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Agility is considered the silver bullet for survival in the VUCA world. However, many organisations are afraid of endangering their ISO 9001 certificate when introducing agile processes. A joint research project of the University of Applied Sciences and Arts Hannover and the DGQ has set itself the goal of providing more security in this area. The findings were based on interviews with managers and team members from various organisations of different sizes and industries working in an agile manner as well as on common audit practices and a literature analysis. The outcome presents a clear distinction of agility from flexibility as well as useful guidelines for the integration of agile processes in QM systems - for QM practitioners and auditors alike.
The increasing variety of combinations of different building technology components offers a high potential for energy and cost savings in today's buildings. However, in most cases, this potential is not yet fully exploited due to the lack of intelligent supervisory control systems that are required to manage the complexity of the resulting overall systems. In this article, we present the implementation of a mixed-integer nonlinear model predictive control approach as a smart realtime building energy management system. The presented methodology is based on a forward-looking optimization of the overall energy costs. It takes into account energy demand forecasts and varying electricity market prices. We achieve real-time capability of the controller by applying a decomposition approach, which approximates the optimal solution of the underlying mixed-integer optimal control problem by convexification and rounding of the relaxed solution. The quality of the suboptimal solution is evaluated by comparison with the globally optimal solution obtained by the dynamic programming method. Based on a real-world scenario, we demonstrate that utilization of the real-time capable mixedinteger nonlinear model predictive control approach in a building control system leads to savings of 16% in the total operating costs and 13% in primary energy compared to the state-of-the-art control strategy without any loss of comfort for the residents.
This paper presents a novel approach for modelling the energy consumption of the coupled parallel moulding sand mixers of a foundry as an optimal control problem. The minimization of energy consumption is optimized by scheduling the mixing processes in a linear integer programming scheme. The sand flow through the foundry’s sand preparation is characterized by a physical model. This model considers the sand demand of the moulding machine as disturbance, the stored sand masses in the mixer hoppers and machine hoppers, respectively. The novel approach of handling dwell-times for dosing, mixing and transport processes using dead-time systems and constraint pushing allows the application of a linear model. The formulation of the optimal control problem aims at real-time application as model predictive control at the production plant. Initial application results indicate an improvement in energy consumption of approximately 8%.
The German Corona Consensus (GECCO) established a uniform dataset in FHIR format for exchanging and sharing interoperable COVID-19 patient specific data between health information systems (HIS) for universities. For sharing the COVID-19 information with other locations that use openEHR, the data are to be converted in FHIR format. In this paper, we introduce our solution through a web-tool named “openEHR-to-FHIR” that converts compositions from an openEHR repository and stores in their respective GECCO FHIR profiles. The tool provides a REST web service for ad hoc conversion of openEHR compositions to FHIR profiles.
Industrial Control Systems (ICS) succumb to an ever evolving variety of threats. Additionally, threats are increasing in number and get more complex. This requires a holistic and up-to-date security concept for ICS as a whole. Usually security concepts are applied and updated based on regularly performed ICS security assessments. Such ICS security assessments require high effort and extensive knowledge about ICS and its security. This is often a problem for small and mediumsized enterprises (SME), which do not have sufficient respective sufficiently skilled human resources. This paper defines in a first step requirements on the knowledge needed to perform an ICS security assessment and the life cycle of this knowledge. Afterwards the ICS security knowledge and its life cycle are developed and discussed considering the requirements and related work.
In parcel delivery, the “last mile” from the parcel hub to the customer is costly, especially for time-sensitive delivery tasks that have to be completed within hours after arrival. Recently, crowdshipping has attracted increased attention as a new alternative to traditional delivery modes. In crowdshipping, private citizens (“the crowd”) perform short detours in their daily lives to contribute to parcel delivery in exchange for small incentives. However, achieving desirable crowd behavior is challenging as the crowd is highly dynamic and consists of autonomous, self-interested individuals. Leveraging crowdshipping for time-sensitive deliveries remains an open challenge. In this paper, we present an agent-based approach to on-time parcel delivery with crowds. Our system performs data stream processing on the couriers’ smartphone sensor data to predict delivery delays. Whenever a delay is predicted, the system attempts to forge an agreement for transferring the parcel from the current deliverer to a more promising courier nearby. Our experiments show that through accurate delay predictions and purposeful task transfers many delays can be prevented that would occur without our approach.
In this paper we investigate how concreteness and abstractness are represented in word embedding spaces. We use data for English and German, and show that concreteness and abstractness can be determined independently and turn out to be completely opposite directions in the embedding space. Various methods can be used to determine the direction of concreteness, always resulting in roughly the same vector. Though concreteness is a central aspect of the meaning of words and can be detected clearly in embedding spaces, it seems not as easy to subtract or add concreteness to words to obtain other words or word senses like e.g. can be done with a semantic property like gender.
The dependency of word similarity in vector space models on the frequency of words has been noted in a few studies, but has received very little attention. We study the influence of word frequency in a set of 10 000 randomly selected word pairs for a number of different combinations of feature weighting schemes and similarity measures. We find that the similarity of word pairs for all methods, except for the one using singular value decomposition to reduce the dimensionality of the feature space, is determined to a large extent by the frequency of the words. In a binary classification task of pairs of synonyms and unrelated words we find that for all similarity measures the results can be improved when we correct for the frequency bias.
Portable-micro-Combined-Heat-and-Power-units are a gateway technology bridging conventional vehicles and Battery Electric Vehicles (BEV). Being a new technology, new software has to be created that can be easily adapted to changing requirements. We propose and evaluate three different architectures based on three architectural paradigms. Using a scenario-based evaluation, we conclude that a Service-Oriented Architecture (SOA) using microservices provides a higher quality solution than a layered or Event-Driven Complex-Event-Processing (ED-CEP) approach. Future work will include implementation and simulation-driven evaluation.
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