Search results for " reduction"

showing 10 items of 891 documents

Optimized Class-Separability in Hyperspectral Images

2016

International audience; Image visualization techniques are mostly based on three bands as RGB color composite channels for human eye to characterize the scene. This, however, is not effective in case of hyper-spectral images (HSI) because they contain dozens of informative spectral bands. To eliminate redundancy of spectral information among these bands, dimensionality reduction (DR) is applied while at the same trying to retain maximum information. In this paper, we propose a new method of information-preserved hyper-spectral satellite image visualization that is based on fusion of unsupervised band selection techniques and color matching function (CMF) stretching. The results show consist…

010504 meteorology & atmospheric sciencesBand SelectionComputer science0211 other engineering and technologiesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[SDU.STU]Sciences of the Universe [physics]/Earth Sciences02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing01 natural sciencesTransformation[SPI]Engineering Sciences [physics][ SPI.NRJ ] Engineering Sciences [physics]/Electric powerDisplay[ SPI ] Engineering Sciences [physics]Computer visionclass separabilityFusion021101 geological & geomatics engineering0105 earth and related environmental sciencesColor imagebusiness.industry[SPI.NRJ]Engineering Sciences [physics]/Electric powerHyperspectral imagingPattern recognition[ SDU.STU ] Sciences of the Universe [physics]/Earth SciencesImage segmentationSpectral bandsDimensionality reductionVisualization[SPI.TRON]Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/ElectronicsImaging spectroscopyFull spectral imagingRGB color modelArtificial intelligencehyper-spectral image visualizationbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Statistical retrieval of atmospheric profiles with deep convolutional neural networks

2019

Abstract Infrared atmospheric sounders, such as IASI, provide an unprecedented source of information for atmosphere monitoring and weather forecasting. Sensors provide rich spectral information that allows retrieval of temperature and moisture profiles. From a statistical point of view, the challenge is immense: on the one hand, “underdetermination” is common place as regression needs to work on high dimensional input and output spaces; on the other hand, redundancy is present in all dimensions (spatial, spectral and temporal). On top of this, several noise sources are encountered in the data. In this paper, we present for the first time the use of convolutional neural networks for the retr…

010504 meteorology & atmospheric sciencesComputer science0211 other engineering and technologiesWeather forecasting02 engineering and technologycomputer.software_genreAtmospheric measurements01 natural sciencesConvolutional neural networkLinear regressionRedundancy (engineering)Information retrievalInfrared measurementsComputers in Earth SciencesEngineering (miscellaneous)021101 geological & geomatics engineering0105 earth and related environmental sciencesArtificial neural networkbusiness.industryDeep learningDimensionality reductionPattern recognitionAtomic and Molecular Physics and OpticsComputer Science Applications13. Climate actionNoise (video)Artificial intelligencebusinesscomputerNeural networksISPRS Journal of Photogrammetry and Remote Sensing
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Hyperspectral dimensionality reduction for biophysical variable statistical retrieval

2017

Abstract Current and upcoming airborne and spaceborne imaging spectrometers lead to vast hyperspectral data streams. This scenario calls for automated and optimized spectral dimensionality reduction techniques to enable fast and efficient hyperspectral data processing, such as inferring vegetation properties. In preparation of next generation biophysical variable retrieval methods applicable to hyperspectral data, we present the evaluation of 11 dimensionality reduction (DR) methods in combination with advanced machine learning regression algorithms (MLRAs) for statistical variable retrieval. Two unique hyperspectral datasets were analyzed on the predictive power of DR + MLRA methods to ret…

010504 meteorology & atmospheric sciencesMean squared errorComputer science0211 other engineering and technologies02 engineering and technologycomputer.software_genre01 natural sciencessymbols.namesakeLinear regressionComputers in Earth SciencesEngineering (miscellaneous)Gaussian processHyMap021101 geological & geomatics engineering0105 earth and related environmental sciencesData stream miningbusiness.industryDimensionality reductionHyperspectral imagingPattern recognitionAtomic and Molecular Physics and OpticsComputer Science ApplicationsKernel (statistics)symbolsData miningArtificial intelligencebusinesscomputerISPRS Journal of Photogrammetry and Remote Sensing
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Insect repellent and chemical agronomic treatments to reduce seed numberin'Afourer'mandarin. Effect on yield and fruit diameter

2019

Abstract Obtaining citrus fruits without seeds is a recurrent objective for farmers as it is one of the most valued characteristics, especially in mandarins. ‘Afourer’ tangor is a highly valuable well-established mandarin, and a high percentage of seeded fruits are produced under cross-pollination conditions. Several agronomic techniques have been suggested to control presence of seeds, such as covering with nets and copper sulfate (CuSO4) and gibberellic acid (GA3) treatments. Natural bee repellents are also proposed to reduce the number of seeds per fruit. In this study, we aimed to compare the effect of several agronomic treatments to reduce the seed number in 'Afourer' mandarin. To this…

0106 biological sciences0301 basic medicineInsecticidesAfourerBOTANICACitrus fruitsAgricultura ExperimentacióHorticulture01 natural sciencesMandarin Chinese03 medical and health scienceschemistry.chemical_compoundYield (wine)Copper sulfateGibberellic acidGibberellic acidTangorbiologySeed numberWeak relationshipInsect repellentfood and beveragesCopper sulfatebiology.organism_classificationlanguage.human_languageHorticultureCapsicum annuumFruita030104 developmental biologychemistrylanguageSeed reductionNet-covered treesInsect repellentFruit diameter010606 plant biology & botany
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Seasonal cycle of benthic denitrification and DNRA in the aphotic coastal zone, northern Baltic Sea

2020

Current knowledge on the seasonality of benthic nitrate reduction pathways in the aphotic, density stratified coastal zone of the Baltic Sea is largely based on data from muddy sediments, neglecting the potential contribution of sandy sediments. To gain a more comprehensive understanding of seasonality in this part of the Baltic Sea coast, we measured rates of benthic denitrification, anammox and dissimilatory nitrate reduction to ammonium (DNRA) monthly in the ice-free period of 2016 in both sandy and muddy aphotic sediments, northwestern Gulf of Finland. No anammox was observed. The seasonal cycle of denitrification in both sediment types was related to the hydrography-driven development …

0106 biological sciencesDenitrification010504 meteorology & atmospheric sciencesMARINE-SEDIMENTSFIXED-NITROGENsedimentitANAMMOX01 natural scienceswater column density stratificationCoastal zoneorganic matterNUTRIENT FLUXESEcologykausivaihtelutnitraatitWater column density stratificationOceanographyBenthic zoneOrganic matterorgaaninen ainesSeasonal cycledenitrifikaatioSandy sedimentrannikkoalueetDISSIMILATORY NITRATE REDUCTIONNutrient fluxAquatic ScienceNITRIFICATIONNitrate reduction14. Life underwaterCoastal filter1172 Environmental sciencesEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesbenthic−pelagic coupling010604 marine biology & hydrobiologyGeomorphologyISOTOPE PAIRING TECHNIQUENorthern Gulf of FinlandBenthic-pelagic couplingAMMONIUMgeomorphologysandy sedimentESTUARINE SEDIMENTNITROGEN REMOVALnitrate reductionBaltic sea13. Climate actionAphotic zonecoastal filteraineiden kiertoEnvironmental scienceNitrificationMarine Ecology Progress Series
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Genome Economization in the Endosymbiont of the Wood Roach Cryptocercus punctulatus Due to Drastic Loss of Amino Acid Synthesis Capabilities

2011

Cockroaches (Blattaria: Dictyoptera) harbor the endosymbiont Blattabacterium sp. in their abdominal fat body. This endosymbiont is involved in nitrogen recycling and amino acid provision to its host. In this study, the genome of Blattabacterium sp. of Cryptocercus punctulatus (BCpu) was sequenced and compared with those of the symbionts of Blattella germanica and Periplaneta americana, BBge and BPam, respectively. The BCpu genome consists of a chromosome of 605.7 kb and a plasmid of 3.8 kb and is therefore approximately 31 kb smaller than the other two aforementioned genomes. The size reduction is due to the loss of 55 genes, 23 of which belong to biosynthetic pathways for amino acids. The …

0106 biological sciencesMaleMolecular Sequence DataCockroachesBiology010603 evolutionary biology01 natural sciences03 medical and health scienceschemistry.chemical_compoundBlattabacteriumGenome SizeValineGeneticsEndophytesAnimalsAmino Acidsgenome reductionGenome sizeEcology Evolution Behavior and SystematicsAmino acid synthesisResearch Articles030304 developmental biology2. Zero hungerchemistry.chemical_classificationGenetics0303 health sciencesBlattabacteriumMethionineBacteroideteswood-feedingbiology.organism_classificationsymbiosisAmino acidchemistryBiochemistrymetabolic pathway lossFemaleIsoleucineLeucineGenome BacterialGenome Biology and Evolution
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Aflatoxins and A. flavus Reduction in Loaf Bread through the Use of Natural Ingredients

2018

In this study, the antifungal activity of yellow mustard (YMF) and oriental mustard (OMF) meal extracts against 14 strains of fungi was tested on a solid medium. The results obtained with the YMF were next confirmed in liquid medium determining the minimum inhibitory concentration (MIC) and the minimum fungicide concentration (MFC). Finally, the use of YMF as a natural preservative to extend the useful life of bread was evaluated. Breads with different concentrations of YMF (2, 4, 6 and 8 g/kg) were prepared and contaminated with Aspergillus flavus ISPA 8111 and Penicillium nordicum CECT 2320. For 10 days the formation of mycelium was observed, and after that the fungal growth and the mycot…

0106 biological sciencesPreservativeAflatoxinaflatoxinsAntifungal AgentsMustard CompoundsPharmaceutical ScienceAspergillus flavusMicrobial Sensitivity TestsShelf life01 natural sciencesArticleAnalytical Chemistrylcsh:QD241-441chemistry.chemical_compound0404 agricultural biotechnologylcsh:Organic chemistry010608 biotechnologyDrug DiscoveryFood sciencePhysical and Theoretical ChemistryLC-MS/MSMycotoxinMyceliumMolecular Structurebiologymycotoxin reductionOrganic Chemistrydigestive oral and skin physiologyPenicilliumfood and beveragesBread04 agricultural and veterinary sciencesbiology.organism_classification040401 food sciencemustard flourFungicideFood StoragechemistryChemistry (miscellaneous)Sodium propionateFood MicrobiologyFood PreservativesMolecular Medicineshelf lifePropionatesAspergillus flavusMolecules
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Use of biochar as peat substitute for growing substrates of Euphorbia × lomi potted plants

2016

Biochar from conifers wood was used in soilless culture as growing substrate alternative to peat for ornamental crops. Potted plants of Euphorbia × lomi Rauh cv. ‘Ilaria’ were grown with different mixtures (v:v) of brown peat and biochar in order to evaluate main physical and chemical characteristics of this biomaterial as well as its effect on plant growth, ornamental characteristics and nutrients uptake. Biochar addition to peat increased pH, EC and K content of the growing substrates, as well as air content and bulk density. Biochar content of substrates significantly affected plant growth and biomass partitioning: higher number of shoots and leaves, leaf area and leaf dry weight were re…

0106 biological sciencesSettore BIO/07 - EcologiaPeatSettore AGR/13 - Chimica Agrariasoilless culture01 natural scienceslcsh:Agriculturegrowing mediaBiocharOrnamental plantOrnamentalagriculture; plant productionWater-use efficiencyCharcoalChemistrylcsh:S04 agricultural and veterinary sciencesplant growthCharcoal; Growing media; Ornamentals; Peat reduction; Plant growth; Soilless culture; Agronomy and Crop ScienceHydroponicscharcoal; growing media; ornamentals; peat reduction; plant growth; soilless cultureAgronomyvisual_artShoot040103 agronomy & agriculturevisual_art.visual_art_medium0401 agriculture forestry and fisheriesornamentalsBiomass partitioningAgronomy and Crop Sciencecharcoalpeat reduction010606 plant biology & botany
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Reducing waste and ecological impacts through a sustainable and efficient management of perishable food based on the Monte Carlo simulation

2019

Abstract In today’s competitive global market it is mandatory to improve warehousing operations integrating economic, environmental and social aspects. The recent advancement in monitoring technologies can greatly improve the performance of the food supply chain reducing product loss. In particular, in the perishable food supply chain, initially inventory operations are critical because they manage the material flows in very variable conditions. The deterioration level of the products as well as the market demand are the main factors that can influence warehouse strategy. This research aims to consider the application of sustainability principles in the context of warehouse storage, evaluat…

0106 biological sciencesTraceabilityComputer scienceSupply chainGeneral Decision SciencesContext (language use)010501 environmental sciences010603 evolutionary biology01 natural sciencesWarehouse managementSupply and demandSettore ING-IND/17 - Impianti Industriali MeccaniciMonte Carlo simulationEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesEcologyEcological impacts Food waste reduction Monte Carlo simulation Shelf life model Sustainability Warehouse managementEnvironmental economicsEcological impactWarehouseProduct (business)SustainabilitySustainabilityShelf life modelCarbon footprintEcological impacts; Food waste reduction; Monte Carlo simulation; Shelf life model; Sustainability; Warehouse managementFood waste reductionEcological Indicators
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Health Indicator for Low-Speed Axial Bearings Using Variational Autoencoders

2020

This paper proposes a method for calculating a health indicator (HI) for low-speed axial rolling element bearing (REB) health assessment by utilizing the latent representation obtained by variational inference using Variational Autoencoders (VAEs), trained on each speed reference in the dataset. Further, versatility is added by conditioning on the speed, extending the VAE to a conditional VAE (CVAE), thereby incorporating all speeds in a single model. Within the framework, the coefficients of autoregressive (AR) models are used as features. The dimensionality reduction inherent in the proposed method lowers the need of expert knowledge to design good condition indicators. Moreover, the sugg…

0209 industrial biotechnologyGeneral Computer Sciencegenerative modelsComputer sciencecondition monitoring02 engineering and technologyLatent variableunsupervised learningFault detection and isolationBearing fault detection020901 industrial engineering & automationVDP::Teknologi: 500::Maskinfag: 5700202 electrical engineering electronic engineering information engineeringGeneral Materials Sciencevariational autoencoderconditional variational autoencoderbusiness.industryDimensionality reduction020208 electrical & electronic engineeringGeneral EngineeringPattern recognitionData pointAutoregressive modelRolling-element bearingFalse alarmArtificial intelligencelcsh:Electrical engineering. Electronics. Nuclear engineeringbusinesslcsh:TK1-9971IEEE Access
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