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Software and system development is complex and diverse, and a multitude of development approaches is used and combined with each other to address the manifold challenges companies face today. To study the current state of the practice and to build a sound understanding about the utility of different development approaches and their application to modern software system development, in 2016, we launched the HELENA initiative. This paper introduces the 2nd HELENA workshop and provides an overview of the current project state. In the workshop, six teams present initial findings from their regions, impulse talk are given, and further steps of the HELENA roadmap are discussed.
How to protect the skin from getting sun burnt? The sun can damage your skin e.g. skin cancer. But the sun has a positive effect to the human. The time in sun and the intensity are key values between enjoy the sunbath and having a negative effect to the skin. A smart device like a UV flower could help you to enjoy the sunbath. It measures the UV index around you and gives this information to a smartphone app. The development steps of such a device are described in this paper. The UV flower is made of textile fabrics.
Sleep quality and in general, behavior in bed can be detected using a sleep state analysis. These results can help a subject to regulate sleep and recognize different sleeping disorders. In this work, a sensor grid for pressure and movement detection supporting sleep phase analysis is proposed. In comparison to the leading standard measuring system, which is Polysomnography (PSG), the system proposed in this project is a non invasive sleep monitoring device. For continuous analysis or home use, the PSG or wearable actigraphy devices tends to be uncomfortable. Besides this fact, they are also very expensive. The system represented in this work classifies respiration and body movement with only one type of sensor and also in a non invasive way. The sensor used is a pressure sensor. This sensor is low cost and can be used for commercial proposes. The system was tested by carrying out an experiment that recorded the sleep process of a subject. These recordings showed the potential for classification of breathing rate and body movements. Although previous researches show the use of pressure sensors in recognizing posture and breathing, they have been mostly used by positioning the sensors between the mattress and bedsheet. This project however, shows an innovative way to position the sensors under the mattress.
Pokémon Go was the first mobile augmented reality (AR) game to reach the top of the download charts of mobile applications. However, little is known about this new generation of mobile online AR games. Existing theories provide limited applicability for user understanding. Against this background, this research provides a comprehensive framework based on uses and gratification theory, technology risk research, and flow theory. The proposed framework aims to explain the drivers of attitudinal and intentional reactions, such as continuance in gaming or willingness to invest money in in-app purchases. A survey among 642 Pokémon Go players provides insights into the psychological drivers of mobile AR games. The results show that hedonic, emotional, and social benefits and social norms drive consumer reactions while physical risks (but not data privacy risks) hinder consumer reactions. However, the importance of these drivers differs depending on the form of user behavior.
Die Arbeit stellt die Möglichkeiten von 3D-Controllern für den Einsatz in der interventionellen Radiologie und insbesondere für die Steuerung der Echtzeit-Magnetresonanztomographie (MRT) dar. Dies ist interessant in Bezug auf die kontrollierte Navigation in ein Zielgewebe. Dabei kann der Interventionalist durch Echtzeit- Bildgebung den Verlauf des Eingriffs verfolgen, allerdings kann er bisher das MRT während der Durchführung des Eingriffs nicht selbst steuern, da dies durch den Assistenten im Nebenraum erfolgt. Die Kommunikation ist bei dem hohen Geräuschpegel aber sehr schwer. Diese Arbeit setzt an dieser Stelle an und analysiert 3D-Controller auf die Eignung für die Echtzeit-Steuerung eines MRTs. Dabei wurden trackingbasierte und trackinglose Geräte betrachtet. Als Ergebnis ließ sich festhalten, dass trackingbasierte Verfahren weniger geeignet sind, aufgrund der nicht ausreichenden Interpretation der Eingaben. Die trackinglosen Geräte hingegen sind aufgrund der korrekten Interpretation aller Eingaben und der intuitiven Bedienung geeignet.
In der Medizin existieren verschiedene Reifegradmodelle, die die Digitalisierung von Krankenhäusern unterstützen können. Die Anforderungen an ein Reifegradmodell für diesen Zweck umfassen Aspekte aus allgemeinen und spezifischen Bereichen des Krankenhauses. Die Analyse der Reifegradmodelle HIN, CCMM, EMRAM und O-EMRAM zeigt große Lücken im Bereich des OP sowie fehlende Aspekte in der Notaufnahme auf. Ein umfassendes Reifegradmodell wurde nicht gefunden. Durch eine Kombination aus HIN und CCMM könnten fast alle Bereiche ausreichend abgedeckt werden. Zusätzliche Ergänzungen durch spezialisierte Reifegradmodelle oder sogar die Entwicklung eines umfassenden Reifegradmodells wären sinnvoll.
Anforderungen an die Mensch-Maschine-Schnittstelle im Automobil auf dem Weg zum autonomen Fahren
(2017)
In den letzten Jahrzehnten haben immer mehr Fahrerassistenzsysteme Einzug in das Automobil gefunden und bereiten damit den Weg zu vollautonomen Fahrzeugen der Zukunft vor. So bieten bereits viele Hersteller Ausstattungsvarianten ihrer Fahrzeuge an, die für den Umstieg in die vollautonome Zukunft gewappnet sind. Um den Menschen mit auf den Weg zu nehmen, werden einige Anforderungen an die Mensch-Maschine-Schnittstelle (MMS) des Automobils gestellt. Für die teilautonomen Fahrzeuge der nächsten Generation gilt es, den Fahrerwechsel zwischen manuellem und autonomen Fahren für die Menschen bestmöglich zu gestalten. Die Arbeit wirft einen Blick auf ausgewählte Ansätze für zukünftige MMS-Systeme und bewertet diese anhand der Übergabezeiten zwischen Mensch und Maschine. Ein Wandel der MMS im Automobil wird empfohlen, um den Menschen mit den neuen Technologien vertraut zu machen.
Purpose: Medical processes can be modeled using different methods and notations.Currently used modeling systems like Business Process Model and Notation (BPMN) are not capable of describing the highly flexible and variable medical processes in sufficient detail.
Methods: We combined two modeling systems, Business Process Management (BPM) and Adaptive Case Management (ACM), to be able to model non-deterministic medical processes. We used the new Standards Case Management Model and Notation (CMMN) and Decision Management Notation (DMN).
Results: First, we explain how CMMN, DMN and BPMN could be used to model non-deterministic medical processes. We applied this methodology to model 79 cataract operations provided by University Hospital Leipzig, Germany, and four cataract operations provided by University Eye Hospital Tuebingen, Germany. Our model consists of 85 tasks and about 20 decisions in BPMN. We were able to expand the system with more complex situations that might appear during an intervention.
Conclusion: An effective modeling of the cataract intervention is possible using the combination of BPM and ACM. The combination gives the possibility to depict complex processes with complex decisions. This combination allows a significant advantage for modeling perioperative processes.
In this paper a method for the generation of gSPM with ontology-based generalization was presented. The resulting gSPM was modeled with BPMN/BPMNsix in an efficient way and could be executed with BPMN workflow engines. In the next step the implementation of resource concepts, anatomical structures, and transition probabilities for workflow execution will be realized.
Painting galleries typically provide a wealth of data composed of several data types. Those multivariate data are too complex for laymen like museum visitors to first, get an overview about all paintings and to look for specific categories. Finally, the goal is to guide the visitor to a specific painting that he wishes to have a more closer look on. In this paper we describe an interactive visualization tool that first provides such an overview and lets people experiment with the more than 41,000 paintings collected in the web gallery of art. To generate such an interactive tool, our technique is composed of different steps like data handling, algorithmic transformations, visualizations, interactions, and the human user working with the tool with the goal to detect insights in the provided data. We illustrate the usefulness of the visualization tool by applying it to such characteristic data and show how one can get from an overview about all paintings to specific paintings.
In a time of digital transformation, the ability to quickly and efficiently adapt software systems to changed business requirements becomes more important than ever. Measuring the maintainability of software is therefore crucial for the long-term management of such products. With service-based systems (SBSs) being a very important form of enterprise software, we present a holistic overview of such metrics specifically designed for this type of system, since traditional metrics – e.g. object oriented ones – are not fully applicable in this case. The selected metric candidates from the literature review were mapped to 4 dominant design properties: size, complexity, coupling, and cohesion. Microservice-based systems (μSBSs) emerge as an agile and fine grained variant of SBSs. While the majority of identified metrics are also applicable to this specialization (with some limitations), the large number of services in combination with technological heterogeneity and decentralization of control significantly impacts automatic metric collection in such a system. Our research therefore suggests that specialized tool support is required to guarantee the practical applicability of the presented metrics to μSBSs.
This paper contributes to the automatic detection of perioperative workflow by developing a binary endoscope localization. Automated situation recognition in the context of an intelligent operating room requires the automatic conversion of low level cues into more abstract high level information. Imagery from a laparoscope delivers rich content that is easy to obtain but hard to process. We introduce a system which detects if the endoscope's distal tip is inside or outsiede the patient based on the endoscope video. This information can be used as one parameter in a situation recognition pipeline. Our localization performs in real-time at a video resolution of 1280x720 and 5-fold cross validation yields mean F1-scores of up to 0,94 on videos of 7 laparoscopies.
This paper investigates the impact of dynamic capabilities (DC) on brand love. From a resource-based view, there is little clarity vis-à-vis the specific capabilities that drive the ability to create brand love. This paper focuses on three research questions: Firstly, which dynamic capabilities are relevant for brand love? Secondly, how strong is the impact of certain dynamic capabilities on brand love? Thirdly, which conditions mediate and moderate the impact of specific dynamic capabilities on brand love? Data from a multi-method research approach have been used to itentify the specific capabilities that corporations need, to enhance brand love. Furthermore, a standardized online survey was conducted on marketing executives and evaluated by structural equation modeling. The results indicate, that customer expertise plays a major role in the relationship between dynamic capabilities and brand love. Furthermore, this relationship is more important in markets that have a low competitive differentiation in products and services.
To analyze the humans’ sleep it is necessary as to identify the sleep stages, occurring during the sleep, their durations and sleep cycles. The gold standard procedure for this approach is polysomnography (PSG), which classify the sleep stages based on Rechtschaffen and Kales (R-K) method. This method aside the advantages as high accuracy has however some disadvantages, among others time-consuming and uncomfortable for the patient procedure. Therefore, the development of further methods for the sleep classification in addition to PSG is a promising topic for the investigation and this work has as its aim the presentation of possible ways and goals for this development.
With the Internet of Things being one of the most discussed trends in the computer world lately, many organizations find themselves struggling with the great paradigm shift and thus the implementation of IoT on a strategic level. The Ignite methodoogy as a part of the Enterprise-IoT project promises to support organizations with these strategic issues as it combines best practices with expert knowledge from diverse industries helping to create a better understanding of how to transform into an IoT driven business. A framework that is introduced within the context of IoT business model development is the Bosch IoT Business Model Builder. In this study the provided framework is compared to the Osterwalder Business Model Canvas and the St. Gallen Business Model Navigator, the most commonly used and referenced frameworks according to a quantitative literature analysis.
The business landscape is changing radically because of software. Companies in all industry sectors are continously finding new flexibilities in this programmable world. They are able to deliver new functionalities even after the product is already in the customer's hands. But success is far from guaranteed if they cannot validate their assumptions about what their customers actually need. A competitor with better knowledge of customer needs can disrupt the market in an instant.
This book introduces continuous experimentation, an approach to continuously and systematically test assumptions about the company's product or service strategy and verify customers' needs through experiments. By observing how customers actually use the product or early versions of it, companies can make better development decisions and avoid potentially expensive and wasteful activities. The book explains the cycle of continuous experimentation, demonstrates its use through industry cases, provides advice on how to conduct experiments with recipes, tools, and models, and lists some common pitfalls to avoid. Use it to get started with continuous experimentation and make better product and service development decisions that are in-line with your customers' needs.
Saving energy and road safety became important in the last decades, hence several driving assistant systems were developed that help to improve the driving behaviour. However, these driving systems cover the area of either energy-efficiency or safety. Furthermore, they do not consider the reaction of the driver to a shown recommendation and the driver stress level. In this paper, the decision process of showing a recommendation to the driver in an energy-efficient and safety relevant driving system is presented. The decision process considers the driver's reaction to a shown recommendation and the driver stress in order to increase the user acceptance and the road safety. The results of the evaluation showed that the driving system was able to show recommendations when needed, while suppressing recommendations when the driver ignored a recommendation repeatedly or when the driver was in stress.
Electronic word-of-mouth (eWoM) communication has received a lot of attention from the academic community. As multiple research papers focus on specific facets of eWoM, there is a need to integrate current research results systematically. Thus, this paper presents a scientific literature analysis in order to determine the current state-of-the-art in the field of eWoM.
The increasing number of connected mobile devices such as fitness trackers and smartphones define new data for health insurances, enabling them to gain deeper insights into the health of their customers. These additional data sources plus the trend towards an interconnected health community, including doctors, hospitals and insurers, lead to challenges regarding data filtering, organization and dissemination. First, we analyze what kind of information is relevant for a digital health insurance. Second, functional and non-functional requirements for storing and managing health data in an interconnected environment are defined. Third, we propose a data architecture for a digitized health insurance, consisting of a data model and an application architecture.