Search results for " Models"

showing 10 items of 4240 documents

Algorithmic Differentiation for Cloud Schemes

2019

<p>Numerical models in atmospheric sciences do not only need to approximate the flow equations on a suitable computational grid, they also need to include subgrid effects of many non-resolved physical processes. Among others, the formation and evolution of cloud particles is an example of such subgrid processes. Moreover, to date there is no universal mathematical description of a cloud, hence many cloud schemes were proposed and these schemes typically contain several uncertain parameters. In this study, we propose the use of algorithmic differentiation (AD) as a method to identify parameters within the cloud scheme, to which the output of the cloud scheme is most sensitive.…

Scheme (programming language)Mathematical optimizationAutomatic differentiationbusiness.industryComputer scienceCloud computingLimitingNumerical modelsGridFlow (mathematics)Uncertainty quantificationbusinesscomputercomputer.programming_language
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The Multilevel Model in the Computer-Generated Appraisal: A Case in Palermo

2017

The construction of a mass appraisal model requires the preliminary study of the real estate market, the sampling of sold properties, the development of a forecasting model and the verification of the appraisal results. They are generally computerised methods, that work with geo-referenced data. This experimental work has proceeded to build a mass appraisal model, collecting a data sample of sales of apartments in the city of Palermo, in the five years 2008–2012, using a multivariate statistical model (multilevel), testing the results and providing the operating applications in a scheme of online real estate valuations.

Scheme (programming language)Operations researchComputer scienceMass appraisalMultilevel model0211 other engineering and technologiesSampling (statistics)021107 urban & regional planningReal estate02 engineering and technologyWork (electrical)021105 building & constructionComputer-generated appraisal Multilevel models AVMSettore ICAR/22 - EstimoExperimental workMultivariate statisticalcomputercomputer.programming_language
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Partial Methylation at Am100 in 18S rRNA of Baker's Yeast Reveals Ribosome Heterogeneity on the Level of Eukaryotic rRNA Modification

2014

Ribosome heterogeneity is of increasing biological significance and several examples have been described for multicellular and single cells organisms. In here we show for the first time a variation in ribose methylation within the 18S rRNA of Saccharomyces cerevisiae. Using RNA-cleaving DNAzymes, we could specifically demonstrate that a significant amount of S. cerevisiae ribosomes are not methylated at 2'-O-ribose of A100 residue in the 18S rRNA. Furthermore, using LC-UV-MS/MS of a respective 18S rRNA fragment, we could not only corroborate the partial methylation at A100, but could also quantify the methylated versus non-methylated A100 residue. Here, we exhibit that only 68% of A100 in t…

Science5.8S ribosomal RNAYeast and Fungal ModelsSaccharomyces cerevisiaeMycologyBiologyMethylationBiochemistryMicrobiologyMolecular GeneticsModel OrganismsMolecular cell biologyRRNA modification23S ribosomal RNANucleic Acidsddc:570GeneticsEukaryotic Small Ribosomal SubunitBiologyNucleic Acid ComponentsGeneticsMultidisciplinaryQRTranslation (biology)DNAMethylationRibosomal RNAYeastRNA processingBiochemistryRNA RibosomalRibosome SubunitsMedicineRNARibosomesResearch ArticlePLoS ONE
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Volatility Transmission Models: A Survey

2005

This study reviews the literature on volatility transmission in order to determine what we have learnt about the different methodologies applied. In particular, GARCH, regime switching and stochastic volatility models are analysed. In addition, this study covers several concrete aspects such as their scope of application, the overlapping problem, the concept of efficiency and asymmetry modelling. Finally, emerging topics and unanswered questions are identified, serving as an agenda for future research.

Scope (project management)Stochastic volatilityOrder (exchange)Financial economicsFinancial models with long-tailed distributions and volatility clusteringAutoregressive conditional heteroskedasticityVolatility swapVolatility smileEconometricsEconomicsImplied volatilitySSRN Electronic Journal
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Inhibition of the pro-inflammatory mediators' production and anti-inflammatory effect of the iridoid scrovalentinoside.

2007

We have studied scrovalentinoside, an iridoid with anti-inflammatory properties isolated from Scrophularia auriculata ssp. pseudoauriculata, as an anti-inflammatory agent in different experimental models of delayed-type hypersensitivity. We found that scrovalentinoside reduced the edema induced by oxazolone at 0.5 mg/ear and sheep red blood cells at 10 mg/kg. The observed effect occurred during the last phase or inflammatory response; during the earlier phase or induction of the delayed-type hypersensitivity reaction, no significant activity was noted. Thus, scrovalentinoside reduced both the edema and cell infiltration in vivo and reduced lymphocyte proliferation in vitro, affecting the cy…

ScrophulariaLeukotriene B4medicine.medical_treatmentT-LymphocytesBlotting WesternAnti-Inflammatory AgentsInflammationLymphocyte proliferationPharmacologyOxazolonechemistry.chemical_compoundMiceReceptors GlucocorticoidEdemaDrug DiscoverymedicineAnimalsEdemaHumansHypersensitivity DelayedIridoidsGlycosidesPhytohemagglutininsUnsaturated fatty acidCell ProliferationPharmacologyPlants MedicinalChemistryMacrophagesCell CycleOxazoloneRatsDisease Models AnimalCytokineEicosanoidImmunologyIridoid GlycosidesFemalePlant Preparationsmedicine.symptomInflammation MediatorsJournal of ethnopharmacology
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Minimum contrast for point processes' first-order intensity estimation

2023

In this paper, we exploit some theoretical results, from which we know the expected value of the K-function weighted by the true first-order intensity function of a point pattern. This theoretical result can serve as an estimation method for obtaining the parameter estimates of a specific model, assumed for the data. The only requirement is the knowledge of the first-order intensity function expression, completely avoiding writing the likelihood, which is often complex to deal with in point process models. We illustrate the method through simulation studies for spatio-temporal point processes.

Second-order characteristics Spatial statistics Spatio-temporal point processes Local models Minimum contrastSettore SECS-S/01 - Statistica
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Apoyo social de familia, profesorado y amigos, ajuste escolar y bienestar subjetivo en adolescentes peruanos

2021

espanolIntroduccion: La psicologia positiva ha senalado la importancia del bienestar subjetivo de los adolescentes, por ser un precursor del desarrollo positivo de los jovenes. La investigacion resalta la importancia del apoyo social percibido y el ajuste escolar como determinantes del bienestar adolescente. Por ello, este articulo tiene como finalidad analizar las relaciones de la percepcion de apoyo social (de familia, profesorado, amigos) con el bienestar subjetivo de los adolescentes, mediado por su ajuste escolar. Metodo: Participaron 1035 estudiantes peruanos de educacion secundaria, con edades entre 12 y 16 anos. Se probaron dos modelos teoricos con variables latentes, uno con mediac…

Secondary educationTheoretical modelsContext (language use)School adjustmentApoyo socialPsychologyHumanitiesGeneral PsychologySuma Psicológica
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Automatic Segmentation Using a Hybrid Dense Network Integrated With an 3D-Atrous Spatial Pyramid Pooling Module for Computed Tomography (CT) Imaging

2020

Computed tomography (CT) with a contrast-enhanced imaging technique is extensively proposed for the assessment and segmentation of multiple organs, especially organs at risk. It is an important factor involved in the decision making in clinical applications. Automatic segmentation and extraction of abdominal organs, such as thoracic organs at risk, from CT images are challenging tasks due to the low contrast of pixel values surrounding other organs. Various deep learning models based on 2D and 3D convolutional neural networks have been proposed for the segmentation of medical images because of their automatic feature extraction capability based on large labeled datasets. In this paper, we p…

SegTHOR0209 industrial biotechnologyGeneral Computer ScienceComputer scienceFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyConvolutional neural network020901 industrial engineering & automationPyramid0202 electrical engineering electronic engineering information engineeringMedical imagingGeneral Materials ScienceSegmentationPyramid (image processing)3D deep learning modelsPixelbusiness.industryDeep learningGeneral EngineeringPattern recognition3D-atrous spatial pyramid pooling (ASPP)Feature (computer vision)3D volumetric segmentation020201 artificial intelligence & image processinglcsh:Electrical engineering. Electronics. Nuclear engineeringArtificial intelligencebusinesslcsh:TK1-9971IEEE Access
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Elementi di un modellino architettonico in pietra dal Santuario di Contrada Mango a Segesta

2022

Nel 1957, in occasione di una campagna di scavo in Contrada Mango di Segesta, Vincenzo Tusa rinvenne due frammenti litici di membrature architettoniche miniaturistiche, appartenenti ad un fregio dorico e ad una cornice, parimenti dorica. In questa sede, oltre a proporre un’analisi dettagliata dei due frammenti, si cercherà di avanzare alcune ipotesi sul contesto della loro realizzazione, sulla loro funzione e sull’eventuale monumento di riferimento, con una rapida disamina della problematica legata ai paradeigmata architettonici nell’antichità. In 1957, during an excavation campaign in Contrada Mango of Segesta, Vincenzo Tusa found two lithic fragments of miniaturistic architectural element…

Segesta Contrada Mango architectural models paradeigmata templeSettore L-ANT/07 - Archeologia ClassicaSettore ICAR/18 - Storia Dell'ArchitetturaSegesta Contrada Mango modellini architettonici paradeigmata tempio
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Action Recognition based on Hierarchical Self-Organizing Maps

2014

We propose a hierarchical neural architecture able to recognise observed human actions. Each layer in the architecture represents increasingly complex human activity features. The first layer consists of a SOM which performs dimensionality reduction and clustering of the feature space. It represents the dynamics of the stream of posture frames in action sequences as activity trajectories over time. The second layer in the hierarchy consists of another SOM which clusters the activity trajectories of the first-layer SOM and thus it learns to represent action prototypes independent of how long the activity trajectories last. The third layer of the hierarchy consists of a neural network that le…

Self-Organizing Map Neural Network Action Recognition Hierarchical models Intention UnderstandingSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni
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