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showing 10 items of 3931 documents
Rectilinear evolution in arvicoline rodents and numerical dating of Iberian Early Pleistocene sites
2014
Abstract Lozano-Fernandez et al. (2013a) have recently published a method intended for numerical dating of Early Pleistocene sites, which is based on the assumption of uniform, constant rate increase through time of mean lower molar tooth length of water voles ( Mimomys savini ) in a number of levels sampled in the stratigraphic sequence of Atapuerca TD site. They suggest that the regression equation obtained in this local section for site chronology on tooth size could be useful for estimating the numerical age of other localities from southwestern Europe. However, in our opinion this biostratigraphic approach has severe conceptual and methodological problems, which discourage its use as a…
European society of hypertension position paper on ambulatory blood pressure monitoring
2013
Ambulatory blood pressure monitoring (ABPM) is being used increasingly in both clinical practice and hypertension research. Although there are many guidelines that emphasize the indications for ABPM, there is no comprehensive guideline dealing with all aspects of the technique. It was agreed at a consensus meeting on ABPM in Milan in 2011 that the 34 attendees should prepare a comprehensive position paper on the scientific evidence for ABPM.This position paper considers the historical background, the advantages and limitations of ABPM, the threshold levels for practice, and the cost-effectiveness of the technique. It examines the need for selecting an appropriate device, the accuracy of dev…
Comparison of approaches for generation of fully non-stationary artificial accelerograms
2019
The modelling of the seismic input is a critical aspect when non-linear time-history analyses (NLTHAs) are carried out. As a matter of fact, seismic response of structures is very sensitive to the input excitation time history. The present work aims to highlight the differences in the input modelling and the assessment of seismic response of three r.c. structures employing four generation methods of fully non-stationary artificial accelerogram sets at a given construction site. For each method, seven accelerograms are generated and employed to perform NLTHAs on three r.c. structures having irregular mass and stiffness distributions. The original contribution of the paper relies in the crite…
Intrusion Detection with Interpretable Rules Generated Using the Tsetlin Machine
2020
The rapid deployment in information and communication technologies and internet-based services have made anomaly based network intrusion detection ever so important for safeguarding systems from novel attack vectors. To this date, various machine learning mechanisms have been considered to build intrusion detection systems. However, achieving an acceptable level of classification accuracy while preserving the interpretability of the classification has always been a challenge. In this paper, we propose an efficient anomaly based intrusion detection mechanism based on the Tsetlin Machine (TM). We have evaluated the proposed mechanism over the Knowledge Discovery and Data Mining 1999 (KDD’99) …
Predicting hospital associated disability from imbalanced data using supervised learning.
2019
Hospitalization of elderly patients can lead to serious adverse effects on their functional capability. Identifying the underlying factors leading to such adverse effects is an active area of medical research. The purpose of the current paper is to show the potential of artificial intelligence in the form of machine learning to complement the existing medical research. This is accomplished by studying the outcome of hospitalization of elderly patients as a supervised learning task. A rich set of features characterizing the medical and social situation of elderly patients is leveraged and using confusion matrices, association rule mining, and two different classes of supervised learning algo…
Bayesian dynamic modeling of time series of dengue disease case counts
2017
The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model’s short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order …
Machine Learning VS Transfer Learning - Smart Camera Implementation for Face Authentication
2018
The aim of this paper is to highlight differences between classical machine learning and transfer learning applied to low cost real-time face authentication. Furthermore, in an access control context, the size of biometric data should be minimized so it can be stored on a remote personal media. These constraints have led us to compare only lightest versions of these algorithms. Transfer learning applied on Mobilenet v1 raises to 85% of accuracy, for a 457Ko model, with 3680s and 1.43s for training and prediction tasks. In comparison, the fastest integrated method (Random Forest) shows accuracy up to 90% for a 7,9Ko model, with a fifth of a second to be trained and a hundred of microseconds …
Protocol for developing a mental imagery intervention: a randomised controlled trial testing a novel implementation imagery e-health intervention to …
2019
IntroductionDrowning due to driving into floodwater accounts for a significant proportion of all deaths by drowning. Despite awareness campaigns such as ‘If it’s flooded, forget it’, people continue to drive into floodwater. This causes loss of life, risk to rescuers and damage to vehicles. The aim of this study was to develop and evaluate an online e-health intervention to promote safe driving behaviour during flood events.Methods and analysisThe study will use a 2×3 randomised controlled trial in which participants are randomised into one of two conditions: (1) education about the risks of driving into floodwater or (2) education about the risks of driving into floodwater plus a theory-ba…
Protocol for developing a mental imagery intervention: a randomised controlled trial testing a novel implementation imagery e-health intervention to …
2019
IntroductionDrowning due to driving into floodwater accounts for a significant proportion of all deaths by drowning. Despite awareness campaigns such as 'If it's flooded, forget it', people continue to drive into floodwater. This causes loss of life, risk to rescuers and damage to vehicles. The aim of this study was to develop and evaluate an online e-health intervention to promote safe driving behaviour during flood events.Methods and analysisThe study will use a 2×3 randomised controlled trial in which participants are randomised into one of two conditions: (1) education about the risks of driving into floodwater or (2) education about the risks of driving into floodwater plus a theory-ba…
Stochastic differential calculus for wind-exposed structures with autoregressive continuous (ARC) filters
2008
In this paper, an alternative method to represent Gaussian stationary processes describing wind velocity fluctuations is introduced. The technique may be considered the extension to a time continuous description of the well-known discrete-time autoregressive model to generate Gaussian processes. Digital simulation of Gaussian random processes with assigned auto-correlation function is provided by means of a stochastic differential equation with time delayed terms forced by Gaussian white noise. Solution of the differential equation is a specific sample of the target Gaussian wind process, and in this paper it describes a digitally obtained record of the wind turbolence. The representation o…