004 Informatik
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Rapid Prototyping Plattformen reduzieren die Entwicklungszeit, indem das Überprüfen einer Idee in Form eines Prototyps schnell umzusetzen ist und mehr Zeit für die eigentliche Anwendungsentwicklung mit Benutzerschnittstellen zur Verfügung steht. Dieser Ansatz wird schon lange bei technischen Plattformen, wie bspw. dem Arduino, verfolgt. Um diese Form von Prototyping auf Wearables zu übertragen, wird in diesem Paper WearIT vorgestellt. WearIT besteht als Wearable Prototyping Plattform aus vier Komponenten: Einer Weste, Sensor- und Aktorshieldss, einer eigenen bibliothek sowie einem Mainboard bestehend aus Arduino, Raspberry Pi, einer Steckplatine und einem GPS-Modul. Als Ergebnis kann ein Wearable Prototyp schnell, durch das Anbringen von Sensor- und Aktorshields an der WearIT Weste, entwickelt werden. Diese Sensor- und Aktorshields können anschließend durch die WearIT-Bibliothek programmiert werden. Dafür kann über Virtual Network Computing (VNC) mit einem entfernten Rechner auf die Bildschirminhalte des Rasperry Pis zugegriffen und der Arduino programmiert werden.
Enterprises and societies currently face crucial challenges, while Society 5.0 can contribute to a supersmart society, especially for manufacturing and healthcare, and Industry 4.0 becomes important in the global manufacturing industry. Smart energy digital platforms are architected to manage energy supply efficiently. Furthermore, the above digital platforms are expected to collect various kinds of data and analyze Big Data for the trends in the sharing economy in ecosystems. The adaptive integrated digital architecture framework (AIDAF) for Design Thinking Approach with Risk Management is expected to make an alignment with digital IT strategy. In this paper, we propose that various energy management systems and related digital platforms are designed and implemented in an alignment to digital IT strategy for sharing economy toward Society 5.0, with the AIDAF framework for Design Thinking Approach with Risk Management. The vision of AIDAF applications to enable sharing economy and digital platforms is explained and extended in the context of Society 5.0. In addition, challenges and future activities for this area are discussed that cover the directions of smart energy for Society 5.0.
Im Rahmen dieser Arbeit wurde ein urbaner Mixed-Reality Fahrsimulator umgesetzt. Die reale Umgebung wird hierbei in einer Greenscreen-Kammer mit Hilfe von Kamerabildern aus Nutzersicht und einem Chroma Key Shader innerhalb der virtuellen Umgebung sichtbar gemacht. Dies soll die Immersion und die Interaktivität innerhalb der virtuellen Umgebung durch die Darstellung und Verwendung von realen Elementen erhöhen.
Als virtuelle Umgebung wurde eine zufallsgenerierte Stadt geschaffen, in der KI-Fahrzeuge fahren. Die Ergebnisse der Entwicklung dieses Fahrsimulators werden in dieser Arbeit erläutert.
Der Fahrsimulator soll der Entwicklung von menschzentrierten Human-Machine-Interfaces und Motion-Capture-Komponenten dienen.
Intermittent time series forecasting is a challenging task which still needs particular attention of researchers. The more unregularly events occur, the more difficult is it to predict them. With Croston’s approach in 1972 (1.Nr. 3:289–303), intermittence and demand of a time series were investigated the first time separately. He proposes an exponential smoothing in his attempt to generate a forecast which corresponds to the demand per period in average. Although this algorithm produces good results in the field of stock control, it does not capture the typical characteristics of intermittent time series within the final prediction. In this paper, we investigate a time series’ intermittence and demand individually, forecast the upcoming demand value and inter-demand interval length using recent machine learning algorithms, such as long-short-term-memories and light-gradient-boosting machines, and reassemble both information to generate a prediction which preserves the characteristics of an intermittent time series. We compare the results against Croston’s approach, as well as recent forecast procedures where no split is performed.
Automatisierte Analyse von Review-Daten beschäftigt sich mit den Möglichkeiten, freien Text zu analysieren und relevante Informationen daraus zu extrahieren. Die Arbeit setzt sich dabei mit Methoden des unüberwachten Lernens auseinander. Hierbei steht die Methode der Topic Modellierung im Mittelpunkt. Es werden Verfahren betrachtet, die im Bereich der textbasierten Informationsgewinnung bekannt sind. Latent Semantic Indexing LSI, (probabilistic) pLSI und Latent Dirichlet Allocation (LDA) werden erläutert und verglichen. Die Arbeit zeigt, wie LDA genutzt wurde, um einen nhaltlichen Überblick über einen Datenkorpus von 1 Mio. Reviews zu bekommen und diesen auf einen feineren Detailgrad zu betrachten. Die Topic-basierte Analyse wird genutzt, um Erkentnisse für ein Opinion Mining System zu generieren, welches eine tiefergehende Analyse vornehmen wird. Der gesamte Prozess ist als vollständig automatisiert und maschinell unüberwacht konzeptioniert.
Theoretical foundation, effectiveness, and design artefact for machine learning service repositories
(2022)
Machine learning (ML) has played an important role in research in recent years. For companies that want to use ML, finding the algorithms and models that fit for their business is tedious. A review of the available literature on this problem indicates only a few research papers. Given this gap, the aim of this paper is to design an effective and easy-to-use ML service repository. The corresponding research is based on a multi-vocal literature analysis combined with design science research, addressing three research questions: (1) How is current white and gray literature on ML services structured with respect to repositories? (2) Which features are relevant for an effective ML service repository? (3) How is a prototype for an effective ML service repository conceptualized? Findings are relevant for the explanation of user acceptance of ML repositories. This is essential for corporate practice in order to create and use ML repositories effectively.
Study programs in higher education have to reflect important societal and industrial challenges to prepare the next generations of professionals for future tasks. The focus of this paper is the challenge of digitalization and digital transformation. The paper proposes the IS education profile of a Digital Business Architect (DBA). The study program emphasizes design thinking, model centricity, and capability thinking as a response to domain requirements from digital transformation and educational system and structure requirements. Experiences in implementing the DBA include the need for integrating deductive and inductive teaching, a strong basis in real-world cases, and collaborative learning approaches to develop adequate competences in business model management, enterprise modeling, enterprise architecture management, and capability management.
With significant advancements in digital technologies, firms find themselves competing in an increasingly dynamic business environment. Therefore, the logic of business decisions is based on the agility to respond to emerging trends in a proactive way. By contrast, traditional IT governance (ITG) frameworks rely on hierarchy and standardized mechanisms to ensure better business/IT alignment. This conflict leads to a call for an ambidextrous governance, in which firms alternate between stability and agility in their ITG mechanisms. Accordingly, this research aims to explore how agility might be integrated in ITG. A quantitative research strategy is implemented to explore the impact of agility on the causal relationship among ITG, business/IT alignment, and firm performance. The results show that the integration of agile ITG mechanisms contributes significantly to the explanation of business/IT alignment. As such, firms need to develop a dual governance model powered by traditional and agile ITG mechanisms.
What might the attendee be able to do after being in your session?
Our work shows how to connect intra-operative devices via IEEE 11073 Service-oriented Device Connectivity (SDC).
Description of the Problem or Gap
Standardized device communication is essential for interoperability, availability of device data, and therefore for the intelligent operating room (OR) and arising solutions. The SDC standard was developed to make information from medical devices available in a uniform manner and enable interoperability. Existing devices are rarely SDC-capable and need interfaces to be interoperable via SDC.
Methods: What did you do to address the problem or gap?
We conceived an SDC-based architecture consisting of a service provider and service consumer. In our concept, the service provider is connected to the medical device and capable to translate the proprietary protocol of the device into SDC and vice versa. The service consumer is used to request or send information via the SDC protocol to the service provider and can function as a uniform bidirectional interface (e.g. for displaying or controlling). This concept was exemplarily demonstrated with the patient monitor MX800 of Philips to retrieve the device data (e.g. vital parameters) via SDC and partly for the operating light marLED X of KLS Martin Group.
Results: What was the outcome(s) of what you did to address the problem or gap?
The patient monitor MX800 was connected to a Raspberry Pi (RPi) via LAN, on which the service provider is running. The python script on the RPi establishes a connection to the monitor and translates incoming and outgoing messages from the proprietary protocol to SDC and vice versa to/from the service consumer. The service consumer is running on a laptop and acts as a simulation for different kinds of systems that want to get vital parameters or other information from the patient monitor. The operating light marLED X was connected to an RPi via USB-to-RS232. A python script on the RPi establishes a connection to the light and makes it possible via proprietary commands to get information of the light (e.g. status) and to control it (e.g. toggle the light, increment the intensity). A translation to SDC is not integrated yet.
Discussion of Results
Our practical implementation shows that medical devices can be accessed via external connections to get device data and control the device via commands. The example SDC implementation of the patient monitor MX800 makes it possible to request its data via the standardized communication protocol SDC. This is also possible for the operating light marLED X if its proprietary protocol is analyzed to be translatable to/from SDC. This would allow to control the device from an external system, or automatically depending on the status of the ongoing procedure. The advantage is, that existing intra-operative devices can be extended by a service provider which is capable of translating the proprietary protocol of the device in SDC and vice versa. This enables interoperability and an intelligent OR that, for example, is aware of all devices, their status, and data and can use this information to optimally support the surgeons and their team (e.g. provision of information, automated documentation). This interoperability allows that future innovations merely need to understand the SDC protocol instead of all vendor-dependent communication protocols.
Conclusion
Standardized device communication is essential to reach interoperability, and therefore intelligent ORs. Our contribution addresses the possibility of subsequently making medical devices SDC-capable. This may eliminate the need of understanding all the different proprietary protocols when developing new innovative solutions for the OR.
Rotating machinery occupies a predominant place in many industrial applications. However, rotating machines are often encountered with severe vibration problems. The measurement of these machines’ vibrations signal is of particular importance since it plays a crucial role in predictive maintenance. When the vibrations are too high, they often cause fatigue failure. They announce an unexpected stop or break and, consequently, a significant loss of productivity or an attack on the personnel’s safety. Therefore, fault identification at early stages will significantly enhance the machine’s health and significantly reduce maintenance costs. Although considerable efforts have been made to master the field of machine diagnostics, the usual signal processing methods still present several drawbacks. This paper examines the rotating machinery condition monitoring in the time and frequency domains. It also provides a framework for the diagnosis process based on machine learning by analyzing the vibratory signals.