Informatik
Refine
Year of publication
Document Type
- Conference proceeding (568)
- Journal article (199)
- Book chapter (62)
- Doctoral Thesis (18)
- Book (10)
- Anthology (10)
- Patent / Standard / Guidelines (2)
- Report (2)
- Working Paper (2)
Is part of the Bibliography
- yes (873)
Institute
- Informatik (873)
- Technik (2)
- ESB Business School (1)
Publisher
- Springer (173)
- Hochschule Reutlingen (104)
- IEEE (89)
- Gesellschaft für Informatik (60)
- Elsevier (46)
- ACM (33)
- IARIA (26)
- Springer Gabler (15)
- Association for Information Systems (AIS) (12)
- De Gruyter (12)
- RWTH Aachen (11)
- Università Politecnica delle Marche (11)
- MDPI (10)
- Deutsche Gesellschaft für Computer- und Roboterassistierte Chirurgie e.V. (9)
- SCITEPRESS (8)
- Haufe (7)
- IOS Press (7)
- Emerald (6)
- University of Hawai'i at Manoa (6)
- Association for Computing Machinery (5)
- SPIE (5)
- Fac. of Organization & Informatics, Univ. of Zagreb (4)
- IGI Global (4)
- RWTH (4)
- Springer International Publishing (4)
- University of Hawaii at Manoa (4)
- Universität Tübingen (4)
- American Marketing Association (3)
- Deutsche Gesellschaft für Computer- und Roboterassistierte Chirurgie e. V. (3)
- International Academy of Business Disciplines (3)
- Open Proceedings.org, Univ. of Konstanz (3)
- Riga Technical University Press (3)
- Sage (3)
- Science and Technology Publications (3)
- Springer Science + Business Media B.V (3)
- Springer Science + Business Media B.V. (3)
- University of Konstanz, University Library (3)
- Wiley-Blackwell (3)
- Academic Conferences International (2)
- American Marketing Assoc. (2)
- BioMed Central (2)
- CSW-Verlag (2)
- Curran Associates (2)
- Curran Associates Inc. (2)
- Deutsche Aktuarvereinigung (DAV) e.V. (2)
- EuroMed Press (2)
- GMDS e.V. (2)
- Gabler (2)
- Gesellschaft für Informatik e.V (2)
- HTWG Konstanz (2)
- IADIS (2)
- IADIS Press (2)
- IBM Research Division (2)
- International Association for Development of the Information Society (2)
- International Society for Photogrammetry and Remote Sensing (2)
- PeerJ Ltd. (2)
- Smart Home & Living Baden-Württemberg e.V. (2)
- Springer Vieweg (2)
- Taylor & Francis (2)
- The Association for Computing Machinery, Inc. (2)
- Thieme (2)
- University of Hawaii (2)
- University of the West of Scotland (2)
- Universität Stuttgart (2)
- 3m5.Media GmbH (1)
- AIP Publishing (1)
- ARVO (1)
- Academic Conferences International Limited (1)
- Association for Computing Machinery ACM (1)
- Association of Computing Machinery (1)
- CIDR (1)
- CMP-WEKA-Verlag (1)
- Cambridge University Press (1)
- Circle International (1)
- Copenhagen Business School (1)
- Cornell Universiy (1)
- Cuvillier Verlag (1)
- DIMECC Oy (1)
- DUZ Medienhaus (1)
- Deutsche Gesellschaft für Medizinische Physik (1)
- Deutsche Gesellschaft für die Computer- und Roboterassistierte Chirurgie e.V. (1)
- EDP Sciences (1)
- EMAC (1)
- Ed2.0Work (1)
- Elektronikpraxis, Vogel Business Media GmbH & Co. KG (1)
- EuroMedPress (1)
- Eurographics Association (1)
- Fachausschuß Management der Anwendungsentwicklung und -wartung (1)
- Faculty of Economics (1)
- Faculty of Organization and Informatics, University of Zagreb (1)
- Frontiers Media (1)
- Frontiers Research Foundation (1)
- GBI-Genios (1)
- GITO-Verl. (1)
- German Medical Science Publishing House (1)
- Haufe Group (1)
- Hochschule Heilbronn (1)
- Hochschule der Medien (1)
- IGI Publ. (1)
- IGI Publishing (1)
- IMC Information multimedia communication AG (1)
- Inderscience Publ. (1)
- Inst. of Electrical and Electronics Engineers (1)
- JMIR Publications (1)
- Johannes Kepler University Linz (1)
- Karlsruher Institut für Technologie (1)
- Lund University (1)
- MCB University Press (1)
- MFG Stiftung Baden-Württemberg (1)
- MHP. a Porsche Company (1)
- Morressier (1)
- NextMed (1)
- OpenProceedings (1)
- PLOS (1)
- Pabst Science Publishers (1)
- Pallas Press (1)
- PeerJ (1)
- Riga Technical University (1)
- Routledge, Taylor & Francis Group (1)
- SISSA (1)
- SSRN (1)
- SciKA (1)
- Science and Technology Publications, Lda (1)
- Shaker Verlag (1)
- Society for Science and Education (1)
- Springer Nature (1)
- Springer Science + Business Media (1)
- Technical University (1)
- Technische Universität Darmstadt (1)
- The Association for Computing Machinery (1)
- UVW, Universitätsverlag Verlag Webler (1)
- Univ. de Jaén (1)
- Universidad Carlos III de Madrid (1)
- University of Minho (1)
- University of Portsmouth (1)
- University of Zagreb Faculty of Organization and Informatics (1)
- Universität Leipzig (1)
- Universität Trier (1)
- Universität des Saarlandes (1)
- Univerzita Tomáe Bati (1)
- Wiley (1)
- World Scientific (1)
- World Scientific Publishing (1)
- de Gruyter (1)
- dpunkt-Verlag (1)
- libreriauniversitaria.it.edizioni (1)
- vwh (1)
In this paper a method for the generation of gSPM with ontology-based generalization was presented. The resulting gSPM was modeled with BPMN/BPMNsix in an efficient way and could be executed with BPMN workflow engines. In the next step the implementation of resource concepts, anatomical structures, and transition probabilities for workflow execution will be realized.
Development work within an experimental environment, in which certain properties are investigated and optimized, requires many test runs and is therefore often associated with long execution times, costs and risks. This can affect product, material and technology development in industry and research. New digital driver technologies offer the possibility to automate complex manual work steps in a cost-effective way, to increase the relevance of the results and to accelerate the processes many times over. In this context, this article presents a low-cost, modular and open-source machine vision system for test execution and evaluates it on the basis of a real industrial application. For this purpose a methodology for the automated execution of the load intervals, the process documentation and for the evaluation of the generated data by means of machine learning to classify wear levels. The software and the mechanical structure are designed to be adaptable to different conditions, components and for a variety of tasks in industry and research. The mechanical structure is required for tracking the test object and represents a motion platform with independent positioning by machine vision operators or machine learning. An evaluation of the state of the test object is performed by the transfer learning after the initial documentation run. The manual procedure for classifying the visually recorded data on the state of the test object is described for the training material. This leads to an increased resource efficiency on the material as well as on the personnel side since on the one hand the significance of the tests performed is increased by the continuous documentation and on the other hand the responsible experts can be assigned time efficiently. The presence and know-how of the experts are therefore only required for defined and decisive events during the execution of the experiments. Furthermore, the generated data are suitable for later use as an additional source of data for predictive maintenance of the developed object.
Literature reviews are essential for any scientific work, both as part of a dissertation or as a stand-alone work. Scientists benefit from the fact that more and more literature is available in electronic form, and finding and accessing relevant literature has become more accessible through scientific databases. However, a traditional literature review method is characterized by a highly manual process, while technologies and methods in big data, machine learning, and text mining have advanced. Especially in areas where research streams are rapidly evolving, and topics are becoming more comprehensive, complex, and heterogeneous, it is challenging to provide a holistic overview and identify research gaps manually. Therefore, we have developed a framework that supports the traditional approach of conducting a literature review using machine learning and text mining methods. The framework is particularly suitable in cases where a large amount of literature is available, and a holistic understanding of the research area is needed. The framework consists of several steps in which the critical mind of the scientist is supported by machine learning. The unstructured text data is transformed into a structured form through data preparation realized with text mining, making it applicable for various machine learning techniques. A concrete example in the field of smart cities makes the framework tangible.
The character of knowledge-intense processes is that participants decide the next process activities on base of the present information and their expert knowledge. The decisions of these knowledge workers are in general non-deterministic. It is not possible to model these processes in advance and to automate them using a process engine of a BPM system. Hence, in this context a process instance is called a case, because there is no predefined model that could be instantiated. Domain-specific or general case management systems are used to support the knowledge workers. These systems provide all case information and enable users to define the next activities, but they have no or only limited activity recommendation capabilities. In the following paper, we present a general concept for a self-learning system based on process mining that suggests the next best activity on quantitative and qualitative data for a given case. As a proof of concept, it was applied to the area of insurance claims settlement.
Knowledge transfer is very important to our knowledge-based society and many approaches have been proposed to describe this transfer. However, these approaches take a rather abstract view on knowledge transfer, which makes implementation difficult. In order to address this issue, we introduce a layered model for knowledge transfer that structures the individual steps of knowledge transfer in more detail. This paper gives a description of the process and also an example of the application of the layered model for knowledge transfer. The example is located in the area of business process modelling. Business processes contain the important knowledge describing the procedures of the company to produce products and services. Knowledge transfer is the fundamental basis in the modelling and usage of Business processes, which makes it an interesting use case for the layered model for knowledge transfer.
Enterprises and societies currently face essential challenges, and digital transformation can contribute to their resolution. Enterprise architecture (EA) is useful for promoting digital transformation in global companies and information societies covering ecosystem partners. The advancement of new business models can be promoted with digital platforms and architectures for Industry 4.0 and Society 5.0. Therefore, products from the sector of healthcare, manufacturing and energy, etc. can increase in value. The adaptive integrated digital architecture framework (AIDAF) for Industry 4.0 and the design thinking approach is expected to promote and implement the digital platforms and digital products for healthcare, manufacturing and energy communities more efficiently. In this paper, we propose various cases of digital transformation where digital platforms and products are designed and evaluated for digital IT, digital manufacturing and digital healthcare with Industry 4.0 and Society 5.0. The vision of AIDAF applications to perform digital transformation in global companies is explained and referenced, extended toward the digitalized ecosystems such as Society 5.0 and Industry 4.0.
Enterprises and societies currently face crucial challenges, while Industry 4.0 becomes important in the global manufacturing industry all the more. Industry 4.0 offers a range of opportunities for companies to increase the flexibility and efficiency of production processes. The development of new business models can be promoted with digital platforms and architectures for Industry 4.0. Therefore, products from the healthcare sector can increase in value. The adaptive integrated digital architecture framework (AIDAF) for Industry 4.0 is expected to promote and implement the digital platforms and robotics for healthcare and medical communities efficiently. In this paper, we propose that various digital platforms and robotics are designed and evaluated for digital healthcare as for manufacturing industry with Industry 4.0. We argue that the design of an open healthcare platform “Open Healthcare Platform 2030 - OHP2030” for medical product design and robotics can be developed with AIDAF. The vision of AIDAF applications to enable Industry 4.0 in the OHP2030 research initiative is explained and referenced, extended in the context of Society 5.0.
The evolution of Services Oriented Architectures (SOA) presents many challenges due to their complex, dynamic and heterogeneous nature. We describe how SOA design principles can facilitate SOA evolvability and examine several approaches to support SOA evolution. SOA evolution approaches can be classified based on the level of granularity they address, namely, service code level, service interaction level and model level. We also discuss emerging trends, such as microservices and knowledge-based support, which can enhance the evolution of future SOA systems.
Enterprises are currently transforming their strategy, processes, and their information systems to extend their degree of digitalization. The potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, artificial intelligence, big data with analytics, mobile systems, collaboration networks, and cyber physical systems both drives and enables new business designs. Digitalization deeply disrupts existing businesses, technologies and economies and fosters the architecture of digital environments with many rather small and distributed structures. This has a strong impact for new value producing opportunities and architecting digital services and products guiding their design through exploiting a Service-Dominant Logic. The main result of the book chapter extends methods for integral digital strategies with value-oriented models for digital products and services which are defined in the framework of a multi-perspective digital enterprise architecture reference model.
Our paper gives first answers on a fundamental question: how can the design of architectures of intelligent digital systems and services be accomplished methodologically? Intelligent systems and services are the goals of many current digitalization efforts today and part of massive digital transformation efforts based on digital technologies. Digital systems and services are the foundation of digital platforms and ecosystems. Digtalization disrupts existing businesses, technologies, and economies and promotes the architecture of open environments. This has a strong impact on new value-added opportunities and the development of intelligent digital systems and services. Digital technologies such as artificial intelligence, the Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, and social enterprise networks systems are important enablers of digitalization. The current publication presents our research on the architecture of intelligent digital ecosystems and products and services influenced by the service-dominant logic. We present original methodological extensions and a new reference model for digital architectures with an integral service and value perspective to model intelligent systems and services that effectively align digital strategies and architectures with artificial intelligence as main elements to support intelligent digitalization.
The current advancement of Artificial Intelligence (AI) combined with other digitalization efforts significantly impacts service ecosystems. Artificial intelligence has a substantial impact on new opportunities for the co-creation of value and the development of intelligent service ecosystems. Motivated by experiences and observations from digitalization projects, this paper presents new methodological perspectives and experiences from academia and practice on architecting intelligent service ecosystems and explores the impact of artificial intelligence through real cases supporting an ongoing validation. Digital enterprise architecture models serve as an integral representation of business, information, and technological perspectives of intelligent service-based enterprise systems to support management and development. This paper focuses on architectural models for intelligent service ecosystems, showing the fundamental business mechanism of AI-based value co-creation, the corresponding digital architecture, and management models. The focus of this paper presents the key architectural model perspectives for the development of intelligent service ecosystems.
Presently, many companies are transforming their strategy and product base, as well as their culture, processes and information systems to become more digital or to approach for a digital leadership. In the last years new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, edge and fog computing, social networks, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, Microservices, or other micro-granular elements. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of micro-granular system architectures defines the moving context for adaptable systems. We are focusing on a continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, as part of a new digital enterprise architecture for service dominant digital products.
This chapter presents an introduction to the emerging trends for architecting the digital transformation having a strong focus on digital products, intelligent services, and related systems together with methods, models and architectures. The primary aim of this book is to highlight some of the most recent research results in the field. We are providing a focused set of brief descriptions of the chapters included in the book.
This research-oriented book presents key contributions on architecting the digital transformation. It includes the following main sections covering 20 chapters: · Digital Transformation · Digital Business · Digital Architecture · Decision Support · Digital Applications Focusing on digital architectures for smart digital products and services, it is a valuable resource for researchers, doctoral students, postgraduates, graduates, undergraduates, academics and practitioners interested in digital transformation.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. The Internet of Things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud services environments are emerging to support smart connected products and services and the digital transformation. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self-optimizing and resilient run-time environments for intelligent business services and service-oriented enterprise architectures. Our aim is to support flexibility and agile transformations for both business domains and related information technology. The present research paper investigates mechanisms for decision analytics in the context of multi-perspective explorations of enterprise services and their digital enterprise architectures by extending original architecture reference models with state of art elements for agile architectural engineering for the digitization and collaborative architectural decision support. The paper’s context focuses on digital transformations of business and IT and integrates fundamental mappings between adaptable digital enterprise architectures and service-oriented information systems. We are putting a spotlight on the example domain – Internet of Things.
Dieses forschungsorientierte Buch enthält wichtige Beiträge zur Gestaltung der digitalen Transformation. Es umfasst die folgenden Hauptabschnitte in 20 Kapiteln:
- Digitale Transformation
- Digitales Geschäft
- Digitale Architektur
- Entscheidungshilfe
- Digitale Anwendungen
Es konzentriert sich auf digitale Architekturen für intelligente digitale Produkte und Dienstleistungen und ist eine wertvolle Ressource für Forscher, Doktoranden, Postgraduierte, Absolventen, Studenten, Akademiker und Praktiker, die sich für die digitale Transformation interessieren.
Unternehmen sind derzeit dabei, ihre Strategie, ihre Prozesse und ihre Informationssysteme zu verändern, um ihren Digitalisierungsgrad zu erhöhen. Das Potenzial des Internets und verwandter digitaler Technologien wie Internet der Dinge, Services Computing, Cloud Computing, künstliche Intelligenz, Big Data mit Analysen, mobile Systeme, Kollaborationsnetzwerke und cyber-physikalische Systeme treibt neue Geschäftsmodelle an und ermöglicht sie. Die Digitalisierung führt zu einer tiefgreifenden Umwälzung bestehender Unternehmen, Technologien und Volkswirtschaften und fördert die Architektur digitaler Umgebungen mit vielen eher kleinen und verteilten Strukturen. Dies hat starke Auswirkungen auf neue Wertschöpfungsmöglichkeiten und die Gestaltung digitaler Dienste und Produkte, die durch die Nutzung einer service-dominanten Logik gesteuert werden. Das Hauptergebnis des Buchkapitels erweitert Methoden für integrale digitale Strategien um wertorientierte Modelle für digitale Produkte und Dienstleistungen, die im Rahmen eines multiperspektivischen digitalen Unternehmensarchitektur-Referenzmodells definiert werden.
Artefaktkorrektur und verfeinerte Metriken für ein EEG-basiertes System zur Müdigkeitserkennung
(2019)
Fragestellung: Müdigkeit ist ein oft unterschätztes, aber dennoch großes Problem im Straßenverkehr. Von rund 2,5 Mio. Verkehrsunfällen 2015 in Deutschland, waren 2898 Unfälle, mit insgesamt 59 Toten (~1,7 % der Todesfälle), auf Übermüdung zurückzuführen. Schätzungen gehen von einer Dunkelziffer von bis zu 20 % aus. In einer ersten eigenen Studie wurde überprüft, ob ein mobiles EEG in einem Fahrsimulator Müdigkeitszustände zuverlässig erkennen kann. Die Erkennungsrate lag lediglich bei 61 %. Ziel dieser Arbeit ist, das verwendete Messsystem zu verbessern. Dazu wird die Genauigkeit durch eine Artefaktkorrektur und mit Hilfe von verfeinerten Qualitätsmetriken erhöht. Eine erkannte Übermüdung wird dem Fahrer dann in angemessener Weise angezeigt, so dass er entsprechend reagieren kann.
Patienten und Methoden: Die Independent Component Analysis (ICA) ist ein multivariates Verfahren, um mehrere Zufallsvariablen zu analysieren. Für die Entscheidung, ob ein Fahrer gerade müde oder wach ist, wird der erstellte Merkmalsvektor für jede Sequenz mit ICA klassifiziert. Dafür wird ein trainierter Machine-Learning-Algorithmus eingesetzt, der in der Lage ist, auch unbekannte Datensätze in Klassen einzuteilen. Um die benötigten Frequenzwerte zu erhalten, wurde für jeden EEG-Kanal eine Fourier Transformation durchgeführt. Der erstellte Merkmalsvektor wird im nächsten Schritt durch ein Künstliches Neuronales Netz klassifiziert. Für das Training werden vorab erstellte Merkmalsvektoren mit den Klassen „Wach“ und „Müde“ versehen. Diese Daten werden zufällig gemischt und im Verhältnis 2:1 in eine Trainings- und Testmenge geteilt. Das Experiment wurde mit acht Personen mit jeweils zweimal 45 min Testfahrt durchgeführt.
Ergebnisse: Der komplette Datensatz besteht aus 150.000 Signalwerten, welche zu ca. 7000 Sequenzen zusammengefasst werden. Durch die Anwendung der Qualitätsmetrik bleiben 4370 Sequenzen für das Training übrig. Bei invaliden Sequenzen aufgrund von EEG-Artefakten gibt es deutliche Unterschiede. Im „Wach“ Zustand werden dreimal so viele Sequenzen verworfen als im „Müde“ Zustand. Insgesamt werden bei wachen Probanden im Schnitt ca. 50 % der Sequenzen verworfen, bei Müden lediglich 25 %. Im Durchschnitt erreicht das System eine Erkennungsrate von 73 % für beide Zustände. Vergleicht man nun das Verhältnis von „Wach“ und „Müde“ und lässt „Leichte Müdigkeit“ außen vor, liegen die Ergebnisse bei über 90 %.
Schlussfolgerungen: Die Ergebnisse zeigen, dass die Aufmerksamkeit während des Experiments abnimmt bzw. die Müdigkeit zunimmt. Dies verdeutlichen zum einen subjektive und objektive Beobachtungen von Müdigkeitsanzeichen. Zum anderen lassen sich messbare und klassifizierbare Unterschiede im EEG Signal nachweisen. Die als Merkmale eingesetzten Theta-Wellen zeigten eine niedrigere Amplitude gegen Ende des Experiments. Die Erweiterung der binären Klassifizierung führt zu einer weiteren Stabilisierung der Ergebnisse. Artefaktkorrektur und Qualitätsmetriken steigern die Güte der Daten weiter. Die entwickelte Anwendung zur Müdigkeitserkennung ermittelt messbare Zeichen von Müdigkeit und kann eine gute Entscheidung über die Fahrtauglichkeit treffen.
Painting galleries typically provide a wealth of data composed of several data types. Those multivariate data are too complex for laymen like museum visitors to first, get an overview about all paintings and to look for specific categories. Finally, the goal is to guide the visitor to a specific painting that he wishes to have a more closer look on. In this paper we describe an interactive visualization tool that first provides such an overview and lets people experiment with the more than 41,000 paintings collected in the web gallery of art. To generate such an interactive tool, our technique is composed of different steps like data handling, algorithmic transformations, visualizations, interactions, and the human user working with the tool with the goal to detect insights in the provided data. We illustrate the usefulness of the visualization tool by applying it to such characteristic data and show how one can get from an overview about all paintings to specific paintings.
New storage technologies, such as Flash and Non- Volatile Memories, with fundamentally different properties are appearing. Leveraging their performance and endurance requires a redesign of existing architecture and algorithms in modern high performance databases. Multi-Version Concurrency Control (MVCC) approaches in database systems, maintain multiple timestamped versions of a tuple. Once a transaction reads a tuple the database system tracks and returns the respective version eliminating lock-requests. Hence under MVCC reads are never blocked, which leverages well the excellent read performance (high throughput, low latency) of new storage technologies. Upon tuple updates, however, established implementations of MVCC approaches (such as Snapshot Isolation) lead to multiple random writes – caused by (i) creation of the new and (ii) in-place invalidation of the old version – thus generating suboptimal access patterns for the new storage media. The combination of an append based storage manager operating with tuple granularity and snapshot isolation addresses asymmetry and in-place updates. In this paper, we highlight novel aspects of log-based storage, in multi-version database systems on new storage media. We claim that multi-versioning and append-based storage can be used to effectively address asymmetry and endurance. We identify multi-versioning as the approach to address dataplacement in complex memory hierarchies. We focus on: version handling, (physical) version placement, compression and collocation of tuple versions on Flash storage and in complex memory hierarchies. We identify possible read- and cacherelated optimizations.
In order to ensure sufficient recovery of the human body and brain, healthy sleep is indispensable. For this purpose, appropriate therapy should be initiated at an early stage in the case of sleep disorders. For some sleep disorders (e.g., insomnia), a sleep diary is essential for diagnosis and therapy monitoring. However, subjective measurement with a sleep diary has several disadvantages, requiring regular action from the user and leading to decreased comfort and potential data loss. To automate sleep monitoring and increase user comfort, one could consider replacing a sleep diary with an automatic measurement, such as a smartwatch, which would not disturb sleep. To obtain accurate results on the evaluation of the possibility of such a replacement, a field study was conducted with a total of 166 overnight recordings, followed by an analysis of the results. In this evaluation, objective sleep measurement with a Samsung Galaxy Watch 4 was compared to a subjective approach with a sleep diary, which is a standard method in sleep medicine. The focus was on comparing four relevant sleep characteristics: falling asleep time, waking up time, total sleep time (TST), and sleep efficiency (SE). After evaluating the results, it was concluded that a smartwatch could replace subjective measurement to determine falling asleep and waking up time, considering some level of inaccuracy. In the case of SE, substitution was also proved to be possible. However, some individual recordings showed a higher discrepancy in results between the two approaches. For its part, the evaluation of the TST measurement currently does not allow us to recommend substituting the measurement method for this sleep parameter. The appropriateness of replacing sleep diary measurement with a smartwatch depends on the acceptable levels of discrepancy. We propose four levels of similarity of results, defining ranges of absolute differences between objective and subjective measurements. By considering the values in the provided table and knowing the required accuracy, it is possible to determine the suitability of substitution in each individual case. The introduction of a “similarity level” parameter increases the adaptability and reusability of study findings in individual practical cases.
Physicians in interventional radiology are exposed to high physical stress. To avoid negative long-term effects resulting from unergonomic working conditions, we demonstrated the feasibility of a system that gives feedback about unergonomic
situations arising during the intervention based on the Azure Kinect camera. The overall feasibility of the approach could be shown.
The influence of sleep on human health is enormous. Accordingly, sleep disorders can have a negative impact on it. To avoid this, they should be identified and treated in time. For this purpose, objective (with an appropriate device) or subjective (based on perceived values) measurement methods are used for sleep analysis to understand the problem. The aim of this work is to find out whether an exchange of the two methods is possible and can provide reliable results. In accordance with this goal, a study was conducted with people aged over 65 years old (a total of 154 night-time recordings) in which both measurement methods were compared. Sleep questionnaires and electronic devices for sleep assessment placed under the mattress were applied to achieve the study aims. The obtained results indicated that the correlation between both measurement methods could be observed for sleep characteristics such as total sleep time, total time in bed and sleep efficiency. However, there are also significant differences in absolute values of the two measurement approaches for some subjects/nights, which leads us to conclude that the substitution is more likely to be considered in case of long-term monitoring where the trends are of more importance and not the absolute values for individual nights.
Assistant platforms
(2023)
Many assistant systems have evolved toward assistant platforms. These platforms combine a range of resources from various actors via a declarative and generative interface. Among the examples are voice-oriented assistant platforms like Alexa and Siri, as well as text-oriented assistant platforms like ChatGPT and Bard. They have emerged as valuable tools for handling tasks without requiring deeper domain expertise and have received large attention with the present advances in generative artificial intelligence. In view of their growing popularity, this Fundamental outlines the key characteristics and capabilities that define assistant platforms. The former comprise a multi-platform architecture, a declarative interface, and a multi-platform ecosystem, while the latter include capabilities for composition, integration, prediction, and generativity. Based on this framework, a research agenda is proposed along the capabilities and affordances for assistant platforms.
Home health applications have evolved over the last few decades. Assistive systems such as a data platform in connection with health devices can allow for health-related data to be automatically transmitted to a database. However, there remain significant challenges concerning intermodular communication. Central among them is the challenge of achieving interoperability, the ability of devices to communicate and share data with each other. A major goal of this project was to extend an existing data platform (COMES®) and establish working interoperability by connecting assistive devices with differing approaches. We describe this process for a sleep monitoring and a physical exercise device. Furthermore, we aimed to test this setup and the implementation with a data platform in both a laboratory and an in-home setting with 11 elderly participants. The platform modification was realized, and the relevant changes were made so that the incoming data could be processed by the data platform, as well as visually displayed in real-time. Data was recorded by the respective device and transmitted into the data server with minor disruptions. Our observations affirmed that difficulties and data loss are far more likely to occur with increasing technical complexity, in the event of instable internet connection, or when the device setup requires (elderly) subjects to take specific steps for proper functioning. We emphasize the importance for tests and evaluations of home health technologies in real-life circumstances.
While Microservices promise several beneficial characteristics for sustainable long-term software evolution, little empirical research covers what concrete activities industry applies for the evolvability assurance of Microservices and how technical debt is handled in such systems. Since insights into the current state of practice are very important for researchers, we performed a qualitative interview study to explore applied evolvability assurance processes, the usage of tools, metrics, and patterns, as well as participants’ reflections on the topic. In 17 semi-structured interviews, we discussed 14 different Microservice-based systems with software professionals from 10 companies and how the sustainable evolution of these systems was ensured. Interview transcripts were analyzed with a detailed coding system and the constant comparison method.
We found that especially systems for external customers relied on central governance for the assurance. Participants saw guidelines like architectural principles as important to ensure a base consistency for evolvability. Interviewees also valued manual activities like code review, even though automation and tool support was described as very important. Source code quality was the primary target for the usage of tools and metrics. Despite most reported issues being related to Architectural Technical Debt (ATD), our participants did not apply any architectural or service-oriented tools and metrics. While participants generally saw their Microservices as evolvable, service cutting and finding an appropriate service granularity with low coupling and high cohesion were reported as challenging. Future Microservices research in the areas of evolution and technical debt should take these findings and industry sentiments into account.
In mehreren Untersuchungen hat sich gezeigt, dass sich die Wahrnehmung des eigenen Körpers in einer virtuellen Umgebung positiv auf die Wahrnehmung der gesamten Umgebung auswirkt. Für diese Untersuchungen wurden der Körper einer Person, oder Teile davon, als animierter Avatar aus der Ego-Perspektive dargestellt. Im Kontext der Informatikkonferenz Informatics Inside 2014 an der Hochschule Reutlingen soll in dieser Arbeit eine andere Möglichkeit der Darstellung untersucht werden. In einer prototypischen Augmented Virtuality Anwendung soll die virtuelle Umgebung um reale Inhalte erweitert werden. Es soll einer Person ermöglicht werden, Teile ihres eigenen Körpers nicht als Avatar, sondern auf Basis einer Kameraaufnahme als realistische Repräsentation wahrzunehmen. Die Arbeit beschreibt hierbei die gesetzten Ziele, sowie Aufbau und Funktionsweise der prototypischen Anwendung und deren derzeitigen Stand.
The state of the art proposes the microservices architectural style to build applications. Additionally, container virtualization and container management systems evolved into the perfect fit for developing, deploying, and operating microservices in line with the DevOps paradigm. Container virtualization facilitates deployment by ensuring independence from the runtime environment. However, microservices store their configuration in the environment. Therefore, software developers have to wire their microservice implementation with technologies provided by the target runtime environment such as configuration stores and service registries. These technological dependencies counteract the portability benefit of using container virtualization. In this paper, we present AUTOGENIC - a model-based approach to assist software developers in building microservices as self configuring containers without being bound to operational technologies. We provide developers with a simple configuration model to specify configuration operations of containers and automatically generate a self-configuring microservice tailored for the targeted runtime environment. Our approach is supported by a method, which describes the steps to automate the generation of self-configuring microservices. Additionally, we present and evaluate a prototype, which leverages the emerging TOSCA standard.
Data collected from internet applications are mainly stored in the form of transactions. All transactions of one user form a sequence, which shows the user´s behaviour on the site. Nowadays, it is important to be able to classify the behaviour in real time for various reasons: e.g. to increase conversion rate of customers while they are in the store or to prevent fraudulent transactions before they are placed. However, this is difficult due to the complex structure of the data sequences (i.e. a mix of categorical and continuous data types, constant data updates) and the large amounts of data that are stored. Therefore, this thesis studies the classification of complex data sequences. It surveys the fields of time series analysis (temporal data mining), sequence data mining or standard classification algorithms. It turns out that these algorithms are either difficult to be applied on data sequences or do not deliver a classification: Time series need a predefined model and are not able to handle complex data types; sequence classification algorithms such as the apriori algorithm family are not able to utilize the time aspect of the data. The strengths and weaknesses of the candidate algorithms are identified and used to build a new approach to solve the problem of classification of complex data sequences. The problem is thereby solved by a two-step process. First, feature construction is used to create and discover suitable features in a training phase. Then, the blueprints of the discovered features are used in a formula during the classification phase to perform the real time classification. The features are constructed by combining and aggregating the original data over the span of the sequence including the elapsed time by using a calculated time axis. Additionally, a combination of features and feature selection are used to simplify complex data types. This allows catching behavioural patterns that occur in the course of time. This new proposed approach combines techniques from several research fields. Part of the algorithm originates from the field of feature construction and is used to reveal behaviour over time and express this behaviour in the form of features. A combination of the features is used to highlight relations between them. The blueprints of these features can then be used to achieve classification in real time on an incoming data stream. An automated framework is presented that allows the features to adapt iteratively to a change in underlying patterns in the data stream. This core feature of the presented work is achieved by separating the feature application step from the computational costly feature construction step and by iteratively restarting the feature construction step on the new incoming data. The algorithm and the corresponding models are described in detail as well as applied to three case studies (customer churn prediction, bot detection in computer games, credit card fraud detection). The case studies show that the proposed algorithm is able to find distinctive information in data sequences and use it effectively for classification tasks. The promising results indicate that the suggested approach can be applied to a wide range of other application areas that incorporate data sequences.
The recent years and especially the Internet have changed the ways in which data is stored. It is now common to store data in the form of transactions, together with ist creation time-stamp. These transactions can often be attributed to Logical units, e.g., all transactions that belong to one customer. These groups, we refer to them as data sequences, have a more complex structure than tuple-based data. This makes it more difficult to find discriminatory patterns for classification purposes. However, the complex structure potentially enables us to track behaviour and its change over the course of time. This is quite interesting, especially in the e-commerce area, in which classification of a sequence of customer actions is still a challenging task for data miners. However, before standard algorithms such as Decision Trees, Neural Nets, Naive Bayes or Bayesian Belief Networks can be applied on sequential data, preparations are required in order to capture the information stored within the sequences. Therefore, this work presents a systematic approach on how to reveal sequence patterns among data and how to construct powerful features out of the primitive sequence attributes. This is achieved by sequence aggregation and the incorporation of time dimension into the feature construction step. The proposed algorithm is described in detail and applied on a real-life data set, which demonstrates the ability of the proposed algorithm to boost the classification performance of well-known data mining algorithms for binary classification tasks.
Automatic anode rod inspection in aluminum smelters using deep-learning techniques: a case study
(2020)
Automatic fault detection using machine learning has become an exciting and promising area of research. This because it accurate and timely way to manage and classify with minimal human effort. In the computer vision community, deep-learning methods have become the most suitable approaches for this task. Anodes are large carbon blocks that are used to conduct electricity during the aluminum reduction process. The most basic function of anode rod inspection is to prevent a situation where the anode rod will not fit into the stub-holes of a new anode. It would be the case for a rod containing either severe toe-in, missing stubs, or a retained thimble on one or more stubs. In this work, to improve the accuracy of shape defect inspection for an anode rod, we use the Fast Region-based Convolutional Network method (Fast R-CNN), model. To train the detection model, we collect an image dataset composed of multi-class of anode rod defects with annotated labels. Our model is trained using a small number of samples, an essential requirement in the industry where the number of available defective samples is limited. It can simultaneously detect multi-class of defects of the anode rod in nearly real-time.
Automatic classification of rotating machinery defects using Machine Learning (ML) algorithms
(2020)
Electric machines and motors have been the subject of enormous development. New concepts in design and control allow expanding their applications in different fields. The vast amount of data have been collected almost in any domain of interest. They can be static; that is to say, they represent real-world processes at a fixed point of time. Vibration analysis and vibration monitoring, including how to detect and monitor anomalies in vibration data are widely used techniques for predictive maintenance in high-speed rotating machines. However, accurately identifying the presence of a bearing fault can be challenging in practice, especially when the failure is still at its incipient stage, and the signal-to-noise ratio of the monitored signal is small. The main objective of this work is to design a system that will analyze the vibration signals of a rotating machine, based on recorded data from sensors, in the time/frequency domain. As a consequence of such substantial interest, there has been a dramatic increase of interest in applying Machine Learning (ML) algorithms to this task. An ML system will be used to classify and detect abnormal behavior and recognize the different levels of machine operation modes. The proposed solution can be deployed as predictive maintenance for Industry 4.0.
Checklists are a valuable tool to ensure process quality and quality of care. To ensure proper integration in clinical processes, it would be desirable to generate checklists directly from formal process descriptions. Those checklists could also be used for user interaction in context-aware surgical assist systems. We built a tool to automatically convert Business Process Model and Notation (BPMN) process models to checklists displayed as HTML websites. Gateways representing decisions are mapped to checklist items that trigger dynamic content loading based on the placed checkmark. The usability of the resulting system was positively evaluated regarding comprehensibility and end-user friendliness.
In a time of digital transformation, the ability to quickly and efficiently adapt software systems to changed business requirements becomes more important than ever. Measuring the maintainability of software is therefore crucial for the long-term management of such products. With service-based systems (SBSs) being a very important form of enterprise software, we present a holistic overview of such metrics specifically designed for this type of system, since traditional metrics – e.g. object oriented ones – are not fully applicable in this case. The selected metric candidates from the literature review were mapped to 4 dominant design properties: size, complexity, coupling, and cohesion. Microservice-based systems (μSBSs) emerge as an agile and fine grained variant of SBSs. While the majority of identified metrics are also applicable to this specialization (with some limitations), the large number of services in combination with technological heterogeneity and decentralization of control significantly impacts automatic metric collection in such a system. Our research therefore suggests that specialized tool support is required to guarantee the practical applicability of the presented metrics to μSBSs.
Das Provisioning Tool automaIT wurde prototypisch um die Möglichkeit eines Data Discovery erweitert, mit dem Ziel, nicht durch automaIT verwaltete Systeme anbinden und steuern zu können. Daten aus dem Data Discovery werden mittels dem Tool Facter gesammelt und können dynamisch in ausführbare Modelle von automaIT integriert und ausgewertet werden. Dadurch kann der Verlauf weiterer Provisionierungsschritte gesteuert werden, ohne dass es eines manuellen Eingriffs bedarf.
Virtual Reality (VR) technology has the potential to support knowledge communication in several sectors. Still, when educators make use of immersive VR technology in favor of presenting their knowledge, their audience within the same room may not be able to see them anymore due to wearing head-mounted displays (HMDs). In this paper, we propose the Avatar2Avatar system and design, which augments the visual aspect during such a knowledge presentation. Avatar2Avatar enables users to see both a realistic representation of their respective counterpart and the virtual environment at the same time. We point out several design aspects of such a system and address design challenges and possibilities that arose during implementation. We specifically explore opportunities of a system design for integrating 2D video-avatars in existing roomscale VR setups. An additional user study indicates a positive impact concerning spatial presence when using Avatar2Avatar.
Back to the future: origins and directions of the “Agile Manifesto” – views of the originators
(2018)
In 2001, seventeen professionals set up the manifesto for agile software development. They wanted to define values and basic principles for better software development. On top of brought into focus, the manifesto has been widely adopted by developers, in software-developing organizations and outside the world of IT. Agile principles and their implementation in practice have paved the way for radical new and innovative ways of software and product development. In parallel, the understanding of the manifesto’s underlying principles evolved over time. This, in turn, may affect current and future applications of agile principles. This article presents results from a survey and an interview study in collaboration with the original contributors of the manifesto for agile software development. Furthermore, it comprises the results from a workshop with one of the original authors. This publication focuses on the origins of the manifesto, the contributors’ views from today’s perspective, and their outlook on future directions. We evaluated 11 responses from the survey and 14 interviews to understand the viewpoint of the contributors. They emphasize that agile methods need to be carefully selected and agile should not be seen as a silver bullet. They underline the importance of considering the variety of different practices and methods that had an influence on the manifesto. Furthermore, they mention that people should question their current understanding of "agile" and recommend reconsidering the core ideas of the manifesto.
Bausparverträge sind kombinierte Spar- und Finanzierungsinstrumente, die für die breite Bevölkerung ausgelegt sind. Im Jahr 2020 umfasste der Bestand an Bausparverträgen in Deutschland ca. 25 Mio. Verträge. Ein wesentlicher Teil der Attraktivität des Bausparvertrags für Kunden liegt in der hohen Flexibilität dieser Finanzprodukte, die im Vertragsablauf eine flexible Anpassung an individuelle Finanzierungsbedingungen ermöglicht. In der Sparphase sind das insbesondere Möglichkeiten zur Erhöhung, Ermäßigung und Teilung der Verträge sowie zur relativ flexiblen Anpassung der Sparrate. Bei einem zuteilungsreifen Vertrag kann die Sparphase innerhalb bestimmter zeitlicher Grenzen fortgesetzt werden. In der Darlehensphase sind flexible Sondertilgungen jederzeit und ohne Vorfälligkeitsentschädigung möglich.
Die Vielzahl eingebetteter Optionen beeinflussen sich wechselseitig und müssen in ihrer Wirkungsweise immer gesamthaft betrachtet und gesteuert werden. Die empirische Erfahrung der letzten Jahrzehnte zeigt bezüglich der Optionsausübung ein Kundenverhalten, das sich zwar an finanzmathematischen Überlegungen orientiert, aber nicht vollständig finanzrational abläuft.
Excellence in IT is a key enabler for the digital transformation of enterprises. To realize the vision of digital enterprises it is necessary to cope with changing business requirements and to align business and IT. In order to evaluate the contribution of enterprise architecture management to these goals, our paper explores the impact of various factors to the perceived benefit of EAM in enterprises. Based on literature, we build an empirical research model. It is tested with empirical data of European EAM experts using a structural equation modelling approach. It is shown that changing business requirements, IT business alignment, the complexity of information technology infrastructure as well as enterprise architecture knowledge of information technology employees are crucial impact factors to the perceived benefit of EAM in enterprises.
In Zusammenarbeit mit dem Medizinproduktehersteller ulrich medical wird eine User Experience und Usability Studie an der Software der im Moment eingesetzten Kontrastmittelinjektoren durchgeführt. Das Unternehmen möchte eine neue Variante eines Kontrastmittelinjektors entwickeln, der als Basis eine verbesserte Version dieser Softwares enthält. Benutzerstudien können mit den unterschiedlichsten Methoden durchgeführt werden. Das geeignete Vorgehen muss definiert und die Testpersonen in Bezug zur eingesetzten Methode ermittelt werden. Bei Medizinprodukten muss zusätzlich auf strikte Auflagen in Normen und Gesetzen geachtet werden. Die Grundlage zur Methodenauswahl bildet eine Recherche zu Usability und User Experience Vorgaben für Medizinprodukte. Die Studie wird anhand quantitativer Daten eines Usability Tests im Labor, Fragebögen zur User Experience und qualitativen Post Test- Interviews evaluiert. In erster Linie dient diese Studie der Ermittlung von möglichen Verbesserungen, welche in der darauf folgenden Masterthesis vertieft und umgesetzt werden.
This paper contributes to the automatic detection of perioperative workflow by developing a binary endoscope localization. Automated situation recognition in the context of an intelligent operating room requires the automatic conversion of low level cues into more abstract high level information. Imagery from a laparoscope delivers rich content that is easy to obtain but hard to process. We introduce a system which detects if the endoscope's distal tip is inside or outsiede the patient based on the endoscope video. This information can be used as one parameter in a situation recognition pipeline. Our localization performs in real-time at a video resolution of 1280x720 and 5-fold cross validation yields mean F1-scores of up to 0,94 on videos of 7 laparoscopies.
Sowohl bei den industriellen als auch wissenschaftlichen Institutionen nimmt die Anwendung der additiven Fertigung stetig zu und ist insbesondere in den Bereichen der Prototypenentwicklung nicht mehr wegzudenken. Die werkzeuglose Herstellung von Teilen ermöglicht eine dynamische Nutzung der Produktionsressourcen bis unmittelbar zum Fertigungsstart. Dies erlaubt, einerseits in den Bereichen der Feinterminierung und Ablaufplanung, agil auf Veränderungen zu reagieren und andererseits Modelle unterschiedlicher Fertigungsaufträge miteinander zu kombinieren, um somit eine hohe Effizienz der Fertigungsanlagen zu erreichen. Bei der Nutzung von multiplen Anlagen in einem Unternehmen oder im Partnerverbund stellt die vorhandene Intransparenz Unternehmen und Unternehmensnetzwerke vor viele Herausforderungen. Die Blockchain Technologie ermöglicht eine gemeinsame Datenbasis zwischen den Teilnehmern. Die Einträge werden protokolliert und die Authentizität der Teilnehmer wird gewährleistet. Dies führt, im Falle der Beziehung zwischen Kunden und Produzenten, zu einer nachprüfbaren Zusammenarbeit, da Unternehmen Dienstleistungsverträge abschließen, die auf dem Fluss vieler kleiner Transaktionen basieren. In diesem Beitrag wird dargestellt, wie verfügbare additive Fertigungsressourcen erkannt werden, sowie, unter der Verwendung der Blockchain-Technologie, in einem dezentralen Produktionsnetzwerk angeboten und von unterschiedlichen Akteuren genutzt werden können.
Background: One of the most promising health care development areas is introducing telemedicine services and creating solutions based on blockchain technology. The study of systems combining both these domains indicates the ongoing expansion of digital technologies in this market segment.
Objective: This paper aims to review the feasibility of blockchain technology for telemedicine.
Methods: The authors identified relevant studies via systematic searches of databases including PubMed, Scopus, Web of Science, IEEE Xplore, and Google Scholar. The suitability of each for inclusion in this review was assessed independently. Owing to the lack of publications, available blockchain-based tokens were discovered via conventional web search engines (Google, Yahoo, and Yandex).
Results: Of the 40 discovered projects, only 18 met the selection criteria. The 5 most prevalent features of the available solutions (N=18) were medical data access (14/18, 78%), medical service processing (14/18, 78%), diagnostic support (10/18, 56%), payment transactions (10/18, 56%), and fundraising for telemedical instrument development (5/18, 28%).
Conclusions: These different features (eg, medical data access, medical service processing, epidemiology reporting, diagnostic support, and treatment support) allow us to discuss the possibilities for integration of blockchain technology into telemedicine and health care on different levels. In this area, a wide range of tasks can be identified that could be accomplished based on digital technologies using blockchains.
We introduce bloomRF as a unified method for approximate membership testing that supports both point- and range-queries. As a first core idea, bloomRF introduces novel prefix hashing to efficiently encode range information in the hash-code of the key itself. As a second key concept, bloomRF proposes novel piecewisemonotone hash-functions that preserve local order and support fast range-lookups with fewer memory accesses. bloomRF has near-optimal space complexity and constant query complexity. Although, bloomRF is designed for integer domains, it supports floating-points, and can serve as a multi-attribute filter. The evaluation in RocksDB and in a standalone library shows that it is more efficient and outperforms existing point-range-filters by up to 4× across a range of settings and distributions, while keeping the false-positive rate low.
Enterprise Architecture (EA) management is an activity that seeks to foster the alignment of business and IT, and pursues various goals further operationalizing this alignment. Key to effective EA management is a framework that defines the roles, activities, and viewpoints used for EA management in accordance to the concerns that the stakeholders aim to address. Consensus holds that such frameworks are organization-specific and hence they are designed in governance activities for EA management. As of today, top-down approaches for governance are used to derive organization-specific frameworks. These usually lack systematic mechanisms for improving the framework based on the feedback of the responsible stakeholders. We outline a bottom-up approach for EA management governance that systematically observes the behavior of the actors to learn user concerns and recommend appropriate viewpoints. With this approach, we complement traditional top-down governance activities.
This paper investigates the impact of dynamic capabilities (DC) on brand love. From a resource-based view, there is little clarity vis-à-vis the specific capabilities that drive the ability to create brand love. This paper focuses on three research questions: Firstly, which dynamic capabilities are relevant for brand love? Secondly, how strong is the impact of certain dynamic capabilities on brand love? Thirdly, which conditions mediate and moderate the impact of specific dynamic capabilities on brand love? Data from a multi-method research approach have been used to itentify the specific capabilities that corporations need, to enhance brand love. Furthermore, a standardized online survey was conducted on marketing executives and evaluated by structural equation modeling. The results indicate, that customer expertise plays a major role in the relationship between dynamic capabilities and brand love. Furthermore, this relationship is more important in markets that have a low competitive differentiation in products and services.
The energy turnaround, digitalization and decreasing revenues forces enterprises in the energy domain to develop new business models. Following a Design Science Research approach, we showed in two action research projects that businesses models in the energy domain result in complex ecosystems with multiple actors. Additionally, we identified that municipal utilities have problems with the systematic development of business models. In order to solve the problem, we captured together with the partners of the enterprises the requirements in a second phase. Further we developed a method which consist of the following components: Method for the creative development of a new business model in form of a Business Model Canvas (BMC). A mapping between the e3Value ontology and the BMC for modelling a business ecosystem. The Business Model Configurator (BMConfig) prototype for modelling and simulating the e3Value-Ontology. The Business model can be quantified and analyzed for its viability. We demonstrate the feasibility of our approach in business model of a power community.