Walker algorithm; Brain Neoplasms; Humans; Radiosurgery; Magnetic Resonance Imaging; Multimodal Imaging; Positron-Emission Tomography; Radiotherapy Planning Computer-AssistedArtificial intelligencebusinessGamma knife treatmentsSoftware
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Condition Assessment and Analysis of Bearing of Doubly Fed Wind Turbines Using Machine Learning Technique

2023

Condition monitoring of wind turbines is progressively increasing to maintain the continuity of clean energy supply to power grids. This issue is of great importance since it prevents wind turbines from failing and overheating, as most wind turbines with doubly fed induction generators (DFIG) are overheated due to faults in generator bearings. Bearing fault detection has become a main topic targeting the optimum operation, unscheduled downtime, and maintenance cost of turbine generators. Wind turbines are equipped with condition monitoring devices. However, effective and reliable fault detection still faces significant difficulties. As the majority of health monitoring techniques are primar…

SCADA dataControl and OptimizationRenewable Energy Sustainability and the Environmentcondition monitoringEnergy Engineering and Power TechnologyBuilding and ConstructionSettore ING-IND/33 - Sistemi Elettrici Per L'Energiawind turbineDFIGbearingsbearings condition monitoring DFIG K means SCADA data wind turbineElectrical and Electronic EngineeringEngineering (miscellaneous)K meansEnergy (miscellaneous)Energies
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Automatic Detection of Hemangioma through a Cascade of Self-organizing Map Clustering and Morphological Operators

2016

Abstract In this paper we propose a method for the automatic detection of hemangioma regions, consisting of a cascade of algorithms: a Self Organizing Map (SOM) for clustering the image pixels in 25 classes (using a 5x5 output layer) followed by a morphological method of reducing the number of classes (MMRNC) to only two classes: hemangioma and non-hemangioma. We named this method SOM-MMRNC. To evaluate the performance of the proposed method we have used Fuzzy C-means (FCM) for comparison. The algorithms were tested on 33 images; for most images, the proposed method and FCM obtain similar overall scores, within one percent of each other. However, in about 18% of the cases, there is a signif…

Self-organizing mapComputer science050801 communication & media studies02 engineering and technologycomputer.software_genreFuzzy logicImage (mathematics)Hemangioma0508 media and communications0202 electrical engineering electronic engineering information engineeringmedicineLayer (object-oriented design)Cluster analysisFuzzy C-meansGeneral Environmental SciencePixelbusiness.industry05 social sciencesPattern recognitionmedicine.diseasehemangiomaCascadeGeneral Earth and Planetary Sciences020201 artificial intelligence & image processingArtificial intelligenceData miningbusinesscomputerSelf Organizing MapclusteringProcedia Computer Science
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Stable Automatic Unsupervised Segmentation of Retinal Vessels Using Self-Organizing Maps and a Modified Fuzzy C-Means Clustering

2011

In this paper an automatic unsupervised method for the segmentation of retinal vessels is proposed. Three features are extracted from the tested image. The features are scaled down by a factor of 2 and mapped into a Self-Organizing Map. A modified Fuzzy C-Means clustering algorithm is used to divide the neuron units of the map in 2 classes. The entire image is again input for the Self-Organizing Map and the class of each pixel will be the class of its best matching unit in the Self-Organizing Map. Finally, the vessel network is post-processed using a hill climbing strategy on the connected components of the segmented image. The experimental evaluation on the DRIVE database shows accurate ex…

Self-organizing mapGround truthPixelSettore INF/01 - Informaticabusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognitionFuzzy logicComputer visionSegmentationArtificial intelligenceCluster analysisbusinessHill climbingRetinal Vessels Self-Organizing Map Fuzzy C-Means.
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Automatic Unsupervised Segmentation of Retinal Vessels Using Self-Organizing Maps and K-Means Clustering

2011

In this paper an automatic unsupervised method for the segmentation of retinal vessels is proposed. A Self-Organizing Map is trained on a portion of the same image that is tested and K-means clustering algorithm is used to divide the map units in 2 classes. The entire image is again input for the Self-Organizing Map, and the class of each pixel will be the class of the best matching unit on the Self-Organizing Map. Finally, the vessel network is post-processed using a hill climbing strategy on the connected components of the segmented image. The experimental evaluation on the publicly available DRIVE database shows accurate extraction of vessels network and a good agreement between our segm…

Self-organizing mapGround truthSettore INF/01 - InformaticaPixelbusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONk-means clusteringScale-space segmentationPattern recognitionRetinal vessels Self-Organizing Map K-MeansSegmentationComputer visionArtificial intelligenceCluster analysisbusinessHill climbing
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The Hydrothermal System of Solfatara Crater (Campi Flegrei, Italy) Inferred From Machine Learning Algorithms

2019

Two machine learning algorithms were applied to three multivariate datasets acquired at Solfatara volcano. Our aim was to find an unbiased and coherent synthesis among the large amount of data acquired within the crater and along two orthogonal vertical NNE- and WNW-trending cross-sections. The first algorithm includes a new approach for a soft K-means clustering based on the use of the silhouette index to control the color palette of the clusters. The second algorithm which uses the self-organizing maps incorporates an alternative method for choosing the number of nodes of the neural network which aims to avoid the need for downstream clustering of the results of the classification. Both m…

Self-organizing mapMultivariate statistics010504 meteorology & atmospheric sciencesself-organizing maps010502 geochemistry & geophysicsMachine learningcomputer.software_genre01 natural sciencesSilhouetteImpact craterSolfataralcsh:ScienceCluster analysisK-means0105 earth and related environmental sciencesExploration geophysicsArtificial neural networkbusiness.industryk-means clusteringseismic methodsmachine learningGeneral Earth and Planetary Scienceslcsh:QArtificial intelligenceCampi FlegreibusinesscomputerAlgorithmGeologyFrontiers in Earth Science
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Hierarchical and non-hierarchical clustering methods to study students algebraic thinking in solving an open-ended questionnaire

2017

The problem of taking a data set and separating it into subgroups, where the members of each subgroup are more similar to each other than they are to members outside the subgroup, has been extensively studied in science and mathematics education research. Student responses to written questions and multiple-choice tests have been characterised and studied using several qualitative and/or quantitative analysis methods. However, there are inherent difficulties in the categorisation of student responses in the case of open-ended questionnaires. Very often, researcher bias means that the categories picked out tend to find the groups of students that the researcher is seeking out. In our contribu…

Settore FIS/08 - Didattica E Storia Della Fisicak-means methodAlgebraic thinking Clustering k-means method dendrogramsAlgebraic thinking[MATH] Mathematics [math][SHS] Humanities and Social SciencesSettore MAT/04 - Matematiche Complementari[MATH]Mathematics [math]dendrogramsComputingMilieux_MISCELLANEOUS[SHS]Humanities and Social Sciencesclustering
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Implementare il patrimonio archivistico: ricostruzione virtuale di una villa non realizzata di Giuseppe Samonà in Sicilia

2023

Questo saggio vuole essere una testimonianza dell’importanza culturale e cognitiva degli archivi (del progetto) intesi come patrimonio pubblico. L’azione di re-immaginarli può costituire un veicolo per la loro conoscenza? Con l’analisi di un caso-studio di un’abitazione non realizzata di un architetto del Novecento come Giuseppe Samonà si prova a verificare l’efficacia degli strumenti digitali per l’interpretazione dell’architettura come mezzi per l’implementazione comunicativa di un archivio.

Settore ICAR/17 - DisegnoThis essay is a testimony to the cultural and cognitive importance of (project) archives as public heritage. Can the action of re-imagining them be a vehicle for their knowledge? With the analysis of a case study of an unrealised house by a 20th century architect such as Giuseppe Samonà an attempt is made to verify the effectiveness of digital tools for the interpretation of architecture as a means for the communicative implementation of an archive.
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Fast Fingerprints Classification only using the Directional Image

2007

The classification phase is an important step of an automatic fingerprint identification system, where the goal is to restrict only to a subset of the whole database the search time. The proposed system classifies fingerprint images in four classes using only directional image information. This approach, unlike the literature approaches, uses the acquired fingerprint image without enhancement phases application. The system extracts only directional image and uses three concurrent decisional modules to classify the fingerprint. The proposed system has a high classification speed and a very low computational cost. The experimental results show a classification rate of 87.27%.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniBayesian networkc-means algorithmDecision networkFingerprint classificationNeural network
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