Search results for "85"

showing 10 items of 1612 documents

Modelling, Analysis, and Simulation of the Micro-Doppler Effect in Wideband Indoor Channels with Confirmation Through Pendulum Experiments

2020

This paper is about designing a 3D no n-stationary wideband indoor channel model for radio-frequency sensing. The proposed channel model allows for simulating the time-variant (TV) characteristics of the received signal of indoor channel in the presence of a moving object. The moving object is modelled by a point scatterer which travels along a trajectory. The trajectory is described by the object&rsquo

Computer scienceAcousticsdoppler frequency02 engineering and technologylcsh:Chemical technologyBiochemistryArticleAnalytical Chemistry0203 mechanical engineeringInertial measurement unitspectrogramindoor channels0202 electrical engineering electronic engineering information engineeringlcsh:TP1-1185micro-doppler effectElectrical and Electronic EngineeringWidebandVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Instrumentationchannel state informationComputer Science::Information Theory3d no n-stationary channels020301 aerospace & aeronauticswi-fi 802.11nPendulum020206 networking & telecommunicationsAtomic and Molecular Physics and Opticsinertial measurement unitsChannel state informationcsiTrajectoryCommunication channelSensors
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Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.

2007

Abstract Background Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rath…

Computer scienceAlgorismesPrediction by partial matchingCompression dissimilaritycomputer.software_genreBiochemistryProtein Structure SecondaryPhylogenetic studiesStructural BiologySequence Analysis ProteinDatabases Proteinlcsh:QH301-705.5Biological dataNCDApplied MathematicsGenomicsClassificationCDComputer Science ApplicationsBenchmarking:Informàtica::Informàtica teòrica [Àrees temàtiques de la UPC]Universal compression dissimilarityArea Under CurveMetric (mathematics)lcsh:R858-859.7Data miningAlgorithmsData compressionResearch Article:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]Normalization (statistics)lcsh:Computer applications to medicine. Medical informaticsBioinformatics Sequence Alignment AlgorithmsSet (abstract data type)Similarity (network science)Normalized compression sissimilarityData compression (Computer science)AnimalsHumansAmino Acid SequenceMolecular BiologyBiologyDades -- Compressió (Informàtica)USMUniversal similarity metricProteinsUCDProtein Structure TertiaryData setGenòmicaStatistical classificationlcsh:Biology (General)ROC CurvecomputerSequence AlignmentSoftwareBMC bioinformatics
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CORENup: a combination of convolutional and recurrent deep neural networks for nucleosome positioning identification

2020

Abstract Background Nucleosomes wrap the DNA into the nucleus of the Eukaryote cell and regulate its transcription phase. Several studies indicate that nucleosomes are determined by the combined effects of several factors, including DNA sequence organization. Interestingly, the identification of nucleosomes on a genomic scale has been successfully performed by computational methods using DNA sequence as input data. Results In this work, we propose CORENup, a deep learning model for nucleosome identification. CORENup processes a DNA sequence as input using one-hot representation and combines in a parallel fashion a fully convolutional neural network and a recurrent layer. These two parallel …

Computer scienceCelllcsh:Computer applications to medicine. Medical informaticsBiochemistryConvolutional neural networkDNA sequencingchemistry.chemical_compoundStructural BiologyTranscription (biology)medicineHumansNucleosomeA-DNAEpigeneticsMolecular Biologylcsh:QH301-705.5Nucleosome classificationSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticabiologybusiness.industryApplied MathematicsDeep learningResearchEpigeneticPattern recognitionGenomicsbiology.organism_classificationNucleosomesComputer Science ApplicationsRecurrent neural networkmedicine.anatomical_structurechemistrylcsh:Biology (General)Recurrent neural networkslcsh:R858-859.7Deep learning networksEukaryoteNeural Networks ComputerArtificial intelligenceDNA microarraybusinessDNABMC Bioinformatics
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PVAmpliconFinder: a workflow for the identification of human papillomaviruses from high-throughput amplicon sequencing

2019

Abstract Background The detection of known human papillomaviruses (PVs) from targeted wet-lab approaches has traditionally used PCR-based methods coupled with Sanger sequencing. With the introduction of next-generation sequencing (NGS), these approaches can be revisited to integrate the sequencing power of NGS. Although computational tools have been developed for metagenomic approaches to search for known or novel viruses in NGS data, no appropriate tool is available for the classification and identification of novel viral sequences from data produced by amplicon-based methods. Results We have developed PVAmpliconFinder, a data analysis workflow designed to rapidly identify and classify kno…

Computer scienceComputational biologylcsh:Computer applications to medicine. Medical informaticsBiochemistryWorkflowUser-Computer Interface03 medical and health sciencessymbols.namesakeStructural BiologyHumansVirus discoverylcsh:QH301-705.5PapillomaviridaeMolecular BiologyThroughput (business)PhylogenyAmplicon sequencing030304 developmental biologySanger sequencing0303 health sciencesBiological data030306 microbiologyMethodology ArticleApplied MathematicsHigh-Throughput Nucleotide SequencingPapillomavirusAmpliconComputer Science ApplicationsIdentification (information)Workflowlcsh:Biology (General)MetagenomicsDNA ViralAmplicon sequencingsymbolslcsh:R858-859.7Primer (molecular biology)DNA microarrayBMC Bioinformatics
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Automatic Calibration of an Industrial RGB-D Camera Network Using Retroreflective Fiducial Markers

2019

This paper describes a non-invasive, automatic, and robust method for calibrating a scalable RGB-D sensor network based on retroreflective ArUco markers and the iterative closest point (ICP) scheme. We demonstrate the system by calibrating a sensor network comprised of six sensor nodes positioned in a relatively large industrial robot cell with an approximate size of 10 m × 10 m × 4 m . Here, the automatic calibration achieved an average Euclidean error of 3 c m at distances up to 9.45 m . To achieve robustness, we apply several innovative techniques: Firstly, we mitigate the ambiguity problem that occurs when detecting a marker at long range or low resolution by comparing the…

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologylcsh:Chemical technologytime-of-flightBiochemistryArticleVDP::Food science and technology: 600Analytical Chemistrylaw.inventionIndustrial robotlawRegion of interestRobustness (computer science)automatic calibration0202 electrical engineering electronic engineering information engineeringCalibrationVDP::Næringsmiddelteknologi: 600lcsh:TP1-1185Computer visionElectrical and Electronic EngineeringInstrumentationbusiness.industryambiguity problemIterative closest point3D sensors020207 software engineeringretroreflective markersAtomic and Molecular Physics and OpticsTime of flightTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESRGB color model020201 artificial intelligence & image processingArtificial intelligencebusinessFiducial markerWireless sensor networkSensors
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Optimal Filter Estimation for Lucas-Kanade Optical Flow

2012

Optical flow algorithms offer a way to estimate motion from a sequence of images. The computation of optical flow plays a key-role in several computer vision applications, including motion detection and segmentation, frame interpolation, three-dimensional scene reconstruction, robot navigation and video compression. In the case of gradient based optical flow implementation, the pre-filtering step plays a vital role, not only for accurate computation of optical flow, but also for the improvement of performance. Generally, in optical flow computation, filtering is used at the initial level on original input images and afterwards, the images are resized. In this paper, we propose an image filt…

Computer scienceGaussianComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowGaussian blurlcsh:Chemical technologyGaussian filteringcomputer.software_genreBiochemistryArticleAnalytical Chemistryoptical flowsymbols.namesakeLucas–Kanade methodoptical flow; Lucas-Kanade; Gaussian filtering; optimal filteringGaussian functionlcsh:TP1-1185SegmentationComputer visionLucas-KanadeElectrical and Electronic EngineeringInstrumentationbusiness.industryoptimal filteringMotion detectionFilter (signal processing)Atomic and Molecular Physics and OpticsComputer Science::Computer Vision and Pattern RecognitionsymbolsArtificial intelligenceData miningMotion interpolationbusinesscomputerData compressionSensors
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pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components

2019

AbstractBackgroundPrincipal component analysis (PCA) is frequently useentirely written ind in genomics applications for quality assessment and exploratory analysis in high-dimensional data, such as RNA sequencing (RNA-seq) gene expression assays. Despite the availability of many software packages developed for this purpose, an interactive and comprehensive interface for performing these operations is lacking.ResultsWe developed the pcaExplorer software package to enhance commonly performed analysis steps with an interactive and user-friendly application, which provides state saving as well as the automated creation of reproducible reports. pcaExplorer is implemented in R using the Shiny fra…

Computer scienceInterface (computing)ShinyBioconductorPrincipal component analysis610 MedizinRNA-SeqGenomicslcsh:Computer applications to medicine. Medical informaticsReproducible researchBioconductorTranscriptomeExploratory data analysisUser-friendly610 Medical sciencesGene expressionHumansRNA-SeqGenelcsh:QH301-705.5Data CurationBase Sequencebusiness.industrySequence Analysis RNARRNAReproducibility of Resultslcsh:Biology (General)Principal component analysisRNAlcsh:R858-859.7Software engineeringbusinessSoftware
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Open Set Audio Classification Using Autoencoders Trained on Few Data.

2020

Open-set recognition (OSR) is a challenging machine learning problem that appears when classifiers are faced with test instances from classes not seen during training. It can be summarized as the problem of correctly identifying instances from a known class (seen during training) while rejecting any unknown or unwanted samples (those belonging to unseen classes). Another problem arising in practical scenarios is few-shot learning (FSL), which appears when there is no availability of a large number of positive samples for training a recognition system. Taking these two limitations into account, a new dataset for OSR and FSL for audio data was recently released to promote research on solution…

Computer scienceOpen set02 engineering and technologylcsh:Chemical technologyMachine learningcomputer.software_genreBiochemistryArticleAnalytical ChemistrySet (abstract data type)open set recognition020204 information systemsaudio classificationautoencoders0202 electrical engineering electronic engineering information engineeringFeature (machine learning)lcsh:TP1-1185few-shot learningElectrical and Electronic EngineeringRepresentation (mathematics)Instrumentationbusiness.industryopen set classificationPerceptronClass (biology)AutoencoderAtomic and Molecular Physics and OpticsEmbedding020201 artificial intelligence & image processingArtificial intelligenceTransfer of learningbusinesscomputerSensors (Basel, Switzerland)
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CultReal—A Rapid Development Platform for AR Cultural Spaces, with Fused Localization

2021

Virtual and augmented reality technologies have known an impressive market evolution due to their potential to provide immersive experiences. However, they still have significant difficulties to enable fully fledged, consumer-ready applications that can handle complex tasks such as multi-user collaboration or time-persistent experiences. In this context, CultReal is a rapid creation and deployment platform for augmented reality (AR), aiming to revitalize cultural spaces. The platform’s content management system stores a representation of the environment, together with a database of multimedia objects that can be associated with a location. The localization component fuses data from beacons …

Computer scienceOrientation (computer vision)Chemical technologyContext (language use)TP1-1185Mobile ApplicationsBiochemistryArticleAtomic and Molecular Physics and Opticsaugmented realitylocalizationcomputer visionAnalytical ChemistryBeaconHuman–computer interactionSoftware deploymentComputers HandheldComponent (UML)beaconsAugmented realitySmartphoneElectrical and Electronic EngineeringInstrumentationMobile deviceImplementationSensors
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Embedded Processing and Compression of 3D Sensor Data for Large Scale Industrial Environments

2019

This paper presents a scalable embedded solution for processing and transferring 3D point cloud data. Sensors based on the time-of-flight principle generate data which are processed on a local embedded computer and compressed using an octree-based scheme. The compressed data is transferred to a central node where the individual point clouds from several nodes are decompressed and filtered based on a novel method for generating intensity values for sensors which do not natively produce such a value. The paper presents experimental results from a relatively large industrial robot cell with an approximate size of 10 m &times

Computer sciencePoint cloud02 engineering and technologylcsh:Chemical technologytime-of-flightBiochemistryArticleAnalytical ChemistryComputational sciencelaw.inventionIndustrial robotOctreelawpoint clouds0202 electrical engineering electronic engineering information engineeringdenoisinglcsh:TP1-1185Electrical and Electronic EngineeringInstrumentationlidarscalabilityLocal area network020206 networking & telecommunications020207 software engineering3D sensorscompressionAtomic and Molecular Physics and OpticsScalabilitySensors (Basel, Switzerland)
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