Search results for "PREDICTION"

showing 10 items of 511 documents

Contributions to the knowledge base on PV performance: Evaluation of the operation of PV systems using different technologies installed in southern N…

2011

To assist in establishing an accepted knowledge base on PV-modules and systems performance using a representative range of technologies, devices have to be installed at diverse locations, covering a broad range of environmental conditions. For the example of a high latitude location, modules and systems are installed and under investigation in southern Norway (Kristiansand region) by the University of Agder in cooperation with industrial partners. This paper presents first results of the analysis of module performance. The operational behavior of the modules is used to derive a modeling scheme applicable for performance prediction. This use is demonstrated by giving the expected annual perf…

Scheme (programming language)business.industryComputer sciencePhotovoltaic systemElectrical engineeringData modelingKnowledge baseRange (aeronautics)Systems engineeringPerformance predictionOperational behaviorbusinesscomputercomputer.programming_language2011 37th IEEE Photovoltaic Specialists Conference
researchProduct

Survival Prediction in Intrahepatic Cholangiocarcinoma: A Proof of Concept Study Using Artificial Intelligence for Risk Assessment

2021

Several scoring systems have been devised to objectively predict survival for patients with intrahepatic cholangiocellular carcinoma (ICC) and support treatment stratification, but they have failed external validation. The aim of the present study was to improve prognostication using an artificial intelligence-based approach. We retrospectively identified 417 patients with ICC who were referred to our tertiary care center between 1997 and 2018. Of these, 293 met the inclusion criteria. Established risk factors served as input nodes for an artificial neural network (ANN). We compared the performance of the trained model to the most widely used conventional scoring system, the Fudan score. Pr…

Scoring systemTertiary careArticle03 medical and health sciences0302 clinical medicineintrahepatic cholangiocarcinomaMedicinesurvival predictionIntrahepatic Cholangiocarcinomarisk scoringTraining setFudan scoreArtificial neural networkbusiness.industryRExternal validationGeneral Medicineartificial intelligencemachine learningCholangiocellular carcinoma030220 oncology & carcinogenesisMedicine030211 gastroenterology & hepatologyArtificial intelligencebusinessRisk assessmentartificial neural networkJournal of Clinical Medicine
researchProduct

Screening for Slow Reading Acquisition in Norway and Finland : a Quest for Context Specific Predictors

2020

Early identification of children at risk of developing reading difficulties is crucial for effective interventions. While orthographies and educational contexts differ, predictors included in early at-risk screening tend to remain rather homogeneous across countries. In this study, we compared longitudinal prediction patterns of being among the 20 percent lowest performing in reading fluency by the end of Grade 1 in Norway (N = 918) and Finland (N =378). The two countries differ in orthographic consistency (semi-transparent versus transparent), age at school entry and pre-primary education. Letter knowledge, phoneme isolation and rapid automatized naming (RAN) were unique predictors in the …

Screening testmedia_common.quotation_subjectEducationDevelopmental psychologyEffective interventionsoppimisvaikeudetPhonological awarenessReading (process):Samfunnsvitenskap: 200::Pedagogiske fag: 280 [VDP]vertaileva tutkimus0501 psychology and cognitive sciencesreading difficultieskielen oppiminenAt-risk studentsmedia_commonFamily characteristics05 social sciences050301 educationennusteetpredictionoikeinkirjoitusIdentification (information)Context specificcross-linguistic comparisonPsychologylukihäiriöt0503 education050104 developmental & child psychologyat-risk students
researchProduct

A fast and efficient picking algorithm for earthquake early warning application based on the variance piecewise constant models

2020

An earthquake warning system, or earthquake early warning system, is a system of accelerometers, seismometers, communication, computers, and alarms that is devised for notifying adjoining regions of a substantial earthquake while it is in progress. This is not the same as earthquake prediction, which is currently incapable of producing decisive event warnings. The implementation of efficient and computationally simple picking algorithm is necessary for this purpose, as well as automatic picking of seismic phases for seismic surveillance and routine earthquake location for fast hypocenter determination. In this paper a method for picking based on the detection of signals changes in variance …

SeismometerHypocenterWarning systemComputingMethodologies_SIMULATIONANDMODELINGComputer scienceEarthquake predictionEarthquake warning systemVariance (accounting)PickingEarthquake Early WarningPiecewiseChange-pointsSettore SECS-S/01 - StatisticaAlgorithmEarthquake location
researchProduct

Prior precision modulates the minimisation of prediction error in human auditory cortex

2018

AbstractThe predictive coding model of perception proposes that successful representation of the perceptual world depends upon cancelling out the discrepancy between prediction and sensory input (i.e., prediction error). Recent studies further suggest a distinction between prediction error associated with non-predicted stimuli of different prior precision (i.e., inverse variance). However, it is not fully understood how prediction error from different precision levels is minimised in the predictive process. The current research used magnetoencephalography (MEG) to examine whether prior precision modulates the cortical dynamics of the making of perceptual inferences. We presented participant…

Sensory inputPredictive codingmedicine.diagnostic_testMean squared prediction errorSpeech recognitionPerceptionmedia_common.quotation_subjectmedicineMagnetoencephalographyAuditory cortexMinimisation (clinical trials)Mathematicsmedia_common
researchProduct

Corrigendum: Both attention and prediction are necessary for adaptive neuronal tuning in sensory processing

2017

Sensory processingComputer sciencemedicine.medical_treatmentElectroencephalographyevent-related potentials050105 experimental psychologySensory neurosciencelcsh:RC321-57103 medical and health sciencesBehavioral Neuroscience0302 clinical medicineEvent-related potentialNeuronal tuningmedicine0501 psychology and cognitive sciencessensory processinglcsh:Neurosciences. Biological psychiatry. NeuropsychiatryBiological Psychiatrymedicine.diagnostic_test05 social sciencespredictionattentionPsychiatry and Mental healthNeuropsychology and Physiological PsychologyNeurologyNeuroscience030217 neurology & neurosurgeryelectroencephalographyNeuroscienceFrontiers in Human Neuroscience
researchProduct

Current bioinformatics tools in genomic biomedical research (Review).

2006

On the advent of a completely assembled human genome, modern biology and molecular medicine stepped into an era of increasingly rich sequence database information and high-throughput genomic analysis. However, as sequence entries in the major genomic databases currently rise exponentially, the gap between available, deposited sequence data and analysis by means of conventional molecular biology is rapidly widening, making new approaches of high-throughput genomic analysis necessary. At present, the only effective way to keep abreast of the dramatic increase in sequence and related information is to apply biocomputational approaches. Thus, over recent years, the field of bioinformatics has r…

Sequence databaseGenome HumanGene predictionGene Expression ProfilingComputational BiologyGenomicsSequence alignmentGeneral MedicineGenomicsOncogenomicsBiologyBioinformaticsGenomePolymorphism Single NucleotideComputingMethodologies_PATTERNRECOGNITIONDatabases GeneticHuman Genome ProjectGeneticsHumansHuman genomePromoter Regions GeneticSequence AlignmentSoftwareSequence (medicine)International journal of molecular medicine
researchProduct

PROTEIN SECONDARY STRUCTURE PREDICTION: HOW TO IMPROVE ACCURACY BY INTEGRATION

2006

In this paper a technique to improve protein secondary structure prediction is proposed. The approach is based on the idea of combining the results of a set of prediction tools, choosing the most correct parts of each prediction. The correctness of the resulting prediction is measured referring to accuracy parameters used in several editions of CASP. Experimental evaluations validating the proposed approach are also reported.

Set (abstract data type)Bioinformatics Protein PredictionCorrectnessComputer sciencebusiness.industryArtificial intelligenceData miningMachine learningcomputer.software_genreProtein secondary structure predictionbusinessCASPcomputerApplied Artificial Intelligence
researchProduct

THERMAL TIME REQUIREMENT AND HARVEST TIME FORECAST FOR PEACH CULTIVARS WITH DIFFERENT FRUIT DEVELOPMENT PERIODS

2002

Non-linear models using growing degree hours (GDH), based on the choice of base, critical and optimum temperatures, have been successfully applied to calculate thermal time required for spring bud burst in deciduous fruit trees. The flexibility of the model can fit the wide range of temperatures that occur during the peach fruit development period (FDP), which takes place from early spring to late summer. In this experiment, fruit growth was studied in relation to thermal time accumulated from bloom to fruit harvest for peach and nectarine cultivars whose fruit development period range from 70 to 150 days. Thermal time was calculated in terms of degree days (DD) (base temperature 7 °C, and …

Settore AGR/03 - Arboricoltura Generale E Coltivazioni ArboreeDegree days Prediction Model Growing degree hoursHorticultureDeciduousPhenologyHarvest timeFruit developmentRipeningCultivarHorticultureBloomDegree (temperature)MathematicsActa Horticulturae
researchProduct

Esigenze bio-termiche e stima del periodo di sviluppo del frutto in cultivar di pesco a differente epoca di maturazione

2009

In this experiment carried out in Sicily (37.35N 12.58E), fruit growth was studied in relation to thermal time accumulated from bloom to fruit harvest for peach cultivars whose fruit development period ranges from 76 to 170 days. Thermal time was calculated in terms of GDH (base temperature 6.2-10 °C, optimum temperature 23.3-24.5 °C and critical temperature 33.7-39.4 °C) by the use of non-linear models. Climatic and phenological data (bloom and harvest dates) were considered for a minimum of four to a maximum of six years. Taking into account the whole FDP, the accuracy of the GDH model in predicting harvest time ranged from 0.6 day, in the early ripening peach cultivar Anita, to 6.4 days …

Settore AGR/03 - Arboricoltura Generale E Coltivazioni ArboreeFDP GDH growing degree hours model prediction
researchProduct