Search results for "Scientific enterprise"

showing 3 items of 3 documents

Fuzziness, Cognition and Cybernetics: a historical perspective

2015

In the present paper, we connect some old reflections about the relationships existing between the theory of fuzzy sets and cybernetics with modern, contemporary analyses of the crucial (better: unavoidable) role that fuzziness plays in the attempts at scientifically describing aspects of information sciences. The connection, which has a basic conceptual origin, has been triggered also by the recent 50th anniversary of Norbert Wiener’s death which has been instrumental in looking again at some crucial aspects of the birth of information sciences in the midst of the last century. Fuzzy sets are an essential part of this revolution and share all the innovations as well as the difficulties of …

Scientific enterprisemedicine.medical_specialtySettore INF/01 - InformaticaComputer sciencebusiness.industryPerspective (graphical)Fuzzy setCognitionSettore M-FIL/02 - Logica E Filosofia Della Scienzacybernetics fuzzy set fuzzinessMedical cyberneticsInformation scienceEpistemologymedicineCyberneticsArtificial intelligencebusinessProceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
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Inferring causation from time series in earth system sciences

2019

The heart of the scientific enterprise is a rational effort to understand the causes behind the phenomena we observe. In large-scale complex dynamical systems such as the Earth system, real experiments are rarely feasible. However, a rapidly increasing amount of observational and simulated data opens up the use of novel data-driven causal methods beyond the commonly adopted correlation techniques. Here, we give an overview of causal inference frameworks and identify promising generic application cases common in Earth system sciences and beyond. We discuss challenges and initiate the benchmark platform causeme.net to close the gap between method users and developers.

0301 basic medicineEarth scienceAquatic Ecology and Water Quality ManagementDynamical systems theoryComputer science530 PhysicsDatenmanagement und AnalyseSciencereviewGeneral Physics and Astronomyheart02 engineering and technologyGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciencesDatabasesLife ScienceCausationStatistical physics thermodynamics and nonlinear dynamicsintermethod comparisonlcsh:Scienceresearch workScientific enterpriseMultidisciplinaryWIMEKSeries (mathematics)QComputational sciencefeasibility study500General ChemistryAquatische Ecologie en Waterkwaliteitsbeheersimulation021001 nanoscience & nanotechnologyData sciencecausal inference climateEarth system scienceEnvironmental sciences030104 developmental biologytime series analysisCausal inferencePerspectiveBenchmark (computing)Observational studylcsh:Qconceptual frameworkdata management0210 nano-technologyClimate sciences
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On the obvious positive interspecific relationship between abundance and distribution: a reply to Blackburn and Gaston

2009

Thomas Kuhn described normal science as ‘ … research firmly based upon one or more past scientific achievements … ’, that ‘ … does not aim at novelties of fact or theory and, when successful, finds none’ ([Kuhn 1996][1]). Kuhn divides scientific enterprise into three faces: normal

Scientific enterpriseCommunity EcologyAbundance (ecology)business.industryDistribution (economics)Normal scienceInterspecific competitionBiologyGeneral Agricultural and Biological SciencesbusinessAgricultural and Biological Sciences (miscellaneous)Genealogy
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