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A MATLAB toolbox was developed both for teachers performing quick experimental demonstrations during lectures and for students practicing measurement and frequency analysis procedures. The conceptual purpose was to support fundamental acoustics courses with contents defined by the DEGA recommendation 102. All implemented functions and parameters are visible at once and quickly adjustable by a GUI without submenus. A user manual is provided with explanations of how to get started and how all implemented functions can be applied. The toolbox probably still contains bugs. All users are welcome to inform the author about their experiences and proposals for improvement. In future it is planned to convert "Acoustics" to the MATLAB app designer format as Mathworks announced GUIDE to be replaced. Useful extensions would be additional tabs containing animations of sound propagation phenomena or sound fields caused by different sources.
For a holistic assessment of the interaction between the human body and tight fitted clothing, it is necessary to consider the mechanical properties of the body. Default avatars in CAD software are usually solid and do not take this interaction into account. For this purpose, a solid avatar is converted to a deformable one by using the soft body physics implementation in the simulation program Blender. The fit of a 3D garment on both avatars are compared, which allows a first evaluation of the differences between these approaches.
Lehrbuch zur CAD-Software Creo Parametric und zur Produktdatenverwaltung mit Windchill.
3D-Volumenmodellierung, 3D-Flächenmodellierung, Blechmodellierung, Baugruppen- und Zeichnungserstellung, Definition von Normteilen, Erstellen von Animationen und dynamischen Analysen.
Verfahren zum Umgang mit großen Baugruppen und zur flexiblen Modellierung, Konstruk-tionsvarianten "Top-Down" und "Bottom-Up", Organisation von Konstruktionsprojekten über Skeletttechnik.
Neu: Konstruktion von und mit Mehrkörperobjekten, Rahmenkonstruktion in der Profilumgebung (AFX), intelligente Verbindungen (IFX), Live Simulation und Generatives Design.
A closed-loop control for a cooperative innovation culture in interorganizational R&D projects
(2022)
Since project managers only have a limited authority in interorganizational R&D projects a cooperative innovation culture is essential for team cohesion and thus for achieving project scope in time and cost. For its development different factors depending on underlying values are essential. These factors must be learned iteratively by the project members so that they are living the values of a cooperative innovation culture. Hence, this paper raises the following research question: “How to control living the values of a cooperative innovation culture in interorganizational R&D projects?” To answer this question, a closed-loop control for a cooperative innovation culture is developed. The developed closed-loop control system includes several different functional units which show essential roles and several different variables which show what to consider and design in the control system. In addition, the developed closed-loop control system is generalized for other types of projects such as intraorganizational projects.
The rapid development and growth of knowledge has resulted in a rich stream of literature on various topics. Information systems (IS) research is becoming increasingly extensive, complex, and heterogeneous. Therefore, a proper understanding and timely analysis of the existing body of knowledge are important to identify emerging topics and research gaps. Despite the advances of information technology in the context of big data, machine learning, and text mining, the implementation of systematic literature reviews (SLRs) is in most cases still a purely manual task. This might lead to serious shortcomings of SLRs in terms of quality and time. The outlined approach in this paper supports the process of SLRs with machine learning techniques. For this purpose, we develop a framework with embedded steps of text mining, cluster analysis, and network analysis to analyze and structure a large amount of research literature. Although the framework is presented using IS research as an example, it is not limited to the IS field but can also be applied to other research areas.
Purpose
Supporting the surgeon during surgery is one of the main goals of intelligent ORs. The OR-Pad project aims to optimize the information flow within the perioperative area. A shared information space should enable appropriate preparation and provision of relevant information at any time before, during, and after surgery.
Methods
Based on previous work on an interaction concept and system architecture for the sterile OR-Pad system, we designed a user interface for mobile and intraoperative (stationary) use, focusing on the most important functionalities like clear information provision to reduce information overload. The concepts were transferred into a high-fidelity prototype for demonstration purposes. The prototype was evaluated from different perspectives, including a usability study.
Results
The prototype’s central element is a timeline displaying all available case information chronologically, like radiological images, labor findings, or notes. This information space can be adapted for individual purposes (e.g., highlighting a tumor, filtering for own material). With the mobile and intraoperative mode of the system, relevant information can be added, preselected, viewed, and extended during the perioperative process. Overall, the evaluation showed good results and confirmed the vision of the information system.
Conclusion
The high-fidelity prototype of the information system OR-Pad focuses on supporting the surgeon via a timeline making all available case information accessible before, during, and after surgery. The information space can be personalized to enable targeted support. Further development is reasonable to optimize the approach and address missing or insufficient aspects, like the holding arm and sterility concept or new desired features.
Data governance have been relevant for companies for a long time. Yet, in the broad discussion on smart cities, research on data governance in particular is scant, even though data governance plays an essential role in an environment with multiple stakeholders, complex IT structures and heterogeneous processes. Indeed, not only can a city benefit from the existing body of knowledge on data governance, but it can also make the appropriate adjustments for its digital transformation. Therefore, this literature review aims to spark research on urban data governance by providing an initial perspective for future studies. It provides a comprehensive overview of data governance and the relevant facets embedded in this strand of research. Furthermore, it provides a fundamental basis for future research on the development of an urban data governance framework.
A new planar compact antenna composed of two crossed Cornu spirals is presented. Each Cornu spiral is fed from the center of the linearly part of the curvature between the two spirals, which builds the clothoid. Sequential rotation is applied using a sequential phase network to obtain circular polarization and increase the effective bandwidth. Signal integrity issues have been addressed and designed to ensure high quality of signal propagation. As a result, the antenna shows good radiation characteristics in the bandwidth of interest. Compared to antennas of the same size in the literature, it is broadband and of high gain. Although the proposed antenna has been designed for K- and Ka-band operations, it can also be developed for lower and upper frequencies because of the linearity of the Maxwell equations.
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.
Continuous manufacturing is becoming more important in the biopharmaceutical industry. This processing strategy is favorable, as it is more efficient, flexible, and has the potential to produce higher and more consistent product quality. At the same time, it faces some challenges, especially in cell culture. As a steady state has to be maintained over a prolonged time, it is unavoidable to implement advanced process analytical technologies to control the relevant process parameters in a fast and precise manner. One such analytical technology is Raman spectroscopy, which has proven its advantages for process monitoring and control mostly in (fed-) batch cultivations. In this study, an in-line flow cell for Raman spectroscopy is included in the cell-free harvest stream of a perfusion process. Quantitative models for glucose and lactate were generated based on five cultivations originating from varying bioreactor scales. After successfully validating the glucose model (Root Mean Square Error of Prediction (RMSEP) of ∼0.2 g/L), it was employed for control of an external glucose feed in cultivation with a glucose-free perfusion medium. The generated model was successfully applied to perform process control at 4 g/L and 1.5 g/L glucose over several days, respectively, with variability of ±0.4 g/L. The results demonstrate the high potential of Raman spectroscopy for advanced process monitoring and control of a perfusion process with a bioreactor and scale-independent measurement method.
A single-phase fixed-frequency operated power factor correction circuit with reduced switching losses is proposed. The circuit uses the combination of a boost converter with an added clamp-switch, a pulse wave shaping circuit, and a standard control IC to discharge the transistor's output capacitance prior to its turn-on. In this way, a very low-complexity control circuit implementation to reduce switching losses or even achieve complete zero-voltage switching without additional sensors is possible. Moreover, this operation method is achieved at a constant switching frequency, possibly simplifying the design of the EMI filter and the converter's inductor. Experimental test results for a 100 W prototype converter are presented to validate the feasibility of the proposed operating method and corresponding circuit structure.
The usage of webinars is witnessing a resurgence in popularity, especially since the COVID-19 pandemic. It is now revealing itself to be an actual shift in how buyers and sellers do business in the future. Therefore, this study aims to investigate whether webinars will continue to be a valuable tool in B2B sales in the future. Specifically, it aims to gain a deeper understanding of how the role of webinars evolved in recent years and analyze its future potential.
Webinars are an essential tool for a wide variety of different use cases. While they have been around for over a decade, webinars recently have seen a resurgence in popularity. As the COVID-19 pandemic strictly limited contact between people and made them work from home as an only option, hosting and participating in webinars has become more common than ever - whether in business, education, or leisure.
Webinars can be effective for various purposes as they are held in real-time and allow multiple engagement opportunities between attendees and hosts. Moreover, because of their remote nature, webinars are more cost-effective and time-saving in organizing and supervising. Consequently, it is cheaper and more convenient to reach your desired target group as a webinar host than to hold a seminar in physical form. Among other reasons, convenience and interaction seem to be the most potent aspects of cementing webinars as a tool in the digital world. Nevertheless, where exactly are they used, and how do they create value in their respective usage fields?
Blockchain is a technology for the secure processing and verification of data transactions based on a distributed peer-to-peer network that uses cryptographic processes, consensus algorithms, and backward-linked blocks to make transactions virtually immutable. Within supply chain management, blockchain technology offer potentials in increasing supply chain transparency, visibility, automation, and efficiency. However, its complexity requires future employees to have comprehensive knowledge regarding the functionality of blockchain-based applications in order to be able to apply their benefits to scenarios in supply chain and production. Learning factories represent a suitable environment allowing learners to experience new technologies and to apply them to virtual and physical processes throughout value chains. This paper presents a concept to practically transfer knowledge about the technical functionality of blockchain technology to future engineers and software developers working within supply chains and production operations to sensitize them regarding the advantages of decentralized applications. First, the concept proposes methods to playfully convey immutable backward-linked blocks and the embedment of blockchain smart contracts. Subsequently, the students use this knowledge to develop blockchain-based application scenarios by means of an exemplary product in a learning factory environment. Finally, the developed solutions are implemented with the help of a prototypical decentralized application, which enables a holistic mapping of supply chain events.
Glioblastoma WHO IV belongs to a group of brain tumors that are still incurable. A promising treatment approach applies photodynamic therapy (PDT) with hypericin as a photosensitizer. To generate a comprehensive understanding of the photosensitizer-tumor interactions, the first part of our study is focused on investigating the distribution and penetration behavior of hypericin in glioma cell spheroids by fluorescence microscopy. In the second part, fluorescence lifetime imaging microscopy (FLIM) was used to correlate fluorescence lifetime (FLT) changes of hypericin to environmental effects inside the spheroids. In this context, 3D tumor spheroids are an excellent model system since they consider 3D cell–cell interactions and the extracellular matrix is similar to tumors in vivo. Our analytical approach considers hypericin as probe molecule for FLIM and as photosensitizer for PDT at the same time, making it possible to directly draw conclusions of the state and location of the drug in a biological system. The knowledge of both state and location of hypericin makes a fundamental understanding of the impact of hypericin PDT in brain tumors possible. Following different incubation conditions, the hypericin distribution in peripheral and central cryosections of the spheroids were analyzed. Both fluorescence microscopy and FLIM revealed a hypericin gradient towards the spheroid core for short incubation periods or small concentrations. On the other hand, a homogeneous hypericin distribution is observed for long incubation times and high concentrations. Especially, the observed FLT change is crucial for the PDT efficiency, since the triplet yield, and hence the O2 activation, is directly proportional to the FLT. Based on the FLT increase inside spheroids, an incubation time 30 min is required to achieve most suitable conditions for an effective PDT.
The extracellular matrix (ECM) is the non-cellular part of tissues and represents the natural environment of the cells. Next to structural stability, it provides various physical, chemical, and mechanical cues that strongly regulate and influence cellular behavior and are required for tissue morphogenesis, differentiation, and homeostasis. Due to its promising characteristics, ECM is used in a wide range of tissue engineering and regenerative medicine approaches as a biomaterial for coatings and scaffolds. To date, there are two sources for ECM material. First, native ECM is generated by the removal of the residing cells of a tissue or organ (decellularized ECM; dECM). Secondly, cell-derived ECM (cdECM) can be generated by and isolated from in vitro cultured cells. Although both types of ECM were intensively used for tissue engineering and regenerative medicine approaches, studies directly characterizing and comparing them are rare. Hence, in the first part of this thesis, dECM from adipose tissue and cdECM from stem cells and adipogenic differentiated stem cells from adipose tissue (ASCs) were characterized towards their macromolecular composition, structural features, and biological purity. The dECM was found to exhibit higher levels of collagens and lower levels of sulfated glycosaminoglycans compared to cdECMs. Structural characteristics revealed an immature state of collagen fibers in cdECM samples. The obtained results revealed differences between the two ECMs that can relevantly impact cellular behavior and subsequently experimental outcome and should therefore be considered when choosing a biomaterial for a specific application. The establishment of a functional vascular system in tissue constructs to realize an adequate nutrient supply remains challenging. In the second part, the supporting effect of cdECM on the self‐assembled formation of prevascular‐like structures by microvascular endothelial cells (mvECs) was investigated. It could be observed that cdECM, especially adipogenic differentiated cdECM, enhanced the formation of prevascular-like structures. An increased concentration of proangiogenic factors was found in cdECM substrates. The demonstration of cdECMs capability to induce the spontaneous formation of prevascular‐like structures by mvECs highlights cdECM as a promising biomaterial for adipose tissue engineering. Depending on the purpose of the ECM material chemical modification might be necessary. In the third and last part, the chemical functionalization of cdECM with dienophiles (terminal alkenes, cyclopropene) by metabolic glycoengineering (MGE) was demonstrated. MGE allows the chemical functionalization of cdECM via the natural metabolism of the cells and without affecting the chemical integrity of the cdECM. The incorporated dienophile chemical groups can be specifically addressed via catalysts-free, cell-friendly inverse electron-demand Diels‐Alder reaction. Using this system, the successful modification of cdECM from ASCs with an active enzyme could be shown. The possibility to modify cdECM via a cell-friendly chemical reaction opens up a wide range of possibilities to improve cdECM depending on the purpose of the material. Altogether, this thesis highlighted the differences between adipose dECM and cdECM from ASCs and demonstrated cdECM as a promising alternative to native dECM for application in tissue engineering and regenerative medicine approaches.
The aim of this work is to establish and generalize a relationship between fractional partial differential equations (fPDEs) and stochastic differential equations (SDEs) to a wider class of stochastic processes, including fractional Brownian motions and sub-fractional Brownian motions with Hurst parameter H ∈ (1/2,1). We start by establishing the connection between a fPDE and SDE via the Feynman-Kac Theorem, which provides a stochastic representation of a general Cauchy problem. In hindsight, we extend this connection by assuming SDEs with fractional and sub-fractional Brownian motions and prove the generalized Feynman-Kac formulas under a (sub-)fractional Brownian motion. An application of the theorem demonstrates, as a by-product, the solution of a fractional integral, which has relevance in probability theory.
Affordable Luxury Sports Cars in Germany : Investigating the Determinants of Customer Experience
(2022)
The article discusses the factors affecting the customer experience when buying affordable luxury sports cars in Germany by identifying differences between first-time and experienced buyers. It emphasizes the need for the creation of two different customer journeys based on different customer experience clusters, a touchpoint analysis from the customer perspective identified differences in purchase stages, and staff behaviour and brand trust for customer satisfaction and brand identification.
Parteien streiten oft darüber, ob sich Käufer bei Mängeln der Kaufsache vom Vertrag lösen können. Der Verkäufer will das meistens verhindern: Fallen die Preise, kann sich der Käufer etwa nach dem Rücktritt die Ware am Markt preiswerter verschaffen. Die Ware ist dann zum ursprünglichen Preis nicht mehr handelbar. Steigen die Preise, droht zusätzlich eine Schadensersatzforderung: Der Käufer muss sich die Ware zu einemhöheren Preis bei einem anderen Verkäufer verschaffen. Auch können beim Verkäufer zusätzliche Kosten–etwa Transport-oder Lagerkosten–entstehen. Verkaufsbedingungen machen es dem Käufer deshalb besonders schwer, sich vom Vertrag zu lösen, während Einkaufsbedingungen daran nur geringe Anforderungen stellen.
Wer Ein- und Verkaufsbedingungen für das Auslandsgeschäft gestaltet, muss wissen, wo der Gesetzgeber der Gestaltungsfreiheit Grenzen gesetzt hat. Gelten BGB/HGB, lässt die deutsche Inhaltskontrolle überschaubare Spielräume, beim Rücktritts-recht des Käufers von den gesetzlichen Regeln abzuweichen. Weitgehend ungeklärt ist bislang, welche Vertragsaufhebungsklauseln in AGB wirksam sind, wenn UN-Kaufrecht gilt: Zwar kann sich in diesen Fällen die Inhaltskontrolle wegen Art. 4Satz 2 lit. a) CISG auch nach § 307 Abs. 1 BGB richten. Dann ist aber bei der Klauselkontrolle auch den Wertungen Rechnung zu tragen, die dem UN-Kaufrecht–und eben nicht dem BGB–zugrunde liegen und in dessen Bestimmungen ihren Niederschlag gefunden haben. Bei der Gestaltung von AGB kann dies Freiräume schaffen.
With the digital transformation, companies will experience a change that focuses on shaping the organization into an agile organizational form. In today's competitive and fast-moving business environment, it is necessary to react quickly to changing market conditions. Agility represents a promising option for overcoming these challenges. The path to an agile organization represents a development process that requires consideration of countless levels of the enterprise. This paper examines the impact of digital transformation on agile working practices and the benefits that can be achieved through technology. To enable a solution for today's so-called VUCA (Volatility, Uncertainty, Complexity und Ambiguity) world, agile ways of working can be applied project management requires adaptation. In the qualitative study, expert interviews were conducted and analyzed using the grounded theory method. As a result, a model can be presented that shows the influencing factors and potentials of agile management in the context of the digital transformation of medium-sized companies.
Providing a digital infrastructure, platform technologies foster interfirm collaboration between loosely coupled companies, enabling the formation of ecosystems and building the organizational structure for value co-creation. Despite the known potential, the development of platform ecosystems creates new sources of complexity and uncertainty due to the involvement of various independent actors. For a platform ecosystem to succeed, it is essential that the platform ecosystem participants are aligned, coordinated, and given a common direction. Traditionally, product roadmaps have served these purposes during product development. A systematic mapping study was conducted to better understand how product roadmapping could be used in the dynamic environment of platform ecosystems. One result of the study is that there are hardly any concrete approaches for product roadmapping in platform ecosystems so far. However, many challenges on the topic are described in the literature from different perspectives. Based on the results of the systematic mapping study, a research agenda for product roadmapping in platform ecosystems is derived and presented.
There is a growing consensus in research and practice that value-creating networks and ecosystems are supplementing the traditional distinction between the internal firm and market perspectives. To achieve joint value in ecosystems, it is crucial to align the various interests of independently acting ecosystem actors and create a common vision. In this paper, we argue that the ecosystem-wide use of product roadmaps may help with this. To get a better understanding of how roadmapping is conducted in the dynamic ecosystem environment, we systematize the main characteristics of product roadmaps and perform a conceptual comparison with the known challenges of ecosystem management. Comparing the two concepts of ecosystems and product roadmaps, we highlight the fit between the characteristics and objectives of the roadmaps and the challenges of ecosystem management. Hence, we propose to experiment with the ecosystem-wide use of product roadmaps as well as the empirical study of the challenges emerging in the process and the associated redesign of the roadmaps.
Allyls
(2022)
This chapter addresses the importance and usage of the commercially low-volume thermoset plastics group known as allyls. The three significant subelements of this group are poly(diallylphthalates), poly(diallylisophthalates), and poly(allyldiglycol carbonate). Chemistry, processing, and properties are also described. Allyl polymers are synthesized by radical polymerizations of allyl monomers that usually do not produce high-molecular-mass macromolecules. Therefore only a few specific monomers can produce thermosetting materials. Diallyldiglycolcarbonate (CR-39) and diallylphthalates are the most significant examples that have considerably improved our everyday life.
We propose a novel technique to compensate the effects of R-C / gm-C time-constant (TC) errors due to process variation in continuous-time delta-sigma modulators. Local TC error compensation factors are shifted around in the modulator loop to positions where they can be implemented efficiently with tunable circuit structures, such as current-steering digital-to-analog converters (DAC). This approach constitutes an alternative or supplement to existing compensation techniques, including capacitor or gm tuning. We apply the proposed technique to a third-order, single-bit, low-pass continuous-time delta-sigma modulator in cascaded integrator feedback structure. A feedback path tuning scheme is derived analytically and confirmed numerically using behavioral simulations. The modulator circuit was implemented in a 0.35-μm CMOS process using an active feedback coefficient tuning structure based on current-steering DACs. Post-layout simulations show that with this tuning structure, constant performance and stable operation can be obtained over a wide range of TC variation.
This study empirically analyzes and compares return data from developed and emerging market data based on the Fama French five-factor model and compares it to previous results from the Fama French three-factor model by Kostin, Runge and Adams (2021). It researches whether the addition of the profitability and investment pattern factors show superior results in the assessment of emerging markets during the COVID-19 pandemic compared to developed markets. We use panel data covering eight indices of developed and emerging countries as well as a selection of eight companies from these markets, covering a period from 2000 to 2020. Our findings suggest that emerging markets do not generally outperform developed markets. The results underscore the need to reconsider the assumption that adding more factors to regression models automatically yields results that are more reliable. Our study contributes to the extant literature by broadening this research area. It is the first study to compare the performance of the Fama French three-factor model and the Fama French five-factor model in the cost of equity calculation for developed and emerging countries during the COVID-19 pandemic and other crisis events of the past two decades.
The global demand for resources such as energy, land, or water is constantly increasing. It is therefore not sur- prising that research on the Food-Energy-Water (FEW) nexus has become a scientific as well as a general focus in recent years. A significant increase in publications since 2015 can be observed, and it can be expected that this trend will continue. A multilevel (macro, meso, and micro) perspective is essential, as the FEW nexus has cross- sectoral interdependencies. Several review studies on the FEW nexus can be found in the literature, in general, it can be concluded that the FEW nexus is a multi-disciplinary and complex topic. The studies examined identify essential fields of action for research, policy, and society. However, questions such as what are the main research fields at each level? Is it possible to divide the research into specific clusters? and do the clusters correlate with the levels, and what are the methods of modeling used in the clusters and levels? are still not fully discussed in the literature. An extensive literature review was conducted to get insight into the existing research areas. Especially in such fields as the FEW nexus, the amount of literature can get huge, and a human could get lost analyzing the literature manually. For that, we created word clouds and performed a cluster- and network-analysis to support the selection of most relevant papers for a detailed reading. In 2021, the most publications were published, with 173 publications, which corresponds to a share of 26.6 %. There has been a significant increase since 2015, and it can be expected that this trend will continue in the coming years. Most of the first authors come from the USA (25.4 %), followed by China with 22.4 %. From the word cloud and the top 20 words, which appear in the title and abstract, it can be deduced that the topic water is the most represented. However, the terms system, resource, model, study, change, development, and management also appear to be very important, which indi- cates the importance of a holistic approach to the topic. In total 9 clusters could be identified at the different levels. It can be seen that three clusters form well. For the others, a rather diffuse picture can be observed. In order to find out which topics are hidden behind the individual clusters, 6 publications from each cluster were subjected to a more detailed examination. With these steps, a number of 54 publications were identified for de- tailed consideration. The modeling approaches that are currently being applied in research can be classified into domain-specific tools (e. g. global water models, crop models or global climate models) and into more general tools to perform for example a life cycle analysis, spatial analysis using geographic information system, or system dynamics for a general understanding of the links between the domains. With the domain-specific tools, detailed research questions can be addressed to answer questions for a specific domain. However, these tools have the disadvantage that especially the links between the sectors food, energy, and water are not fully considered. Many implementations that are made today are at lowest level (micro) relate to bounded spatial areas and are derived from macro and meso level goals.
An empirical study on management accountants’ roles and role perceptions: a German perspective
(2022)
The ongoing discussion on roles of management accountants (MAs) leads often to perceive the business partner (BP) role as the role of choice. Yet, many scholars and practitioners seem to assume that this role is clear to managers and MAs, that it makes sense for them and that all managers and MAs agree on it and implement it. Inconsistencies between actual roles, perceived, and expected roles might cause identity and role conflicts. However, we lack evidence of whether managers and MAs perceive, expect and act in the BP role and if tensions and conflicts might exist. This paper is based on a quantitative empirical study of a large German high-tech firm in 2019 whose top management decided to implement the BP role. We found several areas of tension in this role discussion and contribute to the literature on MAs’ roles with a more nuanced view of the interaction between managers and MAs regarding MAs’ roles. The study shows that there are mainly differences in business managers’ expectations of MAs to the role of the BP, which the MAs do not know exactly how to fulfill.
For a long time, most discrete accelerators have been attached to host systems using various generations of the PCI Express interface. However, with its lack of support for coherency between accelerator and host caches, fine-grained interactions require frequent cache-flushes, or even the use of inefficient uncached memory regions. The Cache Coherent Interconnect for Accelerators (CCIX) was the first multi-vendor standard for enabling cache-coherent host-accelerator attachments, and already is indicative of the capabilities of upcoming standards such as Compute Express Link (CXL). In our work, we compare and contrast the use of CCIX with PCIe when interfacing an ARM-based host with two generations of CCIX-enabled FPGAs. We provide both low-level throughput and latency measurements for accesses and address translation, as well as examine an application-level use-case of using CCIX for fine-grained synchronization in an FPGA-accelerated database system. We can show that especially smaller reads from the FPGA to the host can benefit from CCIX by having roughly 33% shorter latency than PCIe. Small writes to the host have a latency roughly 32% higher than PCIe, though, since they carry a higher coherency overhead. For the database use-case, the use of CCIX allowed to maintain a constant synchronization latency even with heavy host-FPGA parallelism.
This paper presents a compact four-arm spiral antenna, which may be used in direction-finding applications but also mobile communication systems. The antenna is fed sequentially at its outside-ends using a sequential phase network embedded in grounded multilayer dielectric media. Sequential rotation is applied to generate the axial mode M1 but also the conical mode M2 in the same frequency band. The antenna exhibits good radiation characteristics in the frequency band of interest.
Data analysis is becoming increasingly important to pursue organizational goals, especially in the context of Industry 4.0, where a wide variety of data is available. Here numerous challenges arise, especially when using unstructured data. However, this subject has not been focused by research so far. This research paper addresses this gap, which is interesting for science and practice as well. In a study three major challenges of using unstructured data has been identified: analytical know-how, data issues, variety. Additionally, measures how to improve the analysis of unstructured data in the industry 4.0 context are described. Therefore, the paper provides empirical insights about challenges and potential measures when analyzing unstructured data. The findings are presented in a framework, too. Hence, next steps of the research project and future research points become apparent.
Wollen Unternehmen sozial und ökologisch nachhaltiger werden, beginnt es meistens mit Ankündigungen: Wir werden mehr Mitarbeiter dazu bewegen, mit dem Fahrrad zu kommen! Wir schaffen die Currywurst in der Kantine ab! Wir werden benachteilige Jugendliche stärker fördern! Solche Ankündigungen werden in der Forschung zu Environment, Social und Governance (ESG) als „Aspirational Talk“ bezeichnet. Sie zeigen den Anspruch eines Unternehmens auf: „Wir erkennen die Herausforderungen an und wollen sie meistern.“ Den Ankündigungen sollten dann freilich Taten folgen. Was aber passiert, wenn die Mitarbeiter zwischen dem, was angekündigt wurde, und dem, was gemacht wird, eine Lücke wahrnehmen?
Today many scientific works are using deep learning algorithms and time series, which can detect physiological events of interest. In sleep medicine, this is particularly relevant in detecting sleep apnea, specifically in detecting obstructive sleep apnea events. Deep learning algorithms with different architectures are used to achieve decent results in accuracy, sensitivity, etc. Although there are models that can reliably determine apnea and hypopnea events, another essential aspect to consider is the explainability of these models, i.e., why a model makes a particular decision. Another critical factor is how these deep learning models determine how severe obstructive sleep apnea is in patients based on the apnea-hypopnea index (AHI). Deep learning models trained by two approaches for AHI determination are exposed in this work. Approaches vary depending on the data format the models are fed: full-time series and window-based time series.
Literature reviews are essential for any scientific work, both as part of a dissertation or as a stand-alone work. Scientists benefit from the fact that more and more literature is available in electronic form, and finding and accessing relevant literature has become more accessible through scientific databases. However, a traditional literature review method is characterized by a highly manual process, while technologies and methods in big data, machine learning, and text mining have advanced. Especially in areas where research streams are rapidly evolving, and topics are becoming more comprehensive, complex, and heterogeneous, it is challenging to provide a holistic overview and identify research gaps manually. Therefore, we have developed a framework that supports the traditional approach of conducting a literature review using machine learning and text mining methods. The framework is particularly suitable in cases where a large amount of literature is available, and a holistic understanding of the research area is needed. The framework consists of several steps in which the critical mind of the scientist is supported by machine learning. The unstructured text data is transformed into a structured form through data preparation realized with text mining, making it applicable for various machine learning techniques. A concrete example in the field of smart cities makes the framework tangible.
The early involvement of experiences gained through intelligence and data analysis is becoming increasingly important in order to develop new products, leading to a completely different conception of product creation, development and engineering processes using the advantages that the dedication of the digital twin entails. Introducing a novel stage gate process in order to be holistically anchored in learning factories adopting idea generation and idea screening in an early stage, beta testing of first prototypes, technical implementation in real production scenarios, business analysis, market evaluation, pricing, service models as well as innovative social media portals. Corresponding product modelling in the sense of sustainability, circular economy, and data analytics forecasts the product on the market both before and after market launch with the interlinking of data interpretation nearby in real-time. The digital twin represents the link between the digital model and the digital shadow. Additionally, the connection of the digital twin with the product provides constantly updated operating status and process data as well as mapping of technical properties and real-world behaviours. A future-networking product, by embedded information technology with the ability to initiate and carry out one's own further development, is able to interact with people and environments and thus is relevant to the way of life of future generations. In today's development work for this new product creation approach, on one hand, "Werk150" is the object of the development itself and on the other hand the validation environment. In the next step, new learning modules and scenarios for trainings at master level will be derived from these findings.
Addressing the high complexity of brand image measurement, the present research paper investigates the use of artificial neural networks in this particular application context. Since profound insights into the image of a brand are essential for management, the deployment of this learning algorithm is considered as it allows modeling of complex non-linear and multilayered relationships. The conceptual approach presented in the paper is illustrated with the empirical example of the sportswear manufacturer adidas. By using quantitative survey data, a multilayer artificial neural network is created to link the evaluations of specific brand attributes with the overall evaluation of the brand. Based on an analysis of the connection weights between neurons of the artificial neural network, the importance of different brand attributes for the brand evaluation is quantified. This results in concrete implications for brand management practice and potential for further investigations on the use of artificial intelligence in marketing analytics.
Demand forecasting intermittent time series is a challenging business problem. Companies have difficulties in forecasting this particular form of demand pattern. On the one hand, it is characterized by many non-demand periods and therefore classical statistical forecasting algorithms, such as ARIMA, only work to a limited extent. On the other hand, companies often cannot meet the requirements for good forecasting models, such as providing sufficient training data. The recent major advances of artificial intelligence in applications are largely based on transfer learning. In this paper, we investigate whether this method, originating from computer vision, can improve the forecasting quality of intermittent demand time series using deep learning models. Our empirical results show that, in total, transfer learning can reduce the mean square error by 65 percent. We also show that especially short (65 percent reduction) and medium long (91 percent reduction) time series benefit from this approach.
Physicians in interventional radiology are exposed to high physical stress. To avoid negative long-term effects resulting from unergonomic working conditions, we demonstrated the feasibility of a system that gives feedback about unergonomic
situations arising during the intervention based on the Azure Kinect camera. The overall feasibility of the approach could be shown.
Home health applications have evolved over the last few decades. Assistive systems such as a data platform in connection with health devices can allow for health-related data to be automatically transmitted to a database. However, there remain significant challenges concerning intermodular communication. Central among them is the challenge of achieving interoperability, the ability of devices to communicate and share data with each other. A major goal of this project was to extend an existing data platform (COMES®) and establish working interoperability by connecting assistive devices with differing approaches. We describe this process for a sleep monitoring and a physical exercise device. Furthermore, we aimed to test this setup and the implementation with a data platform in both a laboratory and an in-home setting with 11 elderly participants. The platform modification was realized, and the relevant changes were made so that the incoming data could be processed by the data platform, as well as visually displayed in real-time. Data was recorded by the respective device and transmitted into the data server with minor disruptions. Our observations affirmed that difficulties and data loss are far more likely to occur with increasing technical complexity, in the event of instable internet connection, or when the device setup requires (elderly) subjects to take specific steps for proper functioning. We emphasize the importance for tests and evaluations of home health technologies in real-life circumstances.
Im Kampf gegen die Ausbreitung des Corona-Virus waren flächendeckende Schulschließungen seit Ausbruch der Pandemie eine zentrale politische Maßnahme. Infolgedessen kam es zu erheblichen Lernzeiteinbußen unter allen Schüler*innen, worunter insbesondere Kinder und Jugendliche aus benachteiligten Verhältnissen immer noch leiden. Über die Auswirkungen der Corona-Pandemie auf das deutsche Bildungssystem wird diskutiert und Maßnahmen zu deren Eindämmung aufgesetzt.
Ausbildung in der Akustik
(2022)
Die Wissenschaft der Akustik mit ihrer Vielfallt und Interdisziplinarität bietet hervorragende Möglichkeiten an beruflichen Betätigungsfeldern und hat viele von uns in ihren Bann gezogen. Ausbildung in der Akustik bedeutet mehr als Studierenden nur Wissen und Fähigkeiten zu vermitteln. Eigentlich ist nach dem Studium auch der Lernprozess nicht abgeschlossen, sondern wie viele Akustiker:innen meinen, fängt dieser erst dann richtig an. Um eine sehr gute Ausbildung zu gestalten, bedarf es neben Vorbildern an Personen auch Lehrformate, Methoden und Tools. Die folgenden sechs Kurzbeiträge sind Beispiele gelungener Maßnahmen in der Ausbildung der Akustik und sollen anregen, die Qualität in der Lehre stetig zu verbessern.
Switched reluctance motors are particularly attractive due to their simple structure. The control of this machine type requires the instants, to switch the currents in the motor phases in an appropriate sequence. These switching instants are determined either based on a position sensor, or on signals generated by a sensorless method. A very simple sensorless method uses the switching frequency of the hysteresis controllers used for phase current control. This paper first presents an automatic commissioning method for this sensorless method and second a startup procedure, thus enhancing this approach towards an application in industry.
According to several surveys and statistics, the great majority of companies previously not accustomed to automation are piloting solutions to automate business processes. Those accustomed to automation also attempt to introduce more of it, focusing on automation-unfriendly processes that remained manual. However, when the decision on what and whether to automate is not trivial for evident reasons, even industry leaders may get stuck on an overwhelming question: where to begin automating? The question remains too often unanswered as state-of-the-art methods fail to consider the whole picture. This paper introduces a holistic approach to the decision-making for investments in automation. The method supports the iterative analysis and evaluation of operative processes, providing tools for a quantitative approach to the decision-making. Thanks to the method, a large pool of processes can be first considered and then filtered out in order to select the one that yields the best value for the automation in the specific context. After introducing the method, a case study is reported for validation before the discussion.
Due to the growing importance of videos for B2B sales outreach, this study proposes an extended model based on the Corporate-Video Model by Büsching and Meidel (2016) and a qualitative survey with high-ranking company representatives. The findings comprise seven complementary categories: structure, communication, product display, information content, unique selling proposition, value-based selling, and dramaturgy of product videos. The model extension aids practitioners in analyzing and conceptualizing compelling B2B product videos.
Die bedarfsgerechte Steuerung dezentraler thermischer Energiesysteme, wie Kraft-Wärme-Kopplungs- (KWK-) Anlagen und Wärmepumpen, kann einen entscheidenden Beitrag zur Deckung bzw. Reduktion der Residuallast leisten und so für eine Verringerung der konventionellen Reststromversorgung und den damit einhergehenden Treibhausgasemissionen sorgen. Dafür wurde an der Hochschule Reutlingen in mehrjähriger Forschungsarbeit ein prognosebasierter Steuerungsalgorithmus entwickelt. Gegenstand dieses Beitrags bilden neben der Vorstellung eben jenes Steuerungsalgorithmus auch dessen praktische Umsetzungsvarianten: Eine auf einer speicherprogrammierbaren Steuerung (SPS) rein lokal ausführbare Version sowie eine Webservice-Anwendung für den parallelen Betrieb mehrerer Anlagen – ausgehend von einem zentralen Server. Erprobungen am KWK-Prüfstand der Hochschule Reutlingen bestätigen die zuverlässige Funktionsweise des Algorithmus in den verschiedenen Umsetzungsvarianten. Gleichzeitig wird der Vorteil der bedarfsgerechten Steuerung gegenüber dem, insbesondere im Mikro-KWK-Bereich standardmäßig vorliegenden, wärmegeführten Betrieb in Form einer Steigerung der Eigenstromdeckung von bis zu 27 % aufgezeigt. Neben der bedarfsgerechten Steuerung bedient der entwickelte Algorithmus zudem noch ein weiteres Anwendungsgebiet: Den vorhersagbaren KWK-Betrieb, der beispielsweise in Form täglicher Einspeiseprognose im Rahmen des Redispatch 2.0 eingefordert wird. Die Vorhersage des KWK-Betriebs ist dabei auf zwei Weisen möglich: Als erste Option kann der wärmegeführte Betrieb direkt über den Algorithmus abgebildet und prognostiziert werden. Eine andere Möglichkeit stellt wiederum die bedarfsgerechte Steuerung der Anlage dar; der berechnete optimale Fahrplan entspricht dabei gleichzeitig der Betriebsprognose des KWK-Geräts. Damit ist der entwickelte Steuerungsalgorithmus in der Lage, auf unterschiedliche Weisen zum Gelingen der Energiewende beizutragen.
Job advertisements are important means of communicating role expectations for management accountants to the labor market. They provide information about which roles of management accountants are sought by companies or which roles are expected. However, which roles are communicated in job advertisements is unknown so far. Using a large sample of 889 job ads and a text-mining approach, we show an apparent mix of different role types with a strong focus on a rather classic role: the watchdog role. However, individuals with business partner characteristics are more often sought for leadership positions or in family businesses and small and medium-sized enterprises (SMEs). The results challenge the current role discussion for management accountants as business partners in practice and some academic fields.
Adipose tissue is related to the development and manifestation of multiple diseases, demonstrating the importance of suitable in vitro models for research purposes. In this study, adipose tissue lobuli were explanted, cultured, and used as an adipose tissue control to evaluate in vitro generated adipose tissue models. During culture, lobule exhibited a stable weight, lactate dehydrogenase, and glycerol release over 15 days. For building up in vitro adipose tissue models, we adapted the biomaterial gelatin methacryloyl (GelMA) composition and handling to homogeneously mix and bioprint human primary mature adipocytes (MA) and adipose-derived stem cells (ASCs), respectively. Accelerated cooling of the bioink turned out to be essential for the homogeneous distribution of lipid-filled MAs in the hydrogel. Last, we compared manual and bioprinted GelMA hydrogels with MA or ASCs and the explanted lobules to evaluate the impact of the printing process and rate the models concerning the physiological reference. The viability analyses demonstrated no significant difference between the groups due to additive manufacturing. The staining of intracellular lipids and perilipin A suggest that GelMA is well suited for ASCs and MA. Therefore, we successfully constructed physiological in vitro models by bioprinting MA-containing GelMA bioinks.
For some time now, eSports has complemented the portfolio of many sponsors in sports. Though partnerships with important organizations, brands are gaining a foothold in the eSports landscape. While the communication work with media and fans in the framework of conventional sports has been tried and tested for many years, Public Relations (PR) in eSports is new for companies. The paper examines the requirements of PR in eSports. These are identified by analyzing a quantitative survey among eSports fans. The results prove the existance of significant differences in the requirements of successful PR in eSports. The differences are mainly based on the different target groups and their media usage behavoir. Classic formats such as TV or print are ignored by eSport fans. This influences the choice of media partners for sponsors. Successful PR in eSports requires patience and long-term planning. It is important to maintain a close exchange with partners in order to jointly design attractive formats for media and their consumers.
The energy turnaround, digitalization and decreasing revenues forces enterprises in the energy domain to develop new business models. Following a Design Science Research approach, we showed in two action research projects that businesses models in the energy domain result in complex ecosystems with multiple actors. Additionally, we identified that municipal utilities have problems with the systematic development of business models. In order to solve the problem, we captured together with the partners of the enterprises the requirements in a second phase. Further we developed a method which consist of the following components: Method for the creative development of a new business model in form of a Business Model Canvas (BMC). A mapping between the e3Value ontology and the BMC for modelling a business ecosystem. The Business Model Configurator (BMConfig) prototype for modelling and simulating the e3Value-Ontology. The Business model can be quantified and analyzed for its viability. We demonstrate the feasibility of our approach in business model of a power community.
Even though near-data processing (NDP) can provably reduce data transfers and increase performance, current NDP is solely utilized in read-only settings. Slow or tedious to implement synchronization and invalidation mechanisms between host and smart storage make NDP support for data-intensive update operations difficult. In this paper, we introduce a low-latency cache-coherent shared lock table for update NDP settings in disaggregated memory environments. It utilizes the novel CCIX interconnect technology and is integrated in neoDBMS, a near-data processing DBMS for smart storage. Our evaluation indicates end-to-end lock latencies of ∼80-100ns and robust performance under contention.
We study whether compulsory religious education in schools affects students' religiosity as adults. We exploit the staggered termination of compulsory religious education across German states in models with state and cohort fixed effects. Using three different datasets, we find that abolishing compulsory religious education significantly reduced religiosity of affected students in adulthood. It also reduced the religious actions of personal prayer, church-going, and church membership. Beyond religious attitudes, the reform led to more equalized gender roles, fewer marriages and children, and higher labor-market participation and earnings. The reform did not affect ethical and political values or non-religious school outcomes.