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Based on social information processing theory, this research examines whether and how an employee’s proactive personality influences intrinsic and extrinsic career growth. It also examines the mediating effects of two types of proactive behaviors (voice behavior and taking charge) and the moderating effect of a leader’s proactive personality. A sample of 307 employee-leader dyads participated in this survey. Structural equation modeling was used to test the hypotheses, and the bootstrap procedure was used to test the indirect effects. Results show that an employee’s proactive personality has significant positive effects on both intrinsic and extrinsic career growth. The mediating effect of taking charge was confirmed, while the mediating effect of voice behavior was not. Leader proactive personality weakens the relationship between employee proactive personality and the two types of proactive behaviors. Employee proactive personality is more positively related to intrinsic and extrinsic career growth via proactive behaviors when a leader’s proactive personality is low. This study extends the literature on proactive personality, proactive behavior, and career development by examining the underlying determination, mediation, and moderation mechanisms.
Evaluation of a contactless accelerometer sensor system for heart rate monitoring during sleep
(2024)
The monitoring of a patient's heart rate (HR) is critical in the diagnosis of diseases. In the detection of sleep disorders, it also plays an important role. Several techniques have been proposed, including using sensors to record physiological signals that are automatically examined and analysed. This work aims to evaluate using a contactless HR monitoring system based on an accelerometer sensor during sleep. For this purpose, the oscillations caused by chest movements during heart contractions are recorded by an installation mounted under the bed mattress. The processing algorithm presented in this paper filters the signals and determines the HR. As a result, an average error of about 5 bpm has been documented, i.e., the system can be considered to be used for the forecasted domain.
In this paper, the essential sponsorship basics are presented and the communication instrument of sports sponsorship is illustrated. Building on this, both the perspectives of sponsors and sponsees are examined in detail. In addition, the special features of sports event sponsorships are highlighted. Finally, current developments in sports sponsorship in the context of the FIFA Soccer World Cup 2022 in Qatar and the UEFA European Soccer Championship 2024 in Germany are compared and discussed.
Business Process Management (BPM) ist aufgrund seiner Bedeutung für prozessorientierte Unternehmen und den daraus resultierenden Anforderungen hinsichtlich interner Betriebsorganisation und Audits, ein zentraler Bestandteil. Die Einführung und Aufrechterhaltung von BPM stellt jedoch einen erheblichen Aufwand dar, da Prozesse aufgenommen, modelliert und aktuell gehalten werden müssen. Empirische Belege zeigen, dass erfolgreiche Prozessmodellierung dabei eine besondere Herausforderung darstellt, welche häufig nicht zufriedenstellend nachhaltig gelingt. Ein wesentlicher Erfolgsfaktor für die nachhaltige Prozessorientierung in Unternehmen ist somit die konsistente und aktuelle Prozessmodellierung, sowie deren Adaption an externe und interne Veränderungen. Mittels einer Literaturrecherche werden die relevanten Dimensionen zur nachhaltigen Prozessorientierung auf Grundlage der Prozessmodellierung ermittelt. Auf deren Basis wird ein adaptives handlungsorientiertes Framework für die praktische Anwendung in Unternehmen abgeleitet.
Rare but extreme events, such as pandemics, terror attacks, and stock market collapses, pose a risk that could undermine cooperation in societies and groups. We extend the public goods game (PGG) to investigate the relationship between rare but extreme external risks and cooperation in a laboratory experiment. By incorporating risk as an external random variable in the PGG, independent of the participants’ contributions, we preserve the economic equilibrium of non-cooperation in the original game. Furthermore, we examine whether cooperation can be restored by the relatively simple intervention of informing about countermeasures while keeping the actual risk constant. Our experimental results reveal that on average extreme risks indeed decrease contributions by about 20%; however, countermeasure information increases contributions by about 10%. Specifically, in the first interactions, cooperation levels can even reach those observed in the riskless baseline. Our results suggest that countermeasure information could help reinforce social cohesion and resilience in the face of rare but extreme risks.
Menopause is the permanent cessation of menstruation occurring naturally in women's aging. The most frequent symptoms associated with menopausal phases are mucosal dryness, increased weight and body fat, and changes in sleep patterns. Oral symptoms in menopause derived from saliva flow reduction can lead to dry mouth, ulcers, and alterations of taste and swallowing patterns. However, the oral health phenotype of postmenopausal women has not been characterized. The aim of the study was to determine postmenopausal women's oral phenotype, including medical history, lifestyle, and oral assessment through artificial intelligence algorithms. We enrolled 100 postmenopausal women attending the Dental School of the University of Seville were included in the study. We collected an extensive questionnaire, including lifestyle, medication, and medical history. We used an unsupervised k-means algorithm to cluster the data following standard features for data analysis. Our results showed the main oral symptoms in our postmenopausal cohort were reduced salivary flow and periodontal disease. Relying on the classical assessment of the collected data, we might have a biased evaluation of postmenopausal women. Then, we used artificial intelligence analysis to evaluate our data obtaining the main features and providing a reduced feature defining the oral health phenotype. We found 6 clusters with similar features, including medication affecting salivation or smoking as essential features to obtain different phenotypes. Thus, we could obtain main features considering differential oral health phenotypes of postmenopausal women with an integrative approach providing new tools to assess the women in the dental clinic.
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.
Wave-like differential equations occur in many engineering applications. Here the engineering setup is embedded into the framework of functional analysis of modern mathematical physics. After an overview, the –Hilbert space approach to free Euler–Bernoulli bending vibrations of a beam in one spatial dimension is investigated. We analyze in detail the corresponding positive, selfadjoint differential operators of 4-th order associated to the boundary conditions in statics. A comparison with free string wave swinging is outlined.
Acting like a startup - using corporate startup structures to manage the digital transformation
(2023)
Digital transformation is proving to be a significant challenge for firms and companies when it comes to maintaining their market position. It is evident that many companies are struggling to find their particular way through this transformation. A corporate startup structure is one way to find a suitable solution quickly. Therefore, we are presenting a model for corporate startup activities, which we will instantiate in an appropriate tool to support the management of corporate startups by their parent firms. We have derived the first requirements and design principles from a comprehensive problem analysis and literature study. In addition to this,we are presenting a first artifact, which should realize the design principles by implementing a practical tool. Forming a cooperation with an automotive firm has enabled us to gain access to real-world data for the design and evaluation of the artifact.
This paper explores the application of People Analytics in
recruiting professors for universities of applied sciences. Using data-driven personas, the research project aims to identify and communicate the different paths and connections leading candidates to a professorship. The authors introduce the concept of personas, describe the underlying data source and derive an example for the current project.
Framework for integrating intelligent product structures into a flexible manufacturing system
(2023)
Increasing individualisation of products with a high variety and shorter product lifecycles result in smaller lot sizes, increasing order numbers, and rising data and information processing for manufacturing companies. To cope with these trends, integrated management of the products and manufacturing information is necessary through a “product-driven” manufacturing system. Intelligent products that are integrated as an active element within the controlling and planning of the manufacturing process can represent flexibility advantages for the system. However, there are still challenges regarding system integration and evaluation of product intel-ligence structures. In light of these trends, this paper proposes a conceptual frame-work for defining, analysing, and evaluating intelligent products using the example of an assembly system. This paper begins with a classification of the existing problems in the assembly and a definition of the intelligence level. In contrast to previous approaches, the analysis of products is expanded to five dimensions. Based on this, a structured evaluation method for a use case is presented. The structure of solving the assembly problem is provided by the use case-specific ontology model. Results are presented in terms of an assignment of different application areas, linking the problem with the target intelligence class and, depending on the intelligence class of the product, suggesting requirements for implementation. The conceptual frame-work is evaluated by utilising a case study in a learning factory. Here, the model-mix assembly is controlled actively by the workpiece carrier in terms of transferring the variant-specific work instructions to the operator and the collaborative robot (cobot) at the workstations. The resulting system thus enables better exploitation of the poten-tials through less frequent errors and shorter search times. Such an implementation has demonstrated that the intelligent workpiece carrier represents an additional part for realising a cyber-physical production system (CPPS).
Automatic content creation system for augmented reality maintenance applications for legacy machines
(2024)
Augmented reality (AR) applications have great potential to assist maintenance workers in their operations. However, creating AR solutions is time-consuming and laborious, which limits its widespread adoption in the industry. It therefore often happens that even with the latest generation machines, instead of an AR solution, the user only receives an electronic manual for the equipment operation and maintenance. This is commonplace with legacy machines. For this reason, solutions are required that simplify the creation of such AR solutions. This paper presents an approach using an electronic manual as a basis to create fast and cost-effective AR solutions for maintenance. As part of the approach, an application was developed to automatically identify and subdivide the chapters of electronic manuals via the bookmarks in the table of contents. The contents are then automatically uploaded to a central server and indexed with a suitable marker to make the data retrievable. The prepared content can then be accessed for creating context-related AR instructions via the marker. The application is characterized by the fact that no developers or experts are required to prepare the information. In addition to complying with common design criteria, the clear presentation of the contents and the intuitive use of the system offer added value for the performance of maintenance tasks. Together, these two elements form a novel way to retrofit legacy machines with AR maintenance instructions. The practical validation of the system took place in a factory environment. For this purpose, the content was created for a filter change on a CNC milling machine. The results show that inexperienced users can extract appropriate content with the software application. Furthermore, it is shown that maintenance workers, can access the content with an AR application developed for the Microsoft HoloLens 2 and complete simple tasks provided in the manufacturer's electronic manual.
Das Thema des Direktvertriebs (Direct-to-Customer oder kurz D-to-C) in der Automobilindustrie ist en vogue, denn nach Valtech (2023, S. 2) ist die Umstellung der Vertriebsmodelle in dieser Branche unumgänglich. Die Covid-19-Pandemie hat zudem noch als Katalysator für den D-to-C fungiert und die digitale Transformation sowie die Akzeptanz virtueller Verkaufsprozesse beschleunigt.
Despite the unstoppable global drive towards electric mobility, the electrification of sub-Saharan Africa’s ubiquitous informal multi-passenger minibus taxis raises substantial concerns. This is due to a constrained electricity system, both in terms of generation capacity and distribution networks. Without careful planning and mitigation, the additional load of charging hundreds of thousands of electric minibus taxis during peak demand times could prove catastrophic. This paper assesses the impact of charging 202 of these taxis in Johannesburg, South Africa. The potential of using external stationary battery storage and solar PV generation is assessed to reduce both peak grid demand and total energy drawn from the grid. With the addition of stationary battery storage of an equivalent of 60 kWh/taxi and a solar plant of an equivalent of 9.45 kWpk/taxi, the grid load impact is reduced by 66%, from 12 kW/taxi to 4 kW/taxi, and the daily grid energy by 58% from 87 kWh/taxi to 47 kWh/taxi. The country’s dependence on coal to generate electricity, including the solar PV supply, also reduces greenhouse gas emissions by 58%.
The massive use of patient data for the training of artificial intelligence algorithms is common nowadays in medicine. In this scientific work, a statistical analysis of one of the most used datasets for the training of artificial intelligence models for the detection of sleep disorders is performed: sleep health heart study 2. This study focuses on determining whether the gender and age of the patients have a relevant influence to consider working with differentiated datasets based on these variables for the training of artificial intelligence models.
Accurate monitoring of a patient's heart rate is a key element in the medical observation and health monitoring. In particular, its importance extends to the identification of sleep-related disorders. Various methods have been established that involve sensor-based recording of physiological signals followed by automated examination and analysis. This study attempts to evaluate the efficacy of a non-invasive HR monitoring framework based on an accelerometer sensor specifically during sleep. To achieve this goal, the motion induced by thoracic movements during cardiac contractions is captured by a device installed under the mattress. Signal filtering techniques and heart rate estimation using the symlets6 wavelet are part of the implemented computational framework described in this article. Subsequent analysis indicates the potential applicability of this system in the prognostic domain, with an average error margin of approximately 3 beats per minute. The results obtained represent a promising advancement in non-invasive heart rate monitoring during sleep, with potential implications for improved diagnosis and management of cardiovascular and sleep-related disorders.
Software scripts for sensor data extraction in Rasberry Pi: user-space and kernel-space comparison
(2024)
This paper compares two popular scripting implementations for hardware prototyping: Python scripts execut from User-Space and C-based Linux-Driver processes executed from Kernel-Space, which can provide information to researchers when considering one or another in their implementations. Conclusions exhibit that deploying software scripts in the kernel space makes it possible to grant a certain quality of sensor information using a Raspberry Pi without the need for advanced real-time operational systems.
The strong demand to transform the textile and fashion industry towards sustainability requires continuous implementation of the Education for Sustainable Development (ESD) mission statement in education and industry. To achieve this goal, the European research project "Fashion DIET - Sustainable Fashion Curriculum at Textile Universities in Europe. Development, Implementation and Evaluation of a Teaching Module for Educators", co-funded by the Erasmus+ programme of the European Union (2020-1-DE01-KA203-005657), aims to create an ESD module for university lecturers and research-based teaching and learning materials delivered through an e-learning portal. First, an online questionnaire was rolled out to assess university faculty attitudes toward and needs for ESD content and methods. The feedback questionnaire enabled the selection of the most relevant data for the elaboration of an action and research-oriented professional development module for ESD in textile education, which will be accessible through an information & e-learning portal. The e-learning portal can be used as a web-based tool to apply and evaluate the project outcomes, e.g. the further education module and the teaching and learning materials for educators, such as manuals, broadcasts and the provision of interactive and physical materials. It thus ensures that the teaching materials can be used sustainably in the classroom. It also provides country-specific data for the fashion and textile industry and its market, taking into account the different perspectives of universities and schools. In any case, the portal represents (1) the web-based platform to support the dissemination of ESD as a guiding principle and (2) a central contact point for the target group to obtain relevant information on ESD. Fashion DIET explores the use of e-learning to improve teaching and learning on ESD, by training educators and empowering them as multipliers for a sustainable textile and fashion industry. At a higher level, the European project strengthens the quality and relevance of learning provision in education towards the latest developments in textile research and innovation in terms of a more sustainable fashion.
Purpose
As a response to the increased frequency of disruptive events and intense competition, organizational agility has become a key concept in organizational research. Fostering organizational agility requires leveraging knowledge that exists both outside (exploration) and inside (exploitation) the organization. This research tests the so-called ambidexterity hypothesis, which claims that a balance between exploration and exploitation leads to increased organizational outcomes, including the development of organizational agility. Complementing previously established measurement models on ambidexterity, this research proposes an alternative measurement model to analyze how ambidexterity can enhance organizational agility and, indirectly, performance, taking into consideration the moderating effect of environmental competitiveness.
Design/methodology/approach
A review of existing measurement models for ambidexterity shows that tension, a crucial aspect of ambidexterity, is often neglected. The authors, therefore, develop a new measurement model of ambidexterity to incorporate ambidexterity-induced tension. Using this measurement model, they examine the effect of ambidexterity on the development of entrepreneurial and adaptive agility as well as performance.
Findings
Ambidexterity positively influences both entrepreneurial and adaptive agility, indicating that a balance between exploration and exploitation has superior organizational effects. This finding confirms the ambidexterity hypothesis with respect to organizational agility. Furthermore, both entrepreneurial and adaptive agility drive organizational performance. These two indirect effects via agility fully mediate the impact of ambidexterity on organizational performance. Finally, environmental competitiveness positively moderates the relationship between ambidexterity and adaptive agility.
Originality/value
The findings extend research on ambidexterity by showing its positive effects on organizational agility. Furthermore, the study proposes an alternative operationalization to capture the ambidexterity construct that may lay the groundwork for further applications of the ambidexterity concept.
Tech hubs (THs) and cognate structures are nowadays ubiquitous in the innovation ecosystem of Sub-Saharan African (SSA) countries. However, the concept of THs is fuzzy due to the lack of a clear and universally accepted definition. This ambiguity is further compounded by the diverse range of organizations that self-identify as hubs, or are categorized as such by others. As a result, research on THs in SSA remained limited. Against the backdrop of established research on the interconnectedness of technology, innovation and entrepreneurship in different organizational forms, this paper is meant to provide fresh insights into the study of THs in SSA. To advance future research, first, it reveals what is special about THs in SSA and how they are related to existing concepts. I particularly argue that they contour a fourth-wave model of incubation. Second, four main categories are unfolded to delineate THs in SSA which is the cornerstone for future research.
Comparative analysis of the chemical and rheological curing kinetics of formaldehyde-based wood adhesives is crucial for assessing their respective performance. Differential scanning calorimetry (DSC) and rheometry are the conventional techniques used for monitoring the curing processes leading to crosslinking polymerization of the adhesives. However, the direct comparison of these techniques is inappropriate due to the intrinsic differences in their underlying procedures. To address this challenge, the two adhesive samples were sequentially cured, firstly with rheometry and followed by DSC. The observed higher curing degree in the subsequent DSC procedure underpins the incomplete curing of the samples during initial rheometry. Furthermore, the comparative assessment of the activation energies, molar ratios, and active groups of the two adhesives highlights the importance of the pre-exponential factor in addition to the activation energies, as it attributes to the probability of active groups coinciding at the appropriate spatial arrangement.
Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential of Raman imaging in SGT determination, a multi-stage evaluation process is necessary. By measuring a sample set of Warthin tumor, pleomorphic adenoma and non-tumor salivary gland tissue, Raman data were obtained and a thorough Raman band analysis was performed. This evaluation revealed highly overlapping Raman patterns with only minor spectral differences. Consequently, a principal component analysis (PCA) was calculated and further combined with a discriminant analysis (DA) to enable the best possible distinction. The PCA-DA model was characterized by accuracy, sensitivity, selectivity and precision values above 90% and validated by predicting model-unknown Raman spectra, of which 93% were classified correctly. Thus, we state our PCA-DA to be suitable for parotid tumor and non-salivary salivary gland tissue discrimination and prediction. For evaluation of the translational potential, further validation steps are necessary.
Im Team zum fliegenden Traum
(2024)
Purpose – This paper aims to determine the affecting factors of the brand authenticity of startups in social media.
Design/methodology/approach – Using a qualitative method based on a grounded theory approach, this research specifies and classifies the affecting factors of brand authenticity of startups in social media through in-depth semi-structured interviews.
Findings – Multiple factors affecting the brand authenticity of startups in social media are determined and categorized as indexical, iconic and existential cues through this research. Connection to heritage and having credible support are determined as indexical cues. Founder intellectuality, brand intellectuality, commitment toward customers and proactive clear and interesting communications are identified as iconic cues. Having self-confidence and self-satisfaction, having intimacy with the brand and a joyful feeling for interactions with the community around the brand are determined as existential cues in this research. This research furthers previous arguments on a multiplicity of brand authenticity by shedding light on the relationship between the different aspects of authenticity and the form that different affecting factors can be organized together. Consumers eventually evaluate a strengthened perception of brand authenticity through existential cues that reflect the cues of other aspects (iconic and indexical) which passed through the goal-based assessment and self-authentication filter.
Research limitations/implications – The research sampling population can be more diversified in terms of sociodemographic attributes. Due to the qualitative methodology of this research, assessment of the findings through quantitative methods can be considered in future research. Practical implications – Using the findings of this research, startup managers can properly build a perception of authenticity in their consumers’ minds by using alternate factors while lacking major indexical cues such as heritage. This research helps startup businesses to design their brand communications better to convey their authenticity to their audiences.
Originality/value – This research determines the factors affecting the authenticity of startup brands in social media. It also defines the process of authenticity perception through different aspects of brand authenticity.
Das Ziel dieses Papiers ist es zu verstehen, inwieweit Musik und Mode voneinander abhängig und miteinander interagieren, wobei der Schwerpunkt auf der Entwicklung von Musik- und Modetrends im Zeitraum von 1950 bis heute liegt. Darüber hinaus soll dem Leser ein Einblick darin ermöglicht werden, ob die zur Verfügung stehende Technologie die Entwicklung und den Zugang zu Musik und Mode in Zukunft beeinflusst. Die Recherche für dieses Papier erforderte die Verwendung von Sekundärquellen, einschließlich Bibliotheks- und Online-Recherchen. Das Ziel war es, Informationen über die frühere und aktuelle Entwicklung von Musik und Mode zu sammeln. Diese Methoden waren die besten Alternativen zu Sekundärquellen, da sie zuverlässige Ergebnisse lieferten und so die Genauigkeit der gesammelten Daten erhöhten. Sie waren jedoch auch begrenzt, da vor allem Daten für die Mode- und Musikentwicklung der Nullerjahre begrenzt waren. Dies ist durch das Hauptergebnis erklärbar, dass die Entwicklung dieser Zeit nicht so deutlich ist wie die der früheren Zeiten, in denen ein Modetrend mit einem neuen Musikgenre oder Hit einherging, was bedeutet, dass Mode und Musik in gewissem Maße korrelieren, aber durch eine Reaktivierung der Musik- und Modetrends der Vorjahre ohne neue Erfindungen gekennzeichnet ist.
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.
Plasmonics and nanophotonics both deal with the interaction of light with structures of typically sub-wavelength size in one of more dimensions. Over the past decade or two, interest in these topics has grown significantly. This includes basic research towards detailed understanding of light-matter interaction and the manipulation of light on the nanometer scale as well as the search for applications ranging from quantum information processing, data storage, solar cells, spectroscopy and microscopy to (bio-)sensors and biomedical devices. Key enablers for this development are advanced materials and the variety of techniques to structure them with nanometer precision on the one hand, and progress in the theoretical description and numerical implementations, on the other. Besides the traditional metals Au, Ag, Al, and Cu also compounds such as refractory metal nitrides with much higher durability as well as semiconductors, dielectrics and hybrid structures have become of interest. Structuring techniques are not only aiming at the fabrication of individual elements with highest precision for detailed interaction analysis, but also at methods for large scale, low-cost nanofabrication mostly for sensor applications. In the former case, mostly electron beam lithography and focused ion beam milling are employed, while for high throughput various forms of nanoimprint and self-assembly based techniques are favored. Thin film deposition and pattern transfer techniques are mostly derived from those developed for nano-electronics, however more recently methods such as electroless plating, atomic layer deposition or etching and 3-D additive techniques are appearing. Thus, highly specialized expertise has been acquired in the different disciplines, and successful research and technology transfer will draw from this pool of knowledge.
Climate change is one of the key challenges of this century due to its impact on society and the economy. Students are asking their business schools to scale up climate change education (CCE) across all disciplines, and employers are looking for graduates ready to work on solutions. This desire for solutions is shared by faculty; however, in a recent survey, many highlighted that they lack knowledge about climate change mitigation and how to integrate CCE into their disciplines.
This chapter supports lecturers, professors and senior management in their journey to get an overview of CCE and, more importantly, to find high-impact climate solutions to be integrated and assessed in their teaching units.
Introduction to the special issue on self‑managing and hardware‑optimized database systems 2022
(2023)
Data management systems have evolved in terms of functionality, performance characteristics, complexity, and variety during the last 40 years. Particularly, the relational database management systems and the big data systems (e.g., Key-Value stores, Document stores, Graph stores and Graph Computation Systems, Spark, MapReduce/Hadoop, or Data Stream Processing Systems) have evolved with novel additions and extensions. However, the systems administration and tasks have become highly complex and expensive, especially given the simultaneous and rapid hardware evolution in processors, memory, storage, or networking. These developments present new open problems and challenges to data management systems as well as new opportunities.
The SMDB (International Workshop on Self-Managing Database Systems) and HardBD&Active (Joint International Workshop on Big Data Management on Emerging Hardware and Data Management on Virtualized Active Systems) workshops organized in conjunction with the IEEE ICDE (International Conference on Data Engineering) offered two distinct platforms for examining the above system-related challenges from different perspectives. The SMDB workshop looks into developing autonomic or self-* features in database and data management systems to tackle complex administrative tasks, while the HardBD&Active workshop focuses on harnessing hardware technologies to enhance efficiency and performance of data processing and management tasks. As a result of these workshops, we are delighted to present the third special issue of DAPD titled “Self-Managing and Hardware-Optimized Database Systems 2022,” which showcases the best contributions from the SMDB 2021/2022 and HardBD&Active 2021/2022 workshops.
Digitalization and enterprise architecture management: a perspective on benefits and challenges
(2023)
Many companies digitally transform their business models, processes, and services. They have also been using Enterprise Architecture Management approaches for a long time to synchronize corporate strategy and information technology. Such digitalization projects bring different challenges for Enterprise Architecture Management. Without understanding and addressing them, Enterprise Architecture Management projects will fail or not deliver the expected value. Since existing research has not yet addressed these challenges, they were investigated based on a qualitative expert study with leading industry experts from Europe. Furthermore, potential benefits of digitalization projects for Enterprise Architecture Management were researched. Our results provide a theoretical framework consisting of five identified challenges, triggers and a number of benefits. Furthermore, we discuss in what ways digitalization and EAM is a promising topic for future research.
§ 251 Haftungsverhältnisse
(2023)
Unter der Bilanz sind, sofern sie nicht auf der Passivseite auszuweisen sind, Verbindlichkeiten aus der Begebung und Übertragung von Wechseln, aus Bürgschaften, Wechsel- und Scheckbürgschaften und aus Gewährleistungsverträgen aus der Bestellung von Sicherheiten für fremde Verbindlichkeiten zu vermerken; sie dürfen in einem Betrag angegeben werden. Haftungsverhältnisse sind auch anzugeben, wenn ihnen gleichwertige Rückgriffsforderungen gegenüberstehen.
In recent years, both fields, AI and VRE, have received increasing attention in scientific research. Thus, this article’s purpose is to investigate the potential of DL-based applications on VRE and as such provide an introduction to and structured overview of the field. First, we conduct a systematic literature review of the application of Artificial Intelligence (AI), especially Deep Learning (DL), on the integration of Variable Renewable Energy (VRE). Subsequently, we provide a comprehensive overview of specific DL-based solution approaches and evaluate their applicability, including a survey of the most applied and best suited DL architectures. We identify ten DL-based approaches to support the integration of VRE in modern power systems. We find (I) solar PV and wind power generation forecasting, (II) system scheduling and grid management, and (III) intelligent condition monitoring as three high potential application areas.
Because of a high product and technology complexity, companies involve external partners in their research and development (R&D) processes. Interorganizational projects result, which represent temporary organizations. In these projects heterogenous organizations work closely together. Since project work is always teamwork, these projects face due to their characteristic’s major challenges on an organizational, relational, and content-related collaboration level. Thus, this paper raises the following research question: “How can a project team be supported on an organizational, relational, and content-related level in an interorganizational new product development setting?” To answer this research question, an explorative expert study was set up with two digital workshops using the interactive presentation tool Mentimeter. The results show that a cooperative innovation culture could support project teams on an organizational and relational level in the future in minimizing predominant problems. Moreover, it supports project teams for example in a functional communication. Furthermore, 18 values of a cooperative innovation culture result which are for example openness and transparency, risk and failure tolerance or respect. On a content-related level the results show that an adaptable tool which promotes creativity and collaboration method as well as content-related input support could be beneficial for problem-solving in an interorganizational new product development setting in the future. Because the tool can guide product developers through the process with suitable creativity and collaboration methods, can give content-related input and can enable interactive interchange on a table-top. Future research could mainly focus on the connection of the cooperative innovation culture and the tool since these potentially influence each other.
In a recently developed study programme at Reutlingen University, which focuses on practical orientations, an innovative product with solid company references is to be defined and realised by student teams. On the basis of this product, all subjects of the business engineering study programme “Sustainable Production and Business” are taught. By focusing on three main paths of future skills that have been developed by NextSkills to analyse upcoming social changes, global challenges and fields of work that are innovation-driven and agile, the new study programme aims to create responsible leaders who will shape global businesses respectfully. Thereby, different TRIZ tools help to support students in developing their own products with a focus on sustainability and pay off on the future skills enhancement. Further, students get to know TRIZ tools in an unbiased way, unburdened by too much theory, and are thus continuously supported in the progressing product development process that accompanies their studies. Hence, students perceive TRIZ on the one hand as a method to develop sustainable products and, on the other hand, to find sustainable solutions for everyday problems. The knowledge and positive experiences gained in this way should then arouse curiosity for the TRIZ class at the end of the study programme. The students can graduate with a TRIZ Level 1 certificate. Thereby, as many students as possible are introduced to the TRIZ methods, and the TRIZ tool is spread widely.
Vor mehr als einem Jahrzehnt stellten die Autoren dieses Beitrags die folgende Denkaufgabe:
“Imagine the business of sports without fans. No spectators at sports matches, no buyers of merchandising, no potential customers for sponsoring companies, no recipients for the sports media. Such a scenario would be unthinkable.“ (Bühler & Nufer, 2010, S. 63)
Während der Corona-Pandemie 2020/21 wurde das Undenkbare dann aber doch Realität, als Zuschauer auf der ganzen Welt keine Sportveranstaltungen mehr besuchen durften. Das größte Sportevent der Welt, die Olympischen Spiele in Tokio 2020, mussten verschoben werden und fanden ein Jahr später unter nicht wirklich besseren Bedingungen vor so gut wie leeren Rängen statt. Das Gleiche galt für die UEFA EURO 2020, die ebenfalls um ein Jahr verschoben werden musste, dann aber zumindest (bis auf wenige Ausnahmen wie beispielsweise das Finale in Wembley) mit reduzierter Zuschauerzulassung stattfinden konnte. Hintergrund der Überlegungen sowohl des Internationalen Olympischen Komitees wie auch der Europäischen Fußballunion war damals die Befürchtung, dass ihre jeweiligen Premiumprodukte ohne Fans in den Stadien leiden würden. Natürlich gab es immer noch Millionen von Menschen, die Live-Streams von Sportveranstaltungen verfolgten oder in diesen schwierigen Corona-Zeiten allerhand Merchandise ihrer Lieblingsmannschaften kauften. Doch die Pandemie bestätigte einmal mehr die Grundregel im Sportbusiness: Der Wirtschaftsmarkt Sport im Allgemeinen und professionelle Sportorganisationen im Besonderen brauchen Fans, die bereit sind, ihre Zeit, ihre Emotionen und ihr Geld für ihren Lieblingssport und ihre Lieblingsmannschaften zu investieren. Zuschauer sind die primären – und wohl wichtigsten – Kunden eines Sportunternehmens. Daher ist es für jede professionelle Sportorganisation unerlässlich, eine nachhaltige Beziehung zu ihren Fans aufzubauen und aufrechtzuerhalten und sie auf jede mögliche Weise einzubeziehen. Vor diesem Hintergrund wird die Bedeutung des Fan-Engagements deutlich.
Sponsoring zählt zu den nicht-klassischen Formen der Marketing-Kommunikationspolitik und spricht Menschen in nicht-kommerziellen Situationen an. Gerade durch Sponsoring können Zielgruppen erreicht werden, die z.B. Werbung gegenüber negativ eingestellt oder durch klassische Kommunikationsinstrumente nicht erreichbar sind. Auch wird ein Sponsoringengagement i.d.R. eher akzeptiert als klassische Werbung, da dem Sponsoring per se eine gewisse Förderabsicht zugrunde liegt. In diesem Kapitel werden die wesentlichen Sponsoring-Grundlagen vorgestellt und das Kommunikationsinstrument Sportsponsoring sowohl aus der Perspektive von Sponsoren als auch aus der Sicht von Gesponserten genau beleuchtet. Zusätzlich werden die Besonderheiten des Sportevent-Sponsorings aufgezeigt und Ambush Marketing als Alternative zum Sportsponsoring präsentiert. Abschließend wird auf aktuelle Entwicklungen im Sportsponsoring im Rahmen der FIFA Fußball-Weltmeisterschaft 2022 und der bevorstehenden EURO 2024 eingegangen.
Modern component-based architectural styles, e.g., microservices, enable developing the components independently from each other. However, this independence can result in problems when it comes to managing issues, such as bugs, as developer teams can freely choose their technology stacks, such as issue management systems (IMSs), e.g., Jira, GitHub, or Redmine. In the case of a microservice architecture, if an issue of a downstream microservice depends on an issue of an upstream microservice, this must be both identified and communicated, and the downstream service’s issues should link to its causing issue. However, agile project management today requires efficient communication, which is why more and more teams are communicating through comments in the issues themselves. Unfortunately, IMSs are not integrated with each other, thus, semantically linking these issues is not supported, and identifying such issue dependencies from different IMSs is time-consuming and requires manual searching in multiple IMS technologies. This results in many context switches and prevents developers from being focused and getting things done. Therefore, in this paper, we present a concept for seamlessly integrating different IMS technologies into each other and providing a better architectural context. The concept is based on augmenting the websites of issue management systems through a browser extension. We validate the approach with a prototypical implementation for the Chrome browser. For evaluation, we conducted expert interviews, which approved that the presented approach provides significant advantages for managing issues of agile microservice architectures.
There are indicators we are entering a new era for MTM research, by moving beyond the structural approach that has characterized MTM research to date, to focus on important and under-researched issues, such as the nature of employees’ experiences in an MTM context. Although team research suggests that the experiences of members impact team functioning, these lines of reasoning have not, until recently, made their way to MTM research. To overcome this limitation, this symposium showcases five papers that use a variety of theoretical perspectives, research designs (i.e., qualitative, quantitative), contexts (e.g., healthcare, automotive manufacturer, online panels), methodologies, and analytical methods (i.e., meta-analysis, content/thematic analysis). The symposium focuses on surfacing and advancing unanswered questions that extend theory and can offer fruitful directions for MTM research by examining critical individual and team level outcomes (e.g., individual/team performance, individual counterproductive and organizational citizenship behavior, individual learning, individual turnover intentions, organizational commitment) in the experiences of MTM employees across their teams (e.g., goals, functions, roles). We hope to provide a forum to advance unanswered questions that offer fruitful directions for MTM research.
Application systems often need to be deployed in different variants if requirements that influence their implementation, hosting, and configuration differ between customers. Therefore, deployment technologies, such as Ansible or Terraform, support a certain degree of variability modeling. Besides, modern application systems typically consist of various software components deployed using multiple deployment technologies that only support their proprietary, non-interoperable variability modeling concepts. The Variable Deployment Metamodel (VDMM) manages the deployment variability across heterogeneous deployment technologies based on a single variable deployment model. However, VDMM currently only supports modeling conditional components and their relations which is sometimes too coarse-grained since it requires modeling entire components, including their implementation and deployment configuration for each different component variant. Therefore, we extend VDMM by a more fine-grained approach for managing the variability of component implementations and their deployment configurations, e.g., if a cheap version of a SaaS deployment provides only a community edition of the software and not the enterprise edition, which has additional analytical reporting functionalities built-in. We show that our extended VDMM can be used to realize variable deployments across different individual deployment technologies using a case study and our prototype OpenTOSCA Vintner.
Different network architectures are being used to build remote laboratories. Historically, it has been difficult to integrate industrial control systems with higher level IT systems like enterprise resource planning (ERP), manufacturing execution systems (MES), and manufacturing operations management (MOM). Getting these systems to communicate with one another has proven to be relatively difficult due to the absence of shared protocols between them. The Open Platform Communications United Architecture (OPC-UA) protocol was introduced as a remedy for this issue and is gaining popularity, but what if open-source protocols that are widely used in the IT industry could be used instead? This paper presents the development of an IT-Architecture for a cyber-physical industrial control systems laboratory that enables a seamless interconnection and integration of its elements. The architecture utilises Node-Red technology. Node-RED is an open-source programming platform developed by IBM that is focused on making it simple to link physical components, APIs, and web services. This cyber-physical laboratory is for learning principles of an industrial cascaded process control factory. Finally, this text will also discuss future work relating to digital twin (DT). A coupled tank system is selected as a teaching factory to illustrate a range of fluid control application in a typical chemical process factory.
Mit zunehmender Dynamik im Forschungsumfeld – Digitalisierung der Produktentwicklung – steigen neben der Komplexität auch die technischen Anforderungen an die künftigen Entscheidungsprozesse. Die Einführung von neuen IT-Systemen zur Automation von Entscheidungen haben Anpassungen in den derzeitigen Geschäftsprozessen der Unternehmen zur Folge. Für eine erfolgreiche Implementierung neuer IT-Informationstools gilt es im Voraus mögliche Auswirkungen auf die bisherigen Anwendersysteme genauer zu untersuchen. Neue Technologien, KI-Informationssysteme oder auch neues Wissen entstehen in der Wissenschaft oft durch Interpretation und Synthese von bestehendem Wissen. Aus diesem Grund nimmt die Qualität von Literaturanalysen eine immer größere Relevanz in der Ingenieur- und Informatikwissenschaft ein. Neben der Anzahl an Publikationen wächst auch der Aufwand für die strukturierte Literaturrecherche (SLA). Die Autoren stellen in diesem Paper den Rechercheprozess und die Ergebnisse einer SLA vor. Mit dieser Arbeit soll der derzeitige Forschungsstand zur Entscheidungsunterstützung in der Produktentwicklung von Klein- und mittelständischen Unternehmen sowie Großunternehmen in der
Automobilbranche ermittelt und nach Analyse sowie Bewertung mögliche Forschungslücken zu automatisierten Entscheidungsunterstützungssystemen (aEUS) aufgezeigt werden.
Do Chinese subordinates trust their German supervisors? A model of inter-cultural trust development
(2023)
In this qualitative study based on 95 interviews with Chinese subordinates and their German supervisors, we inductively develop a model which advances theoretical understanding by showing how inter-cultural trust development in hierarchical relationships is the result of six distinct elements: the subordinate trustor’s cultural profile (cosmopolitans, hybrids, culturally bounds), the psychological mechanisms operating within the trustor (role expectations and cultural accommodation), and contextual moderators (e.g., country context, time spent in foreign culture, and third-party influencers), which together influence the trust forms (e.g., presumptive trust, relational trust) and trust dynamics (e.g., trust breakdown and repair) within relationship phases over time (initial contact, trust continuation, trust disillusionment, separation, and acculturation). Our findings challenge the assumption that cultural differences result in low levels of initial trust and highlight the strong role the subordinate’s cultural profile can have on the dynamics and trajectory of trust in hierarchical relationships. Our model highlights that inter-cultural trust development operates as a variform universal, following the combined universalistic-particularistic paradigm in cross-cultural management, with both culturally generalizable etic dynamics, as well as culturally specific etic manifestations.
Development of an indoor positioning system to create a digital shadow of production plant layouts
(2023)
The objective of this dissertation is to develop an indoor positioning system that allows the creation of a digital shadow of the plant layout in order to continuously represent the actual state of the physical layout in the virtual space. In order to define the requirements for such a system, potential stakeholders who could benefit from a digital shadow in the context of the plant layout were analysed. In order to generate added value for their work, the requirements were derived from their perspective. As the core of an indoor positioning system is the sensory aspect to capture the physical layout parameters, different potential technologies were compared and evaluated in terms of their suitability for this particular application. Derived from this analysis, the selected concept is based on the use of a pan-tilt-zoom (PTZ) camera in combination with fiducial markers. In order to determine specific camera parameters, a series of experiments were conducted which were necessary to develop the measurement method as well as the mathematical calculation method and coordinate transformation for the determination of poses (positions and angular orientations) of the respective facilities in the plant. In addition, an experimental validation was performed to ensure that the limit values for individual parameters determined in the requirements analysis can be met.
The basis for developing future products in the automotive industry is finding creative and innovative solutions. Ideas can be found by means of creativity methods that support product developers throughout the creative process. Product developers are provided with a variety of different and new methods. This leads to a “method jungle” in which it is difficult for product developers to find the most suitable path. The successful use of methods in product development goes hand in hand with the acceptance and implementation of the methods. Despite the added value, only a low use is observed in the development process. The field of Creativity Support Tools also offers a wide variety of different tools that support the creativity process. Although a chasm exists between the many CSTs that are developed and what creative practitioners actually use. Therefore, previous studies iteratively developed a user-centered tool called “IDEA” that tries to provide a tool that responds to users' needs. The question arises how the developed tool IDEA performs in “real life setting” regarding its UX and usability as well as the creativity method acceptance and level of mental workload.
Gegenstand dieser Arbeit ist die Darstellung und Charakterisierung einheitlicher, mesoporöser Silica-Partikel (MPSM) im Mikrometerbereich mit maßgeschneiderten Partikel- und Porendesign für die Hochleistungsflüssigkeitschromatographie. Die Synthese umfasst die Einlagerung von Silica-Nanopartikeln (SNP) in poröse organische Template, welche anschließend bei 600°C zersetzt werden. Die Impfsuspensionspolymerisation von Polystyrol-Partikeln, unter Verwendung von Glycidylmethacrylat, Ethylenglycoldimethacrylat und Porogenen, ermöglicht die Herstellung hochgradig einheitlicher, poröser p(GMA-co-EDMA)-Template. Der Einfluss wesentlicher Faktoren, einschließlich des Monomer-Porogen-Verhältnisses, des Monomerverhältnisses und der Porogenzusammensetzung, werden systematisch untersucht sowie ihre Auswirkungen auf die Porengröße, das Porenvolumen und die spezifische Oberfläche erläutert. Die Anbindung aminofunktionalisierter Substanzen erfolgt durch die Ringöffnung der Epoxidgruppe. Im anschließenden basischen Sol-Gel-Prozess werden die Silica-Nanopartikel aufgrund der Ladungsunterschiede in die funktionalisierten p(GMA-co-EDMA)-Template eingebaut. Die Partikelgröße der SNP beeinflusst wesentlich die Poreneigenschaften der MPSM und hängt von drei Faktoren ab: (i) der Wachstumsgeschwindigkeit in der kontinuierlichen Phase, die durch die Einstellungen des Sol-Gel-Prozesses gesteuert wird, (ii) der Diffusionsrate, die durch elektrostatische Anziehung reguliert wird und vom Grad der Funktionalisierung abhängt und (iii) der Porosität des Polymer-Templats. Die gezielte Anpassung der Poreneigenschaften durch die Prozesseinstellungen erlaubt die präzise Herstellung von MPSM, die auf spezifische Trennherausforderungen zugeschnitten werden und somit die Qualität der HPLC verbessern. Die vorgestellte Synthesestrategie ermöglicht, aufgrund des stufenweisen molekularen Aufbaus, eine bessere Adaption der stationären Phase an spezifische Trennherausforderungen.
The targeted design of monodisperse, mesoporous silica microspheres (MPSMs) as HPLC separation phases is still a challenge. The MPSMs can be generated via a multi-step template-assisted method. However, this method and the factors affecting the individual process steps and resulting material properties are scarcely understood, and specific control of the complex multi-step process has been hardly discussed. In this work, the key synthesis steps were systematically investigated by means of statistical Design of Experiment (DoE). In particular, three steps were considered in detail: 1) the synthesis of porous poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate) (p(GMA-co-EDMA)) particles, which as template particles, determine the structure for the final MPSMs. In this context, functional models were generated, which allow the control of the template properties pore volume, pore size and specific surface area. 2) In the presence of amino-functionalized template particles, the sol-gel process was carried out under Stöber process conditions. The water to tetraethyl orthosilicate (TEOS) ratio, as well as the concentration of ammonia as basic catalyst were varied according to a face-centered central composite design (FCD). The incorporation of silica nanoparticles (SNPs) into the pore network of the porous polymers was investigated by scanning electron microscopy (SEM), evaluation of the pore properties assessed by nitrogen sorption measurements and determination of the inorganic content by thermogravimetric analysis (TGA). Here, the material properties, such as the amount of attached silica, can be specifically controlled in the resulting organic/silica hybrid material (hybrid beads, HBs). Furthermore, depending on the sol-gel conditions three, potentially four, reaction regimes were identified, leading to different HBs. These range from porous polymer particles coated with a thin protective silica layer, to interpenetrating networks of polymer and silica, to potential particles consisting of a porous polymer core coated with a silica shell. Also, the effects of the use of different precursors and solvents on silica incorporation were investigated. 3) To obtain MPSMs from the HBs, the organic polymer template was removed by calcination. The effects of sol-gel process conditions on the resulting MPSMs were evaluated and relationships between process conditions and material properties were shown in predictive models. Fully porous, spherical, monodisperse silica particles with sizes ranging from 0.5 µm to 7.8 µm and pore sizes from 3.5 nm to 72.4 nm can be prepared specifically. Subsequent to organo-functionalization, prepared MPSMs were applied as reversed-phase HPLC column materials. Here, the columns were successfully applied for the separation of proteins and amino acids. The separation performance of the materials depends largely on the property profile of the MPSMs, which is predetermined during the preparation of the HBs.
In the context of Industry 4.0, intralogistics faces an increasingly complex and dynamic environment driven by a high level of product customisation and complex manufacturing processes. One approach to deal with these changing conditions is the decentralised and intelligent connectivity of intralogistics systems. However, wireless connectivity presents a major challenge in the industry due to strict requirements such as safety and real-time data transmission. In this context, the fifth generation of mobile communications (5G) is a promising technology to meet the requirements of safety-critical applications. Particularly, since 5G offers the possibility of establishing private 5G networks, also referred to as standalone non-public networks. Through their isolation from public networks, private 5G networks provide exclusive coverage for private organisations offering them high intrinsic network control and data security. However, 5G is still under development and is being gradually introduced in a continuous release process. This process lacks transparency regarding the performance of 5G in individual releases, complicating the successful adoption of 5G as an industrial communication. Additionally, the evaluation of 5G against the specified target performance is insufficient due to the impact of the environment and external interfering factors on 5G in the industrial environment. Therefore, this paper aims to develop a technical decision-support framework that takes a holistic approach to evaluate the practicality of 5G for intralogistics use cases by considering two fundamental stages. The first of these analyses technical parameters and characteristics of the use case to evaluate the theoretical feasibility of 5G. The second stage investigates the application's environment, which substantially impacts the practicality of 5G, for instance, the influence of surrounding materials. Finally, a case study validates the proposed framework by means of an autonomous mobile robot. As a result, the validation proves the proposed framework's applicability and shows the practicality of the autonomous mobile robot, when integrating it into a private 5G network testbed.
In the era of digital transformation, the notion of software quality transcends its traditional boundaries, necessitating an expansion to encompass the realms of value creation for customers and the business. Merely optimizing technical aspects of software quality can result in diminishing returns. Product discovery techniques can be seen as a powerful mechanism for crafting products that align with an expanded concept of quality - one that incorporates value creation. Previous research has shown that companies struggle to determine appropriate product discovery techniques for generating, validating, and prioritizing ideas for new products or features to ensure they meet the needs and desires of the customers and the business. For this reason, we conducted a grey literature review to identify various techniques for product discovery. First, the article provides an overview of different techniques and assesses how frequently they are mentioned in the literature review. Second, we mapped these techniques to an existing product discovery process from previous research to provide concrete guidelines for establishing product discovery in their organizations. The analysis shows, among other things, the increasing importance of techniques to structure the problem exploration process and the product strategy process. The results are interpreted regarding the importance of the techniques to practical applications and recognizable trends.
Cyber-Physical Production Systems increasingly use semantic information to meet the grown flexibility requirements. Ontologies are often used to represent and use this semantic information. Existing systems focus on mapping knowledge and less on the exchange with other relevant IT systems (e.g., ERP systems) in which crucial semantic information, often implicit, is contained. This article presents an approach that enables the exchange of semantic information via adapters. The approach is demonstrated by a use case utilizing an MES system and an ERP system.
Transforming our food system is important to achieving global climate neutrality and food security. Germany has set a national target of reaching a 30% share in organic farming to support the goal. When looking at the transformation process from conventional to organic farming, it becomes apparent that measures need to be taken to reach this anticipated goal. A particular emphasis of this work is placed on finding a digital solution and process improvements to ensure longevity and efficiency. Interviews with actors along the farm-to-fork value chain were conducted to identify central barriers and drivers of organic transformation. The results of the interviews show firstly, that three subsystems need to be distinguished when talking about the farm-to-fork value chain: (1) farmers, (2) intermediaries, and (3) the canteen system. Although all three subsystems can be combined to form a coherent value chain, they rarely act and communicate beyond the boundaries of their subsystem. Secondly, we were able to allocate primary barriers and drivers to each of the subsystems, highlighting the need to include all three in the transformation process and aim for a comprehensive digital solution. This work explores the potential of a network-based platform to improve the current practice of rigid and strictly hierarchical value chains. We focus on deriving user requirements from the interviews to describe the necessary functionality of the platform to address the identified barriers and exploit existing drivers.
Applications often need to be deployed in different variants due to different customer requirements. However, since modern applications often need to be deployed using multiple deployment technologies in combination, such as Ansible and Terraform, the deployment variability must be considered in a holistic way. To tackle this, we previously developed Variability4TOSCA and the prototype OpenTOSCA Vintner, which is a TOSCA preprocessing and management layer that implements Variability4TOSCA. In this demonstration, we present a detailed case study that shows how to model a deployment using Variability4TOSCA, how to resolve the variability using Vintner, and how the result can be deployed.
Gamification has been increasingly applied to software engineering education in the past. The approaches vary from applying game elements on a conceptual phase in the course to using specific tools to engage the students more and support their learning goals. However, existing tools usually have game elements, such as quizzes or challenges, but do not provide a more computer game-like experience. Therefore, we try to raise the level of gamified learning experience to another level by proposing Gamify-IT. Gamify-IT is a Unity- and web-based game platform intended to help students learn software engineering. It follows an immersive role-play game characteristic where the students explore a world, find and solve minigames and clear dungeons with SE tasks. Lecturers can configure the worlds, e.g., to add content hints. Furthermore, they can add and configure minigames and dungeons to include exercises in a fully gamified way. Thereby, they customize their course in Gamify-IT to adapt the world very precisely to other materials such as lectures or exercises. Results of an evaluation of our initial prototype show that (i) students like to engage with the platform, (ii) students are motivated to learn when using Gamify-IT, and (iii) the minigames support students in understanding the learning objectives.
Intelligent Tutoring Systems (ITSs) are increasingly used in modern education to automatically give students individual feedback on their performance. The advantage for students is fast individual feedback on their answers to asked questions, while lecturers benefit from considerable time savings and easy delivery of educational material. Of course, it is important that the provided feedback is as effective as direct feedback from the lecturer. However, in digital teaching, lecturers cannot assess the student’s knowledge precisely but can only provide information on which questions were answered correctly and incorrectly. Therefore, this paper presents a concept for integrating ITS elements into the gamified e-learning platform IT-REX so that the feedback quality can be improved to support students in the best possible way.
The COVID-19 pandemic necessitated significant changes in foreign language education, forcing teachers to reconstruct their identities and redefine their roles as language educators. To better understand these adaptations and perspectives, it is crucial to study how the pandemic has influenced teaching practices. This mixed-methods study focused on the less-explored aspects of foreign language teaching during the pandemic, specifically examining how language teachers adapted and perceived their practices, including rapport building and learner autonomy, during emergency remote teaching (ERT) in higher education institutions. It also explored teachers’ intentions for their teaching in the post-pandemic era. An online survey was conducted, involving 118 language educators primarily from Germany, with a smaller representation from New Zealand, the United States, and the United Kingdom. The analysis of participants’ responses revealed issues and opportunities regarding lesson formats, tool usage, rapport, and learner autonomy. Our findings offer insights into the desired changes participants envisioned for the post-pandemic era. The results highlight the opportunities ERT had created in terms of teacher development, and we offer suggestions to enhance professional development programmes based on these findings.
The present study investigated the possibilities and limitations of using a low-cost NIR spectrometer for the verification of the presence of the declared active pharmaceutical ingredients (APIs) in tablet formulations, especially for medicine screening studies in low-resource settings. Spectra from 950 to 1650 nm were recorded for 170 pharmaceutical products representing 41 different APIs, API combinations or placebos. Most of the products, including 20 falsified medicines, had been collected in medicine quality studies in African countries. After exploratory principal component analysis, models were built using data-driven soft independent modelling of class analogy (DD-SIMCA), a one-class classifier algorithm, for tablet products of penicillin V, sulfamethoxazole/trimethoprim, ciprofloxacin, furosemide, metronidazole, metformin, hydrochlorothiazide, and doxycycline. Spectra of amoxicillin and amoxicillin/clavulanic acid tablets were combined into a single model. Models were tested using Procrustes cross-validation and by projection of spectra of tablets containing the same or different APIs. Tablets containing no or different APIs could be identified with 100 % specificity in all models. A separation of the spectra of amoxicillin and amoxicillin/clavulanic acid tablets was achieved by partial least squares discriminant analysis. 15 out of 19 external validation products (79 %) representing different brands of the same APIs were correctly identified as members of the target class; three of the four rejected samples showed an API mass percentage of the total tablet weight that was out of the range covered in the respective calibration set. Therefore, in future investigations larger and more representative spectral libraries are required for model building. Falsified medicines containing no API, incorrect APIs, or grossly incorrect amounts of the declared APIs could be readily identified. Variation between different NIR-S-G1 spectroscopic devices led to a loss of accuracy if spectra recorded with different devices were pooled. Therefore, piecewise direct standardization was applied for calibration transfer. The investigated method is a promising tool for medicine screening studies in low-resource settings.
Impact of a large distribution network on radiation characteristics of planar spiral antenna arrays
(2023)
Designing antenna arrays with a central feed point has gained ground in the antenna technique. This approach, which is usually applied because of manufacturing costs, is difficult to achieve and leads to a large feeding network. The impact of which is numerically investigated in the present work. Upon comparing three different antennas, it is shown that the enlargement of the feed strongly affects the antenna's overall dimensions and the antenna's radiation characteristics. The antenna with the plug-in solution is not only small in size but also performs better compared to antennas with a central feed point. Considering the high effort in designing the feed network with a central point and the influence of the resulting enlarged network on the dimensions and radiation characteristics of the antenna, the cost saving in production can be put into perspective.
The Belt and Road Initiative (BRI) has reinforced China’s business engagement in Sub-Saharan Africa (SSA). While previous international business research focused on the internationalization and investments of Chinese companies, this viewpoint uncovers how both local African and international non-Chinese Small and Medium Sized Enterprises (SMEs) may benefit from and participate in the BRI. A focus is laid on the infrastructure sector accounting for the highest investments since the inception of the BRI in 2013. In a conceptual way, the motives of SMEs to participate in infrastructure project business in the context of the BRI are explored. Investigating the challenges of two large transport infrastructure projects, the business potentials for SMEs become visible. It is argued that SMEs find business potentials particularly as investors, sub-contractors and project management experts in the BRI in Sub-Saharan Africa.
Im E-Sport-Ökosystem gibt es eine Vielzahl an Akteuren, die auf verschiedene Art und Weisen vom Erfolg des elektronischen Sports profitieren: Sponsoren präsentieren sich einer attraktiven Zielgruppe, Publisher fördern eine intensivere Nutzung ihres Videospiels und Übertragungsplattformen erhalten professionell organisierte Inhalte zum Vertrieb an eine wachsende Zuschauerschaft. Lediglich die Team-Organisationen und Veranstalter konzentrierten sich bisher allein auf die Erzielung von Erträgen durch die Ausübung oder Organisation von E-Sport-Wettkämpfen. Getrieben von Profitabilitätsschwächen versuchen sie jedoch, ihre Abhängigkeit von Sponsoring zu reduzieren und neue Ertragsquellen zu erschließen. Insbesondere Team-Organisationen sehen die Möglichkeiten hierfür eher außerhalb des originären E-Sport-Geschäfts und entwickeln sich dadurch immer mehr zu Marketing- und Unterhaltungsunternehmen.
The introduction of smart contracts has expanded the applicability of blockchains to many domains beyond finance and cryptocurrencies. Moreover, different blockchain technologies have evolved that target special requirements. As a result, in practice, often a combination of different blockchain systems is required to achieve an overall goal. However, due to the heterogeneity of blockchain protocols, the execution of distributed business transactions that span several blockchains leads to multiple interoperability and integration challenges. Therefore, in this article, we examine the domain of Cross-Chain Smart Contract Invocations (CCSCIs), which are distributed transactions that involve the invocation of smart contracts hosted on two or more blockchain systems. We conduct a systematic multi-vocal literature review to get an overview of the available CCSCI approaches. We select 20 formal literature studies and 13 high-quality gray literature studies, extract data from them, and analyze it to derive the CCSCI Classification Framework. With the help of the framework, we group the approaches into two categories and eight subcategories. The approaches differ in multiple characteristics, e.g., the mechanisms they follow, and the capabilities and transaction processing semantics they offer. Our analysis indicates that all approaches suffer from obstacles that complicate real-world adoption, such as the low support for handling heterogeneity and the need for trusted third parties.
Blockchains have become increasingly important in recent years and have expanded their applicability to many domains beyond finance and cryptocurrencies. This adoption has particularly increased with the introduction of smart contracts, which are immutable, user-defined programs directly deployed on blockchain networks. However, many scenarios require business transactions to simultaneously access smart contracts on multiple, possibly heterogeneous blockchain networks while ensuring the atomicity and isolation of these transactions, which is not natively supported by current blockchain systems. Therefore, in this work, we introduce the Transactional Cross-Chain Smart Contract Invocation (TCCSCI) approach that supports such distributed business transactions while ensuring their global atomicity and serializability. The approach introduces the concept of Resource Manager Smart Contracts, and 2PC for Blockchains (2PC4BC), a client-driven Atomic Commit Protocol (ACP) specialized for blockchain-based distributed transactions. We validate our approach using a prototypical implementation, evaluate its introduced overhead, and prove its correctness.
The Circular Economy aims to reintroduce the value of products back into the economic cycle at the same value chain level. While the activities of the Circular Economy are already well-defined, there exists a gap in how returned products are treated by the industry. This study aims to examine how a process should be designed to handle returned products in the context of the Circular Economy. To achieve this, a machine learning-based algorithm is used to classify data and extract relevant information throughout the product life cycle. The focus of this research is limited to land transportation systems within the Sharing Economy sector.
Die meisten Innovationsprojekte in Unternehmen scheitern nicht am Mangel an Ideen, Kreativität oder am Umsetzungswillen, sondern an vielen kleinen Hürden, die die Projekte massiv entschleunigen. So verlieren Initiativen an der Dynamik, die dafür sorgt, dass sich zügig Erfolge einstellen. Ein Bereich, in dem unkonventionell, agil und schnell Ergebnisse erzielt werden, ist das Guerilla Marketing. Was können Innovations-, Forschungs- und Projektleiter aus dem Methodenbaukasten lernen? Wie können konkrete Taktiken aus dem Marketing auch Innovationsprojekten zu mehr Viralität und Schwung verhelfen, um die Eigendynamik der Initiativen „unbremsbar“ zu machen? Das erfahren Sie in diesem essential.
The members of the European TRIZ Campus (ETC) have been learning from and working together with many honorable members of MATRIZ Official for many years and feel very connected to the official International TRIZ Association.
To further spread the TRIZ methodology and TRIZ teaching in the European area in the past 12 months the ETC has put a lot of thought in how making TRIZ accessible to a broader audi-ence and getting more professionals in touch with the methodology was one of the focal points.
To this end, we have developed new formats such as the "Trainer Day" to support trainers on their way into practice. We have drawn up detailed quality guidelines for the teaching of the TRIZ methodology, which are intended to provide orientation for the design of training classes and docu-mentation. We strive for exchange with representatives of "neighbouring" methods such as Six sigma, Lean, DFMA and Design Thinking to indicate synergies and added value among methods and approaches of different kinds. We are testing formats for community building, in order to connect users of all places more strongly with the TRIZ methodology through communication and information of-fers. If TRIZ users feel alone in their organizations, the exchange outside their organi-zation helps them to keep up with the TRIZ methodology. Moreover, the ETC strives to increase the ability to communicate the benefits of TRIZ-usage inside organizations. We discuss, how to reach teachers and students of all age, to make them the unique way of inventive thinking accessible.
In our paper we want to give other MATRIZ Official members insights and share our experi-ences and best practices with our fellow MO members.
Advancing mental health diagnostics: AI-based method for depression detection in patient interviews
(2023)
In this paper, we present a novel artificial intelligence (AI) application for depression detection, using advanced transformer networks to analyse clinical interviews. By incorporating simulated data to enhance traditional datasets, we overcome limitations in data protection and privacy, consequently improving the model’s performance. Our methodology employs BERT-based models, GPT-3.5, and ChatGPT-4, demonstrating state-of-the-art results in detecting depression from linguistic patterns and contextual information that significantly outperform previous approaches. Utilising the DAIC-WOZ and Extended-DAIC datasets, our study showcases the potential of the proposed application in revolutionising mental health care through early depression detection and intervention. Empirical results from various experiments highlight the efficacy of our approach and its suitability for real-world implementation. Furthermore, we acknowledge the ethical, legal, and social implications of AI in mental health diagnostics. Ultimately, our study underscores the transformative potential of AI in mental health diagnostics, paving the way for innovative solutions that can facilitate early intervention and improve patient outcomes.
This research evaluates current measurement scales for ambidexterity and proposes a new approach for the measurement of this important construct. We argue that current measurement approaches may be unsuitable to capture the concept of ambidexterity. Through a systematic scale development process, we derive a measurement scale with dual items that simultaneously refer to both dimensions, exploitation and exploration, thus reflecting the true nature of ambidexterity. An extensive pre-test with 39 executives suggests that our scale is suitable for capturing ambidexterity. Our measurement model enhances conceptual clarity of ambidexterity and can serve as a base for future investigations of the concept.
Why are organizations and markets slow to transform toward sustainability despite the abundant well-recognized opportunities it provides? An important subset of the phenomena this question addresses involves decision-makers recognizing the existence of opportunities but failing to undertake ambitious, effective, sufficient, or timely action. Building on existing research on capability traps, market formation, and managing sustainability, we focus on the forces con-straining organizations from developing the capabilities and market infrastructures required for sustainability transformations. We characterize types of sustainability initiatives and, using causal loop diagramming, visualize structures that enable and constrain how organizations can navigate individually and collectively worse-before-better dynamics resulting from uncertain,nonlinear, and delayed returns. Being under day-to-day pressures and deeply intertwined within their environment, organizational actors find it difficult to recognize, undertake, maintain, and coordinate necessary efforts internally and externally. We discuss research implications and directions for future research on avoiding these traps and accelerating sustainability transformations.
Cyber-Physical Production Systems increasingly use semantic information to meet the grown flexibility requirements. Ontologies are often used to represent and use this semantic information. Existing systems focus on mapping knowledge and less on the exchange with other relevant IT systems (e.g., ERP systems) in which crucial semantic information, often implicit, is contained. This article presents an approach that enables the exchange of semantic information via adapters. The approach is demonstrated by a use case utilizing an MES system and an ERP system.
Verschleiß an Zerspanwerkzeugen mit geometrisch definierter Schneide führt zu schlechter Oberflächenqualität, erhöhten Kräften, Maßabweichungen und Bruch. Bisher wird dieser Verschleiß außerhalb der Maschine oder indirekt (z. B. Durchmesser) erfasst. Der Tausch der Werkzeuge findet nach einer bestimmten Werkstückzahl, Zeit, oder einem Standweg statt. In diesem Beitrag wird ein neuartiges System zur direkten Ermittlung des Freiflächenverschleißes im Arbeitsraum eines Bearbeitungszentrums dargestellt. Dabei wird eine geschützt integrierte Industriekamera mit Objektiv im Arbeitsraum installiert. Die Maschinenachsen bzw. die Bearbeitungsspindel positionieren das Werkzeug davor. Nach einer nur wenige Sekunden dauernden Messung findet die Auswertung des Verschleißes hauptzeitparallel statt.
The EAT–Lancet planetary health diet (PHD) provides guidelines on a global scale and calls for red meat consumption to be halved. Operational PHD guidelines at country level have yet to be determined. Here we argue that the biological link between milk and bovine-meat production must be considered when operationalizing the globally calculated PHD to national contexts. Using a stylized computer simulation model rooted in a food system approach, we explore the impact of dietary scenarios on milk and bovine-meat production and show that ignoring this biological link can lead to substantial imbalances between national dietary guidelines and production outcomes and potentially lead to food waste. Furthermore, we assess current national dietary guidelines in Europe and find that most disregard this biological link and are incompatible with the PHD, with implications for policymakers and consumers to consider when adapting the PHD in national contexts.
Fragestellung: Das klinische Standardverfahren und Referenz der Schlafmessung und der Klassifizierung der einzelnen Schlafstadien ist die Polysomnographie (PSG). Alternative Ansätze zu diesem aufwändigen Verfahren könnten einige Vorteile bieten, wenn die Messungen auf eine komfortablere Weise durchgeführt werden. Das Hauptziel dieser Forschung Studie ist es, einen Algorithmus für die automatische Klassifizierung von Schlafstadien zu entwickeln, der ausschließlich Bewegungs- und Atmungssignale verwendet [1].
Patienten und Methoden: Nach der Analyse der aktuellen Forschungsarbeiten haben wir multinomiale logistische Regression als Grundlage für den Ansatz gewählt [2]. Um die Genauigkeit der Auswertung zu erhöhen, wurden vier Features entwickelt, die aus Bewegungs- und Atemsignalen abgeleitet wurden. Für die Auswertung wurden die nächtlichen Aufzeichnungen von 35 Personen verwendet, die von der Charité-Universitätsmedizin Berlin zur Verfügung gestellt wurden. Das Durchschnittsalter der Teilnehmer betrug 38,6 +/– 14,5 Jahre und der BMI lag bei durchschnittlich 24,4 +/– 4,9 kg/m2. Da der Algorithmus mit drei Stadien arbeitet, wurden die Stadien N1, N2 und N3 zum NREM-Stadium zusammengeführt. Der verfügbare Datensatz wurde strikt aufgeteilt: in einen Trainingsdatensatz von etwa 100 h und in einen Testdatensatz mit etwa 160 h nächtlicher Aufzeichnungen. Beide Datensätze wiesen ein ähnliches Verhältnis zwischen Männern und Frauen auf, und der durchschnittliche BMI wies keine signifikante Abweichung auf.
Ergebnisse: Der Algorithmus wurde implementiert und lieferte erfolgreiche Ergebnisse: die Genauigkeit der Erkennung von Wach-/NREM-/REM-Phasen liegt bei 73 %, mit einem Cohen’s Kappa von 0,44 für die analysierten 19.324 Schlafepochen von jeweils 30 s. Die beobachtete gewisse Überschätzung der NREM-Phase lässt sich teilweise durch ihre Prävalenz in einem typischen Schlafmuster erklären. Selbst die Verwendung eines ausbalancierten Trainingsdatensatzes konnte dieses Problem nicht vollständig lösen.
Schlussfolgerungen: Die erreichten Ergebnisse haben die Tauglichkeit des Ansatzes prinzipiell bestätigt. Dieser hat den Vorteil, dass nur Bewegungs- und Atemsignale verwendet werden, die mit weniger Aufwand und komfortabler für Benutzer aufgezeichnet werden können als z. B. Herz- oder EEG-Signale. Daher stellt das neue System eine deutliche Verbesserung im Vergleich zu bestehenden Ansätzen dar. Die Zusammenführung der beschriebenen algorithmischen Software mit dem in [1] beschriebenen Hardwaresystem zur Messung von Atem- und Körperbewegungssignalen zu einem autonomen, berührungslosen System zur kontinuierlichen Schlafüberwachung ist eine mögliche Richtung zukünftiger Arbeiten.
Organizational agility may be an antidote against threats from volatile, uncertain, complex, or ambiguous corporate environments. While agility has been extensively examined in manufacturing enterprises, comparably less is known about agility in knowledge-intensive organizations. As results may not be transferable, there is still some confusion about how agility in knowledge-intensive organizations can be characterized, what factors facilitate its development, what its organizational effects are, and what environmental conditions favor these effects. This study closes these gaps by presenting a systematic literature review on agility in knowledge-intensive organizations. A systematic literature search led to a sample of 37 relevant papers for our review. Integrating the knowledge-based view and a dynamic capabilities perspective, we (1) present different relevant conceptualizations of organizational agility, (2) discuss relevant knowledge management-related as well as information technology-related capabilities that support the development of organizational agility, and (3) shed light on the moderating role of environmental conditions in enhancing organizational agility and its effect on organizational performance. This academic paper adds value to theory by synthesizing existing research on agility in knowledge-intensive organizations. It furthermore may serve as a map for closing research gaps by proposing an extensive agenda for future research. Our study expands existing literature reviews on agility with its specific focus on a knowledge-intensive context and its integration of the research streams of knowledge management capabilities as well as information technology capabilities. It integrates relevant organizational knowledge management practices and the use of knowledge management systems to ensure superior performance effects. Our study can serve as a base for future examinations of organizational agility by illustrating fruitful topics for further examination as well as open questions. It may also provide value to practitioners by showing what factors favor the development of agility in knowledge-intensive organizations and what organizational effects can be achieved under which conditions.
Knowledge-intensive organizations primarily rely on knowledge and expertise as key strategic resources. In light of economic, social, and health-related crises in recent years, such organizations increasingly need to operate in dynamic environments. However, examinations on dynamic capabilities specifically in knowledge-intensive organizations remain scarce. This is remarkable given the role that knowledge holds as an economic resource in developed countries. To provide an explanation of how knowledge-intensive organizations can prevail among competitors under dynamic conditions, the authors integrate two literature streams in a knowledge-intensive context: the knowledge-based view and the dynamic capabilities approach. The knowledge-based view focuses on the nature of organizational knowledge as a critical resource and illustrates specific properties of knowledge in contrast to traditional means of labor such as capital. The dynamic capabilities approach on the other hand is about a firm's ability to integrate, build, and reconfigure internal and external resources and can be drawn on to explain organizational success through adaptation to dynamic contexts. In this conceptual study, the authors propose a research model linking knowledge processes to organizational performance through two different paths: (1) Operational capabilities permit organizations to make their living in the present and refer to efficiency. (2) Dynamic capabilities allow organizations to change their resource base and, therefore, enable their long-term survival in dynamic environments by focusing on effectiveness. Additionally, the authors hypothesize a moderating effect of environmental dynamics on the relationship between dynamic capabilities and performance. The study offers a comprehensive overview on the interplay between dynamic capabilities and the knowledge-based view, offering valuable insights for both researchers and practitioners in the field.
Context
In a world of high dynamics and uncertainties, it is almost impossible to have a long-term prediction of which products, services, or features will satisfy the needs of the customer. To counter this situation, the conduction of Continuous Improvement or Design Thinking for product discovery are common approaches. A major constraint in conducting product discovery activities is the high effort to discover and validate features and requirements. In addition, companies struggle to integrate product discovery activities into their agile processes and iterations.
Objective
This paper aims at suggests a supportive tool, the “Discovery Effort Worthiness (DEW) Index”, for product owners and agile teams to determine a suitable amount of effort that should be spent on Design Thinking activities. To operationalize DEW, proposals for practitioners are presented that can be used to integrate product discovery into product development and delivery.
Method
A case study was conducted for the development of the DEW index. In addition, we conducted an expert workshop to develop proposals for the integration of product discovery activities into the product development and delivery process.
Results
First, we present the "Discovery Effort Worthiness Index" in form of a formula. Second, we identified requirements that must be fulfilled for systematic integration of product discovery activities into product development and delivery. Third, we derived from the requirements proposals for the integration of product discovery activities with a company's product development and delivery.
Conclusion
The developed "Discovery Effort Worthiness Index" provides a tool for companies and their product owners to determine how much effort they should spend on Design Thinking methods to discover and validate requirements. Integrating product discovery with product development and delivery should ensure that the results of product discovery are incorporated into product development. This aims to systematically analyze product risks to increase the chance of product success.
Human pose estimation (HPE) is integral to scene understanding in numerous safety-critical domains involving human-machine interaction, such as autonomous driving or semi-automated work environments. Avoiding costly mistakes is synonymous with anticipating failure in model predictions, which necessitates meta-judgments on the accuracy of the applied models. Here, we propose a straightforward human pose regression framework to examine the behavior of two established methods for simultaneous aleatoric and epistemic uncertainty estimation: maximum a-posteriori (MAP) estimation with Monte-Carlo variational inference and deep evidential regression (DER). First, we evaluate both approaches on the quality of their predicted variances and whether these truly capture the expected model error. The initial assessment indicates that both methods exhibit the overconfidence issue common in deep probabilistic models. This observation motivates our implementation of an additional recalibration step to extract reliable confidence intervals. We then take a closer look at deep evidential regression, which, to our knowledge, is applied comprehensively for the first time to the HPE problem. Experimental results indicate that DER behaves as expected in challenging and adverse conditions commonly occurring in HPE and that the predicted uncertainties match their purported aleatoric and epistemic sources. Notably, DER achieves smooth uncertainty estimates without the need for a costly sampling step, making it an attractive candidate for uncertainty estimation on resource-limited platforms.
The Industry 4.0 paradigm requires concepts for integrating intelligent/ smart IoT Solutions into manufacturing. Such intelligent solutions are envisioned to increase flexibility and adaptability in smart factories. Especially autonomous cobots capable of adapting to changing conditions are a key enabler for changeable factory concepts. However, identifying the requirements and solution scenarios incorporating intelligent products challenges the manufacturing industry, especially in the SME sector. In pick and place scenarios, changing coordinate systems of workpiece carriers cause placing process errors. Using the IPIDS framework, this paper describes the development of a tool-center-point positioning method to improve the process stability of a collaborative robot in a changeable assembly workstation. Applying the framework identifies the requirement for an intelligent workpiece carrier as a part of the solution. Implementing and evaluating the solution within a changeable factory validates the IPIDS framework.
Due to constantly changing conditions, demand, and technologies, companies increasingly seek flexibility. Productivity results from automation, improved working conditions and the focus of people in production in interaction with machines. Unfortunately, the human factor is often not considered to increase flexibility and productivity with new concepts. This work aims to develop a hybrid assistance system that allows a dynamic configuration of cyber-physical production systems considering the current order situation and available resources utilizing simulation. The system also considers human factors in addition to economic factors, which contributes to the extended economic appraisal.
In recent years, the demand for accurate and efficient 3D body scanning technologies has increased, driven by the growing interest in personalised textile development and health care. This position paper presents the implementation of a novel 3D body scanner that integrates multiple RGB cameras and image stitching techniques to generate detailed point clouds and 3D mesh models. Our system significantly enhances the scanning process, achieving higher resolution and fidelity while reducing the cost, time and effort required for data acquisition and processing. Furthermore, we evaluate the potential use cases and applications of our 3D body scanner, focusing on the textile technology and health sectors. In textile development, the 3D scanner contributes to bespoke clothing production, allowing designers to construct made-to-measure garments, thus minimising waste and enhancing customer satisfaction through fitting clothing. In mental health care, the 3D body scanner can be employed as a tool for body image analysis, providing valuable insights into the psychological and emotional aspects of self-perception. By exploring the synergy between the 3D body scanner and these fields, we aim to foster interdisciplinary collaborations that drive advancements in personalisation, sustainability, and well-being.
The hard template method for the preparation of monodisperse mesoporous silica microspheres (MPSMs) has been established in recent years. In this process, in situ-generated silica nanoparticles (SNPs) enter the porous organic template and control the size and pore parameters of the final MPSMs. Here, the sizes of the deposited SNPs are determined by the hydrolysis and condensation rates of different alkoxysilanes in a base catalyzed sol–gel process. Thus, tetramethyl orthosilicate (TMOS), tetraethyl orthosilicate (TEOS), tetrapropyl orthosilicate (TPOS) and tetrabutyl orthosilicate (TBOS) were sol–gel processed in the presence of amino-functionalized poly (glycidyl methacrylate-co-ethylene glycol dimethacrylate) (p(GMA-co-EDMA)) templates. The size of the final MPSMs covers a broad range of 0.5–7.3 µm and a median pore size distribution from 4.0 to 24.9 nm. Moreover, the specific surface area can be adjusted between 271 and 637 m2 g−1. Also, the properties and morphology of the MPSMs differ according to the SNPs. Furthermore, the combination of different alkoxysilanes allows the individual design of the morphology and pore parameters of the silica particles. Selected MPSMs were packed into columns and successfully applied as stationary phases in high-performance liquid chromatography (HPLC) in the separation of various water-soluble vitamins.
Patterns are virtually simulated in 3D CAD programs before production to check the fit. However, achieving lifelike representations of human avatars, especially regarding soft tissue dynamics, remains challenging. This is mainly since conventional avatars in garment CAD programs are simulated with a continuous hard surface and not corresponding to the human physical and mechanical body properties of soft tissue. In the real world, the human body’s natural shape is affected by the contact pressure of tight-fitting textiles. To verify the fit of a simulated garment, the interactions between the individual body shape and the garment must be considered. This paper introduces an innovative approach to digitising the softness of human tissue using 4D scanning technology. The primary objective of this research is to explore the interactions between tissue softness and different compression levels of apparel, exerting pressure on the tissue to capture the changes in the natural shape. Therefore, to generate data and model an avatar with soft body physics, it is essential to capture the deform ability and elasticity of the soft tissue and map it into the modification options for a simulation. To aim this, various methods from different fields were researched and compared to evaluate 4D scanning as the most suitable method for capturing tissue deformability in vivo. In particular, it should be considered that the human body has different deformation capabilities depending on age, the amount of muscle and body fat. In addition, different tissue zones have different mechanical properties, so it is essential to identify and classify them to back up these properties for the simulation. It has been shown that by digitising the obtained data of the different defined applied pressure levels, a prediction of the deformation of the tissue of the exact person becomes possible. As technology advances and data sets grow, this approach has the potential to reshape how we verify fit digitally with soft avatars and leverage their realistic soft tissue properties for various practical purposes.
With the rapid development of globalization, the demand for translation between different languages is also increasing. Although pre-training has achieved excellent results in neural machine translation, the existing neural machine translation has almost no high-quality suitable for specific fields. Alignment information, so this paper proposes a pre-training neural machine translation with alignment information via optimal transport. First, this paper narrows the representation gap between different languages by using OTAP to generate domain-specific data for information alignment, and learns richer semantic information. Secondly, this paper proposes a lightweight model DR-Reformer, which uses Reformer as the backbone network, adds Dropout layers and Reduction layers, reduces model parameters without losing accuracy, and improves computational efficiency. Experiments on the Chinese and English datasets of AI Challenger 2018 and WMT-17 show that the proposed algorithm has better performance than existing algorithms.
Analog integrated circuit sizing still relies heavily on human expert knowledge as previous automation approaches have not found wide-spread acceptance in industry. One strand, the optimization-based automation, is often discarded due to inflated constraining setups, infeasible results or excessive run times. To address these deficits, this work proposes a alternative optimization flow featuring a designer’s intuition for feasible design spaces through integration of expert knowledge based on the gm/ID-method. Moreover, the extensive run times of simulation-based optimization flows are overcome by incorporating computationally efficient machine learning methods. Neural network surrogate models predicting eleven performance parameters increase the evaluation speed by 3 400× on average compared to a simulator. Additionally, they enable the use of optimization algorithms dependent on automatic differentiation, that would otherwise be unavailable in this field. First, an up to 4× more efficient way for sampling training data based on the aforementioned space is detailed. After presenting the architecture and training effort regarding the surrogate models, they are employed as part of the objective function for sizing three operational amplifiers with three different optimization algorithms. Additionally, the benefits of using the gm/ID-method become evident when considering technology migration, as previously found solutions may be reused for other technologies.
First-generation university graduates have been found to face a series of disadvantages on their pathway to higher education and the labor market. We use unique, national level data on high achieving university graduates to attempt to disentangle the importance of lower prior attainment from parental educational background on a series of higher education and labor market outcomes. We compare first-generation and non-first-generation graduates who are recipients of a prestigious national scholarship program targeted at the top percentile of the student distribution in Germany. We find the first-generation high achievers are more likely to study at less prestigious institutions and at institutions that are closer to home even though they have the prior attainment to go further afield. They are also less likely to study subjects with high labor market returns and are more likely to work in jobs with high job security. We furthermore find evidence that especially female first-generation high achievers are less likely to see the value of the networking opportunities the scholarship provides.
Natural wood colors occur within a wide range from almost white (e.g., white poplar), various yellowish, reddish, and brownish hues to almost black (e.g., ebony). The intrinsic color of wood is basically defined by its chemical composition. However, other factors such as specific anatomical formations or physical properties further affect the optical impression. Starting with the chemical composition of wood and anatomical basics, wood color and its modifications are discussed in this chapter. The classic method of coloring or re-coloring wood-based material surfaces is the application of a coating containing appropriate dyes or pigments. Different concepts for wood coating and coloration are presented. Another method used dyes for coloration of the wood structure. As alternative techniques, physical methods, for example, drying, steaming, ammoniation, bleaching, enzyme treatment, as well as treatment with electromagnetic irradiation (e.g., UV), are explained in this chapter.
Die neue Arbeitswelt verändert den Arbeitsmarkt rasant und fördert die Entwicklung neuer Arbeitsmodelle. Hybrid Work bietet dabei unzählige Zukunftspotentiale, die das eigene Unternehmen nach innen und außen auf ein ganz neues Niveau heben können. In diesem Buch stellen Expert:innen aus Wirtschaft, Politik und Wissenschaft die Herausforderungen, Chancen und Lösungen der neuen Arbeitsmodelle vor und werfen einen Blick in die Zukunft. Sie diskutieren, wie sich hybride Arbeit auf die Produktivität und das Wohlbefinden der Mitarbeiter:innen auswirkt und welche Anforderungen an Führungskräfte gestellt werden, um erfolgreich zu führen.
Facing ever-looming climate change, studying the drivers for individuals' Information Systems (IS) Use to reduce environmental harm gains momentum. While extant research on the antecedents of sustainable IS Use has focused on specific theories, interventions, contexts, and technologies, a holistic understanding has become increasingly elusive, with a synthesis remaining absent. We employ a systematic literature review methodology to shed light on the driving antecedents for sustainable IS Use among individual consumers. Our results build on findings of 29 empirical studies drawn from 598 articles retrieved from our premier outlets and a forward/backward search. The analysis reveals six salient complementary antecedents: Relief, Empowerment, Default, User-centricity, Salience, and Encouragement. We recommend considering these concepts when developing, deploying, promoting, or regulating digital technologies to mitigate individual consumers' emissions. Along with memorable and implementable concepts, our theoretical framework offers a novel conceptualization and four promising avenues for researchers on sustainable IS Use.
This article presents a modified method of performing power flow calculations as an alternative to pure energy-based simulations of off-grid hybrid systems. The enhancement consists in transforming the scenario-based power flow method into a discrete time-dependent algorithm with the inclusion of bus and controller dynamics.
Fazit und Ausblick
(2023)
In diesem abschließenden Kapitel erfolgt zunächst eine zusammenfassende Diskussion der verschiedenen Teile des vorliegenden Bandes sowie der einzelnen Kapitel. Dabei wird auf die Hauptaussagen der jeweiligen Kapitel eingegangen und ein Fazit zu jedem Teil gezogen. Daran anknüpfend setzen sich die Herausgeber des Bandes mit der Zukunft des Nachhaltigkeitsmanagements im Allgemeinen sowie der Zukunft eines nachhaltigen Sport- und Kulturmanagements im Besonderen auseinander. Abschließend wird ein maßgeschneidertes Weiterbildungsangebot als Baustein zur Bewältigung dieser Herausforderungen vorgestellt.
Delphi Markets
(2023)
Delphi markets refer to approaches and implementations of integrating prediction markets and Delphi studies (Real-time Delphi). The combination of the two methods for producing forecasts can potentially compensate for each other´s weaknesses. For example, prediction markets can be used to select participants with expertise and also motivate long-term participation through their gamified approach and incentive mechanisms. In this paper, two potentials for prediction markets and four potentials for Delphi studies, which are made possible by integration, are derived theoretically. Subsequently, three different integration approaches are presented, on the basis of which the integration on user, market and Delphi question-level is exemplified and it is shown that, depending on the approach, not all potentials can be achieved. At the end, recommendations for the use of Delphi markets are derived, existing limitations for Delphi markets as well as future developments are pointed out.
Film formation of self synthesized Polymer EPM–g–VTMDS (ethylene–propylene rubber, EPM, grafted with vinyltetramethyldisiloxane, VTMDS) was studied regarding bonding to adhesion promoter vinyltrimethoxysilane (VTMS) on oxidized 18/10 chromium/nickel–steel (V2A) stainless steel surfaces. Polymer films of different mixed solutions including commercial siloxane and silicone, dimethyl, vinyl group terminated crosslinker (HANSA SFA 42100, CAS# 68083-19-2, 0.35 mmol Vinyl/g) and platinum, 1,3-diethenyl-1,1,3,3-tetramethyldisiloxane complex Karstedt's catalyst (ALPA–KAT 1, CAS# 68478-92-2) were spin coated on V2A stainless steel surfaces with adsorbed VTMS thin layers in order to analyze film formation of EPM–g–VTMDS at early stages. Surface topography and chemical bonding of the high performance polymers on different oxidized V2A surfaces were investigated with X–ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), scanning electron microscopy (SEM) and surface enhanced Raman spectroscopy (SERS). AFM and SEM as well as XPS results indicated that the formation of the polymer film proceeds via growth of polymer islands. Chemical signatures of the essential polymer contributions, linker and polymer backbones, could be identified using XPS core level peak shape analysis and also SERS. The appearance of signals which are related to Si–O–Si can be seen as a clear indication of lateral crosslinking and silica network formation in the films on the V2A surface.
Smart cities are considered data factories that generate an enormous amount of data from various sources. In fact data is the backbone of any smart services. Therefore, the strategic beneficial handling of this digital capital is crucial for cities. Some smart city pioneers have already written down their approach to data in the form of data strategies, but what should a city's data strategy include, and how can the goals and measures defined in the strategies be operationalized? This paper addresses these questions by looking closely at the data strategies of cities in Germany and the top three countries in the EU Digital Economy and Society Index. The in-depth analysis of 8 city data strategies has yielded 11 dimensions that cities should consider in their data strategy. These are relevance of data, principles, methods, data sharing, technology, data culture, data ethics, organizational structure, data security and privacy, collaborations, data literacy. In addition, data governance is a concept to put these 11 strategic dimensions into practice through standardization measures, training programs, and defining roles and responsibilities by developing a data catalog.
Platforms feature increasingly complex architectures with regard to interconnecting with other digital platforms as well as with a variety of devices and services. This development also impacts the structure of digital platform ecosystems and forces providers of these services, devices, and services to incorporate this complexity in their decision-making. To contribute to the existing body of knowledge on measuring ecosystem complexity, the present research proposes two key artefacts based on ecosystem intelligence: On the one hand, complementarity graphs represent ecosystems with an ecosystem's functional modules as vertices and complementarities as edges. The nodes carry information about the category membership of the module. On the other hand, a process is suggested that can collect important information for ecosystem intelligence using proxies and web scraping. Our approach allows replacing data, which today is largely unavailable due to competitive reasons. We demonstrated the use of the artefacts in category-oriented complementarity maps that aggregate the information from complementarity graphs and support decision-making. They show which combination of module categories creates strong and weak complementarities. The paper evaluates complementarity maps and the data collection process by creating category-oriented complementarity graphs on the Alexa skill ecosystem and concludes with a call to pursue more research based on functional ecosystem intelligence.
Project managers still face management problems in interorganizational Research and Development (R&D) projects due to their limited authority. Addressing a project culture which is conducive to cooperation and innovation in interorganizational R&D project management demands commitment of individual project members and thus balances this limited authority. However, the relational collaboration level at which project culture manifests itself is not addressed by current project management approaches, or it is addressed only at a late stage. Consequently, project culture develops within a predefined framework of project organization and organized contents and thus is not actively targeted. Therefore, a focus shift towards project culture becomes necessary. This can be done by a project-culture-aware management. The method CLIPS actively supports interorganizational project members in this kind of management. It should be integrable in the common project management approaches, that with its application all collaboration levels are addressed in interorganizational R&D project management. The goal of this paper is to demonstrate the integrability of the method CLIPS and show how it can be integrated in common project management approaches. This enriches interorganizational R&D project management by a project culture focus.
The chemical recycling of used motor oil via catalytic cracking to convert it into secondary diesel-like fuels is a sustainable and technically attractive solution for managing environmental concerns associated with traditional disposal. In this context, this study was conducted to screen basic and acidic-aluminum silicate catalysts doped with different metals, including Mg, Zn, Cu, and Ni. The catalysts were thoroughly characterized using various techniques such as N2 adsorption–desorption isotherms, FT-IR spectroscopy, and TG analysis. The liquid and gaseous products were identified using GC, and their characteristics were compared with acceptable ranges from ASTM characterization methods for diesel fuel. The results showed that metal doping improved the performance of the catalysts, resulting in higher conversion rates of up to 65%, compared to thermal (15%) and aluminum silicates (≈20%). Among all catalysts, basic aluminum silicates doped with Ni showed the best catalytic performance, with conversions and yields three times higher than aluminum silicate catalysts. These findings significantly contribute to developing efficient and eco-friendly processes for the chemical recycling of used motor oil. This study highlights the potential of basic aluminum silicates doped with Ni as a promising catalyst for catalytic cracking and encourages further research in this area.
Polyurethane thermosets have a wide range of applications. In this study, alternative raw materials were used to enhance sustainability. In two newly developed biobased polyurethanes (PUs), the cross-linker content was varied, which caused phase separation and therefore affected the turbidity. To investigate this phenomenon, UV–Vis–NIR spectroscopy was utilized. Spectra were recorded from 200 to 2500 nm in transmittance mode, and multivariate data analysis was applied to the three UV, Vis, and NIR sections separately. For the two different PU classes, each with five different cross-linker contents, classification by principal component analysis combined with linear or quadratic discriminant analysis was possible with an accuracy between 93% and nearly 100%. The best separation was achieved in the NIR range. Partial least-squares regression models were determined to predict the cross-linker content. As mentioned, the model for the NIR range is the most suitable, with the highest R2 (validation) of 0.99 for PU1 and 0.98 for PU2. The corresponding root-mean-square error of prediction values of the external validation was the lowest, with 0.82% (PU1) and 1.25% (PU2). Therefore, UV–Vis–NIR absorbance spectroscopy, especially NIR, is a suitable tool for monitoring the appropriate material composition of turbid PU thermosets in line.