Search results for " predictive"

showing 10 items of 163 documents

Innovative tools to diagnose the impact of land use practices on soil microbial communities

2018

International audience; Preservation and sustainable use of soil biological communities represent major challenges in the current agroecological context. Indeed, most of soil ecosystem services results from biological functions particularly driven by taxonomic and functional assemblages of microbiological communities (i.e. nutrient cycling, soil aggregation, depollution, etc.). Consequently, soil microbial communities are logical candidates as effective indicators of soil quality and sustainability. But, good biological indicators must be associated with references that encompass an operating range of measured values that allow performing the desired diagnosis. Even if numerous studies have…

[SDE] Environmental Sciencessoil microbial indicatorssoil biological diagnosisstatistical predictive model[SDE]Environmental Sciences
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Percutaneous Coronary Revascularization for Chronic Total Occlusions A Novel Predictive Score of Technical Failure Using Advanced Technologies

2016

Objectives The aims of this study were to describe the 10-year experience of a single operator dedicated to chronic total occlusion (CTO) and to establish a model for predicting technical failure. Background During the last decade, the interest in percutaneous coronary interventions (PCIs) of chronic total occlusions (CTOs) has increased, allowing the improvement of success rate. Methods One thousand nineteen patients with CTO underwent 1,073 CTO procedures performed by a single CTO-dedicated operator. The study population was subdivided into 2 groups by time period: period 1 (January 2005 to December 2009, n = 378) and period 2 (January 2010 to December 2014, n = 641). Observations were ra…

chronic total occlusions J-CTO score predictive score technical failureSettore MED/11 - Malattie Dell'Apparato Cardiovascolare
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Semi-parametric estimation of conditional intensity functions in inhomogeneous space-time point processes

2009

Dealing with data coming from a space-time inhomogeneous process, there is often the need of obtaining estimates of the conditional intensity function, without a complete defi nition of a parametric model and so nonparametric estimation is required: isotropic or anisotropic kernel estimates can be used. The properties of the intensities estimated are not always good, expecially in seismological field. We could try to choose the bandwidth in order to have good predictive properties of the estimated intensity function. Since a direct ML approach can not be followed, we use an estimation procedure based on the further increments of likelihood obtained adding a new observation. Similarly to cro…

conditional intensity function forward likelihood predictive estimation kernel estimatorSettore SECS-S/01 - Statistica
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Validación de una Medida de Clima de Servicio en las Organizaciones

2012

Service climate is critical for organizations pertaining to the service sector. It reflects the importance organizations attribute to service quality and efforts to please customers. Using previous work of Schneider, White, and Paul (1998) as starting point, this research validates a measure of service climate in the Spanish language. Data from two survey study projects were brought together. A total of 120 hotels, located in Spain, participated in the research. The sample consisted of 508 frontline hotel employees distributed in 152 work-units. Our results confirmed that construct and predictive validity are satisfactory, with four factors describing the facets of service climate: Global S…

construct validity predictive validity service climate shared perceptions
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Predictive control of convex polyhedron LPV systems with Markov jumping parameters

2012

The problem of receding horizon predictive control of stochastic linear parameter varying systems is discussed. First, constant coefficient matrices are obtained at each vertex in the interior of linear parameter varying system, and then, by considering semi-definite programming constraints, weight coefficients between each vertex are calculated, and the equal coefficients matrices for the time variable system are obtained. Second, in the given receding horizon, for each mode sequence of the stochastic convex polyhedron linear parameter varying systems, the optimal control input sequences are designed in order to make the states into a terminal invariant set. Outside of the receding horizon…

convex polyhedronMarkov chainlinear parameter varying systemsLinear systemMathematicsofComputing_NUMERICALANALYSISLinear matrix inequalityOptimal controlModel predictive controlControl theoryConvex polytopeConvex optimizationMarkov jumping parametersInvariant (mathematics)predictive controlMathematics2012 24th Chinese Control and Decision Conference (CCDC)
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An analysis of model predictive control with integral action applied to digital displacement cylinders

2020

This article aims to analyze Model Predictive Control (MPC) for the control of multi-chamber cylinders. MPC with and without integral action has been introduced. Three different algorithms have been used to solve the optimization problem in the MPC. The different algorithms have been compared with an industrial solver. The influence of changing mass, choosing a different middle line pressure, system delays, signal noise, velocity estimation, and changing pressure levels has been investigated. It is concluded that for the small prediction horizon used in the paper a simple algorithm such as A can produce results as good as the previously used Differential Evolution algorithm in less than hal…

digital displacement cylindersOptimizationbusiness.industryStructural engineeringVDP::Mechanical engineering: 570lcsh:QA75.5-76.95Computer Science ApplicationsDigital Displacement CylindersIntegral actionModel predictive controlModell-prediktiv reguleringControl and Systems EngineeringVDP::Maskinfag: 570Modeling and SimulationOptimaliseringDisplacement (orthopedic surgery)lcsh:Electronic computers. Computer scienceModel predictive controlbusinessSoftwareModel Predictive ControlMathematics
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The policy of public health genomics in Italy.

2013

Abstract Italy has a monitoring system for genetic testing, consisting in a periodic census of clinical and laboratory activities performed in the country. The experience is limited, however, concerning the translation of genomic testing for complex diseases into clinical practice. For the first time the Italian Ministry of Health has introduced a policy strategic plan on genomics and predictive medicine within the 2010–2012 National Prevention Plan. This achievement was supported by the Italian Network for Public Health Genomics (GENISAP) and will likely contribute to the integration of public health genomics into health care in the country. Our experience might be of interest not only in …

medicine.medical_specialtyEconomic growthpublic health genomicsSettore MED/03 - GENETICA MEDICASettore MED/42 - Igiene Generale E ApplicataPredictive medicinepredictive medicineEnvironmental healthHealth caremedicineNational PolicyHumansGenetic Testingpolicy genomicsHealth policyGenetic testingStrategic planningnational policyPublic health genomicsmedicine.diagnostic_testbusiness.industryPublic healthHealth PolicyGenetic Diseases InbornGenomicspublic health genomics public health policyHealth PlanningInbornItalyGenetic DiseasesPublic HealthbusinessDelivery of Health Carepolicypublic health genomics; predictive medicine; national policyHealth policy (Amsterdam, Netherlands)
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Prediction of N0 Irradiated Rectal Cancer Comparing MRI Before and After Preoperative Chemoradiotherapy

2017

Background: The prediction of lymph node status using MRI has an impact on the management of rectal cancer, both before and after preoperative chemoradiotherapy. Objective: The purpose of this study was to maximize the negative predictive value and sensitivity of mesorectal lymph node imaging after chemoradiotherapy because postchemoradiation node-negative patients may be treated with rectum-sparing approaches. Design: This was a retrospective study. Settings: The study was conducted at a tertiary care hospital. Patients: Sixty-four patients with locally advanced rectal cancer who underwent preoperative chemoradiotherapy and MRI for staging and the assessment of response were evaluated. Mai…

medicine.medical_specialtyStagingColorectal cancerNegative predictive valuePreoperative care03 medical and health sciences0302 clinical medicineMagnetic resonance imagingmedicineRectal cancer; Chemoradiotherapy; Lymph node; Staging; Magnetic resonance imaging; Negative predictive value.Rectal cancerLymph nodeMesorectalmedicine.diagnostic_testbusiness.industryGastroenterologyMagnetic resonance imagingGeneral MedicineChemoradiotherapymedicine.diseasemedicine.anatomical_structure030220 oncology & carcinogenesisPredictive value of testsAdenocarcinoma030211 gastroenterology & hepatologyLymph nodeRadiologybusinessChemoradiotherapy
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Conditional predictive inference for online surveillance of spatial disease incidence

2011

This paper deals with the development of statistical methodology for timely detection of incident disease clusters in space and time. The increasing availability of data on both the time and the location of events enables the construction of multivariate surveillance techniques, which may enhance the ability to detect localized clusters of disease relative to the surveillance of the overall count of disease cases across the entire study region. We introduce the surveillance conditional predictive ordinate as a general Bayesian model-based surveillance technique that allows us to detect small areas of increased disease incidence when spatial data are available. To address the problem of mult…

multiple comparisonsGeorgiaIncidenceSouth Carolinalagged loss functionBayes TheoremBayesian hierarchical modelspublic health surveillanceArticleconditional predictive ordinatePopulation Surveillancespatial dataSalmonella InfectionsCluster AnalysisHumansComputer SimulationPoisson Distribution
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Mixed estimation technique in semi-parametric space-time point processes for earthquake description

2013

An estimation approach for the semi-parametric intensity function of a particular space-time point process is introduced. In particular we want to account for the estimation of parametric and nonparametric components simultaneously, applying a forward predictive likelihood to semi-parametric models. For each event, the probability of being a background event or one belonging to a seismic sequence is therefore estimated.

point proceNonparametric estimationSettore SECS-S/01 - Statisticaforward predictive likelihoodearthquakesETAS model
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