Search results for "Methodologie"

showing 10 items of 2141 documents

Representere Lean tenkning gjennom bruken av prinsipper : En aksjonsstudie av Lean prinsipper på avdelingsnivå i Veidekke

2020

Master's thesis in Industrial economics and technology management (IND590)

IND590VDP::Samfunnsvitenskap: 200::Psykologi: 260::Organisasjonspsykologi: 268ComputingMethodologies_GENERALVDP::Samfunnsvitenskap: 200::Statsvitenskap og organisasjonsteori: 240::Offentlig og privat administrasjon: 242GeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)
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Erfaringsoverføring i Veidekke : En casestudie av hvordan erfaringsoverføring kan forbedres i Veidekke Drammen

2020

Master's thesis in Industrial economics and technology management (IND590)

IND590VDP::Samfunnsvitenskap: 200::Psykologi: 260::Sosial- og arbeidspsykologi: 263ComputingMethodologies_GENERALVDP::Samfunnsvitenskap: 200::Statsvitenskap og organisasjonsteori: 240::Offentlig og privat administrasjon: 242GeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)
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A novel framework for MR image segmentation and quantification by using MedGA

2019

BACKGROUND AND OBJECTIVES: Image segmentation represents one of the most challenging issues in medical image analysis to distinguish among different adjacent tissues in a body part. In this context, appropriate image pre-processing tools can improve the result accuracy achieved by computer-assisted segmentation methods. Taking into consideration images with a bimodal intensity distribution, image binarization can be used to classify the input pictorial data into two classes, given a threshold intensity value. Unfortunately, adaptive thresholding techniques for two-class segmentation work properly only for images characterized by bimodal histograms. We aim at overcoming these limitations and…

ING-INF/06 - BIOINGEGNERIA ELETTRONICA E INFORMATICAAdaptive thresholding; Bimodal intensity distribution; Evolutionary computation; Image pre-processing; Magnetic Resonance imaging; Quantitative medical imagingComputer scienceAdaptive thresholdingImage ProcessingDecision MakingNeurosurgeryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHealth InformaticsContext (language use)Adaptive thresholding; Bimodal intensity distribution; Evolutionary computation; Image pre-processing; Magnetic Resonance imaging; Quantitative medical imaging; Algorithms; Brain Neoplasms; Computer Simulation; Decision Making; Female; Humans; Image Processing Computer-Assisted; Leiomyoma; Neurosurgery; Radiosurgery; Software; Magnetic Resonance ImagingEvolutionary computationRadiosurgeryING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI030218 nuclear medicine & medical imaging03 medical and health sciencesComputer-Assisted0302 clinical medicineHistogramQuantitative medical imagingmedicineImage Processing Computer-AssistedHumansSegmentationComputer SimulationHistogram equalizationmedicine.diagnostic_testLeiomyomaSettore INF/01 - Informaticabusiness.industryBrain NeoplasmsINF/01 - INFORMATICAMagnetic resonance imagingPattern recognitionImage segmentationThresholdingComputer Science ApplicationsBimodal intensity distributionImage pre-processingTransformation (function)Magnetic Resonance imagingFemaleArtificial intelligencebusiness030217 neurology & neurosurgeryAlgorithmsSoftware
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Structure and function of the vacuolar Ccc1/VIT1 family of iron transporters and its regulation in fungi

2020

Iron is an essential micronutrient for most living beings since it participates as a redox active cofactor in many biological processes including cellular respiration, lipid biosynthesis, DNA replication and repair, and ribosome biogenesis and recycling. However, when present in excess, iron can participate in Fenton reactions and generate reactive oxygen species that damage cells at the level of proteins, lipids and nucleic acids. Organisms have developed different molecular strategies to protect themselves against the harmful effects of high concentrations of iron. In the case of fungi and plants, detoxification mainly occurs by importing cytosolic iron into the vacuole through the Ccc1/V…

ISC Iron-sulfur lusterCS Consistency scoreCcc1Ribosome biogenesisVacuoleReview ArticleYRE Yap response elementsBiochemistryBiotecnologia0302 clinical medicineStructural BiologyCg Candida glabrata0303 health sciencesMAFFT Multiple Alignment using Fast Fourier TransformNRAMP Natural Resistance-Associated Macrophage ProteinbiologyVIT1ChemistryMBD Metal-binding domainPlantsComputer Science ApplicationsBiochemistry030220 oncology & carcinogenesisCRD Cysteine-rich domainEg Eucalyptus grandisIron detoxificationBiotechnologyCBC CCAAT-binding core complexlcsh:BiotechnologySaccharomyces cerevisiaeVTL Vacuolar iron transporter-likeBiophysicsVIT Vacuolar iron transporterbZIP basic leucine-zipper03 medical and health sciencesFongsLipid biosynthesislcsh:TP248.13-248.65GeneticsFe IronIron transportTranscription factor030304 developmental biologyComputingMethodologies_COMPUTERGRAPHICSBLOSUM BLOcks SUbstitution MatrixTMD Transmembrane domainML Maximum-likelihoodIron regulationDNA replicationFungibiology.organism_classificationYeastYeastMetabolic pathwayH HelixHap Heme activator proteinVacuoleROS Reactive oxygen speciesFerroComputational and Structural Biotechnology Journal
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A Practical Approach to EA Planning and Development: the EA Management Grid

2004

Enterprise Architecture is gaining interest as a managerial tool for managing corporate ICT assets and their interplay. Our prior studies indicate that an ICT provider’s viewpoint on EA consulting, planning and development seems to be lacking in the proposed methodologies. Considering both literature and practical EA cases, we suggest an approach that supports restricted assignments in EA management. We present an EA Grid for the management of EA descriptions, requirements, constraints, as well as project tasks and deliverables, task preliminaries and dependencies in EA consulting and development. peerReviewed

IT StrategyliiketoimintastrategiaIT GovernanceTietohallinnon johtaminenComputingMethodologies_MISCELLANEOUSIT-strategiastrateginen suunnitteluBusiness StrategykokonaisarkkitehtuurikonsultointiEnterprise Architecture
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Comparison of Attention Behaviour Across User Sets through Automatic Identification of Common Areas of Interest

2020

Eye tracking is used to analyze and compare user behaviour within numerous domains, but long duration eye tracking experiments across multiple users generate millions of eye gaze samples, making th ...

Identification (information)InformationSystems_MODELSANDPRINCIPLESbusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONEye trackingComputer visionArtificial intelligencebusinessHidden Markov modelProceedings of the Annual Hawaii International Conference on System Sciences
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Methods for Experimentally Determining Stiffness of a Multi-Axis Machining Centre

2019

This paper deals with global methods for experimentally determining the static stiffness of multi-axis machining centres. Different devices used for measuring deflection, in specific, are explored, where accuracy and usability are highlighted. The methods were tested on a 3-axis CNC milling machine, 2-axis trunnion table and a 6-DOF industrial robot.

Identification3-axisComputer scienceMulti axisCNC machineStiffnessMechanical engineeringlcsh:QA75.5-76.95StiffnessComputer Science ApplicationsComputer Science::Robotics5-axisMachiningControl and Systems EngineeringModeling and Simulationmedicinelcsh:Electronic computers. Computer scienceIndustrial robotmedicine.symptomSoftwareComputingMethodologies_COMPUTERGRAPHICSModeling, Identification and Control: A Norwegian Research Bulletin
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Benchmarking Wilms’ tumor in multisequence MRI data: why does current clinical practice fail? Which popular segmentation algorithms perform well?

2019

Wilms' tumor is one of the most frequent malignant solid tumors in childhood. Accurate segmentation of tumor tissue is a key step during therapy and treatment planning. Since it is difficult to obtain a comprehensive set of tumor data of children, there is no benchmark so far allowing evaluation of the quality of human or computer-based segmentations. The contributions in our paper are threefold: (i) we present the first heterogeneous Wilms' tumor benchmark data set. It contains multisequence MRI data sets before and after chemotherapy, along with ground truth annotation, approximated based on the consensus of five human experts. (ii) We analyze human expert annotations and interrater varia…

Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION610 Medicine & healthMachine learningcomputer.software_genre030218 nuclear medicine & medical imagingSet (abstract data type)03 medical and health sciences0302 clinical medicineMedical imagingMedicineRadiology Nuclear Medicine and imagingSegmentationRadiation treatment planningbusiness.industry10042 Clinic for Diagnostic and Interventional RadiologyWilms' tumorBenchmarkingImage segmentationmedicine.disease3. Good healthComputingMethodologies_PATTERNRECOGNITION030220 oncology & carcinogenesisBenchmark (computing)Artificial intelligencebusinesscomputerJournal of Medical Imaging
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Data for: Directive local color transfer based on dynamic look-up table

2019

This data is the image in the article. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONInterdisciplinary sciencesOther
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Learning the relevant image features with multiple kernels

2009

This paper proposes to learn the relevant features of remote sensing images for automatic spatio-spectral classification with the automatic optimization of multiple kernels. The method consists of building dedicated kernels for different sets of bands, contextual or textural features. The optimal linear combination of kernels is optimized through gradient descent on the support vector machine (SVM) objective function. Since a na¨ive implementation is computationally demanding, we propose an efficient model selection procedure based on kernel alignment. The result is a weight — learned from the data — for each kernel where both relevant and meaningless image features emerge after training. E…

Image classificationComputer scienceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingMachine learningcomputer.software_genreKernel (linear algebra)Robustness (computer science)Multiple kernel learning (MKL)Contextual image classificationbusiness.industryModel selectionPattern recognitionSupport vector machineComputingMethodologies_PATTERNRECOGNITIONKernel (image processing)Feature (computer vision)SimpleMKLKernel alignmentSupport vector machine (SVM)Artificial intelligencebusinessGradient descentcomputer2009 IEEE International Geoscience and Remote Sensing Symposium
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