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Wikidata and Wikibase as complementary research data management services for cultural heritage data
(2022)
The NFDI (German National Research Data Infrastructure) consortia are associations of various institutions within a specific research field, which work together to develop common data infrastructures, guidelines, best practices and tools that conform to the principles of FAIR data. Within the NFDI, a common question is: What is the potential of Wikidata to be used as an application for science and research? In this paper, we address this question by tracing current research usecases and applications for Wikidata, its relation to standalone Wikibase instances, and how the two can function as complementary services to meet a range of research needs. This paper builds on lessons learned through the development of open data projects and software services within the Open Science Lab at TIB, Hannover, in the context of NFDI4Culture – the consortium including participants across the broad spectrum of the digital libraries, archives, and museums field, and the digital humanities.
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%.
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.
We present a novel long short-term memory (LSTM) approach for time-series prediction of the sand demand which arises from preparing the sand moulds for the iron casting process of a foundry. With our approach, we contribute to qualify LSTM and its combination with feedback-corrected optimal scheduling for industrial processes.
The sand is produced in an energy intensive mixing process which is controlled by optimal scheduling. The optimal scheduling is solved for a fixed prediction horizon. One major influencing factor is the sand demand, which is highly disturbed, for example due to production interruptions. The causes of production interruptions are in general physically unknown. We assume that information about the future behavior of the sand demand is included in current and past process data. Therefore, we choose LSTM networks for predicting the time-series of the sand demand.
The sand demand prediction is performed by our multi model approach. This approach outperforms the currently used naive estimation, even when predicting far into the future. Our LSTM based prediction approach can forecast the sand demand with a conformity up to 38 % and a mean value accuracy of approximately 99%. Simulating the optimal scheduling with sand demand prediction leads to an improvement in energy savings of approximately 1.1% compared to the naive estimation. The application of our novel approach at the real production plant of a foundry proves the simulation results and verifies the capability of our approach.
In recent years, multiple efforts for reducing energy usage have been proposed. Especially buildings offer high potentials for energy savings. In this paper, we present a novel approach for intelligent energy control that combines a simple infrastructure using low cost sensors with the reasoning capabilities of Complex Event Processing. The key issues of the approach are a sophisticated semantic domain model and a multi-staged event processing architecture leading to an intelligent, situation-aware energy management system.
With regard to climate change, increasing energy efficiency is still a significant issue in the industry. In order to acquire energy data at the field level, so-called energy profiles can be used. They are advantageous as they are integrated into existing industrial ethernet standards (e.g. PROFINET). Commonly used energy profiles such as PROFIenergy and sercos Energy have been established in industrial use. However, as the Industrial Internet of Things (IIoT) continues to develop, the question arises whether the established energy profiles are sufficient to fullfil the requirements of the upcoming IIoT communication technologies. To answer this question the paper compares and discusses the common energy profiles with the current and future challenges of energy data communication. Furthermore, this analysis examines the need for further research in this field.
Da mit wachsender Verwendung von Kunststoffen für konstruktive Anwendungen deren Klebbarkeit immer größere Bedeutung erhält und Vorbehandlungen mit umweltbelastenden Verfahren nur mit Vorbehalt eigesetzt werden können, dürften umweltfreundliche Verbehandlungen, wie die Vorbehandlung im Niederdruckplasma, im Folgenden kurz NDP-Vorbehandlung genannt, eine steigende Bedeutung erlangen. Die Umweltfreundlichkeit des Verfahrens ist darin begründet, dass keine verbrauchten Beizbäder anfallen, die mit hohem Aufwand beseitigt werden müssen, und dass der Prozess in einem geschlossenem System abläuft und somit ein unkontrolliertes Entweichen von Schadstoffen nicht möglich ist. Bei der Ndp-Behandlung gegebenenfalls entstehende Schadstoffe fallen nur in sehr geringem Umfang an und können leicht abgefangen und nachbehandelt werden. Da die verwendeten Gase nicht giftig sind, geht von ihnen keine Gefährdung aus.
In vielen Fällen muss vor dem Kleben eine Klebflächenbehandlung durchgeführt werden, da Klebverbindungen mit unvorbehandelten Teilen häufig zu geringe Klebfestigkeiten und/oder eine unzureichende Alterungsbeständigkeit aufweisen. Zur Klebflächenbehandlung stehen unterschiedliche Verfahren zur Verfügung. Wenn mit mehreren Behandlungen klebtechnisch einwandfreie Verbindungen hergestellt werden können, gilt es, das Verfahren zu ermitteln, welches am besten in den Fertigungsfluss integriert werden kann und die geringsten Kosten verursacht. Dabei muss auch die Arbeitssicherheit und der Umweltschutz mit beachtet werden. Zur Beurteilung der Verfahren werden Bewertungskriterien gegeben. Die Verfahren werden abschließend kurz charakterisiert.
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.
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.
In this paper the workflow of the project 'Untersuchungs-, Simulations- und Evaluationstool für Urbane Logistik` (USEfUL) is presented. Aiming to create a web-based decision support tool for urban logistics, the project needed to integrate multiple steps into a single workflow, which in turn needed to be executed multiple times. While a service-oriented system could not be created, the principles of service orientation was utilized to increase workflow efficiency and flexibility, allowing the workflow to be easily adapted to new concepts or research areas.
In the area of manufacturing and process automation in industrial applications, technical energy management systems are mainly used to measure, collect, store, analyze and display energy data. In addition, PLC programs on the control level are required to obtain the energy data from the field level. If the measured data is available in a PLC as a raw value, it still has to be processed by the PLC, so that it can be passed on to the higher layers in a suitable format, e.g. via OPC UA. In plants with heterogeneous field device installations, a high engineering effort is required for the creation of corresponding PLC programs. This paper describes a concept for a code generator that can be used to reduce this engineering effort.
An der Fachhochschule Hannover wurde Mitte 2007 das Projekt "Herbar-Digital" gestartet. In dem Forschungsprojekt "Herbar-Digital" sollen aus 3,5 Millionen Papierbögen (Herbarbelege) des Botanischen Museums Berlin möglichst alle Objekte erkannt werden und separat verarbeitbar sein. Bei den Objekten handelt es sich um Barcodes, Tüten, Stempel, Farbtabellen, Elemente aus dem Pflanzenbereich sowie Hand- und Druckschriften. Es soll unter Zuhilfenahme des ADA-BOOST-Algorithmus vom Verfasser eine Objekterkennung realisiert werden, die folgende Eigenschaften aufweist: Position der zu erkennenden Objekte im Bild variabel, auch dreidimensionale - und konturschwache Objekte müssen erkannt werden, gleiche Objekte unterschiedlicher Form müssen erkennbar sein, das System muss lernfähig sein.
The miniaturized Mössbauer-spectrometer (MIMOS II), originally devised by Göstar Klingelhöfer, is further developed by the Renz group at the Leibniz University Hanover in cooperation with the Hanover University of Applied Sciences and Arts. A new processing unit with a two-dimensional (2D) data acquisition was developed by M. Jahns. The advantage of this data acquisition is that no thresholds need to be set before the measurement. The energy of each photon is determined and stored with the velocity of the drive. After the measurement, the relevant area can be selected for the Mössbauer spectrum. Now we have expanded the evaluation unit with a power supply for a MIMOS drive and a MIMOS PIN detector. So we have a very compact MIMOS transmissions measurement setup. With this setup it is possible to process the signals of two detectors serially. Currently we are working on a parallel signal processing.
Das Referat klärt zuerst, was man unter "Didaktik der Pflege" versteht und inwieweit allgemeindidaktische Zielsetzungen eine Bedeutung für die Pflegeausbildung haben. Dann werden wichtige didaktische Kriterien für die Auswahl von Inhalten der Pflegeausbildung erörtert und gleichzeitig werden Fragestellungen für eine zukünftige Pflegedidaktik formuliert.
Operators of production plants are increasingly emphasizing secure communication, including real-time communication, such as PROFINET, within their control systems. This trend is further advanced by standards like IEC 62443, which demand the protection of realtime communication in the field. PROFIBUS and PROFINET International (PI) is working on the specification of the security extensions for PROFINET (“PROFINET Security”), which shall fulfill the requirements of secure communication in the field.
This paper discusses the matter in three parts. First, the roles and responsibilities of the plant owner, the system integrator, and the component provider regarding security, and the basics of the IEC 62443 will be described. Second, a conceptual overview of PROFINET Security, as well as a status update about the PI specification work will be given. Third, the article will describe how PROFINET Security can contribute to the defense-in-depth approach, and what the expected operating environment is. We will evaluate how PROFINET Security contributes to fulfilling the IEC 62443-4-2 standard for automation components.
Two of the authors are members of the PI Working Group CB/PG10 Security.
The impact of vertical and horizontal integration in the context of Industry 4.0 requires new concepts for the security of industrial Ethernet protocols. The defense in depth concept, basing on the combination of several measures, especially separation and segmentation, needs to be complimented by integrated protection measures for industrial real-time protocols. To cover this challenge, existing protocols need to be equipped with additional functionality to ensure the integrity and availability of the network communication, even in environments, where possible attackers can be present. In order to show a possible way to upgrade an existing protocol, this paper describes a security concept for the industrial Ethernet protocol PROFINET.
On November 30th, 2022, OpenAI released the large language model ChatGPT, an extension of GPT-3. The AI chatbot provides real-time communication in response to users’ requests. The quality of ChatGPT’s natural speaking answers marks a major shift in how we will use AI-generated information in our day-to-day lives. For a software engineering student, the use cases for ChatGPT are manifold: assessment preparation, translation, and creation of specified source code, to name a few. It can even handle more complex aspects of scientific writing, such as summarizing literature and paraphrasing text. Hence, this position paper addresses the need for discussion of potential approaches for integrating ChatGPT into higher education. Therefore, we focus on articles that address the effects of ChatGPT on higher education in the areas of software engineering and scientific writing. As ChatGPT was only recently released, there have been no peer-reviewed articles on the subject. Thus, we performed a structured grey literature review using Google Scholar to identify preprints of primary studies. In total, five out of 55 preprints are used for our analysis. Furthermore, we held informal discussions and talks with other lecturers and researchers and took into account the authors’ test results from using ChatGPT. We present five challenges and three opportunities for the higher education context that emerge from the release of ChatGPT. The main contribution of this paper is a proposal for how to integrate ChatGPT into higher education in four main areas.
Social skills are essential for a successful understanding of agile methods in software development. Several studies highlight the opportunities and advantages of integrating real-world projects and problems while collaborating with companies into higher education using agile methods. This integration comes with several opportunities and advantages for both the students and the company. The students are able to interact with real-world software development teams, analyze and understand their challenges and identify possible measures to tackle them. However, the integration of real-world problems and companies is complex and may come with a high effort in terms of coordination and preparation of the course. The challenges related to the interaction and communication with students are increased by virtual distance teaching during the Covid-19 pandemic as direct contact with students is missing. Also, we do not know how problem-based learning in virtual distance teaching is valued by the students. This paper presents our adapted eduScrum approach and learning outcome of integrating experiments with real-world software development teams from two companies into a Master of Science course organized in virtual distance teaching. The evaluation shows that students value analyzing real-world problems using agile methods. They highlight the interaction with real-world software development teams. Also, the students appreciate the organization of the course using an iterative approach with eduScrum. Based on our findings, we present four recommendations for the integration of agile methods and real world problems into higher education in virtual distance teaching settings. The results of our paper contribute to the practitioner and researcher/lecturer community, as we provide valuable insights how to fill the gap between practice and higher education in virtual distance settings.