26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Web Scraping – Tools und Techniken zur Beschaffung von Daten aus dem Internet

Das weltweit erzeugte Datenaufkommen steigt rasant an. Daten sind ein wichtiges Unterscheidungsmerkmal für Gesellschaft, Firmen und Unternehmen. Um die enorm große Menge an Daten kontrollieren und auswerten zu können, bedarf es an “Web Scraping”. Unter Web Scraping versteht man gemeinhin das automatisierte Auslesen von Information aus Websites. Im Verlauf dieser Arbeit wird das Thema “Web Scraping" erläutert und anhand von Beispielen der Datenerhebungsprozess von unterschiedlichen “Web Scraping Tools” getestet und dokumentiert. Die erhobenen Daten werden anschließend miteinander verglichen, wodurch erkenntlich wird, welches der Tools die besten Ergebnisse erzielt hat

Forecasting with nonlinear time series models

In this paper, nonlinear models are restricted to mean nonlinear parametric models. Several such models popular in time series econo- metrics are presented and some of their properties discussed. This in- cludes two models based on universal approximators: the Kolmogorov- Gabor polynomial model and two versions of a simple artificial neural network model. Techniques for generating multi-period forecasts from nonlinear models recursively are considered, and the direct (non-recursive) method for this purpose is mentioned as well. Forecasting with com- plex dynamic systems, albeit less frequently applied to economic fore- casting problems, is briefly highlighted. A number of large published studies comparing macroeconomic forecasts obtained using different time series models are discussed, and the paper also contains a small simulation study comparing recursive and direct forecasts in a partic- ular case where the data-generating process is a simple artificial neural network model. Suggestions for further reading conclude the paper.forecast accuracy, Kolmogorov-Gabor, nearest neigh- bour, neural network, nonlinear regression

Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009

In this work we consider forecasting macroeconomic variables dur- ing an economic crisis. The focus is on a specific class of models, the so-called single hidden-layer feedforward autoregressive neural net- work models. What makes these models interesting in the present context is that they form a class of universal approximators and may be expected to work well during exceptional periods such as major economic crises. These models are often difficult to estimate, and we follow the idea of White (2006) to transform the speci?fication and non- linear estimation problem into a linear model selection and estimation problem. To this end we employ three automatic modelling devices. One of them is White's QuickNet, but we also consider Autometrics, well known to time series econometricians, and the Marginal Bridge Estimator, better known to statisticians and microeconometricians. The performance of these three model selectors is compared by look- ing at the accuracy of the forecasts of the estimated neural network models. We apply the neural network model and the three modelling techniques to monthly industrial production and unemployment se- ries of the G7 countries and the four Scandinavian ones, and focus on forecasting during the economic crisis 2007-2009. Forecast accuracy is measured by the root mean square forecast error. Hypothesis testing is also used to compare the performance of the different techniques with each other.Autometrics, economic forecasting, Marginal Bridge estimator, neural network, nonlinear time series model, Wilcoxon's signed-rank test

Forecasting Macroeconomic Variables using Neural Network Models and Three Automated Model Selection Techniques

In this paper we consider the forecasting performance of a well-defined class of flexible models, the so-called single hidden-layer feedforward neural network models. A major aim of our study is to find out whether they, due to their flexibility, are as useful tools in economic forecasting as some previous studies have indicated. When forecasting with neural network models one faces several problems, all of which influence the accuracy of the forecasts. First, neural networks are often hard to estimate due to their highly nonlinear structure. In fact, their parameters are not even globally identified. Recently, White (2006) presented a solution that amounts to converting the specification and nonlinear estimation problem into a linear model selection and estimation problem. He called this procedure the QuickNet and we shall compare its performance to two other procedures which are built on the linearisation idea: the Marginal Bridge Estimator and Autometrics. Second, one must decide whether forecasting should be carried out recursively or directly. Comparisons of these two methodss exist for linear models and here these comparisons are extended to neural networks. Finally, a nonlinear model such as the neural network model is not appropriate if the data is generated by a linear mechanism. Hence, it might be appropriate to test the null of linearity prior to building a nonlinear model. We investigate whether this kind of pretesting improves the forecast accuracy compared to the case where this is not done.artificial neural network, forecast comparison, model selection, nonlinear autoregressive model, nonlinear time series, root mean square forecast error, Wilcoxon’s signed-rank test

Conservering van witte steen: verbetering of verspilde moeite?: de beleving van interventies in Vlaanderen en Nederland

Replacement and repair of natural stone leads to intensive discussions among people involved in restoration. Preservation of the authenticity and compatibility are, besides the costs of replacement, some of the recurrent themes. After intervention the question can be raised whether the results are satisfactory or not. Those results can be viewed either from the perspective of the professional or the layman. This study aims to contribute to the discussion by focussing on the perception of executed conservations. In the framework of the 5th Flemish-Dutch day on natural stone, an illustrated questionnaire was used to investigate the differences and similarities in the perception of the situations shown, between groups of specialists and non-specialists from both Flanders and The Netherlands. The outcome of this study can be used to come to criteria on conservation of white (sandy) limestone

Efficacy of introducing a checklist to reduce central venous line associated bloodstream infections in the ICU caring for adult patients

Abstract Background Central line-associated bloodstream infections (CLABSI) are a major source of sepsis in modern intensive care medicine. Some years ago bundle interventions have been introduced to reduce CLABSI. The use of checklists may be an additional tool to improve the effect of these bundles even in highly specialized institutions. In this study we investigate if the introduction of a checklist reduces the frequency of CLABSI. Methods During the study period from October 2011 to September 2012, we investigated the effect of implementing a checklist for the placement of central venous lines (CVL). Patients were allocated either to the checklist group or to the control group, roughly in a 1:2 ratio. The frequency of CLABSI was compared between the two groups. Results During the study period 4416 CVL were inserted; 1518 in the checklist group and 2898 in the control group. The use of the checklist during CVL placement resulted in a lower CLABSI frequency. The incidence in the checklist group was 3.8 per 1000 catheter days as compared to 5.9 per 1000 catheter days in the control group (IRR = 0.57; p = 0.001). The use of the checklist also reduced the frequency of catheter colonisation significantly, 36.3 per 1000 catheter days in the checklist group vs 21.2 per 1000 catheter days in the control group, respectively (IRR = 0.58; p < 0.001). Conclusion The introduction of a checklist to improve the adherence to hygiene standards while placement of central venous lines reduced the frequency of infections significantly

Additional file 1: of Efficacy of introducing a checklist to reduce central venous line associated bloodstream infections in the ICU caring for adult patients

Figure S1. The English version of the checklist used for this study. (DOCX 191 kb