Search results for "component"
showing 10 items of 1682 documents
Self-Regulation in High-Level Ice Hockey Players: An Application of the MuSt Theory
2021
The purpose of the study was to examine the validity of core action elements and feeling states in ice hockey players in the prediction of performance. A second aim of the study was to explore the effectiveness of a 30-day program targeting action and emotion regulation. Participants were male ice hockey players drawn from two teams competing at the highest level of the junior Finnish ice hockey league. They were assigned to a self-regulation (n = 24) and a control (n = 19) group. The self-regulation program focused on the recreation of optimal execution of core action elements and functional feeling states. Separate repeated measures MANOVAs indicated significant differences in ratings of …
A new approach for estimating a nonlinear growth component in multilevel modeling
2011
This study presents a new approach to estimation of a nonlinear growth curve component with fixed and random effects in multilevel modeling. This approach can be used to estimate change in longitudinal data, such as day-of-the-week fluctuation. The motivation of the new approach is to avoid spurious estimates in a random coefficient regression model due to the synchronized periodical effect (e.g., day-of-the-week fluctuation) appearing both in independent and dependent variables. First, the new approach is introduced. Second, a Monte Carlo simulation study is carried out to examine the functioning of the proposed new approach in the case of small sample sizes. Third, the use of the approac…
Exact extension of the DIRECT algorithm to multiple objectives
2019
The direct algorithm has been recognized as an efficient global optimization method which has few requirements of regularity and has proven to be globally convergent in general cases. direct has been an inspiration or has been used as a component for many multiobjective optimization algorithms. We propose an exact and as genuine as possible extension of the direct method for multiple objectives, providing a proof of global convergence (i.e., a guarantee that in an infinite time the algorithm becomes everywhere dense). We test the efficiency of the algorithm on a nonlinear and nonconvex vector function. peerReviewed
Combining PCA and multiset CCA for dimension reduction when group ICA is applied to decompose naturalistic fMRI data
2015
An extension of group independent component analysis (GICA) is introduced, where multi-set canonical correlation analysis (MCCA) is combined with principal component analysis (PCA) for three-stage dimension reduction. The method is applied on naturalistic functional MRI (fMRI) images acquired during task-free continuous music listening experiment, and the results are compared with the outcome of the conventional GICA. The extended GICA resulted slightly faster ICA convergence and, more interestingly, extracted more stimulus-related components than its conventional counterpart. Therefore, we think the extension is beneficial enhancement for GICA, especially when applied to challenging fMRI d…
Domain Specific Case Tool for ICT-Enabled Service Design
2014
One major problem in service design is the limited availability of information gathered during the development process. In particular, information on end-user requirements is difficult for designers, developers, and maintainers to access. Here, we provide a mechanism that supports the gathering and modeling of various types of information throughout the service and software development life cycle. As various existing tools focus on a particular part of the life cycle, essential information is not available, or it is more difficult to obtain in later stages. The linkage between information collected in the different stages is often lost. The implemented tool support enables the modeling of r…
Can back-projection fully resolve polarity indeterminacy of independent component analysis in study of event-related potential?
2011
a b s t r a c t In the study of event-related potentials (ERPs) using independent component analysis (ICA), it is a traditional way to project the extracted ERP component back to electrodes for correcting its scaling (magnitude and polarity) indeterminacy. However, ICA tends to be locally optimized in practice, and then, the back-projection of a component estimated by the ICA can possibly not fully correct its polarity at every electrode. We demonstrate this phenomenon from the view of the theoretical analysis and numerical simulations and suggest checking and modifying the abnormal polarity of the projected component in the electrode field before further analysis. Moreover, when several co…
Online anomaly detection using dimensionality reduction techniques for HTTP log analysis
2015
Modern web services face an increasing number of new threats. Logs are collected from almost all web servers, and for this reason analyzing them is beneficial when trying to prevent intrusions. Intrusive behavior often differs from the normal web traffic. This paper proposes a framework to find abnormal behavior from these logs. We compare random projection, principal component analysis and diffusion map for anomaly detection. In addition, the framework has online capabilities. The first two methods have intuitive extensions while diffusion map uses the Nyström extension. This fast out-of-sample extension enables real-time analysis of web server traffic. The framework is demonstrated using …
Determining the number of sources in high-density EEG recordings of event-related potentials by model order selection
2011
To high-density electroencephalography (EEG) recordings, determining the number of sources to separate the signal and the noise subspace is very important. A mostly used criterion is that percentage of variance of raw data explained by the selected principal components composing the signal space should be over 90%. Recently, a model order selection method named as GAP has been proposed. We investigated the two methods by performing independent component analysis (ICA) on the estimated signal subspace, assuming the number of selected principal components composing the signal subspace is equal to the number of sources of brain activities. Through examining wavelet-filtered EEG recordings (128…
Chemical composition of the essential oil of Elaeoselinum asclepium (L.) Bertol subsp. meoides (Desf.) Fiori (Umbelliferae) collected wild in Central…
2020
In the present study, the chemical composition of the essential oils from flowers and leaves of Elaeoselinum asclepium(L.) Bertol subsp. meoides(Desf.) Fiori collected in Central Sicily was evaluated by GC and GC-MS. The main volatile components of the flowers were alpha-phellandrene (42.5%), terpinolene (15.7%), p-cymene (11.6%) and beta-phellandrene (10.2%), whereas the ones of the leaves were p-cymene (44.0%), alpha-pinene (13.2%), alpha-phellandrene (11.0%), beta-phellandrene (10.2%) and beta-pinene (9.2%). Furthermore, the antibacterial and antifungal activities against some microorganisms infesting historical art craft were determined. The essential oil from leaves (EL) showed to be p…
Health literacy as a learning outcome in schools
2012
PurposeThe aim of this paper is to define health literacy as a learning outcome in schools, and to describe the learning conditions that are relevant for targeting health literacy.Design/methodology/approachThe paper draws on theoretical and empirical educational literature, and also the experiences of the authors.FindingsHealth literacy is defined as consisting of five core components: theoretical knowledge, practical knowledge, critical thinking, self‐awareness, and citizenship. The first three components are rather similar to the commonly‐accepted health literacy concept, but the definition given in this paper expands the concept via two additional – but essential – components. It is emp…