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Afrika ist ein Kontinent der Chancen, der in der künftigen weltwirtschaftlichen Arbeitsteilung eine deutlich größere Rolle spielen dürfte als bisher. Dennoch tut sich die deutsche Wirtschaft bislang schwer. Die digitale Transformation verändert die Investitions- und Innovationsbedingungen in Afrika. Daraus ergeben sich auch für deutsche Unternehmen Chancen auf dem afrikanischen Kontinent. Die Politik sollte Rahmenbedingungen für ein stärkeres privatwirtschaftliches Engagement deutscher und europäischer Unternehmen in Afrika schaffen.
(57) Zusammenfassung: Die Erfindung betrifft ein Verfahren zur konstruktionslosen Schnittgestaltung für wenigstens ein Bekleidungsstück (250) einer Bekleidungskollektion, wobei ein Modellkörper verwendet wird, auf dem wenigstens ein Markierungspunkt (203) und/oder wenigstens eine Schnittlinie (202) vorhanden ist oder angebracht wird, wobei von dem Modellkörper durch Oberflächenabrollen Schnittteile (204) erhalten werden, wobei als Modellkörper ein Optimalkörper (200) verwendet wird, der eine Soll-Innenkontur (212) eines herzustellenden Bekleidungsstückes (250) repräsentiert. Die Erfindung betrifft ferner den Optimalkörper (200) sowie einen 3D-Datensatz des Optimalkörpers (200) sowie ein Verfahren zum Erzeugen des Optimalkörpers (200).
This article aims to give an overview of what German business needs in current times. By illustrating the Made in Germany label as a perceived image in sales, specific attributes are being evaluated to explain better the challenges German businesses are currently facing: Digitization, Education, Environment, and Quality & China.
Will chatbots play a significant role for B2B marketingin the future? Chatbots in B2B businesses
(2022)
Digitalization has gained a foothold in our everyday lives. However, it remains to be seen what digital tools B2B companies can benefit from. During the last few years, chatbots have been on the rise and have played a more significant role in B2B marketing. Thus, this research follows a literature review to examine the current state of B2B chatbots. With this, the study will discover the buyer’s preferences for chatbots compared to sales agents and the role of chatbots in different stages of the B2B sales funnel.
Enterprises and societies currently face crucial challenges, while Society 5.0 can contribute to a supersmart society, especially for manufacturing and healthcare, and Industry 4.0 becomes important in the global manufacturing industry. Smart energy digital platforms are architected to manage energy supply efficiently. Furthermore, the above digital platforms are expected to collect various kinds of data and analyze Big Data for the trends in the sharing economy in ecosystems. The adaptive integrated digital architecture framework (AIDAF) for Design Thinking Approach with Risk Management is expected to make an alignment with digital IT strategy. In this paper, we propose that various energy management systems and related digital platforms are designed and implemented in an alignment to digital IT strategy for sharing economy toward Society 5.0, with the AIDAF framework for Design Thinking Approach with Risk Management. The vision of AIDAF applications to enable sharing economy and digital platforms is explained and extended in the context of Society 5.0. In addition, challenges and future activities for this area are discussed that cover the directions of smart energy for Society 5.0.
The volume includes papers presented at the International KES Conference on Human Centred Intelligent Systems 2022 (KES HCIS 2022), held in Rhodes, Greece on June 20–22, 2022. This book highlights new trends and challenges in intelligent systems, which play an important part in the digital transformation of many areas of science and practice. It includes papers offering a deeper understanding of the human-centred perspective on artificial intelligence, of intelligent value co-creation, ethics, value-oriented digital models, transparency, and intelligent digital architectures and engineering to support digital services and intelligent systems, the transformation of structures in digital businesses and intelligent systems based on human practices, as well as the study of interaction and the co-adaptation of humans and systems.
The euphoria around microservices has decreased over the years, but the trend of modernizing legacy systems to this novel architectural style is unbroken to date. A variety of approaches have been proposed in academia and industry, aiming to structure and automate the often long-lasting and cost-intensive migration journey. However, our research shows that there is still a need for more systematic guidance. While grey literature is dominant for knowledge exchange among practitioners, academia has contributed a significant body of knowledge as well, catching up on its initial neglect. A vast number of studies on the topic yielded novel techniques, often backed by industry evaluations. However, practitioners hardly leverage these resources. In this paper, we report on our efforts to design an architecture-centric methodology for migrating to microservices. As its main contribution, a framework provides guidance for architects during the three phases of a migration. We refer to methods, techniques, and approaches based on a variety of scientific studies that have not been made available in a similarly comprehensible manner before. Through an accompanying tool to be developed, architects will be in a position to systematically plan their migration, make better informed decisions, and use the most appropriate techniques and tools to transition their systems to microservices.
The respiratory rate is a vital sign indicating breathing illness. It is necessary to analyze the mechanical oscillations of the patient's body arising from chest movements. An inappropriate holder on which the sensor is mounted, or an inappropriate sensor position is some of the external factors which should be minimized during signal registration. This paper considers using a non-invasive device placed under the bed mattress and evaluates the respiratory rate. The aim of the work is the development of an accelerometer sensor holder for this system. The normal and deep breathing signals were analyzed, corresponding to the relaxed state and when taking deep breaths. The evaluation criterion for the holder's model is its influence on the patient's respiratory signal amplitude for each state. As a result, we offer a non-invasive system of respiratory rate detection, including the mechanical component providing the most accurate values of mentioned respiratory rate.
Over the last decades, a tremendous change toward using information technology in almost every daily routine of our lives can be perceived in our society, entailing an incredible growth of data collected day-by-day on Web, IoT, and AI applications.
At the same time, magneto-mechanical HDDs are being replaced by semiconductor storage such as SSDs, equipped with modern Non-Volatile Memories, like Flash, which yield significantly faster access latencies and higher levels of parallelism. Likewise, the execution speed of processing units increased considerably as nowadays server architectures comprise up to multiple hundreds of independently working CPU cores along with a variety of specialized computing co-processors such as GPUs or FPGAs.
However, the burden of moving the continuously growing data to the best fitting processing unit is inherently linked to today’s computer architecture that is based on the data-to-code paradigm. In the light of Amdahl's Law, this leads to the conclusion that even with today's powerful processing units, the speedup of systems is limited since the fraction of parallel work is largely I/O-bound.
Therefore, throughout this cumulative dissertation, we investigate the paradigm shift toward code-to-data, formally known as Near-Data Processing (NDP), which relieves the contention on the I/O bus by offloading processing to intelligent computational storage devices, where the data is originally located.
Firstly, we identified Native Storage Management as the essential foundation for NDP due to its direct control of physical storage management within the database. Upon this, the interface is extended to propagate address mapping information and to invoke NDP functionality on the storage device. As the former can become very large, we introduce Physical Page Pointers as one novel NDP abstraction for self-contained immutable database objects.
Secondly, the on-device navigation and interpretation of data are elaborated. Therefore, we introduce cross-layer Parsers and Accessors as another NDP abstraction that can be executed on the heterogeneous processing capabilities of modern computational storage devices. Thereby, the compute placement and resource configuration per NDP request is identified as a major performance criteria. Our experimental evaluation shows an improvement in the execution durations of 1.4x to 2.7x compared to traditional systems. Moreover, we propose a framework for the automatic generation of Parsers and Accessors on FPGAs to ease their application in NDP.
Thirdly, we investigate the interplay of NDP and modern workload characteristics like HTAP. Therefore, we present different offloading models and focus on an intervention-free execution. By propagating the Shared State with the latest modifications of the database to the computational storage device, it is able to process data with transactional guarantees. Thus, we achieve to extend the design space of HTAP with NDP by providing a solution that optimizes for performance isolation, data freshness, and the reduction of data transfers. In contrast to traditional systems, we experience no significant drop in performance when an OLAP query is invoked but a steady and 30% faster throughput.
Lastly, in-situ result-set management and consumption as well as NDP pipelines are proposed to achieve flexibility in processing data on heterogeneous hardware. As those produce final and intermediary results, we continue investigating their management and identified that an on-device materialization comes at a low cost but enables novel consumption modes and reuse semantics. Thereby, we achieve significant performance improvements of up to 400x by reusing once materialized results multiple times.
Job advertisements are important means of communicating role expectations for management accountants to the labor market. They provide information about which roles of management accountants are sought by companies or which roles are expected. However, which roles are communicated in job advertisements is unknown so far. Using a large sample of 889 job ads and a text-mining approach, we show an apparent mix of different role types with a strong focus on a rather classic role: the watchdog role. However, individuals with business partner characteristics are more often sought for leadership positions or in family businesses and small and medium-sized enterprises (SMEs). The results challenge the current role discussion for management accountants as business partners in practice and some academic fields.
The early involvement of experiences gained through intelligence and data analysis is becoming increasingly important in order to develop new products, leading to a completely different conception of product creation, development and engineering processes using the advantages that the dedication of the digital twin entails. Introducing a novel stage gate process in order to be holistically anchored in learning factories adopting idea generation and idea screening in an early stage, beta testing of first prototypes, technical implementation in real production scenarios, business analysis, market evaluation, pricing, service models as well as innovative social media portals. Corresponding product modelling in the sense of sustainability, circular economy, and data analytics forecasts the product on the market both before and after market launch with the interlinking of data interpretation nearby in real-time. The digital twin represents the link between the digital model and the digital shadow. Additionally, the connection of the digital twin with the product provides constantly updated operating status and process data as well as mapping of technical properties and real-world behaviours. A future-networking product, by embedded information technology with the ability to initiate and carry out one's own further development, is able to interact with people and environments and thus is relevant to the way of life of future generations. In today's development work for this new product creation approach, on one hand, "Werk150" is the object of the development itself and on the other hand the validation environment. In the next step, new learning modules and scenarios for trainings at master level will be derived from these findings.
Especially, if the potential of technical and organizational measures for ergonomic workplace design is limited, exoskeletons can be considered as innovative ergonomic aids to reduce the physical workload of workers. Recent scientific findings from ergonomic analyses with and without exoskeletons are indicating that strain reduction can be achieved, particularly at workplaces with lifting, holding, and carrying processes. Currently, a work system design method is under development incorporating criteria and characteristics for the design of work systems in which a human worker is supported by an exoskeleton. Based on the properties of common passive and active exoskeletons, factors influencing the human on which an exoskeleton can have a positive or negative effect (e.g. additional weight) were derived. The method will be validated by the conceptualization and setup of several work system demonstrators at Werk150, the factory of ESB Business School on campus of Reutlingen University, to prove the positive ergonomic effect on humans and the supporting process to choose the suitable exoskeleton. The developed method and demonstrators enable the user to experience the positive ergonomic effects of exoskeletal support in lifting, holding and carrying processes in logistics and production. The new work system design method will contribute to the fact that employees can pursue their professional activity longer without substantial injuries or can be used more flexibly at different work stations. Also new work concepts, strategies and scenarios are opened up to reduce the risk of occupational accidents and to promote the compatibility of work for employees. A training module is being developed and evaluated with participants from industry and master students to build up competence.
This paper reviews suggestions for changes to database technology coming from the work of many researchers, particularly those working with evolving big data. We discuss new approaches to remote data access and standards that better provide for durability and auditability in settings including business and scientific computing. We propose ways in which the language standards could evolve, with proof-of-concept implementations on Github.
Der Beitrag präsentiert und diskutiert zwei Studien, welche in der Primarstufe im Sachunterricht und Kunst/Werken als Fächer Kultureller Bildung durchgeführt wurden. Sie sind Teil eines Promotionsvorhabens an der Pädagogischen Hochschule Freiburg in Kooperation mit der Hochschule Reutlingen. Das Vorhaben geht der Forschungsfrage nach, inwieweit ein didaktisch-methodischer Ansatz auf Basis der Phasen und Prinzipien des Design Thinking in den Fächern Kunst/Werken und im Sachunterricht bei Kindern der Primarstufe Kreativität, kollaborative Arbeitsweise und Problemlösekompetenz als sogenannte Schlüsselkompetenzen des 21. Jahrhunderts fördern kann. Gemäß dem Bildungsplan von Baden-Württemberg werden im Sachunterricht und in Kunst/Werken prozessorientierte Kompetenzen vermittelt, welche eine hohe Übereinstimmung mit den Phasen des iterativen Design Thinking Prozesses aufweisen. Die Ergebnisse der Studien zeigen Gemeinsamkeiten und Unterschiede zwischen den beiden Fächern und werden anhand von Grafiken präsentiert. Dabei zeigt sich, dass die Ergebnisse aus den Vorstudien im Wesentlichen bestätigt werden. Dies eröffnet die Diskussion, den didaktisch-methodischen Ansatz auf Basis des Design Thinking weiterzuentwickeln, um die kreativen Potenziale der Kinder bei der Wissensvermittlung einzubeziehen.
Context: Nowadays the market environment is characterized by high uncertainties due to high market dynamics, confronting companies with new challenges in creating and updating product roadmaps. Most companies are still using traditional approaches which typically fail in such environments. Therefore, companies are seeking opportunities for new product roadmapping approaches.
Objective: This paper presents good practices to support companies better understand what factors are required to conduct a successful product roadmapping in a dynamic and uncertain market environment.
Method: Based on a grey literature review, essential aspects for conducting product roadmapping in a dynamic and uncertain market environment were identified. Expert workshops were then held with two researchers and three practitioners to develop best practices and the proposed approach for an outcome-driven roadmap. These results were then given to another set of practitioners and their perceptions were gathered through interviews.
Results: The study results in the development of 9 good practices that provide practitioners with insights into what aspects are crucial for product roadmapping in a dynamic and uncertain market environment. Moreover, we propose an approach to product roadmapping that includes providing a flexible structure and focusing on delivering value to the customer and the business. To ensure the latter, this approach consists of the main items outcome hypothesis, validated outcomes, and discovered outputs.
Providing a digital infrastructure, platform technologies foster interfirm collaboration between loosely coupled companies, enabling the formation of ecosystems and building the organizational structure for value co-creation. Despite the known potential, the development of platform ecosystems creates new sources of complexity and uncertainty due to the involvement of various independent actors. For a platform ecosystem to succeed, it is essential that the platform ecosystem participants are aligned, coordinated, and given a common direction. Traditionally, product roadmaps have served these purposes during product development. A systematic mapping study was conducted to better understand how product roadmapping could be used in the dynamic environment of platform ecosystems. One result of the study is that there are hardly any concrete approaches for product roadmapping in platform ecosystems so far. However, many challenges on the topic are described in the literature from different perspectives. Based on the results of the systematic mapping study, a research agenda for product roadmapping in platform ecosystems is derived and presented.
Cell migration plays an essential role in wound healing and inflammatory processes inside the human body. Peripheral blood neutrophils, a type of polymorphonuclear leukocyte (PMN), are the first cells to be activated during inflammation and subsequently migrate toward an injured tissue or infection site. This response is dependent on both biochemical signaling and the extracellular environment, one aspect of which includes increased temperature in the tissues surrounding the inflammation site. In our study, we analyzed temperature-dependent neutrophil migration using differentiated HL-60 cells. The migration speed of differentiated HL-60 cells was found to correlate positively with temperature from 30 to 42 °C, with higher temperatures inducing a concomitant increase in cell detachment. The migration persistence time of differentiated HL-60 cells was higher at lower temperatures (30–33 °C), while the migration persistence length stayed constant throughout the temperature range. Coupled with the increased speed observed at high temperatures, this suggests that neutrophils are primed to migrate more effectively at the elevated temperatures characteristic of inflammation. Temperature gradients exist on both cell and tissue scales. Taking this into consideration, we also investigated the ability of differentiated HL-60 cells to sense and react to the presence of temperature gradients, a process known as thermotaxis. Using a two-dimensional temperature gradient chamber with a range of 27–43 °C, we observed a migration bias parallel to the gradient, resulting in both positive and negative thermotaxis. To better mimic the extracellular matrix (ECM) environment in vivo, a three-dimensional collagen temperature gradient chamber was constructed, allowing observation of biased neutrophil-like differentiated HL-60 migration toward the heat source.
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
Gender pay gaps are commonly studied in populations with already completed educational careers. We focus on an earlier stage by investigating the gender pay gap among university students working alongside their studies. With data from five cohorts of a large-scale student survey from Germany, we use regression and wage decomposition techniques to describe gender pay gaps and potential explanations. We find that female students earn about 6% less on average than male students, which reduces to 4.1% when accounting for a rich set of explanatory variables. The largest explanatory factor is the type of jobs male and female students pursue.
Im Kampf gegen die Ausbreitung des Corona-Virus waren flächendeckende Schulschließungen seit Ausbruch der Pandemie eine zentrale politische Maßnahme. Infolgedessen kam es zu erheblichen Lernzeiteinbußen unter allen Schüler*innen, worunter insbesondere Kinder und Jugendliche aus benachteiligten Verhältnissen immer noch leiden. Über die Auswirkungen der Corona-Pandemie auf das deutsche Bildungssystem wird diskutiert und Maßnahmen zu deren Eindämmung aufgesetzt.
Early exposure makes the entrepreneur: how economics education in school influences entrepreneurship
(2022)
Many countries that seek to boost their economy share the goal of promoting entrepreneurship. Whereas there is ample research on the predictors of entrepreneurship during adulthood, we know little about how pre-adulthood experience influences entrepreneurship later in life. Using a natural experiment, this paper examines whether introducing economics classes in school enhances entrepreneurial behavior in adulthood. Our difference-in-differences approach exploits curricula reforms across German states that introduced compulsory economics education classes in secondary schools. Using information on school and labor market careers for more than 10,000 individuals from 1984 to 2019, we find that the reform increases students’ entrepreneurial activities by three percentage points. Examining gender differences, we find that economics classes equally benefit female and male students. Our results advance our understanding of how pre-adulthood experiences shape individuals’ entrepreneurial behavior.
We study whether compulsory religious education in schools affects students' religiosity as adults. We exploit the staggered termination of compulsory religious education across German states in models with state and cohort fixed effects. Using three different datasets, we find that abolishing compulsory religious education significantly reduced religiosity of affected students in adulthood. It also reduced the religious actions of personal prayer, church-going, and church membership. Beyond religious attitudes, the reform led to more equalized gender roles, fewer marriages and children, and higher labor-market participation and earnings. The reform did not affect ethical and political values or non-religious school outcomes.
Being exposed to compulsory religious education in school can have long-run consequences for students’ lives. At different points in time since the 1970s, German states terminated compulsory religious education in public schools and replaced it by a choice between ethics classes and religious education. This article shows that the reform not only led to reduced religiosity in students’ later life, but also eroded traditional attitudes towards gender roles and increased labor-market participation and earnings.
We study whether compulsory religious education in schools affects students' religiosity as adults. We exploit the staggered termination of compulsory religious education across German states in models with state and cohort fixed effects. Using three different datasets, we find that abolishing compulsory religious education significantly reduced religiosity of affected students in adulthood. It also reduced the religious actions of personal prayer, church-going, and church membership. Beyond religious attitudes, the reform led to more equalized gender roles, fewer marriages and children, and higher labor-market participation and earnings. The reform did not affect ethical and political values or non-religious school outcomes.
Die Lohnlücke zwischen Frauen und Männern (der sogenannte Gender Pay Gap) wird üblicherweise in Bevölkerungsgruppen untersucht, die ihre Bildungslaufbahn bereits abgeschlossen haben. In diesem Beitrag betrachten wir eine frühere Phase der Berufstätigkeit, indem wir den Gender Pay Gap unter Studierenden, die neben ihrem Studium arbeiten, analysieren. Anhand von Daten aus fünf Kohorten einer Studierendenbefragung in Deutschland beschreiben wir den Gender Pay Gap und diskutieren mögliche Erklärungen. Die Ergebnisse zeigen, dass Studentinnen im Durchschnitt etwa 6% weniger verdienen als Studenten. Nach Berücksichtigung verschiedener entlohnungsrelevanter Faktoren verringert sich die Lücke auf 4,1%. Einer der Hauptgründe für die Differenz in der Entlohnung sind die unterschiedlichen Beschäftigungen, die männliche und weibliche Studierende ausüben.
Bioactive cations, including calcium, copper and magnesium, have shown the potential to become the alternative to protein growth factor-based therapeutics for bone healing. Ion substitutions are less costly, more stable, and more effective at low concentrations. Although they have been shown to be effective in providing bone grafts with more biological functions, the precise control of ion release kinetics is still a challenge. Moreover, the synergistic effect of three or more metal ions on bone regeneration has rarely been studied. In this study, vaterite-calcite CaCO3 particles were loaded with copper (Cu2+) and magnesium (Mg2+). The polyelectrolyte multilayer (PEM) was deposited on CaCuMg-CO3 particles via layer-by-layer technique to further improve the stability and biocompatibility of the particles and to enable controlled release of multiple metal ions. The PEM coated microcapsules were successfully combined with collagen at the outmost layer, providing a further stimulating microenvironment for bone regeneration. The in vitro release studies showed remarkably stable release of Cu2+ in 2 months without initial burst release. Mg2+ was released in relatively low concentration in the first 7 days. Cell culture studies showed that CaCuMg-PEM-Col microcapsules stimulated cell proliferation, extracellular maturation and mineralization more effectively than blank control and other microcapsules without collagen adsorption (Ca-PEM, CaCu-PEM, CaMg-PEM, CaCuMg-PEM). In addition, the CaCuMg-PEM-Col microcapsules showed positive effects on osteogenesis and angiogenesis in gene expression studies. The results indicate that such a functional and controllable delivery system of multiple bioactive ions might be a safer, simpler and more efficient alternative of protein growth factor-based therapeutics for bone regeneration. It also provides an effective method for functionalizing bone grafts for bone tissue engineering.
Industrial practice is characterized by random events, also referred to as internal and external turbulences, which disturb the target-oriented planning and execution of production and logistics processes. Methods of probabilistic forecasting, in contrast to single value predictions, allow an estimation of the probability of various future outcomes of a random variable in the form of a probability density function instead of predicting the probability of a specific single outcome. Probabilistic forecasting methods, which are embedded into the analytics process to gain insights for the future based on historical data, therefore offer great potential for incorporating uncertainty into planning and control in industrial environments. In order to familiarize students with these potentials, a training module on the application of probabilistic forecasting methods in production and intralogistics was developed in the learning factory 'Werk150' of the ESB Business School (Reutlingen University). The theoretical introduction to the topic of analytics, probabilistic forecasting methods and the transition to the application domain of intralogistics is done based on examples from other disciplines such as weather forecasting and energy consumption forecasting. In addition, data sets of the learning factory are used to familiarize the students with the steps of the analytics process in a practice-oriented manner. After this, the students are given the task of identifying the influencing factors and required information to capture intralogistics turbulences based on defined turbulence scenarios (e.g. failure of a logistical resource) in the learning factory. Within practical production scenario runs, the students apply probabilistic forecasting using and comparing different probabilistic forecasting methods. The graduate training module allows the students to experience the potentials of using probabilistic forecasting methods to improve production and intralogistics processes in context with turbulences and to build up corresponding professional and methodological competencies.
User innovators follow multiple diffusion and adoption pathways for their self-developed innovations. Users may choose to commercialize their self-developed products on the marketplace by becoming entrepreneurs. Few studies exist that focus on understanding personal and interpersonal factors that affect some user innovators’ entrepreneurial decision-making. Hence, this paper focuses on how user innovators make key decisions relating to opportunity recognition and evaluation and when opportunity evaluation leads to subsequent entrepreneurial action in the entrepreneurial process. We conducted an exploratory study using a multi-grounded theory methodology as the user entrepreneurship phenomenon embodies complex social processes. We collected data through the netnography approach that targeted 18 entrepreneurs with potentially relevant differences through crowdfunding platforms. We integrated self-determination, human capital, and social capital theory to address the phenomena under study. This study’s significant findings posit that users’ motives are dissatisfaction with existing goods, interest in innovation, altruism, social recognition, desire for independence, and economic benefits. Besides, use-related experience, product-related knowledge, product diffusion, and iterative feedback positively impact innovative users’ entrepreneurial decision-making.
Uncontrolled movement of instruments in laparoscopic surgery can lead to inadvertent tissue damage, particularly when the dissecting or electrosurgical instrument is located outside the field of view of the laparoscopic camera. The incidence and relevance of such events are currently unknown. The present work aims to identify and quantify potentially dangerous situations using the example of laparoscopic cholecystectomy (LC). Twenty-four final year medical students were prompted to each perform four consecutive LC attempts on a well-established box trainer in a surgical training environment following a standardized protocol in a porcine model. The following situation was defined as a critical event (CE): the dissecting instrument was inadvertently located outside the laparoscopic camera’s field of view. Simultaneous activation of the electrosurgical unit was defined as a highly critical event (hCE). Primary endpoint was the incidence of CEs. While performing 96 LCs, 2895 CEs were observed. Of these, 1059 (36.6%) were hCEs. The median number of CEs per LC was 20.5 (range: 1–125; IQR: 33) and the median number of hCEs per LC was 8.0 (range: 0–54, IQR: 10). Mean total operation time was 34.7 min (range: 15.6–62.5 min, IQR: 14.3 min). Our study demonstrates the significance of CEs as a potential risk factor for collateral damage during LC. Further studies are needed to investigate the occurrence of CE in clinical practice, not just for laparoscopic cholecystectomy but also for other procedures. Systematic training of future surgeons as well as technical solutions address this safety issue.
With the digital transformation, companies will experience a change that focuses on shaping the organization into an agile organizational form. In today's competitive and fast-moving business environment, it is necessary to react quickly to changing market conditions. Agility represents a promising option for overcoming these challenges. The path to an agile organization represents a development process that requires consideration of countless levels of the enterprise. This paper examines the impact of digital transformation on agile working practices and the benefits that can be achieved through technology. To enable a solution for today's so-called VUCA (Volatility, Uncertainty, Complexity und Ambiguity) world, agile ways of working can be applied project management requires adaptation. In the qualitative study, expert interviews were conducted and analyzed using the grounded theory method. As a result, a model can be presented that shows the influencing factors and potentials of agile management in the context of the digital transformation of medium-sized companies.
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.
Advancements in Internet of Things (IoT), cloud and mobile computing have fostered the digital enrichment—or “digitization”—of physical products, which are gaining increasing relevance in practice. According to recent studies, global IoT spending will exceed USD 1 Trillion by 2021 and there will be over 25 billion IoT connections (KPMG, 2018). Porter and Heppelmann (2014) state that IT is “revolutionizing products [as …] IT is becoming an integral part of the product itself.” Senior business executives like GE’s former CEO Jeff Immelt (2015) are even proposing that “every industrial company in the coming age is also going to become a software and analytics company.” This reflects the increasing relevance of IT components’ (i.e., software, data analytics, cloud computing) integration into previously purely physical products. We call IT-enriched physical products, “digitized” products to differentiate them from purely intangible “digital” products, such as digital music, e-books, and software. Examples of digitized products include the Philips Hue smartphone-controllable lightbulb, Audi Connect internet-connected cars, or Rolls-Royce’s sensor-enabled pay per use jet engines.
Digitized products provide their producers with a wide range of opportunities to offer new functionality and product capabilities (e.g., autonomy) that traditional, physical products do not exhibit (Porter and Heppelmann, 2014). In addition, the digitization of products allows producers to continuously repurpose their offerings, by extending and/or changing the product functionality and, thus, enabling new value creation opportunities. Based on their re-programmability and connectivity, digitized products “remain essentially incomplete […] throughout their lifetime as users continue to add and delete […] and change […] functional capabilities” (Yoo, 2013). For instance, the Philips Hue connected lightbulb enables remote control of basic functions (e.g., switching on and off the light) as well as setting more advanced light scenes for day-to-day tasks (e.g., relax, read) via Amazon’s Alexa artificial intelligence assistant (Signify, 2019), offerings that were not intended use cases when Signify (previously known as Philips Lighting) created Hue in 2012. Thus, digitized products present limitless potentials for new functionality and unforeseen use cases, which provides them with a huge innovation capacity.
Despite the limitless potentials offered by digitized products, there has been a slow uptake of digitized products by businesses so far (Jernigan et al., 2016; Mocker et al., 2019). According to a 2016 MIT Sloan Management Review report (Jernigan et al., 2016) only 24% of the investigated firms were actively using IoT technologies – a key technology for digitized products. In a more recent research study Mocker et al. (2019) found that the median revenue share from digital offerings (i.e., solutions based on IT enriched products) in large companies only accounted for 5% of the total revenue of the investigated companies.
The slow uptake of digitized products might be explained by the challenges that firms face regarding the changing nature of digitized products. Pervasive digital technologies (such as IoT) change the nature of products by adding new functionality that was previously not part of the value proposition of the products/services (e.g., a pair of shoes embedded with sensors and connectivity allows joggers to have access to data regarding their run distance, speed, etc.) (Yoo et al., 2012). The addition of new functionality and use cases of digitized products makes it harder for producers to design and develop relevant products (Hui 2014). As described in the paper ‘Do Your Customers Actually Want a “Smart” Version of Your Product?’, “just because [firms] can make something with IoT technology doesn’t mean people will want it.” (Smith, 2017).
The shift in digitized products’ nature poses new challenges for producers along the entire product development process (Porter and Heppelmann, 2015; Yoo et al., 2012) and create a paradox in product digitization, described by Yoo et al. (2012) as the paradox of pace: while technology accelerates the rate of innovation, companies need to spend more time to digitize their products, extending time to market. The production of these digitized products also becomes more challenging, e.g., as companies need to deal with different clock-speeds of software and hardware development (Porter and Heppelman, 2015). The above-mentioned challenges suggest that producers need to better understand how they can generate value from their digitized products’ generative potentials.
The body of literature on digitized products has been growing in recent years. For instance, Herterich et al. (2016) investigate how digitized product affordances (i.e., potentials) enable industrial service innovation; Nicolescu et al. (2018) explore the emerging meanings of value associated with IoT; and Benbunan-Fich (2019) studies the impact of basic wearable sensors on the quality of the user experience. However, it remains unclear what it takes for firms to generate value with their digitized product potentials. This dissertation investigates this research gap.
To generate greater value faster from digital innovation, many companies are increasing how much they learn from their own innovation efforts. However, in many companies, these changes are limited to one stakeholder group: innovation teams. Two other stakeholder groups, senior executives and experts from corporate functions, also need to learn from digital innovation initiatives. We have defined three learning imperatives that address a company’s needs to learn continually about building (1) a successful innovation, (2) a portfolio of initiatives that realizes strategic objectives faster, and (3) shared resources that propel multiple initiatives. All three imperatives involve collecting data regularly from digital innovation initiatives. In this research briefing we outline the three learning imperatives and provide examples of how companies are pursuing them to achieve strategic objectives more effectively and efficiently.
This research briefing describes the organizational capability of scaling at scale, which we define as enabling multiple digital innovation initiatives to realize bottom-line value from their innovation by leveraging shared resources. We illustrate this concept with a case study from global multi-energy company Repsol, which implemented scaling at scale to cultivate a portfolio of more than 450 initiatives and helped over seventy percent of initiatives to reach the scale-up stage. As a result, over five years Repsol realized €800 million of bottom-line value from digital innovations.
Literature reviews are essential for any scientific work, both as part of a dissertation or as a stand-alone work. Scientists benefit from the fact that more and more literature is available in electronic form, and finding and accessing relevant literature has become more accessible through scientific databases. However, a traditional literature review method is characterized by a highly manual process, while technologies and methods in big data, machine learning, and text mining have advanced. Especially in areas where research streams are rapidly evolving, and topics are becoming more comprehensive, complex, and heterogeneous, it is challenging to provide a holistic overview and identify research gaps manually. Therefore, we have developed a framework that supports the traditional approach of conducting a literature review using machine learning and text mining methods. The framework is particularly suitable in cases where a large amount of literature is available, and a holistic understanding of the research area is needed. The framework consists of several steps in which the critical mind of the scientist is supported by machine learning. The unstructured text data is transformed into a structured form through data preparation realized with text mining, making it applicable for various machine learning techniques. A concrete example in the field of smart cities makes the framework tangible.
The rapid development and growth of knowledge has resulted in a rich stream of literature on various topics. Information systems (IS) research is becoming increasingly extensive, complex, and heterogeneous. Therefore, a proper understanding and timely analysis of the existing body of knowledge are important to identify emerging topics and research gaps. Despite the advances of information technology in the context of big data, machine learning, and text mining, the implementation of systematic literature reviews (SLRs) is in most cases still a purely manual task. This might lead to serious shortcomings of SLRs in terms of quality and time. The outlined approach in this paper supports the process of SLRs with machine learning techniques. For this purpose, we develop a framework with embedded steps of text mining, cluster analysis, and network analysis to analyze and structure a large amount of research literature. Although the framework is presented using IS research as an example, it is not limited to the IS field but can also be applied to other research areas.
Data governance have been relevant for companies for a long time. Yet, in the broad discussion on smart cities, research on data governance in particular is scant, even though data governance plays an essential role in an environment with multiple stakeholders, complex IT structures and heterogeneous processes. Indeed, not only can a city benefit from the existing body of knowledge on data governance, but it can also make the appropriate adjustments for its digital transformation. Therefore, this literature review aims to spark research on urban data governance by providing an initial perspective for future studies. It provides a comprehensive overview of data governance and the relevant facets embedded in this strand of research. Furthermore, it provides a fundamental basis for future research on the development of an urban data governance framework.
With significant advancements in digital technologies, firms find themselves competing in an increasingly dynamic business environment. Therefore, the logic of business decisions is based on the agility to respond to emerging trends in a proactive way. By contrast, traditional IT governance (ITG) frameworks rely on hierarchy and standardized mechanisms to ensure better business/IT alignment. This conflict leads to a call for an ambidextrous governance, in which firms alternate between stability and agility in their ITG mechanisms. Accordingly, this research aims to explore how agility might be integrated in ITG. A quantitative research strategy is implemented to explore the impact of agility on the causal relationship among ITG, business/IT alignment, and firm performance. The results show that the integration of agile ITG mechanisms contributes significantly to the explanation of business/IT alignment. As such, firms need to develop a dual governance model powered by traditional and agile ITG mechanisms.
Organizations that operate under uncertainty need to cultivate their ability to manage their primary resource, knowledge, accordingly. Under such conditions, organizations are required to harvest knowledge from two sources: to explore knowledge that is to be found outside the organization as well as exploit knowledge that is contained within. In a knowledge management context these exploitation and exploration activities have been conceptualized as knowledge ambidexterity. While ambidexterity has been studied extensively in contexts as manufacturing or IT, the notion of knowledge ambidexterity remains scarce in current knowledge management research. This study illustrates knowledge ambidexterity and elaborates its positive impact on organizational performance. Our study furthermore answers the question of how the use of enterprise social media (ESM) can facilitate the performance effects of knowledge ambidexterity. Drawing on the theory of communication visibility, we argue that ESM (e.g., Microsoft Teams, Slack, etc.) allow employees to communicate unhindered while making these communications visible. This allows for capturing tacit knowledge within these communications - this form of knowledge is generally hard to codify and can be a source of competitive edge. With respect to knowledge ambidexterity, ESM use can capture tacit knowledge aspects originating from inside and outside the organization, which fosters the development of a competitive advantage and, thus, supports its positive effect on organizational performance. This paper contributes to IT-enabled ambidexterity research in two aspects: (1) It sheds light on knowledge ambidexterity and, thereby, addresses a major practical challenge for knowledge-intensive organizations, and (2) it elaborates on the effects that ESM use can have on the relationship between knowledge ambidexterity and organizational performance. This work-in-progress paper offers a better understanding of the phenomenon of ambidexterity in a knowledge context, while providing insights on the facilitating role of ESM. Our research serves as a foundation for future empirical examinations of the concept of knowledge ambidexterity.
Digital twins: a meta-review on their conceptualization, application, and reference architecture
(2022)
The concept of digital twins (DTs) is receiving increasing attention in research and management practice. However, various facets around the concept are blurry, including conceptualization, application areas, and reference architectures for DTs. A review of preliminary results regarding the emerging research output on DTs is required to promote further research and implementation in organizations. To do so, this paper asks four research questions: (1) How is the concept of DTs defined? (2) Which application areas are relevant for the implementation of DTs? (3) How is a reference architecture for DTs conceptualized? and (4) Which directions are relevant for further research on DTs? With regard to research methods, we conduct a meta-review of 14 systematic literature reviews on DTs. The results yield important insights for the current state of conceptualization, application areas, reference architecture, and future research directions on DTs.
Theoretical foundation, effectiveness, and design artefact for machine learning service repositories
(2022)
Machine learning (ML) has played an important role in research in recent years. For companies that want to use ML, finding the algorithms and models that fit for their business is tedious. A review of the available literature on this problem indicates only a few research papers. Given this gap, the aim of this paper is to design an effective and easy-to-use ML service repository. The corresponding research is based on a multi-vocal literature analysis combined with design science research, addressing three research questions: (1) How is current white and gray literature on ML services structured with respect to repositories? (2) Which features are relevant for an effective ML service repository? (3) How is a prototype for an effective ML service repository conceptualized? Findings are relevant for the explanation of user acceptance of ML repositories. This is essential for corporate practice in order to create and use ML repositories effectively.
We address the problem of 3D face recognition based on either 3D sensor data, or on a 3D face reconstructed from a 2D face image. We focus on 3D shape representation in terms of a mesh of surface normal vectors. The first contribution of this work is an evaluation of eight different 3D face representations and their multiple combinations. An important contribution of the study is the proposed implementation, which allows these representations to be computed directly from 3D meshes, instead of point clouds. This enhances their computational efficiency. Motivated by the results of the comparative evaluation, we propose a 3D face shape descriptor, named Evolutional Normal Maps, that assimilates and optimises a subset of six of these approaches. The proposed shape descriptor can be modified and tuned to suit different tasks. It is used as input for a deep convolutional network for 3D face recognition. An extensive experimental evaluation using the Bosphorus 3D Face, CASIA 3D Face and JNU-3D Face datasets shows that, compared to the state of the art methods, the proposed approach is better in terms of both computational cost and recognition accuracy.
Startups play a key role in software-based innovation. They make an important contribution to an economy’s ability to compete and innovate, and their importance will continue to grow due to increasing digitalization. However, the success of a startup depends primarily on market needs and the ability to develop a solution that is attractive enough for customers to choose. A sophisticated technical solution is usually not critical, especially in the early stages of a startup. It is not necessary to be an experienced software engineer to start a software startup. However, this can become problematic as the solution matures and software complexity increases. Based on a proposed solution for systematic software development for early-stage startups, in this paper, we present the key findings of a survey study to identify the methodological and technical priorities of software startups. Among other things, we found that requirements engineering and architecture pose challenges for startups. In addition, we found evidence that startups’ software development approaches do not tend to change over time. An early investment in a more scalable development approach could help avoid long-term software problems. To support such an investment, we propose an extended model for Entrepreneurial Software Engineering that provides a foundation for future research.
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.
Hybrid organic/inorganic nanocomposites combine the distinct properties of the organic polymer and the inorganic filler, resulting in overall improved system properties. Monodisperse porous hybrid beads consisting of tetraethylene pentamine functionalized poly(glycidyl methacrylateco-ethylene glycol dimethacrylate) particles and silica nanoparticles (SNPs) were synthesized under Stoeber sol-gel process conditions. A wide range of hybrid organic/silica nanocomposite materials with different material properties was generated. The effects of n(H2O)/n(TEOS) and c(NH3 ) on the hybrid bead properties particle size, SiO2 content, median pore size, specific surface area, pore volume and size of the SNPs were studied. Quantitative models with a high robustness and predictive power were established using a statistical and systematic approach based on response surface methodology. It was shown that the material properties depend in a complex way on the process factor settings and exhibit non-linear behaviors as well as partly synergistic interactions between the process factors. Thus, the silica content, median pore size, specific surface area, pore volume and size of the SNPs are non-linearly dependent on the water-to-precursor ratio. This is attributed to the effect of the water-to-precursor ratio on the hydrolysis and condensation rates of TEOS. A possible mechanism of SNP incorporation into the porous polymer network is discussed.
Turning students into Industry 4.0 entrepreneurs: design and evaluation of a tailored study program
(2022)
Startups in the field of Industry 4.0 could be a huge driver of innovation for many industry sectors such as manufacturing. However, there is a lack of education programs to ensure a sufficient number of well-trained founders and thus a supply of such startups. Therefore, this study presents the design, implementation, and evaluation of a university course tailored to the characteristics of Industry 4.0 entrepreneurship. Educational design-based research was applied with a focus on content and teaching concept. The study program was first implemented in 2021 at a German university of applied sciences with 25 students, of which 22 participated in the evaluation. The evaluation of the study program was conducted with a pretest–posttest-design targeting three areas: (1) knowledge about the application domain, (2) entrepreneurial intention and (3) psychological characteristics. The entrepreneurial intention was measured based on the theory of planned behavior. For measuring psychological characteristics, personality traits associated with entrepreneurship were used. Considering the study context and the limited external validity of the study, the following can be identified in particular: The results show that a university course can improve participants' knowledge of this particular area. In addition, perceived behavioral control of starting an Industry 4.0 startup was enhanced. However, the results showed no significant effects on psychological characteristics.
The energy turnaround, digitalization and decreasing revenues forces enterprises in the energy domain to develop new business models. Following a Design Science Research approach, we showed in two action research projects that businesses models in the energy domain result in complex ecosystems with multiple actors. Additionally, we identified that municipal utilities have problems with the systematic development of business models. In order to solve the problem, we captured together with the partners of the enterprises the requirements in a second phase. Further we developed a method which consist of the following components: Method for the creative development of a new business model in form of a Business Model Canvas (BMC). A mapping between the e3Value ontology and the BMC for modelling a business ecosystem. The Business Model Configurator (BMConfig) prototype for modelling and simulating the e3Value-Ontology. The Business model can be quantified and analyzed for its viability. We demonstrate the feasibility of our approach in business model of a power community.
Today, companies face increasing market dynamics, rapidly evolving technologies, and rapid changes in customer behavior. Traditional approaches to product development typically fail in such environments and require companies to transform their often feature-driven mindset into a product-led mindset. A promising first step on the way to a product-led company is a better understanding of how product planning can be adapted to the requirements of an increasingly dynamic and uncertain market environment in the sense of product roadmapping. The authors developed the DEEP product roadmap assessment tool to help companies evaluate their current product roadmap practices and identify appropriate actions to transition to a more product-led company. Objective: The goal of this paper is to gain insight into the applicability and usefulness of version 1.1 of the DEEP model. In addition, the benefits, and implications of using the DEEP model in corporate contexts will be explored. Method: We conducted a multiple case study in which participants were observed using the DEEP model. We then interviewed each participant to understand their perceptions of the DEEP model. In addition, we conducted interviews with each company's product management department to learn how the application of the DEEP model influenced their attitudes toward product roadmapping. Results: The study showed that by applying the DEEP model, participants better understood which artifacts and methods were critical to product roadmapping success in a dynamic and uncertain market environment. In addition, the application of the DEEP model helped convince management and other stakeholders of the need to change current product roadmapping practices. The application also proved to be a suitable starting point for the transformation in the participating companies.
There is a growing consensus in research and practice that value-creating networks and ecosystems are supplementing the traditional distinction between the internal firm and market perspectives. To achieve joint value in ecosystems, it is crucial to align the various interests of independently acting ecosystem actors and create a common vision. In this paper, we argue that the ecosystem-wide use of product roadmaps may help with this. To get a better understanding of how roadmapping is conducted in the dynamic ecosystem environment, we systematize the main characteristics of product roadmaps and perform a conceptual comparison with the known challenges of ecosystem management. Comparing the two concepts of ecosystems and product roadmaps, we highlight the fit between the characteristics and objectives of the roadmaps and the challenges of ecosystem management. Hence, we propose to experiment with the ecosystem-wide use of product roadmaps as well as the empirical study of the challenges emerging in the process and the associated redesign of the roadmaps.
Context: Companies that operate in the software-intensive business are confronted with high market dynamics, rapidly evolving technologies as well as fast-changing customer behavior. Traditional product roadmapping practices, such as fixed-time-based charts including detailed planned features, products, or services typically fail in such environments. Until now, the underlying reasons for the failure of product roadmaps in a dynamic and uncertain market environment are not widely analyzed and understood.
Objective: This paper aims to identify current challenges and pitfalls practitioners face when developing and handling product roadmaps in a dynamic and uncertain market environment.
Method: To reach our objective we conducted a grey literature review (GLR).
Results: Overall, we identified 40 relevant papers, from which we could extract 11 challenges of the application of product roadmapping in a dynamic and uncertain market environment. The analysis of the articles showed that the major challenges for practitioners originate from overcoming a feature-driven mindset, not including a lot of details in the product roadmap, and ensuring that the content of the roadmap is not driven by management or expert opinion.
Die prä-, intra- und postoperative Entitäts- und Dignitätsbestimmung von Speicheldrüsen-tumoren (ST) allein anhand von histomorphologischen Kriterien ist häufig mit großen Unsicherheiten verbunden.
Die Spektren der Raman-Spektroskopie (RS) und der Infrarot-Spektroskopie (IS) enthalten Informationen zu der molekularen Zusammensetzung des untersuchten Gewebes. Ziel der Arbeit war die Etablierung eines Gewebe-Aufarbeitungs-Workflows und die Analyse des Einflusses der Fixierung auf die spektrale Bioinformation. Zudem wird ein Überblick über den Einsatz der RS und IS im Kopf-Hals Bereich gegeben.
Es wurden 10 mm dicke, konsekutive kryo-, formalin- und paraffinfixierte ST-Gewebeschnitte von Zystadenolymphomen (n=5) und pleomorphen Adenomen (n=4) mit der RS und IS untersucht und die Daten multivariat ausgewertet. Die Messungen erfolgten in Korrelation zur Histomorphologie über einen korrespondierenden HE-Schnitt sowohl im Tumorgewebe als auch im gesunden Speicheldrüsengewebe.
In der Mittelwertspektrenanalyse zeigte sich eine deutliche Paraffin-Signatur, Formalin-Fixierung hatte keinen wesentlichen Einfluss. Dies konnte durch die Hauptkomponentenanalyse (PCA) bestätigt werden. Eine Diskriminierung von Tumor- und Nicht-Tumorgewebe durch die PCA und gekoppelte Diskriminanzanalyse war ebenfalls mit beiden spektroskopischen Methoden mit einer hohen Sensitivität möglich.
Für eine Translation von spektralen Verfahren ist das Wissen über Einflussfaktoren auf die spektrale Bioinformation der Gewebeaufarbeitung und -fixierung unabdingbar. Die Integration spektraler Verfahren additiv in bestehende Arbeitsabläufe ist möglich. Der Einfluss der Formalinfixierung auf die spektrale Bioinformation ist gering. Die bioinformatische Analyse der umfangreichen Datensätze ist herausfordernd.
IZKF Würzburg
§ 303 Schuldenkonsolidierung
(2022)
Determination of accelerometer sensor position for respiration rate detection: initial research
(2022)
Continuous monitoring of a patient's vital signs is essential in many chronic illnesses. The respiratory rate (RR) is one of the vital signs indicating breathing diseases. This article proposes the initial investigation for determining the accelerometric sensor position of a non-invasive and unobtrusive respiratory rate monitoring system. This research aims to determine the sensor position in relation to the patient, which can provide the most accurate values of the mentioned physiological parameter. In order to achieve the result, the particular system setup, including a mechanical sensor holder construction was used. The breathing signals from 5 participants were analyzed corresponding to the relaxed state. The main criterion for selecting a suitable sensor position was each patient's average acceleration amplitude excursion, which corresponds to the respiratory signal. As a result, we provided one more defined important parameter for the considered system, which was not determined before.
Sleep analysis using a Polysomnography system is difficult and expensive. That is why we suggest a non-invasive and unobtrusive measurement. Very few people want the cables or devices attached to their bodies during sleep. The proposed approach is to implement a monitoring system, so the subject is not bothered. As a result, the idea is a non-invasive monitoring system based on detecting pressure distribution. This system should be able to measure the pressure differences that occur during a single heartbeat and during breathing through the mattress. The system consists of two blocks signal acquisition and signal processing. This whole technology should be economical to be affordable enough for every user. As a result, preprocessed data is obtained for further detailed analysis using different filters for heartbeat and respiration detection. In the initial stage of filtration, Butterworth filters are used.
Generating synthetic data is a relevant point in the machine learning community. As accessible data is limited, the generation of synthetic data is a significant point in protecting patients' privacy and having more possibilities to train a model for classification or other machine learning tasks. In this work, some generative adversarial networks (GAN) variants are discussed, and an overview is given of how generative adversarial networks can be used for data generation in different fields. In addition, some common problems of the GANs and possibilities to avoid them are shown. Different evaluation methods of the generated data are also described.
The purpose of this paper is to examine the effects of perceived stress on traffic and road safety. One of the leading causes of stress among drivers is the feeling of having a lack of control during the driving process. Stress can result in more traffic accidents, an increase in driver errors, and an increase in traffic violations. To study this phenomenon, the Stress Perceived Questionnaire (PSQ) was used to evaluate the perceived stress while driving in a simulation. The study was conducted with participants from Germany, and they were grouped into different categories based on their emotional stability. Each participant was monitored using wearable devices that measured their instantaneous heart rate (HR). The preference for wearable devices was due to their non-intrusive and portable nature. The results of this study provide an overview of how stress can affect traffic and road safety, which can be used for future research or to implement strategies to reduce road accidents and promote traffic safety.
Verification of an active time constant tuning technique for continuous-time delta-sigma modulators
(2022)
In this work we present a technique to compensate the effects of R-C / g m -C time-constant (TC) errors due to process variation in continuous-time delta-sigma modulators. Local TC error compensation factors are shifted around in the modulator loop to positions where they can be implemented efficiently with finely tunable circuit structures, such as current-steering digital-to-analog converters (DAC). We apply our technique to a third-order, single-bit, low-pass continuous-time delta-sigma modulator in cascaded integrator feedback structure, implemented in a 0.35-μm CMOS process. A tuning scheme for the reference currents of the feedback DACs is derived as a function of the individual TC errors and verified by circuit simulations. We confirm the tuning technique experimentally on the fabricated circuit over a TC parameter variation range of ±20%. Stable modulator operation is achieved for all parameter sets. The measured performances satisfy the expectations from our theoretical calculations and circuit-level simulations.
Digital assistants like Alexa, Google Assistant or Siri have seen a large adoption over the past years. Using artificial intelligence (AI) technologies, they provide a vocal interface to physical devices as well as to digital services and have spurred an entire new ecosystem. This comprises the big tech companies themselves, but also a strongly growing community of developers that make these functionalities available via digital platforms. At present, only few research is available to understand the structure and the value creation logic of these AI-based assistant platforms and their ecosystem. This research adopts ecosystem intelligence to shed light on their structure and dynamics. It combines existing data collection methods with an automated approach that proves useful in deriving a network-based conceptual model of Amazon’s Alexa assistant platform and ecosystem. It shows that skills are a key unit of modularity in this ecosystem, which is linked to other elements such as service, data, and money flows. It also suggests that the topology of the Alexa ecosystem may be described using the criteria reflexivity, symmetry, variance, strength, and centrality of the skill coactivations. Finally, it identifies three ways to create and capture value on AI-based assistant platforms. Surprisingly only a few skills use a transactional business model by selling services and goods but many skills are complementary and provide information, configuration, and control services for other skill provider products and services. These findings provide new insights into the highly relevant ecosystems of AI-based assistant platforms, which might serve enterprises in developing their strategies in these ecosystems. They might also pave the way to a faster, data-driven approach for ecosystem intelligence.
An autonomous vehicle is a robotic vehicle with decision and action capability capable of performing assigned tasks without or with minimal human intervention. Autonomous cars have been in development for many years. The Society of Automotive Engineers (SAE International) published in 2014 a classification in five levels of driving automation, with level 0 corresponding to completely manual driving, and level 5 to an ideal dream where the vehicle would be able to navigate entirely autonomously for all missions and in all environments. This work addressed the navigation of an autonomous vehicle in general. We focus on one of the most complex scenarios of the road network and crossing of road intersections. In this paper, the critical features of autonomous intelligent vehicles are reviewed. Furthermore, the associated problems are presented, and the most advanced solutions are derived. This article aims to allow a novice in this field to understand the different facets of localization and perception problems for autonomous vehicles.
The Fourteenth International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2022), held between May 22 – 26, 2022, continued a series of international events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base technologies and content processing, as well as specifics in applications domains databases.
Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and agent technologies, as well as from the generalization of the XML adoption.
High-speed communications and computations, large storage capacities, and load-balancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods.
Evolution on e-business, ehealth and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the ‘de facto’ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology.
Repräsentativ zur Erkenntnis
(2022)
In einer immer komplexeren Welt wird es zunehmend schwierig, den Blick aufs große Ganze zu bewahren. Trainingsprofis können Führungskräfte und Teams dabei unterstützen -etwas mit einer speziellen Aufstellungstechnik, der prototypischen Strukturaufstellung. Kerstin Reich erklärt anhand eines Praxisbeispiels, wie sie funktioniert.
Human Digital Twin
(2022)
Man stelle sich vor, man könnte mit Unterstützung von künstlicher Intelligenz Spielabläufe von Bundesligaspielen oder sogar ganze WM-Partien simulieren. Oder der Trainer würde die Mannschaft im Endspiel anhand von Daten über den Gegner aufstellen und entsprechend psychologisch und physiologisch verschiedene Spielertypen auf den Platz schicken (vgl. Jahn). Ist das reine Fiktion? Nicht wirklich. Bereits heute werden die Leistungen von Sportlern immer häufiger digital analysiert und bewertet. Beispielsweise hat SAP eine Plattform entwickelt, die ein digitales Datenbild von Fußballspielern erstellt (vgl. SAP). Bei der letzten WM erhielt jeder Spieler über die neue Fifa Player App kurz nach der Begegnung präzise Statistiken zu seinen Leistungen während des Spiels (vgl. FIFA). Noch bessere Informationen sollen in Zukunft virtuelle Abbilder der Fußballspieler, digitale Zwillinge, liefern. Die dafür notwendigen Daten werden mithilfe von Sensoren im Trikot, in den Schuhen oder im Ball gewonnen. Durch erfassten Bewegungs- und Positionsdaten sowie Ballkontakten entsteht ein präzises Datenbild des Spielers. Solche Simulationen, die auf einem Modell des Menschen in der digitalen Welt beruhen, erfahren derzeit große Aufmerksamkeit in Wissenschaft und Praxis (vgl. van der Valk et al.). Nicht nur in der Fußballwelt, auch in der Medizin und im Kontext von Industrie 4.0 und Produktdesign, haben digitale menschliche Zwillinge das Potenzial, zu einer Schlüsseltechnologie zu werden.
Externe Ladeinfrastruktur kann rechtskonform aus dem Stromnetz einer öffentlichen Liegenschaft versorgt werden. Bisher war die Vorgabe, die Versorgung über einen eigenen (neuen) Netzanschlusspunkt zu realisieren. Die hier vorgestellte Lösung ist ökologisch, wirtschaftlich und technisch deutlich günstiger und dient als Muster für die weitere Erschließung landeseigenen Parkraums in ganz Baden-Württemberg. Ein virtuelles Kraftwerk ermöglicht den gemeinschaftsdienlichen Betrieb.
The strong demand for a transformation of the textile and fashion industry towards sustainability requires a continuous implementation of the guiding principle of Education for Sustainable Development (ESD) in education and industry [1, 2]. In a first step of the European research project "Sustainable fashion curriculum at textile Universities in Europe - Development, Implementation and Evaluation of a Teaching Module for Educators" (Fashion DIET) a continuing education module shall be created to implement ESD as a guiding principle in university teaching. The research-based teaching and learning materials are delivered through an e-learning portal.
The article pleads for Education for Sustainable Development (ESD) in the textile and fashion sector and shows possibilities how this can be implemented from elementary school to higher education and vocational training. It begins by highlighting the non-sustainable practices and deficits that can be found in the fashion and textile sector worldwide and explains the sustainability goals in the context of the UN Roadmap ESD for 2030. In order to raise the awareness for sustainability and implement these goals, education is needed. The article introduces the concept of ESD as a guiding principle with the core element design competence, implemented by the interdisciplinary method of Design Thinking (DT). In order to successfully teach the ESD-relevant design competence, various didactic principles are required. It can be shown that they are very similar to the principles and phases of DT. Within a research project DT and its potential for implementing ESD has been investigated in teaching-learning situations at elementary schools as well as in an interdisciplinary seminar for student teachers. These findings have been transferred to the EU project Fashion DIET, which pursues the goal of implementing ESD in the textile and fashion sector. By means of an online pilot workshop, the methods and principles of DT were presented and explained to lecturers, teachers and educators, who gave their feedback on the potential of DT as a method to implement ESD as a guiding principle in their curricula.
Student-faculty interactions that promote learning are essential contributors to student retention, academic success and satisfaction. But the factors that causally initiate and frame these interactions are not well understood. Only if students evaluate these interactions as positive will they seek them. We conducted a survey experiment with students (n = 375) from a tuition-fee-free German business school, using conditional process analysis to assess which factors frame effective interactions. We focus on out-of-classroom standard and non-standard requests that students make to faculty, then investigate how faculty and student gender and students’ academic entitlement influence the interaction. Our study examines how students evaluate the interaction with faculty: when they seek interaction, their expectations of getting their requests approved, and their disappointment when their requests are declined. We find a significant influence of the request type along with moderating effects of faculty gender, student gender and student entitlement, particularly for non-standard work requests. We conclude with policy implications for university management: developing target-group-specific measures that facilitate the desired and positively evaluated student-faculty interactions might benefit all university stakeholders.
For optimization of production processes and product quality, often knowledge of the factors influencing the process outcome is compulsory. Thus, process analytical technology (PAT) that allows deeper insight into the process and results in a mathematical description of the process behavior as a simple function based on the most important process factors can help to achieve higher production efficiency and quality. The present study aims at characterizing a well-known industrial process, the transesterification reaction of rapeseed oil with methanol to produce fatty acid methyl esters (FAME) for usage as biodiesel in a continuous micro reactor set-up. To this end, a design of experiment approach is applied, where the effects of two process factors, the molar ratio and the total flow rate of the reactants, are investigated. The optimized process target response is the FAME mass fraction in the purified nonpolar phase of the product as a measure of reaction yield. The quantification is performed using attenuated total reflection infrared spectroscopy in combination with partial least squares regression. The data retrieved during the conduction of the DoE experimental plan were used for statistical analysis. A non-linear model indicating a synergistic interaction between the studied factors describes the reactor behavior with a high coefficient of determination (R²) of 0.9608. Thus, we applied a PAT approach to generate further insight into this established industrial process.
„Tue Gutes und rede darüber“ lautet eine leicht verständliche Ur-Definition von Öffentlichkeitsarbeit, die längst zu einem Sprichwort geworden ist. Im Laufe der Zeit kamen auf die Public Relations zahlreiche Veränderungen zu: Die Sozialen Medien bewirkten, dass der interaktive Dialog und das Zuhören in den Fokus der PR rückten: „Tue Gutes und lasse andere darüber reden“ war die hierzu passende Aktualisierung. Einer der jüngsten Trends in der PR ist die Nachhaltigkeitskommunikation, die sogenannte „Green PR“, das heißt die Umsetzung glaubwürdiger, nachhaltiger Kommunikationsstrategien. Damit erfährt das Sprichwort ein weiteres Update zu „Tue nachhaltig Gutes und lasse andere dabei mitreden.“
This article provides a stochastic agent-based model to exhibit the role of aggregation metrics in order to mitigate polarization in a complex society. Our sociophysics model is based on interacting and nonlinear Brownian agents, which allow us to study the emergence of collective opinions. The opinion of an agent, x i (t) is a continuous positive value in an interval [0, 1]. We find (i) most agent-metrics display similar outcomes. (ii) The middle-metric and noisy-metric obtain new opinion dynamics either towards assimilation or fragmentation. (iii) We show that a developed 2-stage metric provide new insights about convergence and equilibria. In summary, our simulation demonstrates the power of institutions, which affect the emergence of collective behavior. Consequently, opinion formation in a decentralized complex society is reliant to the individual information processing and rules of collective behavior.
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.
How mechanical and physicochemical material characteristics influence adipose-derived stem cell fate
(2023)
Adipose-derived stem cells (ASCs) are a subpopulation of mesenchymal stem cells. Compared to bone marrow-derived stem cells, they can be harvested with minimal invasiveness. ASCs can be easily expanded and were shown to be able to differentiate into several clinically relevant cell types. Therefore, this cell type represents a promising component in various tissue engineering and medical approaches (e.g., cell therapy). In vivo cells are surrounded by the extracellular matrix (ECM) that provides a wide range of tissue-specific physical and chemical cues, such as stiffness, topography, and chemical composition. Cells can sense the characteristics of their ECM and respond to them in a specific cellular behavior (e.g., proliferation or differentiation). Thus, in vitro biomaterial properties represent an important tool to control ASCs behavior. In this review, we give an overview of the current research in the mechanosensing of ASCs and current studies investigating the impact of material stiffens, topography, and chemical modification on ASC behavior. Additionally, we outline the use of natural ECM as a biomaterial and its interaction with ASCs regarding cellular behavior.
In countries such as Germany, where municipalities have planning sovereignty, problems of urban sprawl often arise. As the dynamics of land development have not substantially subsided over the last years, the national government decided to test the instrument of ‘Tradable Planning Permits’ (TPP) in a nationwide field experiment with 87 municipalities involved. The field experiment was able to implement the key features of a TPP system in a laboratory setting with approximated real socioeconomic and planning conditions. In a TPP system allocated planning permits must be used by municipalities for developing land. The permits can be traded between local jurisdictions, so that they have flexibility in deciding how to comply with the regulation. In order to evaluate the performance of such a system, specific field data about future building areas and their impact on community budgets for the period 2014–2028 were collected. The field experiment contains several sessions with representatives of the municipalities and with students. The participants were confronted with two (municipalities) and four (students) schemes. The results show that a trading system can curb down land development in an effective and also efficient manner. However, depending on the regulatory framework, the trading schemes show different price developments and distributional effects. The unexperienced representatives of the local authorities can easily handle with the permits in the administration and in the established market. A trading scheme sets very high incentives to save open space and to direct development activities to areas within existing planning boundaries. It is therefore a promising instrument for Germany and also other regions or countries with an established land-use planning system.
At the beginning of 2022, Frontiers in Bioengineering and Biotechnology - Biomaterials Section has published a Research Topic on “Functional Surfaces and Biomaterials.” The aim of this Research Topic is to summarize the current state of research and development in the field of functional surfaces and biomaterials with a particular focus on biotechnological and medical applications.
The guest editorial team would like to thank all colleagues from around the world who submitted their reviews and research articles for the Research Topic. By the end of August 2022, we have successfully collected 20 articles by 138 participating authors following the peer review process. We also tried to select manuscripts from different research areas to cover the most relevant Research Topic of interest, from drug delivery systems to bone tissue engineering to biosensors and general aspects in biomedicine. By the end of December, the 20 articles had been viewed for more than 21000 times with downloads more than 4,000 times, and 11 articles have reached more than 1,000 views.
Titanium(IV) surface complexes bearing chelating catecholato ligands for enhanced band-gap reduction
(2023)
Protonolysis reactions between dimethylamido titanium(IV) catecholate [Ti(CAT)(NMe2)2]2 and neopentanol or tris(tert-butoxy)silanol gave catecholato-bridged dimers [(Ti(CAT)(OCH2tBu)2)(HNMe2)]2 and [Ti(CAT){OSi(OtBu)3}2(HNMe2)2]2, respectively. Analogous reactions using the dimeric dimethylamido titanium(IV) (3,6-di-tert-butyl)catecholate [Ti(CATtBu2-3,6)(NMe2)2]2 yielded the monomeric Ti(CATtBu2-3,6)(OCH2tBu)2(HNMe2)2 and Ti(CATtBu2-3,6)[OSi(OtBu)3]2(HNMe2)2. The neopentoxide complex Ti(CATtBu2-3,6)(OCH2tBu)2(HNMe2)2 engaged in further protonolysis reactions with Si–OH groups and was consequentially used for grafting onto mesoporous silica KIT-6. Upon immobilization, the surface complex [Ti(CATtBu2-3,6)(OCH2tBu)2(HNMe2)2]@[KIT-6] retained the bidentate chelating geometry of the catecholato ligand. This convergent grafting strategy was compared with a sequential and an aqueous approach, which gave either a mixture of bidentate chelating species with a bipodally anchored Ti(IV) center along with other physisorbed surface species or not clearly identifiable surface species. Extension of the convergent and aqueous approaches to anatase mesoporous titania (m-TiO2) enabled optical and electronic investigations of the corresponding surface species, revealing that the band-gap reduction is more pronounced for the bidentate chelating species (convergent approach) than for that obtained via the aqueous approach. The applied methods include X-ray photoelectron spectroscopy, ultraviolet photoelectron spectroscopy, and solid-state UV/vis spectroscopy. The energy-level alignment for the surface species from the aqueous approach, calculated from experimental data, accounts for the well-known type II excitation mechanism, whereas the findings indicate a distinct excitation mechanism for the bidentate chelating surface species of the material [Ti(CATtBu2-3,6)(OCH2tBu)2(HNMe2)2]@[m-TiO2].
The Commitment of Traders report (CoT) has been around for over 30 years, consistently revealing the futures positions of key market players. This study's primary aim is to use the comprehensive data from the Commitment of Traders reports to develop a short-term reversal trading strategy. Against the benchmark, a S&P 500 buy-and-hold approach with a Sharpe ratio of 1.07, the CoT long only strategy generated significant results in six individual markets. Extending the strategy to long-and-short, two markets outperformed the benchmark significantly. However, a scenario analysis indicated underperformance of the CoT strategy when traded in a portfolio, confirming that the chosen strategy parameters could not generate excess Sharpe ratios. Our results indicate that the Commodity Futures Trading Commission, more specifically the CoT report, contributed to efficient derivatives market.
Purpose
The authors study the valuation effect of corporate diversification in the initial phase of the COVID-19 pandemic in 2020 in Europe.
Design/methodology/approach
Applying a cross-sectional regression model to a sample of public companies headquartered in the European Union, the authors investigate the existence of and the change in a diversification discount between 2018 and 2020. By applying the Excess Q methodology, the authors make an industry adjustment of diversified companies to measure the value effect of corporate diversification.
Findings
The authors find an economically and statistically significant diversification discount that increases from an average Excess Q of −0.05 in 2019 to −0.10 in 2020. The diversified companies' inferior fundamental financial performance in 2020 accompanies the discount. The results deviate from those of previous research, which mostly show a decrease in the diversification discount in economic crises, and thereby, shed doubt on whether diversification provides insurance against pandemic-induced adverse value effects.
Originality/valueThe study distinguishes the role of corporate diversification during recessionary periods by establishing that the valuation effect of diversification depends on the nature of the crisis. The analysis incorporates criticism of previous studies concerning a biased methodology and uniform data source by applying the Excess Q methodology and using FactSet industry segment data.
Polyester fibers are widely employed in a multitude of sectors and applications from the technical textiles to everyday life thanks to their durability, strength, and flexibility. Despite these advantages, polyester lacks in dyeability, adhesion of coating, hydrophilicity, and it is characterized by a low wettability respect to natural fibers. On this regard, beyond the harmful hydrophobic textile finishings of polyester fabrics containing fluorine-compounds, and in order to avoid pre-treatments, such as laser irradiation to improve their surface properties, research is moving towards the development of fluorine-free and safer coatings. In this work, the (3-glycidyloxypropyl)trimethoxysilane (GPTMS) and various long alkyl-chain alkoxysilanes were employed for the fabrication in the presence of a catalyst of a water-based superhydrophobic finishing for polyester fabrics with a simple sol-gel, non-fluorinated, sustainable approach and the dip-pad-dry-cure method. The finished polyester fabrics surface properties were investigated by static and dynamic water repellency tests. Additionally, the resistance to common water-based liquids, abrasion resistance, moisture adsorption, and air permeability measurements were performed. Scanning electron microscopy was employed to examine the micro- and nano-morphology of the functionalized polyester fabrics surfaces. The obtained superhydrophobic finishings displayed high water-based stain resistance as well as good hydrophobicity after different cycles of abrasion.
Unternehmertum spielt sowohl für die Entwicklung afrikanischer Länder eine Rolle, als auch für ausländische Unternehmen mit Markteintrittsplänen. Die infrastrukturellen und institutionellen Rahmenbedingungen für Unternehmertum sind nach wie vor schwierig, wobei aber die fortschreitende Digitalisierung zu einer zunehmend aktiven Start-Up Szene in vielen afrikanischen Ländern führt. Nach wie vor existiert ein Mismatch zwischen den Bereichen in denen Start-Ups entstehen und den Bereichen, wo ausländische Unternehmen Partner für den Markteintritt suchen. Somit bleibt es trotz positiver Entwicklung beim Unternehmertum in absehbarer Zeit schwierig adäquate Partner zu finden.
Artificial intelligence is considered to be a significant technology for driving the future evolution of smart manufacturing environments. At the same time, automated guided vehicles (AGVs) play an essential role in manufacturing systems due to their potential to improve internal logistics by increasing production flexibility. Thereby, the productivity of the entire system relies on the quality of the schedule, which can achieve production cost savings by minimizing delays and the total makespan. However, traditional scheduling algorithms often have difficulties in adapting to changing environment conditions, and the performance of a selected algorithm depends on the individual scheduling problem. Therefore, this paper aimed to analyze the scheduling problem classes of AGVs by applying design science research to develop an algorithm selection approach. The designed artifact addressed a catalogue of characteristics that used several machine learning algorithms to find the optimal solution strategy for the intended scheduling problem. The contribution of this paper is the creation of an algorithm selection method that automatically selects a scheduling algorithm, depending on the problem class and the algorithm space. In this way, production efficiency can be increased by dynamically adapting the AGV schedules. A computational study with benchmark literature instances unveiled the successful implementation of constraint programming solvers for solving JSSP and FJSSP scheduling problems and machine learning algorithms for predicting the most promising solver. The performance of the solvers strongly depended on the given problem class and the problem instance. Consequently, the overall production performance increased by selecting the algorithms per instance. A field experiment in the learning factory at Reutlingen University enabled the validation of the approach within a running production scenario.
Erst die Corona-Pandemie, dann der Krieg in der Ukraine und die Energiekrise. Es scheint als rutschten wir von einer Katastrophe in die andere ohne zu wissen was als Nächstes kommt. Wir müssen uns der Frage stellen, wie wir solchen Krisen zukünftig begegnen können.
Auch die Forscherinnen und Forscher an der Hochschule Reutlingen leisten einen Beitrag dazu, unsere Gesellschaft widerstandsfähiger und robuster zu machen – sei es durch pfiffige Lösungen für die Energiekrise, durch kompetente Beratung zu Ressourceneffizienz und Lieferketten oder durch aktuelle Forschungsansätze zu resilienten IT-Strukturen und einer resilienten Wirtschaft.
Supply chains have evolved into dynamic, interconnected supply networks, which increases the complexity of achieving end-to-end traceability of object flows and their experienced events. With its capability of ensuring a secure, transparent, and immutable environment without relying on a trusted third party, the emerging blockchain technology shows strong potential to enable end-to-end traceability in such complex multitiered supply networks. This paper aims to overcome the limitations of existing blockchain-based traceability architectures regarding their object-related event mapping ability, which involves mapping the creation and deletion of objects, their aggregation and disaggregation, transformation, and transaction, in one holistic architecture. Therefore, this paper proposes a novel ‘blueprint-based’ token concept, which allows clients to group tokens into different types, where tokens of the same type are non-fungible. Furthermore, blueprints can include minting conditions, which, for example, are necessary when mapping assembly processes. In addition, the token concept contains logic for reflecting all conducted object-related events in an integrated token history. Finally, for validation purposes, this article implements the architecture’s components in code and proves its applicability based on the Ethereum blockchain. As a result, the proposed blockchain-based traceability architecture covers all object-related supply chain events and proves its general-purpose end-to-end traceability capabilities of object flows.
Cytocompatibility analyses of new implant materials or biomaterials are not only prescribed by the Medical Device Regulation (MDR), as defined in the DIN ISO Norm 10993-5 and -12, but are also increasingly replacing animal testing. In this context, jellyfish collagen has already been established as an alternative to mammalian collagen in different cell culture conditions, but a lack of knowledge exists about its applicability for cytocompatibility analyses of biomaterials. Thus, the present study was conducted to compare well plates coated with collagen type 0 derived from Rhizostoma pulmo with plates coated with bovine and porcine collagen. The coated well plates were analysed in vitro for their cytocompatibility, according to EN ISO 10993-5/−12, using both L929 fibroblasts and MC3T3 pre-osteoblasts. Thereby, the coated well plates were compared, using established materials as positive controls and a cytotoxic material, RM-A, as a negative control. L929 cells exhibited a significantly higher viability (#### p < 0.0001), proliferation (## p < 0.01), and a lower cytotoxicity (## p < 0.01 and # p < 0.05)) in the Jellagen® group compared to the bovine and porcine collagen groups. MC3T3 cells showed similar viability and acceptable proliferation and cytotoxicity in all collagen groups. The results of the present study revealed that the coating of well plates with collagen Type 0 derived from R. pulmo leads to comparable results to the case of well plates coated with mammalian collagens. Therefore, it is fully suitable for the in vitro analyses of the cytocompatibility of biomaterials or medical devices.
This paper presents a description model for smart, connected devices used in a manufacturing context. Similar to the wide spread adoption of smart products for personal and private usage, recent developments lead to a plethora of devices offering a variety of features and capabilities. Manufacturing companies undergoing digital transformation demand guidance with respect to the systematic introduction of smart, connected devices. The introduction of smart connected devices constitutes a strategic decision cost due to the high future committed cost after introduction and maintaining a smart device fleet by a vendor. This paper aims to support the introduction efforts by classifying the devices and thus helping companies identify their specific requirements for smart, connected devices before initiating widespread procurement. By mapping the features of these devices based on various attributes, allows the clustering of smart, connected devices including a requirement list for their implementation on the shopfloor. Four individual commercially available smart connected devices were analyzed using the description model.
Parallel grippers offer multiple applications thanks to their flexibility. Their application field ranges from aerospace and automotive to medicine and communication technologies. However, the application of grippers has the problem of exhibition wear and errors during the execution of their operation. This affects the performance of the gripper. In this context, the remaining useful life (RUL) defines the remaining lifespan until failure for an asset at a particular time of operation occurs. The exact lifespan of an asset is uncertain, thus the RUL model and estimation must be derived from available sources of information. This paper presents a method for the estimation of the RUL for a two-jaw parallel gripper. After the introduction to the topic, an overview of existing literature and RUL methods are presented. Subsequently, the method for estimating the RUL of grippers is explained. Finally, the results are summarized and discussed before the outlook and further challenges are presented.
In diesem Beitrag wird der Einfluss von Zuschauern nach den pandemiebedingten Geisterspielen auf den Heimvorteil in der ersten Fußball-Bundesliga analysiert. Für die empirische Untersuchung werden die fünf Spielzeiten 2017/18 bis 2021/22 betrachtet. Während in der Geisterspielphase in der Saison 2019/20 der Heimvorteil vollständig verschwindet, steigt der Heimvorteil in der zweiten Geisterspielphase in der Saison 2020/21 mit der Zeit wieder auf vorpandemisches Niveau an. In der Saison 2021/22 ist nach einer kurzen Phase mit eingeschränkten Zuschauerkapazitäten ein signifikant größerer Heimvorteil als in der Zeit vor der Pandemie zu beobachten. Der überdurchschnittlich positive Effekt der Zuschauer in dieser letzten Phase verschwindet mit der Zeit trotz steigender Zuschauerzahlen. Der Einfluss von Fans auf den Heimvorteil ist insgesamt insbesondere auf psychologische Effekte auf die Spieler der Heimmannschaften zurückzuführen.
Artificial Intelligence (AI) in der Markenführung: Künstliche Neuronale Netze zur Markenimagemessung
(2023)
Da Künstliche Neuronale Netze die Modellierung nichtlinearer und vielschichtiger Beziehungen ermöglichen, befasst sich dieser Beitrag mit deren Einsatzmöglichkeiten für die methodisch anspruchsvolle Analyse und Messung des Markenimages. Zur Veranschaulichung des konzeptionellen Ansatzes wird am empirischen Beispiel des Sportartikelherstellers adidas ein mehrschichtiges Künstliches Neuronales Netz zwischen den Bewertungen spezifischer Markenattribute und der Gesamtbewertung der Marke erzeugt. Auf der Grundlage einer Analyse der Verbindungsgewichte des Künstliches Neuronales Netzes wird die Bedeutung verschiedener Markenattribute für die Markenbewertung gemessen, wodurch sich konkrete Implikationen für die Praxis der Markenführung ableiten lassen.
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.
In order to ensure sufficient recovery of the human body and brain, healthy sleep is indispensable. For this purpose, appropriate therapy should be initiated at an early stage in the case of sleep disorders. For some sleep disorders (e.g., insomnia), a sleep diary is essential for diagnosis and therapy monitoring. However, subjective measurement with a sleep diary has several disadvantages, requiring regular action from the user and leading to decreased comfort and potential data loss. To automate sleep monitoring and increase user comfort, one could consider replacing a sleep diary with an automatic measurement, such as a smartwatch, which would not disturb sleep. To obtain accurate results on the evaluation of the possibility of such a replacement, a field study was conducted with a total of 166 overnight recordings, followed by an analysis of the results. In this evaluation, objective sleep measurement with a Samsung Galaxy Watch 4 was compared to a subjective approach with a sleep diary, which is a standard method in sleep medicine. The focus was on comparing four relevant sleep characteristics: falling asleep time, waking up time, total sleep time (TST), and sleep efficiency (SE). After evaluating the results, it was concluded that a smartwatch could replace subjective measurement to determine falling asleep and waking up time, considering some level of inaccuracy. In the case of SE, substitution was also proved to be possible. However, some individual recordings showed a higher discrepancy in results between the two approaches. For its part, the evaluation of the TST measurement currently does not allow us to recommend substituting the measurement method for this sleep parameter. The appropriateness of replacing sleep diary measurement with a smartwatch depends on the acceptable levels of discrepancy. We propose four levels of similarity of results, defining ranges of absolute differences between objective and subjective measurements. By considering the values in the provided table and knowing the required accuracy, it is possible to determine the suitability of substitution in each individual case. The introduction of a “similarity level” parameter increases the adaptability and reusability of study findings in individual practical cases.
Digitalisierung in Corporate Mergers & Acquisitions (M&A)-Prozessen birgt ein erhebliches Potenzial zur Effizienz- und Effektivitätssteigerung, erfährt jedoch bislang in der betrieblichen Praxis nur eine geringe Aufmerksamkeit. Dieser Beitrag schlägt angesichts dessen ein Reifegradmodell vor, womit sich der Ist-Stand der digitalen Reife eines Unternehmens bei Corporate M&A ermitteln und darauf aufbauend Optimierungspotenziale identifizieren lassen. Grundlage der Modellerstellung sind einerseits eine Analyse der vorhandenen Reifegradmodelle und andererseits Interviews mit M&A-Experten unterschiedlicher Unternehmen.
The scoring of sleep stages is one of the essential tasks in sleep analysis. Since a manual procedure requires considerable human and financial resources, and incorporates some subjectivity, an automated approach could result in several advantages. There have been many developments in this area, and in order to provide a comprehensive overview, it is essential to review relevant recent works and summarise the characteristics of the approaches, which is the main aim of this article. To achieve it, we examined articles published between 2018 and 2022 that dealt with the automated scoring of sleep stages. In the final selection for in-depth analysis, 125 articles were included after reviewing a total of 515 publications. The results revealed that automatic scoring demonstrates good quality (with Cohen's kappa up to over 0.80 and accuracy up to over 90%) in analysing EEG/EEG + EOG + EMG signals. At the same time, it should be noted that there has been no breakthrough in the quality of results using these signals in recent years. Systems involving other signals that could potentially be acquired more conveniently for the user (e.g. respiratory, cardiac or movement signals) remain more challenging in the implementation with a high level of reliability but have considerable innovation capability. In general, automatic sleep stage scoring has excellent potential to assist medical professionals while providing an objective assessment.
Die folgende Veröffentlichung ist ein Konferenzband, der im Sommersemester 2023 stattgefundenen Studierendenkonferenz Informatics Inisde, die für die Fakultät Informatik und die Studierenden ein besonderes Ereignis ist. Mit der Veröffentlichung Ihrer Artikel in diesem Konferenzband haben die Studierende eine handfeste Publikation, die durch ein Peer-Review inhaltlich qualitätsgesichert ist.
In diesem Jahr gibt es eine neue Herausforderung: Seit dem Jahr 2022 steht ChatGPT von OpenAI zur Verfügung, das verblüffende Texte mit nachvollziehbarer Argumentation verfassen kann. Eine Nutzung des Werkzeugs für die Erstellung eines wissenschaftlichen Artikels ist denkbar und gleichzeitig schwer zu beweisen. Ein kritischer Umgang mit Technologie ist wichtiger als ein pauschales Verbot. Dennoch braucht es Regeln im Umgang mit Künstlicher Intelligenz, die einen ethisch richtigen Einsatz solcher Werkzeuge begrenzt. Umso wichtiger ist es, dass umfassender Sachverstand und kritisches Denken vermittelt wird, damit mögliche Fehler oder Plagiatsfälle entlarvt werden können.
Damit sind wir mitten im Thema: Informatik ist allgegenwärtig und in äußerst vielen Produkten in der Industrie und des täglichen Lebens vorhanden. Die vielfältigen Aufsätze dieser Konferenz zeigen das. Sehen Sie selbst, wie breit die Verfahren, Algorithmen, Methoden und Technologieanwendungen sind: Von Augmented-Reality, über Videoübertragung im Operationssaal, hin zu Standards für strukturierten Daten und Künstlicher Intelligenz zeigen die Beiträge doch, wie weit läufig die Informatik inzwischen ist. Allen gemeinsam ist eines: Die menschzentrierte Anwendung von Technologie, die in dem Master Human-centered Computing als Basis aller Veranstaltungen aufgefasst werden.
Background: Polysomnography (PSG) is the gold standard for detecting obstructive sleep apnea (OSA). However, this technique has many disadvantages when using it outside the hospital or for daily use. Portable monitors (PMs) aim to streamline the OSA detection process through deep learning (DL).
Materials and methods: We studied how to detect OSA events and calculate the apnea-hypopnea index (AHI) by using deep learning models that aim to be implemented on PMs. Several deep learning models are presented after being trained on polysomnography data from the National Sleep Research Resource (NSRR) repository. The best hyperparameters for the DL architecture are presented. In addition, emphasis is focused on model explainability techniques, concretely on Gradient-weighted Class Activation Mapping (Grad-CAM).
Results: The results for the best DL model are presented and analyzed. The interpretability of the DL model is also analyzed by studying the regions of the signals that are most relevant for the model to make the decision. The model that yields the best result is a one-dimensional convolutional neural network (1D-CNN) with 84.3% accuracy.
Conclusion: The use of PMs using machine learning techniques for detecting OSA events still has a long way to go. However, our method for developing explainable DL models demonstrates that PMs appear to be a promising alternative to PSG in the future for the detection of obstructive apnea events and the automatic calculation of AHI.
Hybrides Arbeiten in digitalen Prozessen sollte eigentlich sehr gut funktionieren. Durch die Digitalisierung werden Schnittstellen zwischen Abteilungen und Funktionen standardisiert sowie Abläufe durch Workflow-Systeme vorgegeben und ganz oder teilweise automatisiert. Es werden Aufgaben eindeutig zugewiesen, Datenverluste verhindert und Abweichungen vermieden. Die Nachteile der häufig noch etablierten tayloristischen, funktionsorientierten Silo-Aufbauorganisation in administrativen Bereichen werden dadurch ebenso kompensiert wie die räumliche Trennung der beteiligten Personen in einer hybriden Arbeitswelt.
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.
Purpose – This paper explores, which employer attractiveness attributes Generation Z (Gen Z) talents prioritize. Comparing the findings for female and male participants, this study examines whether gender-specific work value orientations prevail among Gen Z talents and impact their expectations toward employers.
Design/methodology/approach – A survey was conducted among 308 students of business, economics and management in Germany. Data were collected using the employer attractiveness scale of Berthon and colleagues (2005) complemented by an additional dimension focusing on work–life balance.
Findings – Findings indicate that Gen Z talents primarily expect a fun work environment, a positive team atmosphere and supportive relations with colleagues and superiors. Application aspects and work–life balance enabling services are expected the least. Expectations of four of the six attributes measured differ significantly among women and men, indicating that traditional gender assumptions continue to be reflected in the work value orientations of Gen Z talents.
Research limitations/implications – The sample was limited to business, economics and management students in Germany. Additional research should include a wider variety of respondents of different disciplines and countries.
Practical implications – Practical implications refer to emphasizing the social value of employment in the employee value proposition and customizing employer branding activities by gender.
Originality/value – This study contributes to the literature by empirically determining which employer attractiveness attributes Gen Z talents expect and whether and how these expectations vary by gender.
AI-based prediction and recommender systems are widely used in various industry sectors. However, general acceptance of AI-enabled systems is still widely uninvestigated. Therefore, firstly we conducted a survey with 559 respondents. Findings suggested that AI-enabled systems should be fair, transparent, consider personality traits and perform tasks efficiently. Secondly, we developed a system for the Facial Beauty Prediction (FBP) benchmark that automatically evaluates facial attractiveness. As our previous experiments have proven, these results are usually highly correlated with human ratings. Consequently they also reflect human bias in annotations. An upcoming challenge for scientists is to provide training data and AI algorithms that can withstand distorted information. In this work, we introduce AntiDiscriminationNet (ADN), a superior attractiveness prediction network. We propose a new method to generate an unbiased convolutional neural network (CNN) to improve the fairn ess of machine learning in facial dataset. To train unbiased networks we generate synthetic images and weight training data for anti-discrimination assessments towards different ethnicities. Additionally, we introduce an approach with entropy penalty terms to reduce the bias of our CNN. Our research provides insights in how to train and build fair machine learning models for facial image analysis by minimising implicit biases. Our AntiDiscriminationNet finally outperforms all competitors in the FBP benchmark by achieving a Pearson correlation coefficient of PCC = 0.9601.