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With the expansion of cyber-physical systems (CPSs) across critical and regulated industries, systems must be continuously updated to remain resilient. At the same time, they should be extremely secure and safe to operate and use. The DevOps approach caters to business demands of more speed and smartness in production, but it is extremely challenging to implement DevOps due to the complexity of critical CPSs and requirements from regulatory authorities. In this study, expert opinions from 33 European companies expose the gap in the current state of practice on DevOps-oriented continuous development and maintenance. The study contributes to research and practice by identifying a set of needs. Subsequently, the authors propose a novel approach called Secure DevOps and provide several avenues for further research and development in this area. The study shows that, because security is a cross-cutting property in complex CPSs, its proficient management requires system-wide competencies and capabilities across the CPSs development and operation.
The tale of 1000 cores: an evaluation of concurrency control on real(ly) large multi-socket hardware
(2020)
In this paper, we set out the goal to revisit the results of “Starring into the Abyss [...] of Concurrency Control with [1000] Cores” and analyse in-memory DBMSs on today’s large hardware. Despite the original assumption of the authors, today we do not see single-socket CPUs with 1000 cores. Instead multi-socket hardware made its way into production data centres. Hence, we follow up on this prior work with an evaluation of the characteristics of concurrency control schemes on real production multi-socket hardware with 1568 cores. To our surprise, we made several interesting findings which we report on in this paper.
In this paper, we present a new approach for achieving robust performance of data structures making it easier to reuse the same design for different hardware generations but also for different workloads. To achieve robust performance, the main idea is to strictly separate the data structure design from the actual strategies to execute access operations and adjust the actual execution strategies by means of so-called configurations instead of hard-wiring the execution strategy into the data structure. In our evaluation we demonstrate the benefits of this configuration approach for individual data structures as well as complex OLTP workloads.
Additive Manufacturing is increasingly used in the industrial sector as a result of continuous development. In the Production Planning and Control (PPC) system, AM enables an agile response in the area of detailed and process planning, especially for a large number of plants. For this purpose, a concept for a PPC system for AM is presented, which takes into account the requirements for integration into the operational enterprise software system. The technical applicability will be demonstrated by individual implemented sections. The presented solution approach promises a more efficient utilization of the plants and a more elastic use.
Development work within an experimental environment, in which certain properties are investigated and optimized, requires many test runs and is therefore often associated with long execution times, costs and risks. This can affect product, material and technology development in industry and research. New digital driver technologies offer the possibility to automate complex manual work steps in a cost-effective way, to increase the relevance of the results and to accelerate the processes many times over. In this context, this article presents a low-cost, modular and open-source machine vision system for test execution and evaluates it on the basis of a real industrial application. For this purpose a methodology for the automated execution of the load intervals, the process documentation and for the evaluation of the generated data by means of machine learning to classify wear levels. The software and the mechanical structure are designed to be adaptable to different conditions, components and for a variety of tasks in industry and research. The mechanical structure is required for tracking the test object and represents a motion platform with independent positioning by machine vision operators or machine learning. An evaluation of the state of the test object is performed by the transfer learning after the initial documentation run. The manual procedure for classifying the visually recorded data on the state of the test object is described for the training material. This leads to an increased resource efficiency on the material as well as on the personnel side since on the one hand the significance of the tests performed is increased by the continuous documentation and on the other hand the responsible experts can be assigned time efficiently. The presence and know-how of the experts are therefore only required for defined and decisive events during the execution of the experiments. Furthermore, the generated data are suitable for later use as an additional source of data for predictive maintenance of the developed object.
The evaluation of the effectiveness of different machine learning algorithms on a publicly available database of signals derived from wearable devices is presented with the goal of optimizing human activity recognition and classification. Among the wide number of body signals we choose a couple of signals, namely photoplethysmographic (optically detected subcutaneous blood volume) and tri-axis acceleration signals that are easy to be simultaneously acquired using commercial widespread devices (e.g. smartwatches) as well as custom wearable wireless devices designed for sport, healthcare, or clinical purposes. To this end, two widely used algorithms (decision tree and k-nearest neighbor) were tested, and their performance were compared to two new recent algorithms (particle Bernstein and a Monte Carlo-based regression) both in terms of accuracy and processing time. A data preprocessing phase was also considered to improve the performance of the machine learning procedures, in order to reduce the problem size and a detailed analysis of the compression strategy and results is also presented.
Context: Fast moving markets and the age of digitization require that software can be quickly changed or extended with new features. The associated quality attribute is referred to as evolvability: the degree of effectiveness and efficiency with which a system can be adapted or extended. Evolvability is especially important for software with frequently changing requirements, e.g. internet-based systems. Several evolvability-related benefits were arguably gained with the rise of service-oriented computing (SOC) that established itself as one of the most important paradigms for distributed systems over the last decade. The implementation of enterprise-wide software landscapes in the style of service-oriented architecture (SOA) prioritizes loose coupling, encapsulation, interoperability, composition, and reuse. In recent years, microservices quickly gained in popularity as an agile, DevOps-focused, and decentralized service-oriented variant with fine-grained services. A key idea here is that small and loosely coupled services that are independently deployable should be easy to change and to replace. Moreover, one of the postulated microservices characteristics is evolutionary design.
Problem Statement: While these properties provide a favorable theoretical basis for evolvable systems, they offer no concrete and universally applicable solutions. As with each architectural style, the implementation of a concrete microservice-based system can be of arbitrary quality. Several studies also report that software professionals trust in the foundational maintainability of service orientation and microservices in particular. A blind belief in these qualities without appropriate evolvability assurance can lead to violations of important principles and therefore negatively impact software evolution. In addition to this, very little scientific research has covered the areas of maintenance, evolution, or technical debt of microservices.
Objectives: To address this, the aim of this research is to support developers of microservices with appropriate methods, techniques, and tools to evaluate or improve evolvability and to facilitate sustainable long-term development. In particular, we want to provide recommendations and tool support for metric-based as well as scenario-based evaluation. In the context of service-based evolvability, we furthermore want to analyze the effectiveness of patterns and collect relevant antipatterns. Methods: Using empirical methods, we analyzed the industry state of the practice and the academic state of the art, which helped us to identify existing techniques, challenges, and research gaps. Based on these findings, we then designed new evolvability assurance techniques and used additional empirical studies to demonstrate and evaluate their effectiveness. Applied empirical methods were for example surveys, interviews, (systematic) literature studies, or controlled experiments.
Contributions: In addition to our analyses of industry practice and scientific literature, we provide contributions in three different areas. With respect to metric-based evolvability evaluation, we identified a set of structural metrics specifically designed for service orientation and analyzed their value for microservices. Subsequently, we designed tool-supported approaches to automatically gather a subset of these metrics from machine-readable RESTful API descriptions and via a distributed tracing mechanism at runtime. In the area of scenario-based evaluation, we developed a tool-supported lightweight method to analyze the evolvability of a service-based system based on hypothetical evolution scenarios. We evaluated the method with a survey (N=40) as well as hands-on interviews (N=7) and improved it further based on the findings. Lastly with respect to patterns and antipatterns, we collected a large set of service-based patterns and analyzed their applicability for microservices. From this initial catalogue, we synthesized a set of candidate evolvability patterns via the proxy of architectural modifiability tactics. The impact of four of these patterns on evolvability was then empirically tested in a controlled experiment (N=69) and with a metric-based analysis. The results suggest that the additional structural complexity introduced by the patterns as well as developers' pattern knowledge have an influence on their effectiveness. As a last contribution, we created a holistic collection of service-based antipatterns for both SOA and microservices and published it in a collaborative repository.
Conclusion: Our contributions provide first foundations for a holistic view on the evolvability assurance of microservices and address several perspectives. Metric- and scenario-based evaluation as well as service-based antipatterns can be used to identify "hot spots" while service-based patterns can remediate them and provide means for systematic evolvability construction. All in all, researchers and practitioners in the field of microservices can use our artifacts to analyze and improve the evolvability of their systems as well as to gain a conceptual understanding of service-based evolvability assurance.
While many maintainability metrics have been explicitly designed for service-based systems, tool-supported approaches to automatically collect these metrics are lacking. Especially in the context of microservices, decentralization and technological heterogeneity may pose challenges for static analysis. We therefore propose the modular and extensible RAMA approach (RESTful API Metric Analyzer) to calculate such metrics from machine-readable interface descriptions of RESTful services. We also provide prototypical tool support, the RAMA CLI, which currently parses the formats OpenAPI, RAML, and WADL and calculates 10 structural service-based metrics proposed in scientific literature. To make RAMA measurement results more actionable, we additionally designed a repeatable benchmark for quartile-based threshold ranges (green, yellow, orange, red). In an exemplary run, we derived thresholds for all RAMA CLI metrics from the interface descriptions of 1,737 publicly available RESTful APIs. Researchers and practitioners can use RAMA to evaluate the maintainability of RESTful services or to support the empirical evaluation of new service interface metrics.
Scenario-based analysis is a comprehensive technique to evaluate software quality and can provide more detailed insights than e.g. maintainability metrics. Since such methods typically require significant manual effort, we designed a lightweight scenario-based evolvability evaluation method. To increase efficiency and to limit assumptions, the method exclusively targets service- and microservice-based systems. Additionally, we implemented web-based tool support for each step. Method and tool were also evaluated with a survey (N=40) that focused on change effort estimation techniques and hands-on interviews (N=7) that focused on usability. Based on the evaluation results, we improved method and tool support further. To increase reuse and transparency, the web-based application as well as all survey and interview artifacts are publicly available on GitHub. In its current state, the tool-supported method is ready for first industry case studies.
The shift of populations to cities is creating challenges in many respects, thus leading to increasing demand for smart solutions of urbanization problems. Smart city applications range from technical and social to economic and ecological. The main focus of this work is to provide a systematic literature review of smart city research to answer two main questions: (1) How is current research on smart cities structured? and (2) What directions are relevant for future research on smart cities? To answer these research questions, a text-mining approach is applied to a large number of publications. This provides an overview and gives insights into relevant dimensions of smart city research. Although the main dimensions of research are already described in the literature, an evaluation of the relevance of such dimensions is missing. Findings suggest that the dimensions of environment and governance are popular, while the dimension of economy has received only limited attention.
The shift of populations to cities is creating challenges in many respects, thus leading to increasing demand for smart solutions of urbanization problems. Smart city applications range from technical and social to economic and ecological. The main focus of this work is to provide a systematic literature review of smart city research to answer two main questions: (1) How is current research on smart cities structured? And (2) What directions are relevant for future research on smart cities? To answer these research questions, a text-mining approach is applied to a large number of publications. This provides an overview and gives insights into relevant dimensions of smart city research. Although the main dimensions of research are already described in the literature, an evaluation of the relevance of such dimensions is missing. Findings suggest that the dimensions of environment and governance are popular, while the dimension of economy has received only limited attention.
Zero or plus energy office buildings must have very high building standards and require highly efficient energy supply systems due to space limitations for renewable installations. Conventional solar cooling systems use photovoltaic electricity or thermal energy to run either a compression cooling machine or an absorption-cooling machine in order to produce cooling energy during daytime, while they use electricity from the grid for the nightly cooling energy demand. With a hybrid photovoltaic-thermal collector, electricity as well as thermal energy can be produced at the same time. These collectors can produce also cooling energy at nighttime by longwave radiation exchange with the night sky and convection losses to the ambient air. Such a renewable trigeneration system offers new fields of applications. However, the technical, ecological and economical aspects of such systems are still largely unexplored.
In this work, the potential of a PVT system to heat and cool office buildings in three different climate zones is investigated. In the investigated system, PVT collectors act as a heat source and heat sink for a reversible heat pump. Due to the reduced electricity consumption (from the grid) for heat rejection, the overall efficiency and economics improve compared to a conventional solar cooling system using a reversible air-to-water heat pump as heat and cold source.
A parametric simulation study was carried out to evaluate the system design with different PVT surface areas and storage tank volumes to optimize the system for three different climate zones and for two different building standards. It is shown such systems are technically feasible today. With a maximum utilization of PV electricity for heating, ventilation, air conditioning and other electricity demand such as lighting and plug loads, high solar fractions and primary energy savings can be achieved.
Annual costs for such a system are comparable to conventional solar thermal and solar electrical cooling systems. Nevertheless, the economic feasibility strongly depends on country specific energy prices and energy policy. However, even in countries without compensation schemes for energy produced by renewables, this system can still be economically viable today. It could be shown, that a specific system dimensioning can be found at each of the investigated locations worldwide for a valuable economic and ecological operation of an office building with PVT technologies in different system designs.
In dieser Ausarbeitung wird auf Visualisierungsmöglichkeiten von neuronalen Netzen eingegangen. Ein neuronales Netz scheint zuerst nicht von außen einsehbar und ist somit für viele eine Blackbox. Häufig genutzte Python-Bibliotheken, zum Beispiel TensorFlow, werden vorgestellt und deren Stärken wie auch Schwächen präsentiert. Anhand dieser werden bereits bestehende Visualisierungen gezeigt und ihr derzeitiger Einsatz wird erläutert. Durch einen Vergleich soll ersichtlich werden, welche Bibliothek am meisten Daten während des Trainings liefert, damit diese Informationen weiter verarbeitet werden. Diese Daten sollen so visualisiert werden, dass sie bei der Entwicklung eines neuronalen Netzes unterstützend sind. Ziel ist es, auf die Möglichkeiten einzugehen, welche geboten werden können. Durch eine Vereinfachung des Debuggings neuronaler Netze sollen weiterführende Entwicklungen in diese Richtung unterstützt werden.
In diesem Beitrag wird ein neuer Ansatz vorgestellt, welcher eine schwerkraftreduzierte Navigation innerhalb einer VR-Umgebung erlaubt, wie beispielsweise ein simulierter Mondspaziergang. Zur Navigation in der VR-Umgebung wird der Cyberith Virtualizer ein-gesetzt. Die Schwerkraftsimulation erfolgt mittels eines einstellbaren Gurtsystems, das anelastischen Seilen aufgehängt wird und abgestufte Schwerkraftkompensationen erlaubt. Als Umgebung wurde ein Raumschiffszenario sowie eine Mondoberfläche generiert. Hier sind in der aktuellen Anwendung einfache Interaktionen möglich. In Anlehnung an existierende Gravity Offload Systeme wird die Lösung ViRGOS bezeichnet. ViRGOS wurde bereits bei verschiedenen Besuchsterminen und Hochschulevents eingesetzt, so dass erste Rückmeldungen von Nutzern eingeholt werden konnten.
Automatic anode rod inspection in aluminum smelters using deep-learning techniques: a case study
(2020)
Automatic fault detection using machine learning has become an exciting and promising area of research. This because it accurate and timely way to manage and classify with minimal human effort. In the computer vision community, deep-learning methods have become the most suitable approaches for this task. Anodes are large carbon blocks that are used to conduct electricity during the aluminum reduction process. The most basic function of anode rod inspection is to prevent a situation where the anode rod will not fit into the stub-holes of a new anode. It would be the case for a rod containing either severe toe-in, missing stubs, or a retained thimble on one or more stubs. In this work, to improve the accuracy of shape defect inspection for an anode rod, we use the Fast Region-based Convolutional Network method (Fast R-CNN), model. To train the detection model, we collect an image dataset composed of multi-class of anode rod defects with annotated labels. Our model is trained using a small number of samples, an essential requirement in the industry where the number of available defective samples is limited. It can simultaneously detect multi-class of defects of the anode rod in nearly real-time.
The ballistocardiography is a technique that measures the heart rate from the mechanical vibrations of the body due to the heart movement. In this work a novel noninvasive device placed under the mattress of a bed estimates the heart rate using the ballistocardiography. Different algorithms for heart rate estimation have been developed.
Globalization has increased the number of road trips and vehicles. The result has been an intensification of traffic accidents, which are becoming one of the most important causes of death worldwide. Traffic accidents are often due to human error, the probability of which increases when the cognitive ability of the driver decreases. Cognitive capacity is closely related to the driver’s mental state, as well as other external factors such as the CO2 concentration inside the vehicle. The objective of this work is to analyze how these elements affect driving. We have conducted an experiment with 50 drivers who have driven for 25 min using a driving simulator. These drivers completed a survey at the start and end of the experiment to obtain information about their mental state. In addition, during the test, their stress level was monitored using biometric sensors and the state of the environment (temperature, humidity and CO2 level) was recorded. The results of the experiment show that the initial level of stress and tiredness of the driver can have a strong impact on stress, driving behavior and fatigue produced by the driving test. Other elements such as sadness and the conditions of the interior of the vehicle also cause impaired driving and affect compliance with traffic regulations.
At DBKDA 2019, we demonstrated that StrongDBMS with simple but rigorous optimistic algorithms, provides better performance in situations of high concurrency than major commercial database management systems (DBMS). The demonstration was convincing but the reasons for its success were not fully analysed. There is a brief account of the results below. In this short contribution, we wish to discuss the reasons for the results. The analysis leads to a strong criticism of all DBMS algorithms based on locking, and based on these results, it is not fanciful to suggest that it is time to re-engineer existing DBMS.
3D assisted 2D face recognition involves the process of reconstructing 3D faces from 2D images and solving the problem of face recognition in 3D. To facilitate the use of deep neural networks, a 3D face, normally represented as a 3D mesh of vertices and its corresponding surface texture, is remapped to image-like square isomaps by a conformal mapping. Based on previous work, we assume that face recognition benefits more from texture. In this work, we focus on the surface texture and its discriminatory information content for recognition purposes. Our approach is to prepare a 3D mesh, the corresponding surface texture and the original 2D image as triple input for the recognition network, to show that 3D data is useful for face recognition. Texture enhancement methods to control the texture fusion process are introduced and we adapt data augmentation methods. Our results show that texture-map-based face recognition can not only compete with state-of-the-art systems under the same precon ditions but also outperforms standard 2D methods from recent years.
Detecting semantic similarities between sentences is still a challenge today due to the ambiguity of natural languages. In this work, we propose a simple approach to identifying semantically similar questions by combining the strengths of word embeddings and Convolutional Neural Networks (CNNs). In addition, we demonstrate how the cosine similarity metric can be used to effectively compare feature vectors. Our network is trained on the Quora dataset, which contains over 400k question pairs. We experiment with different embedding approaches such as Word2Vec, Fasttext, and Doc2Vec and investigate the effects these approaches have on model performance. Our model achieves competitive results on the Quora dataset and complements the well-established evidence that CNNs can be utilized for paraphrase recognition tasks.
Medizinprodukte sind Gegenstände, Stoffe oder Software mit medizinischer Zweckbestimmung für die Anwendung am Menschen. Diese werden von Medizinprodukteherstellern entwickelt und auf den Markt eingeführt. Da die falsche Anwendung von Medizinprodukten bei Menschen zu Verletzbarkeit des menschlichen Körpers führen kann, ist eine angemessene Qualität der Medizinprodukte zu gewährtleisten. Um die Sicherstellung der Qualität einzuhalten, sind Medizinproduktehersteller verpflichtet, sich an die Medizinprodukteverordnung (MDR) zu halten. Für risikoreiche Produkte ist ergänzend die Nutzung eines Qualitätsmanagementsystems (QMS) verpflichtend. Dieses steuert die Struktur, Verantwortlichkeiten, Verfahren und Prozesse des Unternehmens, die für die Medizinprodukteentwicklung notwendig sind. In Zeiten der Digitalisierung werden Softwarelösungen eingesetzt, um die zeitaufwendigen Dokumentations- und Administrationstätigkeiten im QMS zu reduzieren und die Prozesse zu optimieren. Mit der Einführung einer Software wird ein QMS in der Praxis auch als elektronisches QMS (eQMS) bezeichnet. Weiterhin muss das gesamte QMS mit den Regularien konform sein. Deshalb ist das Ziel dieser Arbeit, mithilfe der regulatorischen Anforderungen herauszuarbeiten, welche Vorgaben bei der Einführung eines eQMS zu beachten sind und wie diese erfüllt werden können. Diese Arbeit bezieht sich auf die regulatorsichen Vorgaben aus der MDR und der ISO 13485. Die Norm beinhaltet Anforderungen an ein QMS von Medizinprodukten.
This document presents a new complete standalone system for a recognition of sleep apnea using signals from the pressure sensors placed under the mattress. The developed hardware part of the system is tuned to filter and to amplify the signal. Its software part performs more accurate signal filtering and identification of apnea events. The overall achieved accuracy of the recognition of apnea occurrence is 91%, with the average measured recognition delay of about 15 seconds, which confirms the suitability of the proposed method for future employment. The main aim of the presented approach is the support of the healthcare system with the cost-efficient tool for recognition of sleep apnea in the home environment.
Comparison of sleep characteristics measurements: a case study with a population aged 65 and above
(2020)
Good sleep is crucial for a healthy life of every person. Unfortunately, its quality often decreases with aging. A common approach to measuring the sleep characteristics is based on interviews with the subjects or letting them fill in a daily questionnaire and afterward evaluating the obtained data. However, this method has time and personal costs for the interviewer and evaluator of responses. Therefore, it would be important to execute the collection and evaluation of sleep characteristics automatically. To do that, it is necessary to investigate the level of agreement between measurements performed in a traditional way using questionnaires and measurements obtained using electronic monitoring devices. The study presented in this manuscript performs this investigation, comparing such sleep characteristics as "time going to bed", "total time in bed", "total sleep time" and "sleep efficiency". A total number of 106 night records of elderly persons (aged 65+) were analyzed. The results achieved so far reveal the fact that the degree of agreement between the two measurement methods varies substantially for different characteristics, from 31 minutes of mean difference for "time going to bed" to 77 minutes for "total sleep time". For this reason, a direct exchange of objective and subjective measuring methods is currently not possible.
Autonomous driving is becoming the next big digital disruption in the automotive industry. However, the possibility of integrating autonomous driving vehicles into current transportation systems not only involves technological issues but also requires the acceptance and adoption of users. Therefore, this paper develops a conceptual model for user acceptance of autonomous driving vehicles. The corresponding model is tested through a standardized survey of 470 respondents in Germany. Finally, the findings are discussed in relation to the current developments in the automotive industry, and recommendations for further research are given.
Das ZD.BB - Digitaler Hub für kleine und mittelständische Unternehmen in der Region Stuttgart
(2020)
Die Digitale Transformation ist eines der meistdiskutierten Themen in der heutigen Geschäftswelt. Viele Unternehmen, vor allem kleine und mittelständische Unternehmen (KMU), tun sich schwer die Chancen und Risiken der Digitalisierung einzuschätzen. Mit all den Möglichkeiten und Chancen, welche die Digitalisierung birgt, droht Unternehmen, die sich vor den Entwicklungen verschließen, der Verlust ihrer Markt- und Wettbewerbsposition. Mit dem im Februar 2019 eröffneten Digital Hub ZD.BB (Zentrum Digitalisierung) besteht in der Region Stuttgart eine neue, zentrale Anlaufstelle für Fragen rund um das Thema Digitalisierung. Am ZD.BB erhalten kleine und mittelständische Unternehmen (KMU) sowie Startups für ihre digitalen Transformationsprozesse eine kompetente Beratung und Betreuung. Sie geht von der Sensibilisierung über die Analyse bis zur Lösungsentwicklung für digitale Prozesse. Mithilfe einer digitalen Qualifizierungsoffensive und mittelstandsgerechten Methoden zur Geschäftsmodellentwicklung werden Unternehmen im ZD.BB umfassend bei ihren Digitalisierungsvorhaben unterstützt. Dazu werden in Innovationslaboren, in Coworking Spaces und bei Events unterschiedliche Kompetenzen, Disziplinen, Ideen, Technologien und Kreativität vernetzt und auf diese Weise digitale Innovationen hervorgebracht.
Hochschulen sind Teil des Innovationsökosystems: in einer kooperativen Austauschbeziehung fördern sie die regionale Wirtschaft und die gesellschaftliche Entwicklung. Deshalb ist die Förderung von Innovation, Kreativität und unternehmerischem Denken eine wichtige Aufgabe. Die Europäische Kommission hat bereits 2005 unternehmerisches Denken und Handeln als Schlüsselkompetenz für das 21. Jahrhundert definiert: „Unternehmerische Kompetenz ist die Fähigkeit, Ideen in die Tat umzusetzen“ (Europäische Kommission, 2005, S. 21). Entrepreneurship Education boomt und die Förderung von unternehmerischen Kompetenzen an Hochschulen wird vorangetrieben – damit ist die Förderung von Gründungskultur nicht nur Teil der Wirtschaftsbildung sondern vielmehr als Querschnittsaufgabe zu verstehen. Die Entrepreneurial Mission verändert die Lehr- und Lern kultur an den Hochschulen. Zum einen ist es Ziel, Entrepreneurship in der Breite an den Hochschulen zu verankern: Unternehmerisches Denken und Handeln ist eine Kernkompetenz. Zum anderen fördert die Start-up Education an Hochschulen aktiv Unternehmertalente und Ausgründungen.
Das Projekt “Spinnovation” ist ein Verbundprojekt der Hochschule Reutlingen, der Hochschule Aalen und der Hochschule der Medien und wird vom Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg in der Ausschreibung „Gründungskultur in Studium und Lehre“ gefördert. Seit 2016 wurden dazu an den beteiligten Hochschulen zahlreiche neue Angebote für Studierende entwickelt, um das Thema Entrepreneurship Education curricular zu integrieren und eine Änderung des Mindsets in Richtung Entrepreneurship und Innovation zu bewirken. Basierend auf den Erfahrungen und Ergebnissen aus dem Verbundprojekt Spinnovation können konkrete Handlungsempfehlungen für die Entrepreneurship Education an Hochschulen abgeleitet werden.
Die rasante Entwicklung der Sensortechnik im Endverbraucherbereich lässt einen klinischen Nutzen der verfügbaren dezentral erhobenen Daten aus dem Patientenalltag zur Überwachung des individuellen Gesundheitszustands vermuten. Zur Überprüfung dieser Vermutung ist die Bereitstellung einer entsprechenden Plattform in den klinischen Alltag erforderlich. Hierzu wird die bwHealthApp entwickelt, mit der sowohl die aktuelle Bandbreite als auch die Evolution der Sensortechnik auf die klinische Anwendung abbildbar ist. Mit dem flexiblen Entwurf lässt sich der klinische Nutzen für die personalisierte Medizin evaluieren. Außerdem bietet die bwHealthApp einen an Machbarkeit orientierten Diskussionsbeitrag zu offenen rechtlichen, regulatorischen und ethischen Fragestellungen der Digitalisierung in der Medizin in Deutschland.
Vergleichende Analyse des YouTube-Auftritts von privat- und öffentlich-rechtlichen Sendegruppen
(2020)
Lange wurde das Internet als Antagonismus zum Fernsehen gesehen. Es wurde dementsprechend zur Zuschauerrück- bzw. -gewinnung genutzt, was sich allerdings als ineffizient erwies. Inzwischen haben die einzelnen Sendegruppen das Internet jedoch als mediale Erweiterung erkannt und genutzt. Durch diese späte Akzeptanz zeigen sich starke Unterschiede im Umfang und der Vorgehensweise hinsichtlich der Nutzung des Internets als zusätzliches Medium. Am besten lässt sich dies in einem Vergleich in Bezug auf die wichtigste videotechnische Social Media Plattform YouTube darstellen.
In diesem Vergleich sollen die einzelnen Sendegruppen hinsichtlich ihrer wahrgenommenen Vorteile, Nachteile und Attraktivität bezogen auf das Nutzerverhalten und die Nutzermeinung bewertet werden. Die zielgruppenorientierte Optimierung des YouTube-Auftrittes ist von außerordentlich hoher Bedeutung für die zukünftige Marktdurchdringung.
High Performance Computing (HPC) enables significant progress in both science and industry. Whereas traditionally parallel applications have been developed to address the grand challenges in science, as of today, they are also heavily used to speed up the time-to-result in the context of product design, production planning, financial risk management, medical diagnosis, as well as research and development efforts. However, purchasing and operating HPC clusters to run these applications requires huge capital expenditures as well as operational knowledge and thus is reserved to large organizations that benefit from economies of scale. More recently, the cloud evolved into an alternative execution environment for parallel applications, which comes with novel characteristics such as on-demand access to compute resources, pay-per-use, and elasticity. Whereas the cloud has been mainly used to operate interactive multi-tier applications, HPC users are also interested in the benefits offered. These include full control of the resource configuration based on virtualization, fast setup times by using on-demand accessible compute resources, and eliminated upfront capital expenditures due to the pay-per-use billing model. Additionally, elasticity allows compute resources to be provisioned and decommissioned at runtime, which allows fine-grained control of an application's performance in terms of its execution time and efficiency as well as the related monetary costs of the computation. Whereas HPC-optimized cloud environments have been introduced by cloud providers such as Amazon Web Services (AWS) and Microsoft Azure, existing parallel architectures are not designed to make use of elasticity. This thesis addresses several challenges in the emergent field of High Performance Cloud Computing. In particular, the presented contributions focus on the novel opportunities and challenges related to elasticity. First, the principles of elastic parallel systems as well as related design considerations are discussed in detail. On this basis, two exemplary elastic parallel system architectures are presented, each of which includes (1) an elasticity controller that controls the number of processing units based on user-defined goals, (2) a cloud-aware parallel execution model that handles coordination and synchronization requirements in an automated manner, and (3) a programming abstraction to ease the implementation of elastic parallel applications. To automate application delivery and deployment, novel approaches are presented that generate the required deployment artifacts from developer-provided source code in an automated manner while considering application-specific non-functional requirements. Throughout this thesis, a broad spectrum of design decisions related to the construction of elastic parallel system architectures is discussed, including proactive and reactive elasticity control mechanisms as well as cloud-based parallel processing with virtual machines (Infrastructure as a Service) and functions (Function as a Service). To evaluate these contributions, extensive experimental evaluations are presented.
Elasticity is considered to be the most beneficial characteristic of cloud environments, which distinguishes the cloud from clusters and grids. Whereas elasticity has become mainstream for web-based, interactive applications, it is still a major research challenge how to leverage elasticity for applications from the high-performance computing (HPC) domain, which heavily rely on efficient parallel processing techniques. In this work, we specifically address the challenges of elasticity for parallel tree search applications. Well-known meta-algorithms based on this parallel processing technique include branch-and-bound and backtracking search. We show that their characteristics render static resource provisioning inappropriate and the capability of elastic scaling desirable. Moreover, we discuss how to construct an elasticity controller that reasons about the scaling behavior of a parallel system at runtime and dynamically adapts the number of processing units according to user-defined cost and efficiency thresholds. We evaluate a prototypical elasticity controller based on our findings by employing several benchmarks for parallel tree search and discuss the applicability of the proposed approach. Our experimental results show that, by means of elastic scaling, the performance can be controlled according to user-defined thresholds, which cannot be achieved with static resource provisioning.
Cloud resources can be dynamically provisioned according to application-specific requirements and are payed on a per-use basis. This gives rise to a new concept for parallel processing: Elastic parallel computations. However, it is still an open research question to which extent parallel applications can benefit from elastic scaling, which requires resource adaptation at runtime and corresponding coordination mechanisms. In this work, we analyze how to address these system-level challenges in the context of developing and operating elastic parallel tree search applications. Based on our findings, we discuss the design and implementation of TASKWORK, a cloud-aware runtime system specifically designed for elastic parallel tree search, which enables the implementation of elastic applications by means of higher-level development frameworks. We show how to implement an elastic parallel branch-and-bound application based on an exemplary development framework and report on our experimental evaluation that also considers several benchmarks for parallel tree search.
Documentation of clinical processes, especially in the perioperative are, is a base requirement for quality of service. Nonetheless, the documentation is a burden for the medical staff since it distracts from the clinical core process. An intuitive and user-friendly documentation system could increase documentation quality and reduce documentation workload. The optimal system solution would know what happened and the person documenting the step would need a single “confirm” button. In many cases, such a linear flow of activities is given as long as only one profession (e.g. anaestesiology, scrub nurse) is considered, but even in such cases, there might be derivations from the linear process flow and further interaction is required.
JumpAR kombiniert die Welt der Augmented Reality (AR) mit dem weltbekannten Jump ’n’ Run Genre in einem Mobile Game. Der Spieler kreiert einen individuellen Spielparcours in seiner realen Umgebung und navigiert seine Spielfigur auf virtuellen Plattformen durch diesen. Der mit Unity entwickelte JumpAR Prototyp wurde nach Umsetzungen der Grundfunktionen und Mechaniken im Rahmen eines Nutzertests analysiert. Die Integration von echten Gegenständen aus dem Umfeld des Spielers führt im Spielfluss zu einer starken Verknüpfung der virtuellen und realen Welt, was eine neue AR-Interaktionsform für Handyspiele darstellt.
Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. Every project is unique and, thus, many context factors have to be considered. Recent research took some initial steps towards statistically constructing hybrid development methods, yet, paid little attention to the peculiarities of context factors influencing method and practice selection. In this paper, we utilize exploratory factor analysis and logistic regression analysis to learn such context factors and to identify methods that are correlated with these factors. Our analysis is based on 829 data points from the HELENA dataset. We provide five base clusters of methods consisting of up to 10 methods that lay the foundation for devising hybrid development methods. The analysis of the five clusters using trained models reveals only a few context factors, e.g., project/product size and target application domain, that seem to significantly influence the selection of methods. An extended descriptive analysis of these practices in the context of the identified method clusters also suggests a consolidation of the relevant practice sets used in specific project contexts.
In Zusammenarbeit mit dem Medizinproduktehersteller ulrich medical wird eine User Experience und Usability Studie an der Software der im Moment eingesetzten Kontrastmittelinjektoren durchgeführt. Das Unternehmen möchte eine neue Variante eines Kontrastmittelinjektors entwickeln, der als Basis eine verbesserte Version dieser Softwares enthält. Benutzerstudien können mit den unterschiedlichsten Methoden durchgeführt werden. Das geeignete Vorgehen muss definiert und die Testpersonen in Bezug zur eingesetzten Methode ermittelt werden. Bei Medizinprodukten muss zusätzlich auf strikte Auflagen in Normen und Gesetzen geachtet werden. Die Grundlage zur Methodenauswahl bildet eine Recherche zu Usability und User Experience Vorgaben für Medizinprodukte. Die Studie wird anhand quantitativer Daten eines Usability Tests im Labor, Fragebögen zur User Experience und qualitativen Post Test- Interviews evaluiert. In erster Linie dient diese Studie der Ermittlung von möglichen Verbesserungen, welche in der darauf folgenden Masterthesis vertieft und umgesetzt werden.
Hypermedia as the Engine of Application State (HATEOAS) is one of the core constraints of REST. It refers to the concept of embedding hyperlinks into the response of a queried or manipulated resource to show a client possible follow-up actions and transitions to related resources. Thus, this concept aims to provide a client with a navigational support when interacting with a Web-based application. Although HATEOAS should be implemented by any Web-based API claiming to be RESTful, API providers tend to offer service descriptions in place of embedding hyperlinks into responses. Instead of relying on a navigational support, a client developer has to read the service description and has to identify resources and their URIs that are relevant for the interaction with the API. In this paper, we introduce an approach that aims to identify transitions between resources of a Web-based API by systematically analyzing the service description only. We devise an algorithm that automatically derives a URI Model from the service description and then analyzes the payload schemas to identify feasible values for the substitution of path parameters in URI Templates. We implement this approach as a proxy application, which injects hyperlinks representing transitions into the response payload of a queried or manipulated resource. The result is a HATEOAS-like navigational support through an API. Our first prototype operates on service descriptions in the OpenAPI format. We evaluate our approach using ten real-world APIs from different domains. Furthermore, we discuss the results as well as the observations captured in these tests.
In der Kryochirurgie wird Kälte verwendet, um tumoröses Gewebe abzutöten. Dazu werden Kryosonden in den Tumor gestochen und stark abgekühlt. Hierbei gibt es verschiedene Herausforderungen, welchen computergestützt begegnet werden kann. Diese Arbeit gibt die Ergebnisse einer Literaturrecherche zu den Herausforderungen wieder. Die vorgestellten Arbeiten beschäftigten sich mit der Simulation des im Tumor entstehenden Eisballs, dem korrekten Positionieren der Kryosonden im Tumor, dem Überwachen des Eingriffs sowie dem Entwickeln von Simulationen für Trainingszwecke. Dabei zeigt sich, dass der Einsatz von computergestützten Lösungen die Kryochirurgie für Operateur und Patient verbessern kann.
In networked operating room environments, there is an emerging trend towards standardized non-proprietary communication protocols which allow to build new integration solutions and flexible human-machine interaction concepts. The most prominent endeavor is the IEEE 11073 SDC protocol. For some uses cases, it would be helpful if not just medical devices could be controlled based on SDC, but also building automation systems like light, shutters, air condition, etc. For those systems, the KNX protocol is widely used. We build an SDC-to-KNX gateway which allows to use the SDC protocol for sending commands to connected KNX devices. The first prototype system was successfully implemented at the demonstration operating room at Reutlingen University. This is a first step toward the integration of a broader variety of KNX devices.
The emergence of agile methods and practices has not only changed the development processes but might also have affected how companies conduct software process improvement (SPI). Through a set of complementary studies, we aim to understand how SPI has changed in times of agile software development. Specifically, we aim (1) to identify and characterize the set of publications that connect elements of agility to SPI, (2) to explore to which extent agile methods/practices have been used in the context of SPI, and (3) to understand whether the topics addressed in the literature are relevant and useful for industry professionals. To study these questions, we conducted an in-depth analysis of the literature identified in a previous mapping study, an interview study, and an analysis of the responses given by industry professionals to SPI-related questions stemming from an independently conducted survey study.
Formula One races provide a wealth of data worth investigating. Although the time-varying data has a clear structure, it is pretty challenging to analyze it for further properties. Here the focus is on a visual classification for events, drivers, as well as time periods. As a first step, the Formula One data is visually encoded based on a line plot visual metaphor reflecting the dynamic lap times, and finally, a classification of the races based on the visual outcomes gained from these line plots is presented. The visualization tool is web-based and provides several interactively linked views on the data; however, it starts with a calendar-based overview representation. To illustrate the usefulness of the approach, the provided Formula One data from several years is visually explored while the races took place in different locations. The chapter discusses algorithmic, visual, and perceptual limitations that might occur during the visual classification of time-series data such as Formula One races.
The typed graph model
(2020)
In recent years, the Graph Model has become increasingly popular, especially in the application domain of social networks. The model has been semantically augmented with properties and labels attached to the graph elements. It is difficult to ensure data quality for the properties and the data structure because the model does not need a schema. In this paper, we propose a schema bound Typed Graph Model with properties and labels. These enhancements improve not only data quality but also the quality of graph analysis. The power of this model is provided by using hyper-nodes and hyper edges, which allows to present a data structure on different abstraction levels. We demonstrate by example the superiority of this model over the property graph data model of Hidders and other prevalent data models, namely the relational, object-oriented, and XML model.
Requirements Engineering (RE) umfasst sämtliche systematische Schritte zur Entwicklung eines Systems, um die Bedürfnisse der Nutzer und Vorgaben, die an dieses gestellt werden, zu erfüllen. Das RE eines ausgewählten Herstellers für klinische Informationssysteme (KIS) wurde untersucht und es stellt sich als intransparent als auch teilweise unzureichend dar. Das Ausmaß des Einsatzes von systematischen Vorgehensweisen und Methoden zum RE wurden beim ausgewählten KIS-Hersteller analysiert. Die Analyse zeigt, dass RE weit verbreitet ist, aber differenziert betrieben wird.
Das Ziel dieser Arbeit ist es, den Stand der Technik des RE für die KIS Entwicklung zu ermitteln. Es werden wichtige Faktoren des RE für die Entwicklung von KIS beschrieben. Die Ergebnisse dieser Arbeit werden als erster Schritt für die Optimierung des RE des ausgewählten KIS-Herstellers dienen.
Enhancing data-driven algorithms for human pose estimation and action recognition through simulation
(2020)
Recognizing human actions, reliably inferring their meaning and being able to potentially exchange mutual social information are core challenges for autonomous systems when they directly share the same space with humans. Intelligent transport systems in particular face this challenge, as interactions with people are often required. The development and testing of technical perception solutions is done mostly on standard vision benchmark datasets for which manual labelling of sensory ground truth has been a tedious but necessary task. Furthermore, rarely occurring human activities are underrepresented in these datasets, leading to algorithms not recognizing such activities. For this purpose, we introduce a modular simulation framework, which offers to train and validate algorithms on various human-centred scenarios. We describe the usage of simulation data to train a state-of-the-art human pose estimation algorithm to recognize unusual human activities in urban areas. Since the recognition of human actions can be an important component of intelligent transport systems, we investigated how simulations can be applied for his purpose. Laboratory experiments show that we can train a recurrent neural network with only simulated data based on motion capture data and 3D avatars, which achieves an almost perfect performance in the classification of those human actions on real data.
Unter dem Begriff Innovation Enabling wird im Folgenden ein Konzept für die ganzheitliche Unterstützung interdisziplinärer Teams beim kreativen und innovativen Problemlösen vor-gestellt. Dieses Konzept unterstützt Moderatoren und Teilnehmergleichermaßen und ein damit realisiertes System bleibt durch die implizite Interaktion für den Nutzer im Hintergrund. Eine zentrale Rolle spielt das Konzept der Awareness Pipeline zur Implementation einer impliziten Interaktion auf Basis eines Sensor-Aktor-Systems, welches in diesem Artikel vorgestellt wird. Die Unterstützung der begleitenden Moderations- und Administrationsaufgaben, wie beispielsweise der automatisierten Dokumentation der Sitzung, sollen in Zukunft einen deutlichen Mehrwert gegenüber einer klassischen Brainstorming-Sitzung bieten.
The livestock sector is growing steadily and is responsible for around 18% of global greenhouse‐gas‐emissions, which is more than the global transport sec-tor (Steinfeld et al. 2006). This paper examines the potential of social marketing to reduce meat consumption. The aim is to understand consumers’ motivation in diet choices and to learn what opportunities social marketing can provide to counteract negative environmental and health trends. The authors believe that research to answer this question should start in metropolitan areas, be-cause measures should be especially effective there. Based on the Theory of Planned Behaviour (TPB, Ajzen 1991) and the Technology‐Acceptance‐Model by Huijts et al. (2012), an online‐study with participants from the metropolitan region (n = 708) was conducted in which central socio‐psychological constructs for a meat consumption reduction were examined. It was shown that attitude, personal norm and habit have a critical influence on the intention to reduce meat consumption. A segmentation of consumers based on these factors led to three consumer clusters: vegetarians/flexitarians, potential flexitarians and convinced meat eaters. Potential flexitarians are an especially relevant target group for the development of social‐marketing‐measures to reduce meat consumption. In co‐creation‐workshops with potential flexitarians from the metropolitan region, barriers and benefits of reducing meat consumption were identified. The factors of environmental protection, animal welfare and desire for variety turn out to be the most relevant motivational factors. Based on these factors, consumers proposed a variety of social marketing measures, such as applications and labels to inform about the environmental impact of meat products.
Product roadmaps are an important tool in product development. They provide direction, enable consistent development in relation to a product vision and support communication with relevant stakeholders. There are many different formats for product roadmaps, but they are often based on the assumption that the future is highly predictable. However, especially software-intensive businesses are faced with increasing market dynamics, rapidly evolving technologies and changing user expectations. As a result, many organizations are wondering what roadmap format is appropriate for them and what components it should have to deal with an unpredictable future. Objectives: To gain a better understanding of the formats of product roadmaps and their components, this paper aims to identify suitable formats for the development and handling of product roadmaps in dynamic and uncertain markets. Method: We performed a grey literature review (GLR) according to the guidelines from Garousi. Results: A Google search identified 426 articles, 25 of which were included in this study. First, various components of the roadmap were identified, especially the product vision, themes, goals, outcomes and outputs. In addition, various product roadmap formats were discovered, such as feature-based, goal-oriented, outcome-driven and a theme-based roadmap. The roadmap components were then assigned to the various product roadmap formats. This overview aims at providing initial decision support for companies to select a suitable product roadmap format and adapt it to their own needs.
In recent years companies have faced challenges by high market dynamics, rapidly evolving technologies and shifting user expectations. Together with the adaption of lean and agile practices, it is increasingly difficult to predict upfront which products, features or services will satisfy the needs of the customers and the organization. Currently, many new products fail to produce a significant financial return. One reason is that companies are not doing enough product discovery activities. Product discovery aims at tackling the various risks before the implementation of a product starts. The academic literature only provides little guidance for conducting product discovery in practice. Objective: In order to gain a better understanding of product discovery activities in practice, this paper aims at identifying motivations, approaches, challenges, risks, and pitfalls of product discovery reported in the grey literature. Method: We performed a grey literature review (GLR) according to the guidelines to Garousi et al. Results: The study shows that the main motivation for conducting product discovery activities is to reduce the uncertainty to a level that makes it possible to start building a solution that provides value for the customers and the business. Several product discovery approaches are reported in the grey literature which include different phases such as alignment, problem exploration, ideation, and validation. Main challenges are, among others, the lack of clarity of the problem to be solved, the prescription of concrete solutions through management or experts, and the lack of cross-functional collaboration.
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.
Method: We conducted semi-structured expert interviews with 15 experts from 13 German companies and conducted athematic 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 establishing discovery activities.
In dieser Arbeit werden drei verschiedene Testumgebungen vorgestellt, welche in ein iteratives Vorgehen einfließen, um die Entwicklung von Augmented-Reality-Anwendungen zur Darstellung von autonomen Fahrfunktionen zu unterstützen.
Gestaltungsentwürfe und Softwareentwicklungen können in den Testumgebungen für unterschiedliche Zielsetzungen von Personenbefragungen vorgestellt und bewertet werden. Das entwicklungsbegleitende Testen ermöglicht eine frühzeitige Identifizierung von Änderungshinweisen, welche für einen gültigen Lösungsentwurf eingearbeitet werden können. Die entwickelten Testumgebungen sind ein verkleinertes Modell, ein Fahrsimulator und ein reales Fahrzeug. Eigenschaften, Funktionen und Aufbauten resultieren aus Erkenntnissen der Literatur und Erfahrungen aus ersten Entwicklungen. Diese und die Einsatzmöglichkeiten werden mit dieser Arbeit aufgezeigt.
Modern mixed (HTAP)workloads execute fast update-transactions and long running analytical queries on the same dataset and system. In multi-version (MVCC) systems, such workloads result in many short-lived versions and long version-chains as well as in increased and frequent maintenance overhead.
Consequently, the index pressure increases significantly. Firstly, the frequent modifications cause frequent creation of new versions, yielding a surge in index maintenance overhead. Secondly and more importantly, index-scans incur extra I/O overhead to determine, which of the resulting tuple versions are visible to the executing transaction (visibility-check) as current designs only store version/timestamp information in the base table – not in the index. Such index-only visibility-check is critical for HTAP workloads on large datasets.
In this paper we propose the Multi Version Partitioned B-Tree (MV-PBT) as a version-aware index structure, supporting index-only visibility checks and flash-friendly I/O patterns. The experimental evaluation indicates a 2x improvement for analytical queries and 15% higher transactional throughput under HTAP workloads. MV-PBT offers 40% higher tx. throughput compared to WiredTiger’s LSM-Tree implementation under YCSB.
The advent of chatbots in customer service solutions received increasing attention by research and practice throughout the last years. However, the relevant dimensions and features for service quality and service performance for chatbots remain quite unclear. Therefore, this research develops and tests a conceptual model for customer service quality and customer service performance in the context of chatbots. Additionally, the impact of the developed service dimensions on different customer relationship metrics is measured across different service channels (hotline versus chatbots). Findings of six independent studies indicate a strong main effect of the conceptualized service dimensions on customer satisfaction, service costs, intention to service reusage, word-of-mouth, and customer loyalty. However, different service dimensions are relevant for chatbots compared to a traditional service hotline.
A holistic approach to digitization enables decision-makers to achieve new efficiency in corporate performance management. The digitalization improves the quality, validity and speed of information retrieval and processing. At present, most corporations are confronted with the problem of not being able to organize, categorize and visualize decision-relevant information. To meet the challenges of information management, the Management Cockpit provides an information center for managers. In accordance with the specific working environment of the executives, the Management Cockpit offers a quick and comprehensive overview of the company's situation. Today, the current situation of a company is no longer only influenced by internal factors, but also by its public image. Social media monitoring and analysis is therefore a crucial component for the external factors of successful management. Real-time monitoring of the emotions and behaviors of consumers and customers thus contributes to effective controlling of allbusiness areas. The intelligent factories promise to collect data for internal factors, but the current reality in manufacturing looks different. Production often consists of a large number of different machines, with varying degrees of digitization and limited sensor data availability. In order to close this gap, we developed a compact sensor board with network components, which allows a flexible design with different sensors for a wide variety of applications. The sensor data enable decision makers to adapt the supply chain based on their internal and external observations in the Management Cockpit. Due to the realtime and long-term monitoring and analytic possibilities the Management Cockpit provides a multi-dimensional view of the company and supports an holistic Corporate Performance Management.
Checklists are a valuable tool to ensure process quality and quality of care. To ensure proper integration in clinical processes, it would be desirable to generate checklists directly from formal process descriptions. Those checklists could also be used for user interaction in context-aware surgical assist systems. We built a tool to automatically convert Business Process Model and Notation (BPMN) process models to checklists displayed as HTML websites. Gateways representing decisions are mapped to checklist items that trigger dynamic content loading based on the placed checkmark. The usability of the resulting system was positively evaluated regarding comprehensibility and end-user friendliness.
Going forward with the requirements of missions to the Moon and further into deep space, the European Space Agency is investigating new methods of astronaut training that can help accelerate learning, increase availability and reduce complexity and cost in comparison to currently used methods. To achieve this, technologies such as virtual reality may be utilized. In this paper, an investigation into the benefits of using virtual reality as a means for extravehicular activity training in comparison to conventional training methods, such as neutral buoyancy pools is given. To help determine the requirements and current uses of virtual reality for extravehicular activity training first hand tests of currently available software as well as expert interviews are utilized. With this knowledge a concept is developed that may be used to further advance training methods in virtual reality. The resulting concept is used as a basis for development of a prototype to showcase user interactions and locomotion in microgravity simulations.
Digital technologies are main strategic drivers for digitalization and offer ubiquitous data availability, unlimited connectivity, and massive processing power for a fundamentally changing business. This leads to the development and application of intelligent digital systems. The current state of research and practice of architecting digital systems and services lacks a solid methodological foundation that fully accommodates all requirements linked to efficient and effective development of digital systems in organizations. Research presented in this paper addresses the question, how management of complexity in digital systems and architectures can be supported from a methodological perspective. In this context, the current focus is on a better understanding of the causes of increased complexity and requirements to methodological support. For this purpose, we take an enterprise architecture perspective, i.e. how the introduction of digital systems affects the complexity of EA. Two industrial case studies and a systematic literature analysis result in the proposal of an extended Digital Enterprise Architecture Cube as framework for future methodical support.
Cardiovascular diseases are directly or indirectly responsible for up to 38.5% of all deaths in Germany and thus represent the most frequent cause of death. At present, heart diseases are mainly discovered by chance during routine visits to the doctor or when acute symptoms occur. However, there is no practical method to proactively detect diseases or abnormalities of the heart in the daily environment and to take preventive measures for the person concerned. Long-term ECG devices, as currently used by physicians, are simply too expensive, impractical, and not widely available for everyday use. This work aims to develop an ECG device suitable for everyday use that can be worn directly on the body. For this purpose, an already existing hardware platform will be analyzed, and the corresponding potential for improvement will be identified. A precise picture of the existing data quality is obtained by metrological examination, and corresponding requirements are defined. Based on these identified optimization potentials, a new ECG device is developed. The revised ECG device is characterized by a high integration density and combines all components directly on one board except the battery and the ECG electrodes. The compact design allows the device to be attached directly to the chest. An integrated microcontroller allows digital signal processing without the need for an additional computer. Central features of the evaluation are a peak detection for detecting R-peaks and a calculation of the current heart rate based on the RR interval. To ensure the validity of the detected R-peaks, a model of the anatomical conditions is used. Thus, unrealistic RR-intervals can be excluded. The wireless interface allows continuous transmission of the calculated heart rate. Following the development of hardware and software, the results are verified, and appropriate conclusions about the data quality are drawn. As a result, a very compact and wearable ECG device with different wireless technologies, data storage, and evaluation of RR intervals was developed. Some tests yelled runtimes up to 24 hours with wireless Lan activated and streaming.
In previous studies, we used a method for detecting stress that was based exclusively on heart rate and ECG for differentiation between such situations as mental stress, physical activity, relaxation, and rest. As a response of the heart to these situations, we observed different behavior in the Root Mean Square of the Successive differences heartbeats (RMSSD). This study aims to analyze Virtual Reality via a virtual reality headset as an effective stressor for future works. The value of the Root Mean Square of the Successive Differences is an important marker for the parasympathetic effector on the heart and can provide information about stress. For these measurements, the RR interval was collected using a breast belt. In these studies, we can observe the Root Mean Square of the successive differences heartbeats. Additional sensors for the analysis were not used. We conducted experiments with ten subjects that had to drive a simulator for 25 minutes using monitors and 25 minutes using virtual reality headset. Before starting and after finishing each simulation, the subjects had to complete a survey in which they had to describe their mental state. The experiment results show that driving using virtual reality headset has some influence on the heart rate and RMSSD, but it does not significantly increase the stress of driving.
Methods based exclusively on heart rate hardly allow to differentiate between physical activity, stress, relaxation, and rest, that is why an additional sensor like activity/movement sensor added for detection and classification. The response of the heart to physical activity, stress, relaxation, and no activity can be very similar. In this study, we can observe the influence of induced stress and analyze which metrics could be considered for its detection. The changes in the Root Mean Square of the Successive Differences provide us with information about physiological changes. A set of measurements collecting the RR intervals was taken. The intervals are used as a parameter to distinguish four different stages. Parameters like skin conductivity or skin temperature were not used because the main aim is to maintain a minimum number of sensors and devices and thereby to increase the wearability in the future.
The automation of work by means of disruptive technologies such as Artificial Intelligence (AI) and Robotic Process Automation (RPA) is currently intensely discussed in business practice and academia. Recent studies indicate that many tasks manually conducted by humans today will not in the future. In a similar vein, it is expected that new roles will emerge. The aim of this study is to analyze prospective employment opportunities in the context of RPA in order to foster our understanding of the pivotal qualifications, expertise and skills necessary to find an occupation in a completely changing world of work. This study is based on an explorative, content analysis of 119 job advertisements related to RPA in Germany. The data was collected from major German online job platforms, qualitatively coded, and subsequently analyzed quantitatively. The research indicates that there indeed are employment opportunities, especially in the consulting sector. The positions require different technological expertise such as specific programming languages and knowledge in statistics. The results of this study provide guidance for organizations and individuals on reskilling requirements for future employment. As many of the positions require profound IT expertise, the generally accepted perspective that existing employees affected by automation can be retrained to work in the emerging positions has to be seen extremely critical. This paper contributes to the body of knowledge by providing a novel perspective on the ongoing discussion of employment opportunities, and reskilling demands of the existing workforce in the context of recent technological developments and automation.
Haptisches Feedback ist nach zahlreichen Studien ein wichtiger Bestandteil in der medizinischen Robotik. Die meisten Systeme befinden sich jedoch noch im Forschungsstatus und verfolgen unterschiedliche Ansätze. In der Teleoperation wird mit sensorlosen und Sensor-Systemen geforscht. Sensoren bieten, im Gegensatz zu den Encodern in sensorlosen Systemen, genaue Messungen, sind allerdings teuer in der Anschaffung, schwer zu desinfizieren und müssen in OP-Besteck integriert werden. In Hands-On Systemen fühlt der Operateur im Gegensatz zu Teleoperationssystemen direkt die auftretenden Kräfte bei der Benutzung. Der Roboter bietet in diesen Systemen nur die benötigte Stabilität und Genauigkeit, gesteuert werden sie direkt durch den Menschen. Dagegen werden in Teleoperationssystemen gezielte Controller eingesetzt. Hier hat sich der für den OP entwickelte sigma.7 durchgesetzt. Gegenüber der für die Allgemeinheit entwickelten Konkurrenz bietet er haptisches Feedback in allen nötigen Freiheitsgraden und eine entsprechende Kraftrückkoppelung.
AI technologies such as deep learning provide promising advances in many areas. Using these technologies, enterprises and organizations implement new business models and capabilities. In the beginning, AI-technologies have been deployed in an experimental environment. AI-based applications have been created in an ad-hoc manner and without methodological guidance or engineering approach. Due to the increasing importance of AI-technologies, however, a more structured approach is necessary that enable the methodological engineering of AI-based applications. Therefore, we develop in this paper first steps towards methodological engineering of AI-based applications. First, we identify some important differences between the technological foundations of AI- technologies, in particular deep learning, and traditional information technologies. Then we create a framework that enables to engineer AI-applications using four steps: identification of an AI-application type, sub-type identification, lifecycle phase, and definition of details. The introduced framework considers that AI-applications use an inductive approach to infer knowledge from huge collections and streams of data. It not only enables the rapid development of AI-application but also the efficient sharing of knowledge on AI-applications.
Artificial Intelligence enables innovative applications, and applications based on Artificial Intelligence are increasingly important for all aspects of the Digital Economy. However, the question of how AI resources such as tools and data can be linked to provide an AI-capability and create business value is still open. Therefore, this paper identifies the value-creating mechanisms of connectionist artificial intelligence using a capability-oriented view and points out the connections to different kinds of business value. The analysis supports an agenda that identifies areas that need further research to understand the mechanism of value creation in connectionist artificial intelligence.
Systemische Betrachtung des therapeutischen Roboters Paro im Vergleich zu dem Haustierroboter AIBO
(2020)
Roboter sind in der heutigen Zeit nicht nur in der Industrie zu finden, sondern werden immer häufiger in privaten Lebensbereichen eingesetzt. Ein Beispiel hierfür ist der soziale Therapie-Roboter Paro. Dieser ist dem Verhalten und Aussehen einer jungen Robbe nachempfunden, drückt Gefühle aus und wird besonders in Pflegeheimen eingesetzt. Dabei zeigt er positive Auswirkungen auf das Wohlbefinden pflegebedürftiger Menschen. Diese Arbeit stellt den Roboter Paro in einer systemischen Analyse dar: hierbei werden Systemkontext, Anwendungsfälle, Anforderungen und Struktur betrachtet. Anschließend erfolgt eine Analyse des Haustierroboters AIBO, welcher einem Welpen ähnelt und verstärkt der Unterhaltung von Privatpersonen dient. Es werden Gemeinsamkeiten und Unterschiede zwischen den Systemen herausgearbeitet. Dabei wird ersichtlich, dass beide Systeme dem Nutzer vorrangig Gesellschaft leisten, jedoch verschiedene Anforderungen besitzen und in unterschiedlichen Anwendungsdomänen eingesetzt werden. Zudem besitzt AIBO vielfältigere Fähigkeiten und einen höheren Bewegungsgrad als Paro. Dies spiegelt sich in einer komplexeren Struktur der Hardware wider.
Die Entwicklung eines Medizinproduktes benötigt in der Regel mehrere Jahre. Gesetzliche Vorgaben, wie zum Beispiel das Medizinprodukte Durchführungsgesetz, bestimmen, welche Schritte während der Entwicklung durchgeführt werden müssen. Deren Einhaltung muss in der technischen Dokumentation nachgewiesen werden. Die darin enthaltenen technischen Dokumente entstehen im Verlauf der Entwicklung. Diese bauen aufeinander auf und verweisen sich gegenseitig. Dadurch entstehen heterogene und unübersichtliche Strukturen. Eine Lösung für dieses Problem bietet Traceability. Traceability sorgt dafür, dass die Anforderungen an das Medizinprodukt mit Dokumenten, wie dem Anforderungskatalog, Lastenheft oder der Spezifikation verknüpft werden können. Somit ist jederzeit nachvollziehbar, welche Anforderungen mit welchem Test, welchen Änderungen oder welchen Ergebnissen zusammenhängen. Ein wichtiger Prozess bei der Entwicklung von Medizinprodukten ist zudem das Usability Engineering, wodurch die Sicherheit eines Medizinprodukts sichergestellt und Risiken bei der Anwendung minimiert werden sollen. In diesem Prozess entstehen viele Artefakte, wie zum Beispiel Usability-Berichte. Um den Überblick über alle Usability-Daten behalten zu können, können diese mithilfe von Traceability verknüpft werden. In diesem Artikel wird herausgestellt, welche Voraussetzungen für das Usability Engineering in der Medizintechnik an Traceability gestellt
werden.
This work is a study about a comparison of survey tools and it should help developers in selecting a suited tool for application in an AAL environment. The first step was to identify the basic required functionality of the survey tools used for AAL technologies and to compare these tools by their functionality and assignments. The comparative study was derived from the data obtained, previous literature studies and further technical data. A list of requirements was stated and ordered in terms of relevance to the target application domain. With the help of an integrated assessment method, the calculation of a generalized estimate value was performed and the result is explained. Finally, the planned application of this tool in a running project is explained.
Hardly any software development process is used as prescribed by authors or standards. Regardless of company size or industry sector, a majority of project teams and companies use hybrid development methods (short: hybrid methods) that combine different development methods and practices. Even though such hybrid methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. In this article, we make a first step towards a statistical construction procedure for hybrid methods. Grounded in 1467 data points from a large‐scale practitioner survey, we study the question: What are hybrid methods made of and how can they be systematically constructed? Our findings show that only eight methods and few practices build the core of modern software development. Using an 85% agreement level in the participants' selections, we provide examples illustrating how hybrid methods can be characterized by the practices they are made of. Furthermore, using this characterization, we develop an initial construction procedure, which allows for defining a method frame and enriching it incrementally to devise a hybrid method using ranked sets of practice.
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. Based on 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.
Facial expressions play a dominant role in facilitating social interactions. We endeavor to develop tactile displays to reinstate facial expression modulated communication. The high spatial and temporal dimensionality of facial movements poses a unique challenge when designing tactile encodings of them. A further challenge is developing encodings that are at-tuned to the perceptual characteristics of our skin. A caveat of using vibrotactile displays is that tactile stimuli have been shown to induce perceptual tactile aftereffects when used on the fingers, arm and face. However, at present, despite the prevalence of waist-worn tactile displays, no such investigations of tactile aftereffects at the waist region exist in the literature, though they are warranted by the unique sensory and perceptual signalling characteristics of this area. Using an adaptation paradigm we investigated the presence of perceptual tactile aftereffects induced by continuous and burst vibrotactile stimuli delivered at the navel, side and spinal regions of the waist. We report evidence that the tactile perception topology of the waist is non-uniform, and specifically that the navel and spine regions are resistant to adaptive aftereffects while side regions are more prone to perceptual adaptations to continuous but not burst stimulations. Results of our current investigations highlight the unique set of challenges posed by designing waist-worn tactile displays. These and future perceptual studies can directly inform more realistic and effective implementations of complex high-dimensional spatiotemporal social cues.
Context: A product roadmap is an important tool in product development. It sets the strategic direction in which the product is to be developed to achieve the company’s vision. However, for product roadmaps to be successful, it is essential that all stakeholders agree with the company’s vision and objectives and are aligned and committed to a common product plan.
Objective: In order to gain a better understanding of product roadmap alignment, this paper aims at identifying measures, activities and techniques in order to align the different stakeholders around the product roadmap.
Method: We conducted a grey literature review according the guidelines to Garousi et al.
Results: Several approaches to gain alignment were identified such as defining and communicating clear objectives based on the product vision, conducting cross-functional workshops, shuttle diplomacy, and mission briefing. In addition, our review identified the “Behavioural Change Stairway Model” that suggests five steps to gain alignment by building empathy and a trustful relationship.
Nowadays companies are facing increasing market dynamics, rapidly evolving technologies and shifting user expectations. Together with the adoption of lean and agile practices this situation makes it increasingly difficult to plan and predict upfront which products, services or features should be developed in the future. Consequently, many organizations are struggling with their ability to provide reliable and stable product roadmaps by applying traditional approaches. This paper aims at identifying and getting a better understanding of which measures companies have taken to transform their current product roadmapping practices to the requirements of a dynamic and uncertain market environment. This also includes challenges and success factors within this transformation process as well as measures that companies have planned for the future. We conducted 18 semi-structured expert interviews with practitioners of different companies and performed a thematic data analysis. The study shows that the participating companies are aware that the transformation of traditional product roadmapping practices to fulfill the requirements of a dynamic and uncertain market environment is necessary. The most important measures that the participating companies have taken are 1) adequate item planning concerning the timeline, 2) the replacement of a fixed time-based chart by a more flexible structure, 3) the use of outcomes to determine the items (such as features) on the a roadmap, 4) the creation of a central roadmap which allows deriving different representation for each stakeholder and department.
It is essential for the success of a company to set a strategic direction in which a product offering will be developed over time to achieve the company vision. For this reason, roadmaps are used in practice. in general, roadmaps can be expressed in various forms such as technology roadmaps, product roadmaps or industry roadmaps. From the point of view of industry, the basic purpose of a roadmap is to explore, visualize and communicate the dynamic linkage between markets, products and technology.
Due to decreased mobility or families living apart, older adults are especially vulnerable to the issue of social isolation. Literature suggests that technology can help to prevent this isolation. The present work addresses an approach to participate in society by sharing knowledge that is cherished. We propose the cooking recipe exchange application PrecRec for older adults to make them feel precious and valued. PrecRec has been developed and evaluated in an iterative process with eleven older adults. The results show that a broad perspective has to be taken into account when designing such systems.
IT governance: current state of and future perspectives on the concept of agility in IT governance
(2020)
Digital transformation has changed corporate reality and, with that, corporates’ IT environments and IT governance (ITG). As such, the perspective of ITG has shifted from the design of a relatively stable, closed and controllable system of a self-sufficient enterprise to a relatively fluid, open, agile and transformational system of networked co-adaptive entities. Related to the paradigm shift in ITG, this thesis aims to conceptualize a framework to integrate the concept of agility into the traditional ITG framework and to test the effects of such an extended ITG framework on corporate performance.
To do so, the thesis uses literature research and a mixed method design by blending both qualitative and quantitative research methods. Given the poorly understood situation of the agile mechanisms within the ITG framework, the building process of this thesis’ research model requires an adaptive and flexible approach which involves four different research phases. The initial a priori research model based on a comprehensive review of the extant literature is critically examined and refined at the end of each research phase, which later forms the basis of a subsequent research phase. As a result, the final research model provides guidance on how the conceptualized framework leads to better business/IT alignment as well as how business/IT alignment can mediate the effectiveness of such an extended ITG framework on corporate performance.
The first research phase explores the current state of literature with a focus on the ITG-corporate performance association. This analysis identifies five perspectives with respect to the relationship between ITG and corporate performance. The main variables lead to the perspectives of business/IT alignment, IT leadership, IT capability and process performance, resource relatedness and culture. Furthermore, the analysis presents core aspects explored within the identified perspectives that could act as potential mediators or moderators in the relationship between ITG and corporate performance.
The second research phase investigates the agile aspect of an effective ITG framework in the dynamic contemporary world through a qualitative study. Gleaned from 46 semi-structured interviews across various industries with governance experts, the study identifies 25 agile ITG mechanisms and 22 traditional ITG mechanisms that corporations use to master digital transformation projects. Moreover, the research offers two key patterns indicating to a call for ambidextrous ITG, with corporations alternating between stability and agility in their ITG mechanisms.
In research phase three, a scale development process is conducted in order to develop the agile items explored in research phase two. Through 56 qualitative interviews with professionals the evaluation uncovers 46 agile governance mechanisms. Moreover, these dimensions are rated by 29 experts to identify the most effective ones. This leads to the identification of six structure elements, eight processes, and eight relational mechanisms.
Finally, in research phase four a quantitative research approach through a survey of 400 respondents is established to test and predict the formulated relationships by using the partial least squares structural equation modelling (PLS-SEM) method. The results provide evidence for a strong causal relationship among an expanded ITG concept, business/IT alignment, and corporate performance. These findings reveal that the agile ITG mechanisms within an effective ITG framework seem critical in today’s digital age.
This research is unique in exploring the combination of traditional and agile ITG mechanisms. It contributes to the theoretical base by integrating and extending the literature on ITG, business/IT alignment, ambidexterity and agility, all of which have long been recognized as critical for achieving organizational goals. In summary, this work presents an original analysis of an effective ITG framework for digital transformation by including the agile aspect within the ITG construct. It highlights that is not enough to apply only traditional mechanisms to achieve effective business/IT alignment in today’s digital age; agile ITG mechanisms are also needed. Therefore, a novel ITG framework following an ambidextrous approach is provided consisting of traditional ITG mechanisms as well as newly developed agile ITG practices. This thesis also demonstrates that agile ITG mechanisms can be measured independently of traditional ITG mechanisms within one causal model. This is an important theoretical outcome that allows the current state of ITG to be assessed in two distinct dimensions, offering various pathways for further research on the different antecedents and effects of traditional and agile ITG mechanisms. Furthermore, this thesis makes practical contributions by highlighting the need to develop a basic governance framework powered by traditional ITG mechanisms and simultaneously increase agility in ITG mechanisms. The results imply that corporations might be even more successful if they include both traditional and agile mechanisms in their ITG framework. In this way, the uncovered agile ITG practices may provide a template for CIOs to derive their own mechanisms in following an ambidextrous approach that is suitable for their corporation.
With significant advancements in digital technologies, firms find themselves competing in an increasingly dynamic business environment. It is of paramount importance that organizations undertake proper governance mechanisms with respect to their business and IT strategies. Therefore, IT governance (ITG) has become an important factor for firm performance. In recent years, agility has evolved as a core concept for governance, especially in the area of software development. However, the impact of agility on ITG and firm performance has not been analyzed by the broad scientific community. This paper focuses on the question, how the concept of agility affects the ITG–firm performance relationship. The conceptual model for this question was tested by a quantitative research process with 400 executives responding to a standardized survey. Findings show that the adoption of agile principles, values, and best practices to the context of ITG leads to meaningful results for governance, business/IT alignment, and firm performance.
Ein nicht unerheblicher Anteil der Autounfälle ist auf Müdigkeit am Steuer zurückzuführen. Um Unfälle aufgrund von Müdigkeit zu vermeiden, existieren schon einige Ansätze wie beispielsweise die Erkennung der Fahrweise. Im Rahmen des IOT-Labors des Masterstudiengangs Human Centered Computing der Hochschule Reutlingen sollen verschiedene Fahrassistenzsysteme entwickelt und getestet werden, um Unfälle aufgrund von Müdigkeit zu verhindern. Diese Arbeit beschäftigt sich mit der Müdigkeitserkennung über Computer Vision (CV) und das Elektrokardiogramm (EKG). Im Rahmen dieses Papers wird die Müdigkeitserkennung über CV am Steuer mittels den Open Source Bibliotheken OpenCV und Dlib und dem Embedded PC Nvidia Jetson Nano verwirklicht. Die Müdigkeit über EKG wird über den Herzschlag und die Herzfrequenzvariabilität erkannt. Ebenfalls wurde in dieser Arbeit eine Schnittstelle aus CV und EKG entwickelt, um aus den Python-Skripten der Müdigkeitserkennung über Computer Vision und der Müdigkeitserkennung über EKG die zur Erkennung wichtigen Daten zusammenzufassen. Diese werden anschließend zu einem gesamten Ergebnis ausgewertet.
The field of breath analysis has developed to be of growing interest in medical diagnosis and patient monitoring. The main advantages are that it’s noninvasive, painless and repeatable in flexible cycles. Even though breath analysis is being researched for a couple of decades there are still many unanswered questions. Human breath contains volatile organic compounds which are emitted from inside the body. Some of these compounds can be assigned to specific sources, such as inflammation or cancer, but also to non health related origins. This paper gives an overview of breath analysis for the purpose of disease diagnosis and health monitoring. Therefore, literature regarding breath analysis in the medical field has been analyzed, from its early stages to the present. As a result, this paper gives an outline of the topic of breath analysis.
nKV in action: accelerating KVstores on native computational storage with NearData processing
(2020)
Massive data transfers in modern data intensive systems resulting from low data-locality and data-to-code system design hurt their performance and scalability. Near-data processing (NDP) designs represent a feasible solution, which although not new, has yet to see widespread use.
In this paper we demonstrate various NDP alternatives in nKV, which is a key/value store utilizing native computational storage and near-data processing. We showcase the execution of classical operations (GET, SCAN) and complex graph-processing algorithms (Betweenness Centrality) in-situ, with 1.4x-2.7x better performance due to NDP. nKV runs on real hardware - the COSMOS+ platform.
Massive data transfers in modern key/value stores resulting from low data-locality and data-to-code system design hurt their performance and scalability. Near-data processing (NDP) designs represent a feasible solution, which although not new, have yet to see widespread use.
In this paper we introduce nKV, which is a key/value store utilizing native computational storage and near-data processing. On the one hand, nKV can directly control the data and computation placement on the underlying storage hardware. On the other hand, nKV propagates the data formats and layouts to the storage device where, software and hardware parsers and accessors are implemented. Both allow NDP operations to execute in host-intervention-free manner, directly on physical addresses and thus better utilize the underlying hardware. Our performance evaluation is based on executing traditional KV operations (GET, SCAN) and on complex graph-processing algorithms (Betweenness Centrality) in-situ, with 1.4×-2.7× better performance on real hardware – the COSMOS+ platform.
Massive data transfers in modern data intensive systems resulting from low data-locality and data-to-code system design hurt their performance and scalability. Near-data processing (NDP) and a shift to code-to-data designs may represent a viable solution as packaging combinations of storage and compute elements on the same device has become viable.
The shift towards NDP system architectures calls for revision of established principles. Abstractions such as data formats and layouts typically spread multiple layers in traditional DBMS, the way they are processed is encapsulated within these layers of abstraction. The NDP-style processing requires an explicit definition of cross-layer data formats and accessors to ensure in-situ executions optimally utilizing the properties of the underlying NDP storage and compute elements. In this paper, we make the case for such data format definitions and investigate the performance benefits under NoFTL-KV and the COSMOS hardware platform.
Purpose: Gliomas are the most common and aggressive type of brain tumors due to their infiltrative nature and rapid progression. The process of distinguishing tumor boundaries from healthy cells is still a challenging task in the clinical routine. Fluid attenuated inversion recovery (FLAIR) MRI modality can provide the physician with information about tumor infiltration. Therefore, this paper proposes a new generic deep learning architecture, namely DeepSeg, for fully automated detection and segmentation of the brain lesion using FLAIR MRI data.
Methods: The developed DeepSeg is a modular decoupling framework. It consists of two connected core parts based on an encoding and decoding relationship. The encoder part is a convolutional neural network (CNN) responsible for spatial information extraction. The resulting semantic map is inserted into the decoder part to get the full-resolution probability map. Based on modified U-Net architecture, different CNN models such as residual neural network (ResNet), dense convolutional network (DenseNet), and NASNet have been utilized in this study.
Results: The proposed deep learning architectures have been successfully tested and evaluated on-line based on MRI datasets of brain tumor segmentation (BraTS 2019) challenge, including s336 cases as training data and 125 cases for validation data. The dice and Hausdorff distance scores of obtained segmentation results are about 0.81 to 0.84 and 9.8 to 19.7 correspondingly.
Conclusion: This study showed successful feasibility and comparative performance of applying different deep learning models in a new DeepSeg framework for automated brain tumor segmentation in FLAIR MR images. The proposed DeepSeg is open source and freely available at https://github.com/razeineldin/DeepSeg/.
Intraoperative brain deformation, so called brain shift, affects the applicability of preoperative magnetic resonance imaging (MRI) data to assist the procedures of intraoperative ultrasound (iUS) guidance during neurosurgery. This paper proposes a deep learning-based approach for fast and accurate deformable registration of preoperative MRI to iUS images to correct brain shift. Based on the architecture of 3D convolutional neural networks, the proposed deep MRI-iUS registration method has been successfully tested and evaluated on the retrospective evaluation of cerebral tumors (RESECT) dataset. This study showed that our proposed method outperforms other registration methods in previous studies with an average mean squared error (MSE) of 85. Moreover, this method can register three 3D MRI-US pair in less than a second, improving the expected outcomes of brain surgery.
Background
The actual task of electrocardiographic examinations is to increase the reliability of diagnosing the condition of the heart. Within the framework of this task, an important direction is the solution of the inverse problem of electrocardiography, based on the processing of electrocardiographic signals of multichannel cardio leads at known electrode coordinates in these leads (Titomir et al. Noninvasiv electrocardiotopography, 2003), (Macfarlane et al. Comprehensive Electrocardiology, 2nd ed. (Chapter 9), 2011).
Results
In order to obtain more detailed information about the electrical activity of the heart, we carry out a reconstruction of the distribution of equivalent electrical sources on the heart surface. In this area, we hold reconstruction of the equivalent sources during the cardiac cycle at relatively low hardware cost. ECG maps of electrical potentials on the surface of the torso (TSPM) and electrical sources on the surface of the heart (HSSM) were studied for different times of the cardiac cycle. We carried out a visual and quantitative comparison of these maps in the presence of pathological regions of different localization. For this purpose we used the model of the heart electrical activity, based on cellular automata.
Conclusions
The model of cellular automata allows us to consider the processes of heart excitation in the presence of pathological regions of various sizes and localization. It is shown, that changes in the distribution of electrical sources on the surface of the epicardium in the presence of pathological areas with disturbances in the conduction of heart excitation are much more noticeable than changes in ECG maps on the torso surface.
Today, many companies are adapting their strategy, business models, products, services as well as business processes and information systems in order to expand their digitalization level through intelligent systems and services. The paper raises an important question: What are cognitive co-creation mechanisms for extending digital services and architectures to readjust the usage value of smart services? Typically, extensions of digital services and products and their architectures are manual design tasks that are complex and require specialized, rare experts. The current publication explores the basic idea of extending specific digital artifacts, such as intelligent service architectures, through mechanisms of cognitive co-creation to enable a rapid evolutionary path and better integration of humans and intelligent systems. We explore the development of intelligent service architectures through a combined, iterative, and permanent task of co-creation between humans and intelligent systems as part of a new concept of cognitively adapted smart services. In this paper, we present components of a new platform for the joint co-creation of cognitive services for an ecosystem of intelligent services that enables the adaptation of digital services and architectures.
Intelligent systems and services are the strategic targets of many current digitalization efforts and part of massive digital transformations based on digital technologies with artificial intelligence. Digital platform architectures and ecosystems provide an essential base for intelligent digital systems. The paper raises an important question: Which development paths are induced by current innovations in the field of artificial intelligence and digitalization for enterprise architectures? Digitalization disrupts existing enterprises, technologies, and economies and promotes the architecture of cognitive and open intelligent environments. This has a strong impact on new opportunities for value creation and the development of intelligent digital systems and services. Digital technologies such as artificial intelligence, the Internet of Things, service computing, cloud computing, blockchains, big data with analysis, mobile systems, and social business network systems are essential drivers of digitalization. We investigate the development of intelligent digital systems supported by a suitable digital enterprise architecture. We present methodological advances and an evolutionary path for architectures with an integral service and value perspective to enable intelligent systems and services that effectively combine digital strategies and digital architectures with artificial intelligence.
Artificial Intelligence-based Assistants AIAs are spreading quickly both in homes and offices. They already have left their original habitats of "intelligent speakers" providing easy access to music collections. The initiated a multitude of new devices and are already populating devices such as TV sets. Characteristic for the intelligent digital assistants is the formation of platforms around their core functionality. Thus, AIS capabilities of the assistants are used to offer new services and create new interfaces for business processes. There are positive network effects between the assistants and the services as well as within the services. Therefore, many companies see the need to get involved in the field of digital assistants but lack a framework to align their initiatives with their corporate strategies. In order to lay the foundation for a comprehensive method, we are therefore investigating intelligent digital assistants. Based on this analysis, we are developing a framework of strategic opportunities and challenges.
A fast way to test business ideas and to explore customer problems and needs is to talk to them. Customer interviews help to understand what solutions customers will pay for before investing valuable resources to develop solutions. Customer interviews are a good way to gain qualitative insights. However, conducting interviews can be a difficult procedure and requires specific skills. The current ways of teaching interview skills have significant deficiencies. They especially lack guidance and opportunities to practice. Objective: The goal of this work is to develop and validate a workshop format to teach interview skills for conducting good customer interviews in a practical manner. Method: The research method is based on design science research which serves as a framework. A game-based workshop format was designed to teach interview skills. The approach consists of a half-day, hands-on workshop and is based on an analysis of necessary interview skills. The approach has been validated in several workshops and improved based on learnings from those workshops. Results: Results of the validation show that participants could significantly improve their interview skills while enjoying the game-based exercises. The game-based learning approach supports learning and practicing customer interview skills with playful and interactive elements that encourage greater motivation among participants to conduct interviews.
Motto der Herbstkonferenz Informatics Inside 2020 ist KInside. Wieder einmal blicken Studierende inside und schauen sich Methoden, Anwendungen und Zusammenhänge genauer an. Die Beiträge sind vielfältig und entsprechend dem Studiengang human-centered. Es ist der Anspruch, dass sich die Themen um die Bedürfnisse der Menschen drehen und eingesetzte Methoden kein Selbstzweck sind, sondern am Nutzen für den Menschen gemessen werden.
The Twelfth International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2020) continued a series of 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 load-balancing 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.
Anhaltend erlebt die Künstliche Intelligenz (KI) eine Renaissance in vielen Branchen. Der Trend, komplexe Zusammenhänge in Daten zu erfassen und zu nutzen, hält an. Hierbei ist jedoch der Grundgedanke des Maschinellen Lernens basierend auf empirischen Daten nicht neu. Es bleibt nach wie vor die Herausforderung, erst ein oft auch interdisziplinäres Verständnis von komplexen Zusammenhängen für verschiedenste Anwendungs-Domänen zu gewinnen, um zum Beispiel KI sinnvoll zum Einsatz zu bringen. Als Besucher der Konferenz erwarten Sie Beiträge aus den unterschiedlichsten Bereichen. Hierzu gehören zum Beispiel Müdigkeitserkennungssysteme im Automobil, ein Tastsinn auch für Roboter, aber auch neue Ansätze zur Erzeugung und Nutzung von Virtuellen Realitäten für die Erprobung des autonomen Fahrens bis hin zur Simulation von Außenboardeinsätzen in der Raumfahrt.