Search results for "Information Science"
showing 10 items of 3627 documents
sj-docx-1-dhj-10.1177_20552076221074485 - Supplemental material for The role of age and digital competence on the use of online health and social car…
2022
Supplemental material, sj-docx-1-dhj-10.1177_20552076221074485 for The role of age and digital competence on the use of online health and social care services: A cross-sectional population-based survey by T Heponiemi, A-M Kaihlanen, A Kouvonen, L Leemann, S Taipale and K Gluschkoff in Digital Health
Active and inactive quarantine in epidemic spreading on adaptive activity-driven networks
2020
We consider an epidemic process on adaptive activity-driven temporal networks, with adaptive behaviour modelled as a change in activity and attractiveness due to infection. By using a mean-field approach, we derive an analytical estimate of the epidemic threshold for SIS and SIR epidemic models for a general adaptive strategy, which strongly depends on the correlations between activity and attractiveness in the susceptible and infected states. We focus on strong social distancing, implementing two types of quarantine inspired by recent real case studies: an active quarantine, in which the population compensates the loss of links rewiring the ineffective connections towards non-quarantining …
Combinatorial proofs of two theorems of Lutz and Stull
2021
Recently, Lutz and Stull used methods from algorithmic information theory to prove two new Marstrand-type projection theorems, concerning subsets of Euclidean space which are not assumed to be Borel, or even analytic. One of the theorems states that if $K \subset \mathbb{R}^{n}$ is any set with equal Hausdorff and packing dimensions, then $$ \dim_{\mathrm{H}} π_{e}(K) = \min\{\dim_{\mathrm{H}} K,1\} $$ for almost every $e \in S^{n - 1}$. Here $π_{e}$ stands for orthogonal projection to $\mathrm{span}(e)$. The primary purpose of this paper is to present proofs for Lutz and Stull's projection theorems which do not refer to information theoretic concepts. Instead, they will rely on combinatori…
sj-pdf-1-jis-10.1177_01655515211043708 – Supplemental material for How do gender, Internet activity and learning beliefs predict sixth-grade students…
2021
Supplemental material, sj-pdf-1-jis-10.1177_01655515211043708 for How do gender, Internet activity and learning beliefs predict sixth-grade students’ self-efficacy beliefs in and attitudes towards online inquiry? by Eero Sormunen, Norbert Erdmann, Suzanne CSA Otieno, Mirjamaija Mikkilä-Erdmann, Eero Laakkonen, Teemu Mikkonen, Md Arman Hossain, Roberto González-Ibáñez, Mario Quintanilla-Gatica, Paavo HT Leppänen and Marja Vauras in Journal of Information Science
sj-pdf-1-jis-10.1177_01655515211043708 – Supplemental material for How do gender, Internet activity and learning beliefs predict sixth-grade students…
2021
Supplemental material, sj-pdf-1-jis-10.1177_01655515211043708 for How do gender, Internet activity and learning beliefs predict sixth-grade students’ self-efficacy beliefs in and attitudes towards online inquiry? by Eero Sormunen, Norbert Erdmann, Suzanne CSA Otieno, Mirjamaija Mikkilä-Erdmann, Eero Laakkonen, Teemu Mikkonen, Md Arman Hossain, Roberto González-Ibáñez, Mario Quintanilla-Gatica, Paavo HT Leppänen and Marja Vauras in Journal of Information Science
Flood Detection On Low Cost Orbital Hardware
2019
Satellite imaging is a critical technology for monitoring and responding to natural disasters such as flooding. Despite the capabilities of modern satellites, there is still much to be desired from the perspective of first response organisations like UNICEF. Two main challenges are rapid access to data, and the ability to automatically identify flooded regions in images. We describe a prototypical flood segmentation system, identifying cloud, water and land, that could be deployed on a constellation of small satellites, performing processing on board to reduce downlink bandwidth by 2 orders of magnitude. We target PhiSat-1, part of the FSSCAT mission, which is planned to be launched by the …
Core of communities in bipartite networks
2017
We use the information present in a bipartite network to detect cores of communities of each set of the bipartite system. Cores of communities are found by investigating statistically validated projected networks obtained using information present in the bipartite network. Cores of communities are highly informative and robust with respect to the presence of errors or missing entries in the bipartite network. We assess the statistical robustness of cores by investigating an artificial benchmark network, the co-authorship network, and the actor-movie network. The accuracy and precision of the partition obtained with respect to the reference partition are measured in terms of the adjusted Ran…
Explaining the unique nature of individual gait patterns with deep learning
2019
Machine learning (ML) techniques such as (deep) artificial neural networks (DNN) are solving very successfully a plethora of tasks and provide new predictive models for complex physical, chemical, biological and social systems. However, in most cases this comes with the disadvantage of acting as a black box, rarely providing information about what made them arrive at a particular prediction. This black box aspect of ML techniques can be problematic especially in medical diagnoses, so far hampering a clinical acceptance. The present paper studies the uniqueness of individual gait patterns in clinical biomechanics using DNNs. By attributing portions of the model predictions back to the input …
Exploratory and Confirmatory Factor Analyses of Religiosity. A Four-Factor Conceptual Model
2017
We describe an exploratory and confirmatory factor analysis of the International Social Survey Programme Religion Cumulation (1991-1998-2008) data set, to identify the factors of individual religiosity and their interrelations in quantitative terms. The exploratory factor analysis was performed using data from the first two waves (1991 and 1998), and led to the identification of four strongly correlated and reliable factors which we labeled Religious formation, Supernatural beliefs, Belief in God, and Religious practice. The confirmatory factor analysis was run using data from 2008, and led to the confirmation of this four-factor structure with very good fit measures. We also ran a set of s…
Bayesian longitudinal models for exploring European sardine fishing in the Mediterranean Sea
2020
In the Mediterranean Sea, catches are dominated by small pelagic fish, representing nearly the 49\% of the total harvest. Among them, the European sardine (Sardina pilchardus) is one of the most commercially important species showing high over-exploitation rates in recent last years. In this study we analysed the European sardine landings in the Mediterranean Sea from 1970 to 2014. We made use of Bayesian longitudinal linear mixed models in order to assess differences in the temporal evolution of fishing between and within countries. Furthermore, we modelled the subsequent joint evolution of artisanal and industrial fisheries. Overall results confirmed that Mediterranean fishery time series…