Search results for " learning."
showing 10 items of 5179 documents
Accelerometry - Simple, but challenging
2017
Effect of a Service-Learning Program on the Active Lifestyle of Children with Autism Spectrum Disorder: A Pilot Study
2020
Background: active lifestyles and Physical Activity (PA) are closely related to health. Healthy habits such as being physically active should be consolidated during childhood. Children with Autism Spectrum Disorders (ASD) present fewer opportunities to be involved in PA. For this reason, we conducted a Service-Learning (SL) program to enhance the possibility of participating ASD children enjoying PA sessions. The aim of this study was to analyze and describe the evolution in terms of the frequency and intensity of PA performed by ASD children who participated in the SL program. Methods: we used a quasi-experimental design. The sample was formed by 26 children with ASD (Experimental group: n…
Analisi di test di Immunofluorescenze indiretta per il supporto alla diagnosi di Malattie Autoimmuni basata su Deep Learning.
2019
La diagnosi delle malattie autoimmuni rappresenta un problema molto importante in medicina. Il test più utilizzato a questo scopo è il test anticorpo antinucleo, un test indiretto di immunofluorescenza. Il metodo proposto affronta tale problema sfruttando le metodologie del Machine Learning. In particolare, fa uso di reti neurali pre-addestrate in grado di classificare i pattern auto anticorpali collegati alle patologie autoimmuni. Gli strati delle reti pre-addestrate e vari parametri di sistema sono stati valutati al fine di ottimizzare il processo. Le prestazioni del sistema sono state valutate in termini di accuratezza in un processo di cross validation, mostrando efficienza e robustezza.
Discriminating and simulating actions with the associative self-organising map
2015
We propose a system able to represent others’ actions as well as to internally simulate their likely continuation from a partial observation. The approach presented here is the first step towards a more ambitious goal of endowing an artificial agent with the ability to recognise and predict others’ intentions. Our approach is based on the associative self-organising map, a variant of the self-organising map capable of learning to associate its activity with different inputs over time, where inputs are processed observations of others’ actions. We have evaluated our system in two different experimental scenarios obtaining promising results: the system demonstrated an ability to learn discrim…
Magic beans : a material package for teaching English through storytelling and creative drama in primary school
2013
Tarinat ovat universaali tapa jäsentää maailmaa ja kokemuksia. Tarinat ovat yksi vanhimmista opetusmenetelmistä, joka on koonnut ihmisiä yhteen viihtymään sekä oppimaan uutta. Vaikka tarinat ovat myös olennainen osa kielten opetuksen oppimateriaaleja, niitä hyödynnetään harvoin monipuolisesti kielitaidon kaikilla osa-alueilla puhumisen, kirjoittamisen, kuuntelun sekä lukemisen opetuksessa. Perinteisissä oppikirjoissa tarinoita seuraa tehtäviä, jotka testaavat ymmärrystä sekä opittua ainesta kirjallisesti. Tämän tutkielman pyrkimyksenä on työstää tarinoita uudesta näkökulmasta, luovan draaman keinoin. Tämä tutkielma on oppimateriaalipaketti, jonka kaksi kulmakiveä ovat modernin englanninkiel…
Inlärning och behärskning av svenskans verb- och adjektivböjning samt negationens placering hos finska grundskoleelever
2015
L'adozione nel contesto e co-testo scuola. Literature review su adozione-scuola con Atlas.ti
Our research wants to be a meta-analysis work; its purpose is to focus on adoption and to analyse the “textual-semantic correlates” through which this topic has been understood and interpreted by international literature. In particular, the aim is to describe and codify the semantic-linguistic treatment of “adoption of children” theme with reference to school adjustment issue. In the title of the following thesis, “Adoption in the school context and co-text”, the term co-text (stemming from linguistics) points out the inquiry function in texts and the purpose of meta-reflective comparison among texts of articles coming from the journals with a high impact factor. After selecting those journ…
CONTEMPORARY THEORIES OF ADULT LEARNING
2015
<p>Due to the adult learning theory transition from cognitive to comprehensive aspects, this article analyses contemporary theoretical notions about adult’s learning. In order to characterise the modern view on adult, the most recent insights into the education of whole adult person (P. Jarvis), three dimensions of learning (K.Illeris) and the critical theory contribution (S.D. Brookfield) will be discussed. All of mentioned, globally-renowned theorists are of the same opinion and contribute to the general adult learning theory – P. Jarvis pictures the learning process from a viewpoint of a human as holistic organism, K.Illeris develops his theory in relation to the pedagogical condit…
Sustainable agriculture: Recognizing the potential of conflict as a positive driver for transformative change
2020
International audience; Transformative changes in agriculture at multiple scales are needed to ensure sustainability, i.e. achieving food security while fostering social justice and environmental integrity. These transformations go beyond technological fixes and require fundamental changes in cognitive, relational, structural and functional aspects of agricultural systems. However, research on agricultural transformations fails to engage deeply with underlying social aspects such as differing perceptions of sustainability, uncertainties and ambiguities, politics of knowledge, power imbalances and deficits in democracy. In this paper, we suggest that conflict is one manifestation of such und…
A Deep Learning Model for Automatic Sleep Scoring using Multimodality Time Series
2021
Sleep scoring is a fundamental but time-consuming process in any sleep laboratory. Automatic sleep scoring is crucial and urgent to help address the increasing unmet need for sleep research. Therefore, this paper aims to develop an end-to-end deep learning architecture using raw polysomnographic recordings to automate sleep scoring. The proposed model adopts two-dimensional convolutional neural networks (2D-CNN) to automatically learn features from multi-modality signals, together with a "squeeze and excitation" block for recalibrating channel-wise feature responses. The learnt representations are finally fed to a softmax classifier to generate predictions for each sleep stage. The model pe…