Search results for "Component analysis"

showing 10 items of 562 documents

A Statistical Approach for A-Posteriori Deployment of Microclimate Sensors in Museums: A Case Study

2022

[EN] The deployment of sensors is the first issue encountered when microclimate monitoring is planned in spaces devoted to the conservation of artworks. Sometimes, the first decision regarding the position of sensors may not be suitable for characterising the microclimate close to climate sensitive artworks or should be revised in light of new circumstances. This paper fits into this context by proposing a rational approach for a posteriori deployment of microclimate sensors in museums where long-term temperature and relative humidity observations were available (here, the Rosenborg Castle, Copenhagen, Denmark). Different statistical tools such as box-and-whisker plots, principal component …

principal component analysisMuseumsClimatemuseumESTADISTICA E INVESTIGACION OPERATIVAtemperatureHumidityUNESCO::CIENCIAS ECONÓMICASmultivariate approachsensorsrelative humidityBiochemistryAtomic and Molecular Physics and OpticsAnalytical Chemistrymuseum; microclimate; multivariate approach; principal component analysis; cluster analysis; sensors; deployment; temperature; relative humiditycluster analysis; deployment; microclimate; multivariate approach; museum; principal component analysis; relative humidity; sensors; temperature; Climate; Humidity; Temperature; Microclimate; MuseumsFISICA APLICADAdeploymentElectrical and Electronic EngineeringInstrumentationmicroclimatecluster analysisSensors; Volume 22; Issue 12; Pages: 4547
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UInDeSI4.0 : An efficient Unsupervised Intrusion Detection System for network traffic flow in Industry 4.0 ecosystem

2023

In an Industry 4.0 ecosystem, all the essential components are digitally interconnected, and automation is integrated for higher productivity. However, it invites the risk of increasing cyber-attacks amid the current cyber explosion. The identification and monitoring of these malicious cyber-attacks and intrusions need efficient threat intelligence techniques or intrusion detection systems (IDSs). Reducing the false positive rate in detecting cyber threats is an important step for a safer and reliable environment in any industrial ecosystem. Available approaches for intrusion detection often suffer from high computational costs due to large number of feature instances. Therefore, this paper…

principal component analysisintrusion detectionisolation forestälytekniikkaICAvalvontajärjestelmätindustry 4.0kyberturvallisuustuotantotekniikkaverkkohyökkäyksetrandom forest
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Closed tank pneumatic press application to improve Sauvignon Blanc wine quality and nutraceutical properties

2019

The machines used in the winemaking process directly affect the quality of wine and its nutraceutical properties. Grapes-pressing is a very important step in winemaking as it may promote the presence and/or absence of enzymatic processes on the must, leading to the creation of different products in terms of chemical composition, starting from the same grapes. The aim of the study was to compare two different pressing systems of Sauvignon Blanc grapes using an innovative pneumatic discontinuous closed tank press in two operating modes: the traditional pressing mode in presence of oxygen and the inert pressing mode, performed through grapes pressing under inert gas with nitrogen recovery. Che…

principal component analysismedia_common.quotation_subjectBioengineering030204 cardiovascular system & hematologyIndustrial and Manufacturing Engineering040501 horticulturelcsh:Agriculture03 medical and health sciences0302 clinical medicineNutraceuticalwinemaking.Quality (business)lcsh:Agriculture (General)Inert gasBrowning reactionWinemakingmedia_commoninert atmosphere low-oxygen must pressing principal component analysis winemakingPressingWineInertMechanical Engineeringlcsh:SSettore AGR/09 - Meccanica AgrariaInert pressingmust and wine04 agricultural and veterinary sciencesPulp and paper industrylcsh:S1-972Environmental science0405 other agricultural sciencesJournal of Agricultural Engineering
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Determination of Changes in the Quality of Surface Water in the River—Reservoir System

2021

Assessing the changing parameters of water quality at different points in the river–reservoir system can help prevent river pollution and implement remedial policies. It is also crucial in modeling water resources. Multivariate statistical analysis is useful for the analysis of changes in surface water quality. It helps to identify indicators that may be responsible for the eutrophication process of a reservoir. Additionally, the analysis of the water quality profile and the water quality index (WQI) is useful in assessing water pollution. These tools can support and verify the results of a multivariate statistical analysis. In this study, changes in water quality parameters of the Turawa r…

reservoirRDAriver0208 environmental biotechnologyGeography Planning and Developmentlcsh:TJ807-830lcsh:Renewable energy sourceschemistry.chemical_elementSoil science02 engineering and technology010501 environmental sciencesManagement Monitoring Policy and Law01 natural scienceswater qualitywater quality; reservoir; river; eutrophication; RDA; PCA; WQI; water quality profileWater pollutionlcsh:Environmental sciences0105 earth and related environmental scienceslcsh:GE1-350PCARenewable Energy Sustainability and the EnvironmentPhosphoruslcsh:Environmental effects of industries and plantsNitrogen020801 environmental engineeringWater resourceseutrophicationlcsh:TD194-195chemistryPrincipal component analysisEnvironmental scienceWater qualityEutrophicationSurface waterSustainability
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Emulation of Sun-Induced Fluorescence from Radiance Data Recorded by the HyPlant Airborne Imaging Spectrometer

2021

The retrieval of sun-induced fluorescence (SIF) from hyperspectral radiance data grew to maturity with research activities around the FLuorescence EXplorer satellite mission FLEX, yet full-spectrum estimation methods such as the spectral fitting method (SFM) are computationally expensive. To bypass this computational load, this work aims to approximate the SFM-based SIF retrieval by means of statistical learning, i.e., emulation. While emulators emerged as fast surrogate models of simulators, the accuracy-speedup trade-offs are still to be analyzed when the emulation concept is applied to experimental data. We evaluated the possibility of approximating the SFM-like SIF output directly based…

sif010504 meteorology & atmospheric sciencesprincipal component analysisComputer scienceSciencesun-induced fluorescenceMultispectral image0211 other engineering and technologiesImaging spectrometeremulation02 engineering and technology01 natural sciencesRobustness (computer science)emulation; machine learning; sun-induced fluorescence; sif; spectral fitting method (sfm); principal component analysis021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingEmulationDimensionality reductionQHyperspectral imagingspectral fitting method (sfm)machine learningPrincipal component analysisRadianceGeneral Earth and Planetary Sciencesddc:620Remote Sensing
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Combining PCA and multiset CCA for dimension reduction when group ICA is applied to decompose naturalistic fMRI data

2015

An extension of group independent component analysis (GICA) is introduced, where multi-set canonical correlation analysis (MCCA) is combined with principal component analysis (PCA) for three-stage dimension reduction. The method is applied on naturalistic functional MRI (fMRI) images acquired during task-free continuous music listening experiment, and the results are compared with the outcome of the conventional GICA. The extended GICA resulted slightly faster ICA convergence and, more interestingly, extracted more stimulus-related components than its conventional counterpart. Therefore, we think the extension is beneficial enhancement for GICA, especially when applied to challenging fMRI d…

ta113MultisetPCAGroup (mathematics)business.industrydimension reductionSpeech recognitionDimensionality reductionPattern recognitionMusic listeningta3112naturalistic fMRIGroup independent component analysisPrincipal component analysistemporal cocatenationArtificial intelligenceCanonical correlationbusinessmultiset CCAMathematics
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Can back-projection fully resolve polarity indeterminacy of independent component analysis in study of event-related potential?

2011

a b s t r a c t In the study of event-related potentials (ERPs) using independent component analysis (ICA), it is a traditional way to project the extracted ERP component back to electrodes for correcting its scaling (magnitude and polarity) indeterminacy. However, ICA tends to be locally optimized in practice, and then, the back-projection of a component estimated by the ICA can possibly not fully correct its polarity at every electrode. We demonstrate this phenomenon from the view of the theoretical analysis and numerical simulations and suggest checking and modifying the abnormal polarity of the projected component in the electrode field before further analysis. Moreover, when several co…

ta113Theoretical computer scienceComputer sciencePolarity (physics)Parallel projectionHealth InformaticsIndependent component analysisComponent (UML)Signal ProcessingPoint (geometry)Projection (set theory)Global optimizationScalingAlgorithmBiomedical Signal Processing and Control
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Online anomaly detection using dimensionality reduction techniques for HTTP log analysis

2015

Modern web services face an increasing number of new threats. Logs are collected from almost all web servers, and for this reason analyzing them is beneficial when trying to prevent intrusions. Intrusive behavior often differs from the normal web traffic. This paper proposes a framework to find abnormal behavior from these logs. We compare random projection, principal component analysis and diffusion map for anomaly detection. In addition, the framework has online capabilities. The first two methods have intuitive extensions while diffusion map uses the Nyström extension. This fast out-of-sample extension enables real-time analysis of web server traffic. The framework is demonstrated using …

ta113Web serverComputer Networks and Communicationsbusiness.industryComputer scienceRandom projectionDimensionality reductionRandom projectionPrincipal component analysisIntrusion detection systemAnomaly detectionMachine learningcomputer.software_genreCyber securityWeb trafficPrincipal component analysisDiffusion mapAnomaly detectionIntrusion detectionArtificial intelligenceData miningWeb servicebusinesskyberturvallisuuscomputer
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Determining the number of sources in high-density EEG recordings of event-related potentials by model order selection

2011

To high-density electroencephalography (EEG) recordings, determining the number of sources to separate the signal and the noise subspace is very important. A mostly used criterion is that percentage of variance of raw data explained by the selected principal components composing the signal space should be over 90%. Recently, a model order selection method named as GAP has been proposed. We investigated the two methods by performing independent component analysis (ICA) on the estimated signal subspace, assuming the number of selected principal components composing the signal subspace is equal to the number of sources of brain activities. Through examining wavelet-filtered EEG recordings (128…

ta113medicine.diagnostic_testNoise (signal processing)business.industryPattern recognitionElectroencephalographyExplained variationIndependent component analysisSignalPrincipal component analysismedicineArtificial intelligencebusinessSubspace topologyMathematicsSignal subspace2011 IEEE International Workshop on Machine Learning for Signal Processing
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Sustaining Attention for a Prolonged Duration Affects Dynamic Organizations of Frequency-Specific Functional Connectivity

2020

Sustained attention encompasses a cascade of fundamental functions. The human ability to implement a sustained attention task is supported by brain networks that dynamically formed and dissolved through oscillatory synchronization. The decrement of vigilance induced by prolonged task engagement affects sustained attention. However, little is known about which stage or combinations are affected by vigilance decrement. Here, we applied an analysis framework composed of weighted phase lag index (wPLI) and tensor component analysis (TCA) to an EEG dataset collected during 80 min sustained attention task to examine the electrophysiological basis of such effect. We aimed to characterize the phase…

vigilance decrementmedia_common.quotation_subjecttensor component analysisWeighted phase lag indexElectroencephalographybehavioral disciplines and activitiesFrequency-specific dynamic functional connectivitySustaining attentionRewardmotivationmedicineHumansRadiology Nuclear Medicine and imagingAttentionWakefulnesstarkkaavaisuusmedia_commonmotivaatioOriginal PaperMotivationRadiological and Ultrasound Technologymedicine.diagnostic_testsignaalinkäsittelyFunctional connectivityBrainsignaalianalyysiTask engagementSustained attentionPhase lagElectrophysiological PhenomenaElectrophysiologysustained attentionNeurologyTensor component analysisSensorimotor networkVigilance decrementweighted phase lag indexfrequency-specific dynamic functional connectivityNeurology (clinical)kognitiivinen neurotiedeAnatomyPsychologyNeuroscienceVigilance (psychology)
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