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The aim of this paper is to show to what extent Artificial Intelligence can be used to optimize forecasting capability in procurement as well as to compare AI with traditional statistic methods. At the same time this article presents the status quo of the research project ANIMATE. The project applies Artificial Intelligence to forecast customer orders in medium-sized companies.
Precise forecasts are essential for companies. For planning, decision making and controlling. Forecasts are applied, e.g. in the areas of supply chain, production or purchasing. Medium-sized companies have major challenges in using suitable methods to improve their forecasting ability.
Companies often use proven methods such as classical statistics as the ARIMA algorithm. However, simple statistics often fail while applied for complex non-linear predictions.
Initial results show that even a simple MLP ANN produces better results than traditional statistic methods. Furthermore, a baseline (Implicit Sales Expectation) of the company was used to compare the performance. This comparison also shows that the proposed AI method is superior.
Until the developed method becomes part of corporate practice, it must be further optimized. The model has difficulties with strong declines, for example due to holidays. The authors are certain that the model can be further improved. For example, through more advanced methods, such as a FilterNet, but also through more data, such as external data on holiday periods.
We propose a method for recognizing dynamic gestures using a 3D sensor. New aspects of the developed system include problem-adapted data conversion and compression as well as automatic detection of different variants of the same gesture via clustering with a suitable metric inspired by Jaccard metric. The combination of Hidden Markov Models and clustering leads to robust detection of different executions based on a small set of training data. We achieved an increase of 5% recognition rate compared to regular Hidden Markov Models. The system has been used for human-machine interaction and might serve as an assistive system in physiotherapy and neurological or orthopedic diagnosis.
Urban platforms are essential for smart and sustainable city planning and operation. Today they are mostly designed to handle and connect large urban data sets from very different domains. Modelling and optimisation functionalities are usually not part of the cities software infrastructure. However, they are considered crucial for transformation scenario development and optimised smart city operation. The work discusses software architecture concepts for such urban platforms and presents case study results on the building sector modelling, including urban data analysis and visualisation. Results from a case study in New York are presented to demonstrate the implementation status.
Additive manufacturing (AM) is a promising manufacturing method for many industrial sectors. For this application, industrial requirements such as high production volumes and coordinated implementation must be taken into account. These tasks of the internal handling of production facilities are carried out by the Production Planning and Control (PPC) information system. A key factor in the planning and scheduling is the exact calculation of manufacturing times. For this purpose we investigate the use of Machine Learning (ML) for the prediction of manufacturing times of AM facilities.
This study describes a non-contact measuring and system identification procedure for evaluating inhomogeneous stiffness and damping characteristics of the annular ligament in the physiological amplitude and frequency range without the application of large static external forces that can cause unnatural displacements of the stapes. To verify the procedure, measurements were first conducted on a steel beam. Then, measurements on an individual human cadaveric temporal bone sample were performed. The estimated results support the inhomogeneous stiffness and damping distribution of the annular ligament and are in a good agreement with the multiphoton microscopy results which show that the posterior-inferior corner of the stapes footplate is the stiffest region of the annular ligament.
Dieser Bericht fasst die wesentlichen Arbeiten und Ergebnisse zusammen, die in dem Verbundvorhaben „GalvanoFlex_BW“ im Kalenderjahr 2018 durchgeführt und erzielt wurden. Dazu lässt sich zunächst sagen, dass die Messwertaufnahme und –auswertung abgeschlossen ist. Es wurden verschiedene Messkampagnen bei der Fa. NovoPlan durchgeführt. Bei C&C Bark konnte man teilweise auf bestehende Daten zurückgreifen, die punktuell durch weitere Messungen ergänzt wurden. Bei der Fa. Hartchrom konnten aufgrund von Personalmangel keine Messungen durchgeführt werden. Die aufgenommenen Daten wurden in eine Effizienzbewertung überführt, aus der im Folgenden allgemeine Aussagen abgeleitet werden sollen. Dazu ist ein Simulationsprogramm aufgesetzt worden, das in der Lage ist, Prozessketten energetisch abzubilden und zu optimieren. Zudem sollen aus den Messdaten verbesserte Profile für den Wärmebedarf in den Unternehmen entwickelt werden, die daraufhin der KWK-Optimierung zur Verfügung gestellt werden. Im Zuge der Entwicklung und Bewertung stromoptimierter KWK- Strategien ist ein bestehendes Simulationsmodell entsprechend weiterentwickelt worden. Konkret wurde das Modell um eine verbesserte Lastprognose für Strom und Wärme für Industriebetriebe ergänzt, und das Optimierungsverfahren wurde um eine zweite Dimension erweitert. Während bislang allein die Optimierung der Eigenstromdeckung mit einer Begrenzung der BHKW-Starts als Nebenbedingung möglich war, ist jetzt die Kappung der elektrischen Lastspitze zusätzlich in der Zielfunktion integriert. Gerade bei Industrieunternehmen lässt sich auf diese Weise eine weitere, zum Teil nicht unerhebliche Energiekosteneinsparung erreichen, was durch die ersten Berechnungen anhand der drei im Reallabor vertretenden Betriebe bestätigt wird. Die Ergebnisse werden unter AP 8 (Umsetzung) diskutiert. Der Dialog mit weiteren Unternehmen und Institutionen außerhalb des Vorhabens konnte über die Branchenplattfom weitergeführt werden. In 2018 wurden zwei Veranstaltungen dieser Art durchgeführt, und im Frühjahr 2019 wird ein weiterer Workshop zu diesem Thema durchgeführt. Die sozialwissenschaftliche Begleitforschung wurde mit der zweiten Phase der Firmenbefragungen ebenfalls planmäßig weitergeführt. Mit Blick auf die Umsetzung eines BHKW-Konzeptes haben sich dabei zwei wichtige Punkte wie folgt gezeigt: Zum einen muss die umsetzende Firma eine gewisse „Energieeffizienz-Reife“ besitzen, die sich u.a. in der Erfahrung bei der Durchführung von Energieeffizienzmaßnahmen zeigt, da die Installation eines BHKWs eine äußerst komplexe Maßnahme darstellt. Zum anderen müssen andere unternehmensspezifische Kontextfaktoren hinzukommen, wie z.B. aus anderen Gründen durchzuführende bauliche Maßnahmen, so dass gewisse zeitliche Entscheidungsfenster entstehen, in denen die Umsetzung von KWK-Maßnahmen sinnvoll sind.
IC layout automation with self-organized wiring and arrangement of responsive modules (SWARM)
(2019)
Focused on automating analog IC layout, the multi-agent-system Self-organized Wir ing and Arrangement of Responsive Modules (SWARM) combines the powers of pro-cedural generators and algorithmic optimization into a novel bottom-up meets top-down flow of supervised layout module interaction. Provoking self-organization via the effect of emergence, examples show SWARM finding even optimal placement solutions and producing constraint-compliant layout blocks which fit into a specified zone.
In Folge der gegenwärtigen Digitalisierung in der produzierenden Industrie werden Anwendungen oder Services mit potentiell positiven Auswirkungen auf Faktoren wie Effektivität und Arbeitsqualität entwickelt. Ein geeigneter Ansatz zur Stärkung motivierender Aspekte im Arbeitskontext kann Gamification darstellen. In dieser Arbeit ist die initiale Konzeption und Evaluation eines Gamification-Ansatzes für Anwender eines KI-Service zur Maschinenoptimierung dargestellt und möglichen Anforderungen an ein Konzept zur Motivationssteigerung extrahiert.
In dieser Ausarbeitung wird eine zeitliche Vorhersage von Erdbeben getroffen. Hierfür werden mit einem Datensatz aus Labor-Erdbeben Convolutional Neural Networks (CNN) trainiert. Die trainierten Netzwerke geben Vorhersagen, indem sie einen Input an seismischen Daten klassifizieren. Durch das Klassifizieren kann das CNN die zeitliche Entfernung zum nächsten Erdbeben vorhersagen. Es werden hierfür zwei Ansätze miteinander verglichen. Beim ersten Ansatz werden die Originaldaten in ein CNN gegeben. Beim zweiten Ansatz wird vor dem CNN eine Vorverarbeitung der Daten mit den Mel Frequency Cepstral Coefficients (MFCC) durchgeführt. Es zeigt sich, dass mit beiden Ansätzen eine gute Klassifikation möglich ist. Die Kombination aus MFCC und CNN liefert die besseren quantitativen Ergebnisse. Hierbei konnte eine Genauigkeit von 65 % erreicht werden.
Semi-automated image data labelling using AprilTags as a pre-processing step for machine learning
(2019)
Data labelling is a pre-processing step to prepare data for machine learning. There are many ways to collect and prepare this data, but these are usually associated with a greater effort. This paper presents an approach to semi-automated image data labelling using AprilTags. The AprilTags attached to the object, which contain a unique ID, make it possible to link the object surfaces to a particular class. This approach will be implemented and used to label data of a stackable box.
The data is evaluated by training a You Only Look Once (YOLO) net, with a subsequent evaluation of the detection results. These results show that the semi-automatically collected and labelled data can certainly be used for machine learning. However, if concise features of an object surface are covered by the AprilTag, there is a risk that the concerned class will not be recognized. It can be assumed that the labelled data can not only be used for YOLO, but also for other machine learning approaches.
Bereits zum elften Mal findet nun die Studierendenkonferenz Informatics Inside statt. Als Teil des Masterstudiengangs Human-Centered Computing organisieren Masterstudierende selbständig eine vollumfängliche wissenschaftliche Konferenz. Die Informatik ist nach wie vor ständigem Wandel unterworfen. Unsere Studierenden tragen diesem Wandel bei, indem sie in ihrer wissenschaftllichen Vertiefung aktuelle Problemstellungen durch innovative Konzepte lösen. Inzwischen ist die Informatik aber auch nicht immer sofort sichtbar. Das merken wir immer dann, wenn etwas nicht wie vorgesehen funktioniert. Das diesjährige Motto der Informatics Inside ist experience (IT);, verdeckt als Funktionsaufruf:).
In this paper, we address the novel EDP (Expert Design Plan) principle for procedural design automation of analog integrated circuits, which captures the knowledge-based design strategy of human circuit designers in an executable script, making it reusable. We present the EDP Player, which enables the creation and execution of EDPs for arbitrary circuits in the Cadence® Virtuoso® Design Environment. The tool provides a generic version of an instruction set, called EDPL (EDPLanguage), enabling emulation of a typical manual analog sizing flow. To automate the design of a Miller Operational Amplifier and to create variants of a Smart Power IC, several EDPs were implemented using this tool. Employing these EDPs leads to a strong reduction of design time without compromising design quality or reliability.
Serverless computing is an emerging cloud computing paradigm with the goal of freeing developers from resource management issues. As of today, serverless computing platforms are mainly used to process computations triggered by events or user requests that can be executed independently of each other. These workloads benefit from on-demand and elastic compute resources as well as per-function billing. However, it is still an open research question to which extent parallel applications, which comprise most often complex coordination and communication patterns, can benefit from serverless computing.
In this paper, we introduce serverless skeletons for parallel cloud programming to free developers from both parallelism and resource management issues. In particular, we investigate on the well known and widely used farm skeleton, which supports the implementation of a wide range of applications. To evaluate our concepts, we present a prototypical development and runtime framework and implement two applications based on our framework: Numerical integration and hyperparameter optimization - a commonly applied technique in machine learning. We report on performance measurements for both applications and discuss
the usefulness of our approach.
The Virtual Power Plant Neckar-Alb is a demonstration platform for operation, optimization and control of distributed energy resources, which are able to produce, store or consume electric energy. A heterogeneous set of distributed energy devices has been installed at the Campus of Reutlingen University by the Reutlingen Energy Centre (REZ) of the School of Engineering. The distributed energy devices have been combined to local microgrids and connected to an operative central power plant with additional participants. The demonstration platform serves students, researchers and industry experts for education and investigation of new technologies, devices and software.
A digital twin - a replica of energy devices - was established in the computing environment of MATLAB and Simulink. It simulates continuously their operation and is time synchronized and connected to the cenral energy management and control system of a virtual power plant. The model can be used as a platform for testing device performance in various conditions, working schedules and new optimization options.
Companies are continuously changing their strategy, processes, and information systems to benefit from the digital transformation. Controlling the digital architecture and governance is the fundamental goal. Enterprise Governance, Risk and Compliance (GRC) systems are vital for managing digital risks threatening in modern enterprises from many different angles. The most significant constituent to GRC systems is the definition of controls that is implemented on different layers of a digital Enterprise Architecture (EA). As part of the compliant aspect of GRC, the effectiveness of these controls is assessed and reported to relevant management bodies within the enterprise. In this paper, we present a metamodel which links controls to the affected elements of a digital EA and supplies a way of expressing associated assessment techniques and results. We complement a metamodel with an expository instantiation of a control compliance cockpit in an international insurance enterprise.
Business process models provide a considerable number of benefits for enterprises and organizations, but the creation of such models is costly and time-consuming, which slows down the organizational adoption of business process modeling. Social paradigms pave new ways for business process modeling by integrating stakeholders and leveraging knowledge sources. However, empirical research about the impact of social paradigms on costs of business process modeling is sparse. A better understanding of their impact could help to reduce the cost of business process modeling and improve decision-making on BPM activities. The paper constributes to this field by reporting about an empirical investigation via survey research on the perceived influence of different cost factors among experts. Our results indicate that different cost components, as well as the use of social paradigms, influence cost.
Due to the consequential impact of technological breakdowns, companies have to be prepared to deal with breakdowns or even better prevent them. In today's information technology, several methods and tools exist to downscale this concern. Therefore, this paper deals with the initial determination of a resilient enterprise architecture supporting predictive maintenance in the information technology domain and furthermore, concerns several mechanisms on how to reactively and proactively secure the state of resiliency on several abstraction levels. The objective of this paper is to give an overview on existing mechanisms for resiliency and to describe the foundation of an optimized approach, combining infrastructure and process mining techniques.
This book contains the proceedings of the KES International conferences on Innovation in Medicine and Healthcare (KES-InMed-19) and Intelligent Interactive Multimedia Systems and Services (KES-IIMSS-19), held on 17–19 June 2019 and co-located in St. Julians, on the island of Malta, as part of the KES Smart Digital Futures 2019 multi theme conference.
The major areas covered by KES-InMed-19 include: Digital IT Architecture in Healthcare; Advanced ICT for Medical and Healthcare; Biomedical Engineering, Trends, Research and Technologies and Healthcare Support System. The major areas covered by KES-IIMSS-19 were: Interactive Technologies; Artificial Intelligence and Data Analytics; Intelligent Services and Architectures and Applications.
This book is of use to researchers in these vibrant areas, managers, industrialists and anyone wishing to gain an overview of the latest research in these fields.
The rise of digital technologies has become an important driver for change in multiple industries. Therefore, firms need to develop digital capabilities to manage the transformation process successfully. Prior research assumes that the development of a specific set of digital capabilities leads to higher digital maturity. However, a measurement framework for digital maturity does not exist in scholarly work. Therefore, this paper develops a conceptualization and measuremnent model for digital maturity.
In 2017, Philips' goal was to use innovation to improve the lives of three billion people a year by 2025. To achieve that, the company was shifting from selling medical products in a transactional manner to providing integrated healthcare solutions based on digital health technology. Based on our interviews with 23 executives at Philips, the case examines the two directions of the transformation required by this shift: externally, Philips worked on transforming how healthcare was conducted. Healthcare professionals would have to change the way they worked and reimbursement schemes needed to change to incentivize payers, providers, and patients in vastly different ways. Internally, Philips needed to redesign how its employees worked. The company componentized its business, introduced digital platforms, and co-created integrated solutions with the various stakeholders of the healthcare industry. In other words: Philips was transforming itself in order the reinvent healthcare in the digital age.
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.
Continuous refactoring is necessary to maintain source code quality and to cope with technical debt. Since manual refactoring is inefficient and error prone, various solutions for automated refactoring have been proposed in the past. However, empirical studies have shown that these solutions are not widely accepted by software developers and most refactorings are still performed manually. For example, developers reported that refactoring tools should support functionality for reviewing changes. They also criticized that introducing such tools would require substantial effort for configuration and integration into the current development environment.
In this paper, we present our work towards the Refactoring-Bot, an autonomous bot that integrates into the team like a human developer via the existing version control platform. The bot automatically performs refactorings to resolve code smells and presents the changes to a developer for asynchronous review via pull requests. This way, developers are not interrupted in their workflow and can review the changes at any time with familiar tools. Proposed refactorings can then be integrated into the code base via the push of a button. We elaborate on our vision, discuss design decisions, describe the current state of development, and give an outlook on planned development and research activities.
The Eleventh International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2019), held between June 02, 2019 to June 06, 2019 - Athens, Greece, continued a series of international events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base technologies and content processing, as well as specifics in applications domains databases.
Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and agent technologies, as well as from the generalization of the XML adoption.
High-speed communications and computations, large storage capacities, and loadbalancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods.
Evolution on e-business, ehealth and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the ‘de facto’ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology.
We welcomed academic, research and industry contributions. The conference had the followingtracks:
Knowledgeanddecisionbase
Databasestechnologies
Datamanagement
GraphSM: Large-scale Graph Analysis, Management and Applications
This paper presents an approach for the implementation of a modular and scalable power electronics device for controlling electric drives in the field of electric vehicles using wide bandgap semiconductor devices. The main idea is to achieve the required output currents or voltages by connecting adequately designed hardware modules in parallel or in series. This particular design is based on the fact that the single modules generate a continuous and specified output voltage from a given dc voltage, e.g. an intermediate circuit or battery voltage. The main benefit is, that different current or voltage requirements can be satisfied based on a single module thus decreasing development and production costs. The current paper focuses on the connection in parallel of such modules. A control architecture is illustrated and a first proof of concept is given.
Creativity, problem-solving skills and the ability for collaborative work are considered key competences for facing the challenges of the 21st century. Children are born with an inherent creativity that decreases throughout their school careers. A research team of designers and educators investigates whether the implementation of Design Thinking (DT) in textile education in German elementary schools is a suitable method to preserve children’s creativity. Initial surveys with teachers and pilot studies in elementary schools showed high motivation and openmindedness towards DT in classroom. The challenge will be to develop suitable teaching modules for elementary schools of the federal state Baden Württemberg.
Kreativität, Problemlösekompetenz und kollaboratives Arbeiten werden in zahlreichen internationalen Studien sowie von der OECD (2017) als Schlüsselkompetenzen des 21. Jahrhunderts definiert. Ungeachtet dessen orientieren sich viele Lehr-Lern Methoden noch immer an der Vermittlung vordefinierter Lösungswege. Studien im Sekundarbereich in den USA, Deutschland und Asien zeigen, dass Design Thinking durch seine kreativen und kollaborativen Elemente zu einem nachhaltigeren Lernerfolg bei Lernenden und seitens der Lehrenden zu höherer Zufriedenheit bei der Vermittlung der Inhalte führen kann.
Kernelemente des Design Thinking sind: der iterative Prozess mit seinen Phasen Verstehen, Beobachten, Sichtweisen definieren, Ideen finden, Prototypen bauen, Testen; die Arbeit in multidisziplinären Teams sowie die Nutzerorientierung bei der Definition der Aufgabe (Brown, 2009). Die Phasen des iterativen Prozesses weisen eine hohe Kongruenz mit den prozessorientierten Kompetenzen des Faches Kunst/Werken und des Sachunterrichts gemäß dem Bildungsplan für Grundschulen (Ministerium für Kultus, Jugend und Sport Baden Württemberg, 2016) auf. Im Rahmen eines interdisziplinären Promotionsvorhabens an der PH Freiburg soll, basierend auf einem qualitativen Forschungsdesign, untersucht werden, inwieweit sich Design Thinking eignet, Kreativität, Problemlösekompetenz und kollaboratives Arbeiten von Grundschulkindern in Kunst/Werken und im Sachunterricht aus Sicht von Lehrpersonen zu fördern. Vorstudien mit Lehrpersonen und Ausbildungslehrkräften, bei welchen Erhebungen per Fragebogen nach Teilnahme an einem Design Thinking Workshop eingesetzt wurden, sowie zwei Pilotunterrichtseinheiten an Grundschulen mit Teilnehmender Beobachtung, Experteninterviews und Kinderinterviews in Kleingruppen, zeigen erste Ergebnisse.
To remain competitive in a fast changing environment, many companies started to migrate their legacy applications towards a Microservices architecture. Such extensive migration processes require careful planning and consideration of implications and challenges likewise. In this regard, hands-on experiences from industry practice are still rare. To fill this gap in scientific literature, we contribute a qualitative study on intentions, strategies, and challenges in the context of migrations to Microservices. We investigated the migration process of 14 systems across different domains and sizes by conducting 16 in-depth interviews with software professionals from 10 companies. Along with a summary of the most important findings, we present a separate discussion of each case. As primary migration drivers, maintainability and scalability were identified. Due to the high complexity of their legacy systems, most companies preferred a rewrite using current technologies over splitting up existing code bases. This was often caused by the absence of a suitable decomposition approach. As such, finding the right service cut was a major technical challenge, next to building the necessary expertise with new technologies. Organizational challenges were especially related to large, traditional companies that simultaneously established agile processes. Initiating a mindset change and ensuring smooth collaboration between teams were crucial for them. Future research on the evolution of software systems can in particular profit from the individual cases presented.
While Microservices promise several beneficial characteristics for sustainable long-term software evolution, little empirical research covers what concrete activities industry applies for the evolvability assurance of Microservices and how technical debt is handled in such systems. Since insights into the current state of practice are very important for researchers, we performed a qualitative interview study to explore applied evolvability assurance processes, the usage of tools, metrics, and patterns, as well as participants’ reflections on the topic. In 17 semi-structured interviews, we discussed 14 different Microservice-based systems with software professionals from 10 companies and how the sustainable evolution of these systems was ensured. Interview transcripts were analyzed with a detailed coding system and the constant comparison method.
We found that especially systems for external customers relied on central governance for the assurance. Participants saw guidelines like architectural principles as important to ensure a base consistency for evolvability. Interviewees also valued manual activities like code review, even though automation and tool support was described as very important. Source code quality was the primary target for the usage of tools and metrics. Despite most reported issues being related to Architectural Technical Debt (ATD), our participants did not apply any architectural or service-oriented tools and metrics. While participants generally saw their Microservices as evolvable, service cutting and finding an appropriate service granularity with low coupling and high cohesion were reported as challenging. Future Microservices research in the areas of evolution and technical debt should take these findings and industry sentiments into account.
Small and Medium Enterprises (SMEs) which play substantial role in the development of any economy have been on the rise in the recent periods. Consequently, these enterprises are faced with a myriad of challenges which could potentially be solved through adoption of technology. Nonetheless, it has been observed that the new technological uptake among SMEs remains limited with the majority of them opting to maintain the status quo with regards to technology awareness and innovation strategies.
In a literature review, this paper explores three major dynamics curtailing adoption of new technologies by SMEs in the manufacturing: Knowledge absorptive capacity and management factors, organisational structures as well as technological awareness. Firstly, with regards to knowledge absorptive capacity and management factors, this study shows how these factors drive innovation potentials in SMEs.
Secondly, with regards to technological awareness factors, this study documents how perceived usefulness, costs, network and infrastructure, education and skills, training and attitude as well as knowledge influence adoption of new technologies among SMEs in the world. Lastly, the study concludes by analysing how organisational structures drive innovation potentials of SMEs in the wake of swift and profound technological changes in the market.
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.
The energy turnaround, digitalization and decreasing revenues forces enterprises in the energy domain to develop new business models. Business models for renewable energy are compound on different logic than business models for larger scale power plants. Following a design science research approach, we examined the business models of three enterprises in the energy domain in a first step. We identified that these business models result in complex ecosystems with multiple actors and difficult relationships between them. One cause is the fast changing and complicated state regulation in Germany. In order to solve the problem, we captured together with the partners of the enterprises the requirements in a second phase. Further we developed the prototype Business Model Configurator (BMConfig) based on the e3Value Ontology on the metamodelling platform ADOxx. We demonstrate the feasibility of our approach in business model of energy efficiency service based on smart meter data.
In a time of upheaval and digitalization, new business models for companies play an important role. Decentralized power generation and energy efficiency indicators to achieve climate goals and to reduce global warming are currently forcing energy companies to develop new business models. In recent years, many methods of business model development have been introduced to create new business ideas. But what are the obstacles in implementing these business models in the energy sector to develop new business opportunities? And what challenges do companies face in this respect? To answer this question, a systematic literature review was conducted in this paper. As a result, eight categories were identified which summarise the main barriers for the implementation of new business models in the energy domain.
We introduce IPA-IDX – an approach to handle index modifications modern storage technologies (NVM, Flash) as physical in-place appends, using simplified physiological log records. IPA-IDX provides similar performance and longevity advantages for indexes as basic IPA [5] does for tables. The selective application of IPA-IDX and basic IPA to certain regions and objects, lowers the GC overhead by over 60%, while keeping the total space overhead to 2%. The combined effect of IPA and IPA-IDX increases performance by 28%.
Because of saturated markets and of the low profit margins in the sales of cars, car manufacturers focus more and more on profitable product related services. This paper deals with the question how to classify product related services in the automotive industry and which characteristic product related services are offered to the end-users (consumers) in a standardized format. Two research studies on the provided product related services in 2010 und 2017 by 15 car manufacturers and 20 exemplary automotive brands in Germany revealed that the application degree by the OEM (original equipment manufacturers) in these years increased considerably. While in 2010, the average range of services only amounted to 33%, the value in the automotive industry increased until 2017 to 57%.
Mit der Überarbeitung der DIN EN 50173 (VDE 0800-173) Serie, wurden unter anderem die optischen Übertragungsstreckenklassen ersatzlos gestrichen. Um die so entstandene Lücke zu schließen, hat das deutsche Gremium DKE GUK 715.3 „Informationstechnische Verkabelung von Gebäudekomplexen“ neue Klassen erarbeitet, die in der DIN VDE 0800- 173-100 „Klassifizierung von Lichtwellenleiter-Übertragungsstrecken“ im Juni 2019 veröffentlicht wurden. Die Norm klassifiziert Lichtwellenleiter Übertragungsstrecken für anwendungsneutrale Kommunikationskabelanlagen nach DIN EN 50173-1.
Sie dient Benutzern, eine breite Palette von Anwendungen zu ermöglichen, die Auswahl des Verkabelungssystems zu erleichtern, eine zukunftssichere Klassifizierung von LWL-Verkabelungen zu generieren und dazu, Systemanforderungen zu beschreiben.
Die in der Norm definierten Klassen beschreiben die Anforderungen an die Übertragungsstrecken und basieren auf einer maximal zulässigen Einfügedämpfung in dB für maximale Übertragungsstreckenlängen, wobei zusätzlich das Bandbreitenlängenprodukt berücksichtigt wird.
Der Beitrag liefert einen Überblick über die Norm und zeigt Anwendungsbeispiele auf.
Workflow driven support systems in the peri-operative area have the potential to optimize clinical processes and to allow new situation-adaptive support systems. We started to develop a workflow management system supporting all involved actors in the operating theatre with the goal to synchronize the tasks of the different stakeholders by giving relevant information to the right team members. Using the OMG standards BPMN, CMMN and DMN gives us the opportunity to bring established methods from other industries into the medical field. The system shows each addressed actor their information in the right place at the right time to make sure every member can execute their task in time to ensure a smooth workflow. The system has the overall view of all tasks. Accordingly, a workflow management system including the Camunda BPM workflow engine to run the models, and a middleware to connect different systems to the workflow engine and some graphical user interfaces to show necessary information or to interact with the system are used. The complete pipeline is implemented with a RESTful web service. The system is designed to include different systems like hospital information system (HIS) via the RESTful web service very easily and without loss of data. The first prototype is implemented and will be expanded.
This paper discusses the optimal control problem for increasing the energy efficiency of induction machines in dynamic operation including field weakening regime. In an offline procedure optimal current and flux trajectories are determined such that the copper losses are minimized during transient operations. These trajectories are useful for a subsequent online implementation.
In this work design rules for a novel brushless excitation system for externally excited synchronous machines are discussed. The concept replaces slip rings with a fullbridge active rectifier and a controller mounted on the rotor. An AC signal induced from the stator is used to charge the rotor DC link. The DC current for the rotor excitation is provided from this DC link source. Finite element analysis of an existing machine is used to analyze the practicability of the excitation system.
A novel brushless excitation concept for synchronous machines with a rotating power converter is proposed in this paper. The concept does not need an auxiliary winding or any other modification to the machine structure apart from an inverter with a DC link capacitor and a controller on the rotor. The power required for the rotor excitation is provided by injecting harmonics into the stator winding. Thus, a voltage in the field coil is induced. The rotor inverter is controlled such that the alternating current charges the DC link capacitor. At the same time the inverter supplies the DC field current to the field coil. The excitation concept is first developed in theory, then presented using an analytical model and FEA, and lastly investigated with a prelimininary experimental setup.
Digital technologies are moving into physical products. Smart cars, connected lightbulbs and data-generating tennis rackets are examples of previously “pure” physical products that turned into “digitized products”. Digitizing products offers many use cases for consumers that will hopefully persuade them to buy these products. Yet, as revenues from selling digitized products will remain small in the near future, digitized product manufacturers have to look for other sources of benefits. Producer-side use cases describe how manufacturers can benefit internally from the digitized products they produce. Our article identifies three categories of such use cases: product-, service-, and process-related ones.
The goal of the presented project is to develop the concept of home e-health centers for barrier-free and cross-border telemedicine. AAL technologies are already present on the market but there is still a gap to close until they can be used for ordinary patient needs. The general idea needs to be accompanied by new services, which should be brought together in order to provide a full coverage of service for the users. Sleep and stress were chosen as predominant influence in the population. The executed scientific study of available home devices analyzing sleep has provided the necessary to select appropriate devices. The first choice for the project implementation is the device EMFIT QS+. This equipment provides a part of a complete system that a home telemedical hospital can provide at a level of precision and communication with internal and/or external health services.
Ein virtuelles Kraftwerk ist ein Verbund von Energieanlagen, koordiniert von einem gemeinsamen Leitsystem, um eine bessere Ausnutzung wetterabhängiger Energiequellen oder die gemeinsame Vermarktung von erzeugtem Strom zu ermöglichen. Der Demonstrator Virtuelles Kraftwerk Neckar-Alb ist eine Demonstrationsplattform für Forschung und Lehre, die Anlagen auf dem Campus der Hochschule Reutlingen und verteilte Anlagen in der Region Neckar-Alb integriert.
Novel design for a coreless printed circuit board transformer realizing high bandwidth and coupling
(2019)
Rogowski coils offer galvanic isolation and can measure alternating currents with a high bandwidth. Coreless printed circuit board (PCB) transformers have been used as an alternative to limit the additional stray inductance if a Rogowski coil can not be attached to the circuit. A new PCB transformer layout is proposed to reduce cost, decrease additional stray inductance, increase the bandwidth of current measurements and simplify the integration into existing designs.
Improved inductive feed-forward for fast turn-on of power semiconductors during hard switching
(2019)
A transformer is used to increase the gate voltage during turn-on, thus reducing the necessary bias voltage of the gate driver. Counteracting the voltage dependency of the gate capacitance of high-voltage power devices, faster transitions are possible. The additional transformer only slighly increases the over-voltage during turn-off.
In this paper, an approach is introduced how reinforcement learning can be used to achieve interoperability between heterogeneous Internet of Things (IoT) components. More specifically, we model an HTTP REST service as a Markov Decision Process and adapt Q-Learning to the properties of REST so that an agent in the role of an HTTP REST client can learn the semantics of the service and, especially an optimal sequence of service calls to achieve an application specific goal. With our approach, we want to open up and facilitate a discussion in the community, as we see the key for achieving interoperability in IoT by the utilization of artificial intelligence techniques.
Interoperability is an important topic in the Internet of Things (IoT), because this domain incorporates diverse and heterogeneous objects, communication protocols and data formats. Many models and classification schemes have been proposed to make the degree of interoperability measurable - however only on the basis of a hierarchical scale. In the course of this paper we introduce a novel approach to measure the degree of interoperability using a metric scaled quantity. We consider IoT as a distributed system, where interoperable objects exchange messages with each other. Under this premise, we interpret messages as operation calls and formalize this view as a causal model. The analysis of this model enables us to quantify the interoperable behavior of communicating objects.
Increasing flexibility, greater transparency and faster adaptability play a key role in the development of future intralogistics. Ever-changing environmental conditions require easy extensibility and modifiability of existing bin systems. This research project explores approaches to transfer the Internet of Things (IoT) paradigm to intralogistics. This allows a synchronization of the material and information flow. The bin is enabled by the implementation of adequate hardware and software components to capture, store, process and forward data to selected system subscribers. Monitoring the processes in the intralogistics by means of the smart bin system ensures the implementation of appropriate actions in case of defined deviations. By using explorative expert interviews with representatives from the automotive and pharmaceutical industries, seven practical application scenarios were defined. On this basis, the requirements of smart bin systems were examined. For each individual case of application, a system model was created in order to obtain an overview of the system components and thus reveal similarities and differences. Based on the similarities of the system models, a general requirement profile was derived. After the hardware components of the bin system had been determined, a utility analysis was carried out to find the adequate IoT software. The utility analysis was conducted with a focus on data acquisition and data transfer, data storage, data analysis, data presentation as well as authorization management and data security. The results show that there is great interest in easily expandable and modifiable bin systems, as in all cases, the necessary information flow in the existing bin system has to be improved by means of new IoT hardware and software components.
The global demand for individualized products leading to decreasing production batch sizes requires innovative approaches how to organize production and logistics systems in a dynamic manner. Current material flow systems mainly rely on predefined system structures and processes, which result in a huge increase of complexity and effort for system and process changes to realize an optimized production and material provision of individualized products. Autonomous production and logistics entities in combination with intelligent products or logistic load carriers following the vision of the “Internet of Things” offer a promising solution for mastering this complexity based on autonomous, decentralized and target size-optimized decision making and structure formation without the need for predefined processes and central decision-making bodies. Customer orders are going to prioritize themselves and communicate directly with the required production and logistics resources. Bins containing the required materials are going to communicate with the conveyors or workers of the respective intralogistics system organizing and controlling the material flow to the autonomously selected workstation. A current research project is the development of a collaborative tugger train combing the potential of automation and human-robot collaboration in intralogistics. This tugger train is going to be integrated into a self organized intralogistics scenario involving individualized customer orders (low to high batch sizes). To classify the application of self-organization within intralogistics systems, a criteria catalogue has been developed. The application of this criteria catalogue will be demonstrated on the example of a self-organization scenario involving the collaborative tugger train and an intelligent bin system.
The 21st century: an era where emojis and hashtags find their way into every sentence, where taking selfies, live tweeting and mining bitcoin are the norm, and where Insta-culture dictates what we say and do. This is the era into which the digital native was born. With so many changes in every aspect of our lives, how is it that one of the most influential aspects, our education, has remained unchanged? Our education system not only fails to appeal to today’s students, but more importantly, it fails to equip them with the skills required in the 21st Century. It is thus of no surprise that industries feel graduates entering the workplace lack skills in critical thinking, problem solving and self-directed learning. AI, machine learning and big data: Tools and mechanisms we so eagerly incorporate to create smart factories yet are hesitant to use elsewhere. Gamification and games have shown great results in education and training; with most research suggesting a stronger focus on personalization and adaptation. When combined with analytics and machine learning, the potential of games is yet to be realized. A real-time adaptive game would not only always present an appropriate degree of challenge for the individual but would allow for a shift in focus from the recitation of facts, to the application of information filtered to solve the particular problem at hand. South Africa, a country faced with a severe skills gap, could benefit greatly from games. If used correctly, they may just offer a desperately needed contribution toward equipping both current and future employees with the skills needed to survive in the 21st century. This paper explores the feasibility of using such games for enhanced knowledge dissemination and the upskilling of the workforce.
Due to Industry 4.0, the full value creation has the chance to undergo a fundamental technological transformation, the realisation of which, however, requires the commitment of every company for its own benefit. The new approaches of Industry 4.0 are often hardly evaluated, let alone proven, so that SMEs in particular often cannot properly estimate the potentials and risks, and often waiting too long with the migration towards Industry 4.0. In addition, they often do not pursue an integrated concept in order to identify possible potentials through changes in their business models. . As part of the research project "GEN-I 4.0 – Geschäftsmodell-Entwicklung für die Industrie 4.0” ", the ESB Business School at Reutlingen University of Applied Sciences and the Fraunhofer Institute for Industrial Engineering and Organization FHG IAO were engaged by the Baden-Württemberg Foundation from 2016 to 2018 to develop tools and an approach how the local economy can develop digital business models for itself in a methodical, beneficial and targeted manner. Through international analyses and interviews GEN-I 4.0 gained and concretized the knowledge required for the evaluation and selection of solutions and approaches for the transfer to develop digital business models. Together with the know-how of the project partners on Industry 4.0 and business model development, the findings were incorporated into the development of two software tools with which SMEs are shown the potentials of Industry 4.0 for their individual business model, online and in selfassessment, and given a comprehensive structured, concrete approach to development, as well as their individual risk. Users of the tools are supported by the selected platform for the networking of different players to implement innovative business models accompanied by coaching concepts for the companies in the follow-up and implementation of the assessment results.
Changing requirements and qualification profiles of employees, increasingly complex digital systems up to artificial intelligence, missing standards for the seamless embedding of existing resources and unpredictable return on investments are just a few examples of the challenges of an SME in the age of digitalisation. In most cases there is a lack of suitable tools and methods to support companies in the digital transformation process in the value creation processes, but also of training and learning materials. A European research project (BITTMAS - Business Transformation towards Digitalisation and Smart systems, ERASMUS+, 2016-1 DE02-KA202-003437) with international partners from science, associations and industry has addressed this issue and developed various methods and instruments to support SMEs. Within the scope of a literature search, 16 suitable digitalisation concepts for production and logistics were identified. In the following, a learning platform with a literature database with multivariable sorting options according to branches and keywords of digitalisation, a video gallery with basic and advanced knowledge and a glossary were created in order to provide the user with consolidated and structured specialist knowledge. The 16 identifying concepts for transforming value-added processes in the context of digitalisation were transferred to a learning platform using developed learning paths in coaching and training to online course modules including test questions. A maturity model was developed and implemented in a self assessment tool for the analysis to identify the potential of digitalisation in production and logistics in relation to the current technological digitalisation level of the company. As a result, the user receives one or more of the 16 potential digitalisation concepts suggested or the delta for the necessary, not yet available enabler technologies is presented as a spider diagram. For a successful implementation of the identified suitable digitalisation concepts in production and logistics, a further tool was developed to identify supplementary requirements for all company divisions and stakeholders in relation to the "digital transformation" in the form of a self-evaluation. This paper presents the methods and tools developed, the accompanying learning materials and the learning platform.
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.
Nowadays, the demand for a MEMS development/design kit (MDK) is even more in focus than ever before. In order to achieve a high quality and cost effectiveness in the development process for automotive and consumer applications, an advanced design flow for the MEMS (micro electro mechanical systems) element is urgently required. In this paper, such a development methodology and flow for parasitic extraction of active semiconductor devices is presented. The methodology considers geometrical extraction and links the electrically active pn junctions to SPICE standard library models and subsequently extracts the netlist. An example for a typical pressure sensor is presented and discussed. Finally, the results of the parasitic extraction are compared with fabricated devices in terms of accuracy and capability.
Rapidly growing population and increasing amount of shipments induced by the e-commerce are two of the main reasons for the constantly rising urban freight traffic. Cities are therefore overwhelmed by a growing stream of goods and the available infrastructure, shared between people and goods traffic, often reached its maximum capacity. Phenomena such as traffic congestion, pollution and lack of space are direct consequences of this trend and their impact on the quality of life in the city is not negligible. City administrations are keen to evaluate innovative city logistics concepts and adopt alternative solutions, to overcome the challenges posed by such a dynamic environment, constrained in existing infrastructure. In this paper, a heuristic method based on the utility analysis is presented. Thanks to a modular approach accounting for stakeholders´ requirements, possible different scenarios and available technologies, the development of new city logistic concepts is supported. The proposed method is then applied to a case study concerning the city of Reutlingen (Germany). Results are presented and a brief discussion leads to the conclusion.
The metric and qualitative analysis of models of the upper and lower dental arches is an important aspect of orthodontic treatment planning. Currently available eLearning systems for dental education only allow access to digital learning materials, and do not interactively support the learning progress. Moreover, to date no study compared the efficiency of learning methods based on physical or digital study models. For this pilot study, 18 dental students were separated into two groups to investigate whether the learning success in study model analysis with an interactive elearning system is higher based on digital models or on conventional plaster models. The results show that with the digital method less time is needed per model analysis. Moreover, the digital approach leads to higher total scores than that based on plaster models. We conclude that interactive eLearning using digital dental arch models is a promising tool for dental education.
OR-Pad - Entwicklung eines Prototyps zur sterilen Informationsanzeige am OP-Situs : meeting abstract
(2019)
Hintergrund: Oftmals werden Informationen aus der Krankenakte oder von Bildgebungsverfahren nur auf recht weit vom Operationsgebiet entfernten Monitoren, außerhalb der ergonomischen Sichtachse des Operateurs, dargestellt. Dies führt dazu, dass relevante Informationen übersehen werden oder ihr Informationspotenzial nicht ausgeschöpft werden kann. In Papierform mitgenommene Notizen befinden sich während der OP außerhalb des sterilen Bereichs und sind dadurch für den Operateur nicht ohne Weiteres zugänglich. Auch bei intraoperativen Einträgen für die OP Dokumentation ist der Operateur auf die Mithilfe der Assistenz angewiesen. Durch die zusätzlichen Kommunikationswege entstehen dabei ein personeller und zeitlicher Mehraufwand und das Fehlerpotenzial nimmt zu. Das anwendungsorientierte Forschungsprojekt OR-Pad - Nutzung von portablen Informationsanzeigen im Operationssaal - soll dem Operateur zu einem verbesserten Informationsfluss verhelfen. Die Idee entstand aus der klinischen Routine der Anatomie und Urologie des Universitätsklinikums Tübingen und wird nun durch Fördermittel vom Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg sowie vom Europäischen Fonds für regionale Entwicklung an der Hochschule Reutlingen zu einem High Fidelity-Prototypen weiterentwickelt.
Ziel: Ziel des OR-Pad Projekts ist es, während einer OP zum aktuellen Zeitpunkt klinisch relevante Informationen in unmittelbarer Nähe zum Operateur darzustellen. Mithilfe des Systems soll der Informationsfluss zwischen dem Eingriff sowie dessen Vor- und Nachbereitung optimiert werden. Der Operateur soll vorab relevante Informationen, wie aktuelle Röntgenbilder oder persönliche Notizen, zur intraoperativen Anzeige auswählen können, die dann am OP-Situs auf einer sterilen Informationsanzeige dargestellt werden. Durch die Positionierung soll eine ergonomische Sichtachse sowie die direkte Interaktion mit dem System ermöglicht werden. Kontextrelevante Informationen sollen basierend auf dem aktuellen OP-Verlauf durch die Entwicklung einer Situationserkennung automatisch bereitgestellt werden. Zur Optimierung des Informationsflusses gehört ebenfalls die Unterstützung der OP-Dokumentation. Für diese sollen während des Eingriffs manuell vom Operateur sowie automatisch vom System Einträge, wie Zeitpunkte oder intraoperative Aufnahmen, erstellt werden. Aus diesen soll nach dem Eingriff die OP-Dokumentation generiert und damit der Prozess qualitativer und zeiteffizienter gestaltet werden.
Methodik: Zur Erreichung des Ziels werden zunächst die klinischen Anforderungen spezifiziert und in ein Lastenheft überführt. Hierfür werden Interviews und Beobachtungen bei mehreren Interventionen durchgeführt. Nach dem User-Centered-Designprozess werden Personas und Nutzungsszenarien entworfen und mit klinischen Projektpartnern in mehreren Iterationen evaluiert. Es gilt eine Informationsarchitektur aufzubauen, die eine Einbettung klinischer Informationssysteme sowie Bild- und Gerätedaten aus dem OP-Netzwerk erlaubt. Eine Situationserkennung, basierend auf Prozessmodellen, soll zur Abschätzung des Operationsfortschritts entwickelt werden. Zur Befestigung der Informationsanzeige sollen geeignete Haltemechanismen eingesetzt werden. Das OR-Pad System soll laufend im Lehr- und Forschungs-OP der Hochschule Reutlingen getestet und im Sinne agiler Produktentwicklung mit den klinischen Projektpartnern abgestimmt werden. Der finale Funktionsprototyp soll abschließend in den Versuchs-OPs der Anatomie Tübingen getestet und evaluiert werden.
Ergebnisse: Über eine erste Datenerhebung mittels Contextual Inquiry konnten erste Anforderungen an das OR-Pad System erfasst werden, woraus ein Low-Fidelity-Prototyp resultierte. Die Evaluation über Experteninterviews führte in die zweite Iteration, in der das Konzept entsprechend der Ergebnisse angepasst wurde. Über Hospitationen am Uniklinikum Tübingen fand eine weitere Datenerhebung zur Erstellung von Szenarien für die intraoperativen Anwendungsfälle statt. Anhand der Anforderungen wurde ein Konzept für die Benutzerschnittstelle entworfen, die im weiteren Verlauf mit den klinischen Projektpartnern evaluiert wird.
Powered by e-commerce and vital in the manufacturing industry, intralogistics became an increasingly important and labour-intensive process. In highly standardized automation-friendly environments, such as the automotive sector, most of efficiently automatable intralogistics tasks have already been automated. Due to aging population in EU and ergonomic regulations, the urge to automate intralogistics tasks became consistent also where product and process standardization is lower. That is the case of the production line or cell material supply process, where an increasing number of product variants and individually customized products combined with the necessary ability of reacting to changes in market conditions led to smaller and more frequent replenishment to the points of use in the production plant and to the chaotic addition of production cells in shop floor layout. This led in turn to inevitable traffic growth with unforeseeable related delays and increased level of safety threats and accidents. In this paper, we use the structured approach of the Quality Interaction Function Deployment to analyse the process of supply of assembly lines, seeking the most efficient combination of automation and manual labour, satisfying all stakeholders´ requirements. Results are presented and discussed.
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.
It is expected that ongoing digitalisation will drive the merger between the manufacturing world and the internet world, possibly leading to a next industrial revolution, currently called “Industry 4.0”. The driving forces behind this development are new business opportunities and competition advantages arising from mass production customisation as well as rapid individual product development and manufacturing. Key factors of the development towards Industry 4.0 are discussed. Threats and opportunities arising from these developments for future production are discussed. Actual examples from real-time customized manufacturing of consumer products are given. As mechatronic systems and industrial robots are widely used in manufacturing and in particular in assembly, it is discussed how they can be connected to and used in digitalised industrial systems. Different examples of remote controlled systems are presented, like remote controlled KUKA robot for handling and quality control, PLC-controlled equipment, drive systems, FESTO handling system and others. The architecture of an assembly cell is presented, where industrial robots are set-up for batch-one production or can directly receive control / production information on-line and in real-time over the factory network. Methods for remote maintenance and monitoring of systems over the internet and production operator support over the internet are presented as well.
Potentials of smart contracts-based disintermediation in additive manufacturing supply chains
(2019)
We investigate which potentials are created by using smart contracts for disintermediation in supply chains for additive manufacturing. Using a qualitative, critical realist research approach, we analyzed three case studies with companies active in additive manufactures. Based on interviews with experts from these companies, we could identify eight key requirements for disintermediation and associate four potentials of smart contracts-based disintermediation.
Among the multitude of software development processes available, hardly any is used by the book. Regardless of company size or industry sector, a majority of project teams and companies use customized processes that combine different development methods— so-called hybrid development methods. Even though such hybrid development methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. In this paper, we make a first step towards devising such guidelines. Grounded in 1,467 data points from a large-scale online survey among practitioners, we study the current state of practice in process use to answer the question: What are hybrid development methods made of? Our findings reveal that only eight methods and few practices build the core of modern software development. This small set allows for statistically constructing hybrid development methods. Using an 85% agreement level in the participants’ selections, we provide two examples illustrating how hybrid development methods are characterized by the practices they are made of. Our evidence-based analysis approach lays the foundation for devising hybrid development methods.
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.
Through increasing market dynamics, rapidly evolving technologies and shifting user expectations coupled with the adoption of lean and agile practices, companies are struggling with their ability to provide reliable product roadmaps by applying traditional approaches. Currently, most companies are seeking opportunities to improve their product roadmapping practices. As a first challenge they have to assess their current product roadmapping capabilities in order to better understand how to improve their practices and how to switch to a new approach. The aim of this article is to provide an initial maturity model for product roadmapping practices that is especially suited for assessing the roadmapping capabilities of companies operating in dynamic and uncertain market environments. Based on interviews with 15 experts from 13 various companies the current state of practice regarding product roadmapping was identified. Afterwards, the model development was conducted in the context of expert workshops with the Robert Bosch GmbH and researchers. The study results in the so-called DEEP 1.0 product roadmap maturity model which allows companies to conduct a self assessment of their product roadmapping practice.
Context: Organizations are increasingly challenged by dynamic and technical market environments. Traditional product roadmapping practices such as detailed and fixed long-term planning typically fail in such environments. Therefore, companies are actively seeking ways to improve their product roadmapping approach. Goal: This paper aims at identifying problems and challenges with respect to product roadmapping. In addition, it aims at understanding how companies succeed in improving their roadmapping practices in their respective company contexts. The study focuses on mid-sized and large companies developing software-intensive products in dynamic and technical market environments. Method: We conducted semi structured expert interviews with 15 experts from 13 German companies and conducted a thematic data analysis. Results: The analysis showed that a significant number of companies is still struggling with traditional feature based product-roadmapping and opinion based prioritization of features. The most promising areas for improvement are stating the outcomes a company is trying to achieve and making them part of the roadmap, sharing or co-developing the roadmap with stakeholders, and the establishing discovery activities.
Context: Companies in highly dynamic markets increasingly struggle with their ability to plan product development and to create reliable roadmaps. A main reason is the decreasing lack of predictability of markets, technologies, and customer behaviors. New approaches for product roadmapping seem to be necessary in order to cope with today's highly dynamic conditions. Little research is available with respect to such new approaches. Objective: In order to better understand the state of the art and to identify research gaps, this article presents a review of the scientific literature with respect to product roadmapping. Method: We performed a systematic literature review (SLR) with respect to identify papers in the field of computer science. Results: After filtering, the search resulted in a set of 23 relevant papers. The identified papers focus on different aspects such as roadmap types, processes for creating and updating roadmaps, problems and challenges with roadmapping, approaches to visualize roadmaps, generic frameworks and specific aspects such as the combination of roadmaps with business modeling. Overall, the scientific literature covers many important aspects of roadmapping but does provide only little knowledge on how to create product roadmaps under highly dynamic conditions. Research gaps address, for instance, the inclusion of goals or outcomes into product roadmaps, the alignment of a roadmap with a product vision, and the inclusion of product discovery activities in product roadmaps. In addition, the transformation from traditional roadmapping processes to new ways of roadmapping is not sufficiently addressed in the scientific literature.
Software process improvement (SPI) is around for decades, but it is a critically discussed topic. In several waves, different aspects of SPI have been discussed in the past, e.g., large scale company-level SPI programs, maturity models, success factors, and in-project SPI. It is hard to find new streams or a consensus in the community, but there is a trend coming along with agile and lean software development. Apparently, practitioners reject extensive and prescriptive maturity models and move towards smaller, faster and continuous project-integrated SPI. Based on data from two survey studies conducted in Germany (2012) and Europe (2016), we analyze the process customization for projects and practices for implementing SPI in the participating companies. Our findings indicate that, even in regulated industry sectors, companies increasingly adopt in-project SPI activities, primarily with the goal to continuously optimize specific processes. Therefore, with this paper, we want to stimulate a discussion on how to evolve traditional SPI towards a continuous learning environment.
Efficient and robust 3D object reconstruction based on monocular SLAM and CNN semantic segmentation
(2019)
Various applications implement slam technology, especially in the field of robot navigation. We show the advantage of slam technology for independent 3d object reconstruction. To receive a point cloud of every object of interest void of its environment, we leverage deep learning. We utilize recent cnn deep learning research for accurate semantic segmentation of objects. In this work, we propose two fusion methods for cnn-based semantic segmentation and slam for the 3d reconstruction of objects of interest in order to obtain a more robustness and efficiency. As a major novelty, we introduce a cnn-based masking to focus slam only on feature points belonging to every single object. Noisy, complex or even non-rigid features in the background are filtered out, improving the estimation of the camera pose and the 3d point cloud of each object. Our experiments are constrained to the reconstruction of industrial objects. We present an analysis of the accuracy and performance of each method and compare the two methods describing their pros and cons.
Digitalization of products and services commonly causes substantial changes in business models, operations, organization structures and IT infrastructures of enterprises. Motivated by experiences and observations from digitalization projects, the paper investigates the effects of digitalization on enterprise architectures (EA). EA models serve as representation of business, information system and technical aspects of an enterprise to support management and development. By comparing EA models before and after digitalization, the paper analyzes the kinds of changes visible in the EA model. The most important finding is that newly created digitized products and the associated (product)- and enterprise architecture are no longer properly integrated into the overall architecture and even exist in parallel. Thus, the focus of this work is on showing these parallel architectures and proposing derivations for a better integration.
The Dual Active Bridge (DAB) is a very promising topology for future power converters. However, careless operation can lead to a DC component in the transformer current. The problem is further exacerbated when the phase shift changes during operation. This work presents a study of DC bias effects on the DAB with special regard to transient effects introduced by sudden shifts in the output load. We present a simple yet effective approach to avoid DC bias entirely.
Enterprises are transforming their strategy, culture, processes, and their information systems to enlarge their digitalization efforts or to approach for digital leadership. The digital transformation profoundly disrupts existing enterprises and economies. In current times, a lot of new business opportunities appeared using the potential of the Internet and related digital technologies: The Internet of Things, services computing, cloud computing, artificial intelligence, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, microservices, or other micro-granular elements. Architecting micro-granular structures have a substantial impact on architecting digital services and products. The change from a closed-world modeling perspective to more flexible Open World of living software and system architectures defines the context for flexible and evolutionary software approaches, which are essential to enable the digital transformation. In this paper, we are revealing multiple perspectives of digital enterprise architecture and decisions to effectively support value and service oriented software systems for intelligent digital services and products.
Presently, many companies are transforming their strategy and product base, as well as their culture, processes and information systems to become more digital or to approach for a digital leadership. In the last years new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, edge and fog computing, social networks, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, Microservices, or other micro-granular elements. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of micro-granular system architectures defines the moving context for adaptable systems. We are focusing on a continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, as part of a new digital enterprise architecture for service dominant digital products.
Recognizing human actions is a core challenge for autonomous systems as they directly share the same space with humans. Systems must be able to recognize and assess human actions in real-time. To train the corresponding data-driven algorithms, a significant amount of annotated training data is required. We demonstrate a pipeline to detect humans, estimate their pose, track them over time and recognize their actions in real-time with standard monocular camera sensors. For action recognition, we transform noisy human pose estimates in an image like format we call Encoded Human Pose Image (EHPI). This encoded information can further be classified using standard methods from the computer vision community. With this simple procedure, we achieve competitive state-of-the-art performance in pose based action detection and can ensure real-time performance. In addition, we show a use case in the context of autonomous driving to demonstrate how such a system can be trained to recognize human actions using simulation data.
RoPose-Real: real world dataset acquisition for data-driven industrial robot arm pose estimation
(2019)
It is necessary to employ smart sensory systems in dynamic and mobile workspaces where industrial robots are mounted on mobile platforms. Such systems should be aware of flexible and non-stationary workspaces and able to react autonomously to changing situations. Building upon our previously presented RoPose-system, which employs a convolutional neural network architecture that has been trained on pure synthetic data to estimate the kinematic chain of an industrial robot arm system, we now present RoPose-Real. RoPose-Real extends the prior system with a comfortable and targetless extrinsic calibration tool, to allow for the production of automatically annotated datasets for real robot systems. Furthermore, we use the novel datasets to train the estimation network with real world data. The extracted pose information is used to automatically estimate the observing sensor pose relative to the robot system. Finally we evaluate the performance of the presented subsystems in a real world robotic scenario.
Learning to translate between real world and simulated 3D sensors while transferring task models
(2019)
Learning-based vision tasks are usually specialized on the sensor technology for which data has been labeled. The knowledge of a learned model is simply useless when it comes to data which differs from the data on which the model has been initially trained or if the model should be applied to a totally different imaging or sensor source. New labeled data has to be acquired on which a new model can be trained. Depending on the sensor, this can even get more complicated when the sensor data becomes more abstract and hard to be interpreted and labeled by humans. To enable reuse of models trained for a specific task across different sensors minimizes the data acquisition effort. Therefore, this work focuses on learning sensor models and translating between them, thus aiming for sensor interoperability. We show that even for the complex task of human pose estimation from 3D depth data recorded with different sensors, i.e. a simulated and a Kinect 2TM depth sensor, human pose estimation can greatly improve by translating between sensor models without modifying the original task model. This process especially benefits sensors and applications for which labels and models are difficult if at all possible to retrieve from raw sensor data.
The investigation of stress requires to distinguish between stress caused by physical activity and stress that is caused by psychosocial factors. The behaviour of the heart in response to stress and physical activity is very similar in case the set of monitored parameters is reduced to one. Currently, the differentiation remains difficult and methods which only use the heart rate are not able to differentiate between stress and physical activity, without using additional sensor data input. The approach focusses on methods which generate signals providing characteristics that are useful for detecting stress, physical activity, no activity and relaxation.
Autismus-Spektrum-Störungen (ASD) bei Kindern werden häufig zu spät diagnostiziert und die Begleitung der chronischen Krankheit gestaltet sich schwierig. Der vorgestellte Ansatz erlaubt die Behandlung der Kinder in dem bekannten häuslichen Umfeld und versucht die Beziehungen zwischen Schlaf und Verhalten herauszuarbeiten. Die gewonnenen Erkenntnisse sollen die Lebensqualität der Patienten verbessern und den Eltern Hilfestellung geben. Die notwendige infrastrukturelle Unterstützung wird durch medizinisches Fachpersonal geleistet, das auf einen web-basierten Service zurückgreifen kann, der sämtliche Prozesse (Diagnostik, Datenerfassung, -aufzeichnung und Training etc.) begleitet. Die anonymisierten Daten werden in einem Diagnosesystem zentral abgelegt und können so für zukünftige Behandlungsstrategien nutzbar sein. Die umfassende Lösung setzt auf zentrale Elemente von Smart-Homes und AAL auf.
Die Erholung unseres Körpers und Gehirns von Müdigkeit ist direkt abhängig von der Qualität des Schlafes, die aus den Ergebnissen einer Schlafstudie ermittelt werden kann. Die Klassifizierung der Schlafstadien ist der erste Schritt dieser Studie und beinhaltet die Messung von Biovitaldaten und deren weitere Verarbeitung. Das non-invasive Schlafanalyse-System basiert auf einem Hardware-Sensornetz aus 24 Drucksensoren, das die Schlafphasenerkennung ermöglicht. Die Drucksensoren sind mit einem energieeffizienten Mikrocontroller über einen systemweiten Bus mit Adressarbitrierung verbunden. Ein wesentlicher Unterschied dieses Systems im Vergleich zu anderen Ansätzen ist die innovative Art, die Sensoren unter der Matratze zu platzieren. Diese Eigenschaft erleichtert die kontinuierliche Nutzung des Systems ohne fühlbaren Einfluss auf das gewohnte Bett. Das System wurde getestet, indem Experimente durchgeführt wurden, die den Schlaf verschiedener gesunder junger Personen aufzeichneten. Die ersten Ergebnisse weisen auf das Potenzial hin, nicht nur Atemfrequenz und Körperbewegung, sondern auch Herzfrequenz zu erfassen.
This document presents an algorithm for a nonobtrusive recognition of Sleep/Wake states using signals derived from ECG, respiration, and body movement captured while lying in a bed. As a core mathematical base of system data analytics, multinomial logistic regression techniques were chosen. Derived parameters of the three signals are used as the input for the proposed method. The overall achieved accuracy rate is 84% for Wake/Sleep stages, with Cohen’s kappa value 0.46. The presented algorithm should support experts in analyzing sleep quality in more detail. The results confirm the potential of this method and disclose several ways for its improvement.
The goal of this paper pretends to show how a bed system with an embedded system with sensor is able to analyze a person’s movement, breathing and recognizing the positions that the subject is lying on the bed during the night without any additional physical contact. The measurements are performed with sensors placed between the mattress and the frame. An Intel Edison board was used as an endpoint that served as a communication node from the mesh network to external service. Two nodes and Intel Edison are attached to the bottom of the bed frame and they are connected to the sensors.
Power loss measurement of power electronic components and overall systems is sometimes difficult by use of electrical quantities and in few applications even not possible. The calorimetric power loss measurement is an established method to identify the overall system losses with a suitable accuracy. This paper presents a novel method with an open chamber calorimeter under accurate air mass flow, air pressure, humidity measurement and temperature control. The benefits are the approximately halved measurement time compared to established systems and the possibility to control the chamber temperature. So it is possible to measure the power losses at different ambient temperatures.
This study is about estimating the reproducibility of finding palpation points of three different anatomical landmarks in the human body (Xiphoid Process and the 2 Hip Crests) to support a navigated ultrasound application. On 6 test subjects with different body mass index the three palpation points were located five times by two examiners. The deviation from the target position was calculated and correlated to the fat thickness above each palpation point. The reproducibility of the measurements had a mean error of ≈13.5 mm +- 4 mm, which seems to be sufficient for the desired application field.
In der Orthopädie werden Robotersysteme bereits seit mehreren Jahren erfolgreich unterstützend eingesetzt. Dieser Ansatz erfordert die vorgelagerte Erstellung eines digitalen Modells auf Basis von medizinischen Bilddatensätzen. Die Erstellung und Überprüfung der Modelle soll in einer browserbasierten Client- Server-Anwendung erfolgen. Hierfür ist die Darstellung von zweidimensionalen und dreidimensionalen Datensätzen erforderlich. Basis dieses Papers ist die Entwicklung eines Ansatzes zur interaktiven, browserbasierten dreidimensionalen Darstellung medizinischer Planungsdaten. Die Anwendung stellt ein Proof of Concept dar, ob die bestehenden Desktopanwendungen zur Darstellung von Planungsdaten ersetzt werden können. Mit Hilfe des Frameworks AMI.js wurde die Anwendung umgesetzt. Sie erfüllt alle definierten Anforderungen und kann somit die aktuellen Desktopanwendungen ersetzen.
Zur Unterstützung des Operateurs wird eine patientennahe Informationsanzeige entwickelt, die kontextrelevante Informationen entsprechend der aktuellen Situation bereitstellen kann. Hierfür soll eine Situationserkennung konzipiert werden, die auf unterschiedliche intraoperative Prozesse übertragen werden kann. Ziel der adaptiven Situationserkennung ist das Erkennen spezifischer Situationen durch intraoperative Informationen unterschiedlicher Datenquellen im Operationssaal. Innerhalb der Datenerhebung und -analyse wurden Anwendungsfälle für die Situationserkennung definiert sowie chirurgische Prozessmodelle erstellt, die intraoperative Ereignisse abbilden. Auf Basis dieser Informationen wurde ein Konzept entworfen, das sich zunächst auf die Erkennung abstrakter generalisierter Phasen, unabhängig vom Eingriff, fokussiert und sich Schritt für Schritt auf granulare Prozessschritte spezifizieren lässt. Diese Flexibilität soll die Übertragbarkeit des Konzepts auf intraoperative Prozesse ermöglichen und den Operateur dadurch gezielt mit kontextrelevanten Informationen unterstützen. Das Konzept wird in zukünftigen Schritten weiterentwickelt.
Mammographie-Geräte werden in der Diagnostik von Mammakarzinomen eingesetzt. Die ursprüngliche Technik wurde in den letzten Jahren von analogen Röntgenfilmen zu digital integrierten Systemen weiterentwickelt. Durch die Tomosynthese, bei der in einem Schnittbildverfahren mehrere Schichten des Organismus untersucht werden können, können auch überlagerte Strukturen sichtbar gemacht werden. Um als adäquate Grundlage zur Diagnostik von malignen Tumoren dienen zu können, müssen einige qualitative Anforderungen erfüllt werden. Bisher gibt es wenig Literatur, die Anforderungen und den Aufbau solcher Geräte systematisch beschreiben. Im Rahmen dieser Arbeit werden auf Basis der Literatur und bestehender Systeme die qualitativen Anforderungen identifiziert. Der prinzipielle Aufbau solcher Systeme wird anhand der einzelnen Systembausteine in der semiformalen Notationssprache SysML gezeigt. Die grundlegende Funktionsweise eines tomosynthesefähigen Mammographie Gerätes wird in dieser Arbeit zusammenfassend und anhand der einzelnen Systembausteine beschrieben. Diese Arbeit dient der Vermittlung eines umfassenden Verständnisses für die digitale Mammographie, um als Grundlage für die Dokumentation von qualitativen Anforderungen dienen zu können.
This study describes a non-contact measuring and parameter identification procedure designed to evaluate inhomogeneous stiffness and damping characteristics of the annular ligament in the physiological amplitude and frequency range without the application of large static external forces that can cause unnatural displacements of the stapes. To verify the procedure, measurements were first conducted on a steel beam. Then, measurements on an individual human cadaveric temporal bone sample were performed. The estimated results support the inhomogeneous stiffness and damping distribution of the annular ligament and are in a good agreement with the multiphoton microscopy results which show that the posterior-inferior corner of the stapes footplate is the stiffest region of the annular ligament. This method can potentially help to establish a correlation between stiffness and damping characteristics of the annular ligament and inertia properties of the stapes and, thus, help to reduce the number of independent parameters in the model-based hearing diagnosis.
Due to the large interindividual variances and the poor optical accessibility of the ear, the specificity of hearing diagnostics today is severely restricted to a certain clinical picture and quantitative assessment. Often only a yes or no decision is possible, which depends strongly on the subjective assessment of the ENT physician. A novel approach, in which objectively obtainable, non invasive audiometric measurements are evaluated using a numerical middle ear model, makes it possible to make the hidden middle ear properties visible and quantifiable. The central topic of this paper is a novel parameter identification algorithm that combines inverse fuzzy arithmetic with an artificial neural network in order to achieve a coherent diagnostic overall picture in the comparison of model and measurement. Its usage is shown at a pathological pattern called malleus fixation where the upper ligament of the malleus is pathologically stiffened.
Telemetrie und Homemonitoring werden bereits in vielen Gesundheitsbereichen erfolgreich genutzt. Moderne Herzschrittmacher ermöglichen durch telemetrische Datenübertragung das Homemonitoring aktueller Gesundheits- und Zustandsdaten durch PatientInnen und ÄrztInnen. Für die Weiterentwicklung existierender Produkte ist ein grundlegendes Verständnis der Anforderungen an und des Aufbaus solcher Systeme notwendig. Bisher existieren
herstellerunabhängige Betrachtungen dieser noch nicht. Durch die Verwendung von SysML als semiformale Notationssprache wird das System Herzschrittmacher und Homemonitoring modelliert. Die Anforderungen an ein solches System lassen sich aus bestehenden Produkten ableiten. Die vorliegende Arbeit beschreibt die Systemarchitektur solcher Systeme, anhand derer die Anbindung an Informationssysteme über das Homemonitoringsystem und die dadurch umgesetzten Funktionen gezeigt werden.
Companies are constantly changing their business process models. In team environments, different versions of a process model are created at the same time. These versions of a process model need to be merged from time to time to consolidate changes and create a new common version.
In this short paper, we propose a solution for modifying a merge result. The goal is to create a meaningful merge result by adding connector nodes to the model at specific locations. This increases the amount of possible result models and reduces additional implementation effort.
While several service-based maintainability metrics have been proposed in the scientific literature, reliable approaches to automatically collect these metrics are lacking. Since static analysis is complicated for decentralized and technologically diverse microservice-based systems, we propose a dynamic approach to calculate such metrics from runtime data via distributed tracing. The approach focuses on simplicity, extensibility, and broad applicability. As a first prototype, we implemented a Java application with a Zipkin integrator, 23 different metrics, and five export formats. We demonstrated the feasibility of the approach by analyzing the runtime data of an example microservice based system. During an exploratory study with six participants, 14 of the 18 services were invoked via the system’s web interface. For these services, all metrics were calculated correctly from the generated traces.
Microservices are a topic driven mainly by practitioners and academia is only starting to investigate them. Hence, there is no clear picture of the usage of Microservices in practice. In this paper, we contribute a qualitative study with insights into industry adoption and implementation of Microservices. Contrary to existing quantitative studies, we conducted interviews to gain a more in-depth understanding of the current state of practice. During 17 interviews with software professionals from 10 companies, we analyzed 14 service-based systems. The interviews focused on applied technologies, Microservices characteristics, and the perceived influence on software quality. We found that companies generally rely on well established technologies for service implementation, communication, and deployment. Most systems, however, did not exhibit a high degree of technological diversity as commonly expected with Microservices. Decentralization and product character were different for systems built for external customers. Applied DevOps practices and automation were still on a mediocre level and only very few companies strictly followed the you build it, you run it principle. The impact of Microservices on software quality was mainly rated as positive. While maintainability received the most positive mentions, some major issues were associated with security. We present a description of each case and summarize the most important findings of companies across different domains and sizes. Researchers may build upon our findings and take them into account when designing industry-focused methods.
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.
The coupling of the heat and power sector is required as supply and demand in the German electricity mix drift further and further apart with a high percentage of renewable energy. Heat pumps in combination with thermal energy storage systems can be a useful way to couple the heat and power sectors. This paper presents a hardware-in the-loop test bench for experimental investigation of optimized control strategies for heat pumps. 24-hour experiments are carried out to test whether the heat pump is able to serve optimized schedules generated by a MATLAB algorithm. The results show that the heat pump is capable of following the generated schedules, and the maximum deviation of the operational time between schedule and experiment is only 3%. Additionally, the system can serve the demand for space heating and DHW at any time.
A large body of literature is concerned with models of presence— the sensory illusion of being part of a virtual scene— but there is still no general agreement on how to measure it objectively and reliably. For the presented study, we applied contemporary theory to measure presence in virtual reality. Thirty-seven participants explored an existing commercial game in order to complete a collection task. Two startle events were naturally embedded in the game progression to evoke physical reactions and head tracking data was collected in response to these events. Subjective presence was recorded using a post-study questionnaire and real-time assessments. Our novel implementation of behavioral measures lead to insights which could inform future presence research: We propose a measure in which startle reflexes are evoked through specific events in the virtual environment, and head tracking data is compared to the range and speed of baseline interactions.
In recent years, the parallel computing community has shown increasing interest in leveraging cloud resources for executing parallel applications. Clouds exhibit several fundamental features of economic value, like on-demand resource provisioning and a pay-per-use model. Additionally, several cloud providers offer their resources with significant discounts; however, possessing limited availability. Such volatile resources are an auspicious opportunity to reduce the costs arising from computations, thus achieving higher cost efficiency. In this paper, we propose a cost model for quantifying the monetary costs of executing parallel applications in cloud environments, leveraging volatile resources. Using this cost model, one is able to determine a configuration of a cloud-based parallel system that minimizes the total costs of executing an application.
In this paper we describe an interactive web-based visual analysis tool for Formula one races. It first provides an overview about all races on a yearly basis in a calendar-like representation. From this starting point, races can be selected and visually inspected in detail. We support a dynamic race position diagram as well as a more detailed lap times line plot for showing the drivers’ lap times in comparison. Many interaction techniques are supported like selections, filtering, highlighting, color coding, or details-on demand. We illustrate the usefulness of our visualization tool by applying it to a Formula one dataset while we describe the different dynamic visual racing patterns for a number of selected races and drivers.
Data analytics tasks on large datasets are computationally intensive and often demand the compute power of cluster environments. Yet, data cleansing, preparation, dataset characterization and statistics or metrics computation steps are frequent. These are mostly performed ad hoc, in an explorative manner and mandate low response times. But, such steps are I/O intensive and typically very slow due to low data locality, inadequate interfaces and abstractions along the stack. These typically result in prohibitively expensive scans of the full dataset and transformations on interface boundaries.
In this paper, we examine R as analytical tool, managing large persistent datasets in Ceph, a wide-spread cluster file-system. We propose nativeNDP – a framework for Near Data Processing that pushes down primitive R tasks and executes them in-situ, directly within the storage device of a cluster-node. Across a range of data sizes, we show that nativeNDP is more than an order of magnitude faster than other pushdown alternatives.
Ganz gleich, ob im privaten oder beruflichen Alltag, begleiten uns digitale Medien heute nahezu überall. Dabei dienen sie nicht nur zur Unterhaltung, sondern helfen uns, Arbeitsabläufe effizienter und produktiver durchzuführen. Doch die Arbeit des Menschen ist bei Weitem nicht überflüssig geworden. Durch die steigenden Anforderungen ist die Nachfrage nach qualifiziertem Fachpersonal heute höher denn je. Währenddessen müssen Mitarbeiter in der Lage sein, mit der rasanten Entwicklung neuer Produkte und Technologien Schritt zu halten. Dabei ist eine qualitative Aus- und Weiterbildung unumgänglich. Beginnend mit der Bildung von Medienkompetenz in Schulen bis hin zur Fach- und Berufsbildung sowie beruflichen Weiterbildung, muss der Umgang mit digitalen Technologien gelehrt sein. Darüber hinaus bieten diese Technologien neue Potenziale zur Verbesserung von Bildungskonzepten und können zudem dabei helfen, den Lernerfolg zu steigern.
Diese Arbeit beschäftigt sich mit der Evaluation einer VR-basierten Lernumgebung und untersucht mögliche Auswirkungen auf den Lernerfolg durch die verkörperte Darstellung eines virtuellen Instruktors. Dazu wurde die technische Implementierung einer kollaborativen Lernumgebung vorgenommen, mit welcher anschließend eine Versuchsreihe mit 16 Probanden durchgeführt wurde. Im Hinblick auf eine mögliche Steigerung der Effizienz in der eigenständigen Bewältigung von Montageaufgaben nach unterschiedlichen Instruktionsarten, wurden keine signifikanten Leistungsverbesserungen festgestellt.
Type 1 diabetes is a chronic and a life threatening disease: an adjusted treatment and a proper management of the disease are crucial to prevent or delay the complications of diabetes. Although during the last decade the development of the artificial pancreas has presented great advances in diabetes care, the multiple daily injections therapy still represents the most widely used treatment option for type 1 diabetes. This work presents the proposal and first development stages of an application focused on guiding patients using the continuous glucose monitors and smart pens together with insulin and carbohydrates recommendations. Our proposal aims to develop a platform to integrate a series of innovative machine learning models and tools rigorously tested together with the use of the latest IoT devices to manage type 1 diabetes. The resulting system actually closes the loop, like the artificial pancreas, but in an intermittent way.