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This paper presents the latest prototype of the integrated emitter turn-off thyristor concept, which potentially ranks among thyristor high-power devices like the gate turn-off thyristor and the integrated gate-commutated thyristor (IGCT). Due to modifications of the external driver stage and mechanical press-pack design optimization, this prototype allows for full device characterization. The turn-off capability was increased to 1600 A with an active silicon area of 823mm2 . This leads to a transient peak power of 672.1kW/cm² . Within this paper, measurements and concept assessment are presented and a comparison to state-of-the-art IGCT devices is provided.
Monitoring the cellular metabolism of bacteria in (bio)fermentation processes is crucial to control and steer them, and to prevent undesired disturbances linked to metabolically inactive microorganisms. In this context, cell-based biosensors can play an important role to improve the quality and increase the yield of such processes. This work describes the simultaneous analysis of the metabolic behavior of three different types of bacteria by means of a differential light-addressable potentiometric sensor (LAPS) set-up. The study includes Lactobacillus brevis, Corynebacterium glutamicum, and Escherichia coli, which are often applied in fermentation processes in bioreactors. Differential measurements were carried out to compensate undesirable influences such as sensor signal drift, and pH value variation during the measurements. Furthermore, calibration curves of the cellular metabolism were established as a function of the glucose concentration or cell number variation with all three model microorganisms. In this context, simultaneous (bio)sensing with the multi-organism LAPS-based set-up can open new possibilities for a cost-effective, rapid detection of the extracellular acidification of bacteria on a single sensor chip. It can be applied to evaluate the metabolic response of bacteria populations in a (bio)fermentation process, for instance, in the biogas fermentation process.
Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers’ cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.
As the potential of a next generation network (NGN) is recognised, telecommunication companies consider switching to it. Although the implementation of an NGN seems to be merely a modification of the network infrastructure, it may trigger or require changes in the whole company, because it builds upon the separation between service and transport, a flexible bundling of services to products and the streamlining of the IT infrastructure. We propose a holistic framework, structured into the layers ‘strategy’, ‘processes’ and ‘information systems’ and incorporate into each layer all concepts necessary for the implementation of an NGN, as well as the alignment of these concepts. As a first proof-of-concept for our framework we have performed a case study on the introduction of NGN in a large telecommunication company; we show that our framework captures all topics that are affected by an NGN implementation.
Ensuring access to water and sanitation for all is Goal No. 6 of the 17 UN Sustainability Development Goals to transform our world. As one step towards this goal, we present an approach that leverages remote sensing data to plan optimal water supply networks for informal urban settlements. The concept focuses on slums within large urban areas, which are often characterized by a lack of an appropriate water supply. We apply methods of mathematical optimization aiming to find a network describing the optimal supply infrastructure. Hereby, we choose between different decentral and central approaches combining supply by motorized vehicles with supply by pipe systems. For the purposes of illustration, we apply the approach to two small slum clusters in Dhaka and Dar es Salaam. We show our optimization results, which represent the lowest cost water supply systems possible. Additionally, we compare the optimal solutions of the two clusters (also for varying input parameters, such as population densities and slum size development over time) and describe how the result of the optimization depends on the entered remote sensing data.
The importance of validating and reproducing the outcome of computational processes is fundamental to many application domains. Assuring the provenance of workflows will likely become even more important with respect to the incorporation of human tasks to standard workflows by emerging standards such as WS-HumanTask. This paper addresses this trend by an actor-based workflow approach that actively support provenance. It proposes a framework to track and store provenance information automatically that applies for various workflow management systems. In particular, the introduced provenance framework supports the documentation of workflows in a legally binding way. The authors therefore use the concept of layered XML documents, i.e. history-tracing XML. Furthermore, the proposed provenance framework enables the executors (actors) of a particular workflow task to attest their operations and the associated results by integrating digital XML signatures.