Search results for "koneoppiminen"

High-dimensional Big Data processing with dictionary learning and diffusion maps

2015

Algorithms for modern Big Data analysis deal with both massive amount of sam- ples and a large number of features (high-dimension). One way to cope with these challenges is to assume and discover the existence of localization in the data by uncovering its intrinsic geometry. This approach suggests that different data segments can be analyzed separately and then unified in order to gain an understanding of the whole phenomenon. Methods that utilize efficiently local- ized data are attractive for high-dimensional big data analysis, because they can be parallelized, and thus the computational resources, which are needed for their utilization, are realistic and affordable. These methods can explo…

On Combining Explainable Artificial Intelligence and Interactive Multiobjective Optimization in Data-Driven Decision Support

2019

Agile Deep Learning UAVs Operating in Smart Spaces : Collective Intelligence Versus “Mission-Impossible”

2018

The environments, in which we all live, are known to be complex and unpredictable. The complete discovery of these environments aiming to take full control over them is a “mission-impossible”, however, still in our common agenda. People intend to make their living spaces smarter utilizing innovations from the Internet of Things and Artificial Intelligence. Unmanned aerial vehicles (UAVs) as very dynamic, autonomous and intelligent things capable to discover and control large areas are becoming important “inhabitants” within existing and future smart cities. Our concern in this paper is to challenge the potential of UAVs in situations, which are evolving fast in a way unseen before, e.g., em…

Kognitiivisen tietojenkäsittelyn teknologia terveydenhuollon tietovarantojen hyödyntämisessä

2018

Tutkielmassa tarkastellaan kognitiivisen tietojenkäsittelyn teknologiaa ja kuinka sen käyttöönotto terveydenhuollon eri osa-alueilla vaikuttaa palveluihin ja prosesseihin. Kognitiivisen teknologian merkitystä terveydenhuollossa kartoitetaan sote-uudistuksessa asetettujen tavoitteiden kautta ja siihen yhdistetään ennakoivan terveydenhuollon näkökulma. Tutkielmassa käsitellään terveydenhuoltoon kohdistuvia muutoksia digitalisaation kautta. Kognitiivinen tietojenkäsittely pyritään selittämään teoriatasolla ja sen tueksi haetaan esimerkkejä terveydenhuollossa jo käytössä olevista tai suunnitelluista prosesseista sekä IBM Watson yhteistyön tarjoamista tutkimussuunnitelmista. Tutkielmalla pyritää…

Kernels and Graphs on M25 + H

2023

Codes related to article "Graphs and Kernelized Learning Applied to Interactions of Hydrogen with Doped Gold Nanoparticle Electrocatalysts". There are two main types of codes: codes to transform a catalytic system of protected gold nanoparticle and a single hydrogen atom into a graph-based representation, and codes to run kernel-based machine learning methods to predict interaction energies between the nanoparticle and the hydrogen atom. This is a snapshot of the code dataset that has been taken on 06.06.2023. A more detailed description of the data and the address to the GitLab repository for the latest version of the code can be found from the parent dataset of this data publication.

Kernels and Graphs on M25 + H (parent repository)

2023

The repository contains codes related to article "Graphs and Kernelized Learning Applied to Interactions of Hydrogen with Doped Gold Nanoparticle Electrocatalysts". There are two main types of codes: codes to transform a catalytic system of protected gold nanoparticle and a single hydrogen atom into a graph-based representation, and codes to run kernel-based machine learning methods to predict interaction energies between the nanoparticle and the hydrogen atom. This is the metadata for the parent repository of the codes. Updates and possible corrections are documented in the GitLab project, where the material saved and shared. The GitLab project can be found and downloaded from the followin…

Koneoppivat järjestelmät osana organisaation strategista kehittämistä

2017

Tekoälyjärjestelmiä on tutkittu jo useiden vuosikymmenien ajan, mutta vasta lähivuosina niitä on menestyksekkäästi onnistuttu ottamaan käyttöön eri toimialoilla. Tekoäly käsitteenä on laaja ja sen rajaaminen on verrattain haastavaa. Koneoppiminen on yksi tekoälyn alakategorioista. Koneoppivalla järjestelmällä tarkoitetaan itsenäisesti toimivaa ja oppivaa tekoälyjärjestelmää. Koneoppimisen hyödyistä ja uhista on paljon keskustelua, mutta varsinaisia tutkimustuloksia liiketoiminnallisista hyödyistä ei juuri ole. Tutkielmani tarkastelee koneoppimista osana organisaation kehitysstrategiaa ja erilaisia kehitysmahdollisuuksia, joita koneoppivat järjestelmät voivat tarjota. Tarkoituksena on selvit…

CM3 – TRANSPORT 2023 : New Greener and Digital Modern Transport – its Challenges in Design Methods, Tools and Technologies : Book of Abstracts and Pr…

2023

The CM3 – Transport Conference 2023 is organized by the University of Jyväskylä, supported by Jamk – University of Applied Sciences, in Jyväskylä/ Finland. The event represents an ECCOMAS Thematic Conference in the context of the activities proposed by the Industrial Interest Group (IIG) of ECCOMAS. Green and efficient European transport represents an important factor of economic growth to be considered in view of environmental and societal challenges. It is essential to develop the scientific and technological mechanisms to encourage cooperation and competitiveness between transport systems in Europe and in the World. It is also crucial to answer the questions how to conduct and apply rese…

Supplementary data for the article "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relev…

2022

The data set contains the supplementary data of the article "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions" published in J. Phys. Chem. Lett., https://doi.org/10.1021/acs.jpclett.2c02612. The data includes: - A machine learning (EMLM) model for predicting chemical potentials of individual conformers of multifunctional organic compounds calculated by the COSMOtherm program - COSMO-files used for training and testing the EMLM model - Descriptors and chemical potentials used for the training and testing the model Artikkelin "Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds i…

Assessment of microalgae species, biomass and distribution from spectral images using a convolution neural network

2021

Artikkeliin "Assessment of microalgae species, biomass and distribution from spectral images using a convolution neural network" liittyvä aineisto koostuu seuraavista osista: 1.Transmittanssi-hyperspektrikuvat levänäytteistä kuvattuina 24-kuoppalevyllä 2.Biomassamääritykset elektronisella solulaskurilla 3.Opetus- ja validointiaineisto konvoluutioneuroverkolle 4.Testiaineisto konvoluutioneuroverkolle 5.Opetus-, validointi- ja testiaineiston käsittelyyn käytetty Python koodi 6.Seitsemään eri malliin käytetty Python koodi ja mallit itsessään The data and code related to the article "Assessment of microalgae species, biomass and distribution from spectral images using a convolution neural netwo…