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Motto der Herbstkonferenz Informatics Inside 2020 ist KInside. Wieder einmal blicken Studierende inside und schauen sich Methoden, Anwendungen und Zusammenhänge genauer an. Die Beiträge sind vielfältig und entsprechend dem Studiengang human-centered. Es ist der Anspruch, dass sich die Themen um die Bedürfnisse der Menschen drehen und eingesetzte Methoden kein Selbstzweck sind, sondern am Nutzen für den Menschen gemessen werden.
Steady state efficiency optimization techniques for induction motors are state of the art and various methods have already been developed. This paper provides new insights in the efficiency optimized operation in dynamic regime. The paper proposes an anticipative flux modification in order to decrease losses during torque and speed transients. These trajectories are analyzed based on a numerical study for different motors. Measurement results for one motor are given as well.
Sol-Gel basierte Flammschutzmittel stellen einen vielversprechenden Ansatz für Textilien dar, gerade im Bereich des Ersatzes von derzeit etablierten halogenhaltigen Flammschutzmitteln. Letztere sind aufgrund ihrer toxikologisch Bedenklichkeit sowie ihrer mitunter bioakkumulierenden Eigenschaften in die Kritik geraten. In diesem Forschungsvorhaben wurde daher untersucht auf welche Weise ein Flammschutz per Sol-Gel-Ansatz auf Stickstoff- und/oder Phosphorbasis als halogenfreie Alternative verwirklicht werden kann. Die Sol-Gel-Schicht fungierte dabei zum einen als nicht brennbarer Binder, zum anderen konnten über das Einführen entsprechender funktioneller Seitenketten für den Flammschutz aktive Gruppen direkt mit eingebunden werden. Verschiedene Ansätze wurden dabei verfolgt. Vor allem durch die Nutzung von additivierten Systemen, d.h. durch Sol-Gel-Schichten mit Zusätzen von stickstoff- und/oder phosphorhaltigen Verbindungen konnte ein Flammschutz nach DIN EN ISO 15025 (Schutzkleidung – Schutz gegen Hitze und Flammen) erhalten werden. Anhand eines Modellsystems, bei dem in zwei aufeinanderfolgenden Schritten zuerst eine funktionalisierte Sol-Gel-Schicht und anschließend eine Phosphorverbindung in einem zweiten Schritt aufgebracht wurde, konnten die Vorteile des Flammschutzes auf Sol-Gel-Basis nachgewiesen werden. Dabei wurde unter anderem auch gezeigt, dass ein Mechanismus auf Basis der Bildung einer Schutzschicht hauptsächlich verantwortlich für den Flammschutz ist. Dieses Ergebnis ist für eine zukünftige, weitere Optimierung entsprechender Ausrüstungen nicht zu unterschätzen. Durch Ausrüstungsversuche im semi-industriellen Maßstab konnte weiterhin gezeigt werden, dass einer großtechnischen Umsetzung der angewandten Ausrüstungen prinzipiell nichts im Wege steht. Abstriche müssen bis dato lediglich bezüglich der Waschstabilität gemacht werden. Die Sol-Gel-Schichten überstanden zwar im allgemeinen typische Waschprozesse, eine Permanenz der Flammfestigkeit von additivierten Systemen ergab sich aber nur in einzelnen Fällen. Ausgehend von den Ergebnissen wurde ein neuer Ansatz vorgestellt, der über den hier zugrundeliegenden Ansatz hinausgeht. Dieser sieht vor, durch den Einsatz von neu-synthetisierten Silanen mit Stickstoff- und Phosphorgruppen Sol-Gel-Schichten herzustellen, die ein vielversprechendes Verhalten zeigen. Hier konnte auch nach ersten Waschtests eine Aufrechterhaltung der verbesserten Flammfestigkeit nachgewiesen werden. Insgesamt konnte innerhalb des Forschungsvorhabens gezeigt werden, dass ein Flammschutz auf Sol-Gel-Basis für Textilien erhalten werden kann. Darüberhinaus konnte auch erklärt werden auf welchem Mechanismus dieser Flammschutz begründet ist und wie die derzeit noch ungenügende Waschpermanenz verbessert werden kann.
Driven by digital transformation, manufacturing systems are heading towards autonomy. The implementation of autonomous elements in manufacturing systems is still a big challenge. Especially small and medium sized enterprises (SME) often lack experience to assess the degree of Autonomous Production. Therefore, a description model for the assessment of stages for Autonomous Production has been identified as a core element to support such a transformation process. In contrast to existing models, the developed SME-tailored model comprises different levels within a manufacturing system, from single manufacturing cells to the factory level. Furthermore, the model has been validated in several case studies.
Process quality has reached a high level on mass production, utilizing well known methods like the DoE. The drawback of the unterlying statistical methods is the need for tests under real production conditions, which cause high costs due to the lost output. Research over the last decade let to methods for correcting a process by using in-situ data to correct the process parameters, but still a lot of pre-production is necessary to get this working. This paper presents a new approach in improving the product quality in process chains by using context data - which in part are gathered by using Industry 4.0 devices - to reduce the necessary pre-production.
In recent years, machine learning algorithms have made a huge development in performance and applicability in industry and especially maintenance. Their application enables predictive maintenance and thus offers efficiency increases. However, a successful implementation of such solutions still requires high effort in data preparation to obtain the right information, interdisciplinarity in teams as well as a good communication to employees. Here, small and medium sized enterprises (SME) often lack in experience, competence and capacity. This paper presents a systematic and practice-oriented method for an implementation of machine learning solutions for predictive maintenance in SME, which has already been validated.
The chemical synthesis of polysiloxanes from monomeric starting materials involves a series of hydrolysis, condensation and modification reactions with complex monomeric and oligomeric reaction mixtures. Real-time monitoring and precise process control of the synthesis process is of great importance to ensure reproducible intermediates and products and can readily be performed by optical spectroscopy. In chemical reactions involving rapid and simultaneous functional group transformations and complex reaction mixtures, however, the spectroscopic signals are often ambiguous due to overlapping bands, shifting peaks and changing baselines. The univariate analysis of individual absorbance signals is hence often only of limited use. In contrast, batch modelling based on the multivariate analysis of the time course of principal components (PCs) derived from the reaction spectra provides a more efficient tool for real time monitoring. In batch modelling, not only single absorbance bands are used but information over a broad range of wavelengths is extracted from the evolving spectral fingerprints and used for analysis. Thereby, process control can be based on numerous chemical and morphological changes taking place during synthesis. “Bad” (or abnormal) batches can quickly be distinguished from “normal” ones by comparing the respective reaction trajectories in real time. In this work, FTIR spectroscopy was combined with multivariate data analysis for the in-line process characterization and batch modelling of polysiloxane formation. The synthesis was conducted under different starting conditions using various reactant concentrations. The complex spectral information was evaluated using chemometrics (principal component analysis, PCA). Specific spectral features at different stages of the reaction were assigned to the corresponding reaction steps. Reaction trajectories were derived based on batch modelling using a wide range of wavelengths. Subsequently, complexity was reduced again to the most relevant absorbance signals in order to derive a concept for a low-cost process spectroscopic set-up which could be used for real-time process monitoring and reaction control.
Der Anspruch an Energieversorger wird wachsen: in Zukunft gewinnen vor allem Aufgaben wie die Entwicklung digitalisierter Produkte/Dienstleistungen sowie ökologische Aktivitäten an Relevanz. Dies zeigt die Hochschule Reutlingen in ihrer aktuellen Untersuchung unter Aufsichtsräten, Geschäftsführern und Führungskräften. Trotz der erwarteten Veränderungen: die Aufsichtsräte sind sich zwar ihrem Druck zu mehr Professionalisierung bewusst, scheinen aktuell aber nur mäßig für die künftigen Herausforderungen des Unternehmens gerüstet. Besonders relevant dabei: die Professionalisierung der Gremienarbeit in kommunalen EVU ermöglicht einen höheren wahrgenommenen Unternehmenserfolg. So die Studie des Reutlinger Energiezentrums and der Hochschule Reutlingen im Auftrag von fünf Unternehmen der Branche.
Despite strong political efforts in Europe, industrial small- and medium sized enterprises (SMEs) seem to neglect adopting practices for energy effciency. By taking a cultural perspective, this study investigated what drives the establishment of energy effciency and corresponding practices in SMEs. Based on 10 ethnographic case studies and a quantitative survey among 500 manufacturing SMEs, the results indicate the importance of everyday employee behavior in achieving energy savings. The studied enterprises value behavior related measures as similarly important as technical measures. Raising awareness for energy issues within the organization, therefore, constitutes an essential leadership task that is oftentimes perceived as challenging and frustrating. It was concluded that the embedding of energy efficiency in corporate strategy, the use of a broad spectrum of different practices, and the empowerment and involvement of employees serve as major drivers in establishing energy effciency within SMEs. Moreover, the findings reveal institutional influences on shaping the meanings of energy effciency for the SMEs by raising attention for energy effciency in the enterprises and making energy effciency decisions more likely. The main contribution of the paper is to offer an alternative perspective on energy effciency in SMEs beyond the mere adoption of energy-effcient technology.
nKV in action: accelerating KVstores on native computational storage with NearData processing
(2020)
Massive data transfers in modern data intensive systems resulting from low data-locality and data-to-code system design hurt their performance and scalability. Near-data processing (NDP) designs represent a feasible solution, which although not new, has yet to see widespread use.
In this paper we demonstrate various NDP alternatives in nKV, which is a key/value store utilizing native computational storage and near-data processing. We showcase the execution of classical operations (GET, SCAN) and complex graph-processing algorithms (Betweenness Centrality) in-situ, with 1.4x-2.7x better performance due to NDP. nKV runs on real hardware - the COSMOS+ platform.
Massive data transfers in modern key/value stores resulting from low data-locality and data-to-code system design hurt their performance and scalability. Near-data processing (NDP) designs represent a feasible solution, which although not new, have yet to see widespread use.
In this paper we introduce nKV, which is a key/value store utilizing native computational storage and near-data processing. On the one hand, nKV can directly control the data and computation placement on the underlying storage hardware. On the other hand, nKV propagates the data formats and layouts to the storage device where, software and hardware parsers and accessors are implemented. Both allow NDP operations to execute in host-intervention-free manner, directly on physical addresses and thus better utilize the underlying hardware. Our performance evaluation is based on executing traditional KV operations (GET, SCAN) and on complex graph-processing algorithms (Betweenness Centrality) in-situ, with 1.4×-2.7× better performance on real hardware – the COSMOS+ platform.
Massive data transfers in modern data intensive systems resulting from low data-locality and data-to-code system design hurt their performance and scalability. Near-data processing (NDP) and a shift to code-to-data designs may represent a viable solution as packaging combinations of storage and compute elements on the same device has become viable.
The shift towards NDP system architectures calls for revision of established principles. Abstractions such as data formats and layouts typically spread multiple layers in traditional DBMS, the way they are processed is encapsulated within these layers of abstraction. The NDP-style processing requires an explicit definition of cross-layer data formats and accessors to ensure in-situ executions optimally utilizing the properties of the underlying NDP storage and compute elements. In this paper, we make the case for such data format definitions and investigate the performance benefits under NoFTL-KV and the COSMOS hardware platform.
The tale of 1000 cores: an evaluation of concurrency control on real(ly) large multi-socket hardware
(2020)
In this paper, we set out the goal to revisit the results of “Starring into the Abyss [...] of Concurrency Control with [1000] Cores” and analyse in-memory DBMSs on today’s large hardware. Despite the original assumption of the authors, today we do not see single-socket CPUs with 1000 cores. Instead multi-socket hardware made its way into production data centres. Hence, we follow up on this prior work with an evaluation of the characteristics of concurrency control schemes on real production multi-socket hardware with 1568 cores. To our surprise, we made several interesting findings which we report on in this paper.
In this paper, we present a new approach for achieving robust performance of data structures making it easier to reuse the same design for different hardware generations but also for different workloads. To achieve robust performance, the main idea is to strictly separate the data structure design from the actual strategies to execute access operations and adjust the actual execution strategies by means of so-called configurations instead of hard-wiring the execution strategy into the data structure. In our evaluation we demonstrate the benefits of this configuration approach for individual data structures as well as complex OLTP workloads.
Modern mixed (HTAP)workloads execute fast update-transactions and long running analytical queries on the same dataset and system. In multi-version (MVCC) systems, such workloads result in many short-lived versions and long version-chains as well as in increased and frequent maintenance overhead.
Consequently, the index pressure increases significantly. Firstly, the frequent modifications cause frequent creation of new versions, yielding a surge in index maintenance overhead. Secondly and more importantly, index-scans incur extra I/O overhead to determine, which of the resulting tuple versions are visible to the executing transaction (visibility-check) as current designs only store version/timestamp information in the base table – not in the index. Such index-only visibility-check is critical for HTAP workloads on large datasets.
In this paper we propose the Multi Version Partitioned B-Tree (MV-PBT) as a version-aware index structure, supporting index-only visibility checks and flash-friendly I/O patterns. The experimental evaluation indicates a 2x improvement for analytical queries and 15% higher transactional throughput under HTAP workloads. MV-PBT offers 40% higher tx. throughput compared to WiredTiger’s LSM-Tree implementation under YCSB.
Customer orientation should be the core engine of every organisation while IT can be considered as the enabler to generate competitive advantages along customer processes in marketing, sales and service. Research shows that customer relationship management (CRM) enables organisations to perform better and experience indicates that organisations that focus on customer orientation are more successful. With marketplace organisations such as Amazon, Alibaba or Conrad shaping the future of customer centricity and information technology, German B2B organisations need to shift their value contribution from product-centric to customer-centric. While these organisations are currently attempting to implement CRM software and putting their customers more into focus, the question remains how organisations are approaching the implementation of CRM and whether these attempts are paying off in terms of business performance.
Here, we study resin cure and network formation of solid melamine formaldehyde pre-polymer over a large temperature range viadynamic temperature curing profiles. Real-time infrared spectroscopy is used to analyze the chemical changes during network formation and network hardening. By applying chemometrics (multivariate curve resolution,MCR), the essential chemical functionalities that constitute the network at a given stage of curing are mathematically extracted and tracked over time. The three spectral components identified by MCR were methylol-rich, ether linkages-rich and methylene linkages-rich resin entities. Based on dynamic changes of their characteristic spectral patterns in dependence of temperature, curing is divided into five phases: (I) stationary phase with free methylols as main chemical feature, (II) formation of flexible network cross-linked by ether linkages, (III) formation of rigid, ether-cross-linked network, (IV) further hardening via transformation of methylols and ethers into methylene-cross-linkages, and (V) network consolidation via transformation of ether into methylene bridges. The presented spectroscopic/chemometric approach can be used as methodological basis for the functionality design of MF-based surface films at the stage of laminate pressing, i.e., for tailoring the technological property profile of cured MF films using a causal understanding of the underlying chemistry based on molecular markers and spectroscopic fingerprints.
Dieser Beitrag gibt einen Überblick über die verschiedenen Möglichkeiten der Bilanzierung einens Initial Coin Offerings (ICO) beim Emittenten auf der Passivseite nach den Regelungen der IFRS. Ziel ist es, die bilanzielle Einordnung anhand verschiedenenr Arten von Token zu erörtern und den Emittenten bei der Ausgestaltung der Token sowie der anschließenden Bilanzierung zu unterstützen. Die Ergebnisse zeigen, dass die Standards für die bilanzielle Einordnung von ICO-Token zwar ausreichen, allerdings eine große Bandbreite der Bilanzierung zu berücksichtigen ist und eine detaillierte Regelung durch einen eigenen IFRS daher schwierig erscheint.
Das Value-Engineering in der Kundenkommunikation ist eine strukturierte Methode, Kommunikationsprozesse zwischen Unternehmen zu verbessern. Das Konzept greift bewährte Elemente der technischen Wertanalyse und der Gemeinkosten-Wertanalyse auf und überträgt sie auf die Kundenkommunikation. Der Ansatz bietet eine systematische Vorgehensweise, Kommunikationsprozesse zwischen Anbieter und Kunde zu durchleuchten und neu zu gestalten. Value-Engineering in der Kundenkommunikation schafft somit Wettbewerbsvorteile durch eine Optimierung der Kommunikation.
The article studies a novel approach of inflation modeling in economics. We utilize a stochastic differential equation (SDE) of the form dXt=aXtdt+bXtdBtH, where dBtH is a fractional Brownian motion in order to model inflationary dynamics. Standard economic models do not capture the stochastic nature of inflation in the Eurozone. Thus, we develop a new stochastic approach and take into consideration fractional Brownian motions as well as Lévy processes. The benefits of those stochastic processes are the modeling of interdependence and jumps, which is equally confirmed by empirical inflation data. The article defines and introduces the rules for stochastic and fractional processes and elucidates the stochastic simulation output.
Resilienz und Stabilität? Weichenstellungen im Banken- und Finanzsystem in der Corona-Pandemie
(2020)
Seit der globalen Finanzkrise 2008/2009 hat es keine vergleichbare Herausforderung wie die Corona-Krise für das Finanz- und Bankensystem mehr gegeben.
Schwache Profitabilität, ungelöste Regulierungs-herausforderungen und steigende Konkurrenz im Digitalbereich stellen die Banken vor weitere Heraus-forderungen.
Die Stabilität des Finanzsystems und der Zugang zu den Finanzmärkten war während der Pandemie nicht gefährdet. Durch gemeinsame Bemühungen und bes-sere Bankenkapitalisierung ist das Finanzsystem heute widerstandsfähiger als zu Zeiten der Finanzkrise.
Sofern die Zuschüsse und Kredite im „Next Genera-tion EU“-Fund zielgerichtet für Strukturreformen und Zukunftsinvestitionen eingesetzt werden, dürfte dies einen Vertrauens- und Wachstumsimpuls darstellen.
Weitere Verbesserungen der Finanzstabilität, wie erhöhte Eigenkapitalunterlegungen, Regulierung von Schattenbanken oder Reformen im Bereich der Finanzaufsicht, sind jedoch von Nöten.
Since the global financial crisis of 2008/2009, there has been no challenge to the financial and banking system comparable to that during the Corona crisis.
Weak profitability, unresolved regulatory challenges and increasing competition in the digital sector pose further challenges for banks.
The stability of the financial system and access to financial markets was not at risk during the pandemic. Through joint efforts and better bank capitalisation, the financial system is now more resilient than during the financial crisis.
Provided that grants and loans in the “next generation EU” fund are well targeted for structural reforms and investments in the future, this should boost confi-dence and growth.
However, further improvements in financial stability, such as increased capital requirements, regulation of shadow banks or reforms in financial supervision, are needed.
Die rasante Entwicklung der Sensortechnik im Endverbraucherbereich lässt einen klinischen Nutzen der verfügbaren dezentral erhobenen Daten aus dem Patientenalltag zur Überwachung des individuellen Gesundheitszustands vermuten. Zur Überprüfung dieser Vermutung ist die Bereitstellung einer entsprechenden Plattform in den klinischen Alltag erforderlich. Hierzu wird die bwHealthApp entwickelt, mit der sowohl die aktuelle Bandbreite als auch die Evolution der Sensortechnik auf die klinische Anwendung abbildbar ist. Mit dem flexiblen Entwurf lässt sich der klinische Nutzen für die personalisierte Medizin evaluieren. Außerdem bietet die bwHealthApp einen an Machbarkeit orientierten Diskussionsbeitrag zu offenen rechtlichen, regulatorischen und ethischen Fragestellungen der Digitalisierung in der Medizin in Deutschland.
The livestock sector is growing steadily and is responsible for around 18% of global greenhouse‐gas‐emissions, which is more than the global transport sec-tor (Steinfeld et al. 2006). This paper examines the potential of social marketing to reduce meat consumption. The aim is to understand consumers’ motivation in diet choices and to learn what opportunities social marketing can provide to counteract negative environmental and health trends. The authors believe that research to answer this question should start in metropolitan areas, be-cause measures should be especially effective there. Based on the Theory of Planned Behaviour (TPB, Ajzen 1991) and the Technology‐Acceptance‐Model by Huijts et al. (2012), an online‐study with participants from the metropolitan region (n = 708) was conducted in which central socio‐psychological constructs for a meat consumption reduction were examined. It was shown that attitude, personal norm and habit have a critical influence on the intention to reduce meat consumption. A segmentation of consumers based on these factors led to three consumer clusters: vegetarians/flexitarians, potential flexitarians and convinced meat eaters. Potential flexitarians are an especially relevant target group for the development of social‐marketing‐measures to reduce meat consumption. In co‐creation‐workshops with potential flexitarians from the metropolitan region, barriers and benefits of reducing meat consumption were identified. The factors of environmental protection, animal welfare and desire for variety turn out to be the most relevant motivational factors. Based on these factors, consumers proposed a variety of social marketing measures, such as applications and labels to inform about the environmental impact of meat products.
Our paper investigates the response of acquiring firms’ stock returns around the announcement date in cross-border mergers and acquisitions (M&A) between listed Chinese acquirers and German targets. We apply an event study methodology to examine the shareholder value effect based on a sample of M&A deals over the most recent period of 2012-2018. We apply a market model event study based on the argumentation of Brown and Warner (1985) and use short-term observation periods according to Andrade, Mitchell, and Stafford (2001) as well as Hackbarth and Morellec (2008). The results indicate that the announcement of M&A involving German targets results in a positive cumulative abnormal return of on average 2.18% for Chinese acquirers’ shareholders in a five-day symmetric event window. Furthermore, we found slight indications of possible information leakage prior to the formal announcement. Although it shows that the size of acquiring firms is not necessarily correlated with the positive abnormal returns in the short run, this study suggests that Chinese acquirers’ shareholders gain higher abnormal returns when the German targets are non-listed companies.
This paper studies the impact of financial liquidity on the macro-economy. We extend a classic macroeconomic modeland compute numerical simulations. The model confirms that persistently low inflation can occur despite a high degreeof financial liquidity due to a reallocation of cash, normal and risk-free bonds. In that regard, our model uncovers anexplanation of a flat Phillips curve. Overall, our approach contributes to a rather disregarded matter in macroeconomictheory.
This article studies the current debate on Coronabonds and the idea of European public debt in the aftermath of the Corona pandemic. According to the EU-Treaty economic and fiscal policy remains in the sovereignty of Member States. Therefore, joint European debt instruments are risky and trigger moral hazard and free-riding in the Eurozone. We exhibit that a mixture of the principle of liability and control impairs the present fiscal architecture and destabilizes the Eurozone. We recommend that Member States ought to utilize either the existing fiscal architecture available or establish a political union with full sovereignty in Europe. This policy conclusion is supported by the PSPP-judgement of the Federal Constitutional Court of Germany on 5 May 2020. This ruling initiated a lively debate about the future of the Eurozone and Europe in general.
Since Adam Smith, the “homo oeconomicus” is the behavioural model in economics. Commonly this model characterizes a selfish individual, a kind of ruthless type, whose greed for profit seems to take precedence over moral values. Already 100 years ago, Max Weber provided a modernization of the model concerning the methodological individualism. Recent research in cognitive sciences reveals a further modernization of this standard model in economics. Neuro-economics, a highly interdisciplinary research field, is building a new behavioural consensus. This article examines the new properties of the “neuro-homo oeconomicus”. We show that the new behavioural model is rather similar to the long-standing economic prototype. To that extent, the neuro-model is more hype than hope. In principle, this article considers an ancient philosophical question about the nature of humans in general.
Energy efficient electric control of drives is more and more important for electric mobility and manufacturing industries. Online dynamic optimization of induction machines is challenging due to the computational complexity involved and the variable power losses during dynamic operation of induction machines. This paper proposes a simple technique for sub-optimal online loss optimization using rotor flux linkage templates for energy efficient dynamic operation of induction machines. Such a rotor flux linkage template is given by a rotor flux linkage trajectory which is optimal for a specific scenario. This template is calculated in an offline optimization process. For a specific scenario during real time operation the rotor flux linkage is calculated by appropriately scaling the given template.
In this work, a brushless, harmonic-excited wound-rotor synchronous machine is investigated which utilizes special stator and rotor windings. The windings magnetically decouple the fundamental torque-producing field from the harmonic field required for the inductive power transfer to the field coil. In contrast to conventional harmonic-excited synchronous machines, the whole winding is utilized for both torque production and harmonic excitation such that no additional copper for auxiliary windings is needed. Different rotor topologies using rotating power electronic components are investigated and their efficiencies have been compared based on Finite-Element calculation and circuit analysis.
Companies are becoming aware of the potential risks arising from sustainability aspects in supply chains. These risks can affect ecological, economic or social aspects. One important element in managing those risks is improved transparency in supply chains by means of digital transformation. Innovative technologies like blockchain technology can be used to enforce transparency. In this paper, we present a smart contract-based Supply Chain Control Solution to reduce risks. Technological capabilities of the solution will be compared to a similar technology approach and evaluated regarding their benefits and challenges within the framework of supply chain models. As a result, the proposed solution is suitable for the dynamic administration of complex supply chains.
Globalisation, shorter product life cycles, and increasing product varieties have led to complex supply chains. At the same time, there is a growing interest of customers and governments in having a greater transparency of brands, manufacturers, and producers throughout the supply chain. Due to the complex structure of collaborative manufacturing networks, the increase of supply chain transparency is a challenge for manufacturing companies. The blockchain technology offers an innovative solution to increase the transparency, security, authenticity, and auditability of products. However, there are still uncertainties when applying the blockchain technology to manufacturing scenarios and thus enable all stakeholders to trace back each component of an assembled product. This paper proposes a framework design to increase the transparency and auditability of products in collaborative manufacturing networks by adopting the blockchain technology. In this context, each component of a product is marked with a unique identification number generated by blockchain-based smart contracts. In this way, a transparent auditability of assembled products and their components can be achieved for all stakeholders, including the custome.
The key aim of Open Strategy is to open up the process of strategy development to larger groups within and even outside an organization. Furthermore, Open Strategy aims to include broad groups of stakeholders in the various steps of the strategy process. The question at hand is how can Open Strategy be achieved? What approaches can be used? Scenario planning and business wargaming are approaches perceived as relevant tools in the field of strategy and strategic foresight and in the context of Open Strategy because of their participative nature. The aim of this article is to assess to what degree scenario planning and business wargaming can be used in the context of Open Strategy. While these approaches are suitable, their current application limits the number of potential participants. Further research and experimentation in practice with larger groups and/or online approaches, or a combination of both, are needed to explore the potential of scenario planning and business wargaming as tools for Open Strategy.
This study investigates how integrated reporting (IR) creates value for investors. It examines how providers of financial capital benefit from an improved firm information environment provided by IR. Specifically, this study investigates the effect of voluntary IR disclosure on analyst earnings forecast accuracy as well as on firm value. To do so, we use an international sample of 167 listed companies that voluntarily publish an integrated report. Our analysis shows no significant effect of a voluntary IR publication on analyst earnings forecast accuracy and no significant effect on firm value. We thus do not find evidence for the fulfillment of IR's promises regarding improved information environment and value creation of voluntary adopters. We conclude that such companies might already have a relatively high level of transparency leading to an absent additional effect of IR disclosure. Positive effects of IR appear to be more relevant in environments where IR is mandatory.
Customer foresight is a relatively new research field. We introduce the customer foresight territory by discussing it localization between customer research and foresight research. For this purposse, we look at a variety of methods that help to understand customers and future realities. On this basis we provide an overwiew of customer foresight methods and outline an ideal-typical research journey.
Some widely used optical measurement systems require a scan in wavelength or in one spatial dimension to measure the topography in all three dimensions. Novel hyperspectral sensors based on an extended Bayer pattern have a high potential to solve this issue as they can measure three dimensions in a single shot. This paper presents a detailed examination of a hyperspectral sensor including a description of the measurement setup. The evaluated sensor (Ximea MQ022HG-IM-SM5X5-NIR) offers 25 channels based on Fabry–Pérot filters. The setup illuminates the sensor with discrete wavelengths under a specified angle of incidence. This allows characterization of the spatial and angular response of every channel of each macropixel of the tested sensor on the illumination. The results of the characterization form the basis for a spectral reconstruction of the signal, which is essential to obtain an accurate spectral image. It turned out that irregularities of the signal response for the individual filters are present across the whole sensor.
Systemische Betrachtung des therapeutischen Roboters Paro im Vergleich zu dem Haustierroboter AIBO
(2020)
Roboter sind in der heutigen Zeit nicht nur in der Industrie zu finden, sondern werden immer häufiger in privaten Lebensbereichen eingesetzt. Ein Beispiel hierfür ist der soziale Therapie-Roboter Paro. Dieser ist dem Verhalten und Aussehen einer jungen Robbe nachempfunden, drückt Gefühle aus und wird besonders in Pflegeheimen eingesetzt. Dabei zeigt er positive Auswirkungen auf das Wohlbefinden pflegebedürftiger Menschen. Diese Arbeit stellt den Roboter Paro in einer systemischen Analyse dar: hierbei werden Systemkontext, Anwendungsfälle, Anforderungen und Struktur betrachtet. Anschließend erfolgt eine Analyse des Haustierroboters AIBO, welcher einem Welpen ähnelt und verstärkt der Unterhaltung von Privatpersonen dient. Es werden Gemeinsamkeiten und Unterschiede zwischen den Systemen herausgearbeitet. Dabei wird ersichtlich, dass beide Systeme dem Nutzer vorrangig Gesellschaft leisten, jedoch verschiedene Anforderungen besitzen und in unterschiedlichen Anwendungsdomänen eingesetzt werden. Zudem besitzt AIBO vielfältigere Fähigkeiten und einen höheren Bewegungsgrad als Paro. Dies spiegelt sich in einer komplexeren Struktur der Hardware wider.
Wie kann die Digitalisierung in der Bauzulieferbranche erfolgreich gemeistert werden? Die Fülle und Komplexität der Fragen dazu lassen sich auf zwei zentrale Kernfragen reduzieren: Was sind die richtigen Inhalte und wesentlichen Werttreiber der Digitalisierung? Und wie muss zukünftig mit der steigenden Informationsflut, der rasant wachsenden Komplexität und der abnehmenden Planbarkeit umgegangen werden?
In diesem Beitrag wird ein Framework vorgestellt, das Bauzulieferern hilft, ihr digitales Zielbild mit seinen Werttreibern systematisch aus dem Kundennutzen abzuleiten. Das Framework berücksichtigt die Besonderheiten der Bauzulieferindustrie, kann aber mit leichten Anpassungen auch auf andere Branchen angewendet werden. Aufbauend auf dem Zielbild können Unternehmen definieren, welche technischen, personellen und organisatorischen Veränderungen für dessen Umsetzung erforderlich sind. Um flexibel mit den dynamischen Veränderungen in ihrem Ökosystem und kulturellen Herausforderungen umgehen zu können, werden zudem fünf Einflussgrößen identifiziert, die Unternehmen bei der Entwicklung der dafür benötigten Evolutionskompetenz berücksichtigen müssen.
Unter dem Begriff Innovation Enabling wird im Folgenden ein Konzept für die ganzheitliche Unterstützung interdisziplinärer Teams beim kreativen und innovativen Problemlösen vor-gestellt. Dieses Konzept unterstützt Moderatoren und Teilnehmergleichermaßen und ein damit realisiertes System bleibt durch die implizite Interaktion für den Nutzer im Hintergrund. Eine zentrale Rolle spielt das Konzept der Awareness Pipeline zur Implementation einer impliziten Interaktion auf Basis eines Sensor-Aktor-Systems, welches in diesem Artikel vorgestellt wird. Die Unterstützung der begleitenden Moderations- und Administrationsaufgaben, wie beispielsweise der automatisierten Dokumentation der Sitzung, sollen in Zukunft einen deutlichen Mehrwert gegenüber einer klassischen Brainstorming-Sitzung bieten.
The generous feed-in tariffs (FiTs) introduced in Germany—which resulted in major growth in decentralized solar photovoltaic (PV) systems—will phase out in the coming years, making many of the existing distributed generation assets stranded. This challenge creates an opportunity for community-focused energy utilities, such as Elektrizitätswerke Schönau eG (EWS) based in Schönau, Germany, to try a new approach to assist its customers, makes the transition to a more sustainable future. This chapter describes how EWS is developing products and offering community-based solutions including peer-to-peer trading using automated platforms. Such innovative offering may lead to successful differentiation in a competitive and highly decentralized future.
Based on a survey among customers of seven German municipal utilities, we estimate two regression models to identify the most prospective customer segments and their preferences and motivations for participating in peer-to-peer (P2P) electricity trading and develop implications for decision-makers in the energy sector and policy-makers for this currently relatively unknown product. Our results show a large general openness of private households towards P2P electricity trading, which is also the main predictor of respondents' intention to participate. It is mainly influenced by individuals’ environmental attitude, technical interest, and independence aspiration. Respondents with the highest willingness to participate in P2P electricity trading are mainly motivated by the ability to share electricity, and to a lesser extent by economic reasons. They also have stronger preferences for innovative pricing schemes (service bundles, time-of-use tariffs). Differences between individuals can be observed depending on their current ownership (prosumers) or installation probability of a microgeneration unit (consumers, planners). Rather than current prosumers, especially planners willing to install microgeneration in the foreseeable future are considered to be the most promising target group for P2P electricity trading. Finally, our results indicate that P2P electricity trading could be a promising niche option in the German energy transition.
Public transport maps are typically designed in a way to support route finding tasks for passengers while they also provide an overview about stations, metro lines, and city-specific attractions. Most of those maps are designed as a static representation, maybe placed in a metro station or printed in a travel guide. In this paper we describe a dynamic, interactive public transport map visualization enhanced by additional views for the dynamic passenger data on different levels of temporal granularity. Moreover, we also allow extra statistical information in form of density plots, calendar-based visualizations, and line graphs. All this information is linked to the contextual metro map to give a viewer insights into the relations between time points and typical routes taken by the passengers. We illustrate the usefulness of our interactive visualization by applying it to the railway system of Hamburg in Germany while also taking into account the extra passenger data. As another indication for the usefulness of the interactively enhanced metro maps we conducted a user experiment with 20 participants.
This book describes the current state of the art in integrated ring resonators, covering more than two decades in the development of this exciting device. It discusses in depth one of the most fascinating and versatile integrated optical filters, providing readers with a panoramic view spanning from design and simulation to implementation in various material systems. Written by authors with extensive experience in both academia and industry, this second edition offers a much-needed, major update as interest in integrated ring resonators undergoes a global revival. The new edition includes a comprehensive technological update, and a timely discussion of recent advances in new application areas, such as optofluidics and microfluidics, telecom operations and biosensors. This aptly named compendium is the ideal guide for researchers and engineers looking to review the field as a whole while exploring several of its possible and exciting future trajectories.
The objective of the project presented here is to develop an intelligent control algorithm for an energy system consisting of a biogas CHP (combined heat and power), various storage technologies, such as thermal energy storages (TES) and gas storages, and other renewable energy sources, such as photovoltaics. A corresponding algorithm based on the Monte-Carlo method has already been developed at Reutlingen University for CHP units running on natural gas and for heat pumps. The project presented here concentrates on the further development of this algorithm for application to biogas CP units. In this context, an adequate implementation of the gas storage is of primary importance, as it mainly determines the flexibility of the plant. In the course of the validation of the new optimization algorithm, simulations were carried out based on data from the Lower Lindenhof, an agricultural experimental station of the University of Hohenheim. Both an optimization with regard to onsite electricity utilization and an optimization driven by residual load were investigated. Preliminary results show that the optimization algorithm can improve the operation of the biogas CHP unit depending on the selected target function.
The data presented in this article characterize the thermomechanical and microhardness properties of a novel melamine-formaldehyde resin (MF) intended for the use as a self-healing surface coating. The investigated MF resin is able to undergo reversible crosslinking via Diels Alder reactive groups. The microhardness data were obtained from nanoindentation measurements performed on solid resin film samples at different stages of the self-healing cycle. Thermomechanical analysis was performed under dynamic load conditions. The data provide supplemental material to the manuscript published by Urdl et al. 2020 (https://doi.org/10.1016/j.eurpolymj.2020.109601) on the self-healing performance of this resin, where a more thorough discussion on the preparation, the properties of this coating material and its application in impregnated paper-based decorative laminates can be found.
Thermoplastic polymers like ethylene-octene copolymer (EOC) may be grafted with silanes via reactive extrusion to enable subsequent crosslinking for advanced biomaterials manufacture. However, this reactive extrusion process is difficult to control and it is still challenging to reproducibly arrive at well-defined products. Moreover, high grafting degrees require a considerable excess of grafting reagent. A large proportion of the silane passes through the process without reacting and needs to be removed at great expense by subsequent purification. This results in unnecessarily high consumption of chemicals and a rather resource-inefficient process. It is thus desired to be able to define desired grafting degrees with optimum grafting efficiency by means of suitable process control. In this study, the continuous grafting of vinyltrimethoxysilane (VTMS) on ethylene-octene copolymer (EOC) via reactive extrusion was investigated. Successful grafting was verified and quantified by 1H-NMR spectroscopy. The effects of five process parameters and their synergistic interactions on grafting degree and grafting efficiency were determined using a face-centered experimental design (FCD). Response surface methodology (RSM) was applied to derive a causal process model and define process windows yielding arbitrary grafting degrees between <2 and >5% at a minimum waste of grafting agent. It was found that the reactive extrusion process was strongly influenced by several second-order interaction effects making this process difficult to control. Grafting efficiencies between 75 and 80% can be realized as long as grafting degrees <2% are admitted.
Azide-bearing cell-derived extracellular matrices (“clickECMs”) have emerged as a highly exciting new class of biomaterials. They conserve substantial characteristics of the natural extracellular matrix (ECM) and offer simultaneously small abiotic functional groups that enable bioorthogonal bioconjugation reactions. Despite their attractiveness, investigation of their biomolecular composition is very challenging due to the insoluble and highly complex nature of cell-derived matrices (CDMs). Yet, thorough qualitative and quantitative analysis of the overall material composition, organisation, localisation, and distribution of typical ECM-specific biomolecules is essential for consistent advancement of CDMs and the understanding of the prospective functions of the developed biomaterial. In this study, we evaluated frequently used methods for the analysis of complex CDMs. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) and (immune)histochemical staining methods in combination with several microscopic techniques were found to be highly eligible. Commercially available colorimetric protein assays turned out to deliver inaccurate information on CDMs. In contrast, we determined the nitrogen content of CDMs by elementary analysis and converted it into total protein content using conversion factors which were calculated from matching amino acid compositions. The amount of insoluble collagens was assessed based on the hydroxyproline content. The Sircol™ assay was identified as a suitable method to quantify soluble collagens while the Blyscan™ assay was found to be well-suited for the quantification of sulphated glycosaminoglycans (sGAGs). Eventually, we propose a series of suitable methods to reliably characterise the biomolecular composition of fibroblast-derived clickECM.