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This work is a report on practical experiences with the issue of interoperability in German practice management systems (PMSs) from an ongoing clinical trial on teledermatology, the TeleDerm project. A proprietary and established web-platform for store-and-forward telemedicine is integrated with the IT in the GPs’ offices for automatic exchange of basic patient data. Most of the 19 different PMSs included in the study sample lack support of modern health data exchange standards, therefore the relatively old but widely available German health data exchange interface “Gerätedatentransfer” (GDT) is used. Due to the lack of enforcement and regulation of the GDT standard, several obstacles to interoperability are encountered. As a partial, but reusable working solution to cope with these issues, we present a custom middleware which is used in conjunction with GDT. We describe the design, technical implementation and observed hindrances with the existing infrastructure. A discussion on health care interfacing standards and the current state of interoperability in German PMS software is given.
Lots of movies are produced every year, too many to watch all of them and in particular, to get an overview about the evolution of typical movie genres and actors playing in them. Moreover, it is a challenging problem to detect correlations among the movies and the actors in those movies, in particular, if we are interested in time-varying data patterns like trends, countertrends, or anomalies and outliers. Those correlations are specifically interesting if they can be inspected on different levels of granularity, e.g., temporal, but also hierarchical in form of country- or continent-based correlations. In this paper we describe the IMDb Explorer, a webbased visualization tool that consists of two major views denoted by the movie cosmos and the career lines. Both views are linked and interactively manipulable while a list of user-defined metrics are explorable. We illustrate the usefulness of the visualization tool by applying it to the entire movie database provided by IMDb.
Workshops and tutorials
(2018)
The 19th International Conference on Product-Focused Software Process Improvement (PROFES 2018) hosted two workshops and three tutorials. The workshops and tutorials complemented and enhanced the main conference program, offering a wider knowledge perspective around the conference topics. The topics of the two workshops were Hybrid Development Approaches in Software Systems Development (HELENA) and Managing Quality in Agile & Rapid Software Development Processes (QUaSD). The topics of the tutorials were The human factor in agile transitions – using the personas concept in agile oaching, Process Management 4.0 – Best Practices, and Domain-specific languages for specification, development, and testing of autonomous systems.
Being able to monitor the heart activity of patients during their daily life in a reliable, comfortable and affordable way is one main goal of the personalized medicine. Current wearable solutions lack either on the wearing comfort, the quality and type of the data provided or the price of the device. This paper shows the development of a Textile Sensor Platform (TSP) in the form of an electrocardiogram (ECG)-measuring T-shirt that is able to transmit the ECG signal to a smartphone. The development process includes the selection of the materials, the design of the textile electrodes taking into consideration their electrical characteristics and ergonomy, the integration of the electrodes on the garment and their connection with the embedded electronic part. The TSP is able to transmit a real-time streaming of the ECG-signal to an Android smartphone through Bluetooth Low Energy (BLE). Initial results show a good electrical quality in the textile electrodes and promising results in the capture and transmission of the ECG signal. This is still a working- progress and it is the result of an interdisciplinary master project between the School of Informatics and the School of Textiles & Design of the Reutlingen University.
The increasing heterogenecity of students at German Universities of Applied Sciences and the growing importance of digitization call for a rethinking of teaching and learning within higher education. In the next years, changing the learning ecosystem by developing and reflecting upon new teaching and learning techniques using methods of digitalization will be both - most relevant and very challenging. The following article introduces two different learning scenarios, which exemplify the implementation of new educational models that allow discontinuity of time and place, technology and process in teaching and learning. Within a blended learning apporach, the first learning scenario aims at adapting and individualizing the knowledge transfer in the course Foundations of Computer Science by providing knowledge individually and situation-specifically. The second learning scenario proposes a web-based tool to facilitate digital learning environments and thus digital learning communities and the possibility of computer-supported learning. The overall aim of both learning scenarios is to enhance learning for diverse groups by providing a different smart learning ecosystem in stepping away from a teacher-based to a student-centered approach. Both learning scenarios exemplarily represent the educational vision of Reutlingen University - its development into an interactive university.
In this presentation the audience will be: (a) introduced to the aims and objectives of the DBTechNet initiative, (b) briefed on the DBTech EXT virtual laboratory workshops (VLW), i.e. the educational and training (E&T) content which is freely available over the internet and includes vendor-neutral hands-on laboratory training sessions on key database technology topics, and (c) informed on some of the practical problems encountered and the way they have been addressed. Last but not least, the audience will be invited to consider incorporating some or all of the DBTech EXT VLW content into their higher education (HE), vocational education and training (VET), and/or lifelong learning/training type course curricula. This will come at no cost and no commitment on behalf of the teacher/trainer; the latter is only expected to provide his/her feedback on the pedagogical value and the quality of the E&T content received/used.
Die Segmentierung und das Tracking von minimal-invasiven robotergeführten Instrumenten ist ein wesentlicher Bestandteil für verschiedene computer assistierte Eingriffe. Allerdings treten in der minimal-invasiven Chirurgie, die das Anwendungsfeld für den hier beschriebenen Ansatz darstellt, häufig Schwierigkeiten durch Reflexionen, Schatten oder visuelle Verdeckungen durch Rauch und Organe auf und erschweren die Segmentierung und das Tracking der Instrumente.
Dieser Beitrag stellt einen Deep Learning Ansatz für ein markerloses Tracking von minimal-invasiven Instrumenten vor und wird sowohl auf simulierten als auch realen Daten getestet. Es wird ein simulierter als auch realer Datensatz mit Ground Truth Kennzeichnung für die binäre Segmentierung von Instrument und Hintergrund erstellt. Für den simulierten Datensatz werden Bilder aus einem simulierten Instrument und realem Hintergrund zusammengesetzt. Im Falle des realen Datensatzes spricht man von der Zusammensetzung der Bilder aus einem realen Instrument und Hintergrund. Insgesamt wird auf den simulierten Daten eine Pixelgenauigkeit von 94.70 Prozent und auf den realen Daten eine Pixelgenauigkeit von 87.30 Prozent erreicht.
Die minimal-invasive Chirurgie (MIC) entwickelt sich durch den Einsatz von medizinischen Robotern wie dem da Vinci System von Intuitive Surgical stetig weiter. Hierdurch kann eine bessere oder gleichwertige Operation bei deutlich geringerer körperlicher Belastung des Operateurs erreicht werden. Dabei entstehen jedoch neue Problemstellungen wie beispielsweise Kollision zwischen Roboterarmen und die benötigte Zeit zum Einrichten einer geeigneten Roboterkonfiguration. Daher ist eine effiziente Vorbereitung und Planung der Interventionen erforderlich. Diese Arbeit präsentiert einen Ansatz für eine verbesserte Planung mit Augmented Reality (AR) und einer Robotik Simulationssoftware (RS). Die Robotik Simulation dient zur Berechnung einer Roboterkonfiguration unter Vorgabe der Port-Positionen. Augmented Reality wird verwendet, um die berechneten Pose in der realen Umgebung zu visualisieren und somit leichter in den Operationssaal zu übertragen.
The focus of the developed maturity model was set on processes. The concept of the widespread CMM and its practices has been transferred to the perioperative domain and the concept of the new maturity model. Additional optimization goals and technological as well as networking-specific aspects enable a process- and object-focused view of the maturity model in order to ensure broad coverage of different subareas. The evaluation showed that the model is applicable to the perioperative field. Adjustments and extensions of the maturity model are future steps to improve the rating and classification of the new maturity model.
Modern web-based applications are often built as multi-tier architecture using persistence middleware. Middleware technology providers recommend the use of Optimistic Concurrency Control (OCC) mechanism to avoid the risk of blocked resources. However, most vendors of relational database management systems implement only locking schemes for concurrency control. As consequence a kind of OCC has to be implemented at client or middleware side.
A simple Row Version Verification (RVV) mechanism has been proposed to implement an OCC at client side. For performance reasons the middleware uses buffers (cache) of its own to avoid network traffic and possible disk I/O. This caching however complicates the use of RVV because the data in the middleware cache may be stale (outdated). We investigate various data access technologies, including the new Java Persistence API (JPA) and Microsoft’s LINQ technologies for their ability to use the RVV programming discipline.
The use of persistence middleware that tries to relieve the programmer from the low level transaction programming turns out to even complicate the situation in some cases.Programmed examples show how to use SQL data access patterns to solve the problem.
Transaction processing is of growing importance for mobile computing. Booking tickets, flight reservation, banking, ePayment, and booking holiday arrangements are just a few examples for mobile transactions. Due to temporarily disconnected situations the synchronisation and consistent transaction processing are key issues. Serializability is a too strong criteria for correctness when the semantics of a transaction is known. We introduce a transaction model that allows higher concurrency for a certain class of transactions defined by its semantic. The transaction results are ”escrow serializable” and the synchronisation mechanism is non-blocking. Experimental implementation showed higher concurrency, transaction throughput, and less resources used than common locking or optimistic protocols.
Representing users within an immersive virtual environment is an essential functionality of a multi-person virtual reality system. Especially when communicative or collaborative tasks must be performed, there exist challenges about realistic embodying and integrating such avatar representations. A shared comprehension of local space and non-verbal communication (like gesture, posture or self-expressive cues) can support these tasks. In this paper, we introduce a novel approach to create realistic, video-texture based avatars of colocated users in real-time and integrate them in an immersive virtual environment. We show a straight forward and low-cost hard- and software solution to do so. We discuss technical design problems that arose during implementation and present a qualitative analysis on the usability of the concept from a user study, applying it to a training scenario in the automotive sector.
Virtual Reality (VR) technology has the potential to support knowledge communication in several sectors. Still, when educators make use of immersive VR technology in favor of presenting their knowledge, their audience within the same room may not be able to see them anymore due to wearing head-mounted displays (HMDs). In this paper, we propose the Avatar2Avatar system and design, which augments the visual aspect during such a knowledge presentation. Avatar2Avatar enables users to see both a realistic representation of their respective counterpart and the virtual environment at the same time. We point out several design aspects of such a system and address design challenges and possibilities that arose during implementation. We specifically explore opportunities of a system design for integrating 2D video-avatars in existing roomscale VR setups. An additional user study indicates a positive impact concerning spatial presence when using Avatar2Avatar.
Este trabajo se enmarca dentro del vasto contexto de Ciudades Inteligentes, y se centra en el área de la conducción inteligente de vehículos, tanto en zonas urbanas como interurbanas, mediante la recogida de datos en tiempo real, medidos con sensores, por parte de los propios conductores, así como de datos capturados mediante simulación.
El objetivo de este trabajo es doble. Por un lado, el estudio y aplicación de las diferentes técnicas y métodos de detección de valores atípicos en bases de datos multivariantes, además de una comparativa entre ellos mediante las pruebas llevadas a cabo con datos de tráfico real. Y por otro lado, establecer una relación entre las situaciones anómalas de tráfico, como puedan ser atascos o accidentes, con los valores atípicos multivariantes encontrados.
La detección de valores atípicos representa una de las tareas más importantes a la hora de realizar cualquier análisis de datos, sea cual sea el dominio o área de estudio, ya que entre sus funciones primordiales se encuentra el descubrir información útil, que resulta de gran valor, y que por lo general queda oculta por la alta dimensión de los datos.
Con el uso de mecanismos de detección de valores atípicos junto con métodos de clasificación supervisada, se va a poder llevar a cabo el reconocimiento de elementos de la infraestructura vial urbana como pueden ser rotondas, pasos de cebra, cruces o semáforos.
Revenue management information systems are very important in the hospitality sector. Revenue decisions can be better prepared based on different information from different information systems and decision strategies. There is a lack of research about the usage of such systems in small and medium-sized hotels and architectural configurations. Our paper empirically shows the current development of revenue information systems. Furthermore, we define future developments and requirements to improve such systems and the architectural base.
Enterprises are presently transforming their strategy, culture, processes, and their information systems to become more digital. The digital transformation deeply disrupts existing enterprises and economies. Digitization fosters the development of IT systems with many rather small and distributed structures, like Internet of Things or mobile systems. Since years a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of system architectures defines the moving context for adaptable systems, which are essential to enable the digital transformation. In this paper, we are focusing on a decision-oriented architectural composition approach to support the transformation for digital services and products.
Digitization is the use of digital technologies for creating innovative digital business models and transforming existing business models, processes and systems. Digitization creates profound changes in the economy and society. Information is often captured and processed without human intervention using digital means. Digitization impacts nearly all products and services as well as the customer and the value-creation perspective.
Creating new business models, products or services is challenging in fast changing unpredictable environments. Often, product teams need to make many assumptions (e.g., assumptions about future demands) that might not be true. These assumptions impose risks to the success and these risks need to be mitigated early. One of the principles of the Lean Startup approach is to identify and prioritize the riskiest assumptions in order to validate them as early as possible. This helps to avoid wasting effort and time. In the literature there are several different methods for identifying and prioritizing the riskiest assumptions reported. However, only little research exists about the practical application of these methods in practice and how to teach them. In this paper, we present and empirically analyze a workshop format that we have developed for teaching the prioritization of Lean Startup assumptions. We aim at raising the awareness for assumption thinking among the participants and teach them through group work how to prioritize assumptions. The results of the analysis of a multitude of conducted workshops show that the applied method did lead to reasonable results and accompanying learning effects. In addition, the participants got aware of assumption thinking and liked learning in a practical way.
Objective: This paper aims at getting an understanding of current problems and challenges with roadmapping processes in companies that are facing volatile markets with innovative products. It also aims at gathering ideas and attempts on how to react to those challenges.
Method: As an initial step towards the objectice a semi-structured expert interview study with a case company in the Smart Home domain was conducted. Four employees from the case company with different roles around product roadmaps have been interviewed and a content analysis of the data has been performed.
Results: The study shows a significant consensus among the interviewees about several major challenges and the necessity to change the traditional roadmapping process and format. The interviewees stated that based on their experience traditional feature-based product roadmaps are increasingly losing their benefits (such as good planning certainty) in volatile environments. Furthermore, the ability to understand customer needs and behaviors has become highly important for creating and adjusting product roadmaps. The interviewees see the need for both, sufficiently stable goals on the roadmap and flexibility with respect to products or features to be developed. To reach this target the interviewees proposed to create roadmaps based on outcome goals instead of product features. In addition, it was proposed to decrease the level of detail of the roadmaps and to emphasize the long-term view. Decisions about which feature to develop should be open as long as possible. Expected benefits of such a new way of product roadmapping are higher user centricity, a stable overall direction, more flexibility with respect to development decisions, and less breaking of commitments.