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Die Covid-19 Pandemie hat zu einem signifikanten Anstieg der Remote Work geführt. Die Veränderung in der Interaktion und Kollaboration ist für viele agile Teams eine Herausforderung gewesen. Diverse Studien zeigen unterschiedliche Effekte und Auswirkungen auf die Zusammenarbeit agiler Teams während der Pandemie. So ist die Kommunikation sachlicher und zielgerichteter geworden. Ebenso wird eine Verminderung des sozialen Austauschs in den Teams berichtet. Unser Artikel thematisiert die Veränderung der Interaktion in agilen Teams durch die Remote Work. Wir haben eine qualitative Fallstudie bei einem agilen Software-Entwicklungsteam bei Otto durchgeführt. Unsere Ergebnisse zeigen einen Zusammenhang zwischen den Auswirkungen auf die Interaktion und der persönlichen Autonomie der Team-Mitglieder. Darüber hinaus haben wir keine signifikanten negativen Effekte durch die veränderte Interaktion auf die agile Arbeitsweise festgestellt.
Smart Cities require reliable means for managing installations that offer essential services to the citizens. In this paper we focus on the problem of evacuation of smart buildings in case of emergencies. In particular, we present an abstract architecture for situation-aware evacuation guidance systems in smart buildings, describe its key modules in detail, and provide some concrete examples of its structure and dynamics.
During the Corona-Pandemic, information (e.g. from the analysis of balance sheets and payment behavior) traditionally used for corporate credit risk analysis became less valuable because it represents only past circumstances. Therefore, the use of currently published data from social media platforms, which have shown to contain valuable information regarding the financial stability of companies, should be evaluated. In this data e. g. additional information from disappointed employees or customers can be present. In order to analyze in how far this data can improve the information base for corporate credit risk assessment, Twitter data regarding the ten greatest insolvencies of German companies in 2020 and solvent counterparts is analyzed in this paper. The results from t-tests show, that sentiment before the insolvencies is significantly worse than in the comparison group which is in alignment with previously conducted research endeavors. Furthermore, companies can be classified as prospectively solvent or insolvent with up to 70% accuracy by applying the k-nearest-neighbor algorithm to monthly aggregated sentiment scores. No significant differences in the number of Tweets for both groups can be proven, which is in contrast to findings from studies which were conducted before the Corona-Pandemic. The results can be utilized by practitioners and scientists in order to improve decision support systems in the domain of corporate credit risk analysis. From a scientific point of view, the results show, that the information asymmetry between lenders and borrowers in credit relationships, which are principals and agents according to the principal-agent-theory, can be reduced based on user generated content from social media platforms. In future studies, it should be evaluated in how far the data can be integrated in established processes for credit decision making. Furthermore, additional social media platforms as well as samples of companies should be analyzed. Lastly, the authenticity of user generated contend should be taken into account in order to ensure, that credit decisions rely on truthful information only.
We present a feedback-corrected optimal scheduling approach to reduce the demand of electrical energy of batch processes, exemplified at the sand preparation in foundry. The main energy driver in the exemplary foundry is the idle time of the batch-wise working sand mixers. In this novel approach, we use linear integer programming to minimize the demand of energy of the sand mixers by scheduling the batches in real-time. For the optimization we use a physical model of the sand preparation, which takes dwell-times of the processes as dead-time systems into account. In this paper, we present the steps to make the optimal scheduling approach applicable for the production process. The application at the real production plant proves the performance of the suggested approach. Compared to the conventional control, the feedback-corrected optimal scheduling approach leads to an reduction in energy consumption of approximately 6.5 % without modifying the process or the aggregates.
The usage of microservices promises a lot of benefits concerning scalability and maintainability, rewriting large monoliths is however not always possible. Especially in scientific projects, pure microservice architectures are therefore not feasible in every project. We propose the utilization of microservice principles for the construction of microsimulations for urban transport. We present a prototypical architecture for the connection of MATSim and AnyLogic, two widely used simulation tools in the context of urban transport simulation. The proposed system combines the two tools into a singular tool supporting civil engineers in decision making on innovative urban transport concepts.
The automated transfer of flight logbook information from aircrafts into aircraft maintenance systems leads to reduced ground and maintenance time and is thus desirable from an economical point of view. Until recently, flight logbooks have not been managed electronically in aircrafts or at least the data transfer from aircraft to ground maintenance system has been executed manually. Latest aircraft types such as the Airbus A380 or the Boeing 787 do support an electronic logbook and thus make an automated transfer possible. A generic flight logbook transfer system must deal with different data formats on the input side – due to different aircraft makes and models – as well as different, distributed aircraft maintenance systems for different airlines as aircraft operators. This article contributes the concept and top level distributed system architecture of such a generic system for automated flight log data transfer. It has been developed within a joint industry and applied research project. The architecture has already been successfully evaluated in a prototypical implementation.
Automatic classification of scientific records using the German Subject Heading Authority File (SWD)
(2012)
The following paper deals with an automatic text classification method which does not require training documents. For this method the German Subject Heading Authority File (SWD), provided by the linked data service of the German National Library is used. Recently the SWD was enriched with notations of the Dewey Decimal Classification (DDC). In consequence it became possible to utilize the subject headings as textual representations for the notations of the DDC. Basically, we we derive the classification of a text from the classification of the words in the text given by the thesaurus. The method was tested by classifying 3826 OAI-Records from 7 different repositories. Mean reciprocal rank and recall were chosen as evaluation measure. Direct comparison to a machine learning method has shown that this method is definitely competitive. Thus we can conclude that the enriched version of the SWD provides high quality information with a broad coverage for classification of German scientific articles.
Automatisierte Steuerung von virtuellen Biogas-Kraftwerksverbünden für den netzorientierten Betrieb
(2019)
Das Steuerungssystem VKV Netz ermöglicht den auf die Erbringung regionaler Systemdienstleistungen ausgerichteten Betrieb virtueller Biogas-Kraftwerksverbünde. Damit leistet es sowohl einen Beitrag zum zukünftig gesteigerten Bedarf an Regelenergie durch regenerative Kraftwerke als es auch alternative, zukunftsfähige Erlöspotenziale für die zumeist landwirtschaftlichen bzw. landwirtschaftsnahen Biogas-Anlagenbetreiber abseits des EEG aufzeigt. Das Steuerungssystem wurde im Rahmen des BMWi-Verbundforschungsvorhabens VKV Netz (Förderkennzeichen 0325943A) durch die Hochschule Hannover, die SLT-Technologies GmbH & Co. KG sowie die Überlandwerk Leinetal GmbH in Kooperation mit assoziierten Biogasanlagen im Zeitraum 01.01.2016 bis 31.12.2018 entwickelt und pilotiert.
Dieser Beitrag adressiert einleitend die aktuelle Bedrohungslage aus Sicht der Industrie mit einem Fokus auf das Feld und die Feldgeräte. Zentral wird dann die Frage behandelt, welchen Beitrag Feldgeräte im Kontext von hoch vernetzten Produktionsanlagen für die künftige IT-Sicherheit leisten können und müssen. Unter anderem werden auf Basis der bestehenden Standards wie IEC 62443-4-1, IEC 62443-4-2 oder der VDI 2182-1 und VDI 2182-4 ausgewählte Methoden und Maßnahmen am Beispiel eines Durchflussmessgerätes vorgestellt, die zur künftigen Absicherung von Feldgeräten notwendig sind.
Das ProFormA-Aufgabenformat wurde eingeführt, um den Austausch von Programmieraufgaben zwischen beliebigen Autobewertern (Grader) zu ermöglichen. Ein Autobewerter führt im ProFormA-Aufgabenformat spezifizierte „Tests“ sequentiell aus, um ein vom Studierenden eingereichtes Programm zu prüfen. Für die Strukturierung und Darstellung der Testergebnisse existiert derzeit kein graderübergreifender Standard. Wir schlagen eine Erweiterung des ProFormA-Aufgabenformats um eine Hierarchie von Bewertungsaspekten vor, die nach didaktischen Aspekten gruppiert ist und entsprechende Testausführungen referenziert. Die Erweiterung wurde in Graja umgesetzt, einem Autobewerter für Java-Programme. Je nach gewünschter Detaillierung der Bewertungsaspekte sind Testausführungen in Teilausführungen aufzubrechen. Wir illustrieren unseren Vorschlag mit den Testwerkzeugen Compiler, dynamischer Softwaretest, statische Analyse sowie unter Einsatz menschlicher Bewerter.