Search results for "e learning"
showing 10 items of 2703 documents
Meeting the Challenges of Generational Change in the Teaching Profession : Towards a European Model for Intergenerational Teacher Collaboration
2013
In a European-wide effort to improve the professional development of teachers, the 2AgePro project was conducted from November 2008 to October 2010. One of its goals was to develop and test different forms of intergenerational teacher collaboration among junior and senior teachers in primary and secondary schools. Another aim was to utilise the results from these pilots, which were conducted in the Czech Republic, Finland, Germany, the Netherlands, and Sweden, to create a model for intergenerational collaboration that could be used in any national or cultural setting. This article reports on the national pilots and proposes a European model for intergenerational collaboration for teachers. …
Social transmission in the wild can reduce predation pressure on novel prey signals
2021
Funder: Suomen Kulttuurirahasto (Finnish Cultural Foundation); doi: https://doi.org/10.13039/501100003125
Machine learning at the interface of structural health monitoring and non-destructive evaluation
2020
While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities and consider ultrasonic/guided-wave inspection as a technology at the interface of the two methodologies. It will discuss how data-based/machine learning analysis provides a powerful approach to ultrasonic NDE/SHM in terms of the available algorithms, and more generally, how different techniques can accommodate the very substantial quantities of data that are provided by modern monitoring campaigns. Several machine learning methods will be illu…
Teachers as frontline agents of integration: Finnish physical education students’ reflections on intercultural encounters
2018
Background and purpose: This article focuses on how future Physical Education and Dance teachers may be better prepared to work in increasingly diverse education environments. It also discusses how tertiary institutions might address issues of social inclusion and cultural pluralism within their programmes, courses and assignments. The authors critically reflect on an experiential learning intervention in Jyväskylä, Finland, in which trainee PE teachers facilitated kinaesthetic language-learning workshops for asylum seekers. The applied use of physical education and dance in this context was aimed at providing a distinct opportunity to consider a PE teacher’s professional competence and rol…
Use of the KSVM-based system for the definition, validation and identification of the incisional hernia recurrence risk factors
2019
BACKGROUND: Incisional hernia is one of the most common complications after abdominal surgery with an incidence rate of 11 to 20% post laparotomy. Many different factors can be considered as risk factors of incisional hernia recurrence. The aim of this study is to confirm and to validate the incisional hernia recurrence risk factors and to identify and to validate new ones. METHODS: In the period from July 2007 to July 2017, 154 patients were selected and subjected to incisional hernia repair. The surgical operations were conducted under general anaesthesia. Patients received antibiotic prophylaxis when indicated, according to the hospital prophylaxis scheme. Inclusion criteria of the study…
Modeling crowd dynamics through coarse-grained data analysis
2018
International audience; Understanding and predicting the collective behaviour of crowds is essential to improve the efficiency of pedestrian flows in urban areas and minimize the risks of accidents at mass events. We advocate for the development of crowd traffic management systems, whereby observations of crowds can be coupled to fast and reliable models to produce rapid predictions of the crowd movement and eventually help crowd managers choose between tailored optimization strategies. Here, we propose a Bi-directional Macroscopic (BM) model as the core of such a system. Its key input is the fundamental diagram for bi-directional flows, i.e. the relation between the pedestrian fluxes and d…
IMI – Oral biopharmaceutics tools project – Evaluation of bottom-up PBPK prediction success part 4: Prediction accuracy and software comparisons with…
2020
Oral drug absorption is a complex process depending on many factors, including the physicochemical properties of the drug, formulation characteristics and their interplay with gastrointestinal physiology and biology. Physiological-based pharmacokinetic (PBPK) models integrate all available information on gastro-intestinal system with drug and formulation data to predict oral drug absorption. The latter together with in vitro-in vivo extrapolation and other preclinical data on drug disposition can be used to predict plasma concentration-time profiles in silico. Despite recent successes of PBPK in many areas of drug development, an improvement in their utility for evaluating oral absorption i…
Network reconstruction for trans acting genetic loci using multi-omics data and prior information.
2022
Background: Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors…
Context-related data processing in artificial neural networks for higher reliability of telerehabilitation systems
2015
Classification is a data processing technique of a great significance both for native eHealth systems and web telemedicine solutions. In this sense, artificial neural networks have been widely applied in telerehabilitation as powerful tools to process information and acquire a new medical knowledge. But effective analysis of multidimensional heterogeneous medical data, still poses considerable difficulties. It was shown that processing too many data features simultaneously is costly and has some adverse effects on the resulting models classification properties. Therefore, there is a strong need to develop new techniques for selecting features from the very large data sets that include many …
Machine learning in remote sensing data processing
2009
Remote sensing data processing deals with real-life applications with great societal values. For instance urban monitoring, fire detection or flood prediction from remotely sensed multispectral or radar images have a great impact on economical and environmental issues. To treat efficiently the acquired data and provide accurate products, remote sensing has evolved into a multidisciplinary field, where machine learning and signal processing algorithms play an important role nowadays. This paper serves as a survey of methods and applications, and reviews the latest methodological advances in machine learning for remote sensing data analysis.