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The aim of this paper is to identify indicators at country level that could prove useful in improving the effectiveness of fraud detection in European Structural and Investment Funds. We analyse data for 454 funds, belonging to the period 2014-2020, from the 28 countries that were members of the European Union in 2014. Explanatory results suggest the convenience of tracking funds, especially in countries with higher GDP and higher transparency levels, and the lesser relevance of the number of irregularities for countries with higher GDP and those receiving larger funds. Fraud and fraud detection rates in individual funds vary significantly across states. Federal states, such as the Federal Republic of Germany, are comparatively successful in detecting fraud in EU funds.
Purpose
This study aims to investigate a systematic approach to the production and use of additively manufactured injection mould inserts in product development (PD) processes. For this purpose, an evaluation of the additive tooling design method (ATDM) is performed.
Design/methodology/approach
The evaluation of the ATDM is conducted within student workshops, where students develop products and validate them using AT-prototypes. The evaluation process includes the analysis of work results as well as the use of questionnaires and participant observation.
Findings
This study shows that the ATDM can be successfully used to assist in producing and using AT mould inserts to produce valid AT prototypes. As a reference for the implementation of AT in industrial PD, extracts from the work of the student project groups and suitable process parameters for prototype production are presented.
Originality/value
This paper presents the application and evaluation of a method to support AT in PD that has not yet been scientifically evaluated.
Der Online-Handel verzeichnet seit Jahren ein stetiges Wachstum. Durch die COVID-19-Pandemie kaufen nun auch Nutzende, die zuvor physische Kanäle bevorzugten, vermehrt online ein. Der Anbietererfolg hängt dabei wesentlich von der Kenntnis über die Kund*innen ab. Allerdings dominieren einige große Anbieter den Markt, während kleinere Online-Shops Schwierigkeiten haben, ihre Angebote zu personalisieren. Eine Lösung bietet der Ansatz selbstbestimmter Identitäten. Dieser ermöglicht Kund*innen, ihre eigenen Shoppingdaten zu kontrollieren und sie selektiv mit Online-Shops zu teilen. Dadurch können individuelle Wünsche und Anforderungen der Kund*innen in Online-Shops berücksichtigt und ein personalisiertes Angebot sowie eine gute Nutzungserfahrung geboten werden. Trotz des großen Potenzials selbstbestimmter Identitäten ist der Ansatz in Deutschland kaum verbreitet. Dieser Beitrag beleuchtet den Einsatz selbstbestimmter Identitäten im Online-Handel. Mithilfe eines menschenzentrierten Gestaltungsprozesses wurden Personas und Ist-Szenarien erstellt, sowie daraus resultierend Anforderungen erhoben und Potenziale identifiziert. Auf Basis dessen konnte ein Daten- und Architekturmodell zur Integration von selbstbestimmten Identitäten im Online-Handel entwickelt werden.
This report examines exporters’ challenges and possible solutions for public intervention to promote foreign trade. Based on fieldwork conducted in Georgia, we explore which policy approaches can help to stimulate Georgian exports further. Our outcomes show that exporters face substantial barriers such as navigating complex trade regulations, lack of knowledge about target markets, trade finance gaps, as well as new export promotion programs (EPPs) in competitor countries. Other upper-middle-income countries can learn from our results that exporters can significantly benefit from a comprehensive export promotion strategy combined with an ecosystem-based “team” approach. EPPs related to awareness and capacity building in Georgia should be part of this strategy, focusing on challenges such as a lack of knowledge about trade practices and international business skills. Other EPPs must help to mitigate related market failures, as information gathering is costly, and firms have no incentive to share this information with competitors. Furthermore, targeted marketing support and customer matchmaking can answer Georgian exporters’ challenges, such as lack of market access and low sector visibility. Our results also show that public intervention through financial support and risk mitigation is essential for firms with an international orientation. The high-quality, rich outcomes provide significant value for other upper-middle-income countries by exploring the example of Georgia’s contemporary circumstances in an in-depth manner based on extensive interviews and document analysis. Limitations include that our work primarily relies on qualitative data and further research could involve a quantitative study with a diverse range of sectors.
Background: Assistive Robotic Arms are designed to assist physically disabled people with daily activities. Existing joysticks and head controls are not applicable for severely disabled people such as people with Locked-in Syndrome. Therefore, eye tracking control is part of ongoing research. The related literature spans many disciplines, creating a heterogeneous field that makes it difficult to gain an overview.
Objectives: This work focuses on ARAs that are controlled by gaze and eye movements. By answering the research questions, this paper provides details on the design of the systems, a comparison of input modalities, methods for measuring the performance of these controls, and an outlook on research areas that gained interest in recent years.
Methods: This review was conducted as outlined in the PRISMA 2020 Statement. After identifying a wide range of approaches in use the authors decided to use the PRISMA-ScR extension for a scoping review to present the results. The identification process was carried out by screening three databases. After the screening process, a snowball search was conducted.
Results: 39 articles and 6 reviews were included in this article. Characteristics related to the system and study design were extracted and presented divided into three groups based on the use of eye tracking.
Conclusion: This paper aims to provide an overview for researchers new to the field by offering insight into eye tracking based robot controllers. We have identified open questions that need to be answered in order to provide people with severe motor function loss with systems that are highly useable and accessible.
In a dynamic global landscape, the role of UK Export Finance (UKEF) and other export credit agencies (ECAs) has never been more important. Access to finance is critical for exporters as it enables them to invest in production, expand operations, manage cash flow and mitigate trade risks. However, businesses face challenges in securing export finance and trade credit insurance as geopolitical and trade megatrends lead to increased political, market and credit risks. Drawing on qualitative data from 35 semi-structured interviews and expert discussions and based on the Futures Triangle analytical framework, this white paper analyses the geopolitical and trade megatrends that UKEF and other ECAs will face in the coming years. It presents novel findings about the implications for ECA mandates, strategies, products and operations: The evolution of mandates towards a “growth promoter”, the need to further scale up operations, the use of big data and artificial intelligence for risk analysis and forecasting, and the need to balance multiple and conflicting priorities, including export growth, support for small and medium-sized exporters, inclusive trade, climate action, and positive impact in developing markets.
Online grocery shopping (OGS) has significantly risen due to accelerated retail digitization and reshaped consumer shopping behaviors over the last years. Despite this trend, the German online grocery market lags behind its international counterparts. Notably, with almost half of the German population aged over 50 and the 55–64 age group emerging as the largest user segment in e-commerce, the over-50 demographic presents an attractive yet relatively overlooked audience for the expansion of the online grocery market. However, research on OGS behavior among German over-50s is scarce. This study addresses this gap, empirically investigating OGS adoption factors within this demographic through an online survey with 179 respondents. Our findings reveal that over a third of the over-50 demographic has embraced OGS, indicating a growing receptivity for OGS among the over-50s. Notably, home delivery, product variety, convenience, and curiosity emerged as primary drivers for OGS adoption among this demographic. Surprisingly, most adopters did not increase online grocery orders since 2020 and a not inconsiderable proportion have even stopped buying groceries online again. For potential OGS adopters, regional product availability turned out as a motivator, signaling substantial growth potential and providing online grocers with strategic opportunities to target this demographic. In light of our research, we offer practical suggestions to online grocery retailers, aiming to overcome barriers and capitalize on key drivers identified in our study for sustained growth in the over-50 market segment.
Printed circuit boards (PCB) are a foundation of electronical devices in modern society. The fabrication of these boards requires various processes and machines. The utilisation of a robot with multiple tools can shorten the process chain compared to screen printing. In this paper a system is presented, which utilises an industrial six axis robot to manufacture
PCBs. The process flow and conversion process of the Gerber format into robot specific commands is presented. The advantages and challenges applying a robot to print circuits are discussed.
Plastics are used today in many areas of the automotive, aerospace and mechanical engineering industries due to their lightweight potential and ease of processing. Additive manufacturing is applied more and more frequently, as it offers a high degree of design freedom and eliminates the need for complex tools. However, the application of additively manufactured components made of plastics have so far been limited due to their comparatively low strength. For this reason, processes that offer additional reinforcement of the plastic matrix using fibers made of high-strength materials have been developed. However, these components represent a composite of different materials produced on the basis of fossil raw materials, which are difficult to recycle and generally not biodegradable.
Therefore, this paper will explore the potential for new composite materials whose matrix consists of a bio-based plastic. In this investigation, it is assumed that the matrix is reinforced with a fibrous material made of natural fiber to significantly increase the strength. This potential material should offer a lightweight yet strong structure and be biodegradable after use under controlled conditions. Therefore, the state of the art in the use of bio-based materials in 3D printing is first presented. In order to determine the economic boundary conditions, the growth potentials for bio-based materials are analyzed. Also, the recycling prospects for bio-based plastics will also be highlighted. The greenhouse gas emissions and land use to be expected when using bio-based materials are also estimated. Finally, the degradability of the composites is discussed.
Projektmanagement und mit ihm die PM-Prozesse, Methoden und Werkzeuge entwickeln sich stetig weiter, in kleinen, kaum spürbaren Schritten oder in großen unübersehbaren Veränderungen. In den letzten Jahren war der Diskurs über das Pro & Contra agiler Vorgehensweisen so allgegenwärtig, dass andere Aspekte nicht immer die notwendige Aufmerksamkeit bekamen. Erkannte Notwendigkeiten der PM-Entwicklung konnten noch nicht in spürbare Fortschritte umgewandelt werden. Einflüsse der Globalisierung und der IT, aber auch die aus der zunehmenden Forderung nach Nachhaltigkeit resultierenden Veränderungen in der Projektarbeit sollen daher genauer betrachtet werden. Ist erst einmal die Sensibilität für relevante Trends beim Projektpersonal geschaffen, rücken ein aktualisiertes Kompetenzprofil und ein erweiterter Methodenkanon in greifbare Nähe.
Decentralized applications (dApp) have proliferated in recent years, but their long-term viability is a topic of debate. However, for dApps to be sustainable, and suitable for integration into a larger service networks, they need to attract users and promise reliable availability. Therefore, assessing their longevity is crucial. Analyzing the utilization trajectory of a service is, however, challenging due to several factors, such as demand spikes, noise, autocorrelation, and non-stationarity. In this study, we employ robust statistical techniques to identify trends in currently popular dApps. Our findings demonstrate that a significant proportion of dApps, across a range of categories, exhibit statistically significant positive overall trends, indicating that success in decentralized computing can be sustainable and transcends specific fields. However, there is also a substantial number of dApps showing negative trends, with a disproportionately high number from the decentralized finance (DeFi) category. Furthermore, a more detailed inspection of time series segments shows a clearly diminishing proportion of positive trends from mid-2021 to the present. In summary, we conclude that the dApp economy might have lost some momentum, and that there is a strong element of uncertainty regarding its future significance.
In the framework of electro-elasticity theory and the finite element method (FEM), a model is set up for the computation of quantities in surface acoustic wave (SAW) devices accounting for nonlinear effects. These include second-order and third-order intermodulations, second and third harmonic generation and the influence of electro-acoustic nonlinearity on the frequency characteristics of SAW resonators. The model is based on perturbation theory, and requires input material constants, e.g., the elastic moduli up to fourth order for all materials involved. The model is two-dimensional, corresponding to an infinite aperture, but all three Cartesian components of the displacement and electrical fields are accounted for. The first version of the model pertains to an infinite periodic arrangement of electrodes. It is subsequently generalized to systems with a finite number of electrodes. For the latter version, a recursive algorithm is presented which is related to the cascading scheme of Plessky and Koskela and strongly reduces computation time and memory requirements. The model is applied to TC-SAW systems with copper electrodes buried in an oxide film on a LiNbO3 substrate. Results of computations are presented for the electrical current due to third-order intermodulations and the displacement field associated with the second harmonic and second-order intermodulations, generated by monochromatic input tones. The scope of this review is limited to methodological aspects with the goal to enable calculations of nonlinear quantities in SAW devices on inexpensive and easily accessible computing platforms.
Marketing and sales have high expectations of new methods such as Big Data, artificial intelligence, machine learning, and predictive analytics. But following the “garbage in—garbage out” principle, the results leave much to be desired. The reason is often insufficient quality in the underlying customer data. This article sheds light on this problem using the data quality and value pyramid as an example. The higher up the value-added pyramid the data is located, the higher its quality and the more value it generates for a company. In addition, we show how the use of monitoring systems, such as a data quality scorecard, makes data quality visible and improvements measurable. In this way, the actual value of data for companies becomes obvious and manageable.
Mathematik lässt sich in vielen Objekten finden. Sei es die lineare Steigung eines Handlaufs zum Schulgebäude oder die nahezu zylindrische Form einer Litfaßsäule in der Innenstadt. Das Bestreben, Schüler*innen diese Zusammenhänge entdecken zu lassen, steht im Zentrum des MathCityMap Projekts (Ludwig et al., 2013). Auf sogenannten mathematischen Wanderpfaden (bzw. Mathtrails) werden Schüler*innen durch eine App zu Mathematikaufgaben an realen Objekten bzw. in realen Situationen ihrer Umwelt geleitet. Um die Aufgaben zu lösen, werden Daten erhoben, z. B. durch Messungen oder Zählen. Entscheidend ist, dass die Aufgaben so gestellt sind, dass der Schritt der Datenbeschaffung nur vor Ort stattfinden kann und somit direkt mit dem Objekt bzw. der Situation verknüpft wird.
Learning programming fundamentals is considered as one of the most challenging and complex learning activities. Some authors have proposed visual programming language (VPL) approaches to address part of the inherent complexity [1]. A visual programming language lets users develop programs by combining program elements, like loops graphically rather than by specifying them textually. Visual expressions, spatial arrangements of text and graphic symbols are used either as syntax elements or secondary notation. VPLs are normally used for educational multimedia, video games, system development, and data warehousing/business analytics purposes. For example, Scratch, a platform of Massachusetts Institute of Technology, is designed for kids and after school programs.
Design of mobile software applications is considered as one of the most challenging application domains due to the build in sensors as part of a mobile device, like GPS, camera or Near Field Communication (NFC). Sensors enable creation of context-aware mobile applications in which applications can discover and take advantage of contextual information, such as user location, nearby people and objects, and the current user activity. As a consequence, context-aware mobile applications can sense clues about the situational environment making mobile devices more intelligent, adaptive, and personalized. Such context aware mobile applications seem to be motivating and attractive case studies, especially for programming beginners (“my own first app”).
In this work, we introduce a use-case centered approach as well as clear separation of user interface design and sensor-based program development. We provide an in-depth discussion of a new VPL based teaching method, a step by step development process to enable programming beginners the creation of context aware mobile applications. Finally, we argue that addressing challenges for programming beginners by our teaching approach could make programming teaching more motivating, with an additional impact on the final software quality and scalability.
The key contributions of our study are the following:
- An overview of existing attempts to use VPL approaches for mobile applications
- A use case centered teaching approach based on a clear separation of user interface design and sensor-based program development
- A teaching case study enabling beginners a step by step creation of context-aware mobile applications based on the MIT App Inventor (a platform of Massachusetts Institute of Technology)
- Open research challenges and perspectives for further development of our teaching approach
References:
[1] Idrees, M., Aslam, F. (2022). A Comprehensive Survey and Analysis of Diverse Visual Programming Languages, VFAST Transactions on Software Engineering, 2022, Volume 10, Number 2, pp 47-60.
In 4D printing an additively manufactured component is given the ability to change its shape or function under the influence of an external stimulus. To achieve this, special smart materials are used that are able to react to external stimuli in a specific way. So far, a number of different stimuli have already been investigated and initial applications have been impressively demonstrated, such as self-folding bodies and simple grippers. However, a methodical specification for the selection of the stimuli and their implementation was not yet in the foreground of the development.
The focus of this work is therefore to develop a methodical approach with which the technology of 4DP can be used in a solution- and application-oriented manner. The developed approach is based on the conventional design methodology for product development to solve given problems in a structured way. This method is extended by specific approaches under consideration of the 4D printing and smart materials.
To illustrate the developed method, it is implemented in practice using a problem definition in the form of an application example. In this example, which represents the recovery of an object from a difficult-to-access environment, the individual functions of positioning, gripping and extraction are implemented using 4D printing. The material extrusion process is used for additive manufacturing of all components of the example. Finally, the functions are successfully tested. The developed approach offers an innovative and methodical approach to systematically solve technical complex problems using 4DP and smart materials.
Public export credits and trade insurance require a global framework of institutions, rules and regulations to avoid subsidies and a race to the bottom. The extensive modernisation of the Arrangement on Officially Supported Export Credits (Arrangement) of the Organisation for Economic Co-operation and Development intends to re-level the playing field. This Practitioner Commentary describes the demand for adequate government interventions, considers the need for the reform and discusses key aspects of the new Arrangement. We argue that there is a breakthrough in several important areas such as tenors, repayment terms and green finance. However, we also find that the modernisation falls short in areas such as the interplay between different rulebooks, pre-shipment instruments' regulations and climate action.
This thesis deals with the redesign of manufacturing systems by simulation and optimization. Material flow simulation is a common tool for solving problems in system design. Limitations are the high requirements in time and knowledge to execute simulation studies, evaluate results and solve design problems. New chances arrives with the technologies of industry 4.0 and the digital shadow, providing data for simulation. However, the methods to use production data for the redesign of production systems are not available yet. Purpose of this work is providing the methods to automate simulation from digital shadow, use simulation to optimize and solve problems in system design. Two case studies are used to support the action research approach of this work. The result of this work is a framework for the application of the digital shadow in optimization and problem-solving.
Voice User Experience
(2023)
Sprachassistenten wie Alexa, Google Assistant, Siri, Cortana, Magenta und Bixby erfreuen sich dank ihrer intuitiven, schnellen und bequemen Interaktionsmöglichkeiten zunehmender Beliebtheit und bieten deshalb spannende Möglichkeiten für die Weiterentwicklung des digitalen Kundendialogs. Doch ob die Technologie wirklich breite Akzeptanz finden wird, hängt nicht nur mit ihrer technischen Qualität oder Usability zusammen. Auch die User Experience, die neben den Reaktionen der Nutzer*innen während der Anwendung auch ihre Erwartungen und Wahrnehmungen vor und nach der Anwendung umfasst, spielt eine zentrale Rolle. Die Messung der Qualität der Voice User Experience (Voice UX) ist daher von großem Interesse für die Bewertung und Optimierung von Sprachapplikationen. Die Frage, wie die Voice UX von sprachgesteuerten Systemen gemessen werden kann, ist jedoch noch offen. Aktuelle Methoden stützen sich häufig auf UX-Forschung zu grafischen Benutzeroberflächen, obwohl die sprachbasierten Interaktionsformen in der Regel weder visuell noch haptisch greifbar sind. In unserem Beitrag möchten wir den aktuellen Status quo der deutschen Voice User Experience untersuchen. Folgende Fragen stehen dabei im Mittelpunkt: Wie können Sprachanwendungen zu einem erfolgreichen Kundendialog beitragen? Welche Nutzerirritationen treten aktuell bei der Anwendung von Sprachassistenten auf? Mit welchen Methoden lässt sich die Voice User Experience messen?
The present paper addresses the research question: What recommendations for action and potential adjustments should an online magazine for beauty and fashion implement in order to make affiliate articles in these sections even more appealing to the target group and provide added value for them?
To be able to answer this research question, three hypotheses were defined and tested with using qualitative and quantitative research. The qualitative research consisted of user experience testings, where four affiliate articles in the fields of beauty and fashion were tested with 13 participants. The quantitative research involved collecting, analyzing and evaluating data from the four affiliate articles conducted with the company's real-life target group. Based on these results, recommendations for action were derived, which should not only improve the quality of the content in the future, but also increase the efficiency of the implementation of those articles.
Novel approaches for the design of assistive technology controls propose the usage of eye tracking devices such as for smart wheelchairs and robotic arms. The advantages of artificial feedback, especially vibrotactile feedback, as opposed to their use in prostheses, have not been sufficiently explored. Vibrotactile feedback reduces the cognitive load on the visual and auditory channel. It provides tactile sensation, resulting in better use of assistive technologies. In this study the impact of vibration on the precision and accuracy of a head-worn eye tracking device is investigated. The presented system is suitable for further research in the field of artificial feedback. Vibration was perceivable for all participants, yet it does not produce any significant deviations in precision and accuracy.
Established robot manufacturers have developed methods to determine and optimize the accuracy of their robots. These methods vary from robot manufacturers to their competitors. Due to the lack of published data, a comparison of robot performance is difficult. The aim of this article is to find methods to evaluate important characteristics of a robot with an accurate and cost-effective setup. A laser triangulation sensor and geometric referenced spheres were used as a base to compare the robot performance.
Material flow simulation is a core technology of Industry 4.0. It can analyze and improve large-scale production systems through experimentation with digital simulation models. However, modeling in discrete event simulation is considered as an effortful and time-consuming activity and challenges especially small and medium-sized enterprises. Systematic experiments and what-if-analysis require a large number of models. Modeling and simulation becomes a repetitive activity and the ability to model and simulate instantly becomes crucial for industry, 4.0. However, model generation typically uses specific methods to build models with individual properties for specific physical systems. A general literature review cannot sufficiently describe the current state of model generation. This study aims to provide an analysis of model generation based on the modeling strategy, modeling view, and production system type, as well as model properties and limitations.
Kundendaten im E-Commerce – Optimierungspotenzial im Checkout-Prozess des deutschen Online-Handels
(2023)
Die Gestaltung eines benutzungsfreundlichen Checkout-Prozesses ist für den Erfolg des E-Commerce von großer Bedeutung. Die Abfrage der Kundendaten bildet einen wichtigen Teil der Customer Journey. Auf der einen Seite wollen die Handelsunternehmen so viel wie möglich über ihre Kundschaft erfahren, um möglichst zielgenaue Angebote und Marketingmaßnahmen ausspielen und das perfekte Einkaufserlebnis generieren zu können. Auf der anderen Seite möchten sich die Kundinnen und Kunden beim Online-Shopping auf den Kauf konzentrieren und erwarten einen reibungslosen Ablauf. Der Checkout-Prozess ist in diesem Zusammenhang ein kritischer Punkt. Dies spiegelt sich auch in den hohen Warenkorbabbruchraten wider. Um Online-Shoppende nachhaltig zu begeistern, gibt es noch viel Raum für Verbesserungen. Mit dem Ziel, den Status quo im deutschen Online-Handel besser zu verstehen und Usability und User Experience für eine höhere Konvertierungsrate zu optimieren, untersuchte die hier vorgestellte Forschungsarbeit den Anmelde- und Checkout-Prozess der 100 umsatzstärksten Online-Shops in Deutschland. Es werden die Ergebnisse der Studie präsentiert und aufgezeigt, an welchen Stellen Optimierungspotenzial besteht – bspw. bei zu komplizierten Formularen, unnötigen Datenabfragen oder erzwungenen Registrierungen – sowie Vorschläge für die Praxis des Online-Handels diskutiert.
Additive manufacturing enables the production of lightweight and resilient components with extensive design freedom. In the low-cost sector, material extrusion (e.g. Fused Deposition Modeling - FDM) has been the main method used to date. Thus, robust 3D printers and inexpensive 3D materials (polymer filaments) can be used. However, the printing times for FDM are very long and the quality of the dimensions and surfaces is limited. Recently, new processes from the field of Vat polymerization have entered the market. For example, masked stereolithography (mSLA) offers a significant improvement in component quality and build speed through the use of resins and large-area curing at still reasonable costs. Currently, there is only limited knowledge available on the optimal design of components using this young process. In this contribution, design guidelines are developed to determine the possibilities and limitations of mSLA from a design point of view. For this purpose, a number of test geometries are designed and investigated to obtain systematic insights into important design features, such as wall thickness, grooves and holes. In addition, typical problems in additive manufacturing, such as the design of overhangs and fits or the hollowing of components, are investigated. The evaluation of practical 3D printing tests thus provides important parameters that can be transferred to design guidelines of components for additive manufacturing using mSLA.
International trade requires sufficient, reliable, and affordable sources of financing. Export credit agencies (ECAs) fill trade finance gaps by offering financing, insurance and guarantees to provide liquidity or mitigate risks. They help to create or secure jobs in the domestic economy. However, comprehensive government support is required to create significant impact. This includes ‘full faith and credit’ of the state. In the context of public foreign trade promotion, full faith and credit is defined as an explicit, direct or indirect, irrevocable, legal commitment to accept all liabilities of an ECA as unconditional obligations of the respective government. Our policy recommendations for countries with relatively young ECAs, for example in Ukraine, Armenia, and Malawi, are to establish a full guarantee in addition to an efficient legal set-up, sufficient capital, and sound risk management of the respective agency. Without full faith and credit, policy goals of fostering economic growth through foreign trade fall short.
In an extensive research project, we have assessed the application of different service models by export credit agencies (ECAs) and export-import banks (EXIMs). We conducted interviews with 35 representatives of ECAs and EXIMs from 27 countries. The question guiding this study is: How do ECAs and EXIMs adopt public service models for supporting exporters? We conducted a holistic multiple case study, investigating if and how these organisations apply public service models developed by Schedler and Guenduez, and which roles of the state are relevant. We find that there is a variety of different service models used by ECAs and EXIMs, and that the service model approaches have great potential to learn from each other and innovate existing services.
Robotic Process Automation (RPA) is a technology for automating business processes and connecting systems by means of software robots in organizations that is gaining traction and growing out of its infancy. Thus, it is no longer just a question of what is technologically feasible, but rather how this technology can be used most profitably. However, business models for RPA remain underinvestigated in literature. Existing work is highly heterogenous, lacking structure and applicability in practice. To close this gap, we present an approach to sustainably establish RPA as a driver of digitization and automation within a company based on an iterative, holistic view of business models with the Business Model Canvas as analysis tool.
In 4D printing, an additively manufactured component is given the ability to change its shape or function in an intended and useful manner over time. The technology of 4D printing is still in an early stage of development. Nevertheless, interesting research and initial applications exist in the literature. In this work, a novel methodical approach is presented that helps transfer existing 4D printing research results and knowledge into solving application tasks systematically. Moreover, two different smart materials are analyzed, used, and combined following the presented methodical approach to solving the given task in the form of recovering an object from a poorly accessible space. This is implemented by self-positioning, grabbing, and extracting the target object. The first smart material used to realize these tasks is a shape-memory polymer, while the second is a polymer-based magnetic composite. In addition to the presentation and detailed implementation of the methodical approach, the potentials and behavior of the two smart materials are further examined and narrowed down as a result of the investigation. The results show that the developed methodical approach contributes to moving 4D printing closer toward a viable alternative to existing technologies due to its problem-oriented nature.
Staatliche Exportkreditagenturen und Export-Import-Banken finanzieren, versichern und garantieren jährlich fast 1 Bio. US-Dollar – mehr als 3 % der globalen Güterexporte. Ihre Interventionen sind an internationale Rahmenbedingungen gebunden, insbesondere an das WTO-Subventionsübereinkommen (ASCM) und den OECD-Konsensus. Das komplexe Zusammenspiel beider Rechtsrahmen sorgt seit langem für Herausforderungen, vor allem hinsichtlich des Anwendungsbereichs des “safe haven” des ASCM und des “Matching”-Mechanismus der OECD. In den vergangenen Jahren hinzugekommen ist die Problematik neuer Instrumente der Exportvor- sowie der Klimafinanzierung. Der folgende Beitrag erörtert Herausforderungen und Lösungsansätze. Er zeigt auf, dass der neue OECD-Konsensus trotz zahlreicher Verbesserungen zentrale rechtliche Probleme nicht behebt.
In order to attract new students, German universities must provide quick and easy access to relevant information. A chatbot can help increase the efficiency in academic advising for prospective students. In this study we evaluate the acceptance and effects of chatbots in German student-university communication. We conducted a qualitative UX-Study with the chatbot prototype of Offenburg University of Applied Sciences (HSO), in order to determine which features are particularly relevant and which requirements are made by the users. The results show that acceptance increases if the chatbot offers quick and adequate assistance, furthermore, our participants preferred an informal communication style and valued friendly and helpful personality traits for chatbots.
Wissenschaftler treten als Berater auf und nehmen nicht nur Einfluss auf wirtschaftliche, sondern auch auf politische Entscheidungen. Welche Anforderungen sind an diese Art der Entscheidungsunterstützung zu stellen? Lassen sich für Wissenschaftler zulässige und unzulässige Einflussmöglichkeiten identifizieren? Der Beitrag beantwortet diese Frage unter Rückgriff auf Erkenntnisse aus Soziologie und Entscheidungslehre.
4D printing (4DP) is an evolutionary step of 3D printing, which includes the fourth dimension, in this case the time. In different time steps the printed structure shows different shapes, influenced by external stimuli like light, temperature, pH value, electric or magnetic field. The advantage of 4DP is the solution of technical problems without the need for complex internal energy supply via cables or pipes. Previous approaches to 4D printing with magnetoresponsive materials only use materials with limited usability (e.g. hydrogels) and complex programming during the manufacturing process (e.g. using magnets on the nozzle). The 4D printing using unmagnetized particles and the later magnetization allows the use of a standard 3D printer and has the advantage of being easily reproducible and relatively inexpensive for further application. Therefore, a magnetoresponsive feedstock filament is produced which shows elastic and magnetic properties. In a first step, pellets are produced by compounding polymer with magnetic particles. In a second step, those pellets are extruded in form of filament. This filament is printed using a conventional printing system for Material Extrusion (MEX-TRB/P). Various prototypes have been printed, deformed and magnetized, which is called programming. In comparison to shape memory polymers (SMP) the repeatability of the movement is better. The results show the possibilities of application and function of magnetoresponsive materials. In addition, an understanding of the behaviour of this novel material is achieved.
In this contribution, we present a novel 3D printed multi-material, electromagnetic vibration harvester. The harvester is based on a cantilever design and utilizes an embedded constantan wire within a matrix of polyethylene terephthalate glycol (PETG). A prototype has been manufactured with a combination of a fused filament fabrication (FFF) printer and a robot with a custom-made tool.
Artificial Intelligence (AI) can potentially transform many aspects of modern society in various ways, including automation of tasks, personalization of products and services, diagnosis of diseases and their treatment, transportation, safety, and security in public spaces, etc. Recently, AI technology has been transforming the financial industry, offering new ways to analyse data and automate processes, reduce costs, increase efficiency, and provide more personalized services to customers. However, it also raised important ethical and regulatory questions that need to be addressed by the industry and society as a whole. The aim of the Erasmus+ project Transversal Skills in Applied Artificial Intelligence - TSAAI (KA220-HED - Cooperation Partnerships in higher education) has been to establish a training platform that will incorporate teaching guidelines based on a curriculum covering different areas of application of AI technology. In this work, we will focus on applying AI models in the financial and insurance sectors.
Günter Knieps hat das Forschungsgebiet der Netzökonomie in Deutschland maßgeblich geprägt. Ein in seinen Forschungsarbeiten immer wiederkehrendes Thema ist die Frage nach der richtigen Balance zwischen Wettbewerb und Regulierung in Netzsektoren. Unter den vielen wissenschaftlichen Beiträgen, die Günter Knieps bislang vorgelegt hat, genießt ein Beitrag einen besonderen Stellenwert: sein im August 1997 in der Zeitschrift Kyklos erschienener Aufsatz „Phasing out Sector-Specific Regulation in Competitive Telecommunications“. Der 25. Jahrestag des Erscheinens dieses Aufsatzes wurde von der Herausgeberin und den Herausgebern des vorliegenden Sammelbandes zum Anlass genommen, den Versuch zu unternehmen, das wissenschaftliche Werk und das Wirken von Günter Knieps als Forscher und Hochschullehrer mit einer Festschrift zu würdigen. Mit Beiträgen von (in der Reihenfolge der Kapitel): Johannes M. Bauer, Falk von Bornstaedt, Manfred J. Holler & Florian Rupp, Hans-Ulrich Küpper, Kay Mitusch, Friedrich Schneider, Viktor J. Vanberg, Achim Wambach, Bernhard Wieland und Patrick Zenhäusern sowie einem Geleitwort von Carl Christian von Weizsäcker.
KINLI
(2023)
Konsumenten haben immer höhere Ansprüche an Lebensmittelsicherheit, -qualität und -nachhaltigkeit. Bei Fleisch erwarten viele Menschen auch eine artgerechte und ethisch vertretbare Aufzucht, Haltung und Schlachtung der Tiere. Im Projekt KINLI sollen eine Datenplattform und Dienste mit künstlicher Intelligenz entwickelt werden, um mögliche Probleme vorherzusagen. Unternehmen in der Lieferkette können damit proaktiv ihre Prozesse anpassen, bevor Probleme tatsächlich eintreten.
Differentiation between human and non-human objects can increase efficiency of human-robot collaborative applications. This paper proposes to use convolutional neural networks for classifying objects in robotic applications. The body temperature of human beings is used to classify humans and to estimate the distance to the sensor. Using image classification with convolutional neural networks it is possible to detect humans in the surroundings of a robot up to five meters distance with low-cost and low-weight thermal cameras. Using transfer learning technique we trained the GoogLeNet and MobilenetV2. Results show accuracies of 99.48 % and 99.06 % respectively.
While most ultrafast time-resolved optical pump-probe experiments in magnetic materials reveal the spatially homogeneous magnetization dynamics of ferromagnetic resonance (FMR), here we explore the magneto-elastic generation of GHz-to-THz frequency spin waves (exchange magnons). Using analytical magnon oscillator equations, we apply time-domain and frequency-domain approaches to quantify the results of ultrafast time-resolved optical pump-probe experiments in free-standing ferromagnetic thin films. Simulations show excellent agreement with the experiment, provide acoustic and magnetic (Gilbert) damping constants and highlight the role of symmetry-based selection rules in phonon-magnon interactions. The analysis is extended to hybrid multilayer structures to explore the limits of resonant phonon-magnon interactions up to THz frequencies.
The technique of laser ultrasonics perfectly meets the need for noncontact, noninvasive, nondestructive mechanical probing of nanometer- to millimeter-size samples. However, this technique is limited to the excitation of low-amplitude strains, below the threshold for optical damage of the sample. In the context of strain engineering of materials, alternative optical techniques enabling the excitation of high-amplitude strains in a nondestructive optical regime are needed. We introduce here a nondestructive method for laser-shock wave generation based on additive superposition of multiple laser-excited strain waves. This technique enables strain generation up to mechanical failure of a sample at pump laser fluences below optical ablation or melting thresholds. We demonstrate the ability to generate nonlinear surface acoustic waves (SAWs) in Nb-SrTiO3 substrates, with associated strains in the percent range and pressures up to 3 GPa at 1 kHz repetition rate and close to 10 GPa for several hundred shocks. This study paves the way for the investigation of a host of high-strain SAW-induced phenomena, including phase transitions in conventional and quantum materials, plasticity and a myriad of material failure modes, chemistry and other effects in bulk samples, thin layers, and two-dimensional materials.
We revisit the quantitative analysis of the ultrafast magnetoacoustic experiment in a freestanding nickel thin film by Kim and Bigot [J.-W. Kim and J.-Y. Bigot, Phys. Rev. B 95, 144422 (2017)] by applying our recently proposed approach of magnetic and acoustic eigenmode decomposition. We show that the application of our modeling to the analysis of time-resolved reflectivity measurements allows for the determination of amplitudes and lifetimes of standing perpendicular acoustic phonon resonances with unprecedented accuracy. The acoustic damping is found to scale as ∝ω2 for frequencies up to 80 GHz, and the peak amplitudes reach 10−3. The experimentally measured magnetization dynamics for different orientations of an external magnetic field agrees well with numerical solutions of magnetoelastically driven magnon harmonic oscillators. Symmetry-based selection rules for magnon-phonon interactions predicted by our modeling approach allow for the unambiguous discrimination between spatially uniform and nonuniform modes, as confirmed by comparing the resonantly enhanced magnetoelastic dynamics simultaneously measured on opposite sides of the film. Moreover, the separation of timescales for (early) rising and (late) decreasing precession amplitudes provide access to magnetic (Gilbert) and acoustic damping parameters in a single measurement.
Digitalisierung ist heute allgegenwärtig. Wo im Privaten bereitwillig neue digitale Tools, Apps und Funktionen genutzt werden, tun sich Unternehmen in der Umsetzung von Digitalisierungsprojekten oft schwer. Dieser Beitrag beleuchtet die Motive für Digitalisierungsvorhaben, ihre Hürden sowie die Auswirkung auf die Arbeitsbelastung von Mitarbeitenden und versucht in der Verknüpfung mit den Grundprinzipien des Kontinuierlichen Verbesserungsprozesses, Handlungsempfehlungen für eine erfolgreiche Umsetzung dieser abzuleiten.
In Zeiten großer Veränderungen haben genossenschaftlich organisierte KMU die Möglichkeit, auf komplexe Herausforderungen mit kooperativen Lösungsansätzen zu reagieren, vor allem wenn dabei die Kraft und Kreativität der Gemeinschaft genutzt wird. Getreu dem Motto „Was einer alleine nicht schafft, das schaffen viele“ des Genossenschaftsvorreiters Friedrich Wilhelm Raiffeisen ist gemeinschaftliches unternehmerisches Handeln identitätsstiftend und motivierend, woraus wiederum eine sich selbst verstärkende Eigendynamik entstehen kann. Wie Mittelstand, Politik und Gesellschaft davon profitieren, stellen Prof. Dr. Tobias Popovic und Prof. Dr. Thomas Baumgärtler in diesem Beitrag dar.
This paper presents a system that uses a multi-stage AI analysis method for determining the condition and status of bicycle paths using machine learning methods. The approach for analyzing bicycle paths includes three stages of analysis: detection of the road surface, investigation of the condition of the bicycle paths, and identification of substrate characteristics. In this study, we focus on the first stage of the analysis. This approach employs a low-threshold data collection method using smartphone-generated video data for image recognition, in order to automatically capture and classify surface condition and status.
For the analysis convolutional neural networks (CNN) are employed. CNNs have proven to be effective in image recognition tasks and are particularly well-suited for analyzing the surface condition of bicycle paths, as they can identify patterns and features in images. By training the CNN on a large dataset of images with known surface conditions, the network can learn to identify common features and patterns and reliably classify them.
The results of the analysis are then displayed on digital maps and can be utilized in areas such as bicycle logistics, route planning, and maintenance. This can improve safety and comfort for cyclists while promoting cycling as a mode of transportation. It can also assist authorities in maintaining and optimizing bicycle paths, leading to more sustainable and efficient transportation system.
In this paper we present the concept of the "KI-Labor Südbaden" to support regional companies in the use of AI technologies. The approach is based on the "Periodic Table of AI" and is extended with both new dimensions for sustainability, and the impact of AI on the working environment. It is illustrated on the basis of three real-world use cases: 1. The detection of humans with lowresolution infrared (IR) images for collaborative robotics; 2. The use of machine data from specifically designed vehicles; 3. State-of-the-art Large Language Models (LLMs) applied to internal company documents. We explain the use cases, thereby demonstrating how to apply the Periodic Table of AI to structure AI applications.
3D Bin Picking with an innovative powder filled gripper and a torque controlled collaborative robot
(2023)
A new and innovative powder filled gripper concept will be introduced to a process to pick parts out of a box without the use of a camera system which guides the robot to the part. The gripper is a combination of an inflatable skin, and a powder inside. In the unjammed condition, the powder is soft and can adjust to the geometry of the part which will be handled. By applying a vacuum to the inflatable skin, the powder gets jammed and transforms to a solid shaped form in which the gripper was brought before applying the vacuum. This physical principle is used to pick parts. The flexible skin of the gripper adjusts to all kinds of shapes, and therefore, can be used to realize 3D bin picking. With the help of a force controlled robot, the gripper can be pushed with a consistent force on flexible positions depending of the filling level of the box. A Kuka LBR iiwa with joint torque sensors in all of its seven axis’ was used to achieve a constant contact pressure. This is the basic criteria to achieve a robust picking process.
In this work the nonlinear behavior of layered surface acoustic wave (SAW) resonators is studied with the help of finite element (FE) computations. The full calculations depend strongly on the availability of accurate tensor data. While there are accurate material data for linear computations, the complete sets of higher-order material constants, needed for nonlinear simulations, are still not available for relevant materials. To overcome this problem, scaling factors were used for each available nonlinear tensor. The approach here considers piezoelectricity, dielectricity, electrostriction, and elasticity constants up to the fourth order. These factors act as a phenomenological estimate for incomplete tensor data. Since no set of fourth-order material constants for LiTaO3 is available, an isotropic approximation for the fourth-order elastic constants was applied. As a result, it was found that the fourth-order elastic tensor is dominated by one-fourth order Lamé constant. With the help of the FE model, derived in two different, but equivalent ways, we investigate the nonlinear behavior of a SAW resonator with a layered material stack. The focus was set to third-order nonlinearity. Accordingly, the modeling approach is validated using measurements of third-order effects in test resonators. In addition, the acoustic field distribution is analyzed.