Search results for "e learning"
showing 10 items of 2703 documents
Ensemble deep clustering analysis for time window determination of event-related potentials
2023
Objective Cluster analysis of spatio-temporal event-related potential (ERP) data is a promising tool for exploring the measurement time window of ERPs. However, even after preprocessing, the remaining noise can result in uncertain cluster maps followed by unreliable time windows while clustering via conventional clustering methods. Methods We designed an ensemble deep clustering pipeline to determine a reliable time window for the ERP of interest from temporal concatenated grand average ERP data. The proposed pipeline includes semi-supervised deep clustering methods initialized by consensus clustering and unsupervised deep clustering methods with end-to-end architectures. Ensemble clusterin…
Unstable feature relevance in classification tasks
2011
Evolution of scientific conceptions and knowledge among gymnasium pupils
2014
International audience; Two major models investigate the relationship between conceptions and knowledge: the KVP model of Clement and the structural model of Balacheff. In order to prove the necessity to shift the conceptions as claimed by Giordan’s allosteric model, it is important to study the evolution and the relationship between conceptions and knowledge. This research deals with the following questions: what sort of relationship can be established between conceptions and knowledge? What factor can make these two parameters evolve? This study was carried out on 45 pupils (two classrooms). It intended to collect conceptions and knowledge before and after science learning training. Indiv…
Brain Responses to Letters and Speech Sounds and Their Correlations With Cognitive Skills Related to Reading in Children
2018
Letter-speech sound (LSS) integration is crucial for initial stages of reading acquisition. However, the relationship between cortical organization for supporting LSS integration, including unimodal and multimodal processes, and reading skills in early readers remains unclear. In the present study, we measured brain responses to Finnish letters and speech sounds from 29 typically developing Finnish children in a child-friendly audiovisual integration experiment using magnetoencephalography. Brain source activations in response to auditory, visual and audiovisual stimuli as well as audiovisual integration response were correlated with reading skills and cognitive skills predictive of reading…
Rozwój kompetencji społecznych studentów w dobie nauczania online
2021
Artykuł jest komunikatem z badań, których celem była próba odpowiedzi na pytanie, jak studenci oceniają rozwój swoich kompetencji społecznych w związku z nauką online, która stała się koniecznością z powodu pandemii COVID19. W badaniu wzięło udział 350 studentów z trzech uczelni wyższych miasta Opola. Posłużono się metodą sondażu diagnostycznego. W celu zgromadzenia materiału badawczego wykorzystano kwestionariusz ankiety własnego autorstwa, w wersji online. Badani odpowiadali na pytania w oparciu o pięciostopniową skalę. Analiza wyników wskazuje na to, że respondenci najwyżej ocenili umiejętność zarządzania sobą w czasie (M=3,71) oraz umiejętność wyrażania własnego zdania (M=3,66), natomi…
On Assessing Vulnerabilities of the 5G Networks to Adversarial Examples
2022
The use of artificial intelligence and machine learning is recognized as the key enabler for 5G mobile networks which would allow service providers to tackle the network complexity and ensure security, reliability and allocation of the necessary resources to their customers in a dynamic, robust and trustworthy way. Dependability of the future generation networks on accurate and timely performance of its artificial intelligence components means that disturbance in the functionality of these components may have negative impact on the entire network. As a result, there is an increasing concern about the vulnerability of intelligent machine learning driven frameworks to adversarial effects. In …
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…
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…
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…