Search results for "Support"
showing 10 items of 2310 documents
The Role of a Supportive Interpersonal Environment and Education-Related Goal Motivation During the Transition Beyond Upper Secondary Education
2018
This longitudinal study investigated the role of parents and peers as well as of education-related goal motivation during educational transitioning in late adolescence. The sample consisted of 1520 upper secondary education students attending either academic or vocational upper secondary school in Finland. They were surveyed three times: (1) in the first year of their upper secondary education, (2) in the second year of their upper secondary education, and (3) two years later. The results show, first, that when students in upper secondary education pursued their educational goals out of autonomous motivation they also invested more effort in their goals, which was reflected in high levels o…
Students' experiences in different forms of support during doctoral studies
2011
Doctoral student experience has been seen to have impact on study satisfaction and further the successful degree completion. Earlier research suggests that students need different forms of support during their studies. Therefore, this study investigates how different forms of support effect on doctoral students' experience in progress, particularly in experienced progress in research. The study was conducted in one Department of Industrial Engineering and Management in Finland. The quantitative data (N=64) was collected for the study. The results indicate that only network and peer support has a positive effect on students' experienced progress in research.
A genetic integrated fuzzy classifier
2005
This paper introduces a new classifier, that is based on fuzzy-integration schemes controlled by a genetic optimisation procedure. Two different types of integration are proposed here, and are validated by experiments on real data sets of biological cells. The performance of our classifier is tested against a feed-forward neural network and a Support Vector Machine. Results show the good performance and robustness of the integrated classifier strategies.
Towards a Reduction of Greenhouse Gases: a New Decision Support System for Design, Management and Operation of Wastewater Treatment Plants
2015
The increasing attention for the environment has led to reduce the emissions from wastewater treatment plants (WWTPs). Moreover, the increasing interest towards the greenhouse gas (GHG) emissions from WWTPs suggests to reconsider the traditional tools used for designing and managing WWTPs. Indeed, nitrous oxide (N2O), carbon dioxide (CO2) and methane (CH4) can be emitted from wastewater treatment significantly contributing to the greenhouse gas (GHG) footprint. The reduction of energy consumption as well as GHG emission are of particular concern for large WWTPs which treat the majority of wastewater in terms of both volume and pollution load. Nowadays, there is an increasing need to develop…
Game Mechanics in the Design of a Collaborative 3D Serious Game
2014
Background. This article investigates the potential of utilizing game mechanics in designing 3-D serious games for Computer-Supported Collaborative Learning (CSCL) and attempt to produce new information about designing collaborative serious games. Aim. This article has two aims: first, to clarify how theoretical knowledge of collaborative learning was related to game design in previous studies; and, second, to design a collaborative serious game based on theoretical knowledge of collaborative learning and game design. Results. The reviewed studies revealed the potential of using collaborative games in education. However, they showed that collaborative learning games were typically designed …
No-Reference 3D Mesh Quality Assessment Based on Dihedral Angles Model and Support Vector Regression
2016
International audience; 3D meshes are subject to various visual distortions during their transmission and geometrical processing. Several works have tried to evaluate the visual quality using either full reference or reduced reference approaches. However, these approaches require the presence of the reference mesh which is not available in such practical situations. In this paper, the main contribution lies in the design of a computational method to automatically predict the perceived mesh quality without reference and without knowing beforehand the distortion type. Following the no-reference (NR) quality assessment principle, the proposed method focuses only on the distorted mesh. Specific…
A Decision Support System for Reverse Engineering Gene Regulatory Networks
2009
In this paper we present a knowledge-based system that aims at helping scientists in the reverse engineering process of gene regulatory networks. The main motivation of the proposed approach is to support scientists in the choice of the wide variety of algorithms and methods currently applied in the literature to infer Gene Regulatory Networks starting from gene expression measured using microarray technology. The Decision Support System (DSS) architecture is based on an ontology to model the knowledge base, a logical reasoner that builds the workflow of tasks to be done starting from the user’s request and a set of rules, and, finally, an agenda that runs the algorithms and software schedu…
Talent identification in soccer using a one-class support vector machine
2019
Abstract Identifying potential future elite athletes is important in many sporting events. The successful identification of potential future elite athletes at an early age would help to provide high-quality coaching and training environments in which to optimize their development. However, a large variety of different skills and qualities are needed to succeed in elite sports, making talent identification generally a complex and multifaceted problem. Due to the rarity of elite athletes, datasets are inherently imbalanced, making classical statistical inference difficult. Therefore, we approach talent identification as an anomaly detection problem. We trained a nonlinear one-class support ve…
A Machine Learning Approach for Fall Detection and Daily Living Activity Recognition
2019
The number of older people in western countries is constantly increasing. Most of them prefer to live independently and are susceptible to fall incidents. Falls often lead to serious or even fatal injuries which are the leading cause of death for elderlies. To address this problem, it is essential to develop robust fall detection systems. In this context, we develop a machine learning framework for fall detection and daily living activity recognition. We use acceleration and angular velocity data from two public databases to recognize seven different activities, including falls and activities of daily living. From the acceleration and angular velocity data, we extract time- and frequency-do…
A Machine Learning Approach for Fall Detection Based on the Instantaneous Doppler Frequency
2019
Modern societies are facing an ageing problem that is accompanied by increasing healthcare costs. A major share of this ever-increasing cost is due to fall-related injuries, which urges the development of fall detection systems. In this context, this paper paves the way for the development of radio-frequency-based fall detection systems, which do not require the user to wear any device and can detect falls without compromising the user's privacy. For the design of such systems, we present an activity simulator that generates the complex path gain of indoor channels in the presence of one person performing three different activities: slow fall, fast fall, and walking. We have developed a mac…