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Smart cities are considered data factories that generate an enormous amount of data from various sources. In fact data is the backbone of any smart services. Therefore, the strategic beneficial handling of this digital capital is crucial for cities. Some smart city pioneers have already written down their approach to data in the form of data strategies, but what should a city's data strategy include, and how can the goals and measures defined in the strategies be operationalized? This paper addresses these questions by looking closely at the data strategies of cities in Germany and the top three countries in the EU Digital Economy and Society Index. The in-depth analysis of 8 city data strategies has yielded 11 dimensions that cities should consider in their data strategy. These are relevance of data, principles, methods, data sharing, technology, data culture, data ethics, organizational structure, data security and privacy, collaborations, data literacy. In addition, data governance is a concept to put these 11 strategic dimensions into practice through standardization measures, training programs, and defining roles and responsibilities by developing a data catalog.
While the concepts of object-oriented antipatterns and code smells are prevalent in scientific literature and have been popularized by tools like SonarQube, the research field for service-based antipatterns and bad smells is not as cohesive and organized. The description of these antipatterns is distributed across several publications with no holistic schema or taxonomy. Furthermore, there is currently little synergy between documented antipatterns for the architectural styles SOA and Microservices, even though several antipatterns may hold value for both. We therefore conducted a Systematic Literature Review (SLR) that identified 14 primary studies. 36 service-based antipatterns were extracted from these studies and documented with a holistic data model. We also categorized the antipatterns with a taxonomy and implemented relationships between them. Lastly, we developed a web application for convenient browsing and implemented a GitHub-based repository and workflow for the collaborative evolution of the collection. Researchers and practitioners can use the repository as a reference, for training and education, or for quality assurance.
Analysis is an important part of the enterprise architecture management process. Prior to decisions regarding transformation of the enterprise architecture, the current situation and the outcomes of alternative action plans have to be analysed. Many analysis approaches have been proposed by researchers and current enterprise architecture management tools implement analysis functionalities. However, few work has been done structuring and classifying enterprise architecture analysis approaches. This paper collects and extends existing classification schemes, presenting a framework for enterprise architecture analysis classification. For evaluation, a collection of enterprise architecture analysis approaches has been classified based on this framework. As a result, the description of these approaches has been assessed, a common set of important categories for enterprise architecture analysis classification has been derived and suggestions for further development are drawn.
Autonomous driving is becoming the next big digital disruption in the automotive industry. However, the possibility of integrating autonomous driving vehicles into current transportation systems not only involves technological issues but also requires the acceptance and adoption of users. Therefore, this paper develops a conceptual model for user acceptance of autonomous driving vehicles. The corresponding model is tested through a standardized survey of 470 respondents in Germany. Finally, the findings are discussed in relation to the current developments in the automotive industry, and recommendations for further research are given.
Many start-ups are in search of cooperation partners to develop their innovative business models. In response, incumbent firms are introducing increasingly more cooperation systems to engage with start-ups. However, many of these cooperations end in failure. Although qualitative studies on cooperation models have tried to improve the effectiveness of incumbent start-up strategies, only a few have empirically examined start-up cooperation behavior. Considering the lack of adequate measurement models in current research, this paper focuses on developing a multi-item scale on cooperation behavior of start-ups, drawing from a series of qualitative and quantitative studies. The resultant scale contributes to recent research on start-up cooperation and provides a framework to add an empirical perspective to current research.
In this work, a comparison between different brushless harmonic-excited wound-rotor synchronous machines is performed. The general idea of all topologies is the elimination of the slip rings and auxiliary windings by using the already existing stator and rotor winding for field excitation. This is achieved by injecting a harmonic airgap field with the help of power electronics. This harmonic field does not interact with the fundamental field, it just transfers the excitation power across the airgap. Alternative methods with varying number of phases, different pole-pair combinations, and winding layouts are covered and compared with a detailed Finite-Element-parameterized model. Parasitic effects due to saturation and coupling between the harmonic and main windings are considered.
Automatisierte Analyse von Review-Daten beschäftigt sich mit den Möglichkeiten, freien Text zu analysieren und relevante Informationen daraus zu extrahieren. Die Arbeit setzt sich dabei mit Methoden des unüberwachten Lernens auseinander. Hierbei steht die Methode der Topic Modellierung im Mittelpunkt. Es werden Verfahren betrachtet, die im Bereich der textbasierten Informationsgewinnung bekannt sind. Latent Semantic Indexing LSI, (probabilistic) pLSI und Latent Dirichlet Allocation (LDA) werden erläutert und verglichen. Die Arbeit zeigt, wie LDA genutzt wurde, um einen nhaltlichen Überblick über einen Datenkorpus von 1 Mio. Reviews zu bekommen und diesen auf einen feineren Detailgrad zu betrachten. Die Topic-basierte Analyse wird genutzt, um Erkentnisse für ein Opinion Mining System zu generieren, welches eine tiefergehende Analyse vornehmen wird. Der gesamte Prozess ist als vollständig automatisiert und maschinell unüberwacht konzeptioniert.
Distributed ledger technologies such as the blockchain technology offer an innovative solution to increase visibility and security to reduce supply chain risks. This paper proposes a solution to increase the transparency and auditability of manufactured products in collaborative networks by adopting smart contract-based virtual identities. Compared with existing approaches, this extended smart contract-based solution offers manufacturing networks the possibility of involving privacy, content updating, and portability approaches to smart contracts. As a result, the solution is suitable for the dynamic administration of complex supply chains.
The increase in distributed energy generation, such as photovoltaic systems (PV) or combined heat and power plants (CHP), poses new challenges to almost every distribution network operator (DNO). In the low-voltage (LV) grids, where installed PV capacity approaches the magnitude of household load, reverse power flow occurs at the secondary substa-tions. High PV penetration leads to voltage rise, flicker and loading problems. These problems have been addressed by the application of various techniques amongst which is the deployment of step voltage regulators (SVR). SVR can solve the voltage problem, but do not prevent or reduce reverse power flows. Therefore, the application of SVR in low voltage grids can result in significant power losses upstream. In this paper we present part of a research project investi-gating the application of remote-controlled cable cabinets (CC) with metering units in a low-voltage network as a possible alternative for SVR. A new generation of custom-made remote-control cable cabinets has been deployed and dynamic network reconfigurations (NR) have been realized with the following objectives: (i) reduction of reverse power flow through the secondary substation to the upstream network and therefore a reduction of upstream losses, (ii) reduction of the voltage rise caused by distributed energy resources and (iii) load balancing in the low-voltage grid. Secondary objec-tives are to improve the DNO's insight into the state of the network and to provide further information on future smart grid integration.
For large-scale processes as implemented in organizations that develop software in regulated domains, comprehensive software process models are implemented, e.g., for compliance requirements. Creating and evolving such processes is demanding and requires software engineers having substantial modeling skills to create consistent and certifiable processes. While teaching process engineering to students, we observed issues in providing and explaining models. In this paper, we present an exploratory study in which we aim to shed light on the challenges students face when it comes to modeling. Our findings show that students are capable of doing basic modeling tasks, yet, fail in utilizing models correctly. We conclude that the required skills, notably abstraction and solution development, are underdeveloped due to missing practice and routine. Since modeling is key to many software engineering disciplines, we advocate for intensifying modeling activities in teaching.
In der Mikroelektronik werden Chips häufig in Mold-Gehäusen verpackt. Die elektrischen Verbindungen vom Chip zu den Anschlussbeinchen des Gehäuses werden mit Bonddrähten realisiert. Für die Berechnung der Gleichgewichtstemperatur in einem Bonddraht bei konstantem Strom sowie von Temperaturverläufen bei transienten Strömen ist die herkömmliche FEM-Methode langsam und unhandlich. Daher wurde der Bondrechner entwickelt, der ein zylindersymmetrisches Ersatz-Modell für das Package in geeigneten mathematischen Gleichungen abbildet.
Im Gegensatz zum Bondrechner der ersten Generation [1], der auf den Gleichungen von [2] basiert, bietet ein neuer mathematischer Ansatz die Möglichkeit, eine endliche effektive Package-Größe, sowie einen endlichen Wärmeübergang zwischen Bonddraht und Mold-Masse zu berücksichtigen. Ebenso wurde die Berechnung der Interaktion von mehreren benachbarten Drähten verfeinert. Die Berechnung von beliebigen transienten Pulsformen mittlerer Länge wurde ebenfalls verbessert. Eine quadratische Komponente in der Temperaturabhängigkeit des spezifischen Widerstandes des Drahtmaterials kann jetzt ebenfalls berücksichtigt werden.
Die Ergebnisse wurden erfolgreich mit FEM-Berechnungen verglichen und die Geschwindigkeit der Berechnung ist um Größenordnungen schneller als mit kommerziellen FEM-Programmen.
Theoretical foundation, effectiveness, and design artefact for machine learning service repositories
(2022)
Machine learning (ML) has played an important role in research in recent years. For companies that want to use ML, finding the algorithms and models that fit for their business is tedious. A review of the available literature on this problem indicates only a few research papers. Given this gap, the aim of this paper is to design an effective and easy-to-use ML service repository. The corresponding research is based on a multi-vocal literature analysis combined with design science research, addressing three research questions: (1) How is current white and gray literature on ML services structured with respect to repositories? (2) Which features are relevant for an effective ML service repository? (3) How is a prototype for an effective ML service repository conceptualized? Findings are relevant for the explanation of user acceptance of ML repositories. This is essential for corporate practice in order to create and use ML repositories effectively.
Due to the rising need for palliative care in Russia, it is crucial to provide timely and high-quality solutions for patients, relatives, and caregivers. A methodology for remote monitoring of patients in need of palliative care and the requirements will be developed for a hardware-software complex for remote monitoring of patients' health at home.
The typed graph model
(2020)
In recent years, the Graph Model has become increasingly popular, especially in the application domain of social networks. The model has been semantically augmented with properties and labels attached to the graph elements. It is difficult to ensure data quality for the properties and the data structure because the model does not need a schema. In this paper, we propose a schema bound Typed Graph Model with properties and labels. These enhancements improve not only data quality but also the quality of graph analysis. The power of this model is provided by using hyper-nodes and hyper edges, which allows to present a data structure on different abstraction levels. We demonstrate by example the superiority of this model over the property graph data model of Hidders and other prevalent data models, namely the relational, object-oriented, and XML model.
The time has come : application of artificial intelligence in small- and medium-sized enterprises
(2022)
Artificial intelligence (AI) is not yet widely used in small- and medium-sized industrial enterprises (SME). The reasons for this are manifold and range from not understanding use cases, not enough trained employees, to too little data. This article presents a successful design-oriented case study at a medium-sized company, where the described reasons are present. In this study, future demand forecasts are generated based on historical demand data for products at a material number level using a gradient boosting machine (GBM). An improvement of 15% on the status quo (i.e. based on the root mean squared error) could be achieved with rather simple techniques. Hence, the motivation, the method, and the first results are presented. Concluding challenges, from which practical users should derive learning experiences and impulses for their own projects, are addressed.
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.
Compared to the automotive sector, where automation is the rule, in many other less standardized sectors automation is still the exception. This could soon hurt the productivity of industrialized countries, where the unemployment is low and the population is aging. Phenomena like the recent downfall in productivity, due to lockdowns and social distancing for prevention of health hazards during the COVID19 pandemic, only add to the problem. For these reasons, the relevance, motivation and intention for more automation in less standardized sectors has probably never been higher. However, available statistics say that providers and users of technologies struggle to bring more automation into action in automation-unfriendly sectors. In this paper, we present a decision support method for investment in automation that tackles the problem: the STIC analysis. The method takes a holistic and quantitative approach tying together technological, context-related and economic input parameters and synthetizing them in a final economic indicator. Thanks to the modelling of such parameters, it is possible to gain sensibility on the technological and/or process adjustments that would have the highest impact on the efficiency of the automation, thereby delivering value for both technology users and technology providers.
The success of an autonomous robotic system is influenced by several interdependent factors not easily identifiable. This paper is set to lay the foundation of a new integrated approach in order to deeply examine all the parameters and understand their contribution to success. After introducing the problem, two cutting edge autonomous systems for the process of unloading of containers will be presented. Then the STIC analysis, a recently developed method for modelling and interpreting all the parameters, will be introduced. The preliminary results of applying such a methodology to a first study case, based on one of the two systems available to the authors, will be shortly presented. Future research is in the end recommended in order to prove that this methodology is the only way to efficiently and effectively mitigate the risk that stops potential users from investing in autonomous systems in the logistics sector.
The digital twin concept has been widely known for asset monitoring in the industry for a long time. A clear example is the automotive industry. Recently, there has also been significant interest in the application of digital twins in healthcare, especially in genomics in what is known as precision medicine. This work focuses on another medical speciality where digital twins can be applied, sleep medicine. However, there is still great controversy about the fundamentals that constitute digital twins, such as what this concept is based on and how it can be included in healthcare effectively and sustainably. This article reviews digital twins and their role so far in what is known as personalized medicine. In addition, a series of steps will be exposed for a possible implementation of a digital twin for a patient suffering from sleep disorders. For this, artificial intelligence techniques, clinical data management, and possible solutions for explaining the results derived from artificial intelligence models will be addressed.
Due to rapidly changing technologies and business contexts, many products and services are developed under high uncertainties. It is often impossible to predict customer behaviors and outcomes upfront. Therefore, product and service developers must continuously find out what customers want, requiring a more experimental mode of management and appropriate support for continuously conducting experiments. We have analytically derived an initial model for continuous experimentation from prior work and matched it against empirical case study findings from two startup companies. We examined the preconditions for setting up an experimentation system for continuous customer experiments. The resulting RIGHT model for Continuous Experimentation (Rapid Iterative value creation Gained through High-frequency Testing) illustrates the building blocks required for such a system and the necessary infrastructure. The major findings are that a suitable experimentation system requires the ability to design, manage, and conduct experiments, create so-called minimum viable products or features, link experiment results with a product roadmap, and manage a flexible business strategy. The main challenges are proper, rapid design of experiments, advanced instrumentation of software to collect, analyse, and store relevant data, and integration of experiment results in the product development cycle, software development process, and business strategy. This summary refers to the article The RIGHT Model for Continuous Experimentation, published in the Journal of Systems and Software [Fa17].
The relevance of technology knowledge in digital transformation especially in small and mediumsized enterprises (SMEs) that are still largely dependent on physical human capital has become increasingly obvious. This is due to the rapid revolution in business environment coupled with increased living examples of firms disrupted by advancement in technological knowledge. Consequently, we find it progressively vital for SMEs to spot and mitigate both threats and take advantage of opportunities arising from digital transformation dynamism.
Our study aims at exploring the relevance of technology knowledge in SMEs for digital transformation to uncover the opportunities, roadmaps, and models that SMEs can take advantage of in the digital transformation and gain a competitive edge.
We conclude that irrespective relevance of technology knowledge for digital transformation coupled with its low costs and accessibility, SMEs are yet to realize the full potential of technological knowledge. This is mainly due to technologies appearing, changing and also vanishing so rapidly in the digital age, that gaining proper understanding without dedicated resources is utterly difficult for SMEs - making them less competitive as incumbent large firms in the market.
In standardized sectors such as the automotive, the cost-benefit ratio of automation solutions is high as they contribute to increase capacity, decrease costs and improve product quality. In less standardized application fields, the contribution of automation to improvements in capacity, cost and quality blurs. The automation of complex and unstructured tasks requires sophisticated, expensive and low-performing systems, whose impact on product quality is oftentimes not directly perceived by customers. As a result, the full automation of process chains in the general manufacturing or the logistic sectors is often a sub optimal solution. Taking the distance from the false idea that a process should be either fully automated, or fully manual, this paper presents a novel heuristic method for design of lean human-robot interaction, the Quality Interaction Function Deployment, with the objective of the “right level of automation”. Functions are divided among human and automated agents and several automation scenarios are created and evaluated with respect to their compliance to the requirements of all process´ stakeholders. As a result, synergies among operators (manual tasks) and machines (automated tasks) are improved, thus reducing time-losses and increasing productivity.
Context: Organizations are increasingly challenged by high market dynamics, rapidly evolving technologies and shifting user expectations. In consequence, many organizations are struggling with their ability to provide reliable product roadmaps by applying traditional roadmapping approaches. Currently, many companies are seeking opportunities to improve their product roadmapping practices and strive for new roadmapping approaches. A typical first step towards advancing the roadmapping capabilities of an organization is to assess the current situation. Therefore, the so-called maturity model DEEP for assessing the product roadmapping capabilities of companies operating in dynamic and uncertain environments has been developed and published by the authors.
Objective: The aim of this article is to conduct an initial validation of the DEEP model in order to understand its applicability better and to see if important concepts are missing. In addition, the aim of this article is to evolve the model based on the findings from the initial validation.
Method: The model has been given to practitioners such as product managers with the request to perform a self-assessment of the current product roadmapping practices in their company. Afterwards, interviews with each participant have been conducted in order to gain insights.
Results: The initial validation revealed that some of the stages of the model need to be rearranged and minor usability issues were found. The overall structure of the model was well received. The study resulted in the development of the version 1.1 of the DEEP product roadmap maturity model which is also presented in this article.
Steady growing research material in a variety of databases, repositories and clouds make academic content more than ever hard to discover. Finding adequate material for the own research however is essential for every researcher. Based on recent developments in the field of artificial intelligence and the identified digital capabilities of future universities a change in the basic work of academic research is predicted. This study defines the idea of how artificial intelligence could simplifiy academic research at a digital university. Today's studies in the field of AI spectacle the true potential and its commanding impact on academic research.
Electromigration (EM) is becoming a progressively severe reliability challenge due to increased interconnect current densities. A shift from traditional (post-layout) EM verification to robust (pro-active) EM aware design - where the circuit layout is designed with individual EM-robust solutions - is urgently needed. This tutorial will give an overview of EM and its effects on the reliability of present and future integrated circuits (ICs). We introduce the physical EM process and present its specific characteristics that can be affected during physical design. Examples of EM countermeasures which are applied in today’s commercial design flows are presented. We show how to improve the EM-robustness of metallization patterns and we also consider mission proiles to obtain application-oriented current density limits. The increasing interaction of EM with thermal migration is investigated as well. We conclude with a discussion of application examples to shift from the current post layout EM verification towards an EM aware physical design process. Its methodologies, such as EM-aware routing, increase the EM-robustness of the layout with the overall goal of reducing the negative impact of EM on the circuit’s reliability.
This paper describes the design and outcomes of an experimental study that addresses stock-and-flow-failure from a cognitive perspective. It is based on the assumption that holistic (global) and analytic (local) processing are important cognitive mechanisms underlying the ability to infer the behavior of dynamic systems. In a stock-and-flow task that is structurally equivalent to the department store task, we varied the format in which participants are primed to think about an environmental system, in particular whether they are primed to concentrate on lower-level (local) or higher-level (global) system elements. 148 psychology, geography and business students participated in our study. Students’ answers support our hypothesis that global processing increases participants’ ability to infer the overall system behavior. The beneficial influence of global presentation is even stronger when data are presented numerically rather than in the form of a graph. Our results suggest presenting complex dynamic systems in a way that facilitates global processing. This is particularly important as policy-designers and decision makers deal with complex issues in their everyday and professional life.
During the first years of their employment, the graduates are a liability to industry. The employer goes an extra mile to bridge the gap between university-exiting and profitable employment of engineering graduates. Unfortunately some cannot take this risk. Given this scenario, this paper presents a learning factory approach as a platform for the application of knowledge so as to develop the required engineering competences in South African engineering graduates before they enter the labour market. It spells out the components of a Stellenbosch University Learning Factory geared towards production of engineering graduates with the required industrial skills. It elaborates on the didactics embedded in the learning factory environment, tailor-made to produce engineers who can productively contribute to the growth of the industry upon exiting the university.
Internet of things innovations and the industrial internet these days become more and more decisive factors of future success for companies. Especially manufacturing oriented SME will face the challenge to develop innovative technology driven business models alongside technology innovations in this field which will be essential for future competitiveness. Failing in developing these technology driven business models in an internationally highly competitive environment will have a serious impact both on companies and on the society. Hence, securing economic stability and success of these technology driven business models is an indispensable task. To identify challenges for innovative industrial internet business models first it is necessary to understand what the industrial internet means to the leading parties and applying companies and start-ups in the field. Second, challenges from general business model development will be outlined. In a third step risks and challenges in business model development will be discussed with regard to the special characteristics of technology driven business models in the context of the industrial internet and the important role of the technological key component of the business model. Especially the capability to deal with an integrated consideration of the indivisible linked dimensions of economic and technological aspects of these business models is questioned. In the fourth place the specific challenges for industrial internet business models are derived. On the basis of these results it is also discussed what might be done to handle these challenges successfully with the goal to turn them into chances. The need for future research on the integration of the risk management perspective into the development of these technology driven business models is derived. This will help established companies and start-ups to realize great technological innovations for the industrial internet in sound and successful innovative business models.
Relationship Marketing (RM) presumes trust as an important antecedent for the performance of interfirm relationships. Current research is dominated by an interpersonal perspective. In this research tack, trust chiefly emerges as a result of interpersonal relationships. But multiple risks arise if customer trust rests solely on elements inextricably linked to single representatives. Hence, this paper evaluates the impact of organizational capabilities and the moderating role of customer preferences on the trust creation process. The framework presented here is tested cross-industry on 220 customers for IT solutions. The results offer significant insight into the effectiveness of individual and organizational RM strategies.
IT Governance (ITG) is crucial due to its significant impact on enabling innovation and enhancing firm performance. Hence, in the last decade ITG has become important in both academic and in practical research. Although several studies have investigated individual aspects of ITG success and its impact on single determinants, the causal relationship of how ITG promotes firm performance remains unclear. Thus, a more comprehensive understanding about the link between ITG and firm performance is needed. To address this gap, this research aims at understanding how ITG and firm performance are related. Therefore, we conducted a systematic literature review (1) to create an overview on how current research structures the link between ITG mechanisms and firm performance, (2) to uncover key constructs as potential mediators or moderators on the general link between ITG and performance, and (3) to set the basis for future studies on the ITG-firm performance relationship.
Digitization transforms business process models and processes in many enterprises. However, many of them need guidance, how digitization is impacting the design of their information systems. Therefore, this paper investigates the influence of digitization on information system design. We apply a two-phase research method applying a literature review and an exploratory case study. The case study took place in the IT service provider of a large insurance enterprise. The study’s results suggest that a number of areas of information system design are affected, such as architecture, processes, data and services.
The advent of chatbots in customer service solutions received increasing attention by research and practice throughout the last years. However, the relevant dimensions and features for service quality and service performance for chatbots remain quite unclear. Therefore, this research develops and tests a conceptual model for customer service quality and customer service performance in the context of chatbots. Additionally, the impact of the developed service dimensions on different customer relationship metrics is measured across different service channels (hotline versus chatbots). Findings of six independent studies indicate a strong main effect of the conceptualized service dimensions on customer satisfaction, service costs, intention to service reusage, word-of-mouth, and customer loyalty. However, different service dimensions are relevant for chatbots compared to a traditional service hotline.
It is essential for the success of a company to set a strategic direction in which a product offering will be developed over time to achieve the company vision. For this reason, roadmaps are used in practice. in general, roadmaps can be expressed in various forms such as technology roadmaps, product roadmaps or industry roadmaps. From the point of view of industry, the basic purpose of a roadmap is to explore, visualize and communicate the dynamic linkage between markets, products and technology.
Electronic design automation approaches can roughly be divided into optimizers and procedures. While the former have enabled highly automated synthesis flows for digital integrated circuits, the latter play a vital (but mostly underestimated role) in the analog domain. This paper describes both automation strategies in comparison, identifying two fundamentally different automation paradigms that reflect the two basic design practices known as “top-down” and “bottom-up”. Then, with a focus on the latter, the history of procedural approaches is traced from their
early beginnings until today’s evolvements and future prospects to underline their practical importance and to accentuate their scientific value, both in itself and in the overall context of EDA.
Study programs in higher education have to reflect important societal and industrial challenges to prepare the next generations of professionals for future tasks. The focus of this paper is the challenge of digitalization and digital transformation. The paper proposes the IS education profile of a Digital Business Architect (DBA). The study program emphasizes design thinking, model centricity, and capability thinking as a response to domain requirements from digital transformation and educational system and structure requirements. Experiences in implementing the DBA include the need for integrating deductive and inductive teaching, a strong basis in real-world cases, and collaborative learning approaches to develop adequate competences in business model management, enterprise modeling, enterprise architecture management, and capability management.
The paper studies the deciding parameters that influence business students' selection of internships in Germany. The findings are based on literature research and a survey amongst students and company representatives and asks to rate the importance of 24 different aspects of internships. The benefits and negative impacts of internships on students, companies and universities are discussed in detail. The results of different demographic groups are compared.
With significant advancements in digital technologies, firms find themselves competing in an increasingly dynamic business environment. Therefore, the logic of business decisions is based on the agility to respond to emerging trends in a proactive way. By contrast, traditional IT governance (ITG) frameworks rely on hierarchy and standardized mechanisms to ensure better business/IT alignment. This conflict leads to a call for an ambidextrous governance, in which firms alternate between stability and agility in their ITG mechanisms. Accordingly, this research aims to explore how agility might be integrated in ITG. A quantitative research strategy is implemented to explore the impact of agility on the causal relationship among ITG, business/IT alignment, and firm performance. The results show that the integration of agile ITG mechanisms contributes significantly to the explanation of business/IT alignment. As such, firms need to develop a dual governance model powered by traditional and agile ITG mechanisms.
Since project managers still face problems in managing interorganizational R&D projects, it is a promising approach to manage these projects project-culturally-aware. However, an important prerequisite for a project-culture-aware management is that the involved individual organizations pursue a collaborative strategy. Therefore, our article provides a conceptual approach including a new tool, the Collaborative Iron Triangle, which supports both project sponsors and managers in different phases of the collaboration process to pursue a collaborative strategy in interorganizational R&D projects.
Early reduction of risks in a startup or an innovation project is highly important. Appropriate means for risk reduction, such as testing business models with different kinds of experiments exist. However, deciding what to test and how to select the right test, is challenging for many startups and innovation projects. This article presents the so-called Business Experiments Navigator (BEN), a toolkit to assist startup and innovation processes. It compliments other tools such as the Business Model Canvas or the Lean Startup process. The main contribution of BEN is to bridge the gap between the riskiest assumptions of a business model and the multitude of available testing techniques by providing assumption templates. The Business Experiments Navigator has been validated in several workshops. Results show that it creates awareness among the workshop participants that a business model is based on assumptions which impose risks and need to be validated. Further, users of BEN were able to identify relevant assumptions and map different kinds of assumptions to appropriate testing techniques. The process applied in the workshops, as well as the assumption templates, helped the participants understand the main concepts and transfer their learnings, to their own business ideas.
Digital transformation has changed corporate reality and, with that, firms’ IT environments and IT governance (ITG). As such, the perspective of ITG has shifted from the design of a relatively stable, closed and controllable System of a self-sufficient Enterprise to a relatively fluid, open, agile and transformational system of networked co-adaptive entities. Related to this paradigm shift in ITG, this paper aims to clarify how the concept of an effective ITG framework has changed in terms of the demand for agility in organizations. Thus, this study conducted 33 qualitative interviews with executives and senior managers from the banking industry in Germany, Switzerland and Austria. Analysis of the interviews focused on the formation of categories and the assignment of individual text parts (codings)
to these categories to allow for a quantitative evaluation of the codings per category. Regarding traditional and agile ITG dimensions, 22 traditional and 25 agile dimensions in terms of structures, processes and relational mechanisms were identified. Moreover, agile strategies within the agile ITG construct and ten ITG patterns were identified from the interview data. The data show relevant perspectives on the implementation of traditional and new ITG dimensions and highlight ambidextrous aspects in ITG in the German-speaking banking industry.
The shift of populations to cities is creating challenges in many respects, thus leading to increasing demand for smart solutions of urbanization problems. Smart city applications range from technical and social to economic and ecological. The main focus of this work is to provide a systematic literature review of smart city research to answer two main questions: (1) How is current research on smart cities structured? And (2) What directions are relevant for future research on smart cities? To answer these research questions, a text-mining approach is applied to a large number of publications. This provides an overview and gives insights into relevant dimensions of smart city research. Although the main dimensions of research are already described in the literature, an evaluation of the relevance of such dimensions is missing. Findings suggest that the dimensions of environment and governance are popular, while the dimension of economy has received only limited attention.
Most Question-answering (QA) systems rely on training data to reach their optimal performance. However, acquiring training data for supervised systems is both time-consuming and resource-intensive. To address this, in this paper, we propose TFCSG, an unsupervised similar question retrieval approach that leverages pre-trained language models and multi-task learning. Firstly, topic keywords in question sentences are extracted sequentially based on a latent topic-filtering algorithm to construct unsupervised training corpus data. Then, the multi-task learning method is used to build the question retrieval model. There are three tasks designed. The first is a short sentence contrastive learning task. The second is the question sentence and its corresponding topic sequence similarity judgment task. The third is using question sentences to generate their corresponding topic sequence task. The three tasks are used to train the language model in parallel. Finally, similar questions are obtained by calculating the cosine similarity between sentence vectors. The comparison experiment on public question datasets that TFCSG outperforms the comparative unsupervised baseline method. And there is no need for manual marking, which greatly saves human resources.
3D assisted 2D face recognition involves the process of reconstructing 3D faces from 2D images and solving the problem of face recognition in 3D. To facilitate the use of deep neural networks, a 3D face, normally represented as a 3D mesh of vertices and its corresponding surface texture, is remapped to image-like square isomaps by a conformal mapping. Based on previous work, we assume that face recognition benefits more from texture. In this work, we focus on the surface texture and its discriminatory information content for recognition purposes. Our approach is to prepare a 3D mesh, the corresponding surface texture and the original 2D image as triple input for the recognition network, to show that 3D data is useful for face recognition. Texture enhancement methods to control the texture fusion process are introduced and we adapt data augmentation methods. Our results show that texture-map-based face recognition can not only compete with state-of-the-art systems under the same precon ditions but also outperforms standard 2D methods from recent years.
Being able to monitor the heart activity of patients during their daily life in a reliable, comfortable and affordable way is one main goal of the personalized medicine. Current wearable solutions lack either on the wearing comfort, the quality and type of the data provided or the price of the device. This paper shows the development of a Textile Sensor Platform (TSP) in the form of an electrocardiogram (ECG)-measuring T-shirt that is able to transmit the ECG signal to a smartphone. The development process includes the selection of the materials, the design of the textile electrodes taking into consideration their electrical characteristics and ergonomy, the integration of the electrodes on the garment and their connection with the embedded electronic part. The TSP is able to transmit a real-time streaming of the ECG-signal to an Android smartphone through Bluetooth Low Energy (BLE). Initial results show a good electrical quality in the textile electrodes and promising results in the capture and transmission of the ECG signal. This is still a working- progress and it is the result of an interdisciplinary master project between the School of Informatics and the School of Textiles & Design of the Reutlingen University.
In dieser Arbeit werden drei verschiedene Testumgebungen vorgestellt, welche in ein iteratives Vorgehen einfließen, um die Entwicklung von Augmented-Reality-Anwendungen zur Darstellung von autonomen Fahrfunktionen zu unterstützen.
Gestaltungsentwürfe und Softwareentwicklungen können in den Testumgebungen für unterschiedliche Zielsetzungen von Personenbefragungen vorgestellt und bewertet werden. Das entwicklungsbegleitende Testen ermöglicht eine frühzeitige Identifizierung von Änderungshinweisen, welche für einen gültigen Lösungsentwurf eingearbeitet werden können. Die entwickelten Testumgebungen sind ein verkleinertes Modell, ein Fahrsimulator und ein reales Fahrzeug. Eigenschaften, Funktionen und Aufbauten resultieren aus Erkenntnissen der Literatur und Erfahrungen aus ersten Entwicklungen. Diese und die Einsatzmöglichkeiten werden mit dieser Arbeit aufgezeigt.
Virtual prototyping of integrated mixed-signal smart-sensor systems requires high-performance co-simulation of analog frontend circuitry with complex digital controller hardware and embedded real-time software. We use SystemC/TLM 2.0 in combination with a cycle-count accurate temporal decoupling approach to simulate digital components and firmware code execution at high speed while preserving clock cycle accuracy and, thus, real-time behavior at time quantum boundaries. Optimal time quanta ensuring real-time capability can be calculated and set automatically during simulation if the simulation engine has access to exact timing information about upcoming communication events. These methods fail in case of non-deterministic, asynchronous events resulting in a possibly invalid simulation result. In this paper, we propose an extension of this method to the case of asynchronous events generated by blackbox sources from which a-priori event timing information is not available, such as coupled analog simulators or hardware in the loop. Additional event processing latency and/or rollback effort caused by temporal decoupling is minimized by calculating optimal time quanta dynamically in a SystemC model using a linear prediction scheme. For an example smart-sensor system model, we show that quasi- periodic events that trigger activities in temporally decoupled processes are handled accurately after the predictor has settled.
When a bonding wire becomes too hot, it fuses and fails. The ohmic heat that is generated in the wire can be partially dissipated to a mold package. For this cooling effect the thermal contact between wire and package is an important parameter. Because this parameter can degrade over lifetime, the fusing of a bonding wire can also occur as a long-term effect. Another important factor is the thermal power generated in the vicinity of the bond pads. Nowadays, the reliability of bond wires relies on robust dimensioning based on estimations. Smaller package sizes increase the need for better predictive methods.
The Bond Calculator, a new thermo-electrical simulation tool, is able to predict the temperature profiles along bond wires of arbitrary dimensions in dependence on the applied arbitrary transient current profile, the mold surrounding the wire, and the thermal contact between wire and mold.
In this paper we closely investigated the spatial temperature profiles along different bond wires in air in order to make a first step towards the experimental verification of the simulation model. We are using infrared microscopy in order to measure the thermal radiation generated along the bond wire. This is easier to perform quantitatively in air than in the mold package, because of the non-negligible absorbance of the mold material in the infrared wavelength region.
Autism spectrum disorders (ASD) affect a large number of children both in the Russian Federation and in Germany. Early diagnosis is key for these children, because the sooner parents notice such disorders in a child and the rehabilitation and treatment program starts, the higher the likelihood of his social adaptation. The difficulties in raising such a child lie in the complexity of his learning outside of children's groups and the complexity of his medical care. In this regard, the development of digital applications that facilitate medical care and education of such children at home is important and relevant. The purpose of the project is to improve the availability and quality of healthcare and social adaptation at home of children with ASD through the use of digital technologies.
The 17 SDGs, as agreed upon by the international community, are designed to be implemented across all levels of human activity. Alongside the level of international politics, this also includes the local levels, national politics, wider society, and the economic sphere. Many channels are called on to further implementation, including the transfer of technology to developing and emerging countries. As the patent holders, this must include the active participation of companies. While the literature examines the important role of technology transfer in North-South business-to-business (B2B) partnerships, studies on the technology transfer between European and African companies are scarce. Therefore, in this study we use original data from 26 interviews conducted with managers engaged in sales partnerships between German manufacturers and their distributors in African markets to examine the existence and forms of technology transfer. We find that training and marketing excellence are the predominant forms of technology transfer and based on that suggest a refinement of established frameworks on B2B technology transfer.