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Appropriate mechanical properties and fast endothelialization of synthetic grafts are key to ensure long-term functionality of implants. We used a newly developed biostable polyurethane elastomer (TPCU) to engineer electrospun vascular scaffolds with promising mechanical properties (E-modulus: 4.8 ± 0.6 MPa, burst pressure: 3326 ± 78 mmHg), which were biofunctionalized with fibronectin (FN) and decorin (DCN). Neither uncoated nor biofunctionalized TPCU scaffolds induced major adverse immune responses except for minor signs of polymorph nuclear cell activation. The in vivo endothelial progenitor cell homing potential of the biofunctionalized scaffolds was simulated in vitro by attracting endothelial colony-forming cells (ECFCs). Although DCN coating did attract ECFCs in combination with FN (FN + DCN), DCN-coated TPCU scaffolds showed a cell-repellent effect in the absence of FN. In a tissue-engineering approach, the electrospun and biofunctionalized tubular grafts were cultured with primary-isolated vascular endothelial cells in a custom-made bioreactor under dynamic conditions with the aim to engineer an advanced therapy medicinal product. Both FN and FN + DCN functionalization supported the formation of a confluent and functional endothelial layer.
It has been widely shown that biomaterial surface topography can modulate host immune response, but a fundamental understanding of how different topographies contribute to pro-inflammatory or anti-inflammatory responses is still lacking. To investigate the impact of surface topography on immune response, we undertook a systematic approach by analyzing immune response to eight grades of medical grade polyurethane of increasing surface roughness in three in vitro models of the human immune system. Polyurethane specimens were produced with defined roughness values by injection molding according to the VDI 3400 industrial standard. Specimens ranged from 0.1 μm to 18 μm in average roughness (Ra), which was confirmed by confocal scanning microscopy. Immunological responses were assessed with THP-1-derived macrophages, human peripheral blood mononuclear cells (PBMCs), and whole blood following culture on polyurethane specimens. As shown by the release of pro-inflammatory and anti-inflammatory cytokines in all three models, a mild immune response to polyurethane was observed, however, this was not associated with the degree of surface roughness. Likewise, the cell morphology (cell spreading, circularity, and elongation) in THP-1-derived macrophages and the expression of CD molecules in the PBMC model on T cells (HLA-DR and CD16), NK cells (HLA-DR), and monocytes (HLA-DR, CD16, CD86, and CD163) showed no influence of surface roughness. In summary, this study shows that modifying surface roughness in the micrometer range on polyurethane has no impact on the pro-inflammatory immune response. Therefore, we propose that such modifications do not affect the immunocompatibility of polyurethane, thereby supporting the notion of polyurethane as a biocompatible material.
3D assisted 2D face recognition involves the process of reconstructing 3D faces from 2D images and solving the problem of face recognition in 3D. To facilitate the use of deep neural networks, a 3D face, normally represented as a 3D mesh of vertices and its corresponding surface texture, is remapped to image-like square isomaps by a conformal mapping. Based on previous work, we assume that face recognition benefits more from texture. In this work, we focus on the surface texture and its discriminatory information content for recognition purposes. Our approach is to prepare a 3D mesh, the corresponding surface texture and the original 2D image as triple input for the recognition network, to show that 3D data is useful for face recognition. Texture enhancement methods to control the texture fusion process are introduced and we adapt data augmentation methods. Our results show that texture-map-based face recognition can not only compete with state-of-the-art systems under the same precon ditions but also outperforms standard 2D methods from recent years.
”I have never seen one who loves virtue as much as he loves beauty,” Confucius once said. If beauty is more important as goodness, it becomes clear why people invest so much effort in their first impression. The aesthetic of faces has many aspects and there is a strong correlation to all characteristics of humans, like age and gender. Often, research on aesthetics by social and ethic scientists lacks sufficient labelled data and the support of machine vision tools. In this position paper we propose the Aesthetic-Faces dataset, containing training data which is labelled by Chinese and German annotators. As a combination of three image subsets, the AF-dataset consists of European, Asian and African people. The research communities in machine learning, aesthetics and social ethics can benefit from our dataset and our toolbox. The toolbox provides many functions for machine learning with state-of-the-art CNNs and an Extreme-Gradient-Boosting regressor, but also 3D Morphable Model technolo gies for face shape evaluation and we discuss how to train an aesthetic estimator considering culture and ethics.
Deep learning-based fabric defect detection methods have been widely investigated to improve production efficiency and product quality. Although deep learning-based methods have proved to be powerful tools for classification and segmentation, some key issues remain to be addressed when applied to real applications. Firstly, the actual fabric production conditions of factories necessitate higher real-time performance of methods. Moreover, fabric defects as abnormal samples are very rare compared with normal samples, which results in data imbalance. It makes model training based on deep learning challenging. To solve these problems, an extremely efficient convolutional neural network, Mobile-Unet, is proposed to achieve the end-to-end defect segmentation. The median frequency balancing loss function is used to overcome the challenge of sample imbalance. Additionally, Mobile-Unet introduces depth-wise separable convolution, which dramatically reduces the complexity cost and model size of the network. It comprises two parts: encoder and decoder. The MobileNetV2 feature extractor is used as the encoder, and then five deconvolution layers are added as the decoder. Finally, the softmax layer is used to generate the segmentation mask. The performance of the proposed model has been evaluated by public fabric datasets and self-built fabric datasets. In comparison with other methods, the experimental results demonstrate that segmentation accuracy and detection speed in the proposed method achieve state-of-the-art performance.
Im Projekt GalvanoFlex_BW sind verschiedene Möglichkeiten zur Verbesserung der Energieeffizienz von energieintensiven Industrieunternehmen aufgezeigt und untersucht worden. Die Einführung der KWK im stromoptimierten Betrieb stellte dabei einen besonders betrachteten Aspekt dar. Neben der technischen Untersuchung ist zudem eine sozialwissenschaftliche Betrachtung vorgenommen worden, um die Einführung und Umsetzung entsprechender Maßnahmen auch unter diesem Aspekt zu betrachten. Ein zusätzlicher wichtiger Schwerpunkt des Projektes war die Übertragung des erarbeiteten Wissens an weitere Unternehmen, Institutionen etc., die nicht direkt am Projekt beteiligt waren.
Durch die Zusammenarbeit von vier Forschungs- und drei Industriepartnern sind die Arbeiten praxisorientiert auf Basis realer Messdaten sowie im Zuge von Befragungen der handelnden Personen bei den Projektpartnern im Sinne eines Reallabors durchgeführt worden.
Die Notwendigkeit zur Einsparung von Energie und damit zur Umsetzung von Effizienzmaßnahmen ist ein wichtiger Schritt, um die von der EU geplante Reduktion von Treibhausgasen zu erreichen. Darüber hinaus ist zu erwarten, dass die Energiekosten auch zukünftig weiter ansteigen. Dadurch werden Maßnahmen zur Steigerung der Energieeffizienz zu einem wichtigen Element, eine wettbewerbsfähige Produktion zu gewährleisten. Im Rahmen des Projektes sind deshalb verschiedene Energieeffizienzmaßnahmen speziell für die Galvanotechnik recherchiert, analysiert und in einen Maßnahmenkatalog überführt worden. Des Weiteren wurde eine Bewertungsmethode entwickelt, die die Unternehmen der Galvanotechnik bei der Identifikation von sinnvollen Energieeffizienzmaßnahmen unterstützen soll.
Bei den Untersuchungen zur Umsetzung von Kraft-Wärme-Kopplungsanlagen konnte am Beispiel von zwei Unternehmen mit stark unterschiedlichen Strom- und Wärmebedarfswerten gezeigt werden, dass der Einsatz entsprechender Anlagen wirtschaftlich lohnenswert ist. Im günstigsten Fall ergeben sich Amortisationszeiten von etwa zwei Jahren. Es hat sich weiterhin gezeigt, dass die Auslegung des Block-heizkraftwerkes stark von den Strom- und Wärmebedarfswerten abhängt und dass der Pufferspeicher keinesfalls zu klein ausgelegt werden sollte. Eine intelligente stromoptimierte Steuerung mit Lastspitzenmanagement kann die Wirtschaftlichkeit jedoch häufig nur noch wenig gegenüber dem wärmegeführten Betrieb verbessern. Ursache dafür ist, dass das derzeitige Förder- und Vergütungssystem für Kraft-Wärme-Kopplungsanlagen nahezu keine Anreize für einen am Strombedarf und damit an der Deckung von Residuallast orientierten Betrieb bietet. Einzig bei Unternehmen mit ausgeprägten Spitzen im Strombezug, kann der gezielte Einsatz eines Blockheizkraftwerkes zu einer signifikanten Senkung des Leistungspreises führen.
Darüber hinaus ist die Einführung einer Kraft-Wärme-Kopplungsanlage generell als komplexe Energieeffizienzmaßnahme anzusehen, die deshalb neben den wirtschaftlichen Aspekten erhöhte Anforderungen an die Unternehmen und das professionelle Umfeld stellt, die im Rahmen der sozialwissenschaftlichen Begleitforschung untersucht worden sind. Dabei konnten Treiber aber auch Hemmnisse zur Umsetzung der Technologie sowohl innerhalb der Unternehmen als auch außerhalb identifiziert werden. Die internen Hemmnisse sind dabei auf unterschiedliche Ursachen zurückzuführen, wie die hohe Komplexität der KWK-Technologie, die schwierige Bewertung des Gesamtnutzens im Unternehmen, die mangelnde personelle Ausstattung und fehlende Unternehmerentscheidungen. Abhilfe schaffen, und damit als Treiber wirken, können hier ein verbessertes Beratungsangebot insbesondere seitens neutraler Stellen sowie der Anlagenbetrieb im Contracting.
Die Übertragung der im Projekt erarbeiteten Ergebnisse ist bereits während der Projektlaufzeit über die Branchenplattform im Zuge verschiedener Workshops, die speziell auf Unternehmen und Institutionen außerhalb des Projektkonsortiums ausgerichtet waren, erfolgt. Zur Verstärkung der Verbreitung des erarbeiteten Wissens ist zum Projektende eine Serie aus vier Fachartikeln in einem namhaften Branchenmagazin erschienen, und es ist eine Internetseite zum Projekt erstellt worden (www.galvanoflex_bw.de). Letztere hat dabei nicht nur die Aufgabe der Wissensverbreitung, sondern sie soll auch über das Projektende hinaus als Kontaktplattform dienen, um die Umsetzung von Effizienzmaßnahmen mit dem im Projekt generierten Wissen zu unterstützen.
With the continuous development of economy, consumers pay more attention to the demand for personalization clothing. However, the recommendation quality of the existing clothing recommendation system is not enough to meet the user’s needs. When browsing online clothing, facial expression is the salient information to understand the user’s preference. In this paper, we propose a novel method to automatically personalize clothing recommendation based on user emotional analysis. Firstly, the facial expression is classified by multiclass SVM. Next, the user’s multi-interest value is calculated using expression intensity that is obtained by hybrid RCNN. Finally, the multi-interest value is fused to carry out personalized recommendation. The experimental results show that the proposed method achieves a significant improvement over other algorithms.
Sol-Gel basierte Flammschutzmittel stellen einen vielversprechenden Ansatz für Textilien dar, gerade im Bereich des Ersatzes von derzeit etablierten halogenhaltigen Flammschutzmitteln. Letztere sind aufgrund ihrer toxikologisch Bedenklichkeit sowie ihrer mitunter bioakkumulierenden Eigenschaften in die Kritik geraten. In diesem Forschungsvorhaben wurde daher untersucht wie aus Phosphor- und stickstoffhaltige Silane halogenfreie Flammschutzmittel verwirklicht werden können. Die Sol-Gel-Schicht fungierte dabei zum einen als nicht brennbarer Binder, zum anderen konnten über das Anbinden von Phosphorgruppen in an kommerziell verfügbare Silane Flammschutz aktive Gruppen direkt mit eingebunden werden. Verschiedene Syntheseansätze wurden dabei verfolgt, wobei durch alle hergestellten N-P-Silane ein Flammschutz nach DIN EN ISO 15025 (Schutzkleidung – Schutz gegen Hitze und Flammen) erhalten wurden. Dabei hängt die Flammschutzwirkung stark von den funktionellen Gruppen und der Oxidationsstufe des Phosphors ab, dabei konnte ein entsprechender Flammschutz bei Auflagen von 5 % erzielt werden. Es konnte gezeigt werden, dass ein Mechanismus auf Basis der Bildung einer Schutzschicht hauptsächlich verantwortlich für den Flammschutz ist. Dieses Ergebnis ist für eine zukünftige, weitere Optimierung entsprechender Ausrüstungen nicht zu unterschätzen. Durch Ausrüstungsversuche im semi-industriellen Maßstab konnte weiterhin gezeigt werden, dass einer großtechnischen Umsetzung der angewandten Ausrüstungen prinzipiell nichts im Wege steht. Je nach funktioneller Gruppe am Phosphor konnte die Wasserlöslichkeit und die Waschstabilität kontrolliert werden. Dabei konnte zum einen gezeigt werden, dass hydrophobes N-P-Silane eine bessere Waschbeständigkeit aufweisen, hydrophile N-P-Silane erhalten diese erst bei Fixierungstemperaturen von 180 °C. Ausgehend von den Ergebnissen konnten sticktstoffgenerierende und cyanursäure-basierte N-P-Silane entwickelt werden, welche sich besonders in einer guten Flammschutzwirkung bei Mischgeweben auszeichnen. Insgesamt konnte innerhalb des Forschungsvorhabens gezeigt werden, dass N-P-Silane hervorragende permanente Flammschutzmittel für Textilien sind und auf welchem Mechanismus dieser Flammschutz begründet ist.
The design process for a single phase, smart, universal charger for light electric vehicles, is presented. With a step up, power factor correction circuit, followed by a phase shifted, full bridge converter, with synchronous rectification on the secondary side. Due to the resistor-capacitor-diode snubber on the secondary side, the current peak at the start of power transfer, leads to false triggering during light load control with peak current mode control. The solution developed for light loads, is to change from peak current control to voltage control. This is achieved by limiting the maximum phase shift, instead of changing the reference value. For the power factor correction stage, measured and calculated efficiencies are compared as a function of the output power. The voltage and current waveforms are shown for the power factor correction circuit, and for the phase shifted bridge, the measured current waveform is compared with simulation.
Enhancing data-driven algorithms for human pose estimation and action recognition through simulation
(2020)
Recognizing human actions, reliably inferring their meaning and being able to potentially exchange mutual social information are core challenges for autonomous systems when they directly share the same space with humans. Intelligent transport systems in particular face this challenge, as interactions with people are often required. The development and testing of technical perception solutions is done mostly on standard vision benchmark datasets for which manual labelling of sensory ground truth has been a tedious but necessary task. Furthermore, rarely occurring human activities are underrepresented in these datasets, leading to algorithms not recognizing such activities. For this purpose, we introduce a modular simulation framework, which offers to train and validate algorithms on various human-centred scenarios. We describe the usage of simulation data to train a state-of-the-art human pose estimation algorithm to recognize unusual human activities in urban areas. Since the recognition of human actions can be an important component of intelligent transport systems, we investigated how simulations can be applied for his purpose. Laboratory experiments show that we can train a recurrent neural network with only simulated data based on motion capture data and 3D avatars, which achieves an almost perfect performance in the classification of those human actions on real data.
Facial expressions play a dominant role in facilitating social interactions. We endeavor to develop tactile displays to reinstate facial expression modulated communication. The high spatial and temporal dimensionality of facial movements poses a unique challenge when designing tactile encodings of them. A further challenge is developing encodings that are at-tuned to the perceptual characteristics of our skin. A caveat of using vibrotactile displays is that tactile stimuli have been shown to induce perceptual tactile aftereffects when used on the fingers, arm and face. However, at present, despite the prevalence of waist-worn tactile displays, no such investigations of tactile aftereffects at the waist region exist in the literature, though they are warranted by the unique sensory and perceptual signalling characteristics of this area. Using an adaptation paradigm we investigated the presence of perceptual tactile aftereffects induced by continuous and burst vibrotactile stimuli delivered at the navel, side and spinal regions of the waist. We report evidence that the tactile perception topology of the waist is non-uniform, and specifically that the navel and spine regions are resistant to adaptive aftereffects while side regions are more prone to perceptual adaptations to continuous but not burst stimulations. Results of our current investigations highlight the unique set of challenges posed by designing waist-worn tactile displays. These and future perceptual studies can directly inform more realistic and effective implementations of complex high-dimensional spatiotemporal social cues.
Automatic anode rod inspection in aluminum smelters using deep-learning techniques: a case study
(2020)
Automatic fault detection using machine learning has become an exciting and promising area of research. This because it accurate and timely way to manage and classify with minimal human effort. In the computer vision community, deep-learning methods have become the most suitable approaches for this task. Anodes are large carbon blocks that are used to conduct electricity during the aluminum reduction process. The most basic function of anode rod inspection is to prevent a situation where the anode rod will not fit into the stub-holes of a new anode. It would be the case for a rod containing either severe toe-in, missing stubs, or a retained thimble on one or more stubs. In this work, to improve the accuracy of shape defect inspection for an anode rod, we use the Fast Region-based Convolutional Network method (Fast R-CNN), model. To train the detection model, we collect an image dataset composed of multi-class of anode rod defects with annotated labels. Our model is trained using a small number of samples, an essential requirement in the industry where the number of available defective samples is limited. It can simultaneously detect multi-class of defects of the anode rod in nearly real-time.
Die Blockchain-Technologie stellt einen vielversprechenden Ansatz für Transparenz und Resilienz in Lieferketten dar. In diesem Beitrag wird untersucht, welche Blockchain-Lösungen derzeit für die Supply-Chain zur Verfügung stehen, und die bislang umgesetzten Projekte in diesem Bereich analysiert. Die meisten der realisierten Projekte beziehen sich auf einfache Produkte und Supply-Chain-Strukturen. Der Grund ist, dass bislang Lösungen zur ganzheitlichen Abbildung von komplexen Produkten in dynamischen Supply-Chain-Strukturen gefehlt haben. Doch jetzt stehen erste vielversprechende Ansätze zur Verfügung.
Deutschland, quo vadis?
(2020)
Shutdown in Deutschland im März 2020. Stillstand in Handel und Industrie. Der Börsenwert einer beachtlichen Anzahl von Unternehmen hat sich in kürzester Zeit halbiert. Anleger warfen alles auf den Markt. Und bei der hohen Unsicherheit verloren sämtliche Anlageklassen, zeitweise sogar Gold. Selbst Konzerne wie die Lufthansa werden es ohne Staatshilfe nicht mehr schaffen zu existieren.
Melamine-formaldehyde resins are widely used for decorative paper impregnation. Resin properties relevant for impregnation are mainly determined already at the stage of resin synthesis by the applied reaction conditions. Thus, understanding the relationship between reaction conditions and technological properties is important. Response surface methodology based on orthogonal parameter level variations is the most suitable tool to identify and quantify factor effects and deduce causal correlation patterns. Here, two major process factors of MF resin synthesis were systematically varied using such a statistical experimental design. To arrive at resins having a broad range of technological properties, initial pH and M:F ratio were varied in a wide range (pH: 7.9–12.1; M:F ratio: 1:1.5–1:4.5). The impregnation behavior of the resins was modeled using viscosity, penetration rate and residual curing capacity as technological responses. Based on the response surface models, nonlinear and synergistic action of process factors was quantified and a suitable process window for preparing resins with favorable impregnation performance was defined. It was found that low M:F ratios (~1:2–1:2.5) and comparatively high starting pHs (~pH 11) yield impregnation resins with rapid impregnation behavior and good residual curing capacity.
In modernen Arbeitswelten werden zunehmend arbeitsplatzbezogene digitale Technologien eingesetzt. Wenngleich dies zahlreiche Chancen bietet, kann es auch negative Folgen für die Gesundheit von Mitarbeitenden haben. Diese Herausforderungen werden durch die aktuelle Corona-Krise für viele Unternehmen noch verschärft. Stress, der direkt oder indirekt durch den Einsatz von Technologien entsteht, wird als «Technostress» bezeichnet. Wichtige Hebel zu dessen Vermeidung umfassen die Gestaltung von Technologien sowie die Berücksichtigung verschiedener individueller und situativer Faktoren im Rahmen technologischer Veränderungsprozesse.
Durch die Digitalisierung der Arbeitswelt und die New Work-Bewegung verändert sich die Art und Weise, wie wir zu-ammenarbeiten. Entsprechend wird derzeit viel über Führung gesprochen – möglicherweise zu viel. Die zentrale These des Beitrags ist, dass wir besser verstehen können, wie Führungskräften und Mitarbeitende zukunftsorientiert zusam-menarbeiten, wenn wir weniger direkt über Führung reden, sondern zunächst von der Situation aus denken, in der sich Akteure koordinieren. Führung wird dann nicht isoliert, sondern zusammen mit verschiedenen Koordinationsformen betrachtet (wie Autonomie, Selbstorganisation, Management und eben Führung). Das kann in der Praxis helfen, den Wandel der Zusammenarbeit – inklusive der neuen Art von Führung – reflektierter und zielorientierter zu gestalten.
In digital transformierten Arbeitswelten organisieren die Mitarbeitenden ihre Arbeitszeit, ihren Arbeitsort und die Art und Weise, wie sie Aufgaben erledigen, in größerem Umfang selbst. Unternehmen, die im Zuge des Transformationsprozesses den Grad der Selbstorganisation erhöhen möchten, stehen vor einer komplexen Herausforderung. Selbstorganisation betrifft zahlreiche Elemente der Organisation wie Arbeitsaufgaben und Rollen, Führung, Regeln und Kompetenzen. Auf Basis eines empirisch entwickelten Bezugsrahmens, dem Digitalisierungsatlas, können die verschiedenen Elemente integrativ betrachtet und die Wechselwirkungen zwischen den Dimensionen in den Blick genommen werden. Wird Selbstorganisation ausgehend von der Autonomie der Beschäftigten, Arbeitsaufgaben und die eigene Rolle in der Organisation selbst zu beeinflussen, in den Blick genommen, sind insbesondere die Wechselwirkungen zwischen den organisationalen Dimensionen sowie Führung relevant. Die Spannungen zwischen diesen Dimensionen werden näher fokussiert. Insgesamt zeigt der Beitrag auf, dass Selbstorganisation nicht als ein unabhängiges Phänomen verstanden werden kann, sondern stets in Wechselwirkung mit anderen Dimensionen steht.
This paper aims at presenting a solution that enables end customers of the energy system to participate in new local micro-energy-markets by providing them with a distributed, decentralized, transparent and secure Peer to Peer (P2P) payment system, which functions automatically applying new concepts of Machine to Machine (M2M) communication technologies. This work was performed within the German project VK_2G, funded by the DBU. The key results were: Providing means to perform microtransactions in a P2P fashion between end consumers and prosumers in local communities at low cost in a transparent and secure manner; Developing a platform with pre-defined smart contracts able to be tailored to different end customers ‘needs in an easy way and; Integrating both the market platform as well as the local control of generation and loads. This solution has been developed, integrated and tested in a laboratory prototype. This paper discusses this solution and presents the results of the first test.
This paper presents a novel emulation concept for the test of smart contracts and Distributed Ledger Technologies (DLT) in distribute control or energy economy tasks and use cases. The concept uses state of the art behavioral modeling tools such as Matlab Simulink but presents a possible way to solve the shortfall of Simulink in communicating to DLT-Nodes directly. This is solved through a middleware solution. After this, an example used in verifying the test bed is presented and the target demonstration object is described. Finally, the possible expansion of the system is discussed and presented.
With the expansion of cyber-physical systems (CPSs) across critical and regulated industries, systems must be continuously updated to remain resilient. At the same time, they should be extremely secure and safe to operate and use. The DevOps approach caters to business demands of more speed and smartness in production, but it is extremely challenging to implement DevOps due to the complexity of critical CPSs and requirements from regulatory authorities. In this study, expert opinions from 33 European companies expose the gap in the current state of practice on DevOps-oriented continuous development and maintenance. The study contributes to research and practice by identifying a set of needs. Subsequently, the authors propose a novel approach called Secure DevOps and provide several avenues for further research and development in this area. The study shows that, because security is a cross-cutting property in complex CPSs, its proficient management requires system-wide competencies and capabilities across the CPSs development and operation.
Artificial Intelligence enables innovative applications, and applications based on Artificial Intelligence are increasingly important for all aspects of the Digital Economy. However, the question of how AI resources such as tools and data can be linked to provide an AI-capability and create business value is still open. Therefore, this paper identifies the value-creating mechanisms of connectionist artificial intelligence using a capability-oriented view and points out the connections to different kinds of business value. The analysis supports an agenda that identifies areas that need further research to understand the mechanism of value creation in connectionist artificial intelligence.
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.
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.
Digital technologies are main strategic drivers for digitalization and offer ubiquitous data availability, unlimited connectivity, and massive processing power for a fundamentally changing business. This leads to the development and application of intelligent digital systems. The current state of research and practice of architecting digital systems and services lacks a solid methodological foundation that fully accommodates all requirements linked to efficient and effective development of digital systems in organizations. Research presented in this paper addresses the question, how management of complexity in digital systems and architectures can be supported from a methodological perspective. In this context, the current focus is on a better understanding of the causes of increased complexity and requirements to methodological support. For this purpose, we take an enterprise architecture perspective, i.e. how the introduction of digital systems affects the complexity of EA. Two industrial case studies and a systematic literature analysis result in the proposal of an extended Digital Enterprise Architecture Cube as framework for future methodical support.
AI technologies such as deep learning provide promising advances in many areas. Using these technologies, enterprises and organizations implement new business models and capabilities. In the beginning, AI-technologies have been deployed in an experimental environment. AI-based applications have been created in an ad-hoc manner and without methodological guidance or engineering approach. Due to the increasing importance of AI-technologies, however, a more structured approach is necessary that enable the methodological engineering of AI-based applications. Therefore, we develop in this paper first steps towards methodological engineering of AI-based applications. First, we identify some important differences between the technological foundations of AI- technologies, in particular deep learning, and traditional information technologies. Then we create a framework that enables to engineer AI-applications using four steps: identification of an AI-application type, sub-type identification, lifecycle phase, and definition of details. The introduced framework considers that AI-applications use an inductive approach to infer knowledge from huge collections and streams of data. It not only enables the rapid development of AI-application but also the efficient sharing of knowledge on AI-applications.
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.
The development of new materials that mimic cartilage and its function is an unmet need that will allow replacing the damaged parts of the joints, instead of the whole joint. Polyvinyl alcohol (PVA) hydrogels have raised special interest for this application due to their biocompatibility, high swelling capacity and chemical stability. In this work, the effect of post-processing treatments (annealing, high hydrostatic pressure (HHP) and gamma-radiation) on the performance of PVA gels obtained by cast-drying was investigated and, their ability to be used as delivery vehicles of the anti-inflammatories diclofenac or ketorolac was evaluated. HHP damaged the hydrogels, breaking some bonds in the polymeric matrix, and therefore led to poor mechanical and tribological properties. The remaining treatments, in general, improved the performance of the materials, increasing their crystallinity. Annealing at 150 °C generated the best mechanical and tribological results: higher resistance to compressive and tensile loads, lower friction coefficients and ability to support higher loads in sliding movement. This material was loaded with the anti-inflammatories, both without and with vitamin E (Vit.E) or Vit.E + cetalkonium chloride (CKC). Vit.E + CKC helped to control the release of the drugs which occurred in 24 h. The material did not induce irritability or cytotoxicity and, therefore, shows high potential to be used in cartilage replacement with a therapeutic effect in the immediate postoperative period.
Der ›AM Field Guide‹ gibt einen ersten strukturierten Überblick in die komplexe und vielschichtige Welt der additiven Fertigungsverfahren. Getrennt nach den Materialien Polymere, Metalle und weitere Materialien werden die gängigsten jeweils auf dem Markt angebotenen AM-Verfahren schematisch dargestellt und der Verfahrenskern in Kurzform beschrieben. Neben den hier dargestellten Hauptverfahren gibt es viele Derivate und Sonderverfahren, die ebenfalls ein gesetzt werden jedoch nicht explizit gezeigt sind. Zu beachten ist, dass in dem jungen Bereich der additiven Fertigung viele Hersteller ihren AM-Anwendungen eigene Namen geben, so dass eine allgemeingültige umfassende Klassifizierung nur ansatzweise erreichbar ist.
Customer orientation should be the core engine of every organisation. Information technology can be considered as the enabler to generate competitive advantages through customer processes in marketing, sales and service. The impact of information technologies is the biggest risk and at the same time a huge opportunity for any organisation. Research shows that Customer Relationship Management (CRM) enables organisations to perform better and focus more on their customers (e.g. market capitalisation of Amazon). While global enterprises are shaping the future of customer centricity and information technology, the question arises how German B2B organisations can shift their value contribution from product-centric to customer-centric. Therefore, these organisations are attempting to implement CRM software and putting their customers more into focus. However, the question remains, how organisations are approaching the implementation of CRM and if these attempts are paying off in terms of business performance.
Contributing to this highly topical discussion, this thesis contributes to the body of knowledge about the implementation of CRM in the German B2B sector and how it impacts their business performance. First, theoretical frameworks have been developed based on an extensive literature review. Hereby different aspects of CRM are worked-out and mapped against three dimensions of business performance, namely process efficiency, customer satisfaction and financial performance. Based on the theory, a conceptual framework was developed to test the relationships between CRM and Business Performance (BP). Therefore, a survey with 500 participants has been conducted. Based on this a measurement model was developed to test five main hypotheses.
The findings of these hypotheses suggest, that the implementation of CRM positively impacts business performance. In specific, the usage of analytical CRM and the establishment of a dedicated CRM success measurement correlate with the performance of German B2B organisations. In addition to these main findings, various key statements could be derived from the research and a measurement model was developed, which can be used for different organisational characteristics assessing BP. As a result, CRM implementations can be enhanced, and business performance can be improved.
In the upcoming years, huge benefits are expected from Artificial Intelligence (AI). However, there are also risks involved in the technology, such as accidents of autonomous vehicles or discrimination by AI-based recruitment systems. This study aims to investigate public perception of these risks, focusing on realistic risks of Narrow AI, i.e., the type of AI that is already productive today. Based on perceived risk theory, several risk scenarios are examined using data from an exploratory survey. This research shows that AI is perceived positively overall. The participants, however, do evaluate AI critically when being confronted with specific risk scenarios. Furthermore, a strong positive relationship between knowledge about AI and perceived risk could be shown. This study contributes to knowledge by advancing our understanding of the awareness and evaluation of the risks by consumers and has important implications for product development, marketing and society.
Public enterprises find themselves in increasingly competitive markets, a situation that makes having an entrepreneurial orientation (EO) an urgent need, given that EO is an indispensable driver of performance. Research describes politicians delaying the strategic change of public enterprises when serving as board members, but empirical evidence of the impact of board behavior on EO in public enterprises is lacking. We draw on stakeholder-agency theory (SAT) and resource dependence theory (RDT) and use structural equation modeling (SEM) to investigate survey data collected from 110 German energy suppliers that are majority government owned. Results indicate that board strategy control and board networking do not seem to predict EO on first sight. Closer analysis reveals a board networking–EO relationship depending on ownership structure. Remarkably, we find that it is not the usually suspected local municipal owner who hinders EO in our sample organizations but minority shareholders engaging in board networking activities. The results shed light on the intersection of governance and entrepreneurship with special reference to the fine-grained conceptualization of RDT.
Although spiral antennas have undergone continuous development and refinement since Edwin Turner conceived them in 1954, only a few compact planar arrays exist. The shortcoming is even more significant when it comes to spiral antenna arrays in mode M2 operation. The present work addresses this issue, among other things. It presents two planar arrays of spiral antennas operating in the same frequency band and radiating for the first one an axial mode M1 and a conical mode M2 for the second. Both arrays are modeled, simulated, and fed with a corporate feeding network embedded in a dielectric substrate. It is shown that keeping the same topology, the array for conical M1 mode can be obtained from the array for mode M2 by a simple introduction of a phase shift on one branch of the feed and vice versa, providing thus the possibility to obtain in the same structure a spiral antenna array operating in both modes in the same frequency band simultaneously. Comparison between simulated and measured data shows good agreement.
The situation in the markets is changing rapidly and competition in the business sector is increasing rapidly. As a result, corporate marketing decisions are based on creating greater value for the consumer, which creates competitiveness and provides an advantage in competing for future customer loyalty. The purpose of this study is to determine whether there is a link between marketing communication tools and consumer perceived value in pursuit of consumer loyalty. Qualitative (observational research) and quantitative (a questionnaire survey) research methods were used to investigate the problem empirically. The observational research elucidated the value provided to the consumer by the research objects through marketing communication tools, supplementing the key questions for the quantitative study. Correlation and regression analysis were used in the study, with the results showing a statistically significant relationship between marketing communication tools and consumer perceived value in terms of user loyalty. It has also been determined that the greatest and strongest relationship in consumer value creation through marketing communication tools is the appropriate, mutually coordinated and complementary use of a package of marketing communication tools to achieve synergies that create the preconditions for increasing consumer loyalty in a competitive market.
In today’s marketplace, the consumption of luxury goods is at a peak due to increasing global wealth and low interest rates, resulting in a vast supply of goods and services to which customer experiences are more relevant than ever before. One of the most recent developments in this field shows that consumers no longer simply purchase a product or service based on the fact sheet; they are also interested in the experience around the product. Successful brands must develop and maintain individual images to sustain their competitive advantage and build brand equity that is beneficial for customers and firms. Ideally, these will lead to satisfaction and loyalty between a brand, its products, and its customers. Existing research about brand experience and brand equity has mainly focused on functional aspects, which seem to differ for high-value luxury goods. Most studies have focused on industries like retail and fashion brands, sampling university students or visitors to shopping malls, and some have even mixed different types of industries together. This underpins the need for research within a single luxury industry with actual luxury customers who have a solid background with brand experiences.
The purpose of this study was to explore the brand experience spectrum within the automotive industry in Germany, particularly in the affordable luxury sport car sector. Identifying the factors and components that constitute, influence, or leverage/drive a brand experience from their perspective was a clear aim of the study. To achieve this, the study collected data from indepth interviews with German (n=60) respondents who had experience with affordable and luxury sport cars. The conceptual framework was based on two empirically tested models guiding this exploratory consumer research. The first model to build on was the consumerbased brand equity model, empirically tested by Çifci et al. (2016) and Nam et al. (2011). The second conceptual framework was Lemon and Verhoef’s (2016) customer journey model consisting of relevant touchpoints along the following three stages: pre-purchase, purchase, and post-purchase.
The findings of the research demonstrate that, although the six brand equity concepts – brand awareness, physical quality, staff behaviour, self-congruence, brand identification, and lifestyle – are broadly applicable in understanding customer experience in the affordable luxury car industry, the content of these dimensions differs from that suggested by the previous authors. The research established that cognitive and affective (or symbolic) components build the foundation of customer brand experience and supports Çifci et al.’s (2016) and Nam et al.’s (2011) study results. The study also identified brand trust as an important and highly relevant concept for customer brand experience in the luxury automotive car industry. Brand trust influences customer satisfaction and loyalty, therefore improving and complementing the existing model. Furthermore, the study confirmed Lemon and Verhoef’s (2016) process model of the customer journey and experience; however, it suggested two different customer journeys depending on the customers’ previous experience (first-time and experienced buyers). The differences between the two groups and the relevance of the journey touchpoints within the three purchase stages vary significantly in terms and are distinct. Identified key touchpoints for both groups are the contact to a dealer as well as information gathering online. Differences have been found in the length of purchase stages and across the customer journey. The study highlights the importance of trust, identification, and product quality for customer brand experience. Moreover, the findings of this study complement the brand equity model of Çifci et al. (2016) by adding the new concept of trust, which is highly relevant. The current knowledge is complemented by a new understanding and mapping of the customer journey for luxury sports cars in Germany. This study can assist practitioners and managers by providing a compass indicating which touchpoints are relevant to which customer group. Social value can be achieved by encouraging interactions between brand and consumer (e.g. central product launch events) and through brand-oriented interactions among consumers (e.g. dealer events, clubs, or communities). Customers are motivated to express their distinctiveness through product experience and brand identification (belonging/distinction) and to develop a loyal link to brands.
Access to clinical information during interventions is an important aspect to support the surgeon and his team in the OR. The OR-Pad research project aims at displaying clinically relevant information close to the patient during surgery. With the OR-Pad system, the surgeon shall be able to access case-specific information, displayed on a sterile-packaged, portable display device. Therefore, information shall be prepared before surgery and also be available afterwards. The project follows an user-centered design process. Within the third iteration, the interaction concept was finalized, resulting in an application that can be used in two modes, mobile and intraoperative, to support the surgeon before/after and during surgery, respectively. By supporting the surgeon perioperatively, it is expected to improve the information situation in the OR and thereby the quality of surgical results. Based on this concept, the system architecture was designed in detail, using a client-server architecture. Components, communication interfaces, exchanged data, and intended standards for data exchange of the OR-Pad system including connecting systems were conceived. Expert interviews by using a clickable prototype were conducted to evaluate the concepts.
Introduction
Despite its high accuracy, polysomnography (PSG) has several drawbacks for diagnosing obstructive sleep apnea (OSA). Consequently, multiple portable monitors (PMs) have been proposed.
Objective
This systematic review aims to investigate the current literature to analyze the sets of physiological parameters captured by a PM to select the minimum number of such physiological signals while maintaining accurate results in OSA detection.
Methods
Inclusion and exclusion criteria for the selection of publications were established prior to the search. The evaluation of the publications was made based on one central question and several specific questions.
Results
The abilities to detect hypopneas, sleep time, or awakenings were some of the features studied to investigate the full functionality of the PMs to select the most relevant set of physiological signals. Based on the physiological parameters collected (one to six), the PMs were classified into sets according to the level of evidence. The advantages and the disadvantages of each possible set of signals were explained by answering the research questions proposed in the methods.
Conclusions
The minimum number of physiological signals detected by PMs for the detection of OSA depends mainly on the purpose and context of the sleep study. The set of three physiological signals showed the best results in the detection of OSA.
Hyperspectral imaging and reflectance spectroscopy in the range from 200–380 nm were used to rapidly detect and characterize copper oxidation states and their layer thicknesses on direct bonded copper in a non-destructive way. Single-point UV reflectance spectroscopy, as a well-established method, was utilized to compare the quality of the hyperspectral imaging results. For the laterally resolved measurements of the copper surfaces an UV hyperspectral imaging setup based on a pushbroom imager was used. Six different types of direct bonded copper were studied. Each type had a different oxide layer thickness and was analyzed by depth profiling using X-ray photoelectron spectroscopy. In total, 28 samples were measured to develop multivariate models to characterize and predict the oxide layer thicknesses. The principal component analysis models (PCA) enabled a general differentiation between the sample types on the first two PCs with 100.0% and 96% explained variance for UV spectroscopy and hyperspectral imaging, respectively. Partial least squares regression (PLS-R) models showed reliable performance with R2c = 0.94 and 0.94 and RMSEC = 1.64 nm and 1.76 nm, respectively. The developed in-line prototype system combined with multivariate data modeling shows high potential for further development of this technique towards real large-scale processes.
A laboratory prototype for hyperspectral imaging in ultra-violet (UV) region from 225 to 400 nm was developed and used to rapidly characterize active pharmaceutical ingredients (API) in tablets. The APIs are ibuprofen (IBU), acetylsalicylic acid (ASA) and paracetamol (PAR). Two sample sets were used for a comparison purpose. Sample set one comprises tablets of 100% API and sample set two consists of commercially available painkiller tablets. Reference measurements were performed on the pure APIs in liquid solutions (transmission) and in solid phase (reflection) using a commercial UV spectrometer. The spectroscopic part of the prototype is based on a pushbroom imager that contains a spectrograph and charge-coupled device (CCD) camera. The tablets were scanned on a conveyor belt that is positioned inside a tunnel made of polytetrafluoroethylene (PTFE) in order to increase the homogeneity of illumination at the sample position. Principal component analysis (PCA) was used to differentiate the hyperspectral data of the drug samples. The first two PCs are sufficient to completely separate all samples. The rugged design of the prototype opens new possibilities for further development of this technique towards real large-scale application.
Hypericin has large potential in modern medicine and exhibits fascinating structural dynamics, such as multiple conformations and tautomerization. However, it is difficult to study individual conformers/tautomers, as they cannot be isolated due to the similarity of their chemical and physical properties. An approach to overcome this difficulty is to combine single molecule experiments with theoretical studies. Time-dependent density functional theory (TD-DFT) calculations reveal that tautomerization of hypericin occurs via a two-step proton transfer with an energy barrier of 1.63 eV, whereas a direct single-step pathway has a large activation energy barrier of 2.42 eV. Tautomerization in hypericin is accompanied by reorientation of the transition dipole moment, which can be directly observed by fluorescence intensity fluctuations. Quantitative tautomerization residence times can be obtained from the autocorrelation of the temporal emission behavior revealing that hypericin stays in the same tautomeric state for several seconds, which can be influenced by the embedding matrix. Furthermore, replacing hydrogen with deuterium further proves that the underlying process is based on tunneling of a proton. In addition, the tautomerization rate can be influenced by a λ/2 Fabry–Pérot microcavity, where the occupation of Raman active vibrations can alter the tunneling rate.
A lens-based Raman spectrometer is characterized by studying the optical elements in the optical path and we study the measure of aberration–diffraction effects. This is achieved by measuring the spectral resolution (SR) thus encompassing almost all optical elements of a spectrometer that are mostly responsible for such effects. An equation for SR is used to determine the quality factor Q which measures aberration/diffraction effects occurring in a spectrometer. We show how the quality factor changes with different spectrometer parameters such as grating groove density, the wavelength of excitation, pinhole width, charge-coupled device (CCD) pixel density, etc. This work provides an insight into the quality of a spectrometer and helps to monitor the performance of the spectrometer over a certain period. Commercially available spectrometers or home-built spectrometers are prone to misalignment in optical elements and can benefit from this work that allows maintaining the overall quality of the setup. Performing such experiments over a period helps to minimize the aberration/ diffraction effects occurring as a result of time and maintaining the quality of measurements.
Porous silica materials are often used for drug delivery. However, systems for simultaneous delivery of multiple drugs are scarce. Here we show that anisotropic and amphiphilic dumbbell core–shell silica microparticles with chemically selective environments can entrap and release two drugs simultaneously. The dumbbells consist of a large dense lobe and a smaller hollow hemisphere. Electron microscopy images show that the shells of both parts have mesoporous channels. In a simple etching process, the properly adjusted stirring speed and the application of ammonium fluoride as etching agent determine the shape and the surface anisotropy of the particles. The surface of the dense lobe and the small hemisphere differ in their zeta potentials consistent with differences in dye and drug entrapment. Confocal Raman microscopy and spectroscopy show that the two polyphenols curcumin (Cur) and quercetin (QT) accumulate in different compartments of the particles. The overall drug entrapment efficiency of Cur plus QT is high for the amphiphilic particles but differs widely between Cur and QT compared to controls of core–shell silica microspheres and uniformly charged dumbbell microparticles. Furthermore, Cur and QT loaded microparticles show different cancer cell inhibitory activities. The highest activity is detected for the dual drug loaded amphiphilic microparticles in comparison to the controls. In the long term, amphiphilic particles may open up new strategies for drug delivery.
Corporate entrepreneurship in the public sector: exploring the peculiarities of public enterprises
(2021)
Entrepreneurship is predominantly treated as a private-sector phenomenon and consequently its increasing importance in the public sector goes largely unremarked. That impedes the research field of entrepreneurship being capable of spanning multiple sectors. Accordingly, recent research calls for the study of corporate entrepreneurship (CE) as it manifests in the public sector where it can be labeled public entrepreneurship (PE). This dissertation considers government an essential entrepreneurial actor and is led by the central research question: What are the peculiarities of the public sector and how do they impact public enterprises’ entrepreneurial orientation (EO)?
Accordingly, this dissertation includes three studies focusing on public enterprises. Two of the studies set the scope of this thesis by investigating a specific type of organization in a specific context—German majority-government-owned energy suppliers. These enterprises operate in a liberalized market experiencing environmental uncertainties like competitiveness and business transformation.
The aims and results of the studies included in this dissertation can be summarized as follows: The systematic literature review illuminates the stimuli of and barriers to entrepreneurial activities in public enterprises and the potential outcomes of such activities discussed so far. The review reveals that research on EO has tended to focus on the private sector and consequently that barriers to and outcomes of entrepreneurial activities in the public sector remain under-researched. Building on these findings, the qualitative study focuses on the interrelated barriers affecting entrepreneurship in public enterprises and the outcomes of entrepreneurial activities being inhibited. The study adopts an explorative comparative causal mapping approach to address the above-mentioned research goal and the lack of clarity around how barriers identified in the public sphere are interrelated. Furthermore, the study bases its investigation on the different business segments of sales (competitive market) and the distribution grid (natural monopoly) to account for recent calls for fine-grained research on PE. Results were compared with prior findings in the public and private sector. That comparison indicates that the barriers revealed align with aspects discussed in prior research findings relating to both sectors. Examples include barriers associated with the external environment such as legal constraints and barriers originating from within the organization such as employee behavior linked to a value system that hampers entrepreneurial action. However, the most important finding is that a public enterprise’s supervisory board can hinder its progress, a finding running counter to those of previous private-sector research and one that underscores the widespread prejudice that the involvement of a public shareholder and its nominated board of directors has a negative effect on EO. The third study is quantitative (data collection via a questionnaire) and builds on both its predecessors to examine the little understood topic of board behavior and public enterprises’ social orientation as predictors of EO. The study’s results indicate that social orientation represses EO, whereas board strategy control (BSC) does not seem to predict EO. Regarding BSC, we find that the local government owners in our sample are less involved in BSC. The third study also examines board networking and finds its relationship with EO depends on the ownership structure of the public-sector organization. An important finding is that minority shareholders, such as majority privately-owned enterprises and hub firms, repress EO when engaging in board networking.
In summary, this doctoral thesis contributes to the under-researched topic of CE in the public sector. It investigates the peculiarities of this sector by focusing on the supervisory board and social oriented activities and their impact on the enterprise’s EO in the quantitative study. The thesis addresses institutional questions regarding ownership and the last study in particular contributes to expanding resource dependence theory, and invites a nuanced perspective: The original perspective suggests that interorganizational arrangements like interfirm network ties and equity holdings reduce external resource dependency and consequently improve firm performance. The findings within this thesis expose resource delivery to potential contrary effects to extend the understanding of interorganizational action with important implications for practice.
This paper presents an improvement in usability and integrity of simulation-based analog circuit sizing. Instead of using geometrical sizing parameters (width, length), a transformed design-space, consisting exclusively of electrical parameters (branch currents, efficiencies and speed) is utilized. This design-space is explored more efficiently by optimizers. Moreover, this design-space can be reduced without affecting the quality of the result. The method is illustrated on two application examples, a symmetrical and a miller operational amplifier. Sizing the circuits using the transformed design-space showed significant reduction in required circuit simulations (up to 11x faster), better convergence, without loss in quality.
Electronic design automation approaches can roughly be divided into optimizers and procedures. While the former have enabled highly automated synthesis flows for digital integrated circuits, the latter play a vital (but mostly underestimated role) in the analog domain. This paper describes both automation strategies in comparison, identifying two fundamentally different automation paradigms that reflect the two basic design practices known as “top-down” and “bottom-up”. Then, with a focus on the latter, the history of procedural approaches is traced from their
early beginnings until today’s evolvements and future prospects to underline their practical importance and to accentuate their scientific value, both in itself and in the overall context of EDA.
Wenn Unternehmen den Schritt in die digitale Arbeitswelt gehen wollen, stehen sie vor der Herausforderung, konkrete Vorstellungen, Ziele und Maßnahmen zu entwickeln und umzusetzen. Häufig fehlt es Unternehmen an Wissen, ihre Transformation der Arbeitswelt strategisch zu gestalten und zu planen. Das Projekt DigiTraIn 4.0 setzt hier an und bietet mit dem Digitalisierungskompass ein Instrument, welches Unternehmen dabei unterstützt, eine Vision und spezifische Ziele für die Digitalisierung ihrer eigenen Arbeitswelt zu entwickeln. Im Anschluss daran unterstützt die Transformationsagenda Unternehmen dabei, konkrete Handlungsmaßnahmen zu entwickeln und deren Ablauf zu planen.
Die digitale Arbeitswelt in ihrer Mehrdimensionalität verstehen: Digitalisierungsatlas und -index
(2021)
Die digitale Transformation der Arbeitswelt ist deshalb so herausfordernd, da die Arbeitswelt für sich bereits ein komplexes mehrdimensionales System ist, das sich kaum überblicken lässt. Für Unternehmen ist es deshalb wichtig, die Mehrdimensionalität und Komplexität der digitalen Arbeitswelt zu verstehen, hierfür ein gemeinsames Sprachspiel zu entwickeln und auf dieser Basis eine gemeinsame Einschätzung des Status quo der eigenen Arbeitswelt zu beschreiben. Mithilfe von zwei Instrumenten, dem Digitalisierungsatlas und dem Digitalisierungsindex, kann dies gelingen. In diesem Beitrag werden diese Instrumente im Detail dargestellt und es wird erklärt, wie sie Organisationen dabei helfen, zu beschreiben und zu verstehen, wo sie selbst in der digitalen Transformation der Arbeitswelt stehen.
Technologische, sozioökonomische und kulturelle Entwicklungen der letzten Jahrzehnte sowie zuletzt die Covid-19-Pandemie führten zu einer erhöhten Nachfrage nach flexiblen Arbeitsformen wie Homeoffice. In der Forschung wird danach gefragt, welche Faktoren die Umsetzung von flexiblen Arbeitsmodellen in Unternehmen beeinflussen und wie die Faktoren miteinander zusammenhängen. Bisher bietet die Forschung allerdings zu wenige Ansatzpunkte, um relevante Handlungsempfehlungen für eine erfolgreiche Umsetzung von Homeoffice für die Praxis abzuleiten. In dieser Fallstudie können auf organisationaler Ebene technologische, formelle und informelle Rahmenbedingungen, auf interaktionaler Ebene das Team und die Kommunikation sowie auf individueller Ebene Präferenzen, Kompetenzen und personenbezogene Rahmenbedingungen der Beschäftigten als relevante Einflussfaktoren identifiziert werden. Die Themenfelder sind eng miteinander verbunden, wobei sich vor allem stark vernetzte und einflussreiche Faktoren, wie formelle und technologische Rahmenbedingungen sowie Kommunikation, als Ansatzpunkte für die Gestaltung von Homeoffice eignen.
Die Corona-Pandemie hat zu einer Einschränkung des Alltags der medizinischen Versorgung geführt. Das zeigt sich u.a. in zum Teil erheblichen Zugangsbeschränkungen zu Krankenhäusern und Praxen mit stark reduzierter Einbestellung von Patienten, der Einhaltung von gesteigerten Hygienemaßnahmen mit entsprechend längeren Wartezeiten, dem Zugangsverbot für Begleitpersonen und nicht zuletzt der Angst vieler Patienten vor einer Ansteckung bei einem Aufenthalt in medizinischen Bereichen. Folge dessen war und ist, dass ein deutlich wahrnehmbarer Rückgang der Patientenzahlen in den Krankenhausambulanzen und Praxen zu verzeichnen war. Davon war die Augenheilkunde als Fachdisziplin mit einem hohen Anteil an ambulanten und geplanten, chirurgischen Eingriffen in besonderem Maße betroffen.
Das Projekt DigiTraIn 4.0 hat ein Beratungskonzept entwickelt und erprobt, das Unternehmen bei der erfolgreichen Digitalisierung ihrer Arbeitswelt unterstützt. Das Beratungskonzept basiert auf vier anwendungsorientierten Instrumenten: Der Digitalisierungsatlas bildet die Digitalisierung der Arbeitswelt in all ihren Dimensionen ab und ermöglicht es, die Notwendigkeit sowie Chancen und Risiken der Veränderungen zu verstehen. Hierauf aufbauend können Unternehmen mit dem Digitalisierungsindex ihren aktuellen Ist-Digitalisierungsgrad der Arbeitswelt individuell bestimmen. Der individuelle Digitalisierungsgrad dient als Ausgangspunkt für den Digitalisierungskompass, der es dem Unternehmen ermöglicht, die Soll-Vorstellung der digitalen Arbeitswelt zu illustrieren und eine unternehmensspezifische Transformationsagenda abzuleiten. Der Beratungsprozess und die Entwicklung der zentralen Instrumente werden in diesem Beitrag dargestellt.