Search results for " Extraction"

showing 10 items of 1344 documents

Cloud point–dispersive μ-solid phase extraction of hydrophobic organic compounds onto highly hydrophobic core–shell Fe 2 O 3 @C magnetic nanoparticles

2012

Abstract A novel two-step extraction technique combining cloud point extraction (CPE) with dispersive micro-solid phase extraction (D-μ-SPE) is presented in this work for the first time. The method involves initial extraction of the target analytes by CPE in the micelles of a non-ionic surfactant medium; then highly hydrophobic polysiloxane-coated core–shell Fe 2 O 3 @C magnetic nanoparticles (MNPs) are used to retrieve the micellar phase. In that manner, the micellar phase containing the analytes is the target of the D-μ-SPE step rather than the analytes directly. MNPs are then collected by the application of an adscititious magnetic field overcoming the need for specific steps associated …

Cloud pointChromatographyChemistryOrganic ChemistryExtraction (chemistry)Analytical chemistryGeneral MedicineBiochemistryMicelleAnalytical ChemistryPulmonary surfactantPhase (matter)Magnetic nanoparticlesSolid phase extractionSolubilityJournal of Chromatography A
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Dimensionality reduction via regression on hyperspectral infrared sounding data

2014

This paper introduces a new method for dimensionality reduction via regression (DRR). The method generalizes Principal Component Analysis (PCA) in such a way that reduces the variance of the PCA scores. In order to do so, DRR relies on a deflationary process in which a non-linear regression reduces the redundancy between the PC scores. Unlike other nonlinear dimensionality reduction methods, DRR is easy to apply, it has out-of-sample extension, it is invertible, and the learned transformation is volume-preserving. These properties make the method useful for a wide range of applications, especially in very high dimensional data in general, and for hyperspectral image processing in particular…

Clustering high-dimensional dataRedundancy (information theory)business.industryDimensionality reductionPrincipal component analysisFeature extractionNonlinear dimensionality reductionHyperspectral imagingPattern recognitionArtificial intelligencebusinessMathematicsCurse of dimensionality2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)
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Influence of Musical Expertise on the processing of Musical Features in a Naturalistic Setting

2019

Musical training causes structural and functional changes in the brain due to its sensory-motor demands, but the modulatory effect of musical training on music feature processing in the brain in a continuous music listening paradigm, has not been investigated thus far. In this work, we investigate the differences between musicians and non-musicians in the encoding of musical features encompassing musical timbre, rhythm and tone. 18 musicians and 18 non-musicians were scanned using fMRI while listening to 3 varied stimuli. Acoustic features corresponding to timbre, rhythm and tone were computationally extracted from the stimuli and correlated with brain responses, followed by t-tests on grou…

Cognitive sciencemuusikotneuropsykologiafMRInaturalistic stimulusmusiikkipsykologiaMusicalacoustic feature extractionbehavioral disciplines and activitieshumanitiestoiminnallinen magneettikuvausprosessointimusicians vs non-musiciansmusic processingPsychologyärsykkeetNaturalism2019 Conference on Cognitive Computational Neuroscience
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Semantic and topological classification of images in magnetically guided capsule endoscopy

2012

International audience; Magnetically-guided capsule endoscopy (MGCE) is a nascent technology with the goal to allow the steering of a capsule endoscope inside a water filled stomach through an external magnetic field. We developed a classification cascade for MGCE images with groups images in semantic and topological categories. Results can be used in a post-procedure review or as a starting point for algorithms classifying pathologies. The first semantic classification step discards over-/under-exposed images as well as images with a large amount of debris. The second topological classification step groups images with respect to their position in the upper gastrointestinal tract (mouth, es…

Color histogramComputer scienceFeature extraction[INFO.INFO-IM] Computer Science [cs]/Medical ImagingImage processingFundus (eye)Content-based image retrieval030218 nuclear medicine & medical imaginglaw.invention03 medical and health sciences0302 clinical medicineDiscriminative modelCapsule endoscopylaw[INFO.INFO-IM]Computer Science [cs]/Medical ImagingmedicineUpper gastrointestinalComputer visionSegmentationAntrumContextual image classification[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingbusiness.industryStomachmedicine.anatomical_structureFeature (computer vision)Duodenum030211 gastroenterology & hepatologyArtificial intelligencebusiness
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S_Kernel: A New Symmetry Measure

2005

Symmetry is an important feature in vision. Several detectors or transforms have been proposed. In this paper we concentrate on a measure of symmetry. Given a transform S, the kernel SK of a pattern is defined as the maximal included symmetric sub-set of this pattern. It is easily proven that, in any direction, the optimal axis corresponds to the maximal correlation of a pattern with its flipped version. For the measure we compute a modified difference between respective surfaces of a pattern and its kernel. That founds an efficient algorithm to attention focusing on symmetric patterns.

CombinatoricsMaximal correlationKernel (image processing)Efficient algorithmDetectorFeature extractionAxial symmetryMathematics
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Outcomes of in-bag transvaginal extraction in a series of 692 laparoscopic myomectomies: results from a large retrospective analysis

2022

Transvaginal extraction is a feasible method to remove surgical specimen. In this study, we aim to report our experience with in-bag transvaginal specimen retrieval after laparoscopic myomectomy over the past 15 years.Single-center retrospective analysis.Academic hospital.Women who underwent laparoscopic myomectomy from January 2005 to April 2021.Posterior colpotomy and in-bag transvaginal extraction of the surgical specimen.We collected and analyzed data about patients' characteristics, main indication for surgery, and intra- and postoperative (within 30 days) complications.A total of 692 women underwent transvaginal specimen retrieval after laparoscopic myomectomy (mean largest myoma diam…

ComplicationsLeiomyomaLaparoscopic myomectomyObstetrics and GynecologyPosterior colpotomySettore MED/40 - Ginecologia E OstetriciaSurgical specimen retrievalUterine NeoplasmsUterine MyomectomySurgical specimen retrieval.HumansFemaleLaparoscopyComplicationRetrospective StudiesIn-bag transvaginal extraction
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Backbone Extraction of Weighted Modular Complex Networks based on their Component Structure

2023

This work introduces a generic backbone extraction framework exploiting the mesoscopic network structure. Indeed, numerous real-world networks are made of dense groups of nodes called communities, multi-core or local components. To deal with these groups' heterogeneity, we propose to extract the backbones independently from their various components and fuse them. Experimental investigations on real-world networks demonstrate the effectiveness of the proposed approach compared to the classical techniques' agnostic of the mesoscopic structure of real-world networks.

Component Structurecommunity-aware backbone extractorBackbone extraction[INFO] Computer Science [cs]Multi-Core StructureCommunity structure
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Generic attribute deviation metric for assessing mesh simplification algorithm quality

2002

International audience; This paper describes an efficient method to compare two triangular meshes. Meshes considered here contain geometric features as well as other surface attributes such as material colors, texture, temperature, radiation, etc. Two deviation measurements are presented to assess the differences between two meshes. The first measurement, called geometric deviation, returns geometric differences. The second measurement , called attribute deviation, returns attribute differences regardless of the attribute type. In this paper we present an application of this method to the Mesh Simplification Algorithm (MSA) quality assessment according to the appearance attributes. This ass…

Computationmedia_common.quotation_subjectFeature extraction[INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR]02 engineering and technologySolid modeling[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]Computer graphics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0202 electrical engineering electronic engineering information engineeringQuality (business)Polygon meshComputingMethodologies_COMPUTERGRAPHICSmedia_commonMathematicsbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringPattern recognitionComputational geometry[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR][INFO.INFO-CG] Computer Science [cs]/Computational Geometry [cs.CG]Metric (mathematics)020201 artificial intelligence & image processingArtificial intelligencebusinessAlgorithmProceedings. International Conference on Image Processing
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Irrelevant Features, Class Separability, and Complexity of Classification Problems

2011

In this paper, analysis of class separability measures is performed in attempt to relate their descriptive abilities to geometrical properties of classification problems in presence of irrelevant features. The study is performed on synthetic and benchmark data with known irrelevant features and other characteristics of interest, such as class boundaries, shapes, margins between classes, and density. The results have shown that some measures are individually informative, while others are less reliable and only can provide complimentary information. Classification problem complexity measurements on selected data sets are made to gain additional insights on the obtained results.

Computational complexity theoryCovariance matrixComputer sciencebusiness.industryFeature extractionPattern recognitionArtificial intelligencebusinessMachine learningcomputer.software_genreClass (biology)computerClass separability2011 IEEE 23rd International Conference on Tools with Artificial Intelligence
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Creating a semantically-enhanced cloud services environment through ontology evolution

2014

Currently, the availability of Web resources has grown enormously to the point that whatever a user needs at a given moment can potentially be found on the Internet. These resources are not limited to data items anymore, functionality delivered through some sort of service architectural model is also offered on the Internet. In the last few years, cloud computing has emerged as one of the most popular computing models to provide services over the Internet. However, as the number of available cloud services increases, the problem of service discovery and selection arises. Experience indicates that semantic technologies can provide the basis for enhanced and more precise search processes. In …

Computer Networks and CommunicationsComputer sciencecomputer.internet_protocolService discoveryCloud computingcomputer.software_genreSocial Semantic WebOWL-SWorld Wide WebSemantic computingSemantic analyticsUpper ontologySemantic Web StackSemantic WebInformation retrievalbusiness.industrySearch engine indexingSemantic searchInformation extractionSemantic gridHardware and ArchitectureOntologySemantic technologyThe InternetWeb resourcebusinesscomputerSoftwareFuture Generation Computer Systems
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