Abstract Anomaly detection in industrial control and cyber-physical systems has gained much attention over the past years due to increasing modernisation exposure of environments. Current dangers connected industry include theft intellectual property, denial service, or compromise cloud components; all which might result a cyber-attack across operational network. However, most scientific work employs device logs, necessitate substantial understanding preprocessing before they can be used...

Four visual censuses targeting Octopus vulgaris living in dens on sandy bottoms were carried out from June to October 2013 the National Park of Atlantic Galician Islands (NW Spain). Censuses undertaken by scuba diving between 5 and 21 m depth daytime. The total area swept was 13.75 ha. There no significant differences octopus presence during open closed fishing seasons. Depth had a negative relationship with occupancy. average number per 1000 m2 3.84±0.84 3.89 October. den 260 m2. Den...

In multiple regression models, when there are a large number (p) of explanatory variables which may or not be relevant for predicting the response, it is useful to able reduce model.To this end, necessary determine best subset q (q ≤ p) predictors will establish model with prediction capacity.FWDselect package introduces new forward stepwisebased selection procedure select in different frameworks (parametric nonparametric).The developed methodology, can equally applied linear generalized...

Abstract Neural Networks are one of the most popular methods nowadays given their high performance on diverse tasks, such as computer vision, anomaly detection, computer-aided disease detection and diagnosis or natural language processing. While neural networks known for performance, they often suffer from so-called “black-box” problem, which means that it is difficult to understand how model makes decisions. We introduce a network topology based Generalized Additive Models. By training an...

One major goal in clinical applications of time-to-event data is the estimation survival with censored data.The usual nonparametric estimator function time-honored Kaplan-Meier product-limit estimator.Though this has been implemented several R packages, development condSURV package motivated by recent contributions that allow for ordered multivariate failure time provides three different approaches all based on estimator.In one these quantities are estimated conditionally current or past...

This study was undertaken using data drawn from 5 sites along the Atlantic shoreline of Galicia (Northwest Spain) for a period 2 y. The length—weight relationship Pollicipes pollicipes (Gmelin, 1789) estimated to observe way in which individuals this species gain weight as they increase size. A classic allometric model used purpose. As an alternative, more general nonparametric also estimated, local linear kernel smoothers. Comparison these two models showed that use resulted better fit...

We present the R npregfast package via some applications involved with study of living organisms. The implements nonparametric estimation procedures in regression models or without factor-by-curve interactions. main feature is its ability to perform inference regarding these models. Namely, implementation different test features estimated curves: on one hand, comparisons between curves which may vary across groups defined by levels a categorical variable factor; other critical points curve...

Survival analysis includes a wide variety of methods for analyzing time-to-event data. One basic but important goal in survival is the comparison curves between groups. Several nonparametric have been proposed literature to test equality censored When null hypothesis rejected, leading clear conclusion that at least one curve different, it can be interesting ascertain whether grouped or if all these are different from each other. A method allows determining groups with an automatic selection...

In longitudinal studies of disease, patients may experience several events through a follow‐up period. these studies, the sequentially ordered are often interest and lead to problems that have received much attention recently. Issues include estimation bivariate survival, marginal distributions, conditional distribution gap times. this work, we consider survival function previous event. Different nonparametric approaches will be considered for estimating quantities, all based on Kaplan–Meier...

Abstract The cumulative incidence function is the standard method for estimating marginal probability of a given event in presence competing risks. One basic but important goal analysis risk data comparison these curves, which limited literature exists. We proposed new procedure that lets us not only test equality curves also group them if they are equal. allows determining composition groups as well an automatic selection their number. Simulation studies show good numerical behavior methods...

Multi-state models are a useful way of describing process in which an individual moves through number finite states continuous time.The illness-death model plays central role the theory and practice these models, dynamics healthy subjects who may move to intermediate "diseased" state before entering into terminal absorbing state.In one important goal is modeling transition rates usually done by studying relationship between covariates disease evolution.However, biomedical researchers also...

In many situations, it could be interesting to ascertain whether groups of curves can performed, especially when confronted with a considerable number curves.This paper introduces an R package, known as clustcurv, for determining clusters automatic selection their number.The package used in multiple survival well regression curves.Moreover, large numbers curves.An illustration the use clustcurv is provided, using both real data examples and artificial data.

The increasing adoption of the Industrial Internet Things and integration operational technology with information networks have made industrial control systems (ICS) more vulnerable to cyber-attacks, which can cause severe consequences such as disruption critical infrastructure, loss data, significant financial losses. To enhance security resilience these systems, anomaly detection in ICS has gained attention recent years. This paper introduces ongoing research focused on using Long...

Marine wildlife and aquaculture species can accumulate large amounts of marine microplastic debris (MMD) (<1 mm) carrying pathogens, thus threatening the health ecosystems posing a risk to food safety human health. Here, we outline theoretical three-perspective approach for studying relationship between MMD disease. First, provide framework retrospective analysis pathogen loads in animal tissues assess these other environmental variables order decide whether compound or should be...