Search results for "laskennallinen tiede"

showing 10 items of 20 documents

How much is enough? : The convergence of finite sample scattering properties to those of infinite media

2021

We study the scattering properties of a cloud of particles. The particles are spherical, close to the incident wavelength in size, have a high albedo, and are randomly packed to 20% volume density. We show, using both numerically exact methods for solving the Maxwell equations and radiative-transfer-approximation methods, that the scattering properties of the cloud converge after about ten million particles in the system. After that, the backward-scattered properties of the system should estimate the properties of a macroscopic, practically infinite system. (C) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.o…

010504 meteorology & atmospheric scienceseducationparticulate random mediapienhiukkasetoptiset ominaisuudet01 natural sciences114 Physical sciencesVolume densityScatteringsymbols.namesakelaskennallinen tiedeConvergence (routing)Radiative transferRadiative transferMaxwellin yhtälötsirontaSpectroscopy0105 earth and related environmental sciencesPhysicsRadiationScatteringscatteringAlbedoSample (graphics)Atomic and Molecular Physics and OpticsComputational physicsWavelengthMaxwell's equationsMaxwell equationsradiative transferParticulate random mediasymbolsapproksimointi
researchProduct

Prospects and challenges for computer simulations of monolayer-protected metal clusters

2021

Precise knowledge of chemical composition and atomic structure of functional nanosized systems, such as metal clusters stabilized by an organic molecular layer, allows for detailed computational work to investigate structure-property relations. Here, we discuss selected recent examples of computational work that has advanced understanding of how these clusters work in catalysis, how they interact with biological systems, and how they can make self-assembled, macroscopic materials. A growing challenge is to develop effective new simulation methods that take into account the cluster-environment interactions. These new hybrid methods are likely to contain components from electronic structure t…

0301 basic medicineWork (thermodynamics)Computational chemistryComputer scienceScienceGeneral Physics and AstronomyNanotechnology02 engineering and technologyElectronic structureGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciencesklusteritMonolayerlaskennallinen tiedesimulointiLayer (object-oriented design)MultidisciplinaryQCommentGeneral Chemistry021001 nanoscience & nanotechnology030104 developmental biologyNanoparticlesnanohiukkaset0210 nano-technologySimulation methodsMetal clustersNature Communications
researchProduct

Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences

2022

With more than 50 years of literature, fuzzy logic has gradually progressed from an emerging field to a developed research domain, incorporating the sub-domain of mathematical fuzzy logic (MFL) [...]

Algebra and Number TheorymatematiikkaLogicsyväoppiminentietojenkäsittelytieteetpääkirjoituksettekoälylaskennallinen tiederahoitusalateknologiaGeometry and Topologysoveltaminenongelmanratkaisusumea logiikkaMathematical PhysicsAnalysis
researchProduct

Systematisation of Systems Solving Physics Boundary Value Problems

2020

A general conservation law that defines a class of physical field theories is constructed. First, the notion of a general field is introduced as a formal sum of differential forms on a Minkowski manifold. By the action principle the conservation law is defined for such a general field. By construction, particular field notions of physics, e.g., magnetic flux, electric field strength, stress, strain etc. become instances of the general field. Hence, the differential equations that constitute physical field theories become also instances of the general conservation law. The general field and the general conservation law together correspond to a large class of relativistic hyperbolic physical …

Class (set theory)Conservation lawField (physics)numeeriset menetelmätDifferential equationDifferential formAction (physics)AlgebraMinkowski spacelaskennallinen tiedeBoundary value problemfysiikkadifferentiaaliyhtälötnumerical mathematics
researchProduct

Array programming with NumPy.

2020

Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programmi…

FOS: Computer and information sciences/639/705/1042Computer science/639/705/794Interoperability/639/705/117Review ArticleStatistics - Computationohjelmointikielet01 natural sciences03 medical and health sciencesSoftwareSoftware Designlaskennallinen tiede0103 physical sciencesFOS: Mathematics010303 astronomy & astrophysicsComputation (stat.CO)030304 developmental biologycomputer.programming_languageSolar physics0303 health sciencesMultidisciplinaryApplication programming interfacebusiness.industryNumPyComputational sciencereview-articleComputational BiologyPython (programming language)Computer science/704/525/870Computational neuroscienceProgramming paradigmSoftware designComputer Science - Mathematical Software/631/378/116/139Programming LanguagesArray programmingohjelmistokirjastotSoftware engineeringbusinessMathematical Software (cs.MS)computerMathematicsSoftwarePythonNature
researchProduct

Interactivized : Visual Interaction for Better Decisions with Interactive Multiobjective Optimization

2022

In today’s data-driven world, decision makers are facing many conflicting objectives. Since there is usually no solution that optimizes all objectives simultaneously, the aim is to identify a solution with acceptable trade-offs. Interactive multiobjective optimization methods are iterative processes in which a human decision maker repeatedly provides one’s preferences to request computing new solutions and compares them. With these methods, the decision maker can learn about the problem and its limitations. However, advanced optimization software usually offer simple visualization tools that can be significantly improved. On the other hand, current approaches for multiobjective optimization…

General Computer SciencevisuaalisuuspäätöksentekoGeneral Engineeringmultiple criteria decision makinginteractive optimizationpäätöksentukijärjestelmätanalyysimenetelmätvisual analyticsmonitavoiteoptimointioptimointilaskennallinen tiedeinteraktiivisuusGeneral Materials Science
researchProduct

Laskennalliset tieteet Suomen yliopistoissa vuonna 2021

2021

Suomilaskennallinen tiedetutkimusopetusyliopistot
researchProduct

A review of second‐order blind identification methods

2022

Second order source separation (SOS) is a data analysis tool which can be used for revealing hidden structures in multivariate time series data or as a tool for dimension reduction. Such methods are nowadays increasingly important as more and more high-dimensional multivariate time series data are measured in numerous fields of applied science. Dimension reduction is crucial, as modelling such high-dimensional data with multivariate time series models is often impractical as the number of parameters describing dependencies between the component time series is usually too high. SOS methods have their roots in the signal processing literature, where they were first used to separate source sig…

aikasarjatmonimuuttujamenetelmätsignaalinkäsittelytilastomenetelmätlaskennallinen tiedeaikasarja-analyysi
researchProduct

SciPy 1.0 : fundamental algorithms for scientific computing in Python

2020

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments. peerReviewed

avoin lähdekoodialgoritmitlaskennallinen tiedeSciPyPython
researchProduct

Laskennallisten tieteiden tutkimuksen ja koulutuksen kehittäminen

2016

big datalaskennallinen tiedetutkimuspolitiikkakorkeakouluopetus
researchProduct