Search results for "Modelli"

On stochastic modelling and reliability of systems with moving cracked material

2015

In many industrial processes, such as printing paper, a material travels through a series of rollers unsupported and under longitudinal tension. The value of the tension has an important role in the system behaviour, such as fracture and me- chanical stability. This thesis develops stochastic models for a system in which an elastic, isotropic cracked material travels through a series of spans and studies the probabilities of fracture and instability of the material. The models focus on describing tension variations and initial cracks in the material. Time-dependent tension fluctuations are modelled by the stationary Ornstein-Uhlenbeck process, and the occurrence and lengths of the cracks are…

The stress-strain state and stabilization of viscoelastoplastic, imperfect moving web continuum

2014

On modelling and stability of axially moving viscoelastic materials

2013

gllvm : Fast analysis of multivariate abundance data with generalized linear latent variable models in R

2019

1.There has been rapid development in tools for multivariate analysis based on fully specified statistical models or “joint models”. One approach attracting a lot of attention is generalized linear latent variable models (GLLVMs). However, software for fitting these models is typically slow and not practical for large datsets. 2.The R package gllvm offers relatively fast methods to fit GLLVMs via maximum likelihood, along with tools for model checking, visualization and inference. 3.The main advantage of the package over other implementations is speed e.g. being two orders of magnitude faster, and capable of handling thousands of response variables. These advances come from using variationa…

EXPERIMENTAL SEISMIC ANALYSIS OF MONUMENTS FOR RISK MITIGATION

2008

An experimental investigation, at the moment in progress, for the evaluation of the seismic vulnerability of a monumental structure and the effects of some reinforcement devices are presented. Referring to this monumental structure, that is a church, the authors obtained the dynamically identified analytical model and recognized that the drum-dome system was one of the macro-elements with highest risk. This result was obtained by analyzing the linear behaviour. In order to study the nonlinear behaviour, tests on reduced scale models were necessary. The models, with and without risk mitigation reinforcements, were subjected to seismic input with rising intensity in order to know the effects …

Teachers' attitudes and self-efficacy on implementing inclusive education in Japan and Finland : A comparative study using multi-group structural equ…

2018

This study aims to explore relationships between teachers' attitudes, self-efficacy, and background variables regarding inclusive education by using a sample of 359 Japanese and 872 Finnish teachers. A multi-group structural equation modelling was conducted to find similarities and differences in how the background variables predict teachers' attitudes and self-efficacy. Experience in teaching students with disabilities had a positive effect on teachers' attitudes and self-efficacy in both countries. However, teachers' teaching career and the amount of inclusive education training affected them differently in Japan and Finland. The findings could be used to improve inclusive education train…

Data from: Transparency reduces predator detection in mimetic clearwing butterflies

2019

1. Predation is an important selective pressure and some prey have evolved conspicuous warning signals that advertise unpalatability (i.e. aposematism) as an antipredator defence. Conspicuous colour patterns have been shown effective as warning signals, by promoting predator learning and memory. Unexpectedly, some butterfly species from the unpalatable tribe Ithomiini possess transparent wings, a feature rare on land but common in water, known to reduce predator detection. 2. We tested if transparency of butterfly wings was associated with decreased detectability by predators, by comparing four butterfly species exhibiting different degrees of transparency, ranging from fully opaque to larg…

Data from: A mechanistic underpinning for sigmoid dose-dependent infection

2016

Theoretical models of environmentally transmitted diseases often assume that transmission is a constant process, which scales linearly with pathogen dose. Here we question the applicability of such an assumption and propose a sigmoidal form for the pathogens infectivity response. In our formulation, this response arises under two assumptions: 1) multiple invasion events are required for a successful pathogen infection and 2) the host invasion state is reversible. The first assumption reduces pathogen infection rates at low pathogen doses, while the second assumption, due to host immune function, leads to a saturating infection rate at high doses. The derived pathogen dose:infection rate -re…

Translating cross-lagged effects into incidence rates and risk ratios: The case of psychosocial safety climate and depression

2017

Longitudinal studies are the gold standard of empirical work and stress research whenever experiments are not plausible. Frequently, scales are used to assess risk factors and their consequences, and cross-lagged effects are estimated to determine possible risks. Methods to translate cross-lagged effects into risk ratios to facilitate risk assessment do not yet exist, which creates a divide between psychological and epidemiological work stress research. The aim of the present paper is to demonstrate how cross-lagged effects can be used to assess the risk ratio of different levels of psychosocial safety climate (PSC) in organisations, an important psychosocial risk for the development of dep…

Predicting survival after transarterial chemoembolization for hepatocellular carcinoma using a neural network: A Pilot Study.

2019

BACKGROUND AND AIMS Deciding when to repeat and when to stop transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC) can be difficult even for experienced investigators. Our aim was to develop a survival prediction model for such patients undergoing TACE using novel machine learning algorithms and to compare it to conventional prediction scores, ART, ABCR and SNACOR. METHODS For this retrospective analysis, 282 patients who underwent TACE for HCC at our tertiary referral centre between January 2005 and December 2017 were included in the final analysis. We built an artificial neural network (ANN) including all parameters used by the aforementioned risk scores a…