Search results for " Detection"

showing 10 items of 1676 documents

Anomaly Detection and Classification of Household Electricity Data : A Time Window and Multilayer Hierarchical Network Approach

2022

With the increasing popularity of the smart grid, huge volumes of data are gathered from numerous sensors. How to classify, store, and analyze massive datasets to facilitate the development of the smart grid has recently attracted much attention. In particular, with the popularity of household smart meters and electricity monitoring sensors, a large amount of data can be obtained to analyze household electricity usage so as to better diagnose the leakage and theft behaviors, identify man-made tampering and data fraud, and detect powerline loss. In this paper, the time window method is first proposed to obtain the features and potential periodicity of household electricity data. Combining th…

autoencoderMains electricityComputer Networks and CommunicationsComputer sciencemultilayer hierarchical networkkotitaloudetverkot (järjestelmät)computer.software_genreanomaly detectionComputer Science Applicationshousehold electricitysähkönkulutussähködataclassificationHardware and ArchitectureTime windowspoikkeavuusSignal ProcessingAnomaly detectionData miningcomputerNetwork approachfeedforward networkInformation Systems
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Estimating Tree Health Decline Caused by Ips typographus L. from UAS RGB Images Using a Deep One-Stage Object Detection Neural Network

2022

Various biotic and abiotic stresses are causing decline in forest health globally. Presently, one of the major biotic stress agents in Europe is the European spruce bark beetle (Ips typographus L.) which is increasingly causing widespread tree mortality in northern latitudes as a consequence of the warming climate. Remote sensing using unoccupied aerial systems (UAS) together with evolving machine learning techniques provide a powerful tool for fast-response monitoring of forest health. The aim of this study was to investigate the performance of a deep one-stage object detection neural network in the detection of damage by I. typographus in Norway spruce trees using UAS RGB images. A Scaled…

bark beetlekirjanpainaja (kaarnakuoriaiset)syväoppiminendeep learningmonitorointiobject detectionneuroverkotmiehittämättömät ilma-aluksetdronetree healthmetsätremote sensingkoneoppiminenbark beetle; deep learning; drone; object detection; remote sensing; tree healthmetsätuhotGeneral Earth and Planetary Scienceskaukokartoitusmetsäkuusihyönteistuhotestimointi
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Search for intermediate mass black hole binaries in the first and second observing runs of the Advanced LIGO and Virgo network

2019

Gravitational wave astronomy has been firmly established with the detection of gravitational waves from the merger of ten stellar mass binary black holes and a neutron star binary. This paper reports on the all-sky search for gravitational waves from intermediate mass black hole binaries in the first and second observing runs of the Advanced LIGO and Virgo network. The search uses three independent algorithms: two based on matched filtering of the data with waveform templates of gravitational wave signals from compact binaries, and a third, model-independent algorithm that employs no signal model for the incoming signal. No intermediate mass black hole binary event was detected in this sear…

binary: massneutron star: binaryAstronomybinary: angular momentumAstrophysicsdetector: network01 natural sciencesGeneral Relativity and Quantum CosmologyPhysics Particles & FieldsLIMITSclustersLIGOgravitational waveGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)QCQBastro-ph.HEPhysicsHigh Energy Astrophysical Phenomena (astro-ph.HE)Settore FIS/01black hole: spinPhysicsintermediate mass black hole binarieNumerical relativityGeneral relativitygravitational wavesgravitational waves; intermediate mass black hole binaries; Advanced LIGO and VirgoPhysical Sciences[PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc]Astrophysics - High Energy Astrophysical PhenomenastarsGeneral relativitygr-qcAstrophysics::High Energy Astrophysical PhenomenaFOS: Physical sciencesalternative theories of gravitySTARS; CLUSTERS; LIMITSAstrophysics::Cosmology and Extragalactic AstrophysicsGeneral Relativity and Quantum Cosmology (gr-qc)Astronomy & Astrophysicsgravitational radiation: direct detectionGeneral Relativity and Quantum CosmologySettore FIS/05 - Astronomia e AstrofisicaBinary black hole0103 physical sciencesddc:530010306 general physicsAstrophysics::Galaxy AstrophysicsSTFCScience & Technology010308 nuclear & particles physicsGravitational waveAdvanced LIGO and Virgointermediate mass black hole binariesRCUKGravitational Wave Physicsblack hole: massMass ratiobinary: compact04.80.NnLIGOgravitational radiation detectorNeutron starVIRGOblack hole: binaryIntermediate-mass black holerelativity theorygravitational radiation: emission95.55.Ymmass ratioDewey Decimal Classification::500 | Naturwissenschaften::530 | Physik07.05.Kflimits[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]CLUSTERSSTARSGravitational waves Black holes (astronomy) Gravitational self force
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Monitoring the effects of therapeutic interventions in depression through self-assessments

2021

The treatment of major psychiatric disorders is an arduous and thorny path for the patients concerned, characterized by polypharmacy, massive adverse side effects, modest prospects of success, and constantly declining response rates. The more important is the early detection of psychiatric disorders prior to the development of clinically relevant symptoms, so that people can benefit from early interventions. A well-proven approach to monitoring mental health relies on voice analysis. This method has been successfully used with psychiatric patients to ‘objectively’ document the progress of improvement or the onset of relapse. The studies with psychiatric patients over 2-4 weeks demonstrated …

biofeedbackselfmonitoringself-monitoringpsychosomatic disturbancesArticleBF1-990voice analysisPsychiatry and Mental healthClinical PsychologydepressionPsychologystress-related health problemsuniversity studentsPsychiatric disordersearly detectionPsychiatry and Mental health; Clinical Psychology
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Brenneria quercina and Serratia spp. isolated from Spanish oak trees Molecular characterization and development of PCR primers

2008

Brenneria quercina has been reported as one of the causal agents of oak decline in Spain. To investigate the bacterial variability of this pathogen from different Spanish oak forests, a collection of 38 bacterial isolates from seven geographic locations and from different oak species was analysed by sequencing 16S rDNA and rep-PCR fingerprinting. All Spanish isolates of B. quercina were grouped by rep-PCR into a homogenous cluster that differed significantly from B. quercina reference strains from California. 16S rDNA analysis revealed that 34 out of 38 isolates were Brenneria. However, four isolates belonged to the genus Serratia, suggesting that this bacterium could cause cankers in oak t…

biologyeducationPlant ScienceDrippy nut diseaseHorticulturebiology.organism_classification16S ribosomal RNASerratiaFagaceaelaw.inventionQuercus pyrenaicaQuercus ilexQuercus pyrenaicaRep-PCR detection and diagnosislawBotanyBrenneriaGeneticsAgronomy and Crop SciencePathogenPolymerase chain reactionWoody plant
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Computer Aided Design for Diabetic Retinopathy

2013

International audience; Computer aided diagnosis and follow up can help in prevention and treatment of diabetes and its related complications. This paper presents a summary of the results we obtained over the last few years regarding the development of a CAD system for diabetic retinopathy. We present a methodology for diagnosis of DME based on exudates segmentation, as well as an automated detection of micro-aneurysm (MA) and DR diagnosis; Our approach uses standard available public database and shows a high power of generalization through cross database experiments.

blob detectionmachine learning[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processingretina imaging
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Colorimetric and fluorescent hydrazone-BODIPY probes for the detection of γ-hydroxybutyric acid (GHB) and cathinones

2022

Consumption and abuse of drugs is a general problem, which concerns our entire society. In some cases, drugs are used for recreational purposes; but in others, they are used to commit crimes such as Drug-Facilitated Sexual Assault (DFSA). In other cases, this consumption alters the consumer mood in such a way that risky situations can rise. In any case, detection of drugs in different environment is worthwhile. Here, two new chromogenic and fluorescent probes are reported. Detection of both cathinone derivatives and γ-hydroxybutyric acid (GHB) can be carried out with naked-eye with limits of detection of 0.4 μM and 0.3 μM for GHB and 2.0 μM for ephedrone. Selectivity in the presence of othe…

bodipy luminescence sensor drug detectionProcess Chemistry and TechnologyGeneral Chemical EngineeringUNESCO::CIENCIAS TECNOLÓGICASDyes and Pigments
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Fluorescent Boron Oxide Nanodisks as Biocompatible Multi-messenger Sensors for Ultrasensitive Ni$^{2+}$ Detection

2023

Boron-based nanocomposites are very promising for a wide range of technological applications, spanning from microelectronics to nanomedicine. A large variety of B-based nanomaterials has been already observed, such as borospherene, B nanotubes and nanoparticles, and boron nitride nanoparticles. However, their fabrication usually involves toxic precursors or leads to very low yields or small boron atom concentration. In this work, we report the synthesis of nanometric B$_{2}$O$_{3}$ nanodisks, a family of nanomaterials with a quasi-2D morphology capable of intense fluorescence in the visible range. Such as boron-based nanomaterial, which we synthesized by pulsed laser ablation of a boron tar…

boron oxide boron nanocomposites nanosensors nickel detection multi-messenger sensorSettore FIS/01 - Fisica Sperimentaleddc:500NATURAL sciences & mathematics
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Learning-based multiresolution transforms with application to image compression

2013

In Harten's framework, multiresolution transforms are defined by predicting finer resolution levels of information from coarser ones using an operator, called prediction operator, and defining details (or wavelet coefficients) that are the difference between the exact and predicted values. In this paper we use tools of statistical learning in order to design a more accurate prediction operator in this framework based on a training sample, resulting in multiresolution decompositions with enhanced sparsity. In the case of images, we incorporate edge detection techniques in the design of the prediction operator in order to avoid Gibbs phenomenon. Numerical tests are presented showing that the …

business.industry020206 networking & telecommunicationsPattern recognition02 engineering and technologySample (graphics)Edge detectionGibbs phenomenonsymbols.namesakeWaveletOperator (computer programming)Control and Systems EngineeringCompression (functional analysis)Statistical learning theorySignal Processing0202 electrical engineering electronic engineering information engineeringsymbols020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceElectrical and Electronic EngineeringbusinessSoftwareImage compressionMathematicsSignal Processing
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Repeatability Study on a Classifier for Gastric Cancer Detection from Breath Sensor Data

2019

The SNIFFPHONE device is a portable multichannel gas sensor, aiming to detect gastric cancer (GC) from breath samples. It employs gold nanoparticle (GNP) sensors reacting to volatile organic compounds (VOCs) in the exhaled breath, a non-invasive technique to support early diagnosis. This study evaluates the repeatability of the SNIFFPHONE classification result for measurements conducted on healthy subjects over a short period of time of less than 10 minutes. Due to the portable nature of the device, repeatability is studied with respect to varying measurement location. We find the classification results repeatable with a statistically significant 81 % Pearson correlation coefficient, even t…

business.industryBreath sensorHealthy subjects02 engineering and technologyCancer detectionRepeatability021001 nanoscience & nanotechnologyCancer detectionPearson product-moment correlation coefficient03 medical and health sciencessymbols.namesake0302 clinical medicineSDG 3 - Good Health and Well-beingVolatile organic compunds030220 oncology & carcinogenesisClassification resultsymbolsMedicine/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingDecision support for health0210 nano-technologybusinessGastric cancerClassifier (UML)Biomedical engineering
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