Search results for " Computer"

showing 10 items of 6910 documents

Tatouage des bases de données

2010

Database watermarking techniques allow for hiding information in a database, like a copyright mark. While watermarking methods are numerous in the multimedia setting, databases present various specificities. This work addresses some of them: how to watermark a numerical database while preserving the result of interesting aggregate queries, how to watermark a structured stream like a typed XML stream or a symbolic music score, how to watermark geographical data sets.

logictatouagedatabasesstreamwatermarkinglogiqueXML[INFO] Computer Science [cs]musique symboliquecomplexitébases de donnéesgeographiquefluxgeographicalcomplexitysymbolic music
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Investigating Novice Developers’ Code Commenting Trends Using Machine Learning Techniques

2023

Code comments are considered an efficient way to document the functionality of a particular block of code. Code commenting is a common practice among developers to explain the purpose of the code in order to improve code comprehension and readability. Researchers investigated the effect of code comments on software development tasks and demonstrated the use of comments in several ways, including maintenance, reusability, bug detection, etc. Given the importance of code comments, it becomes vital for novice developers to brush up on their code commenting skills. In this study, we initially investigated what types of comments novice students document in their source code and further categoriz…

luokitus (toiminta)Numerical Analysismachine learning techniquesohjelmistokehittäjätvasta-alkajatTheoretical Computer Sciencesource code commentsComputational MathematicskoneoppiminenclassificationComputational Theory and Mathematicssource code comments; classification; machine learning techniqueslähdekooditohjelmointiohjelmistokehitysAlgorithms; Volume 16; Issue 1; Pages: 53
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Efficient contour-based annotation by iterative deep learning for organ segmentation from volumetric medical images

2022

Abstract Purpose Training deep neural networks usually require a large number of human-annotated data. For organ segmentation from volumetric medical images, human annotation is tedious and inefficient. To save human labour and to accelerate the training process, the strategy of annotation by iterative deep learning recently becomes popular in the research community. However, due to the lack of domain knowledge or efficient human-interaction tools, the current AID methods still suffer from long training time and high annotation burden. Methods We develop a contour-based annotation by iterative deep learning (AID) algorithm which uses boundary representation instead of voxel labels to incorp…

lääketieteellinen tekniikkaorgan segmentationBiomedical Engineeringdeep learningsyväoppimineninteractive segmentationHealth InformaticsGeneral MedicineComputer Graphics and Computer-Aided Designmedical image annotationComputer Science ApplicationsalgoritmitRadiology Nuclear Medicine and imagingSurgeryComputer Vision and Pattern RecognitionInternational Journal of Computer Assisted Radiology and Surgery
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Spoken-Word Segmentation and Dyslexia

2002

We used magnetoencephalography to elucidate the cortical activation associated with the segmentation of spoken words in nonreading-impaired and dyslexic adults. The subjects listened to binaurally presented sentences where the sentence-ending words were either semantically appropriate or inappropriate to the preceding sentence context. Half of the inappropriate final words shared two or three initial phonemes with the highly expected semantically appropriate words. Two temporally and functionally distinct response patterns were detected in the superior temporal lobe. The first response peaked at approximately 100 msec in the supratemporal plane and showed no sensitivity to the semantic appr…

magnetoencephalographyAdultMalelexical accesstemporal cortexWord processingContext (language use)Medical sciencesAuditory cortexFunctional LateralityLateralization of brain functionN400mTemporal lobeDyslexiaTemporal cortexReference Valuesreading impairmentReaction TimemedicineMagnetoencephalography (MEG)HumansLongitudinal StudiesARTICLEEvoked Potentialsspeech processingAuditory CortexCerebral CortexTemporal cortexLanguage TestsVerbal BehaviorGeneral NeuroscienceDyslexiaReading impairmentMagnetoencephalographyLinguisticsSignal Processing Computer-AssistedMiddle Agedmedicine.diseaseTemporal LobeAcoustic StimulationSpeech processingSpeech Discrimination TestsLexical accessFemalePsychologySentenceCognitive psychology
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Abonder une base EndNote avec un formulaire web et un courriel

2011

National audience; Cet article présente une façon originale d’abonder une base EndNote en limitant le nombre d’erreurs et les doubles saisies. Cette procédure permet d’utiliser un canal unique et d’avoir les informations utiles à leur exploitation. La saisie s’effectue via un formulaire disponible sur l’intranet de l’unité, les données sont intégrées dans un fichier XML et envoyées par courriel à la documentaliste avec éventuellement une pièce attachée pour intégration directe à la base avec la fonction import d’EndNote.

mail[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS][INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS]XMLcourrielEndnotebibliographie
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Bayesian semiparametric long memory models for discretized event data

2020

We introduce a new class of semiparametric latent variable models for long memory discretized event data. The proposed methodology is motivated by a study of bird vocalizations in the Amazon rain forest; the timings of vocalizations exhibit self-similarity and long range dependence. This rules out Poisson process based models where the rate function itself is not long range dependent. The proposed class of FRActional Probit (FRAP) models is based on thresholding, a latent process. This latent process is modeled by a smooth Gaussian process and a fractional Brownian motion by assuming an additive structure. We develop a Bayesian approach to inference using Markov chain Monte Carlo and show g…

mallintaminenFOS: Computer and information sciencesStatistics and Probabilitylong range dependenceaikasarjatMarkovin ketjutfractional Brownian motionsademetsätekologinen mallinnusStatistics - ApplicationsArticleMethodology (stat.ME)fractalApplications (stat.AP)AmazonStatistics - Methodologylatent Gaussian process modelstodennäköisyyslaskentanonparametric Bayesbayesilainen menetelmägaussiset prosessitmatemaattinen tilastotiedeluonnonäänetlinnut -- äänetluonnon monimuotoisuusMonte Carlo -menetelmätComputer Science::SoundModeling and Simulationprobitfraktaalittime seriesStatistics Probability and UncertaintyThe Annals of Applied Statistics
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Toolbox for Distance Estimation and Cluster Validation on Data With Missing Values

2022

Missing data are unavoidable in the real-world application of unsupervised machine learning, and their nonoptimal processing may decrease the quality of data-driven models. Imputation is a common remedy for missing values, but directly estimating expected distances have also emerged. Because treatment of missing values is rarely considered in clustering related tasks and distance metrics have a central role both in clustering and cluster validation, we developed a new toolbox that provides a wide range of algorithms for data preprocessing, distance estimation, clustering, and cluster validation in the presence of missing values. All these are core elements in any comprehensive cluster analy…

mallintaminenGeneral Computer Sciencedistance estimation020209 energyGeneral Engineeringlaatu02 engineering and technologyTK1-9971missing valuesklusteritkoneoppiminendatavalidointialgoritmit0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingGeneral Materials ScienceMissing valuesElectrical engineering. Electronics. Nuclear engineeringcluster validationtietojenkäsittelyclusteringIEEE Access
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New Capabilities of the FLUKA Multi-Purpose Code

2022

We would like to deeply thank the CERN Knowledge Transfer and Legal Service teams for their essential and extended support. Our appreciation also goes to the FLUKA.CERN Collaboration Board members for their strong commitment.

mallintaminendeuteronComputerSystemsOrganization_COMPUTERSYSTEMIMPLEMENTATIONSingle event effects (SEE)acceleratorQC1-999Materials Science (miscellaneous)beam-matter interactionBiophysicsGeneral Physics and Astronomysingle event effects (see)hiukkasfysiikkamedical physicshigh energy physicsFLUKAbenchmarkcrystal channelingbismuthsimulointiddc:530High energy physicsPhysical and Theoretical ChemistryHardware_REGISTER-TRANSFER-LEVELIMPLEMENTATIONMathematical Physicshiukkassäteilymonte carlo transportflukafacilityPhysicstietokoneohjelmatMonte Carlo transportComputing and Computersddc:Monte Carlo -menetelmätBeam-matter interactionsäteilyfysiikkaCrystal channelingaluminumbeamactivationMedical physicssimulationsParticle Physics - Experimentproton
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Motivic Pattern Extraction in Music, and Application to the Study of Tunisian Modal Music

2007

A new methodology for automated extraction of repeated patterns in time-series data is presented, aimed in particular at the analysis of musical sequences. The basic principles consists in a search for closed patterns in a multi-dimensional parametric space. It is shown that this basic mechanism needs to be articulated with a periodic pattern discovery system, implying therefore a strict chronological scanning of the time-series data. Thanks to this modelling global pattern filtering may be avoided and rich and highly pertinent results can be obtained. The modelling has been integrated in a collaborative pro ject between ethnomusicology, cognitive sciences and computer science, aimed at the…

mallintaminenpattern extractionEngineeringaikasarjatmusiikkiséquences temporelles[MATH] Mathematics [math]02 engineering and technology[INFO] Computer Science [cs]Space (commercial competition)computer.software_genre060404 musicanalyse musicalemusiikkianalyysi020204 information systemsmotifs périodiques0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]improvisointiTime series[MATH]Mathematics [math]modaalisuus (musiikki)Parametric statisticsmusic analysismotifs fermésbusiness.industrymusique modale tunisienneextraction de motifstunisian modal musicjaksolliset ilmiöt06 humanities and the artsGeneral MedicineClosed patterntime-series dataarabialainen musiikkiclosed patternMusic theoryEthnomusicologyArtificial intelligencebusinesscomputer0604 artsNatural language processingperiodic pattern
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A Review of Biosensors for Non-Invasive Diabetes Monitoring and Screening in Human Exhaled Breath

2019

Exhaled breath acetone has been identified as a diabetes biomarker for non-invasive diagnosis. Its detection using biosensors features has many advantages over the conventional means. This paper reviews the recent literature on the detection of exhaled breath acetone and acetone vapor of diabetic interest. The biosensors have been classified based on their transduction methods. The performance characteristics of the biosensors have been explored for comparison. The future trends are also highlighted.

mass sensitive sensorsmedicine.medical_specialtyGeneral Computer Sciencemacromolecular substances02 engineering and technology01 natural sciencesDiabetes monitoringmedicineGeneral Materials ScienceBreath acetoneIntensive care medicineoperational temperatureelectrochemical biosensorsfuture trendsmicrowave biosensors optical biosensorsbusiness.industry010401 analytical chemistryNon invasivetechnology industry and agricultureGeneral Engineering021001 nanoscience & nanotechnology0104 chemical sciencesBiomarkerlcsh:Electrical engineering. Electronics. Nuclear engineering0210 nano-technologybusinesslcsh:TK1-9971BiosensorIEEE Access
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