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Henning Eichinger beschäftigt sich seit dem Jahr 2000 in seiner künstlerischen Arbeit mit den scheinbaren Gegensätzen von Kunst und Wissenschaft. Als Gewinner des Kunstpreises des Fabry-Museums im Jahre 2000 stieß er auf den berühmten Wundarzt und Begründer der modernen Chirurgie in Deutschland, Wilhelm Fabry, der im Jahr 1560 in Hilden geboren wurde. In Fabrys Überzeugung, dass der Mediziner sowohl aufmerksam beobachten als auch handwerklich geschickt sein müsse, sah Eichinger eine Parallele zum künstlerischen Arbeiten. "Diese Gemeinsamkeiten haben mich dazu bewegt, die vergangene Welt des Arztes Fabry im Kontext zeitgenössischer Kunst zu betrachten und zu visualisieren", erklärt Eichinger.
In seinen künstlerischen Arbeiten thematisiert Eichinger Fragen wie: Ist unser Körper nicht längst zum Objekt, ja zum Accessoire geworden, welches wir mit viel Geld und medizinischem Aufwand verändern können? Wer liefert die Vorgaben für die ästhetische Veränderung des menschlichen Körpers? Und was ist mit der Einheit von Körper und Geist?
A fast way to test business ideas and to explore customer problems and needs is to talk to them. Customer interviews help to understand what solutions customers will pay for before investing valuable resources to develop solutions. Customer interviews are a good way to gain qualitative insights. However, conducting interviews can be a difficult procedure and requires specific skills. The current ways of teaching interview skills have significant deficiencies. They especially lack guidance and opportunities to practice. Objective: The goal of this work is to develop and validate a workshop format to teach interview skills for conducting good customer interviews in a practical manner. Method: The research method is based on design science research which serves as a framework. A game-based workshop format was designed to teach interview skills. The approach consists of a half-day, hands-on workshop and is based on an analysis of necessary interview skills. The approach has been validated in several workshops and improved based on learnings from those workshops. Results: Results of the validation show that participants could significantly improve their interview skills while enjoying the game-based exercises. The game-based learning approach supports learning and practicing customer interview skills with playful and interactive elements that encourage greater motivation among participants to conduct interviews.
We analyze economics PhDs’ collaborations in peer-reviewed journals from 1990 to 2014 and investigate such collaborations’ quality in relation to each co-author’s research quality, field and specialization. We find that a greater overlap between co-authors’ previous research fields is significantly related to a greater publication success of co-authors’ joint work and this is robust to alternative specifications. Co-authors that engage in a distant collaboration are significantly more likely to have a large research overlap, but this significance is lost when co-authors’ social networks are accounted for. High quality collaboration is more likely to emerge as a result of an interaction between specialists and generalists with overlapping fields of expertise. Regarding interactions across subfields of economics (interdisciplinarity), it is more likely conducted by co- authors who already have interdisciplinary portfolios, than by co-authors who are specialized or starred in different subfields.
Chinas Subsahara-Afrika-Engagement : Chancen und Herausforderungen für die bayerische Wirtschaft
(2022)
Afrika ist ein attraktiver Markt, auch für bayerische Unternehmen
Die Studie zeigt die Attraktivität der Zukunftsmärkte in Subsahara-Afrika für die bayerische Wirtschaft auf. Trotz einiger Herausforderungen und aktuell noch kleinen, aber profitablen Märkten sind viele Länder der Region aufgrund ihrer enormen Wachstumsdynamik grundsätzlich attraktiv für ein geschäftliches Engagement.
Auch die Volksrepublik China hat die Bedeutung Afrikas erkannt und ist seit dem Jahr 2000 verstärkt politisch und wirtschaftlich in Afrika aktiv. Die Initiativen im Rahmen des Forum on China and African Cooperation (FOCAC) und der Belt and Road Initiative bewegten chinesische Firmen seit 2013 zu einem verstärkten Afrikaengagement, das häufig durch massive Subventionierung und politische Flankierung begleitet wird. Im Infrastrukturbereich dominieren inzwischen chinesische Unternehmen. Das sollte von nicht-chinesischen Unternehmen akzeptiert werden. Die letzte FOCAC-Konferenz in Dakar im Jahr 2021 zeigte allerdings einen deutlichen Rückgang der Kredit- und Finanzierungszusagen, was sowohl durch statistische Daten, die einen Rückgang der Finanzierungsflüsse seit 2016 verzeichnen, als auch durch die Experteninterviews bestätigt wurde.
Ein Umgang mit dem chinesischen Wettbewerb sowie Ansatzpunkte für Geschäftsbeziehungen müssen gefunden werden. Auf Basis von Experteninterviews analysiert die Studie die vielschichtigen Implikationen und Handlungsoptionen der bayerischen Wirtschaft in Subsahara-Afrika vor dem Hintergrund der chinesischen Wirtschaftspräsenz. Bei der Analyse wird grundsätzlich differenziert, ob die chinesischen Firmen Wettbewerber oder Kunden bzw. potenzielle Partner sind.
– Auf der einen Seite sind chinesische Firmen oftmals Wettbewerber. Gerade bei Infrastrukturprojekten haben sie Wettbewerbsvorteile durch den niedrigen Preis und die günstige Finanzierung, die häufig von chinesischen Banken wie der Exim-Bank bereitgestellt wird. Gleichzeitig werden die Kredite der chinesischen Banken ohne komplexe Bedingungen für die afrikanischen Regierungen bzw. Auftraggeber vergeben. Neben diesen Wettbewerbsvorteilen wurden auch Wettbewerbsnachteile identifiziert. So offenbaren Infrastrukturprojekte und chinesische Produkte häufig eine niedrige Qualität, was bei großen Infrastrukturprojekten oft ein Resultat des niedrigen Preises ist. Außerdem bieten chinesische Unternehmen nach wie vor wenige After Sales Dienstleistungen an.
– Auf der anderen Seite können chinesische Unternehmen auch Kunden und Partner bayerischer Unternehmen sein. Im Ausschreibungsgeschäft, vor allem im Infrastrukturbereich, sind die Gewinn-Chancen nicht-chinesischer Firmen maßgeblich von der Quelle der Finanzierung abhängig. Sofern China die Finanzierung bereitstellt, finden sich allenfalls Einzelfälle von Zulieferungen durch nicht-chinesische Firmen. Bei den internationalen Ausschreibungen durch die African Development Bank oder Weltbank stehen die Chancen für nicht-chinesische Firmen gut, wenn in den Entscheidungskriterien die Qualität stärker als der Preis gewichtet wird. Die besten Chancen ergeben sich durch europäische Entwicklungsbanken bzw. bei privatwirtschaftlicher Finanzierung. Daher ist es für den Geschäftserfolg wichtig, die richtigen Ausschreibungen und Finanzierungsquellen auszuwählen.
Für den vertrieblichen Erfolg beim Geschäft mit chinesischen Unternehmen in Subsahara-Afrika sollte idealerweise ein Ansatz auf vier Ebenen verfolgt werden.
– Zum einen ist eine Unternehmenspräsenz in China bei den Firmenzentralen wichtig, da dort in den meisten Fällen die Beschaffung für Projekte in Subsahara-Afrika erfolgt. Deshalb sollten bayerische Unternehmen, wenn sie in China vor Ort sind, das Afrikageschäft mit chinesischen Partnern in Gesprächen mitberücksichtigen. Dabei hilft eine eigene Tochtergesellschaft in China oder regelmäßige Besuche des Top-Managements bei bestehenden und potenziellen Partnern.
– Zum anderen ist eine Vor-Ort-Präsenz in den wichtigsten Märkten Subsahara-Afrikas aus mehreren Gründen von Vorteil. Erstens, um mit den örtlichen Niederlassungen chinesischer Baufirmen zusammenzuarbeiten.
– Zweitens bietet die Präsenz in den afrikanischen Märkten die Möglichkeit, die afrikanischen Auftraggeber – zumeist staatliche Institutionen – von den Vorteilen eines bayerischen bzw. deutschen Projektanteils zu überzeugen.
– Drittens können lokal ansässige, chinesische Händler durch eine lokale Präsenz besser von bayerischen Unternehmen adressiert werden.
Im operativen Geschäft in den Märkten Subsahara-Afrikas sollten idealerweise Mitarbeiter mit Chinaerfahrung und chinesischen Sprachkenntnissen den Vertrieb bei den chinesischen Firmen und Partnern bestreiten. Es sollten auch die entsprechenden Kommunikationsmittel, wie WeChat, verwendet werden. Zudem ist es von großer Bedeutung, ein Vertrauensverhältnis zu den chinesischen Firmen aufzubauen. Dies steigert die Chancen auf weitere geschäftliche Beziehungen.
Zusammenfassend lässt sich sagen, dass die Präsenz der chinesischen Firmen zu Herausforderungen für das Afrikageschäft bayerischer Unternehmen führt. Gleichzeitig eröffnen sich aber auch Geschäftspotenziale. Es ist wichtig – je nach Branche und Set-Up des Unternehmens – die erwähnten Erfolgsfaktoren zu berücksichtigen. Dann bestehen durchaus Geschäftsmöglichkeiten – sei es im Wettbewerb mit den chinesischen Unternehmen oder als Partner und Lieferant der chinesischen Firmen.
The 17 SDGs, as agreed upon by the international community, are designed to be implemented across all levels of human activity. Alongside the level of international politics, this also includes the local levels, national politics, wider society, and the economic sphere. Many channels are called on to further implementation, including the transfer of technology to developing and emerging countries. As the patent holders, this must include the active participation of companies. While the literature examines the important role of technology transfer in North-South business-to-business (B2B) partnerships, studies on the technology transfer between European and African companies are scarce. Therefore, in this study we use original data from 26 interviews conducted with managers engaged in sales partnerships between German manufacturers and their distributors in African markets to examine the existence and forms of technology transfer. We find that training and marketing excellence are the predominant forms of technology transfer and based on that suggest a refinement of established frameworks on B2B technology transfer.
In 2015, the United Nations adopted the Sustainable Development Goals (SDGs), a collection of 17 global objectives to promote economic, social and ecological development in all parts of the world. While the academic discussion on the contribution of companies to the Sustainable Development Goals has recently gained momentum, the role of business-to-business (B2B) partnerships in reaching the SDGs is underexplored, particularly when it comes to North-South relationships. With our research, we aim to fill this gap in the literature by investigating sales partnerships between German manufacturers and their distributors in African markets. Based on a qualitative analysis of 28 interviews with managers of German and African companies, we show that long-term partnerships and job creation, technology transfer, training as well as high standards are significant contributions of companies to achieve the SDGs. While several SDGs such as goals 4,6,13,16 and 17 are addressed by B2B partnership, we also discuss approaches on how the firms’ engagement could be further leveraged and expanded.
Das Buch untersucht die Umsetzung der Seidenstraßeninitiative (BRI) in Ostafrika. Die BRI gilt als das zentrale geopolitische und geoökonomische Vorhaben Chinas in der Ära von Präsident Xi Jinping. Durch die Arbeit soll ein Beitrag zur Schließung einiger Forschungslücken geleistet werden, etwa die mangelnde Tiefe von Untersuchungen einzelner BRI-Projekte und die Unterberücksichtigung von Verarbeitungsnarrativen in den teilnehmenden Ländern. Die Leitfrage ist, inwiefern die BRI ein politisches bzw. hegemoniales Projekt des von der KPCh gelenkten Staats-Zivilgesellschafts-Komplexes in Ostafrika ist. Zu deren Beantwortung werden Datenbanken internationaler Organisationen und Policy-Dokumente ausgewertet. Außerdem führt der Verfasser eine qualitative Inhaltsanalyse von Zeitungsartikeln lokaler Medienhäuser in den Ländern Äthiopien, Kenia und Tansania durch, um drei Infrastrukturprojekte zu untersuchen. Die Arbeit verdeutlicht, dass die BRI zur Steigerung der Konnektivität in Ostafrika beiträgt. Gleichzeitig führen die Verdichtung der ökonomischen Beziehungen und die Implementierung der Infrastrukturvorhaben in Ostafrika zu zahlreichen Konsequenzen und konturieren ein hegemoniales Projekt.
This book examines the implementation of the Belt and Road Initiative (BRI) in East Africa. The BRI is considered China's central geopolitical and geo-economic project in the era of President Xi Jinping. Through this work, the author aims to contribute to filling some research gaps, such as the lack of depth in studies of individual BRI projects and the underconsideration of processing narratives in participating countries. The guiding question is the extent to which the BRI is a political or hegemonic project of the CCP-directed state-civil society complex in East Africa. To answer these questions, databases of international organizations and policy documents are analyzed. In addition, the author conducts a qualitative content analysis of newspaper articles from local media houses in the countries of Ethiopia, Kenya, and Tanzania to examine three infrastructure projects. The work illustrates that the BRI contributes to increasing connectivity in East Africa. At the same time, the compression of economic relations and the implementation of infrastructure projects in East Africa lead to numerous consequences and contour a hegemonic project.
The Belt and Road Initiative (BRI) has reinforced China’s business engagement in Sub-Saharan Africa (SSA). While previous international business research focused on the internationalization and investments of Chinese companies, this viewpoint uncovers how both local African and international non-Chinese Small and Medium Sized Enterprises (SMEs) may benefit from and participate in the BRI. A focus is laid on the infrastructure sector accounting for the highest investments since the inception of the BRI in 2013. In a conceptual way, the motives of SMEs to participate in infrastructure project business in the context of the BRI are explored. Investigating the challenges of two large transport infrastructure projects, the business potentials for SMEs become visible. It is argued that SMEs find business potentials particularly as investors, sub-contractors and project management experts in the BRI in Sub-Saharan Africa.
Tech hubs (THs) and cognate structures are nowadays ubiquitous in the innovation ecosystem of Sub-Saharan African (SSA) countries. However, the concept of THs is fuzzy due to the lack of a clear and universally accepted definition. This ambiguity is further compounded by the diverse range of organizations that self-identify as hubs, or are categorized as such by others. As a result, research on THs in SSA remained limited. Against the backdrop of established research on the interconnectedness of technology, innovation and entrepreneurship in different organizational forms, this paper is meant to provide fresh insights into the study of THs in SSA. To advance future research, first, it reveals what is special about THs in SSA and how they are related to existing concepts. I particularly argue that they contour a fourth-wave model of incubation. Second, four main categories are unfolded to delineate THs in SSA which is the cornerstone for future research.
Radiofrequency ablation is an ablation technique to treat tumors with focused heat. Computer tomography, ultrasound and magnetic resonance imaging (MRI) are imaging modalities which can be used for image-guided procedures. MRI offers several advantages in comparison to the other imaging modalities, such as radiation-free fluoroscopic imaging, temperature mapping, a high-soft-tissue contrast and free selection of imaging planes. This work addresses the application of 3Dcontrollers for controlling interventional, fluoroscopic MR sequences at the scenario of MR guided radiofrequency ablation of hepatic malignancies. During this procedure, the interventionalist can monitor the targeting of the tumor with near-real time fluoroscopic sequences. In general, adjustments of the imaging planes are necessary during tumor targeting, which is performed by an assistant in the control room. Therefore, communication between the interventionalist in the scanner room and the assistant in the control room is essential. However, verbal communication is impaired due to the loud scanning noises. Alternatively, non-verbal communication between the two persons is possible, however limited to a few gestures and susceptible to misunderstandings. This work is analyzing different 3D-controllers to enable control of interventional MR sequences during MR-guided procedures directly by the interventionalist. Leap Motion, Wii Remote, SpaceNavigator, Phantom Omni and Foot Switch were selected. For that a simulation was built in C++ with VTK to feign the real scenario for test purposes. Previous results showed that Leap Motion is not suitable for the application while Wii Remote and Foot Switch are possible input devices. Final evaluation showed a generally time reduction with the use of 3D-controllers. Best results were reached with Wii Remote in 34 seconds. Handholding input devices like Wii Remote have further potential to integrate them in real environment to reduce intervention time.
Die Arbeit stellt die Möglichkeiten von 3D-Controllern für den Einsatz in der interventionellen Radiologie und insbesondere für die Steuerung der Echtzeit-Magnetresonanztomographie (MRT) dar. Dies ist interessant in Bezug auf die kontrollierte Navigation in ein Zielgewebe. Dabei kann der Interventionalist durch Echtzeit- Bildgebung den Verlauf des Eingriffs verfolgen, allerdings kann er bisher das MRT während der Durchführung des Eingriffs nicht selbst steuern, da dies durch den Assistenten im Nebenraum erfolgt. Die Kommunikation ist bei dem hohen Geräuschpegel aber sehr schwer. Diese Arbeit setzt an dieser Stelle an und analysiert 3D-Controller auf die Eignung für die Echtzeit-Steuerung eines MRTs. Dabei wurden trackingbasierte und trackinglose Geräte betrachtet. Als Ergebnis ließ sich festhalten, dass trackingbasierte Verfahren weniger geeignet sind, aufgrund der nicht ausreichenden Interpretation der Eingaben. Die trackinglosen Geräte hingegen sind aufgrund der korrekten Interpretation aller Eingaben und der intuitiven Bedienung geeignet.
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.
Excellence in IT is both a driver and a key enabler of the digital transformation. The digital transformation changes the way we live, work, learn, communicate, and collaborate. The Internet of Things (IoT) fundamentally influences today’s digital strategies with disruptive business operating models and fast changing markets. New business information systems are integrating emerging Internet of Things infrastructures and components. With the huge diversity of Internet of Things technologies and products organizations have to leverage and extend previous Enterprise Architecture efforts to enable business value by integrating Internet of Things architectures. Both architecture engineering and management of current information systems and business models are complex and currently integrating beside the Internet of Things synergistic subjects, like Enterprise Architecture in context with services & cloud computing, semantic-based decision support through ontologies and knowledge-based systems, big data management, as well as mobility and collaboration networks. To provide adequate decision support for complex business/IT environments, we have to make transparent the impact of business and IT changes over the integral landscape of affected architectural capabilities, like directly and transitively impacted IoT-objects, business categories, processes, applications, services, platforms and infrastructures. The paper describes a new metamodel-based approach for integrating Internet of Things architectural objects, which are semi-automatically federated into a holistic Digital Enterprise Architecture environment.
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.
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.
Platforms and their surrounding ecosystems are becoming increasingly important components of many companies' strategies. Artificial Intelligence, in particular, has created new opportunities to create and develop ecosystems around the platform. However, there is not yet a methodology to systematically develop these new opportunities for enterprise development strategy. Therefore, this paper aims to lay a foundation for the conceptualization of Artificial Intelligence-based service ecosystems exploiting a Service-Dominant Logic. The basis for conceptualization is the study of value creation and particularly effective network effects. This research investigates the fundamental idea of extending specific digital concepts considering the influence of Artificial Intelligence on the design of intelligent services, along with their architecture of digital platforms and ecosystems, to enable a smooth evolutionary path and adaptability for human-centric collaborative systems and services. The paper explores an extended digital enterprise conceptual model through a combined, iterative, and permanent task of co-creating value between humans and intelligent systems as part of a new idea of cognitively adapted intelligent services.
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.
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.
The Internet of Things (IoT) fundamentally influences today’s digital strategies with disruptive business operating models and fast changing markets. New business information systems are integrating emerging Internet of Things infrastructures and components. With the huge diversity of Internet of Things technologies and products organizations have to leverage and extend previous enterprise architecture efforts to enable business value by integrating the Internet of Things into their evolving Enterprise Architecture Management environments. Both architecture engineering and management of current enterprise architectures is complex and has to integrate beside the Internet of Things synergistic disciplines like EAM - Enterprise Architecture and Management with disciplines like: services & cloud computing, semantic-based decision support through ontologies and knowledge-based systems, big data management, as well as mobility and collaboration networks. To provide adequate decision support for complex business/IT environments, it is necessary to identify affected changes of Internet of Things environments and their related fast adapting architecture. We have to make transparent the impact of these changes over the integral landscape of affected EAM-capabilities, like directly and transitively impacted IoT-objects, business categories, processes, applications, services, platforms and infrastructures. The paper describes a new metamodel-based approach for integrating partial Internet of Things objects, which are semi-automatically federated into a holistic Enterprise Architecture Management environment.
Enterprises are presently transforming their strategy, culture, processes, and their information systems to become more digital. The digital transformation deeply disrupts existing enterprises and economies. Digitization fosters the development of IT systems with many rather small and distributed structures, like Internet of Things or mobile systems. Since years a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. 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 system architectures defines the moving context for adaptable systems, which are essential to enable the digital transformation. In this paper, we are focusing on a decision-oriented architectural composition approach to support the transformation for digital services and products.
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.
Digitization fosters the development of IT environments with many rather small structures, like Internet of Things (IoT), microservices, or mobility systems. They are needed to support flexible and agile digitized products and services. The goal is to create service-oriented enterprise architectures (EA) that are self optimizing and resilient. The present research paper investigates methods for decision-making concerning digitization architectures for Internet of Things and microservices. They are based on evolving enterprise architecture reference models and state of the art elements for architectural engineering for microgranular systems. Decision analytics in this field becomes increasingly complex and decision support, particularly for the development and evolution of sustainable enterprise architectures, is sorely needed. The challenging of the decision processes can be supported with in a more flexible and intuitive way by an architecture management cockpit.
Digitization of societies changes the way we live, work, learn, communicate, and collaborate. In the age of digital transformation IT environments with a large number of rather small structures like Internet of Things (IoT), microservices, or mobility systems are emerging to support flexible and agile digitized products and services. Adaptable ecosystems with service oriented enterprise architectures are the foundation for self-optimizing, resilient run-time environments and distributed information systems. The resulting business disruptions affect almost all new information processes and systems in the context of digitization. Our aim are more flexible and agile transformations of both business and information technology domains with more flexible enterprise information systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates mechanisms for decision-controlled digitization architectures for Internet of Things and microservices by evolving enterprise architecture reference models and state of the art elements for architectural engineering for micro-granular systems.
The digital transformation of our life changes the way we work, learn, communicate, and collaborate. Enterprises are presently transforming their strategy, culture, processes, and their information systems to become digital. The digital transformation deeply disrupts existing enterprises and economies. Digitization fosters the development of IT systems with many rather small and distributed structures, like Internet of Things, Microservices and mobile services. Since years a lot of new business opportunities appear using the potential of services computing, Internet of Things, mobile systems, big data with analytics, cloud computing, collaboration networks, and decision support. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self optimizing and resilient run-time environments for intelligent business services and adaptable distributed information systems with service oriented enterprise architectures. This has a strong impact for architecting digital services and products following both a value-oriented and a service perspective. The change from a closed world modeling world to a more flexible open-world composition and evolution of enterprise architectures defines the moving context for adaptable and high distributed systems, which are essential to enable the digital transformation. The present research paper investigates the evolution of Enterprise Architecture considering new defined value-oriented mappings between digital strategies, digital business models and an improved digital enterprise architecture.
Social networks, smart portable devices, Internet of Things (IoT) on base of technologies like analytics for big data and cloud services are emerging to support flexible connected products and agile services as the new wave of digital transformation. Biological metaphors of living and adaptable ecosystems with service-oriented enterprise architectures provide the foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems. We are extending Enterprise Architecture (EA) with mechanisms for flexible adaptation and evolution of information systems having distributed IoT and other micro-granular digital architecture to support next digitization products, services, and processes. Our aim is to support flexibility and agile transformation for both IT and business capabilities through adaptive digital enterprise architectures. The present research paper investigates additionally decision mechanisms in the context of multi-perspective explorations of enterprise services and Internet of Things architectures by extending original enterprise architecture reference models with state of art elements for architectural engineering and digitization.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change drive current and next information processes and systems that are important business enablers for the context of digitization since years. Our aim is to support flexibility and agile transformations for both business domains and related information technology with more flexible enterprise information systems through adaptation and evolution of digital architectures. The present research paper investigates the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like microservices and the Internet of Things, as part of a new composed digital architecture. To integrate micro-granular architecture models into living architectural model versions we are extending enterprise architecture reference models by state of art elements for agile architectural engineering to support digital products, services, and processes.
New business opportunities appeared using the potential of the Internet and related digital technologies, like the Internet of Things, services computing, artificial intelligence, cloud, edge, and fog computing, social networks, big data with analytics, mobile systems, collaboration networks, and cyber-physical systems. Companies are transforming their strategy and product base, as well as their culture, processes and information systems to adopt digital transformation or to approach for digital leadership. Digitalization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, Microservices, or other micro-granular elements. Digitalization has a substantial impact for architecting the open and complex world of highly distributed digital servcies and products, as part of a new digital enterprise architecture, which structure and direct service-dominant digital products and services. The present research paper investigates mechanisms for supporting the evolution of digital enterprise architectures with user-friendly methods and instruments of interaction, visualization, and intelligent decision management during the exploration of multiple and interconnected perspectives by an architecture management cockpit.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. The digitization of software-intensive products and services is enabled basically by four megatrends: Cloud computing, big data mobile systems, and social technologies. This disruptive change interacts with all information processes and systems that are important business enablers for the current digital transformation. The internet of things, social collaboration systems for adaptive case management, mobility systems and services for big data in cloud services environments are emerging to support intelligent user-centered and social community systems. Modern enterprises see themselves confronted with an ever growing design space to engineer business models of the future as well as their IT support, respectively. The decision analytics in this field becomes increasingly complex and decision support, particularly for the development and evolution of sustainable enterprise architectures (EA), is duly needed. With the advent of intelligent user-centered and social community systems, the challenging decision processes can be supported in more flexible and intuitive ways. Tapping into these systems and techniques, the engineers and managers of the enterprise architecture become part of a viable enterprise, i.e. a resilient and continuously evolving system that develops innovative business models.
Enterprises are transforming their strategy, culture, processes, and their information systems to enlarge their digitalization efforts or to approach for digital leadership. The digital transformation profoundly disrupts existing enterprises and economies. In current times, a lot of new business opportunities appeared using the potential of the Internet and related digital technologies: The Internet of Things, services computing, cloud computing, artificial intelligence, 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. Architecting micro-granular structures have a substantial impact on architecting digital services and products. The change from a closed-world modeling perspective to more flexible Open World of living software and system architectures defines the context for flexible and evolutionary software approaches, which are essential to enable the digital transformation. In this paper, we are revealing multiple perspectives of digital enterprise architecture and decisions to effectively support value and service oriented software systems for intelligent digital services and products.
Artificial Intelligence-based Assistants AIAs are spreading quickly both in homes and offices. They already have left their original habitats of "intelligent speakers" providing easy access to music collections. The initiated a multitude of new devices and are already populating devices such as TV sets. Characteristic for the intelligent digital assistants is the formation of platforms around their core functionality. Thus, AIS capabilities of the assistants are used to offer new services and create new interfaces for business processes. There are positive network effects between the assistants and the services as well as within the services. Therefore, many companies see the need to get involved in the field of digital assistants but lack a framework to align their initiatives with their corporate strategies. In order to lay the foundation for a comprehensive method, we are therefore investigating intelligent digital assistants. Based on this analysis, we are developing a framework of strategic opportunities and challenges.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. This defines the strategical context for composing resilient enterprise architectures for micro-granular digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of system architectures defines the moving context for adaptable systems, which are essential to enable the digital transformation. Enterprises are presently transforming their strategy and culture together with their processes and information systems to become more digital. The digital transformation deeply disrupts existing enterprises and economies. Since years a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT systems with many rather small and distributed structures, like Internet of Things or mobile systems. In this paper, we are focusing on the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like Internet of Things and Microservices, as part of a new digital enterprise architecture. To integrate micro-granular architecture models to living architectural model versions we are extending more traditional enterprise architecture reference models with state of art elements for agile architectural engineering to support the digitalization of services with related products, and their processes.
Der lokale Bekleidungseinzelhandel steht unter immer stärkerem Konkurrenzdruck durch Versandunternehmen. Zusätzlich bestehen durch gewachsene Architekturen eine Reihe von Wachstumshemmnissen. Daher sollen hier eine Reihe von Ansätzen zur Gestaltung datenzentrierter Unternehmensarchitekturen für den Bekleidungseinzelhandel vorgestellt werden. Sie basieren auf dem Einsatz von RFID zur Gewinnung von Kundenprofilen in den Niederlassungen und dem Einsatz von Big-Data basierten Auswertungs- und Analysemechanismen. Mit den vorgestellten Konzepten ist es Unternehmen des Bekleidungseinzelhandels möglich, ähnlich wie Versandunternehmen, individuelle Ansprachen des Kunden und Angebote zu entwickeln
The Internet of Things (IoT), 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 with service oriented enterprise architectures provide the foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems. We are investigating mechanisms for flexible adaptation and evolution for the next digital enterprise architecture systems in the context of the digital transformation. Our aim is to support flexibility and agile transformation for both business and related enterprise systems through adaptation and dynamical evolution of digital enterprise architectures. The present research paper investigates mechanisms for decision case management in the context of multi-perspective explorations of enterprise services and Internet of Things architectures by extending original enterprise architecture reference models with state of art elements for architectural engineering for the digitization and architectural decision support.
Intelligent systems and services are the strategic targets of many current digitalization efforts and part of massive digital transformations based on digital technologies with artificial intelligence. Digital platform architectures and ecosystems provide an essential base for intelligent digital systems. The paper raises an important question: Which development paths are induced by current innovations in the field of artificial intelligence and digitalization for enterprise architectures? Digitalization disrupts existing enterprises, technologies, and economies and promotes the architecture of cognitive and open intelligent environments. This has a strong impact on new opportunities for value creation and the development of intelligent digital systems and services. Digital technologies such as artificial intelligence, the Internet of Things, service computing, cloud computing, blockchains, big data with analysis, mobile systems, and social business network systems are essential drivers of digitalization. We investigate the development of intelligent digital systems supported by a suitable digital enterprise architecture. We present methodological advances and an evolutionary path for architectures with an integral service and value perspective to enable intelligent systems and services that effectively combine digital strategies and digital architectures with artificial intelligence.
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 related distributed information systems with service-oriented enterprise architectures. We are investigating mechanisms for flexible adaptation and evolution for the next digital enterprise architecture systems in the context of the digital transformation. Our aim is to support flexibility and agile transformation for both business and related enterprise systems through adaptation and dynamical evolution of digital enterprise architectures. The present research paper investigates 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 with the example domain – Internet of Things.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change interacts with all information processes and systems that are important business enablers for the digital transformation since years. The Internet of Things, social collaboration systems for adaptive case management, mobility systems and services for Big Data in cloud services environments are emerging to support intelligent user-centered and social community systems. They will shape future trends of business innovation and the next wave of information and communication technology. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems with service-oriented enterprise architectures. The present research investigates mechanisms for flexible adaptation and evolution of digital enterprise architectures in the context of integrated synergistic disciplines like distributed service-oriented architectures and information systems, EAM - Enterprise Architecture and Management, metamodeling, semantic echnologies, web services, cloud computing and Big Data technology. Our aim is to support flexibility and agile transformations for both business domains and related enterprise systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates digital transformations of business and IT and integrates fundamental mappings between adaptable digital enterprise architectures and service-oriented information systems.
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.
In diesem Kapitel wird eine Einführung in die sich abzeichnenden Trends bei der Gestaltung der digitalen Transformation gegeben, wobei der Schwerpunkt auf digitalen Produkten, intelligenten Diensten und damit verbundenen Systemen sowie auf Methoden, Modellen und Architekturen liegt. Das primäre Ziel dieses Buches ist es, einige der neuesten Forschungsergebnisse auf diesem Gebiet hervorzuheben. Wir stellen eine Reihe von Kurzbeschreibungen der im Buch enthaltenen Kapitel zur Verfügung.
In current times, a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Enterprises are presently transforming their strategy, culture, processes, and their information systems to become more digital. The digital transformation deeply disrupts existing enterprises and economies. Digitization fosters the development of IT environments with many rather small and distributed structures, like Internet of Things. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world and living software and system architectures defines the moving context for adaptable and evolutionary software approaches, which are essential to enable the digital transformation. In this paper, we are putting a spotlight to service oriented software evolution to support the digital transformation with micro granular digital architectures for digital services and products.
Current advances in Artificial Intelligence (AI) combined with other digitalization efforts are changing the role of technology in service ecosystems. Human-centered intelligent systems and services are the target of many current digitalization efforts and part of a massive digital transformation based on digital technologies. Artificial intelligence, in particular, is having a powerful impact on new opportunities for shared value creation and the development of smart service ecosystems. Motivated by experiences and observations from digitalization projects, this paper presents new methodological experiences from academia and practice on a joint view of digital strategy and architecture of intelligent service ecosystems and explores the impact of digitalization based on real case study results. Digital enterprise architecture models serve as an integral representation of business, information, and technology perspectives of intelligent service-based enterprise systems to support management and development. This paper focuses on the novel aspect of closely aligned digital strategy and architecture models for intelligent service ecosystems and highlights the fundamental business mechanism of AI-based value creation, the corresponding digital architecture, and management models. We present key strategy-oriented architecture model perspectives for intelligent systems.
Digitization is the use of digital technologies for creating innovative digital business models and transforming existing business models, processes and systems. Digitization creates profound changes in the economy and society. Information is often captured and processed without human intervention using digital means. Digitization impacts nearly all products and services as well as the customer and the value-creation perspective.
Big Data und Cloud Systeme werden zunehmend von mobilen, benutzerzentrierten und agil veränderbaren Informationssystemen im Kontext von digitalen sozialen Netzwerken genutzt. Metaphern aus der Biologie für lebendige und selbstheilende Systeme und Umgebungen liefern die Basis für intelligente adaptive Informationssysteme und für zugehörige serviceorientierte digitale Unternehmensarchitekturen. Wir berichten über unsere Forschungsarbeiten über Strukturen und Mechanismen adaptiver digitaler Unternehmensarchitekturen für die Entwicklung und Evolution von serviceorientierten Ökosystemen und deren Technologien wie Big Data, Services & Cloud Computing, Web Services und Semantikunterstützung. Für unsere aktuellen Forschungsarbeiten nutzen wir praxisrelevante SmartLife Szenarien für die Entwicklung, Wartung und Evolution zukunftsgerechter serviceorientierter Informationssysteme. Diese Systeme nutzen eine stark wachsende Zahl externer und interner Services und fokussieren auf die Besonderheiten der Weiterentwicklung der Informationssysteme für integrierte Big Data und Cloud Kontexte. Unser Forschungsansatz beschäftigt sich mit der systematischen und ganzheitlichen Modellbildung adaptiver digitaler Unternehmensarchitekturen - gemäß standardisierter Referenzmodelle und auf Standards aufsetzenden Referenzarchitekturen, die für besondere Einsatzszenarien auch bei kleineren Anwendungskontexten oder an neue Kontexte einfacher adaptiert werden können. Um Semantik-gestützte Analysen zur Entscheidungsunterstützung von System- und Unternehmensarchitekten zu ermöglichen, erweitern wir unser bisheriges Referenzmodell für ITUnternehmensarchitekturen ESARC – Enterprise Services Architecture Reference Cube – um agile Mechanismen der Adaption und Konsistenzbehandlung sowie die zugehörigen Metamodelle und Ontologien für Digitale Enterprise Architekturen um neue Aspekte wie Big Data und Cloud Kontexte.
Today, many companies are adapting their strategy, business models, products, services as well as business processes and information systems in order to expand their digitalization level through intelligent systems and services. The paper raises an important question: What are cognitive co-creation mechanisms for extending digital services and architectures to readjust the usage value of smart services? Typically, extensions of digital services and products and their architectures are manual design tasks that are complex and require specialized, rare experts. The current publication explores the basic idea of extending specific digital artifacts, such as intelligent service architectures, through mechanisms of cognitive co-creation to enable a rapid evolutionary path and better integration of humans and intelligent systems. We explore the development of intelligent service architectures through a combined, iterative, and permanent task of co-creation between humans and intelligent systems as part of a new concept of cognitively adapted smart services. In this paper, we present components of a new platform for the joint co-creation of cognitive services for an ecosystem of intelligent services that enables the adaptation of digital services and architectures.
Handling complexity in modern software engineering : editorial introduction to issue 32 of CSIMQ
(2022)
The potential of the Internet and related digital technologies, such as the Internet of Things (IoT), cognition and artificial intelligence, data analytics, services computing, cloud computing, mobile systems, collaboration networks, and cyber-physical systems, are both strategic drivers and enablers of modern digital platforms with fast-evolving ecosystems of intelligent services for digital products. This issue of CSIMQ presents three recent articles on modern software engineering. First, we focus on continuous software development and place it in the context of software architectures and digital transformation. The first contribution is followed by the description of the basis of specific security requirements and adequate digital monitoring mechanisms. Finally, we present a practical example of the digital management of livestock farming.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change interacts with all information processes and systems that are important business enablers for the context of digitization since years. Our aim is to support flexibility and agile transformations for both business domains and related information technology and enterprise systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates collaborative decision mechanisms for adaptive 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 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.
The internet of things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud environments are emerging to support smart connected i.e. digital products and services and the digital transformation. Biological metaphors for living and adaptable ecosystems are currently providing the logical foundation for resilient run-time environments with serviceoriented digitization architectures and for self-optimizing intelligent business services and related distributed information systems. We are investigating mechanisms for flexible adaptation and evolution of information systems with digital architecture in the context of the ongoing digital transformation. The goal is to support flexible and agile transformations for both business and related information systems through adaptation and dynamical evolution of their digital architectures. The present research paper investigates mechanisms of decision analytics for digitization architectures, putting a spotlight to internet of things micro-granular architectures, by extending original enterprise architecture reference models with digitization architectures and their multi-perspective architectural decision management.
SmartLife ecosystems are emerging as intelligent user-centered systems that will shape future trends in technology and communication. Biological metaphors of living adaptable ecosystems provide the logical foundation for self-optimizing and self-healing run-time environments for intelligent adaptable business services and related information systems with service-oriented enterprise architectures. The present research in progress work investigates mechanisms for adaptable enterprise architectures for the development of service-oriented ecosystems with integrated technologies like Semantic Technologies, Web Services, Cloud Computing and Big Data Management. With a large and diverse set of ecosystem services with different owners, our scenario of service-based SmartLife ecosystems can pose challenges in their development, and more importantly, for maintenance and software evolution. Our research explores the use of knowledge modeling using ontologies and flexible metamodels for adaptable enterprise architectures to support program comprehension for software engineers during maintenance and evolution tasks of service-based applications. Our previous reference enterprise architecture model ESARC -- Enterprise Services Architecture Reference Cube -- and the Open Group SOA Ontology was extended to support agile semantic analysis, program comprehension and software evolution for a SmartLife applications scenario. The Semantic Browser is a semantic search tool that was developed to provide knowledge-enhanced investigation capabilities for service-oriented applications and their architectures.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change interacts with all information processes and systems that are important business enablers for the context of digitization since years. Our aim is to support flexibility and agile transformations for both business domains and related information technology with more flexible enterprise information systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like microservices and the Internet of Things, as part of a new digital enterprise architecture. To integrate micro granular architecture models to living architectural model versions we are extending more traditional enterprise architecture reference models with state of art elements for agile architectural engineering to support the digitization of products, services, and processes.
Mit dem Kunstbegriff "Virtuelle Realität" beschreibt man die Darstellung von künstlichen Welten und die Interaktion mit den selbigen. Meist verbindet man damit teure Spiel- und Filmproduktionen. Doch durch derzeitige Entwicklungen können auch kleine Entwicklerstudios und Endanwender auf Bewegungserkennungssysteme zurückgreifen. In dieser Ausarbeitung werden zwei Prototypen vorgestellt, die auf eben diese Systeme zurückgreifen. In den Prototypen soll eine Interaktion mit der Umwelt und ein "Mittendringefühl" im Rahmen von Serious Games ermöglicht werden.
An interactive clothing design and a personalized virtual display with user’s own face are presented in this paper to meet the requirement of personalized clothing customization. A customer interactive clothing design approach based on genetic engineering ideas is analyzed by taking suit as an example. Thus, customers could rearrange the clothing style elements, chose available color, fabric and come up with their own personalized suit style. A web 3D customization prototype system of personalized clothing is developed based on the Unity3D and VR technology. The layout of the structure and functions combined with the flow of the system are given. Practical issues such as 3D face scanning, suit style design, fabric selection, and accessory choices are addressed also. Tests to the prototype system indicate that it could show realistic clothing and fabric effect and offer effective visual and customization experience to users.
Usually battery chargers have two stages and DC charging current is considered to by necessary for a proper charging. To decrease the charger volume, a single stage LLC battery charger is investigated in this paper. PFC stage is eliminated, therefore no bulky capacitor is necessary any more, and battery is charged with a sinusoidal-like charging current. However, previous studies show that such a pulsating charging current has only minimal impact on battery life and efficiency. Design considerations of the resonant tank and optimal transformer design are presented. A 360W single stage LLC converter prototype for e-bike charger achieves a power factor of 0.98, efficiency of 0.93 and power density of 1,8kW/dm³.
Background
The actual task of electrocardiographic examinations is to increase the reliability of diagnosing the condition of the heart. Within the framework of this task, an important direction is the solution of the inverse problem of electrocardiography, based on the processing of electrocardiographic signals of multichannel cardio leads at known electrode coordinates in these leads (Titomir et al. Noninvasiv electrocardiotopography, 2003), (Macfarlane et al. Comprehensive Electrocardiology, 2nd ed. (Chapter 9), 2011).
Results
In order to obtain more detailed information about the electrical activity of the heart, we carry out a reconstruction of the distribution of equivalent electrical sources on the heart surface. In this area, we hold reconstruction of the equivalent sources during the cardiac cycle at relatively low hardware cost. ECG maps of electrical potentials on the surface of the torso (TSPM) and electrical sources on the surface of the heart (HSSM) were studied for different times of the cardiac cycle. We carried out a visual and quantitative comparison of these maps in the presence of pathological regions of different localization. For this purpose we used the model of the heart electrical activity, based on cellular automata.
Conclusions
The model of cellular automata allows us to consider the processes of heart excitation in the presence of pathological regions of various sizes and localization. It is shown, that changes in the distribution of electrical sources on the surface of the epicardium in the presence of pathological areas with disturbances in the conduction of heart excitation are much more noticeable than changes in ECG maps on the torso surface.
This paper presents a permanent magnet tubular linear generator system for powering passive sensors using vertical vibration harvesting energy. The system consists of a permanent magnet tubular linear vibration generator and electric circuits. By using the design of mechanical resonant movers, the generator is capable of converting low frequencies small amplitude vertical vibration energy into more regular sinusoidal electrical energy. The distribution of the magnetic field and electromotive force are calculated by Finite Element Analysis. The characteristics of the linear vibration generator system are observed. The experimental results show the generator can produce about 0.4W~1.6W electrical power when the vibration source's amplitude is fixed on 2mm and the frequencies are between 13Hz and 22Hz.
Purpose
Computerized medical imaging processing assists neurosurgeons to localize tumours precisely. It plays a key role in recent image-guided neurosurgery. Hence, we developed a new open-source toolkit, namely Slicer-DeepSeg, for efficient and automatic brain tumour segmentation based on deep learning methodologies for aiding clinical brain research.
Methods
Our developed toolkit consists of three main components. First, Slicer-DeepSeg extends the 3D Slicer application and thus provides support for multiple data input/ output data formats and 3D visualization libraries. Second, Slicer core modules offer powerful image processing and analysis utilities. Third, the Slicer-DeepSeg extension provides a customized GUI for brain tumour segmentation using deep learning-based methods.
Results
The developed Slicer-DeepSeg was validated using a public dataset of high-grade glioma patients. The results showed that our proposed platform’s performance considerably outperforms other 3D Slicer cloud-based approaches.
Conclusions
Developed Slicer-DeepSeg allows the development of novel AI-assisted medical applications in neurosurgery. Moreover, it can enhance the outcomes of computer-aided diagnosis of brain tumours. Open-source Slicer-DeepSeg is available at github.com/razeineldin/Slicer-DeepSeg.
Intraoperative imaging can assist neurosurgeons to define brain tumours and other surrounding brain structures. Interventional ultrasound (iUS) is a convenient modality with fast scan times. However, iUS data may suffer from noise and artefacts which limit their interpretation during brain surgery. In this work, we use two deep learning networks, namely UNet and TransUNet, to make automatic and accurate segmentation of the brain tumour in iUS data. Experiments were conducted on a dataset of 27 iUS volumes. The outcomes show that using a transformer with UNet is advantageous providing an efficient segmentation modelling long-range dependencies between each iUS image. In particular, the enhanced TransUNet was able to predict cavity segmentation in iUS data with an inference rate of more than 125 FPS. These promising results suggest that deep learning networks can be successfully deployed to assist neurosurgeons in the operating room.
A hybrid deep registration of MR scans to interventional ultrasound for neurosurgical guidance
(2021)
Despite the recent advances in image-guided neurosurgery, reliable and accurate estimation of the brain shift still remains one of the key challenges. In this paper, we propose an automated multimodal deformable registration method using hybrid learning-based and classical approaches to improve neurosurgical procedures. Initially, the moving and fixed images are aligned using classical affine transformation (MINC toolkit), and then the result is provided to the convolutional neural network, which predicts the deformation field using backpropagation. Subsequently, the moving image is transformed using the resultant deformation into a moved image. Our model was evaluated on two publicly available datasets: the retrospective evaluation of cerebral tumors (RESECT) and brain images of tumors for evaluation (BITE). The mean target registration errors have been reduced from 5.35 ± 4.29 to 0.99 ± 0.22 mm in the RESECT and from 4.18 ± 1.91 to 1.68 ± 0.65 mm in the BITE. Experimental results showed that our method improved the state-of-the-art in terms of both accuracy and runtime speed (170 ms on average). Hence, the proposed method provides a fast runtime for 3D MRI to intra-operative US pair in a GPU-based implementation, which shows a promise for its applicability in assisting the neurosurgical procedures compensating for brain shift.
Glioblastomas are the most aggressive fast-growing primary brain cancer which originate in the glial cells of the brain. Accurate identification of the malignant brain tumor and its sub-regions is still one of the most challenging problems in medical image segmentation. The Brain Tumor Segmentation Challenge (BraTS) has been a popular benchmark for automatic brain glioblastomas segmentation algorithms since its initiation. In this year, BraTS 2021 challenge provides the largest multi-parametric (mpMRI) dataset of 2,000 pre-operative patients. In this paper, we propose a new aggregation of two deep learning frameworksnamely, DeepSeg and nnU-Net for automatic glioblastoma recognition in pre-operative mpMRI. Our ensemble method obtains Dice similarity scores of 92.00, 87.33, and 84.10 and Hausdorff Distances of 3.81, 8.91, and 16.02 for the enhancing tumor, tumor core, and whole tumor regions, respectively, on the BraTS 2021 validation set, ranking us among the top ten teams. These experimental findings provide evidence that it can be readily applied clinically and thereby aiding in the brain cancer prognosis, therapy planning, and therapy response monitoring. A docker image for reproducing our segmentation results is available online at (https://hub.docker.com/r/razeineldin/deepseg21).
Intraoperative brain deformation, so called brain shift, affects the applicability of preoperative magnetic resonance imaging (MRI) data to assist the procedures of intraoperative ultrasound (iUS) guidance during neurosurgery. This paper proposes a deep learning-based approach for fast and accurate deformable registration of preoperative MRI to iUS images to correct brain shift. Based on the architecture of 3D convolutional neural networks, the proposed deep MRI-iUS registration method has been successfully tested and evaluated on the retrospective evaluation of cerebral tumors (RESECT) dataset. This study showed that our proposed method outperforms other registration methods in previous studies with an average mean squared error (MSE) of 85. Moreover, this method can register three 3D MRI-US pair in less than a second, improving the expected outcomes of brain surgery.
Purpose: Gliomas are the most common and aggressive type of brain tumors due to their infiltrative nature and rapid progression. The process of distinguishing tumor boundaries from healthy cells is still a challenging task in the clinical routine. Fluid attenuated inversion recovery (FLAIR) MRI modality can provide the physician with information about tumor infiltration. Therefore, this paper proposes a new generic deep learning architecture, namely DeepSeg, for fully automated detection and segmentation of the brain lesion using FLAIR MRI data.
Methods: The developed DeepSeg is a modular decoupling framework. It consists of two connected core parts based on an encoding and decoding relationship. The encoder part is a convolutional neural network (CNN) responsible for spatial information extraction. The resulting semantic map is inserted into the decoder part to get the full-resolution probability map. Based on modified U-Net architecture, different CNN models such as residual neural network (ResNet), dense convolutional network (DenseNet), and NASNet have been utilized in this study.
Results: The proposed deep learning architectures have been successfully tested and evaluated on-line based on MRI datasets of brain tumor segmentation (BraTS 2019) challenge, including s336 cases as training data and 125 cases for validation data. The dice and Hausdorff distance scores of obtained segmentation results are about 0.81 to 0.84 and 9.8 to 19.7 correspondingly.
Conclusion: This study showed successful feasibility and comparative performance of applying different deep learning models in a new DeepSeg framework for automated brain tumor segmentation in FLAIR MR images. The proposed DeepSeg is open source and freely available at https://github.com/razeineldin/DeepSeg/.
Accurate and safe neurosurgical intervention can be affected by intra-operative tissue deformation, known as brain-shift. In this study, we propose an automatic, fast, and accurate deformable method, called iRegNet, for registering pre-operative magnetic resonance images to intra-operative ultrasound volumes to compensate for brain-shift. iRegNet is a robust end-to-end deep learning approach for the non-linear registration of MRI-iUS images in the context of image-guided neurosurgery. Pre-operative MRI (as moving image) and iUS (as fixed image) are first appended to our convolutional neural network, after which a non-rigid transformation field is estimated. The MRI image is then transformed using the output displacement field to the iUS coordinate system. Extensive experiments have been conducted on two multi-location databases, which are the BITE and the RESECT. Quantitatively, iRegNet reduced the mean landmark errors from pre-registration value of (4.18 ± 1.84 and 5.35 ± 4.19 mm) to the lowest value of (1.47 ± 0.61 and 0.84 ± 0.16 mm) for the BITE and RESECT datasets, respectively. Additional qualitative validation of this study was conducted by two expert neurosurgeons through overlaying MRI-iUS pairs before and after the deformable registration. Experimental findings show that our proposed iRegNet is fast and achieves state-of-the-art accuracies outperforming state-of-the-art approaches. Furthermore, the proposed iRegNet can deliver competitive results, even in the case of non-trained images as proof of its generality and can therefore be valuable in intra-operative neurosurgical guidance.
Purpose
Artificial intelligence (AI), in particular deep neural networks, has achieved remarkable results for medical image analysis in several applications. Yet the lack of explainability of deep neural models is considered the principal restriction before applying these methods in clinical practice.
Methods
In this study, we propose a NeuroXAI framework for explainable AI of deep learning networks to increase the trust of medical experts. NeuroXAI implements seven state-of-the-art explanation methods providing visualization maps to help make deep learning models transparent.
Results
NeuroXAI has been applied to two applications of the most widely investigated problems in brain imaging analysis, i.e., image classification and segmentation using magnetic resonance (MR) modality. Visual attention maps of multiple XAI methods have been generated and compared for both applications. Another experiment demonstrated that NeuroXAI can provide information flow visualization on internal layers of a segmentation CNN.
Conclusion
Due to its open architecture, ease of implementation, and scalability to new XAI methods, NeuroXAI could be utilized to assist radiologists and medical professionals in the detection and diagnosis of brain tumors in the clinical routine of cancer patients. The code of NeuroXAI is publicly accessible at https://github.com/razeineldin/NeuroXAI.
Automatic segmentation is essential for the brain tumor diagnosis, disease prognosis, and follow-up therapy of patients with gliomas. Still, accurate detection of gliomas and their sub-regions in multimodal MRI is very challenging due to the variety of scanners and imaging protocols. Over the last years, the BraTS Challenge has provided a large number of multi-institutional MRI scans as a benchmark for glioma segmentation algorithms. This paper describes our contribution to the BraTS 2022 Continuous Evaluation challenge. We propose a new ensemble of multiple deep learning frameworks namely, DeepSeg, nnU-Net, and DeepSCAN for automatic glioma boundaries detection in pre-operative MRI. It is worth noting that our ensemble models took first place in the final evaluation on the BraTS testing dataset with Dice scores of 0.9294, 0.8788, and 0.8803, and Hausdorf distance of 5.23, 13.54, and 12.05, for the whole tumor, tumor core, and enhancing tumor, respectively. Furthermore, the proposed ensemble method ranked first in the final ranking on another unseen test dataset, namely Sub-Saharan Africa dataset, achieving mean Dice scores of 0.9737, 0.9593, and 0.9022, and HD95 of 2.66, 1.72, 3.32 for the whole tumor, tumor core, and enhancing tumor, respectively.
Recent advances in artificial intelligence have enabled promising applications in neurosurgery that can enhance patient outcomes and minimize risks. This paper presents a novel system that utilizes AI to aid neurosurgeons in precisely identifying and localizing brain tumors. The system was trained on a dataset of brain MRI scans and utilized deep learning algorithms for segmentation and classification. Evaluation of the system on a separate set of brain MRI scans demonstrated an average Dice similarity coefficient of 0.87. The system was also evaluated through a user experience test involving the Department of Neurosurgery at the University Hospital Ulm, with results showing significant improvements in accuracy, efficiency, and reduced cognitive load and stress levels. Additionally, the system has demonstrated adaptability to various surgical scenarios and provides personalized guidance to users. These findings indicate the potential for AI to enhance the quality of neurosurgical interventions and improve patient outcomes. Future work will explore integrating this system with robotic surgical tools for minimally invasive surgeries.
Purpose
Artificial intelligence (AI), in particular deep learning (DL), has achieved remarkable results for medical image analysis in several applications. Yet the lack of human-like explanations of such systems is considered the principal restriction before utilizing these methods in clinical practice (Yang, Ye, & Xia, 2022).
Methods
Explainable Artificial Intelligence (XAI) provides a human-explainable and interpretable description of the “black-box” nature of DL (Gulum, Trombley, & Kantardzic, 2021). An effective XAI diagnosis generator, namely NeuroXAI (refer to Fig. 1), has been developed to extract 3D explanations from convolutional neural networks (CNN) models of brain gliomas (Zeineldin et al., 2022). By providing visual justification maps, NeuroXAI can help make DL models transparent and thus increase the trust of medical experts.
Results
NeuroXAI has been applied to two applications of the most widely investigated problems in brain imaging analysis, i.e. image classification and segmentation using magnetic resonance imaging (MRI). Visual attention maps of multiple XAI methods have been generated and compared for both applications, which could help to provide transparency about the performance of DL systems.
Conclusion
NeuroXAI helps to understand the prediction process of 3D CNN networks for brain glioma using human-understandable explanations. Results revealed that the investigated DL models behave in a logical human-like manner and can improve the analytical process of the MRI images systematically. Due to its open architecture, ease of implementation, and scalability to new XAI methods, NeuroXAI could be utilized to assist medical professionals in the detection and diagnosis of brain tumors. NeuroXAI code is publicly accessible at https://github.com/razeineldin/NeuroXAI
Intracranial brain tumors are one of the ten most common malignant cancers and account for substantial morbidity and mortality. The largest histological category of primary brain tumors is the gliomas which occur with an ultimate heterogeneous appearance and can be challenging to discern radiologically from other brain lesions. Neurosurgery is mostly the standard of care for newly diagnosed glioma patients and may be followed by radiation therapy and adjuvant temozolomide chemotherapy.
However, brain tumor surgery faces fundamental challenges in achieving maximal tumor removal while avoiding postoperative neurologic deficits. Two of these neurosurgical challenges are presented as follows. First, manual glioma delineation, including its sub-regions, is considered difficult due to its infiltrative nature and the presence of heterogeneous contrast enhancement. Second, the brain deforms its shape, called “brain shift,” in response to surgical manipulation, swelling due to osmotic drugs, and anesthesia, which limits the utility of pre-operative imaging data for guiding the surgery.
Image-guided systems provide physicians with invaluable insight into anatomical or pathological targets based on modern imaging modalities such as magnetic resonance imaging (MRI) and Ultrasound (US). The image-guided toolkits are mainly computer-based systems, employing computer vision methods to facilitate the performance of peri-operative surgical procedures. However, surgeons still need to mentally fuse the surgical plan from pre-operative images with real-time information while manipulating the surgical instruments inside the body and monitoring target delivery. Hence, the need for image guidance during neurosurgical procedures has always been a significant concern for physicians.
This research aims to develop a novel peri-operative image-guided neurosurgery (IGN) system, namely DeepIGN, that can achieve the expected outcomes of brain tumor surgery, thus maximizing the overall survival rate and minimizing post-operative neurologic morbidity. In the scope of this thesis, novel methods are first proposed for the core parts of the DeepIGN system of brain tumor segmentation in MRI and multimodal pre-operative MRI to the intra-operative US (iUS) image registration using the recent developments in deep learning. Then, the output prediction of the employed deep learning networks is further interpreted and examined by providing human-understandable explainable maps. Finally, open-source packages have been developed and integrated into widely endorsed software, which is responsible for integrating information from tracking systems, image visualization, image fusion, and displaying real-time updates of the instruments relative to the patient domain.
The components of DeepIGN have been validated in the laboratory and evaluated in the simulated operating room. For the segmentation module, DeepSeg, a generic decoupled deep learning framework for automatic glioma delineation in brain MRI, achieved an accuracy of 0.84 in terms of the dice coefficient for the gross tumor volume. Performance improvements were observed when employing advancements in deep learning approaches such as 3D convolutions over all slices, region-based training, on-the-fly data augmentation techniques, and ensemble methods.
To compensate for brain shift, an automated, fast, and accurate deformable approach, iRegNet, is proposed for registering pre-operative MRI to iUS volumes as part of the multimodal registration module. Extensive experiments have been conducted on two multi-location databases: the BITE and the RESECT. Two expert neurosurgeons conducted additional qualitative validation of this study through overlaying MRI-iUS pairs before and after the deformable registration. Experimental findings show that the proposed iRegNet is fast and achieves state-of-the-art accuracies. Furthermore, the proposed iRegNet can deliver competitive results, even in the case of non-trained images, as proof of its generality and can therefore be valuable in intra-operative neurosurgical guidance.
For the explainability module, the NeuroXAI framework is proposed to increase the trust of medical experts in applying AI techniques and deep neural networks. The NeuroXAI includes seven explanation methods providing visualization maps to help make deep learning models transparent. Experimental findings showed that the proposed XAI framework achieves good performance in extracting both local and global contexts in addition to generating explainable saliency maps to help understand the prediction of the deep network. Further, visualization maps are obtained to realize the flow of information in the internal layers of the encoder-decoder network and understand the contribution of MRI modalities in the final prediction. The explainability process could provide medical professionals with additional information about tumor segmentation results and therefore aid in understanding how the deep learning model is capable of processing MRI data successfully.
Furthermore, an interactive neurosurgical display has been developed for interventional guidance, which supports the available commercial hardware such as iUS navigation devices and instrument tracking systems. The clinical environment and technical requirements of the integrated multi-modality DeepIGN system were established with the ability to incorporate: (1) pre-operative MRI data and associated 3D volume reconstructions, (2) real-time iUS data, and (3) positional instrument tracking. This system's accuracy was tested using a custom agar phantom model, and its use in a pre-clinical operating room is simulated. The results of the clinical simulation confirmed that system assembly was straightforward, achievable in a clinically acceptable time of 15 min, and performed with a clinically acceptable level of accuracy.
In this thesis, a multimodality IGN system has been developed using the recent advances in deep learning to accurately guide neurosurgeons, incorporating pre- and intra-operative patient image data and interventional devices into the surgical procedure. DeepIGN is developed as open-source research software to accelerate research in the field, enable ease of sharing between multiple research groups, and continuous developments by the community. The experimental results hold great promise for applying deep learning models to assist interventional procedures - a crucial step towards improving the surgical treatment of brain tumors and the corresponding long-term post-operative outcomes.
DMOS transistors are often subject to high power dissipation and thus substantial self-heating. This limits their safe operating area because very high device temperatures can lead to thermal runaway and subsequent destruction. Because the peak temperature usually occurs only in a small region in the device, it is possible to redistribute part of the dissipated power from the hot region to the cooler device areas. In this way, the peak temperature is reduced, whereas the total power dissipation is still the same. Assuming that a certain temperature must not be exceeded for safe operation, the improved device is now capable of withstanding higher amounts of energy with an unchanged device area. This paper presents two simple methods to redistribute the power dissipation density and thus lower the peak device temperature. The presented methods only require layout changes. They can easily be applied to modern power technologies without the need of process modifications. Both methods are implemented in test structures and investigated by simulations and measurements.
DMOS transistors often suffer from substantial self-heating during high power dissipation, which can lead to thermal destruction if the device temperature reaches excessive values. A successfully demonstrated method to reduce the peak temperature is the redistribution of power dissipation density from the hotter to the cooler device areas by careful layout modification. However, this is very tedious and time-consuming if complex-shaped devices as often found in industrial applications are considered.
This paper presents an approach for fully automatic layout optimization which requires only a few hours processing time. The approach is applied to complex shaped test structures which are investigated by measurements and electro-thermal simulations. Results show a significantly lower peak temperature and an energy capability gain of 84 %, offering potential for a 18 % size reduction of active area.
The general conclusion of climate change studies is the necessity of eliminating net CO2 emissions in general and from the electric power systems in particular by 2050. The share of renewable energy is increasing worldwide, but due to the intermittent nature of wind and solar power, a lack of system flexibility is already hampering the further integration of renewable energy in some countries. In this study, we analyze if and how combinations of carbon pricing and power-to-gas (PtG) generation in the form of green power-to-hydrogen followed by methanation (which we refer to as PtG throughout) using captured CO2 emissions can provide transitions to deep decarbonization of energy systems. To this end, we focus on the economics of deep decarbonization of the European electricity system with the help of an energy system model. In different scenario analyses, we find that a CO2 price of 160 €/t (by 2050) is on its own not sufficient to decarbonize the electricity sector, but that a CO2 price path of 125 (by 2040) up to 160 €/t (by 2050), combined with PtG technologies, can lead to an economically feasible decarbonization of the European electricity system by 2050. These results are robust to higher than anticipated PtG costs.
Vehicles have been so far improved in terms of energy-efficiency and safety mainly by optimising the engine and the power train. However, there are opportunities to increase energy-efficiency and safety by adapting the individual driving behaviour in the given driving situation. In this paper, an improved rule match algorithm is introduced, which is used in the expert system of a human-centred driving system. The goal of the driving system is to optimise the driving behaviour in terms of energy-efficiency and safety by giving recommendations to the driver. The improved rule match algorithm checks the incoming information against the driving rules to recognise any breakings of a driving rule. The needed information is obtained by monitoring the driver, the current driving situation as well as the car, using in-vehicle sensors and serial-bus systems. On the basis of the detected broken driving rules, the expert system will create individual recommendations in terms of energy-efficiency and safety, which will allow eliminating bad driving habits, while considering the driver needs.
Detecting the adherence of driving rules in an energy-efficient, safe and adaptive driving system
(2016)
An adaptive and rule-based driving system is being developed that tries to improve the driving behavior in terms of the energy-efficiency and safety by giving recommendations. Therefore, the driving system has to monitor the adherence of driving rules by matching the rules to the driving behavior. However, existing rule matching algorithms are not sufficient, as the data within a driving system is changing frequently. In this paper a rule matching algorithm is introduced that is able to handle frequently changing data within the context of the driving system. 15 journeys were used to evaluate the performance of the rule matching algorithms. The results showed that the introduced algorithm outperforms existing algorithms in the context of the driving system. Thus, the introduced algorithm is suited for matching frequently changing data against rules with a higher performance, why it will be used in the driving system for the detection of broken energy-efficiency of safety-relevant driving rules.
In the last decades, several driving systems were developed to improve the driving behaviour in energy efficiency or safety. However, these driving systems cover either the area of energy-efficiency or safety. Furthermore, they do not consider the stress level of the driver when showing a recommendation, although stress can lead to an unsafe or inefficient driving behaviour. In this paper, an approach is presented to consider the driver stress level in a driving system for safe and energy-efficient driving behaviour. The driving system tries to suppress a recommendation when the driver is in stress in order not to stress the driver additionally with recommendations in a stressful driving situation. This can lead to an increase in the road safety and in the user acceptance of the driving system, as the driver is not getting bothered or stressed by the driving system.
The evaluation of the approach showed, that the driving system
is able to show recommendations to the driver, while also reacting
to a high stress level by suppressing recommendations in
order not to stress the driver additionally.
Besides the optimisation of the car, energy-efficiency and safety can also be increased by optimising the driving behaviour. Based on this fact, a driving system is in development whose goal is to educate the driver in energy-efficient and safe driving. It monitors the driver, the car and the environment and gives energy-efficiency and safety relevant recommendations. However, the driving system tries not to distract or bother the driver by giving recommendations for example during stressful driving situations or when the driver is not interested in that recommendation. Therefore, the driving system monitors the stress level of the driver as well as the reaction of the driver to a given recommendation and decides whether to give a recommendation or not. This allows to suppress recommendations when needed and, thus, to increase the road safety and the user acceptance of the driving system.
Saving energy and road safety became important in the last decades, hence several driving assistant systems were developed that help to improve the driving behaviour. However, these driving systems cover the area of either energy-efficiency or safety. Furthermore, they do not consider the reaction of the driver to a shown recommendation and the driver stress level. In this paper, the decision process of showing a recommendation to the driver in an energy-efficient and safety relevant driving system is presented. The decision process considers the driver's reaction to a shown recommendation and the driver stress in order to increase the user acceptance and the road safety. The results of the evaluation showed that the driving system was able to show recommendations when needed, while suppressing recommendations when the driver ignored a recommendation repeatedly or when the driver was in stress.
Besides the optimisation of the car, energy-efficiency and safety can also be increased by optimising the driving behaviour. Based on this fact, a driving system is in development whose goal is to educate the driver in energy efficient and safe driving. It monitors the driver, the car and the environment and gives energy-efficiency and safety relevant recommendations. However, the driving system tries not to distract or bother the driver by giving recommendations for example during stressful driving situations or when the driver is not interested in that recommendation. Therefore, the driving system monitors the stress level of the driver as well as the reaction of the driver to a given recommendation and decideswhether to give a recommendation or not. This allows to suppress recommendations when needed and, thus, to increase the road safety and the user acceptance of
the driving system.
Energy-efficiency and safety became an important factor for car manufacturers. Thus, the cars have been optimised regarding the energy consumption and safety by optimising for example the power train or the engine. Besides the optimisation of the car itself, energy-efficiency and safety can also be increased by adapting the individual driving behaviour to the current driving situation. This paper introduces a driving system, which is in development. Its goal is to optimise the driving behaviour in terms of energy-efficiency and safety by giving recommendations to the driver. For the creation of a recommendation the driving system monitors the driver and the current driving situation as well as the car using in-vehicle sensors and serial-bus systems. On the basis of the acquired data, the driving system will give individual energy-efficiency and safety recommendations in real-time. This will allow eliminating bad driving habits, while considering the driver needs.
Saving energy and protecting the environment became fundamental for society and politics, why several laws were enacted to increase the energy-efficiency. Furthermore, the growing number of vehicles and drivers leaded to more accidents and fatalities on the roads, why road safety became an important factor as well. Due to the increasing importance of energy-efficiency and safety, car manufacturers started to optimise the vehicle in terms of energy-effciency and safety. However, energy-efficiency and road safety can be also increased by adapting the driving behaviour to the given driving situation. This thesis presents a concept of an adaptive and rule based driving system that tries to educate the driver in energy-efficient and safe driving by showing recommendations on time. Unlike existing driving-systems, the presented driving system considers energy-efficiency and safety relevant driving rules, the individual driving behaviour and the driver condition. This allows to avoid the distraction of the driver and to increase the acceptance of the driving system, while improving the driving behaviour in terms of energy-efficiency and safety. A prototype of the driving system was developed and evaluated. The evaluation was done on a driving simulator using 42 test drivers, who tested the effect of the driving system on the driving behaviour and the effect of the adaptiveness of the driving system on the user acceptance. It has been proven during the evaluation that the energy-efficiency and safety can be increased, when the driving system was used. Furthermore, it has been proven that the user acceptance of the driving system increases when the adaptive feature was turned on. A high user acceptance of the driving system allows a steady usage of the driving system and, thus, a steady improvement of the driving behaviour in terms of energy-efficiency and safety.
In dieser Arbeit wird eine optimierte Bandgap-Referenz zur Erzeugung einer temperaturstabilen Spannung und eines Referenzstroms vorgestellt. Für Low-Power-Anwendungen wurde die Bandgap-Referenz, basierend auf der Brokaw-Zelle, mit minimaler Stromaufnahme und optimierter Chipfläche durch Multi-Emitter-Layout der Bipolartransistoren implementiert. Zusätzliches Merkmal ist ein verbreiteter Versorgungsspannungsbereich von 2,5 bis 5,5 V. Simulationen zeigen, dass eine stabile Ausgangsspannung von 1,218 V und ein Referenzstrom von 1,997 μA realisiert wird. Im Temperaturbereich -40 °C … 50 °C sowie dem gesamten Bereich der Versorgungsspannung beträgt die Genauigkeit der Referenzspannung ± 0,04 % mit einer Gesamtstromaufnahme zwischen 3,5 und 10 μA. Es wird eine Temperaturdrift von 2,18 ppm/K erreicht. Durch das elektronische Trimmen von Widerständen wird der Offset der Ausgangsspannung, bedingt durch Herstellungstoleranzen, auf ±3,5 mV justiert. Die Referenz wird in einer 0,18 μm BiCMOS-Technologie implementiert.
In vitro, hydrogel-based ECMs for functionalizing surfaces of various material have played an essential role in mimicking native tissue matrix. Polydimethylsiloxane (PDMS) is widely used to build microfluidic or organ-on-chip devices compatible with cells due to its easy handling in cast replication. Despite such advantages, the limitation of PDMS is its hydrophobic surface property. To improve wettability of PDMS-based devices, alginate, a naturally derived polysaccharide, was covalently bound to the PDMS surface. This alginate then crosslinked further hydrogel onto the PDMS surface in desired layer thickness. Hydrogel-modified PDMS was used for coating a topography chip system and in vitro investigation of cell growth on the surfaces. Moreover, such hydrophilic hydrogel-coated PDMS is utilized in a microfluidic device to prevent unspecific absorption of organic solutions. Hence, in both exemplary studies, PDMS surface properties were modified leading to improved devices.
Palladium-doped silica materials with SiCH3 groups were fabricated by sol-gel method under various calcination atmospheres and membranes were made thereof by coating process. The results showed that air atmosphere can lead to the partial oxidation of metallic Pd0 to PdO while N2 and H2 atmospheres can effectively prevent metallic Pd0 from being oxidized. H2 atmosphere is proved to be a more prominent way to slow down the decomposition of organic SiCH3 group than N2 and air atmospheres. The surface area, micropore volume and porosity of palladium-doped silica membrane material calcined in H2 atmosphere are much higher than those calcined in N2 atmosphere. Compared with N2 atmosphere, the palladium-doped silica membranes calcined in H2 atmosphere showed higher H2 permeability and H2/CO2 selectivity before and after the steam exposure. The apparent activation energy of H2 permeation through the palladium-doped silica membrane calcined under H2 atmosphere (2.51 ± 0.05 kJ/mol) was slightly lower than that calcined under N2 atmosphere (2.84 ± 0.04 kJ/mol). Calcination atmosphere plays some role in membrane performance, which has greater influence on the permeance than on the gas permselectivity. Calcination under H2 atmosphere is well conducive to improve the gas permeance and H2 permselectivity of palladium-doped silica membrane.
Introducing continuous experimentation in large software-intensive product and service organisations
(2017)
Software development in highly dynamic environments imposes high risks to development organizations. One such risk is that the developed software may be of only little or no value to customers, wasting the invested development efforts.Continuous experiment ation, as an experiment-driven development approach, may reduce such development risks by iteratively testing product and service assumptions that are critical to the success of the software. Although several experiment-driven development approaches are available, there is little guidance available on how to introduce continuous experimentation into an organization. This article presents a multiple-case study that aims at better understanding the process of introducing continuous experimentation into an organization with an already established development process. The results from the study show that companies are open to adopting such an approach and learning throughout the introduction process. Several benefits were obtained, such as reduced development efforts, deeper customer insights, and better support for development decisions. Challenges included complex stakeholder structures, difficulties in defining success criteria, and building experimen- tation skills. Our findings indicate that organizational factors may limit the benefits of experimentation. Moreover, introducing continuous experimentation requires fundamental changes in how companies operate, and a systematic introduction process can increase the chances of a successful start.
Context: Companies need capabilities to evaluate the customer value of software intensive products and services. One way of systematically acquiring data on customer value is running continuous experiments as part of the overall development process. Objective: This paper investigates the first steps of transitioning towards continuous experimentation in a large company, including the challenges faced. Method: We conduct a single-case study using participant observation, interviews, and qualitative analysis of the collected data. Results: Results show that continuous experimentation was well received by the practitioners and practising experimentation helped them to enhance understanding of their product value and user needs. Although the complexities of a large multi-stakeholder business to-business (B2B) environment presented several challenges such as inaccessible users, it was possible to address impediments and integrate an experiment in an ongoing development project. Conclusion: Developing the capability for continuous experimentation in large organisations is a learning process which can be supported by a systematic introduction approach with the guidance of experts. We gained experience by introducing the approach on a small scale in a large organisation, and one of the major steps for future work is to understand how this can be scaled up to the whole development organisation.
Purpose: Human breath analysis is proposed with increasing frequency as a useful tool in clinical application. We performed this study to find the characteristic volatile organic compounds (VOCs) in the exhaled breath of patients with idiopathic pulmonary fibrosis (IPF) for discrimination from healthy subjects. Methods: VOCs in the exhaled breath of 40 IPF patients and 55 healthy controls were measured using a multi-capillary column and ion mobility spectrometer. The patients were examined by pulmonary function tests, blood gas analysis, and serum biomarkers of interstitial pneumonia. Results: We detected 85 VOC peaks in the exhaled breath of IPF patients and controls. IPF patients showed 5 significant VOC peaks; p-cymene, acetoin, isoprene, ethylbenzene, and an unknown compound. The VOC peak of p-cymene was significantly lower (p < 0.001), while the VOC peaks of acetoin, isoprene, ethylbenzene, and the unknown compound were significantly higher (p < 0.001 for all) compared with the peaks of controls. Comparing VOC peaks with clinical parameters, negative correlations with VC (r =−0.393, p = 0.013), %VC (r =−0.569, p < 0.001), FVC (r = −0.440, p = 0.004), %FVC (r =−0.539, p < 0.001), DLco (r =−0.394, p = 0.018), and %DLco (r =−0.413, p = 0.008) and a positive correlation with KL-6 (r = 0.432, p = 0.005) were found for p-cymene. Conclusion: We found characteristic 5 VOCs in the exhaled breath of IPF patients. Among them, the VOC peaks of p-cymene were related to the clinical parameters of IPF. These VOCs may be useful biomarkers of IPF.
This review gives a short overview of the physical processes involved in the formation of the polyelectrolyte multilayers (PEMs) and their destruction. These two processes are vital for the formation of PEMs with desired physical and chemical structures, and for loading them with active substances and their spatial controlled release. It includes a survey of the physical and chemical properties that are key points for controlling film nanostructure in relation to biological processes and different possibilities for controlling cell behavior by means of film composition, bioactivity, mechanical properties, and three-dimensional organization.
In this paper, it aims to model wind speed time series at multiple sites. The five-parameter Johnson distribution is deployed to relate the wind speed at each site to a Gaussian time series, and the resultant m-dimensional Gaussian stochastic vector process Z(t) is employed to model the temporal-spatial correlation of wind speeds at m different sites. In general, it is computationally tedious to obtain the autocorrelation functions (ACFs) and cross-correlation functions (CCFs) of Z(t), which are different to those of wind speed times series. In order to circumvent this correlation distortion problem, the rank ACF and rank CCF are introduced to characterize the temporal-spatial correlation of wind speeds, whereby the ACFs and CCFs of Z(t) can be analytically obtained. Then, Fourier transformation is implemented to establish the cross-spectral density matrix of Z(t), and an analytical approach is proposed to generate samples of wind speeds at m different sites. Finally, simulation experiments are performed to check the proposed methods, and the results verify that the five-parameter Johnson distribution can accurately match distribution functions of wind speeds, and the spectral representation method can well reproduce the temporal-spatial correlation of wind speeds.
Die Coronapandemie hat Deutschland seit dem Frühjahr 2020 fest im Griff. Eine zentrale Maßnahme zur Verlangsamung der Ausbreitung des Coronavirus war von Beginn an die Schließung von Schulen. In einer ersten Studie wurden die Lernzeitverluste durch die Corona-bedingten Schulschließungen im Frühjahr 2020 quantifiziert (Wößmann, Freundl, Lergetporer, Grewenig, Werner & Zierow, 2020). Es zeigte sich, dass sich die Lernzeit der Schülerinnen und Schüler durch die Schulschließungen halbiert hatte und die Verluste bei leistungsschwächeren Schülerinnen und Schülern besonders groß waren. Im Frühjahr 2020 wurde die Verringerung der Lernzeit von den Schulen nicht kompensiert: Nur ein kleiner Teil der Schülerinnen und Schüler hatte in dieser Phase regelmäßigen Distanzunterricht und täglichen Kontakt mit Lehrkräften. Während der Sommer- und Herbstmonate seit der Phase der ersten Schulschließungen hatten Schulverwaltung, Schulen und Lehrkräfte Zeit, sich auf Distanzunterricht und digitale Lehrmethoden umzustellen, um Lernausfällen während etwaiger erneuter Schulschließungen entgegenzuwirken. Inwiefern dies dazu geführt hat, dass die Schülerinnen und Schüler während der Schulschließungen Anfang 2021 tatsächlich mehr Zeit mit Lernen verbracht haben als im Frühjahr 2020, ist jedoch bislang weitgehend unbekannt.
Um zu erfahren, mit welchen Aktivitäten die Schulkinder die Zeit der Schulschließungen Anfang 2021 verbracht haben, wurde erneut eine deutschlandweite Umfrage durchgeführt, diesmal unter mehr als 2.000 Eltern von Schulkindern. Die Ergebnisse liefern umfassende Einblicke in den Alltag von Schulkindern, Eltern und Schulen während der Schulschließungen Anfang 2021. Sie zeigen, wie viele Stunden die Schulkinder in dieser Phase mit Lernen und anderen kreativen und passiven Tätigkeiten verbracht haben, welche konkreten Maßnahmen die Schulen ergriffen haben, um den Schulbetrieb aufrechtzuerhalten, wie effektiv das Lernen zu Hause war, und wie die Eltern das häusliche Lernumfeld einschätzen. Dabei vergleichen wir die Aktivitäten während der Schulschließungen Anfang 2021 mit den Aktivitäten während der ersten Corona-bedingten Schulschließungen im Frühjahr 2020 sowie mit den Aktivitäten vor Corona (vgl. Wößmann et al., 2020). Wir berichten zudem Ergebnisse zum sozio-emotionalen Wohlbefinden der Kinder nach einem Jahr Coronapandemie und zu den Einschätzungen der Eltern, welche breiteren Auswirkungen die Schulschließungen auf verschiedene Lebensbereiche ihrer Kinder haben. Die Befragung liefert somit neue empirische Erkenntnisse über mögliche Folgen der Corona-Krise für den Bildungserfolg von Kindern in Deutschland. Dabei untersuchen wir auch, inwiefern sich die Auswirkungen der Schulschließungen zwischen leistungsstärkeren und -schwächeren Schülerinnen und Schülern sowie zwischen Akademikerkindern und Nicht-Akademikerkindern unterscheiden.
Continuous refactoring is necessary to maintain source code quality and to cope with technical debt. Since manual refactoring is inefficient and error prone, various solutions for automated refactoring have been proposed in the past. However, empirical studies have shown that these solutions are not widely accepted by software developers and most refactorings are still performed manually. For example, developers reported that refactoring tools should support functionality for reviewing changes. They also criticized that introducing such tools would require substantial effort for configuration and integration into the current development environment.
In this paper, we present our work towards the Refactoring-Bot, an autonomous bot that integrates into the team like a human developer via the existing version control platform. The bot automatically performs refactorings to resolve code smells and presents the changes to a developer for asynchronous review via pull requests. This way, developers are not interrupted in their workflow and can review the changes at any time with familiar tools. Proposed refactorings can then be integrated into the code base via the push of a button. We elaborate on our vision, discuss design decisions, describe the current state of development, and give an outlook on planned development and research activities.
Lehr- und Übungsbuch sowie Nachschlagewerk zur CAD-Software Creo Parametric und zu den Grundlagen der Produktdatenverwaltung mit Windchill. Vermittelt werden die Volumenmodellierung, die 3D Flächenmodellierung, die Blechmodellierung, die Baugruppen- und Zeichnungserstellung, das Erstellen von Animationen, die Definition und Anwendung kinematischer sowie dynamischer Analysen und die Definition von Baugruppen, die Konstruktionsvarianten "Top-Down" und "Bottom-Up" sowie die Organisation von Konstruktionsprojekten über Skelett Techniken.
Weiter werden die Grundlagen des Produktdatenmanagements im Konstruktionsbereich unter Windchill vermittelt. Alle Verfahren werden handlungsorientiert an einem weitgehend durchgehenden Modellierungsprojekt erarbeitet. Aufgrund des ausführlichen Inhalts- und Sachwortverzeichnisses sowie einer Vielzahl an Bildern ist das Buch als Grundlage für Vorlesungen, Schulungen oder Praktika und insbesondere auch zum Selbststudium sowie als Nachschlagewerk geeignet.
Lehrbuch zur CAD-Software Creo Parametric und zur Produktdatenverwaltung mit Windchill.
3D-Volumenmodellierung, 3D-Flächenmodellierung, Blechmodellierung, Baugruppen- und Zeichnungserstellung, Definition von Normteilen, Erstellen von Animationen und dynamischen Analysen.
Verfahren zum Umgang mit großen Baugruppen und zur flexiblen Modellierung, Konstruk-tionsvarianten "Top-Down" und "Bottom-Up", Organisation von Konstruktionsprojekten über Skeletttechnik.
Neu: Konstruktion von und mit Mehrkörperobjekten, Rahmenkonstruktion in der Profilumgebung (AFX), intelligente Verbindungen (IFX), Live Simulation und Generatives Design.
Here, we report the mechanical and water sorption properties of a green composite based on Typha latifolia fibres. The composite was prepared either completely binder-less or bonded with 10% (w/w) of a bio-based resin which was a mixture of an epoxidized linseed oil and a tall-oil based polyamide. The flexural modulus of elasticity, the flexural strength and the water absorption of hot pressed Typha panels were measured and the influence of pressing time and panel density on these properties was investigated. The cure kinetics of the biobased resin was analyzed by differential scanning calorimetry (DSC) in combination with the iso-conversional kinetic analysis method of Vyazovkin to derive the curing conditions required for achieving completely cured resin. For the binderless Typha panels the best technological properties were achieved for panels with high density. By adding 10% of the binder resin the flexural strength and especially the water absorption were improved significantly.
Powder coating of engineered wood panels such as medium density fibreboards (MDF) is gaining industrial interest due to ecological and economic advantages of powder coating technology. For transferring powder coating technology to temperature-sensitive substrates like MDF, a thorough understanding of the melting, flowing and curing behaviour of the used low-bake resins is required. In the present study, thermo-analysis in combination with iso-conversional kinetic data analysis as well as rheometry is applied to characterise the properties of an epoxy-based powder coating. Neat resin and cured powder coating films are examined in order to define an ideal production window within which the resin is preferably applied and processed to yield satisfactory surface performance on the one hand and without exposing the carrier MDF too high a temperature load on the other hand to prevent the panel from deteriorating in mechanical strength. In order to produce powder coated films of high surface gloss – a feature that has not yet successfully been realized on MDF with powder coatings – a new curing technology, in-mould surface finishing, has been applied.
Within the scope of the present cumulative doctoral thesis six scientific papers were published which illustrates that modern reaction model-free (=isoconversional) kinetic analysis (ICKA) methods represents a universal and effective tool for the controlled processing of thermosetting materials. In order to demonstrate the universal applicability of ICKA methods, the thermal cure of different thermosetting materials having a very broad range of chemical composition (melamine-formaldehyde resins, epoxy resins, polyester-epoxy resins, and acrylate/epoxy resins) were analyzed and mathematically modelled. Some of the materials were based on renewable resources (an epoxy resin was made from hempseed oil; linseed oil was modified into an acrylate/epoxy resin). With the aid of ICKA methods not only single-step but also complex multi-step reactions were modelled precisely. The analyzed thermosetting materials were combined with wood, wood-based products, paper, and plant fibers which are processed to various final products. Some of the thermosetting materials were applied as coating (in form of impregnated décor papers or powder and wet coatings respectively) on wood substrates and the epoxy resin from hempseed oil was mixed with plant fibers and processed into bio-based composites for lightweight applications. From the final products mechanical, thermal, and surface properties were determined. The activation energy as function of cure conversion derived from ICKA methods was utilized to predict accurately the thermal curing over the course of time for arbitrary cure conditions. Furthermore the cure models were used to establish correlations between the cross-linking during processing into products and the properties of the final products. Therewith it was possible to derive the process time and temperature that guarantee optimal cross-linking as well as optimal product properties
A millimeter-wave power amplifier concept in an advanced silicon germanium (SiGe) BiCMOS technology is presented. The goal of the concept is to investigate the impact of physical limitations of the used heterojunction bipolar transistors (HBT) on the performance of a 77 GHz power amplifier. High current behavior, collectorbase breakdown and transistor saturation can be forced with the presented design. The power amplifier is manufactured in an advanced SiGe BiCMOS technology at Infineon Technologies AG with a maximum transit frequency fT of around 250 GHz for npn HBT’s [1]. The simulation results of the power amplifier show a saturated output power of 16 dBm at a power added efficiency of 13%. The test chip is designed for a supply voltage of 3.3 V and requires a chip size of 1.448 x 0.930 mm².
The dawn of the 21st Century has witnessed a tremendous increase in trade pacts among nations, resulting in renewed hopes for sustainable enterprise development in emerging economies worldwide. Ghana and other sub-Saharan African (SSA) countries have signed onto several North-South and South-South free trade agreements with the hope of strengthening their presence in the international trade arena, and to promote economic growth in SSA. For over two decades, however, very little has changed, and many have dashed their high hopes as enterprises continue to struggle in SSA. Not even the African Continental Free Trade Agreement (AfCFTA) could renew the hopes of sceptics. Several studies opined that enterprises in SSA could improve their domestic and international competitiveness by establishing mutually beneficial partnerships with their counterparts from the Global North and South. This study delved into the issues that affect North-South and South-South business collaborations and recommends key success factors that could help promote mutually beneficial cross-border business partnerships. The research includes both literature and empirical information on the key success factors of business partnerships between African enterprises as well as between African enterprises and firms from the Global North. We approached the study qualitatively using a phenomenological research design. Research participants included important stakeholders in Africa and Europe's international trade and sustainable enterprise development ecosystem. The study identified several challenges with the current business collaborations and recommended new ways of making such partnerships more beneficial.
CODE RED FOR HUMANITY. The alarm bells are deafening, and the evidence is irrefutable: greenhouse-gas emissions from fossil-fuel burning and deforestation are choking our planet and putting billions of people at immediate risk. Global heating is affecting every region on Earth, with many of the changes becoming irreversible. (Guterres 2021)
The digitalisation ongoing in households and sustainability-related challenges are multifaceted and complex. The introducing quote of the United Nations Secretary-General refers to the latest report of the Intergovernmental Panel on Climate Change (IPCC), emphasising the urgency to act – now. As of today, becoming a sustainable population is still a distant destination. As outlined in the previous chapters, the challenges associated with that transformation remain huge, complex, and largely unsolved. Recent dramas such as the power incident in Texas (2021), the floods in Germany (2021), or the drought in sub-Saharan Africa (2020s) – are just a few of the uncountable issues stirring up the debate about fossil-fuel abandonment and the timing of climate neutrality. Business research can actually be accused of referring to the persistent focus on gains and growth, despite early warnings for society at large (e.g., Meadows et al., 1972; Kölsch & Veit, 1981; Veit & Thatcher, 2023). However, academic researchers, corporations, and society are now waking up, as shown by the climate change conference. In fact, it appears that the information systems (IS) discipline just began tackling mammoth challenges around climate change within the last decade (Melville, 2010; Watson et al., 2010). The central discussion in emerging work revolves around the role and use of digital technologies on the path to a healthy planet. But while early studies have focused on organisational settings (e.g., Gholami et al., 2016; Seidel et al., 2013), increasingly research addresses private settings (e.g., Wunderlich et al., 2019).
Aimed at the problem that the accuracy of face image classification in complex environment is not high, a network model F-Net suitable for aesthetic classification of face images is proposed. Based on LeNet-5, the model uses convolutional layers to extract facial image features in complex backgrounds, optimized parameters in the network model, and changes the number of convolutional layers and fully connected layer feature elements in the model. The experimental results show that the F-Net network model proposed in this paper has a face image classifation accuracy of 73% in complex environment background, which is better than other classical convolutional neural network classification models.