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Specifying the target reliability levels is one of the key issues in the assessment of existing structures. For a majority of existing buildings and infrastructures, the design life has been reached or will be reached in the near future. These structures need to be reassessed in order to verify their safety. Eurocodes provide a general basis primarily intended for the design of new structures, but the basic principles can be used for assessing existing buildings, too. Reliability levels are generally based on both economic optimization and criteria for human safety. In this study, both methods are elaborated for existing structures. It appears that the requirement for the same target reliability for existing and new structures is uneconomical. Further, cost optimization seems to yield rather low reliability levels and human safety criteria often become the critical factor. The study concludes with practical guidelines for establishing reliability indices for existing structures linked to Eurocode principles.
EMDLAB: A toolbox for analysis of single-trial EEG dynamics using empirical mode decomposition
(2015)
Background:
Empirical mode decomposition (EMD) is an empirical data decomposition technique. Recently there is growing interest in applying EMD in the biomedical field.
New method:
EMDLAB is an extensible plug-in for the EEGLAB toolbox, which is an open software environment for electrophysiological data analysis.
Results:
EMDLAB can be used to perform, easily and effectively, four common types of EMD: plain EMD, ensemble EMD (EEMD), weighted sliding EMD (wSEMD) and multivariate EMD (MEMD) on EEG data. In addition, EMDLAB is a user-friendly toolbox and closely implemented in the EEGLAB toolbox.
Comparison with existing methods:
EMDLAB gains an advantage over other open-source toolboxes by exploiting the advantageous visualization capabilities of EEGLAB for extracted intrinsic mode functions (IMFs) and Event-Related Modes (ERMs) of the signal.
Conclusions:
EMDLAB is a reliable, efficient, and automated solution for extracting and visualizing the extracted IMFs and ERMs by EMD algorithms in EEG study.
Die Regenbrücke Stefling ist als Beton-Stabbogenbrücke ein neuer, moderner Brückentyp. Besonders hervorzuheben ist neben guten gestalterischen Elementen die Kombination verschiedener optimierter Bauweisen und Konstruktionsdetails, die zu einem Querschnitt führen, der eine äußerst geringe Bauhöhe aufweist. Hauptmerkmale sind hier der Werkstoff Beton anstelle von Stahl für den Stabbogen, der Einsatz verbundloser Vorspannung und die Ausbildung der Hänger als Netzwerk. Zusätzlich ist dieser Brückentyp in wirtschaftlicher Hinsicht äußerst konkurrenzfähig. Dies wurde an der Regenbrücke Stefling bestätigt. Innovation concentrated – Regenbrücke Stefling: a tied arch bridge in concrete The Regenbrücke Stefling is a new and modern bridge structure of tied arch bridges in concrete. Particularly there is to be emphasised beside good formative elements the combination of different optimised construction methods and construction details which induce a cross section which shows an extremely low construction height. Main characteristics are the material concrete in place of steel for the tied arch, the application of internal unbonded prestressing and the construction of the hangers as a network. In addition, this type of bridge is extremely competitive in economic regard. This was confirmed by the Regenbrücke Stefling.
Manual tasks in industrial production are often monotonous, leading to a decrease in concentration and motivation of the worker and thus to deficiencies in the products. With quality as well as performance requirements getting more and more stringent, workers need additional support by their work environment. We developed a novel approach providing worker assistance and inline quality assurance for manual workplaces. The prototypical system Smart Workbench (SWoB) uses a multimodal sensor interface consisting of a 3D depth sensor in combination with a 2D camera to control quality aspects of the product and track the work progress. The bidirectional flow of information is handled via an image processing driven gestural interface and the displaying of advice directly on the work surface. In this paper the developed system is introduced and the current state of evaluating its industrial usage with a manual quality control and packaging task reported.
Today, ubiquitous mobile devices have not only arrived but entered the safety critical domain. There, systems are about to be controlled where human health or even human life is put at risk. For example, in automation systems first ideas surface to control parts of the system via a COTS smartphone. Another example is the idea to control the autonomous parking function of a car via a COTS smartphone too. As beneficial and convenient these ideas are on the first thought, on the second thought, dangers of these approaches become obvious. Especially in case of failures the system’s safety has to be maintained. The open question is how to achieve this mandatory requirement with COTS components, e.g. smartphones that are not developed following the development process necessary for safetycritical systems. This paper presents a concept to reliably detect human interaction while activating safety critical functions via COTS mobile devices. Thus a means is provided to detect erroneous activation requests for the safetycritical function.
As part of a research project to develop design solutions for concrete-masonry buildings for the Canadian market, the apparent sound insulation performance of hybrid assemblies with concrete masonry walls and wood joist floors was evaluated. In this paper, the effect of junction coupling is investigated in an ISO 15712 flanking prediction context. Airborne flanking path data predicted according to ISO 15712 are compared to data measured using the indirect ISO 10848 shielding
method. Recommendations are made on how appropriate the application of ISO 15712 is for this type of hybrid assembly.
The performance of cognitive models often depends on the settings of specific model parameters, such as the rate of memory decay or the speed of motor responses. The systematic exploration of a model’s parameter space can yield relevant insights into model behavior and can also be used to improve the fit of a model to human data. However, exhaustive parameter space searches quickly run into a combinatorial explosion as the number of parameters investigated increases. Taking an established instance-based learning task as example, we show
how simulation using parallel computing and derivative-free optimization methods can be applied to investigate the effects
of different parameter settings. We find that both global optimization methods involving genetic algorithms as well as local methods yield satisfactory results in this case. Furthermore, we show how a model implemented in a specific cognitive architecture (ACT-R) can be mathematically reformulated to prepare the application of derivative-based optimization methods which promise further efficiency gains for quantitative analysis.
It is simple to query a relational database because all columns of the tables are known and the language SQL is easily applicable. In NoSQL, there usually is no fixed schema and no query language. In this article, we present NotaQL, a data-transformation language for wide-column stores. NotaQL is easy to use and powerful. Many MapReduce algorithms like filtering, grouping, aggregation and even breadth-first-search, PageRank and other graph and text algorithms can be expressed in two or three short lines of code.