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Bereits 2018 hat die OPC Foundation die Spezifikation für OPC UA Pub/Sub (Publish/Subscribe) veröffentlicht
hat. Der Softwareentwickler Codesys hat im Oktober 2020 die erste Version der Umsetzung dieses Übertragungsprotokolls veröffentlicht. Die wiederum wurde nun von der Hochschule Kempten dazu genutzt, einen
Industrie-4.0-Demonstrator zukunftsfähig zu vernetzen
To provide overall safety to the automotive domain both vehicle safety and security need to be considered. Cybersecurity is a key to define the quality of the autonomous vehicle by introducing safe and secure development and risk assessment. The implementation of the Over-The-Air (OTA) updates in the automotive industry brought many facilities to the drier and the Original Equipment Manufacturer (OEM). The amount of cost-saving from OTA for OEMs is assumed over several billion. So, research is essential for safe and secure OTA updates in the autonomous vehicle. However, Highly Automated Driving Functions (HADFs) have already raised the necessity of secure development because a threat can lead to harm in certain scenarios including the functional insufficiencies as mentioned in Safety Of The Intended Functionality (SOTIF) of the system. Scenario-based Hazard Analysis and Risk Assessment (HARA) is extensively used in automated vehicle systems and can support for further development of scenario-based threat analysis for OTA updates. Additionally, the scenario-based analysis represents the alliance of safety and security during product development. Therefore, this paper illustrates the scenario-based analysis and assessment of threats including the OTA feature. Furthermore, demonstrates the processes step-by-step to perform Threat Analysis and Risk Assessment (TARA) against potential vulnerabilities to obtain a set of cybersecurity goals for a HADF.
Load Forecasting in District Heating Systems Using Stacked Ensembles of Machine Learning Algorithms
(2021)
For district heating, heat demand forecasting is playing a key role for an optimised power plant dispatch. Machine Learning can help to significantly improve forecasts of thermal loads. The prediction quality of neural networks is higher than that of decision trees in most cases. However, compared to decision trees neural networks have weaknesses when extrapolating outside known ranges. This work presents a novel method called “Deep DHC” (Deep Learning for District Heating and Cooling), which combines these two approaches in order to benefit from strengths of both methods. On the one hand, the novel approach uses conventional decision tree based regression algorithms such as the AdaBoost and Random Forest, as well as artificial neural networks. In addition to common feed forward neural networks (FNN), a deep learning network structure, which consists of long short-term memory (LSTM) cells, is used for the first time. The LSTM method has already proven to be very powerful in modern speech recognition. In order to achieve best possible heat demand forecasts, the aforementioned methods for load forecasting are combined and weighted by an additional machine learning method. Results show that it is possible to achieve a further improvement in forecasting quality for district heating loads by purposefully combining individual forecasting methods. Hence, mean and absolute deviations are significantly reduced in comparison to the individual methods.
Hintergrund: Die COVID-19 Pandemie stellt Bewohner von Altenpflegeeinrichtungen, deren Angehörige bzw. Besucher ebenso wie Mitarbeitende vor große Herausforderungen. Viruseindämmenden Maßnahmen wirken sich stark auf das Wohlbefinden der betroffenen Personengruppen aus. Material und Methode: Systematische Literatursuche nach Studien zu psychosozialen Folgen der Pandemie für Bewohner, deren Angehörige bzw. Besucher und Mitarbeitende und Zusammenführung der Ergebnisse mittels narrativer Synthese.
Ergebnisse: 756 Studien wurden gesichtet, 15 Arbeiten eingeschlossen. Die Daten wurden zwischen Februar und Juni 2020 mit Teilnehmenden aus 14 Ländern erhoben. Es wurden v.a. Einsamkeit, Trauer und Depressivität, aber auch Angst, als häufige Reaktionen der Bewohner auf die Kontakt- und Besuchsrestriktionen berichtet. Bewohner mit kognitiven Einschränkungen litten stärker unter den Auswirkungen, auch wenn es gegenteilige Hinweise gibt. Angehörige bzw. Besucher berichteten ebenfalls von einer Zunahme ihrer Einsamkeit und einer reduzierten Lebensqualität. In den Befragungen der Mitarbeitenden schildern diese Angst vor einer Infektion sowohl bei sich als auch bei den Bewohnern. Infizierte Mitarbeitende in den USA äußerten Wut darüber, nicht ausreichend geschützt geworden zu sein. Darüber hinaus berichteten Mitarbeitende von einer erheblichen Mehrbelastung.
Schlussfolgerung: Infolge der Pandemie und der ergriffenen Maßnahmen wurden negative psychosozialen Folgen bei Bewohnern, deren Angehörigen bzw. Besuchern und den Mitarbeitenden berichtet. Der abzuleitende Unterstützungsbedarfe der drei Personengruppen sind unterschiedlich und sollten bei zukünftigen Maßnahmen hinsichtlich der Pandemie stärker mitevaluiert werden.
The rapidly developing concept of carsharing is an essential and scalable part of sustainable, multimodal mobility in urban environments. There is a clear need for carsharing operators to understand their users and how they use different transportation modes to intensify the development of carsharing and its positive impacts on the environment and urban cohabitation. We foster this understanding by analyzing usage data of carsharing in a medium-sized German city. We compare user groups based on individual characteristics and their carsharing usage behavior. We focus on a station-based two-way carsharing scheme and its relation to free-floating carsharing. Based on different clustering and segmentation approaches, we defined 20 particularly interesting user groups among the carsharing users and analyzed noticeable usage patterns. Additionally, we examined these partially overlapping user groups in the spatial dimension. With these results, we support research and operators in understanding carsharing customers and assessing users’ individual behavior.
Due to the rapid progress in the development of automated vehicles over the last decade, their market entry is getting closer. One of the remaining challenges is the safety assessment and type approval of automated vehicles, as conventional testing in the real world would involve an unmanageable mileage. Scenario-based testing using simulation is a promising candidate for overcoming this approval trap. Although the research community has recognized the importance of safeguarding in recent years, the quality of simulation models is rarely taken into account. Without investigating the errors and uncertainties of models, virtual statements about vehicle safety are meaningless. This paper describes a whole process combining model validation and safety assessment. It is demonstrated by means of an actual type-approval regulation that deals with the safety assessment of lane-keeping systems. Based on a thorough analysis of the current state-of-the-art, this paper introduces two approaches for selecting test scenarios. While the model validation scenarios are planned from scratch and focus on scenario coverage, the type-approval scenarios are extracted from measurement data based on a data-driven pipeline. The deviations between lane-keeping behavior in the real and virtual world are quantified using a statistical validation metric. They are then modeled using a regression technique and inferred from the validation experiments to the unseen virtual type-approval scenarios. Finally, this paper examines safety-critical lane crossings, taking into account the modeling errors. It demonstrates the potential of the virtual-based safeguarding process using exemplary simulations and real driving tests.
Apotheken, die für Pflegeheime verblistern, beklagen häufig die zu niedrige Vergütung des Verblisterns durch ihre Auftraggeber. Die Preise, die Apotheken für die Verblisterung für Selbstzahler erzielen, wurden bisher nicht systematisch untersucht. Die vorliegende Studie hat diese Preise nun für mehr als 60 Apotheken erhoben. Die Untersuchung zeigt neben einer bemerkenswerten Spannbreite der Preise insbesondere auch, dass bei Selbstzahlern deutlich höhere Vergütungen als bei Pflegeheimen realisiert werden können.
The enormous power consumption of Bitcoin has led to undifferentiated discussions in science and practice about the sustainability of blockchain and distributed ledger technology in general. However, blockchain technology is far from homogeneous - not only with regard to its applications, which now go far beyond cryptocurrencies and have reached businesses and the public sector, but also with regard to its technical characteristics and, in particular, its power consumption. This paper summarizes the status quo of the power consumption of various implementations of blockchain technology, with special emphasis on the recent 'Bitcoin Halving' and so-called 'zk-rollups'. We argue that although Bitcoin and other proof-of-work blockchains do indeed consume a lot of power, alternative blockchain solutions with significantly lower power consumption are already available today, and new promising concepts are being tested that could further reduce in particular the power consumption of large blockchain networks in the near future. From this we conclude that although the criticism of Bitcoin's power consumption is legitimate, it should not be used to derive an energy problem of blockchain technology in general. In many cases in which processes can be digitised or improved with the help of more energy-efficient blockchain variants, one can even expect net energy savings.
Emerging digital technologies enable the creation of new services and business models, leading to ecosystems’ continuous change. In the tourism industry, new digital-savvy players like Airbnb have entered and created entirely new market segments, while many existing players are challenged to redefine their business logic. However, the literature does not provide a generic overview of the value network in tourism, including new market players, and their ways of interacting. Therefore, this paper develops a current overview of the value network of the European tourism ecosystem. By analyzing the business models and value streams of 704 European enterprises based on Crunchbase data, we identified 27 distinct roles and their respective interrelations in the domain. To validate the proposed value network, we conducted five expert interviews. Our results highlight the continuously growing importance of intermediaries in tourism. Furthermore, new technology players offer new opportunities for innovative services, creating high dynamism in the industry. Nonetheless, local entities, such as residents and communities, play a central role in European tourism and need to be included in experiences provided to tourists. Scholars and practitioners might use the results to identify disruptive actors and opportunities for innovation and niche creation. Additionally, the results can be used as a basis for further analysis of the ecosystem’s ongoing changes induced through technological advancements or external events such as the COVID-19 pandemic.
In present-day societies, experience orientation and changing consumer needs call for adjusting products and services to satisfy evolving market demands. Tourism markets are inherently international leading to an encounter of tourists and service providers from different cultures. In the global market place, the awareness of how culture influences customers’ experience is essential. By facilitating the emergence of meaningful and memorable experiences for culturally diverse customers, hospitality and tourism companies can create value for their customers. This chapter sets out to give some insights into the role of emotions in the customer experience as well as into culture’s influence on emotions. Suggestions for designing the service environment and the service encounter of hospitality companies to better meet the needs of the culturally diverse customers and thereby enabling positive experiences to emerge, are also made.